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Meng X, Li W, Xu J, Yao Y, Gong A, Yang Y, Qu F, Guo C, Zheng H, Cui G, Suo S, Peng G. Spatiotemporal transcriptome atlas of developing mouse lung. Sci Bull (Beijing) 2025; 70:1641-1658. [PMID: 40118721 DOI: 10.1016/j.scib.2025.03.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2024] [Revised: 01/07/2025] [Accepted: 02/24/2025] [Indexed: 03/23/2025]
Abstract
The functional development of the mammalian lung is a complex process that relies on the spatial and temporal organization of multiple cell types and their states. However, a comprehensive spatiotemporal transcriptome atlas of the developing lung has not yet been reported. Here we apply high-throughput spatial transcriptomics to allow for a comprehensive assessment of mouse lung development comprised of two critical developmental events: branching morphogenesis and alveologenesis. We firstly generate a spatial molecular atlas of mouse lung development spanning from E12.5 to P0 based on the integration of published single cell RNA-sequencing data and identify 10 spatial domains critical for functional lung organization. Furthermore, we create a lineage trajectory connecting spatial clusters from adjacent time points in E12.5-P0 lungs and explore TF (transcription factor) regulatory networks for each lineage specification. We observe the establishment of pulmonary airways within the developing lung, accompanied by the proximal-distal patterning with distinct characteristics of gene expression, signaling landscape and transcription factors enrichment. We characterize the alveolar niche heterogeneity with maturation state differences during the later developmental stage around birth and demonstrate differentially expressed genes, such as Angpt2 and Epha3, which may perform a critical role during alveologenesis. In addition, multiple signaling pathways, including ANGPT, VEGF and EPHA, exhibit increased levels in more maturing alveolar niche. Collectively, by integrating the spatial transcriptome with corresponding single-cell transcriptome data, we provide a comprehensive molecular atlas of mouse lung development with detailed molecular domain annotation and communication, which would pave the way for understanding human lung development and respiratory regeneration medicine.
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Affiliation(s)
- Xiaogao Meng
- Life Science and Medicine, University of Science and Technology of China, Hefei 230026, China; Center for Cell Lineage Technology and Bioengineering, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong-Hong Kong Joint Laboratory for Stem Cell and Regenerative Medicine, GIBH-CUHK Joint Research Laboratory on Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, China-New Zealand Belt and Road Joint Laboratory on Biomedicine and Health, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Wenjia Li
- School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou 511436, China; State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China; Guangzhou National Laboratory, Guangzhou 510005, China
| | - Jian Xu
- School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou 511436, China; Guangzhou National Laboratory, Guangzhou 510005, China
| | - Yao Yao
- Center for Cell Lineage Technology and Bioengineering, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong-Hong Kong Joint Laboratory for Stem Cell and Regenerative Medicine, GIBH-CUHK Joint Research Laboratory on Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, China-New Zealand Belt and Road Joint Laboratory on Biomedicine and Health, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - An Gong
- Guangzhou National Laboratory, Guangzhou 510005, China
| | - Yumeng Yang
- Guangzhou National Laboratory, Guangzhou 510005, China
| | - Fangfang Qu
- Guangzhou National Laboratory, Guangzhou 510005, China
| | - Chenkai Guo
- Center for Cell Lineage Technology and Bioengineering, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong-Hong Kong Joint Laboratory for Stem Cell and Regenerative Medicine, GIBH-CUHK Joint Research Laboratory on Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, China-New Zealand Belt and Road Joint Laboratory on Biomedicine and Health, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Hui Zheng
- Center for Cell Lineage Technology and Bioengineering, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong-Hong Kong Joint Laboratory for Stem Cell and Regenerative Medicine, GIBH-CUHK Joint Research Laboratory on Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, China-New Zealand Belt and Road Joint Laboratory on Biomedicine and Health, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China; School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou 511436, China; Centre for Regenerative Medicine and Health, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong 999077, China
| | - Guizhong Cui
- School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou 511436, China; Guangzhou National Laboratory, Guangzhou 510005, China.
| | - Shengbao Suo
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, China; Guangzhou National Laboratory, Guangzhou 510005, China.
| | - Guangdun Peng
- Center for Cell Lineage Technology and Bioengineering, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong-Hong Kong Joint Laboratory for Stem Cell and Regenerative Medicine, GIBH-CUHK Joint Research Laboratory on Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, China-New Zealand Belt and Road Joint Laboratory on Biomedicine and Health, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China.
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Gharibi B, Inge OCK, Rodriguez-Hernandez I, Driscoll PC, Dubois C, Jiang M, Howell M, Skehel JM, Macrae JI, Santos SDM. Post-gastrulation amnioids as a stem cell-derived model of human extra-embryonic development. Cell 2025:S0092-8674(25)00458-1. [PMID: 40378847 DOI: 10.1016/j.cell.2025.04.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 02/25/2025] [Accepted: 04/16/2025] [Indexed: 05/19/2025]
Abstract
The amnion, an extra-embryonic tissue in mammalian embryos, is thought to provide crucial signaling, structural, and nutritional support during pregnancy. Despite its pivotal importance, studying human amnion formation and function has been hampered by the lack of accurate in vitro models. Here, we present an embryonic stem cell-derived 3D model of the post-gastrulation amnion, post-gastrulation amnioids (PGAs), that faithfully recapitulates extra-embryonic development up to 4 weeks post-fertilization, closely mimicking the functional traits of the human amniotic sac. PGAs self-organize, forming the amnion and the yolk sac, and are surrounded by the extra-embryonic mesoderm. Using PGAs, we show that GATA3 is required and sufficient for amniogenesis and that an autoregulatory feedback loop governs amnion formation, whereby extra-embryonic signals promote amnion specification. The reproducibility and scalability of the PGA system, with its precise cellular, structural, and functional integrity, opens avenues for investigating embryo-amnion interactions beyond gastrulation and offers an ideal platform for large-scale pharmacological and clinical studies.
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Affiliation(s)
- Borzo Gharibi
- Quantitative Stem Cell Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK.
| | - Oliver C K Inge
- Quantitative Stem Cell Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK
| | | | - Paul C Driscoll
- Metabolomics, The Francis Crick Institute, London NW1 1AT, UK
| | | | - Ming Jiang
- High-throughput Screening, The Francis Crick Institute, London NW1 1AT, UK
| | - Michael Howell
- High-throughput Screening, The Francis Crick Institute, London NW1 1AT, UK
| | - J Mark Skehel
- Proteomics, The Francis Crick Institute, London NW1 1AT, UK
| | - James I Macrae
- Metabolomics, The Francis Crick Institute, London NW1 1AT, UK
| | - Silvia D M Santos
- Quantitative Stem Cell Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK.
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3
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Karuna N, Kerrigan L, Edgar K, Ledwidge M, McDonald K, Grieve DJ, Watson CJ. Sacubitril/Valsartan attenuates progression of diabetic cardiomyopathy through immunomodulation properties: an opportunity to prevent progressive disease. Cardiovasc Diabetol 2025; 24:206. [PMID: 40369551 PMCID: PMC12079907 DOI: 10.1186/s12933-025-02741-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2024] [Accepted: 04/14/2025] [Indexed: 05/16/2025] Open
Abstract
BACKGROUND AND AIMS Diabetic cardiomyopathy (DbCM) is recognised as a key mediator and determinant of heart failure (HF), particularly HF with preserved ejection fraction (HFpEF). Improved understanding of mechanisms underlying transition from early-stage DbCM to HFpEF will inform innovative evidence-based treatment approaches, which are urgently required to alleviate increasing disease burden. This study aimed to determine whether inhibition of neprilysin activity by Sacubitril/Valsartan in both experimental and clinical DbCM attenuates adverse remodelling through promotion of cardioprotective signalling. METHODS AND RESULTS Sacubitril/Valsartan effectively reduced plasma neprilysin activity in both diabetic patients with pre-clinical HFpEF from the PARABLE trial (baseline (Val n = 25; Sac/Val n = 35) and 3 months after treatment (Val n = 21/25; Sac/Val n = 33/35)) and DbCM (high-fat diet and streptozotocin) mice. Plasma neprilysin activity at baseline was correlated with worsening cardiac performance at 18 months indicated by left atrial stiffness index in patients (n = 44/60), whilst diastolic dysfunction and pathological remodelling in DbCM mice were improved by Sacubitril/Valsartan, but not Valsartan. snRNA-sequencing showed that progressive experimental DbCM is characterised by chronic low-grade inflammation, reflected by increased infiltration of pro-inflammatory monocytes (Ccr2+ Ly6chi) and reduction in MHC-II macrophages, which was prevented by Sacubitril/Valsartan. Informatics analysis implicated IRF7 as a central mediator of Sacubitril/Valsartan-induced immunomodulation in DbCM, whilst treatment of M2-like pro-repair macrophages with the neprilysin inhibitor, LBQ657 and Valsartan suppressed glucose-induced IRF7 expression and paracrine activation of cardiac fibroblast differentiation in vitro. CONCLUSION Immune cells are significantly involved in DbCM progression, impacting myocardial homeostasis and HF progression. Neprilysin inhibition by Sacubitril/Valsartan improved adverse cardiac remodelling in experimental DbCM through direct regulation of inflammation, highlighting immunomodulation as a novel mechanism underlying established its cardioprotective actions.
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Affiliation(s)
- Narainrit Karuna
- Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, UK
- Department of Pharmaceutical Care, Faculty of Pharmacy, Chiang Mai University, Chiang Mai, Thailand
| | - Lauren Kerrigan
- Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, UK
| | - Kevin Edgar
- Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, UK
| | - Mark Ledwidge
- STOP-HF Unit, St. Vincent's University Healthcare Group and University College Dublin, Dublin, Ireland
| | - Ken McDonald
- STOP-HF Unit, St. Vincent's University Healthcare Group and University College Dublin, Dublin, Ireland
| | - David J Grieve
- Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, UK
| | - Chris J Watson
- Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, UK.
- STOP-HF Unit, St. Vincent's University Healthcare Group and University College Dublin, Dublin, Ireland.
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Wang W, Zheng S, Shin SC, Chávez-Fuentes JC, Yuan GC. ONTraC characterizes spatially continuous variations of tissue microenvironment through niche trajectory analysis. Genome Biol 2025; 26:117. [PMID: 40340854 PMCID: PMC12060293 DOI: 10.1186/s13059-025-03588-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Accepted: 04/25/2025] [Indexed: 05/10/2025] Open
Abstract
Recent technological advances enable mapping of tissue spatial organization at single-cell resolution, but methods for analyzing spatially continuous microenvironments are still lacking. We introduce ONTraC, a graph neural network-based framework for constructing spatial trajectories at niche-level. Through benchmarking analyses using multiple simulated and real datasets, we show that ONTraC outperforms existing methods. ONTraC captures both normal anatomical structures and disease-associated tissue microenvironment changes. In addition, it identifies tissue microenvironment-dependent shifts in gene expression, regulatory network, and cell-cell interaction patterns. Taken together, ONTraC provides a useful framework for characterizing the structural and functional organization of tissue microenvironments.
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Affiliation(s)
- Wen Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Shiwei Zheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Sujung Crystal Shin
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | | | - Guo-Cheng Yuan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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Yu G, Li J, Zhang H, Zi H, Liu M, An Q, Qiu T, Li P, Song J, Liu P, Quan K, Li S, Liu Y, Zhu W, Du J. Single-cell analysis reveals the implication of vascular endothelial cell-intrinsic ANGPT2 in human intracranial aneurysm. Cardiovasc Res 2025; 121:658-673. [PMID: 39187926 DOI: 10.1093/cvr/cvae186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 05/04/2024] [Accepted: 06/13/2024] [Indexed: 08/28/2024] Open
Abstract
AIMS While previous single-cell RNA sequencing (scRNA-seq) studies have attempted to dissect intracranial aneurysm (IA), the primary molecular mechanism for IA pathogenesis remains unknown. Here, we uncovered the alterations of cellular compositions, especially the transcriptome changes of vascular endothelial cells (ECs), in human IA. METHODS AND RESULTS We performed scRNA-seq to compare the cell atlas of sporadic IA and the control artery. The transcriptomes of 43 462 cells were profiled for further analysis. In general, IA had increased immune cells (T/NK cells, B cells, myeloid cells, mast cells, neutrophils) and fewer vascular cells (ECs, vascular smooth muscle cells, and fibroblasts). Based on the obtained high-quantity and high-quality EC data, we found genes associated with angiogenesis in ECs from IA patients. By EC-specific expression of candidate genes in vivo, we observed the involvement of angpt2a in causing cerebral vascular abnormality. Furthermore, an IA zebrafish model mimicking the main features of human IA was generated through targeting pdgfrb gene, and knockdown of angpt2a alleviated the vascular dilation in the IA zebrafish model. CONCLUSION By performing a landscape view of the single-cell transcriptomes of IA and the control artery, we contribute to a deeper understanding of the cellular composition and the molecular changes of ECs in IA. The implication of angiogenic regulator ANGPT2 in IA formation and progression, provides a novel potential therapeutical target for IA interventions.
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Affiliation(s)
- Guo Yu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Jia Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
| | - Hongfei Zhang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Huaxing Zi
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
- University of Chinese Academy of Sciences, 19A Yu-Quan Road, Beijing 100049, China
| | - Mingjian Liu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Qingzhu An
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Tianming Qiu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Peiliang Li
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Jianping Song
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Peixi Liu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Kai Quan
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Sichen Li
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Yingjun Liu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Wei Zhu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, 12 Middle Wulumuqi Road, Shanghai 200040, China
- National Center for Neurological Disorders, 12 Middle Wulumuqi Road, Shanghai 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Neurosurgical Institute of Fudan University, 12 Middle Wulumuqi Road,Shanghai 200040, China
- Shanghai Clinical Medical Center of Neurosurgery,12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Jiulin Du
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China
- University of Chinese Academy of Sciences, 19A Yu-Quan Road, Beijing 100049, China
- School of Life Science and Technology, ShanghaiTech University, 319 Yue-Yang Road, Shanghai 200031, China
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6
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Wang P, Liu W, Wang J, Liu Y, Li P, Xu P, Cui W, Zhang R, Long Q, Hu Z, Fang C, Dong J, Zhang C, Chen Y, Wang C, Liu G, Xie H, Zhang Y, Xiao M, Chen S, Jiang H, Chen Y, Yang G, Zhang S, Meng Z, Wang X, Feng G, Li X, Zhou Y. scCompass: An Integrated Multi-Species scRNA-seq Database for AI-Ready. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025:e2500870. [PMID: 40317650 DOI: 10.1002/advs.202500870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2025] [Revised: 03/29/2025] [Indexed: 05/07/2025]
Abstract
Emerging single-cell sequencing technology has generated large amounts of data, allowing analysis of cellular dynamics and gene regulation at the single-cell resolution. Advances in artificial intelligence enhance life sciences research by delivering critical insights and optimizing data analysis processes. However, inconsistent data processing quality and standards remain to be a major challenge. Here scCompass is proposed, which provides a comprehensive resource designed to build large-scale, multi-species, and model-friendly single-cell data collection. By applying standardized data pre-processing, scCompass integrates and curates transcriptomic data from nearly 105 million single cells across 13 species. Using this extensive dataset, it is able to identify stable expression genes (SEGs) and organ-specific expression genes (OSGs) in humans and mice. Different scalable datasets are provided that can be easily adapted for AI model training and the pretrained checkpoints with state-of-the-art single-cell foundation models. In summary, scCompass is highly efficient and scalable database for AI-ready, which combined with user-friendly data sharing, visualization, and online analysis, greatly simplifies data access and exploitation for researchers in single-cell biology (http://www.bdbe.cn/kun).
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Affiliation(s)
- Pengfei Wang
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Wenhao Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
- College of Life Science, Northeast Agricultural University, Harbin, 150030, China
| | - Jiajia Wang
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
| | - Yana Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Pengjiang Li
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Ping Xu
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Wentao Cui
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Ran Zhang
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Qingqing Long
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Zhilong Hu
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Chen Fang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Jingxi Dong
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Chunyang Zhang
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
| | - Yan Chen
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
| | - Chengrui Wang
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
| | - Guole Liu
- State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Hanyu Xie
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
| | - Yiyang Zhang
- CEMS, NCMIS, HCMS, MDIS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Meng Xiao
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
| | - Shubai Chen
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Yiqiang Chen
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Ge Yang
- State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Shihua Zhang
- CEMS, NCMIS, HCMS, MDIS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Zhen Meng
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Xuezhi Wang
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Guihai Feng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
| | - Yuanchun Zhou
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100083, China
- University of Chinese Academy of Sciences, Beijing, 100864, China
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7
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Yan T, Jiang Z, Tu W, Fang K, Xu X, Huang W, Cao J, Zhang H, Yu D, Zhang S. Single‑cell RNA‑Seq reveals PBMC profile alterations in a patient following a radiation accident. Exp Ther Med 2025; 29:96. [PMID: 40165803 PMCID: PMC11956132 DOI: 10.3892/etm.2025.12846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2024] [Accepted: 01/24/2025] [Indexed: 04/02/2025] Open
Abstract
Nuclear technology has been extensively used in various fields, increasing the possibility of radiation exposure to humans. Radiation exposure outcomes may be classified as whole-body irradiation or local irradiation. Clinically, local irradiation refers to the exposure of a relatively limited portion of the body, with injury confined to the directly exposed tissues. However, locally irradiated tissues can trigger systemic reactions through the release of inflammatory factors or damage to blood cells at the irradiated site. The circulating population of peripheral blood mononuclear cells (PBMCs), a component of normal tissue, is particularly sensitive to ionizing radiation. The present study applied single-cell RNA sequencing (scRNA-Seq) to profile PBMCs from one irradiated patient and 10 healthy controls matched for sex and age. In total, 6,447 and 7,892 cells were collected for analysis from the PBMCs of the irradiated patient on the 113rd and 631st days post radiation, respectively, whereas 9,101 cells were obtained from 10 healthy controls. Following scRNA-Seq, five cell types were annotated via representative markers, revealing distinct cell types whose proportions changed markedly in the irradiated patient. Trajectory analysis indicated that the dysregulation of multiple signaling pathways was associated with radiation exposure. Furthermore, single-cell regulatory network inference and clustering analysis revealed gene regulatory networks and suggested the involvement of several signaling pathways, such as those related to viral infection, in the context of radiation exposure. The present study elucidated the dynamic landscape of human blood immune responses to ionizing radiation and provides evidence of its therapeutic potential for treating radiation injury.
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Affiliation(s)
- Tao Yan
- Department of Plastic Surgery, The Second Affiliated Hospital of Chengdu Medical College (Nuclear Industry 416 Hospital), Chengdu, Sichuan 610051, P.R. China
- NHC Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, Mianyang, Sichuan 621099, P.R. China
| | - Zhiqiang Jiang
- Department of Plastic Surgery, The Second Affiliated Hospital of Chengdu Medical College (Nuclear Industry 416 Hospital), Chengdu, Sichuan 610051, P.R. China
| | - Wenling Tu
- Department of Plastic Surgery, The Second Affiliated Hospital of Chengdu Medical College (Nuclear Industry 416 Hospital), Chengdu, Sichuan 610051, P.R. China
| | - Kai Fang
- Department of Plastic Surgery, The Second Affiliated Hospital of Chengdu Medical College (Nuclear Industry 416 Hospital), Chengdu, Sichuan 610051, P.R. China
| | - Xiaopeng Xu
- Laboratory of Radiation Medicine, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041, P.R. China
| | - Wei Huang
- Department of Plastic Surgery, The Second Affiliated Hospital of Chengdu Medical College (Nuclear Industry 416 Hospital), Chengdu, Sichuan 610051, P.R. China
| | - Jianping Cao
- School of Radiation Medicine and Protection, Medical College of Soochow University, Suzhou, Jiangsu 215123, P.R. China
| | - Huojun Zhang
- Department of Radiation Oncology, Shanghai Changhai Hospital, Naval Medical University, Shanghai 200433, P.R. China
| | - Daojiang Yu
- Department of Plastic Surgery, The Second Affiliated Hospital of Chengdu Medical College (Nuclear Industry 416 Hospital), Chengdu, Sichuan 610051, P.R. China
- Laboratory of Radiation Medicine, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041, P.R. China
- Center of Burn and Trauma, The Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu 214000, P.R. China
- Department of Burn and Plastic Surgery, The Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu 214000, P.R. China
| | - Shuyu Zhang
- Department of Plastic Surgery, The Second Affiliated Hospital of Chengdu Medical College (Nuclear Industry 416 Hospital), Chengdu, Sichuan 610051, P.R. China
- NHC Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, Mianyang, Sichuan 621099, P.R. China
- Laboratory of Radiation Medicine, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041, P.R. China
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8
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Scuderi S, Kang TY, Jourdon A, Nelson A, Yang L, Wu F, Anderson GM, Mariani J, Tomasini L, Sarangi V, Abyzov A, Levchenko A, Vaccarino FM. Specification of human brain regions with orthogonal gradients of WNT and SHH in organoids reveals patterning variations across cell lines. Cell Stem Cell 2025:S1934-5909(25)00141-9. [PMID: 40315847 DOI: 10.1016/j.stem.2025.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Revised: 03/10/2025] [Accepted: 04/09/2025] [Indexed: 05/04/2025]
Abstract
The repertoire of neurons and their progenitors depends on their location along the antero-posterior and dorso-ventral axes of the neural tube. To model these axes, we designed the Dual Orthogonal-Morphogen Assisted Patterning System (Duo-MAPS) diffusion device to expose spheres of induced pluripotent stem cells (iPSCs) to concomitant orthogonal gradients of a posteriorizing and a ventralizing morphogen, activating WNT and SHH signaling, respectively. Comparison with single-cell transcriptomes from the fetal human brain revealed that Duo-MAPS-patterned organoids generated an extensive diversity of neuronal lineages from the forebrain, midbrain, and hindbrain. WNT and SHH crosstalk translated into early patterns of gene expression programs associated with the generation of specific brain lineages with distinct functional networks. Human iPSC lines showed substantial interindividual and line-to-line variations in their response to morphogens, highlighting that genetic and epigenetic variations may influence regional specification. Morphogen gradients promise to be a key approach to model the brain in its entirety.
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Affiliation(s)
- Soraya Scuderi
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale University, New Haven, CT 06520, USA
| | - Tae-Yun Kang
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Systems Biology Institute, Yale University, West Haven, CT 06516, USA; Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Alexandre Jourdon
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale University, New Haven, CT 06520, USA
| | - Alex Nelson
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale University, New Haven, CT 06520, USA
| | - Liang Yang
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Systems Biology Institute, Yale University, West Haven, CT 06516, USA; Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Feinan Wu
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale University, New Haven, CT 06520, USA
| | | | - Jessica Mariani
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale University, New Haven, CT 06520, USA
| | - Livia Tomasini
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale University, New Haven, CT 06520, USA
| | - Vivekananda Sarangi
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Alexej Abyzov
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA
| | - Andre Levchenko
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Systems Biology Institute, Yale University, West Haven, CT 06516, USA; Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA.
| | - Flora M Vaccarino
- Program in Neurodevelopment and Regeneration, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale University, New Haven, CT 06520, USA; Department of Neuroscience, Yale University, New Haven, CT 06520, USA; Yale Stem Cell Center, Yale University, New Haven, CT 06520, USA.
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9
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Ding M, Mao S, Wu H, Fang S, Zhen N, Chen T, Zhu J, Tang X, Wang X, Sun F, Zhu G, Pan Q, Ma J. Malignant Hepatoblast-Like Cells Sustain Stemness via IGF2-Dependent Cholesterol Accumulation in Hepatoblastoma. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025:e2407671. [PMID: 40271711 DOI: 10.1002/advs.202407671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Revised: 02/08/2025] [Indexed: 04/25/2025]
Abstract
Hepatoblastoma, the most aggressive childhood liver tumor, poses significant challenges due to limited knowledge of its pathogenesis, particularly in poorly differentiated advanced tumors where the prognosis is dismal. Single-cell sequencing provides an in-depth exploration at the single-cell level and offers a deep understanding of tumor heterogeneity. Herein, single-cell transcriptomics analysis is used to identify a unique malignant-hepatoblast (HB)-like cell subpopulation as the possible origin of poorly differentiated hepatoblastoma. These cells are associated with an unfavorable clinical prognosis in hepatoblastoma patients. The malignant-HB-like cell subpopulation generated insulin-like growth factor 2 (IGF2) to sustain stem-like features by promoting abnormal cholesterol accumulation via SREBF2. IGF2 also stimulated fibroblast 2 to secrete collagen 1, intensifying tumor malignancy via the collagen 1/integrin α1 signaling pathway. This suggests that targeting malignant HB-like cells by inhibiting IGF2-induced pathways can lead to promising treatments for hepatoblastoma. Additionally, serum IGF2 levels may serve as a diagnostic biomarker for advanced hepatoblastoma. In summary, these findings provide valuable insight into the genesis and malignancy of hepatoblastoma and a foundation for more effective diagnostic tools and therapeutic strategies for this challenging disease.
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Affiliation(s)
- Miao Ding
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
| | - Siwei Mao
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
| | - Han Wu
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
| | - Sijia Fang
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
| | - Ni Zhen
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
| | - Tianshu Chen
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
| | - Jiabei Zhu
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
| | - Xiaochen Tang
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
| | - Xiaoyang Wang
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
| | - Fenyong Sun
- Department Laboratory Medicine, Shanghai Tenth People's Hospital of Tongji University, Shanghai, 200072, P. R. China
| | - Guoqing Zhu
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
| | - Qiuhui Pan
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
- Faculty of Medical Laboratory Science, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200000, P. R. China
- Shanghai Key Laboratory of Clinical Molecular Diagnostics for Pediatrics, Shanghai, 200120, P. R. China
- Sanya Women and Children's Hospital Managed by Shanghai Children's Medical Center, Sanya, 572029, P. R. China
| | - Ji Ma
- Department of Clinical Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120, P. R. China
- Shanghai Key Laboratory of Clinical Molecular Diagnostics for Pediatrics, Shanghai, 200127, P. R. China
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10
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Wang H, He P, Wang Z, Tian C, Liu C, Li X, Yan T, Qin Y, Ling S, Ling H, Wu G, Li Y, Wang J, Jin S. Single-cell RNA-seq analysis identifies the atlas of lymph fluid and reveals a sepsis-related T cell subset. Cell Rep 2025; 44:115469. [PMID: 40178976 DOI: 10.1016/j.celrep.2025.115469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Revised: 02/08/2025] [Accepted: 03/05/2025] [Indexed: 04/05/2025] Open
Abstract
The lymphoid cycle serves as a sentinel of the immune response, yet the cell subtypes and immune properties within lymph fluid remain unclear. This study describes a comprehensive characterization of immune cells in rat lymph fluid using single-cell RNA sequencing, identifying a unique subset of CD4+ T cells (CD4_Icos) that suppresses inflammation in early sepsis. Trajectory analysis reveals that CD4+Icos+ T cells can differentiate into regulatory T cells (Tregs). Transferring CD4+Icos+ T cells alleviates CLP-induced organ injury, while CD4+ Icos-knockout (KO) mice show reduced Treg numbers, increased inflammation, and higher mortality. Further experiments identify Npas2 as an Icos-specific transcription factor regulating Icos expression and promoting the differentiation of CD4+Icos+ T cells. Clinical data show a negative correlation between ICOS expression in CD4+ T cells and clinical outcomes in septic patients. These findings highlight the protective role of CD4+ T cells in modulating immune responses and mitigating sepsis progression.
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Affiliation(s)
- Hui Wang
- Department of Anesthesia and Critical Care, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China; Institute of Autoimmune Diseases, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Panwei He
- Department of Anesthesia and Critical Care, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China; Key Laboratory of Pediatric Anesthesiology, Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China; Precision Anesthesiology Key Laboratory of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Zhenxia Wang
- Department of Emergency Medicine, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China
| | - Chao Tian
- Department of Anesthesiology, Ningbo Medical Center Lihuili Hospital, Ningbo, Zhejiang, China
| | - Chuanlong Liu
- Institute of Autoimmune Diseases, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Xiangyu Li
- Institute of Autoimmune Diseases, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Tao Yan
- Department of Anesthesia and Critical Care, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China; Key Laboratory of Pediatric Anesthesiology, Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China; Precision Anesthesiology Key Laboratory of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yang Qin
- Institute of Autoimmune Diseases, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Sunwang Ling
- Institute of Autoimmune Diseases, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Hanzhi Ling
- Department of Anesthesia and Critical Care, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China; Key Laboratory of Pediatric Anesthesiology, Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China; Precision Anesthesiology Key Laboratory of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Gan Wu
- Department of Anesthesia and Critical Care, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China; Key Laboratory of Pediatric Anesthesiology, Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China; Precision Anesthesiology Key Laboratory of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yan Li
- Department of Emergency Medicine, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
| | - Jianguang Wang
- Department of Anesthesia and Critical Care, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China; Institute of Autoimmune Diseases, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China; Key Laboratory of Pediatric Anesthesiology, Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China; Precision Anesthesiology Key Laboratory of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China.
| | - Shengwei Jin
- Department of Anesthesia and Critical Care, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China; Key Laboratory of Pediatric Anesthesiology, Ministry of Education, Wenzhou Medical University, Wenzhou, Zhejiang, China; Precision Anesthesiology Key Laboratory of Zhejiang Province, Wenzhou Medical University, Wenzhou, Zhejiang, China.
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11
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Li Y, Liu X, Guo L, Han K, Fang S, Wan X, Wang D, Xu X, Jiang L, Fan G, Xu M. SpaGRN: Investigating spatially informed regulatory paths for spatially resolved transcriptomics data. Cell Syst 2025; 16:101243. [PMID: 40179878 DOI: 10.1016/j.cels.2025.101243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 08/30/2024] [Accepted: 03/07/2025] [Indexed: 04/05/2025]
Abstract
Cells spatially organize into distinct cell types or functional domains through localized gene regulatory networks. However, current spatially resolved transcriptomics analyses fail to integrate spatial constraints and proximal cell influences, limiting the mechanistic understanding of tissue organization. Here, we introduce SpaGRN, a statistical framework that reconstructs cell-type- or functional-domain-specific, dynamic, and spatial regulons by coupling intracellular spatial regulatory causality with extracellular signaling path information. Benchmarking across synthetic and real datasets demonstrates SpaGRN's superior precision over state-of-the-art tools in identifying context-dependent regulons. Applied to diverse spatially resolved transcriptomics platforms (Stereo-seq, STARmap, MERFISH, CosMx, Slide-seq, and 10x Visium), complex cancerous samples, and 3D datasets of developing Drosophila embryos and larvae, SpaGRN not only provides a versatile toolkit for decoding receptor-mediated spatial regulons but also reveals spatiotemporal regulatory mechanisms underlying organogenesis and inflammation.
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Affiliation(s)
- Yao Li
- BGI Research, Sanya 572025, China; BGI Research, Qingdao 266555, China
| | | | - Lidong Guo
- BGI Research, Qingdao 266555, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kai Han
- BGI Research, Qingdao 266555, China
| | - Shuangsang Fang
- BGI Research, Beijing 102601, China; BGI Research, Shenzhen 518083, China
| | - Xinjiang Wan
- CAS Key Laboratory of Marine Ecology and Environmental Sciences, and Center of Deep Sea Research Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
| | | | - Xun Xu
- BGI Research, Wuhan 430074, China; State Key Laboratory of Genome and Multi-omics Technologies, BGI Research, Shenzhen 518083, China
| | - Ling Jiang
- State Key Laboratory of Materials-Oriented Chemical Engineering, Nanjing Tech University, Nanjing 211816, China.
| | - Guangyi Fan
- BGI Research, Sanya 572025, China; BGI Research, Qingdao 266555, China; BGI Research, Shenzhen 518083, China; State Key Laboratory of Genome and Multi-omics Technologies, BGI Research, Shenzhen 518083, China.
| | - Mengyang Xu
- BGI Research, Sanya 572025, China; BGI Research, Qingdao 266555, China; BGI Research, Shenzhen 518083, China; State Key Laboratory of Genome and Multi-omics Technologies, BGI Research, Shenzhen 518083, China.
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12
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Zhou X, Zhou Z, Qin X, Cheng J, Fu Y, Wang Y, Wang J, Qin P, Zhang D. Multiomics Analysis Reveals Neuroblastoma Molecular Signature Predicting Risk Stratification and Tumor Microenvironment Differences. J Proteome Res 2025; 24:1606-1623. [PMID: 39762147 DOI: 10.1021/acs.jproteome.4c00882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2025]
Abstract
Neuroblastoma (NB) remains associated with high mortality and low initial response rate, especially for high-risk patients, thus warranting exploration of molecular markers for precision risk classifiers. Through integrating multiomics profiling, we identified a range of hub genes involved in cell cycle and associated with dismal prognosis and malignant cells. Single-cell transcriptome sequencing revealed that a subset of malignant cells, subcluster 1, characterized by high proliferation and dedifferentiation, was strongly correlated with the hub gene signature and orchestrated an immunosuppressive tumor microenvironment (TME). Furthermore, we constructed a robust malignant subcluster 1 related signature (MSRS), which was an independent prognostic factor and superior to other clinical characteristics and published signatures. Besides, TME differences conferred remarkably distinct therapeutic responses between high and low MSRS groups. Notably, polo-like kinase-1 (PLK1) was one of the most crucial contributors to MSRS and remarkably correlated with malignant subcluster 1, and PLK1 inhibition was effective for NB treatment as demonstrated by in silico analysis and in vitro experiments. Overall, our study constructs a novel molecular model to further guide the clinical classification and individualized treatment of NB.
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Affiliation(s)
- Xing Zhou
- Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Zhaokai Zhou
- Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Xiaohan Qin
- Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Jian Cheng
- Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Yongcheng Fu
- Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Yuanyuan Wang
- Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Jingyue Wang
- Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Pan Qin
- Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
| | - Da Zhang
- Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
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13
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Tian Y, Liu S, Shi H, Li J, Wan X, Sun Y, Li H, Cao N, Feng Z, Zhang T, Wang J, Shen W. Revealing the Transcriptional and Metabolic Characteristics of Sebocytes Based on the Donkey Cell Transcriptome Atlas. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2413819. [PMID: 40013957 PMCID: PMC12021041 DOI: 10.1002/advs.202413819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2024] [Revised: 02/15/2025] [Indexed: 02/28/2025]
Abstract
Worldwide, donkeys (Equus asinus) are valued for their meat and milk, and in China also for the medical value of their skin. Physiological characteristics are key to the donkey's adaptability, including their digestive, respiratory, and reproductive systems, which enable them to survive and work in a variety of environments. However, the understanding of donkey physiological characteristics at the cellular level remains poor. Thus, single-cell transcriptome sequencing is used to construct a detailed transcriptional atlas based on 20 tissues from the Dezhou donkey (in total 84 cell types and 275 050 high quality cells) to perform an in-depth investigation of molecular physiology. Cross-species and cross-tissue comparative analyses reveal SOX10 to be an evolutionally conserved regulon in oligodendrocytes and illuminate the distinctive transcriptional patterns of donkey sebocytes. Moreover, through multispecies skin metabolomics, highly abundant, species-specific metabolites in donkey skin are identified, such as arachidonic acid and gamma-glutamylcysteine, and the pivotal role of sebocytes in donkey skin metabolism is highlighted. In summary, this work offers new insights into the unique metabolic patterns of donkey skin and provides a valuable resource for the conservation of donkey germplasm and the advancement of selective breeding programs.
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Affiliation(s)
- Yu Tian
- College of Animal Science and TechnologyQingdao Agricultural UniversityQingdao266109China
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock (R2BGL)College of Life SciencesInner Mongolia UniversityHohhot010070China
| | - Shuqin Liu
- College of Animal Science and TechnologyQingdao Agricultural UniversityQingdao266109China
| | - Hongtao Shi
- School of Science and Information ScienceQingdao Agricultural UniversityQingdao266109China
| | - Jianjun Li
- National Dezhou Donkey Original Breeding FarmBinzhou251903China
| | - Xinglong Wan
- School of Science and Information ScienceQingdao Agricultural UniversityQingdao266109China
| | - Yujiang Sun
- College of Animal Science and TechnologyQingdao Agricultural UniversityQingdao266109China
| | - Huayun Li
- Annoroad Gene TechnologyBeijing100176China
| | - Ning Cao
- Annoroad Gene TechnologyBeijing100176China
| | - Zhixi Feng
- Annoroad Gene TechnologyBeijing100176China
| | - Teng Zhang
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock (R2BGL)College of Life SciencesInner Mongolia UniversityHohhot010070China
| | - Junjie Wang
- College of Animal Science and TechnologyQingdao Agricultural UniversityQingdao266109China
| | - Wei Shen
- College of Animal Science and TechnologyQingdao Agricultural UniversityQingdao266109China
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14
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Liu L, Ba Y, Yang S, Zuo A, Liu S, Zhang Y, Xu S, Weng S, Liu B, Luo P, Cheng Q, Deng J, Xu H, Chen Y, Zhang C, Zhou X, Ren Y, Han X, Hou Z, Liu Z. FOS-driven inflammatory CAFs promote colorectal cancer liver metastasis via the SFRP1-FGFR2-HIF1 axis. Theranostics 2025; 15:4593-4613. [PMID: 40225580 PMCID: PMC11984394 DOI: 10.7150/thno.111625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2025] [Accepted: 03/15/2025] [Indexed: 04/15/2025] Open
Abstract
Rationale: Cancer-associated fibroblasts (CAFs) exhibit diverse functions, yet their roles in colorectal cancer liver metastasis (CRLM) remain poorly understood. Methods: Through integrated analysis of single-cell RNA sequencing and spatial transcriptomics from colorectal cancer patients (CRCP: non-metastatic primary tumors; CRCM: metastatic primary tumors with liver metastases), combined with in vitro and in vivo models to investigate the role of CAFs in CRLM. In vitro experiments included six groups to reveal the role of SFRP1-producing CAFs, comprising PBS (control) and recombinant human SFRP1 (rhSFRP1) treated SW480 cells, PBS (control) and recombinant mouse SFRP1 (rmSFRP1) treated CT26 cells, and conditioned medium (CM) derived from CAF-NC and CAF-Sfrp1 treated CT26 cells. Preclinical models were further employed to elucidate the role of SFRP1 in CRLM. Subcutaneous xenografts models were constructed from PBS (control) and rhSFRP1 treated SW480 cells. For orthotopic tumor metastasis models, CT26 cells were pre-cultured with CAF-NC or CAF-Sfrp1 and then orthotopically injected into BALB/c mice. Results: We identified an inflammatory CAF subtype (CFD+ iCAFs) associated with poor clinical outcomes, advanced staging, and metastasis. Transcriptional regulation analysis revealed FOS-mediated differentiation of CFD+ iCAFs drives SFRP1 overexpression. In vitro and in vivo experiments confirmed that SFRP1-producing CAFs promote tumor stemness and epithelial-mesenchymal transition (EMT). Mechanistically, SFRP1 from CFD+ iCAFs binds FGFR2, activating the HIF1 signaling pathway to enhance tumor stemness, EMT, and CRLM progression. Conclusion: This study highlights CFD+ iCAFs as key regulators of tumor-stromal interactions and identifies SFRP1 as a potential therapeutic target in CRLM.
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Affiliation(s)
- Long Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Department of hepatobiliary surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shanxi, 710061, China
| | - Yuhao Ba
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan, 450052, China
| | - Shuaixi Yang
- Department of Colorectal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Aning Zuo
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan, 450052, China
| | - Shutong Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan, 450052, China
| | - Yuyuan Zhang
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan, 450052, China
| | - Shuqin Xu
- Department of hepatobiliary surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shanxi, 710061, China
| | - Siyuan Weng
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Benyu Liu
- Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Peng Luo
- The Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jinhai Deng
- Richard Dimbleby Department of Cancer Research, Comprehensive Cancer Centre, Kings College London, London, United Kingdom
| | - Hui Xu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan, 450052, China
| | - Yukang Chen
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan, 450052, China
| | - Chuhan Zhang
- Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
| | - Xing Zhou
- Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
| | - Yuqing Ren
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
| | - Xinwei Han
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan, 450052, China
| | - Zhenyu Hou
- Department of General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, China
| | - Zaoqu Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Institute of Zhengzhou University, Zhengzhou, Henan, 450052, China
- Interventional Treatment and Clinical Research Center of Henan Province, Zhengzhou, Henan, 450052, China
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
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15
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Challagundla KB, Pathania AS, Chava H, Kantem NM, Dronadula VM, Coulter DW, Clarke M. FOXJ3, a novel tumor suppressor in neuroblastoma. MOLECULAR THERAPY. ONCOLOGY 2025; 33:200914. [PMID: 39811681 PMCID: PMC11731479 DOI: 10.1016/j.omton.2024.200914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 08/20/2024] [Accepted: 11/26/2024] [Indexed: 01/16/2025]
Abstract
Neuroblastoma (NB) poses a significant challenge in pediatric cancer care due to its aggressive nature and poor prognosis. While advances have been made in clinical treatments, therapy resistance remains a tough hurdle in NB treatment. While much research has focused on identifying oncogenes in NB, there has been less emphasis on understanding tumor suppressors. This study aimed to discover a new transcription factor that could address patient stage, risk level, and MYCN amplification status while exhibiting tumor-suppressive properties in NB patients. Using advanced bioinformatics techniques, we identified unique transcription factor signature that corresponded to patient characteristics. By analyzing regulon specificity scores, we prioritized Forkhead Box J3 (FOXJ3) as a potential novel driver transcription factor with tumor-suppressive functions in NB. Validation experiments on NB patients and patient-derived xenograft (PDX) tumors confirmed higher FOXJ3 expression in low-risk versus high-risk patients and in PDXs from diagnostic tumors versus relapse-specific tumors. Notably, the overexpression of FOXJ3 was associated with reduced cell density, proliferation, cells in S phase, colony-formation ability, transwell migration, neurosphere formation, spheroid diameter, and inhibition of AKT signaling in NB cells. Overall, these findings suggest that FOXJ3 functions as a novel tumor suppressor in NB, holding promise for potential therapeutic interventions.
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Affiliation(s)
- Kishore B. Challagundla
- School of Interdisciplinary Informatics, University of Nebraska Omaha, 1110 South 67th Street, Omaha, NE 68182, USA
- The Child Health Research Institute, Department of Biochemistry and Molecular Biology & Fred and Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198, USA
- Department of Basic Biomedical Sciences, Touro College of Osteopathic Medicine, Middletown, NY 10940, USA
| | - Anup S. Pathania
- The Child Health Research Institute, Department of Biochemistry and Molecular Biology & Fred and Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Haritha Chava
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Naveenkumar M. Kantem
- Department of Mathematical and Statistical Sciences, University of Nebraska Omaha, 1110 South 67th Street, Omaha, NE 68182, USA
| | - Veena M. Dronadula
- School of Interdisciplinary Informatics, University of Nebraska Omaha, 1110 South 67th Street, Omaha, NE 68182, USA
| | - Don W. Coulter
- Department of Pediatrics, Division of Hematology/Oncology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Martina Clarke
- School of Interdisciplinary Informatics, University of Nebraska Omaha, 1110 South 67th Street, Omaha, NE 68182, USA
- Department of Biomedical Informatics, University of Nebraska Medical Center, 42nd and Emile Street, Omaha, NE 68198, USA
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16
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Clarence T, Bendl J, Cao X, Wang X, Zheng S, Hoffman GE, Kozlenkov A, Hong A, Iskhakova M, Jaiswal MK, Murphy S, Yu A, Haroutunian V, Dracheva S, Akbarian S, Fullard JF, Yuan GC, Lee D, Roussos P. Multiomic single-cell profiling identifies critical regulators of postnatal brain. Nat Genet 2025; 57:591-603. [PMID: 39962241 DOI: 10.1038/s41588-025-02083-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 01/08/2025] [Indexed: 03/15/2025]
Abstract
Human brain development spans from embryogenesis to adulthood, with dynamic gene expression controlled by cell-type-specific cis-regulatory element activity and three-dimensional genome organization. To advance our understanding of postnatal brain development, we simultaneously profiled gene expression and chromatin accessibility in 101,924 single nuclei from four brain regions across ten donors, covering five key postnatal stages from infancy to late adulthood. Using this dataset and chromosome conformation capture data, we constructed enhancer-based gene regulatory networks to identify cell-type-specific regulators of brain development and interpret genome-wide association study loci for ten main brain disorders. Our analysis connected 2,318 cell-specific loci to 1,149 unique genes, representing 41% of loci linked to the investigated traits, and highlighted 55 genes influencing several disease phenotypes. Pseudotime analysis revealed distinct stages of postnatal oligodendrogenesis and their regulatory programs. These findings provide a comprehensive dataset of cell-type-specific gene regulation at critical timepoints in postnatal brain development.
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Affiliation(s)
- Tereza Clarence
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xuan Cao
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xinyi Wang
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shiwei Zheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alexey Kozlenkov
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aram Hong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marina Iskhakova
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Manoj K Jaiswal
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Sarah Murphy
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alexander Yu
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vahram Haroutunian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Stella Dracheva
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Schahram Akbarian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Guo-Cheng Yuan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, USA.
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, USA.
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17
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Zhang X, Li L, Shi X, Zhao Y, Cai Z, Ni N, Yang D, Meng Z, Gao X, Huang L, Wang T. Development of a tertiary lymphoid structure-based prognostic model for breast cancer: integrating single-cell sequencing and machine learning to enhance patient outcomes. Front Immunol 2025; 16:1534928. [PMID: 40078998 PMCID: PMC11897234 DOI: 10.3389/fimmu.2025.1534928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2024] [Accepted: 02/10/2025] [Indexed: 03/14/2025] Open
Abstract
Background Breast cancer, a highly prevalent global cancer, poses significant challenges, especially in advanced stages. Prognostic models are crucial to enhance patient outcomes. Tertiary lymphoid structures (TLS) within the tumor microenvironment have been associated with better prognostic outcomes. Methods We analyzed data from 13 independent breast cancer cohorts, totaling over 9,551 patients. Using single-cell RNA sequencing and machine learning algorithms, we identified critical TLS-associated genes and developed a TLS-based predictive model. This model stratified patients into high and low-risk groups. Genomic alterations, immune infiltration, and cellular interactions within the tumor microenvironment were assessed. Results The TLS-based model demonstrated superior accuracy compared to traditional models, predicting overall survival. High TLS patients had higher tumor mutation burden and more chromosomal alterations, correlating with poorer prognosis. High-risk patients exhibited a significant depletion of CD4+ T cells, CD8+ T cells, and B cells, as evidenced by single-cell and bulk transcriptomic analyses. In contrast, immune checkpoint inhibitors demonstrated greater efficacy in low-risk patients, whereas chemotherapy proved more effective for high-risk individuals. Conclusions The TLS-based prognostic model is a robust tool for predicting breast cancer outcomes, highlighting the tumor microenvironment's role in cancer progression. It enhances our understanding of breast cancer biology and supports personalized therapeutic strategies.
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Affiliation(s)
- Xiaonan Zhang
- Department of Pathophysiology, Bengbu Medical University, Bengbu, Anhui, China
| | - Li Li
- Department of Pathophysiology, Bengbu Medical University, Bengbu, Anhui, China
| | - Xiaoyu Shi
- Department of Pathophysiology, Bengbu Medical University, Bengbu, Anhui, China
| | - Yunxia Zhao
- Department of Pathophysiology, Bengbu Medical University, Bengbu, Anhui, China
| | - Zhaogen Cai
- Department of Pathology, Bengbu Medical University, Bengbu, Anhui, China
| | - Ni Ni
- School of Clinical Medicine, Bengbu Medical University, Bengbu, Anhui, China
| | - Di Yang
- School of Clinical Medicine, Bengbu Medical University, Bengbu, Anhui, China
| | - Zixin Meng
- School of Clinical Medicine, Bengbu Medical University, Bengbu, Anhui, China
| | - Xu Gao
- School of Health Administration, Bengbu Medical University, Bengbu, Anhui, China
| | - Li Huang
- Department of Pathophysiology, Bengbu Medical University, Bengbu, Anhui, China
| | - Tao Wang
- Research Laboratory Center, Guizhou Provincial People’s Hospital, Guiyang, Guizhou, China
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18
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De Vriendt S, Laporte E, Abaylı B, Hoekx J, Hermans F, Lambrechts D, Vankelecom H. Single-cell transcriptome atlas of male mouse pituitary across postnatal life highlighting its stem cell landscape. iScience 2025; 28:111708. [PMID: 39898054 PMCID: PMC11787594 DOI: 10.1016/j.isci.2024.111708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 05/17/2024] [Accepted: 12/27/2024] [Indexed: 02/04/2025] Open
Abstract
The pituitary represents the master gland governing the endocrine system. We constructed a single-cell (sc) transcriptomic atlas of male mouse endocrine pituitary by incorporating existing and new data, spanning important postnatal ages in both healthy and injured condition. We demonstrate strong applicability of this new atlas to unravel pituitary (patho)biology by focusing on its stem cells and investigating their complex identity (unveiling stem cell markers) and niche (pinpointing regulatory factors). Importantly, we functionally validated transcriptomic findings using pituitary stem cell organoids, revealing roles for Krüppel-like transcription factor 5 (KLF5), activator protein-1 (AP-1) complex and epidermal growth factor (EGF) pathways in pituitary stem cell regulation. Our investigation substantiated changes in stem cell dynamics during aging, reinforcing the inflammatory/immune nature in elderly pituitary and stem cells. Finally, we show translatability of mouse atlas-based findings to humans, particularly regarding aging-associated profile. This pituitary sc map is a valuable tool to unravel pituitary (patho)biology.
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Affiliation(s)
- Silke De Vriendt
- Laboratory of Tissue Plasticity in Health and Disease, Cluster of Stem Cell and Developmental Biology, Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium
| | - Emma Laporte
- Laboratory of Tissue Plasticity in Health and Disease, Cluster of Stem Cell and Developmental Biology, Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium
| | - Berkehür Abaylı
- Laboratory of Tissue Plasticity in Health and Disease, Cluster of Stem Cell and Developmental Biology, Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium
| | - Julie Hoekx
- Laboratory of Tissue Plasticity in Health and Disease, Cluster of Stem Cell and Developmental Biology, Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium
| | - Florian Hermans
- Department of Cardiology and Organ Systems (COS), Biomedical Research Institute (BIOMED), Faculty of Medicine and Life Sciences, Hasselt University, 3590 Diepenbeek, Belgium
| | - Diether Lambrechts
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, 3000 Leuven, Belgium
- Center for Cancer Biology, Vlaams Instituut voor Biotechnologie (VIB), 3000 Leuven, Belgium
| | - Hugo Vankelecom
- Laboratory of Tissue Plasticity in Health and Disease, Cluster of Stem Cell and Developmental Biology, Department of Development and Regeneration, KU Leuven, 3000 Leuven, Belgium
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19
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Wang T, Wang S, Li Z, Xie J, Jia Q, Hou J. Integrative machine learning model of RNA modifications predict prognosis and treatment response in patients with breast cancer. Cancer Cell Int 2025; 25:43. [PMID: 39948551 PMCID: PMC11827143 DOI: 10.1186/s12935-025-03651-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Accepted: 01/10/2025] [Indexed: 02/16/2025] Open
Abstract
BACKGROUND Breast cancer, a highly heterogeneous and complex disease, remains the leading cause of cancer-related death among women worldwide. Despite advances in treatment modalities, effective prognostic models and therapeutic strategies are still urgently needed. METHODS We retrospectively analyzed 15 independent breast cancer cohorts to explore the role of RNA modifications in the prognosis of patients with breast cancer. By integrating nine types of RNA modifications, we developed a comprehensive machine learning-based RNA modification signature (CMRS). Furthermore, single-cell RNA sequencing data were analyzed to understand the biological mechanisms underlying CMRS. In addition, immune infiltration levels were evaluated via six different algorithms, and immune checkpoint inhibitor responsiveness was predicted. Moreover, the response of high-CMIS patients to chemotherapy was predicted via multiple datasets. Finally, immunohistochemistry was performed on tissue samples from breast cancer patients to validate protein expression levels. RESULTS Our analysis revealed five key RNA modification-related genes (ENO1, ARAF, WT1, GADD45A, and BIRC3) associated with breast cancer prognosis. The CMRS model demonstrated high predictive accuracy across multiple cohorts and was significantly correlated with patient survival outcomes. Multiomics analysis revealed that high CMRS was associated with increased tumor mutational burden and distinct mutational signatures, particularly in pathways related to TP53, MYC, and cell proliferation. Single-cell analysis highlighted the involvement of epithelial cells and MYC signaling in high CMRS activity. Cell‒cell communication analysis revealed reduced interaction strength in hig CMRS patients, indicating poor prognosis. Furthermore, low CMRS patients presented increased immune cell infiltration and improved responsiveness to immune checkpoint inhibitors, whereas high CMRS patients were identified as potential candidates for treatment with panobinostat and vincristine. CONCLUSION Our study elucidates the significant role of RNA modifications in breast cancer prognosis and treatment. The CMRS model serves as a sensitive biomarker for predicting patient survival and treatment responsiveness, offering a new avenue for personalized therapy in patients with breast cancer.
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Affiliation(s)
- Tao Wang
- Research Laboratory Center, Guizhou Provincial People's Hospital, Guiyang, 550002, China
| | - Shu Wang
- Department of Breast Surgery, Guizhou Provincial People's Hospital, Guiyang, 550002, China
| | - Zhuolin Li
- Department of Breast Surgery, Guizhou Provincial People's Hospital, Guiyang, 550002, China
| | - Jie Xie
- Department of Breast Surgery, Guizhou Provincial People's Hospital, Guiyang, 550002, China
| | - Qi Jia
- Department of Breast Surgery, Guizhou Provincial People's Hospital, Guiyang, 550002, China.
| | - Jing Hou
- Department of Breast Surgery, Guizhou Provincial People's Hospital, Guiyang, 550002, China.
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20
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Ma R, Yang W, Guo W, Zhang H, Wang Z, Ge Z. Single-cell transcriptome analysis reveals the dysregulated monocyte state associated with tuberculosis progression. BMC Infect Dis 2025; 25:210. [PMID: 39939918 PMCID: PMC11823163 DOI: 10.1186/s12879-025-10612-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Accepted: 02/06/2025] [Indexed: 02/14/2025] Open
Abstract
BACKGROUND In tuberculosis (TB) infection, monocytes play a crucial role in regulating the balance between immune tolerance and immune response through various mechanisms. A deeper understanding of the roles of monocyte subsets in TB immune responses may facilitate the development of novel immunotherapeutic strategies and improve TB prevention and treatment. METHODS We retrieved and processed raw single-cell RNA-seq data from SRP247583. Single-cell RNA-seq combined with bioinformatics analysis was employed to investigate the roles of monocytes in TB progression. RESULTS Our findings revealed that classical monocytes expressing inflammatory mediators increased as the disease progressed, whereas non-classical monocytes expressing molecules associated with anti-pathogen infection were progressively depleted. Pseudotime analysis delineated the differentiation trajectory of monocytes from classical to intermediate to non-classical subsets. An abnormal differentiation trajectory to non-classical monocytes may represent a key mechanism underlying TB pathogenesis, with CEBPB and CORO1A identified as genes potentially related to TB development. Analysis of key transcription factors in non-classical monocytes indicated that IRF9 was the only downregulated transcription factor with high AUC activity in this subset. The expression of IRF9 exhibited a decreasing trend in both latent TB infection (LTBI) and active TB groups. Furthermore, dysregulation of transcription factor regulatory networks appeared to impair ferroptosis, with ferroptosis-associated genes MEF2C, MICU1, and PRR5 identified as potential targets of IRF9. Through cell communication analysis, we found that interactions between non-classical monocytes and other subpopulations may mediate TB progression, with MIF and LGALS9 highlighted as potential signaling pathways. CONCLUSION This study employs bioinformatics analysis in conjunction with single-cell sequencing technology to uncover the crucial role of monocyte subsets in tuberculosis infection.
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Affiliation(s)
- Rong Ma
- The First Clinical Medical School of Ningxia Medical University, Yinchuan, China
- General Hospital of Ningxia Medical University, Yinchuan, China
| | - Wanzhong Yang
- The First Clinical Medical School of Ningxia Medical University, Yinchuan, China
- General Hospital of Ningxia Medical University, Yinchuan, China
| | - Wei Guo
- The First Clinical Medical School of Ningxia Medical University, Yinchuan, China
| | - Honglai Zhang
- The First Clinical Medical School of Ningxia Medical University, Yinchuan, China
| | - Zemin Wang
- The First Clinical Medical School of Ningxia Medical University, Yinchuan, China
| | - Zhaohui Ge
- The First Clinical Medical School of Ningxia Medical University, Yinchuan, China.
- General Hospital of Ningxia Medical University, Yinchuan, China.
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Liu JN, Tian JY, Liu L, Cao Y, Lei X, Zhang XH, Zhang ZQ, He JX, Zheng CX, Ma C, Bai SF, Sui BD, Jin F, Chen J. The landscape of cell regulatory and communication networks in the human dental follicle. Front Bioeng Biotechnol 2025; 13:1535245. [PMID: 39974190 PMCID: PMC11835805 DOI: 10.3389/fbioe.2025.1535245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2024] [Accepted: 01/15/2025] [Indexed: 02/21/2025] Open
Abstract
Introduction The dental follicle localizes the surrounding enamel organ and dental papilla of the developing tooth germ during the embryonic stage. It can differentiate and develop to form the periodontal ligament, cementum, and alveolar bone tissues. Postnatally, the dental follicle gradually degenerates, but some parts of the dental follicle remain around the impacted tooth. However, the specific cellular components and the intricate regulatory mechanisms governing the postnatal development and biological function of the dental follicle have not been completely understood. Methods We analyzed dental follicles with single-cell RNA sequencing (scRNA-seq) to reveal their cellular constitution molecular signatures by cell cycle analysis, scenic analysis, gene enrichment analysis, and cell communication analysis. Results Ten cell clusters were identified with differential characteristics, among which immune and vessel-related cells, as well as a stem cell population, were revealed as the main cell types. Gene regulatory networks (GRNs) were established and defined four regulon modules underlying dental tissue development and microenvironmental regulation, including vascular and immune responses. Cell-cell communication analysis unraveled crosstalk between vascular and immune cell components in orchestrating dental follicle biological activities, potentially based on COLLAGAN-CD44 ligand-receptor pairs, as well as ANGPTL1-ITGA/ITGB ligand-receptor pairs. Conclusion We establish a landscape of cell regulatory and communication networks in the human dental follicle, providing mechanistic insights into the cellular regulation and interactions in the complex dental follicle tissue microenvironment.
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Affiliation(s)
- Jia-Ning Liu
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Clinical Research Center for Oral Diseases, Department of Orthodontics, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Jiong-Yi Tian
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Lu Liu
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Clinical Research Center for Oral Diseases, Department of Orthodontics, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Yuan Cao
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Clinical Research Center for Oral Diseases, Department of Orthodontics, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Xiao Lei
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Clinical Research Center for Oral Diseases, Department of Orthodontics, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Xiao-Hui Zhang
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Clinical Research Center for Oral Diseases, Department of Orthodontics, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Zi-Qi Zhang
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Clinical Research Center for Oral Diseases, Department of Orthodontics, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Jun-Xi He
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Clinical Research Center for Oral Diseases, Department of Orthodontics, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Chen-Xi Zheng
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Chao Ma
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Sheng-Feng Bai
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Bing-Dong Sui
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Fang Jin
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi Clinical Research Center for Oral Diseases, Department of Orthodontics, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
| | - Ji Chen
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases, Shaanxi International Joint Research Center for Oral Diseases, Center for Tissue Engineering, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
- Department of Oral Implantology, School of Stomatology, The Fourth Military Medical University, Xi’an, Shaanxi, China
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Sicheng Z, Jingcheng Z, Shuo Z, Jiaheng L, Yan C, Xing B, Tao J, Guangji Z. Mendelian randomization and multiomics comprehensively reveal the causal relationship and potential mechanism between atrial fibrillation and gastric cancer. Front Genet 2025; 16:1446661. [PMID: 39963672 PMCID: PMC11830663 DOI: 10.3389/fgene.2025.1446661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Accepted: 01/13/2025] [Indexed: 02/20/2025] Open
Abstract
Objective Gastric cancer is a harmful disease, the comorbidity mechanism and causality relationship between this disease and other diseases are worth studying. Methods Using a two-sample Mendelian Randomization method, this study revealed the potential causal effect of atrial fibrillation (AF) on gastric cancer (GC) risk by constructing a genetic instrument containing 136 AF associated SNPs. Subsequently, analysis identifies 62 AF-GC co-associated genes and constructs a protein-protein interaction network of key genes. High-throughput sequencing data were further used to analyze the association between the two and their impact on the survival outcome of gastric cancer. Results The results showed that AF was negatively associated with gastric cancer, and further analysis revealed that this relationship was independent of GC risk factors such as chronic gastritis, Helicobacter pylori infection, and alcohol consumption. Enrichment analysis reveals associations of key genes with pathways related to cardiovascular disease, inflammatory gastrointestinal diseases, and tumorigenesis. Through single-cell sequencing data analysis, fibroblast subpopulations associated with the key gene set are identified in GC, showing significant correlations with cancer progression and inflammation regulation pathways. Transcription factor analysis and developmental trajectory analysis reveal the potential role of fibroblasts in GC development. Finally, prognosis analysis and gene mutation analysis using TCGA-STAD data indicate an adverse prognosis associated with the key gene set in GC. Conclusion This study provides new insights into the association between AF and GC and offers novel clues for understanding its impact on the pathogenesis and therapeutic strategies of GC.
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Affiliation(s)
- Zhao Sicheng
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Key Laboratory of Blood-stasis-toxin Syndrome of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Zhang Jingcheng
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Key Laboratory of Blood-stasis-toxin Syndrome of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Zhang Shuo
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Key Laboratory of Blood-stasis-toxin Syndrome of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Lou Jiaheng
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Key Laboratory of Blood-stasis-toxin Syndrome of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Cai Yan
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Key Laboratory of Blood-stasis-toxin Syndrome of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Bai Xing
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Key Laboratory of Blood-stasis-toxin Syndrome of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Jiang Tao
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Key Laboratory of Blood-stasis-toxin Syndrome of Zhejiang Province, Hangzhou, Zhejiang, China
- Traditional Chinese Medicine “Preventing Disease” Wisdom Health Project Research, Nanning, Zhejiang, China
| | - Zhang Guangji
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- Key Laboratory of Blood-stasis-toxin Syndrome of Zhejiang Province, Hangzhou, Zhejiang, China
- Traditional Chinese Medicine “Preventing Disease” Wisdom Health Project Research, Nanning, Zhejiang, China
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Song Q, Wang Y, Liu S. Subtype-specific transcription factors affect polyamine metabolism and the tumor microenvironment in breast cancer. CANCER INNOVATION 2025; 4:e138. [PMID: 39629335 PMCID: PMC11612022 DOI: 10.1002/cai2.138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 04/07/2024] [Accepted: 04/22/2024] [Indexed: 12/07/2024]
Abstract
Background Polyamines play important roles in cell growth and proliferation. Polyamine metabolism genes are dysregulated in various tumors. Some polyamine metabolism genes are regulated by transcription factors. However, the transcription factors that regulate polyamine metabolism genes have not been completely identified. Additionally, whether any of the transcriptional regulations depend on tumor heterogeneity and the tumor microenvironment has not been investigated. Methods We used bulk RNA-seq data to identify dysregulated polyamine metabolism genes and their transcription factors across breast cancer subtypes. Genes highly correlated with polyamine changes were obtained, and their subtype-specific expressions were checked in tumor microenvironment cells using single-cell RNA (scRNA)-seq data. Gene Ontology enrichment analysis was used to explore their molecular functions and biological processes, and survival analysis was used to examine the impact of these genes on therapeutic outcome. Results We first analyzed the dysregulation of polyamine synthesis, catabolism, and transport in four breast cancer subtypes. Genes such as AGMAT and CAV1 were dysregulated across all subtypes, while APRT, SAT1, and other genes were dysregulated in the more lethal subtypes. Among the dysregulated genes of polyamine metabolism, we focused on three genes (SRM, APRT, and SAT1) and identified their transcription factors (SPI1 and IRF1 correspond to SAT1, and IRF3 corresponds to SRM and APRT). With scRNA-seq data, we verified that these three transcription factors also regulated these three polyamine metabolism genes in the tumor microenvironment. Both bulk RNA-seq and scRNA-seq data indicated that these genes were specifically upregulated in high-risk breast cancer subtypes, such as the basal-like type. High expression of these genes corresponded to worse outcomes in the basal-like subtype under chemotherapy and radiation treatment. Conclusion Our work identified three subtype-specific transcription factors that regulate three polyamine metabolism genes in high-risk breast cancer subtypes and the tumor microenvironment. Our results deepen the understanding of the role of polyamine metabolism in breast cancer and may help the clinical therapy of advanced breast cancer subtypes.
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Affiliation(s)
- Qi Song
- Cooperative Innovation Center of Industrial Fermentation (Ministry of Education and Hubei Province)Key Laboratory of Fermentation Engineering (Ministry of Education)WuhanHubeiChina
- Hubei Key Laboratory of Industrial Microbiology, National “111” Center for Cellular Regulation and Molecular PharmaceuticsHubei University of TechnologyWuhanHubeiChina
| | - Yixuan Wang
- Cooperative Innovation Center of Industrial Fermentation (Ministry of Education and Hubei Province)Key Laboratory of Fermentation Engineering (Ministry of Education)WuhanHubeiChina
- Hubei Key Laboratory of Industrial Microbiology, National “111” Center for Cellular Regulation and Molecular PharmaceuticsHubei University of TechnologyWuhanHubeiChina
| | - Sen Liu
- Cooperative Innovation Center of Industrial Fermentation (Ministry of Education and Hubei Province)Key Laboratory of Fermentation Engineering (Ministry of Education)WuhanHubeiChina
- Hubei Key Laboratory of Industrial Microbiology, National “111” Center for Cellular Regulation and Molecular PharmaceuticsHubei University of TechnologyWuhanHubeiChina
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Zhuang M, Liu J, Li Y, Zhang J, Jiang Z, Wang X, Tang J. PD-L1 promotes tumor metastasis by regulating the infiltration of FGFBP2(+)Tm cells in colorectal cancer. Oncogene 2025; 44:378-390. [PMID: 39558101 DOI: 10.1038/s41388-024-03223-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Revised: 11/03/2024] [Accepted: 11/06/2024] [Indexed: 11/20/2024]
Abstract
Tumor-infiltrating lymphocytes can influence tumorigenesis and progression. We found PD-L1 can inhibit the infiltration of memory T (Tm) cells in vivo and in vitro by reducing the secretion of CXCL9, CXCL10 in colorectal cancer. Patients with high PD-L1 expression have minimal Tm cell infiltration, accompanied with a higher incidence of tumor metastasis. Single-cell sequencing revealed that PD-L1 mainly inhibited the infiltration of a specific Tm cell subset characterized by the expression of FGFBP2 gene. To clarify the distribution of FGFBP2(+)Tm cells, peripheral blood, lymph nodes, colon polyps, primary tumor, and liver metastases samples were collected. As the tumor progressed, the infiltration of FGFBP2(+) memory T cells gradually increased and accumulated in liver metastases. By establishing a mouse metastasis model, we found in high PD-L1 expression group, the luciferin intensity of metastatic tumor was significantly higher, the number of metastatic nodules and the weight of metastases were also increased. The number of FGFBP2(+) Tm cells in peripheral blood and in liver/lung metastases were increased. Therefore, the expression of PD-L1 in primary tumor can promote the occurrence of metastases, and FGFBP2(+)Tm cells may be involved in the formation of metastases. Furthermore, the result showed that the number of FGFBP2(+) Tm cells in metastases was positively correlated with the number of vessels in liver/lung metastases. In conclusion, we confirmed that the expression of PD-L1 in primary tumor can increase the number of FGFBP2(+) Tm cells in peripheral blood and promote tumor metastasis, which is likely to be caused by the angiogenesis of FGFBP2(+) Tm cells in metastases.
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Affiliation(s)
- Meng Zhuang
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Jialiang Liu
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Yuegang Li
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Jinzhu Zhang
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Zheng Jiang
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Xishan Wang
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
| | - Jianqiang Tang
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
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Guo X, Feng C, Xing J, Cao Y, Liu T, Yang W, Mu R, Wang T. Epigenetic profiling for prognostic stratification and personalized therapy in breast cancer. Front Immunol 2025; 15:1510829. [PMID: 39877345 PMCID: PMC11772270 DOI: 10.3389/fimmu.2024.1510829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2024] [Accepted: 12/16/2024] [Indexed: 01/31/2025] Open
Abstract
Background The rising incidence of breast cancer and its heterogeneity necessitate precise tools for predicting patient prognosis and tailoring personalized treatments. Epigenetic changes play a critical role in breast cancer progression and therapy responses, providing a foundation for prognostic model development. Methods We developed the Machine Learning-derived Epigenetic Model (MLEM) to identify prognostic epigenetic gene patterns in breast cancer. Using multi-cohort transcriptomic datasets, MLEM was constructed with rigorous machine learning techniques and validated across independent datasets. The model's performance was further corroborated through immunohistochemical validation on clinical samples. Results MLEM effectively stratified breast cancer patients into high- and low-risk groups. Low-MLEM patients exhibited improved prognosis, characterized by enhanced immune cell infiltration and higher responsiveness to immunotherapy. High-MLEM patients showed poorer prognosis but were more responsive to chemotherapy, with vincristine identified as a promising therapeutic option. The model demonstrated robust performance across independent validation datasets. Conclusion MLEM is a powerful prognostic tool for predicting breast cancer outcomes and tailoring personalized treatments. By integrating epigenetic insights with machine learning, this model has the potential to improve clinical decision-making and optimize therapeutic strategies for breast cancer patients.
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Affiliation(s)
- Xiao Guo
- School of Pharmacy, Beihua University, Jilin, China
| | - Chuanbo Feng
- School of Pharmacy, Beihua University, Jilin, China
| | - Jiaying Xing
- School of Pharmacy, Beihua University, Jilin, China
| | - Yuyan Cao
- School of Pharmacy, Beihua University, Jilin, China
| | - Tengda Liu
- School of Pharmacy, Beihua University, Jilin, China
| | | | - Runhong Mu
- School of Basic Medical Sciences, Beihua University, Jilin, China
| | - Tao Wang
- Research Laboratory Center, Guizhou Provincial People’s Hospital, Guiyang, Guizhou, China
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Jiang Y, Hu Z, Huang R, Ho K, Wang P, Kang J. Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing. Front Immunol 2025; 15:1512483. [PMID: 39830504 PMCID: PMC11739280 DOI: 10.3389/fimmu.2024.1512483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Accepted: 11/26/2024] [Indexed: 01/22/2025] Open
Abstract
Background Anti-citrullinated peptide antibodies (ACPA)-negative (ACPA-) rheumatoid arthritis (RA) presents significant diagnostic and therapeutic challenges due to the absence of specific biomarkers, underscoring the need to elucidate its distinctive cellular and metabolic profiles for more targeted interventions. Methods Single-cell RNA sequencing data from peripheral blood mononuclear cells (PBMCs) and synovial tissues of patients with ACPA- and ACPA+ RA, as well as healthy controls, were analyzed. Immune cell populations were classified based on clustering and marker gene expression, with pseudotime trajectory analysis, weighted gene co-expression network analysis (WGCNA), and transcription factor network inference providing further insights. Cell-cell communication was explored using CellChat and MEBOCOST, while scFEA enabled metabolic flux estimation. A neural network model incorporating key genes was constructed to differentiate patients with ACPA- RA from healthy controls. Results Patients with ACPA- RA demonstrated a pronounced increase in classical monocytes in PBMCs and C1QChigh macrophages (p < 0.001 and p < 0.05). Synovial macrophages exhibited increased heterogeneity and were enriched in distinct metabolic pathways, including complement cascades and glutathione metabolism. The neural network model achieved reliable differentiation between patients with ACPA- RA and healthy controls (AUC = 0.81). CellChat analysis identified CD45 and CCL5 as key pathways facilitating macrophage-monocyte interactions in ACPA- RA, prominently involving iron-mediated metabolite communication. Metabolic flux analysis indicated elevated beta-alanine and glutathione metabolism in ACPA- RA macrophages. Conclusion These findings underscore that ACPA-negative rheumatoid arthritis is marked by elevated classical monocytes in circulation and metabolic reprogramming of synovial macrophages, particularly in complement cascade and glutathione metabolism pathways. By integrating single-cell RNA sequencing with machine learning, this study established a neural network model that robustly differentiates patients with ACPA- RA from healthy controls, highlighting promising diagnostic biomarkers and therapeutic targets centered on immune cell metabolism.
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Affiliation(s)
- Yafeng Jiang
- Department of Hematology, the Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhaolan Hu
- Department of Anesthesiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Roujie Huang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kaying Ho
- School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China
| | - Pengfei Wang
- Department of Anesthesiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jin Kang
- Department of Rheumatology and Immunology, the Second Xiangya Hospital of Central South University, Changsha, China
- Department of Rheumatology and Immunology, Clinical Medical Research Center for Systemic Autoimmune Diseases in Hunan Province, Changsha, China
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Lin Q, Wang Z, Wang J, Xu M, Zhang X, Sun P, Yuan Y. Innovative strategies to optimise colorectal cancer immunotherapy through molecular mechanism insights. Front Immunol 2024; 15:1509658. [PMID: 39717768 PMCID: PMC11663906 DOI: 10.3389/fimmu.2024.1509658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2024] [Accepted: 11/21/2024] [Indexed: 12/25/2024] Open
Abstract
Background Colorectal cancer (CRC) is a leading cause of cancer-related deaths globally. The heterogeneity of the tumor microenvironment significantly influences patient prognosis, while the diversity of tumor cells shapes its unique characteristics. A comprehensive analysis of the molecular profile of tumor cells is crucial for identifying novel molecular targets for drug sensitivity analysis and for uncovering the pathophysiological mechanisms underlying CRC. Methods We utilized single-cell RNA sequencing technology to analyze 13 tissue samples from 4 CRC patients, identifying key cell types within the tumor microenvironment. Intercellular communication was assessed using CellChat, and a risk score model was developed based on eight prognostic genes to enhance patient stratification for immunotherapeutic approaches. Additionally, in vitro experiments were performed on DLX2, a gene strongly associated with poor prognosis, to validate its potential role as a therapeutic target in CRC progression. Results Eight major cell types were identified across the tissue samples. Within the tumor cell population, seven distinct subtypes were recognized, with the C0 FXYD5+ tumor cells subtype being significantly linked to cancer progression and poor prognosis. CellChat analysis indicated extensive communication among tumor cells, fibroblasts, and immune cells, underscoring the complexity of the tumor microenvironment. The risk score model demonstrated high accuracy in predicting 1-, 3-, and 5-year survival rates in CRC patients. Enrichment analysis revealed that the C0 FXYD5+ tumor cell subtype exhibited increased energy metabolism, protein synthesis, and oxidative phosphorylation, contributing to its aggressive behavior. In vitro experiments confirmed DLX2 as a critical gene associated with poor prognosis, suggesting its viability as a target for improving drug sensitivity. Conclusion In summary, this study advances our understanding of CRC progression by identifying critical tumor subtypes, molecular pathways, and prognostic markers that can inform innovative strategies for predicting and enhancing drug sensitivity. These findings hold promise for optimizing immunotherapeutic approaches and developing new targeted therapies, ultimately aiming to improve patient outcomes in CRC.
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Affiliation(s)
- Quanjun Lin
- Department of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhiqiang Wang
- Department of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jue Wang
- Department of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ming Xu
- Department of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinyi Zhang
- Clinical Medical College, Southwest Medical University, Luzhou, China
| | - Peng Sun
- Department of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yihang Yuan
- Department of General Surgery, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Yang C, Geng H, Yang X, Ji S, Liu Z, Feng H, Li Q, Zhang T, Zhang S, Ma X, Zhu C, Xu N, Xia Y, Li Y, Wang H, Yu C, Du S, Miao B, Xu L, Wang H, Cao Y, Li B, Zhu L, Tang X, Zhang H, Zhu C, Huang Z, Leng C, Hu H, Chen X, Yuan S, Jin G, Bernards R, Sun C, Zheng Q, Qin W, Gao Q, Wang C. Targeting the immune privilege of tumor-initiating cells to enhance cancer immunotherapy. Cancer Cell 2024; 42:2064-2081.e19. [PMID: 39515328 DOI: 10.1016/j.ccell.2024.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 09/09/2024] [Accepted: 10/11/2024] [Indexed: 11/16/2024]
Abstract
Tumor-initiating cells (TICs) possess the ability to evade anti-tumor immunity, potentially explaining many failures of cancer immunotherapy. Here, we identify CD49f as a prominent marker for discerning TICs in hepatocellular carcinoma (HCC), outperforming other commonly used TIC markers. CD49f-high TICs specifically recruit tumor-promoting neutrophils via the CXCL2-CXCR2 axis and create an immunosuppressive milieu in the tumor microenvironment (TME). Reciprocally, the neutrophils reprogram nearby tumor cells toward a TIC phenotype via secreting CCL4. These cells can evade CD8+ T cell-mediated killing through CCL4/STAT3-induced and CD49f-stabilized CD155 expression. Notably, while aberrant CD155 expression contributes to immune suppression, it also represents a TIC-specific vulnerability. We demonstrate that either CD155 deletion or antibody blockade significantly enhances sensitivity to anti-PD-1 therapy in preclinical HCC models. Our findings reveal a new mechanism of tumor immune evasion and provide a rationale for combining CD155 blockade with anti-PD-1/PD-L1 therapy in HCC.
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Affiliation(s)
- Chen Yang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Immune Regulation in Cancer Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Haigang Geng
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xupeng Yang
- Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, State Key Laboratory of Genetic Engineering, Human Phenome Institute, Fudan University, Shanghai, China
| | - Shuyi Ji
- Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, State Key Laboratory of Genetic Engineering, Human Phenome Institute, Fudan University, Shanghai, China; Institute for Regenerative Medicine, Medical Innovation Center and State Key Laboratory of Cardiology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Zhicheng Liu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hao Feng
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qian Li
- Department of Oncology, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tangansu Zhang
- Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Sisi Zhang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xuhui Ma
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chuchen Zhu
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Nuo Xu
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhan Xia
- Department of Biliary-Pancreatic Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Li
- Department of Immunology and Microbiology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Hongye Wang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chune Yu
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shangce Du
- Immune Regulation in Cancer Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Beiping Miao
- Immune Regulation in Cancer Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lei Xu
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hui Wang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ying Cao
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Botai Li
- Shanghai Immune Therapy Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lili Zhu
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiangyu Tang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Haoyu Zhang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chunchao Zhu
- Department of Gastrointestinal Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhao Huang
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chao Leng
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Haiyan Hu
- Department of Oncology, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaoping Chen
- Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shengxian Yuan
- The Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Guangzhi Jin
- Department of Interventional Radiology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - René Bernards
- Division of Molecular Carcinogenesis, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Chong Sun
- Immune Regulation in Cancer Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Quan Zheng
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Wenxin Qin
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Qiang Gao
- Department of Liver Surgery and Transplantation, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, State Key Laboratory of Genetic Engineering, Human Phenome Institute, Fudan University, Shanghai, China.
| | - Cun Wang
- State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute & Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Zhang S, Fang X, Chang M, Zheng M, Guo L, Xu Y, Shu J, Nie Q, Li Z. Cross-species single-cell analysis reveals divergence and conservation of peripheral blood mononuclear cells. BMC Genomics 2024; 25:1169. [PMID: 39623297 PMCID: PMC11613757 DOI: 10.1186/s12864-024-11030-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2024] [Accepted: 11/11/2024] [Indexed: 12/06/2024] Open
Abstract
BACKGROUND Single-cell transcriptome sequencing (scRNA-seq) has revolutionized the study of immune cells by overcoming the limitations of traditional antibody-based identification and isolation methods. This advancement allows us to obtain comprehensive gene expression profiles from a diverse array of vertebrate species, facilitating the identification of various cell types. Comparative immunology across vertebrates presents a promising approach to understanding the evolution of immune cell types. In this study, we conducted a comparative transcriptome analysis of peripheral blood mononuclear cells (PBMCs) at the single-cell level across 12 species. RESULTS Our findings shed light on the cellular compositional features of PBMCs, spanning from fish to mammals. Notably, we identified genes that exhibit vertebrate universality in characterizing immune cells. Moreover, our investigation revealed that monocytes have maintained a conserved transcriptional regulatory program throughout evolution, emphasizing their pivotal role in orchestrating immune cells to execute immune programs. CONCLUSIONS This comprehensive analysis provides valuable insights into the evolution of immune cells across vertebrates.
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Affiliation(s)
- Siyu Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China
- Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, Guangdong, 510642, China
| | - Xiang Fang
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong, 999077, China
| | - Mengyang Chang
- Institute of Aquatic Biotechnology, College of Life Sciences, Qingdao University, Qingdao, Liaoning, 266071, China
| | - Ming Zheng
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China
- Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, Guangdong, 510642, China
| | - Lijin Guo
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China
- Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, Guangdong, 510642, China
| | - Yibin Xu
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China
- Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, Guangdong, 510642, China
| | - Jingting Shu
- Key Laboratory for Poultry Genetics and Breeding of Jiangsu Province, Jiangsu Institute of Poultry Science, Yangzhou, Jiangsu, 225125, China.
| | - Qinghua Nie
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China.
- Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, Guangdong, 510642, China.
| | - Zhenhui Li
- State Key Laboratory of Swine and Poultry Breeding Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, 510642, China.
- Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, Guangdong, 510642, China.
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30
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Guo X, Cao Y, Shi X, Xing J, Feng C, Wang T. Evaluating the prognostic potential of telomerase signature in breast cancer through advanced machine learning model. Front Immunol 2024; 15:1462953. [PMID: 39669558 PMCID: PMC11634871 DOI: 10.3389/fimmu.2024.1462953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Accepted: 11/14/2024] [Indexed: 12/14/2024] Open
Abstract
Background Breast cancer prognosis remains a significant challenge due to the disease's molecular heterogeneity and complexity. Accurate predictive models are critical for improving patient outcomes and tailoring personalized therapies. Methods We developed a Machine Learning-assisted Telomerase Signature (MLTS) by integrating multi-omics data from nine independent breast cancer datasets. Using multiple machine learning algorithms, we identified six telomerase-related genes significantly associated with patient survival. The predictive performance of MLTS was evaluated against 66 existing breast cancer prognostic models across diverse cohorts. Results The MLTS demonstrated superior predictive accuracy, stability, and reliability compared to other models. Patients with high MLTS scores exhibited increased tumor mutational burden, chromosomal instability, and poor survival outcomes. Single-cell RNA sequencing analysis further revealed higher MLTS scores in aneuploid tumor cells, suggesting a role in cancer progression. Immune profiling indicated distinct tumor microenvironment characteristics associated with MLTS scores, potentially guiding therapeutic decisions. Conclusions Our findings highlight the utility of MLTS as a robust prognostic biomarker for breast cancer. The ability of MLTS to predict patient outcomes and its association with key genomic and cellular features underscore its potential as a target for personalized therapy. Future research may focus on integrating MLTS with additional molecular signatures to enhance its clinical application in precision oncology.
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Affiliation(s)
- Xiao Guo
- School of Pharmacy, Beihua University, Jilin, Jilin, China
| | - Yuyan Cao
- School of Pharmacy, Beihua University, Jilin, Jilin, China
| | - Xinlin Shi
- School of Pharmacy, Beihua University, Jilin, Jilin, China
| | - Jiaying Xing
- School of Pharmacy, Beihua University, Jilin, Jilin, China
| | - Chuanbo Feng
- School of Pharmacy, Beihua University, Jilin, Jilin, China
| | - Tao Wang
- Research Laboratory Center, Guizhou Provincial People’s Hospital, Guiyang, Guizhou, China
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31
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Zhang T, Zhang X, Wu Z, Ren J, Zhao Z, Zhang H, Wang G, Wang T. VGAE-CCI: variational graph autoencoder-based construction of 3D spatial cell-cell communication network. Brief Bioinform 2024; 26:bbae619. [PMID: 39581873 PMCID: PMC11586124 DOI: 10.1093/bib/bbae619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 10/04/2024] [Accepted: 11/12/2024] [Indexed: 11/26/2024] Open
Abstract
Cell-cell communication plays a critical role in maintaining normal biological functions, regulating development and differentiation, and controlling immune responses. The rapid development of single-cell RNA sequencing and spatial transcriptomics sequencing (ST-seq) technologies provides essential data support for in-depth and comprehensive analysis of cell-cell communication. However, ST-seq data often contain incomplete data and systematic biases, which may reduce the accuracy and reliability of predicting cell-cell communication. Furthermore, other methods for analyzing cell-cell communication mainly focus on individual tissue sections, neglecting cell-cell communication across multiple tissue layers, and fail to comprehensively elucidate cell-cell communication networks within three-dimensional tissues. To address the aforementioned issues, we propose VGAE-CCI, a deep learning framework based on the Variational Graph Autoencoder, capable of identifying cell-cell communication across multiple tissue layers. Additionally, this model can be applied to spatial transcriptomics data with missing or partially incomplete data and can clustered cells at single-cell resolution based on spatial encoding information within complex tissues, thereby enabling more accurate inference of cell-cell communication. Finally, we tested our method on six datasets and compared it with other state of art methods for predicting cell-cell communication. Our method outperformed other methods across multiple metrics, demonstrating its efficiency and reliability in predicting cell-cell communication.
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Affiliation(s)
- Tianjiao Zhang
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
| | - Xiang Zhang
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
| | - Zhenao Wu
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
| | - Jixiang Ren
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
| | - Zhongqian Zhao
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
| | - Hongfei Zhang
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
| | - Guohua Wang
- College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Tao Wang
- School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China
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Wang T, Wang S, Li Z, Xie J, Du K, Hou J. Machine learning unveils key Redox signatures for enhanced breast Cancer therapy. Cancer Cell Int 2024; 24:368. [PMID: 39522039 PMCID: PMC11549853 DOI: 10.1186/s12935-024-03534-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2024] [Accepted: 10/14/2024] [Indexed: 11/16/2024] Open
Abstract
BACKGROUND Breast cancer remains a leading cause of mortality among women worldwide, necessitating innovative prognostic models to enhance treatment strategies. METHODS Our study retrospectively enrolled 9,439 breast cancer patients from 12 independent datasets and single-cell data from 12 patients (64,308 cells). Moverover, 30 in-house clinical cohort were collected for validation. We employed a comprehensive approach by combining ten distinct machine learning algorithms across 108 different combinations to scrutinize 88 pre-existing signatures of breast cancer. To affirm the efficacy of our developed model, immunohistochemistry assays were performed. Additionally, we investigated various potential immunotherapeutic and chemotherapeutic interventions. RESULTS This study introduces an Artificial Intelligence-aided Redox Signature (AIARS) as a novel prognostic tool, leveraging machine learning to identify critical redox-related gene signatures in breast cancer. Our results demonstrate that AIARS significantly outperforms existing prognostic models in predicting breast cancer outcomes, offering a robust tool for personalized treatment planning. Validation through immunohistochemistry assays on samples from 30 patients corroborated our results, underscoring the model's applicability on a wider scale. Furthermore, the analysis revealed that patients with low AIARS expression levels are more responsive to immunotherapy. Conversely, those exhibiting high AIARS were found to be more susceptible to certain chemotherapeutic agents, including vincristine. CONCLUSIONS Our study underscores the importance of redox biology in breast cancer prognosis and introduces a powerful machine learning-based tool, the AIARS, for personalized treatment strategies. By providing a more nuanced understanding of the redox landscape in breast cancer, the AIARS paves the way for the development of redox-targeted therapies, promising to enhance patient outcomes significantly. Future work will focus on clinical validation and exploring the mechanistic roles of identified genes in cancer biology.
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Affiliation(s)
- Tao Wang
- Research Laboratory Center, Guizhou Provincial People's Hospital, Guiyang, 550002, China
| | - Shu Wang
- Department of Breast Surgery, Guizhou Provincial People's Hospital, Guiyang, 550002, China
| | - Zhuolin Li
- Department of Breast Surgery, Guizhou Provincial People's Hospital, Guiyang, 550002, China
| | - Jie Xie
- Department of Breast Surgery, Guizhou Provincial People's Hospital, Guiyang, 550002, China
| | - Kuiying Du
- Department of Breast Surgery, Guizhou Provincial People's Hospital, Guiyang, 550002, China.
| | - Jing Hou
- Department of Breast Surgery, Guizhou Provincial People's Hospital, Guiyang, 550002, China.
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Westfall AK, Gopalan SS, Kay JC, Tippetts TS, Cervantes MB, Lackey K, Chowdhury SM, Pellegrino MW, Castoe TA. Single-cell resolution of intestinal regeneration in pythons without crypts illuminates conserved vertebrate regenerative mechanisms. Proc Natl Acad Sci U S A 2024; 121:e2405463121. [PMID: 39423244 PMCID: PMC11513969 DOI: 10.1073/pnas.2405463121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Accepted: 09/09/2024] [Indexed: 10/21/2024] Open
Abstract
Canonical models of intestinal regeneration emphasize the critical role of the crypt stem cell niche to generate enterocytes that migrate to villus ends. Burmese pythons possess extreme intestinal regenerative capacity yet lack crypts, thus providing opportunities to identify noncanonical but potentially conserved mechanisms that expand our understanding of regenerative capacity in vertebrates, including humans. Here, we leverage single-nucleus RNA sequencing of fasted and postprandial python small intestine to identify the signaling pathways and cell-cell interactions underlying the python's regenerative response. We find that python intestinal regeneration entails the activation of multiple conserved mechanisms of growth and stress response, including core lipid metabolism pathways and the unfolded protein response in intestinal enterocytes. Our single-cell resolution highlights extensive heterogeneity in mesenchymal cell population signaling and intercellular communication that directs major tissue restructuring and the shift out of a dormant fasted state by activating both embryonic developmental and wound healing pathways. We also identify distinct roles of BEST4+ enterocytes in coordinating key regenerative transitions via NOTCH signaling. Python intestinal regeneration shares key signaling features and molecules with mammalian gastric bypass, indicating that conserved regenerative programs are common to both. Our findings provide different insights into cooperative and conserved regenerative programs and intercellular interactions in vertebrates independent of crypts which have been otherwise obscured in model species where temporal phases of generative growth are limited to embryonic development or recovery from injury.
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Affiliation(s)
- Aundrea K. Westfall
- Department of Biology, University of Texas at Arlington, Arlington, TX76019
- Children’s Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX75235
| | | | - Jarren C. Kay
- Department of Biological Sciences, University of Alabama, Tuscaloosa, AL35401
| | - Trevor S. Tippetts
- Children’s Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX75235
| | - Margaret B. Cervantes
- Children’s Medical Center Research Institute, University of Texas Southwestern Medical Center, Dallas, TX75235
| | - Kimberly Lackey
- Department of Biological Sciences, University of Alabama, Tuscaloosa, AL35401
| | - Saiful M. Chowdhury
- Department of Chemistry and Biochemistry, University of Texas at Arlington, Arlington, TX76019
| | - Mark W. Pellegrino
- Department of Biology, University of Texas at Arlington, Arlington, TX76019
| | - Todd A. Castoe
- Department of Biology, University of Texas at Arlington, Arlington, TX76019
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Wang Z, Li Z, Luan T, Cui G, Shu S, Liang Y, Zhang K, Xiao J, Yu W, Cui J, Li A, Peng G, Fang Y. A spatiotemporal molecular atlas of mouse spinal cord injury identifies a distinct astrocyte subpopulation and therapeutic potential of IGFBP2. Dev Cell 2024; 59:2787-2803.e8. [PMID: 39029468 DOI: 10.1016/j.devcel.2024.06.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 03/26/2024] [Accepted: 06/20/2024] [Indexed: 07/21/2024]
Abstract
Spinal cord injury (SCI) triggers a cascade of intricate molecular and cellular changes that determine the outcome. In this study, we resolve the spatiotemporal organization of the injured mouse spinal cord and quantitatively assess in situ cell-cell communication following SCI. By analyzing existing single-cell RNA sequencing datasets alongside our spatial data, we delineate a subpopulation of Igfbp2-expressing astrocytes that migrate from the white matter (WM) to gray matter (GM) and become reactive upon SCI, termed Astro-GMii. Further, Igfbp2 upregulation promotes astrocyte migration, proliferation, and reactivity, and the secreted IGFBP2 protein fosters neurite outgrowth. Finally, we show that IGFBP2 significantly reduces neuronal loss and remarkably improves the functional recovery in a mouse model of SCI in vivo. Together, this study not only provides a comprehensive molecular atlas of SCI but also exemplifies how this rich resource can be applied to endow cells and genes with functional insight and therapeutic potential.
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Affiliation(s)
- Zeqing Wang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhuxia Li
- Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-CUHK Joint Research Laboratory on Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tianle Luan
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guizhong Cui
- Guangzhou National Laboratory, Guangzhou 510005, China
| | - Shunpan Shu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiyao Liang
- Key Laboratory of CNS Regeneration (Ministry of Education), Guangdong Key Laboratory of Non-human Primate Research, GHM Institute of CNS Regeneration, Jinan University, Guangzhou 510632, China
| | - Kai Zhang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jingshu Xiao
- Guangzhou National Laboratory, Guangzhou 510005, China
| | - Wei Yu
- Key Laboratory of CNS Regeneration (Ministry of Education), Guangdong Key Laboratory of Non-human Primate Research, GHM Institute of CNS Regeneration, Jinan University, Guangzhou 510632, China
| | - Jihong Cui
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China
| | - Ang Li
- Key Laboratory of CNS Regeneration (Ministry of Education), Guangdong Key Laboratory of Non-human Primate Research, GHM Institute of CNS Regeneration, Jinan University, Guangzhou 510632, China.
| | - Guangdun Peng
- Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-CUHK Joint Research Laboratory on Stem Cell and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Yanshan Fang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 201210, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Rexach JE, Cheng Y, Chen L, Polioudakis D, Lin LC, Mitri V, Elkins A, Han X, Yamakawa M, Yin A, Calini D, Kawaguchi R, Ou J, Huang J, Williams C, Robinson J, Gaus SE, Spina S, Lee EB, Grinberg LT, Vinters H, Trojanowski JQ, Seeley WW, Malhotra D, Geschwind DH. Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics. Cell 2024; 187:5753-5774.e28. [PMID: 39265576 PMCID: PMC12017262 DOI: 10.1016/j.cell.2024.08.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Revised: 05/29/2024] [Accepted: 08/09/2024] [Indexed: 09/14/2024]
Abstract
The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNA-seq and ATAC-seq in Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP), analyzing 41 participants and ∼1 million cells (RNA + ATAC) from three brain regions varying in vulnerability and pathological burden. We identify 32 shared, disease-associated cell types and 14 that are disease specific. Disease-specific cell states represent glial-immune mechanisms and selective neuronal vulnerability impacting layer 5 intratelencephalic neurons in AD, layer 2/3 intratelencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We identify disease-associated gene regulatory networks and cells impacted by causal genetic risk, which differ by disorder. These data illustrate the heterogeneous spectrum of glial and neuronal compositional and gene expression alterations in different dementias and identify therapeutic targets by revealing shared and disease-specific cell states.
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Affiliation(s)
- Jessica E Rexach
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Lawrence Chen
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Damon Polioudakis
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Li-Chun Lin
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Vivianne Mitri
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Andrew Elkins
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Xia Han
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Mai Yamakawa
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Anna Yin
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Daniela Calini
- Neuroscience and Rare Diseases, Roche Pharma Research and Early Development, F. Hoffman-LaRoche Ltd., Basel, Switzerland
| | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jing Ou
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jerry Huang
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Christopher Williams
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - John Robinson
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Stephanie E Gaus
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Salvatore Spina
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Edward B Lee
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Lea T Grinberg
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA; Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Harry Vinters
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - John Q Trojanowski
- Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - William W Seeley
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA; Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
| | - Dheeraj Malhotra
- Neuroscience and Rare Diseases, Roche Pharma Research and Early Development, F. Hoffman-LaRoche Ltd., Basel, Switzerland
| | - Daniel H Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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Nakata S, Iwasaki K, Funato H, Yanagisawa M, Ozaki H. Neuronal subtype-specific transcriptomic changes in the cerebral neocortex associated with sleep pressure. Neurosci Res 2024; 207:13-25. [PMID: 38537682 DOI: 10.1016/j.neures.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 03/19/2024] [Accepted: 03/22/2024] [Indexed: 04/07/2024]
Abstract
Sleep is homeostatically regulated by sleep pressure, which increases during wakefulness and dissipates during sleep. Recent studies have suggested that the cerebral neocortex, a six-layered structure composed of various layer- and projection-specific neuronal subtypes, is involved in the representation of sleep pressure governed by transcriptional regulation. Here, we examined the transcriptomic changes in neuronal subtypes in the neocortex upon increased sleep pressure using single-nucleus RNA sequencing datasets and predicted the putative intracellular and intercellular molecules involved in transcriptome alterations. We revealed that sleep deprivation (SD) had the greatest effect on the transcriptome of layer 2 and 3 intratelencephalic (L2/3 IT) neurons among the neocortical glutamatergic neuronal subtypes. The expression of mutant SIK3 (SLP), which is known to increase sleep pressure, also induced profound changes in the transcriptome of L2/3 IT neurons. We identified Junb as a candidate transcription factor involved in the alteration of the L2/3 IT neuronal transcriptome by SD and SIK3 (SLP) expression. Finally, we inferred putative intercellular ligands, including BDNF, LSAMP, and PRNP, which may be involved in SD-induced alteration of the transcriptome of L2/3 IT neurons. We suggest that the transcriptome of L2/3 IT neurons is most impacted by increased sleep pressure among neocortical glutamatergic neuronal subtypes and identify putative molecules involved in such transcriptional alterations.
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Affiliation(s)
- Shinya Nakata
- International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Kanako Iwasaki
- International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Hiromasa Funato
- International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Ibaraki, Japan; Department of Anatomy, Graduate School of Medicine, Toho University, Tokyo, Japan
| | - Masashi Yanagisawa
- International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Ibaraki, Japan; Department of Molecular Genetics, University of Texas Southwestern Medical Center, Dallas, TX, USA; Life Science Center for Survival Dynamics, Tsukuba Advanced Research Alliance, University of Tsukuba, Tsukuba, Ibaraki, Japan.
| | - Haruka Ozaki
- Bioinformatics Laboratory, Institute of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan; Center for Artificial Intelligence Research, University of Tsukuba, Tsukuba, Ibaraki, Japan.
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Jiang Y, Bei W, Li W, Huang Y, He S, Zhu X, Zheng L, Xia W, Dong S, Liu Q, Zhang C, Lv S, Xie C, Xiang Y, Liu G. Single-cell transcriptome analysis reveals evolving tumour microenvironment induced by immunochemotherapy in nasopharyngeal carcinoma. Clin Transl Med 2024; 14:e70061. [PMID: 39415331 PMCID: PMC11483602 DOI: 10.1002/ctm2.70061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 09/28/2024] [Accepted: 10/04/2024] [Indexed: 10/18/2024] Open
Abstract
BACKGROUND Combinatory therapeutic strategy containing immunochemotherapy as part of induction therapy components is one of the current trends in the treatment of high-risk metastatic locally advanced nasopharyngeal carcinoma (NPC). However, the mechanism underlying the heterogeneity of response at the single-cell level has not been underexplored. METHODS 18 bulks and 11 single-cell RNA sequencing from paired before-treatment and on-treatment samples in patients with treatment-naive high-risk metastatic locally advanced NPCs were obtained. Following quality control, a total of 87 191 cells were included in the subsequence bioinformatics analysis. RESULTS Immunochemotherapy was associated with on-treatment tumour microenvironment (TME) remodelling, including upregulation of anti-TMEs signatures, downregulation of pro-TMEs signatures, reversing CD8+ T exhaustion, and repolarizing proinflammatory TAMs. For the patients achieving a complete response, the cytotoxic activity of CD8+ T cells was stimulated and more interferon-gamma was provided, which would be the key for TAMs proinflammatory repolarization and eventually promote the CD8+ T cells maturation in turn. Among patients who did not reach complete response, differentiation and hypoxia signatures for endothelial cells were elevated after therapy. These patients exhibited higher levels of immune checkpoint genes in malignant cells at the baseline (before treatment), and decreased tumour antigen presentation activity, which may underlie the resistance mechanism to therapy. CONCLUSIONS This study pictures a map of TME modulation following immunochemotherapy-based combination induction therapy and provides potential future approaches. HIGHLIGHTS Immunochemotherapy remodeled T cell phenotypes. For the patients achieving complete response, more interferon gamma was provided by CD8+ T cells after therapy, which would be the key for TAMs pro-inflammatory repolarization and eventually promote the CD8+ T cells maturation in turns. Among patients who did not reach complete response, malignant cells exhibited higher level of immune checkpoint genes before therapy, and decreased tumor antigen presentation activity, which may underlie the resistance mechanism to therapy.
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Affiliation(s)
- Yaofei Jiang
- Department of Nasopharyngeal CarcinomaState Key Laboratory of Oncology in South ChinaGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangdong Provincial Clinical Research Center for CancerSun Yat‐Sen University Cancer CenterGuangzhouChina
- Department of Oncologythe First Affiliated Hospital of NanChang UniversityNanChangChina
| | - Weixin Bei
- Department of Nasopharyngeal CarcinomaState Key Laboratory of Oncology in South ChinaGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangdong Provincial Clinical Research Center for CancerSun Yat‐Sen University Cancer CenterGuangzhouChina
| | - Wangzhong Li
- Department of Thoracic Surgery and OncologyThe First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory HealthGuangzhouChina
| | - Ying Huang
- Department of RadiotherapySun Yat‐Sen University Cancer CenterGuangzhouChina
| | - Shuiqing He
- Department of Nasopharyngeal CarcinomaState Key Laboratory of Oncology in South ChinaGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangdong Provincial Clinical Research Center for CancerSun Yat‐Sen University Cancer CenterGuangzhouChina
| | - Xiaobin Zhu
- Thoracic and GI Malignancies BranchNational Cancer Institute, National Institutes of HealthBethesdaUSA
| | - Lisheng Zheng
- Department of PathologyGuangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouChina
| | - Weixiong Xia
- Department of Nasopharyngeal CarcinomaState Key Laboratory of Oncology in South ChinaGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangdong Provincial Clinical Research Center for CancerSun Yat‐Sen University Cancer CenterGuangzhouChina
| | - Shuhui Dong
- Department of Nasopharyngeal CarcinomaState Key Laboratory of Oncology in South ChinaGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangdong Provincial Clinical Research Center for CancerSun Yat‐Sen University Cancer CenterGuangzhouChina
| | - Qin Liu
- Department of Nasopharyngeal CarcinomaState Key Laboratory of Oncology in South ChinaGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangdong Provincial Clinical Research Center for CancerSun Yat‐Sen University Cancer CenterGuangzhouChina
| | - Chuanrun Zhang
- Department of Nasopharyngeal CarcinomaState Key Laboratory of Oncology in South ChinaGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangdong Provincial Clinical Research Center for CancerSun Yat‐Sen University Cancer CenterGuangzhouChina
| | - Shuhui Lv
- Department of Nasopharyngeal CarcinomaState Key Laboratory of Oncology in South ChinaGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangdong Provincial Clinical Research Center for CancerSun Yat‐Sen University Cancer CenterGuangzhouChina
| | - Changqing Xie
- Department of PathologyGuangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouChina
| | - Yanqun Xiang
- Department of Nasopharyngeal CarcinomaState Key Laboratory of Oncology in South ChinaGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangdong Provincial Clinical Research Center for CancerSun Yat‐Sen University Cancer CenterGuangzhouChina
| | - Guoying Liu
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene RegulationDepartment of Radiation OncologyMedical Research CenterSun Yat‐Sen Memorial Hospital, Sun Yat‐Sen UniversityGuangzhouChina
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Chen YJ, Chen Y, Chen P, Jia YQ, Wang H, Hong XP. Characteristics of PD-1 +CD4 + T cells in peripheral blood and synovium of rheumatoid arthritis patients. Clin Transl Immunology 2024; 13:e70006. [PMID: 39345753 PMCID: PMC11427813 DOI: 10.1002/cti2.70006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Revised: 07/29/2024] [Accepted: 09/13/2024] [Indexed: 10/01/2024] Open
Abstract
Objectives PD-1 plays a crucial role in the immune dysregulation of rheumatoid arthritis (RA), but the specific characteristics of PD-1+CD4+ T cells remain unclear and require further investigation. Methods Circulating PD-1+CD4+ T cells from RA patients were analysed using flow cytometry. Plasma levels of soluble PD-1 (sPD-1) were measured using enzyme-linked immunosorbent assay (ELISA). Single-cell RNA sequence data from peripheral blood mononuclear cells (PBMCs) and synovial tissue of patients were obtained from the GEO and the ImmPort databases. Bioinformatics analyses were performed in the R studio to characterise PD-1+CD4+ T cells. Expression of CCR7, KLF2 and IL32 in PD-1+CD4+ T cells was validated by flow cytometry. Results RA patients showed an elevated proportion of PD-1+CD4+ T cells in peripheral blood, along with increased plasma sPD-1 levels, which positively correlated with TNF-α and erythrocyte sedimentation rate. Bioinformatic analysis revealed PD-1 expression on CCR7+CD4+ T cells in PBMCs, and on both CCR7+CD4+ T cells and CXCL13+CD4+ T cells in RA synovium. PD-1 was co-expressed with CCR7, KLF2, and IL32 in peripheral CD4+ T cells. In synovium, PD-1+CCR7+CD4+ T cells had higher expression of TNF and LCP2, while PD-1+CXCL13+CD4+ T cells showed elevated levels of ARID5A and DUSP2. PD-1+CD4+ T cells in synovium also appeared to interact with B cells and fibroblasts through BTLA and TNFSF signalling pathways. Conclusion This study highlights the increased proportion of PD-1+CD4+ T cells and elevated sPD-1 levels in RA. The transcriptomic profiles and signalling networks of PD-1+CD4+ T cells offer new insights into their role in RA pathogenesis.
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Affiliation(s)
- Yan-Juan Chen
- Department of Rheumatology and Immunology The Second Clinical Medical College of Jinan University, Shenzhen People's Hospital Shenzhen China
- Integrated Chinese and Western Medicine Postdoctoral Research Station Jinan University Guangzhou China
| | - Yong Chen
- Department of Rheumatology and Immunology Affiliated Hospital of Zunyi Medical University Zunyi China
| | - Ping Chen
- Department of Rheumatology and Immunology Shenzhen People's Hospital Shenzhen China
| | - Yi-Qun Jia
- Stomatology Center, The Second Clinical Medical College of Jinan University Shenzhen People's Hospital Shenzhen China
| | - Hua Wang
- Department of Orthopaedics, The Second Clinical Medical College of Jinan University, The First Afiliated Hospital of Southern University of Science and Technology Shenzhen People's Hospital Shenzhen China
| | - Xiao-Ping Hong
- Department of Rheumatology and Immunology The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People's Hospital Shenzhen China
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Xu S, Chen X, Ying H, Chen J, Ye M, Lin Z, Zhang X, Shen T, Li Z, Zheng Y, Zhang D, Ke Y, Chen Z, Lu Z. Multi‑omics identification of a signature based on malignant cell-associated ligand-receptor genes for lung adenocarcinoma. BMC Cancer 2024; 24:1138. [PMID: 39267056 PMCID: PMC11395699 DOI: 10.1186/s12885-024-12911-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 09/06/2024] [Indexed: 09/14/2024] Open
Abstract
PURPOSE Lung adenocarcinoma (LUAD) significantly contributes to cancer-related mortality worldwide. The heterogeneity of the tumor immune microenvironment in LUAD results in varied prognoses and responses to immunotherapy among patients. Consequently, a clinical stratification algorithm is necessary and inevitable to effectively differentiate molecular features and tumor microenvironments, facilitating personalized treatment approaches. METHODS We constructed a comprehensive single-cell transcriptional atlas using single-cell RNA sequencing data to reveal the cellular diversity of malignant epithelial cells of LUAD and identified a novel signature through a computational framework coupled with 10 machine learning algorithms. Our study further investigates the immunological characteristics and therapeutic responses associated with this prognostic signature and validates the predictive efficacy of the model across multiple independent cohorts. RESULTS We developed a six-gene prognostic model (MYO1E, FEN1, NMI, ZNF506, ALDOA, and MLLT6) using the TCGA-LUAD dataset, categorizing patients into high- and low-risk groups. This model demonstrates robust performance in predicting survival across various LUAD cohorts. We observed distinct molecular patterns and biological processes in different risk groups. Additionally, analysis of two immunotherapy cohorts (N = 317) showed that patients with a high-risk signature responded more favorably to immunotherapy compared to those in the low-risk group. Experimental validation further confirmed that MYO1E enhances the proliferation and migration of LUAD cells. CONCLUSION We have identified malignant cell-associated ligand-receptor subtypes in LUAD cells and developed a robust prognostic signature by thoroughly analyzing genomic, transcriptomic, and immunologic data. This study presents a novel method to assess the prognosis of patients with LUAD and provides insights into developing more effective immunotherapies.
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Affiliation(s)
- Shengshan Xu
- Department of Thoracic Surgery, Jiangmen Central Hospital, Jiangmen, Guangdong, China.
| | - Xiguang Chen
- Department of Medical Oncology, The First Affiliated Hospital of University of South China, Hengyang, Hunan, China
| | - Haoxuan Ying
- Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Jiarong Chen
- Department of Oncology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Min Ye
- Department of Thoracic Surgery, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Zhichao Lin
- Department of Thoracic Surgery, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Xin Zhang
- Clinical Experimental Center, Jiangmen Key Laboratory of Clinical Biobanks and Translational Research, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Tao Shen
- Department of Thoracic Surgery, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Zumei Li
- Department of Thoracic Surgery, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Youbin Zheng
- Department of Radiology, Jiangmen Wuyi Hospital of Traditional Chinese Medicine, Jiangmen, Guangdong, China
| | - Dongxi Zhang
- Department of Thoracic Surgery, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Yongwen Ke
- Department of Thoracic Surgery, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Zhuowen Chen
- Department of Thoracic Surgery, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Zhuming Lu
- Department of Thoracic Surgery, Jiangmen Central Hospital, Jiangmen, Guangdong, China.
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Unger Avila P, Padvitski T, Leote AC, Chen H, Saez-Rodriguez J, Kann M, Beyer A. Gene regulatory networks in disease and ageing. Nat Rev Nephrol 2024; 20:616-633. [PMID: 38867109 DOI: 10.1038/s41581-024-00849-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/15/2024] [Indexed: 06/14/2024]
Abstract
The precise control of gene expression is required for the maintenance of cellular homeostasis and proper cellular function, and the declining control of gene expression with age is considered a major contributor to age-associated changes in cellular physiology and disease. The coordination of gene expression can be represented through models of the molecular interactions that govern gene expression levels, so-called gene regulatory networks. Gene regulatory networks can represent interactions that occur through signal transduction, those that involve regulatory transcription factors, or statistical models of gene-gene relationships based on the premise that certain sets of genes tend to be coexpressed across a range of conditions and cell types. Advances in experimental and computational technologies have enabled the inference of these networks on an unprecedented scale and at unprecedented precision. Here, we delineate different types of gene regulatory networks and their cell-biological interpretation. We describe methods for inferring such networks from large-scale, multi-omics datasets and present applications that have aided our understanding of cellular ageing and disease mechanisms.
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Affiliation(s)
- Paula Unger Avila
- Cluster of Excellence on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Tsimafei Padvitski
- Cluster of Excellence on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Ana Carolina Leote
- Cluster of Excellence on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - He Chen
- Cluster of Excellence on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
- Department II of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Julio Saez-Rodriguez
- Faculty of Medicine and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg University, Heidelberg, Germany
| | - Martin Kann
- Department II of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Center for Molecular Medicine Cologne, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Andreas Beyer
- Cluster of Excellence on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany.
- Center for Molecular Medicine Cologne, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
- Institute for Genetics, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany.
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Xu J, Li P, Wang Y, Li J, Xu B, Zhao J, Chen C, Gu S, Ding C, Liu P. The role of proliferating stem-like plasma cells in relapsed or refractory multiple myeloma: Insights from single-cell RNA sequencing and proteomic analysis. Br J Haematol 2024; 205:1031-1043. [PMID: 38671576 DOI: 10.1111/bjh.19486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 04/10/2024] [Indexed: 04/28/2024]
Abstract
The management and comprehension of relapsed or refractory multiple myeloma (RRMM) continues to pose a significant challenge. By integrating single-cell RNA sequencing (scRNA-seq) data of 15 patients with plasma cell disorders (PCDs) and proteomic data obtained from mass spectrometry-based analysis of CD138+ plasma cells (PCs) from 144 PCDs patients, we identified a state of malignant PCs characterized by high stemness score and increased proliferation originating from RRMM. This state has been designated as proliferating stem-like plasma cells (PSPCs). NUCKS1 was identified as the gene marker representing the stemness of PSPCs. Comparison of differentially expressed genes among various PC states revealed a significant elevation in LGALS1 expression in PSPCs. Survival analysis on the MMRF CoMMpass dataset and GSE24080 dataset established LGALS1 as a gene associated with unfavourable prognostic implications for multiple myeloma. Ultimately, we discovered three specific ligand-receptor pairs within the midkine (MDK) signalling pathway network that play distinct roles in facilitating efficient cellular communication between PSPCs and the surrounding microenvironment cells. These insights have the potential to contribute to the understanding of molecular mechanism and the development of therapeutic strategies involving the application of stem-like cells in RRMM treatment.
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Affiliation(s)
- Jiadai Xu
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Hematology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, Fujian, China
| | - Panpan Li
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yawen Wang
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jing Li
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Bei Xu
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jiangyan Zhao
- Institutes of Biomedical Sciences, State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Chen Chen
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shiyang Gu
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chen Ding
- Institutes of Biomedical Sciences, State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, China
| | - Peng Liu
- Department of Hematology, Zhongshan Hospital, Fudan University, Shanghai, China
- Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Hematology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, Fujian, China
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Joy MT, Carmichael ST. Activity-dependent transcriptional programs in memory regulate motor recovery after stroke. Commun Biol 2024; 7:1048. [PMID: 39183218 PMCID: PMC11345429 DOI: 10.1038/s42003-024-06723-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 08/12/2024] [Indexed: 08/27/2024] Open
Abstract
Stroke causes death of brain tissue leading to long-term deficits. Behavioral evidence from neurorehabilitative therapies suggest learning-induced neuroplasticity can lead to beneficial outcomes. However, molecular and cellular mechanisms that link learning and stroke recovery are unknown. We show that in a mouse model of stroke, which exhibits enhanced recovery of function due to genetic perturbations of learning and memory genes, animals display activity-dependent transcriptional programs that are normally active during formation or storage of new memories. The expression of neuronal activity-dependent genes are predictive of recovery and occupy a molecular latent space unique to motor recovery. With motor recovery, networks of activity-dependent genes are co-expressed with their transcription factor targets forming gene regulatory networks that support activity-dependent transcription, that are normally diminished after stroke. Neuronal activity-dependent changes at the circuit level are influenced by interactions with microglia. At the molecular level, we show that enrichment of activity-dependent programs in neurons lead to transcriptional changes in microglia where they differentially interact to support intercellular signaling pathways for axon guidance, growth and synaptogenesis. Together, these studies identify activity-dependent transcriptional programs as a fundamental mechanism for neural repair post-stroke.
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Affiliation(s)
- Mary T Joy
- The Jackson Laboratory, Bar Harbor, ME, 04609, USA.
| | - S Thomas Carmichael
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095, USA
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Ali A, Manzoor S, Ali T, Asim M, Muhammad G, Ahmad A, Jamaludin MI, Devaraj S, Munawar N. Innovative aspects and applications of single cell technology for different diseases. Am J Cancer Res 2024; 14:4028-4048. [PMID: 39267684 PMCID: PMC11387862 DOI: 10.62347/vufu1836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2024] [Accepted: 08/24/2024] [Indexed: 09/15/2024] Open
Abstract
Recent developments in single-cell technologies have provided valuable insights from cancer genomics to complex microbial communities. Single-cell technologies including the RNA-seq, next-generation sequencing (NGS), epigenomics, genomics, and transcriptomics can be used to uncover the single cell nature and molecular characterization of individual cells. These technologies also reveal the cellular transition states, evolutionary relationships between genes, the complex structure of single-cell populations, cell-to-cell interaction leading to biological discoveries and more reliable than traditional bulk technologies. These technologies are becoming the first choice for the early detection of inflammatory biomarkers affecting the proliferation and progression of tumor cells in the tumor microenvironment and improving the clinical efficacy of patients undergoing immunotherapy. These technologies also hold a central position in the detection of checkpoint inhibitors and thus determining the signaling pathways evoked by tumor invasion. This review addressed the emerging approaches of single cell-based technologies in cancer immunotherapies and different human diseases at cellular and molecular levels and the emerging role of sequencing technologies leading to drug discovery. Advancements in these technologies paved for discovering novel diagnostic markers for better understanding the pathological and biochemical mechanisms also for controlling the rate of different diseases.
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Affiliation(s)
- Ashiq Ali
- Department of Histology and Embryology, Shantou University Medical College Shantou 515041, Guangdong, China
| | - Saba Manzoor
- Department of Zoology, University of Sialkot Sialkot 51310, Pakistan
| | - Tayyab Ali
- Clinico-Molecular Biochemistry Laboratory, Department of Biochemistry, University of Agriculture Faisalabad 38000, Pakistan
| | - Muhammad Asim
- Clinico-Molecular Biochemistry Laboratory, Department of Biochemistry, University of Agriculture Faisalabad 38000, Pakistan
| | - Ghulam Muhammad
- Jinnah Burn and Reconstructive Surgery Centre, Jinnah Hospital, Allama Iqbal Medical College Lahore 54000, Pakistan
| | - Aftab Ahmad
- Biochemistry/Center for Advanced Studies in Agriculture and Food Security (CAS-AFS), University of Agriculture Faisalabad 38040, Pakistan
| | - Mohamad Ikhwan Jamaludin
- BioInspired Device and Tissue Engineering Research Group (BioInspira), Department of Biomedical Engineering and Health Sciences, Faculty of Electrical Engineering, Universiti Teknologi Malaysia Johor Bahru 81310, Johor, Malaysia
| | - Sutha Devaraj
- Graduate School of Medicine, Perdana University Wisma Chase Perdana, Changkat Semantan, Damansara Heights, Kuala Lumpur 50490, Malaysia
| | - Nayla Munawar
- Department of Chemistry, College of Science, United Arab Emirates University Al-Ain 15551, United Arab Emirates
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Zhang Y, Zhang J, Zhao S, Xu Y, Huang Y, Liu S, Su P, Wang C, Li Y, Li H, Yang P, Yang C. Single-cell RNA sequencing highlights the immunosuppression of IDO1 + macrophages in the malignant transformation of oral leukoplakia. Theranostics 2024; 14:4787-4805. [PMID: 39239507 PMCID: PMC11373622 DOI: 10.7150/thno.99112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Accepted: 07/30/2024] [Indexed: 09/07/2024] Open
Abstract
Rationale: Immunosuppressive tumor microenvironment (iTME) plays an important role in carcinogenesis, and some macrophage subsets are associated with iTME generation. However, the sub-population characterization of macrophages in oral carcinogenesis remains largely unclear. Here, we investigated the immunosuppressive status with focus on function of a macrophage subset that expressed indoleamine 2,3 dioxygenase 1 (Macro-IDO1) in oral carcinogenesis. Methods: We built a single cell transcriptome atlas from 3 patients simultaneously containing oral squamous cell carcinoma (OSCC), precancerous oral leukoplakia (preca-OLK) and paracancerous tissue (PCA). Through single-cell RNA sequencing and further validation using multicolor immunofluorescence staining and the in vitro/in vivo experiments, the immunosuppressive cell profiles were built and the role of a macrophage subset that expressed indoleamine 2,3 dioxygenase 1 (Macro-IDO1) in the malignant transformation of oral leukoplakia was evaluated. Results: The iTME formed at preca-OLK stage, as evidenced by increased exhausted T cells, Tregs and some special subsets of macrophages and fibroblasts. Macro-IDO1 was predominantly enriched in preca-OLK and OSCC, distributed near exhausted T cells and possessed tumor associated macrophage transformation potentials. Functional analysis revealed the established immunosuppressive role of Macro-IDO1 in preca-OLK and OSCC: enriching the immunosuppression related genes; having an established level of immune checkpoint score; exerting strong immunosuppressive interaction with T cells; positively correlating with the CD8-exhausted. The immunosuppression related gene expression of macrophages also increased in preca-OLK/OSCC compared to PCA. The use of the IDO1 inhibitor reduced 4NQO induced oral carcinogenesis in mice. Mechanistically, IFN-γ-JAK-STAT pathway was associated with IDO1 upregulation in OLK and OSCC. Conclusions: These results highlight that Macro-IDO1-enriched in preca-OLK possesses a strong immunosuppressive role and contributes to oral carcinogenesis, providing a potential target for preventing precancerous legions from transformation into OSCC.
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Affiliation(s)
- Yu Zhang
- School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, Shandong, China
- Department of Oral and Maxillofacial Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Jie Zhang
- Advanced Medical Research Institute, Shandong University, Jinan, Shandong, China
| | - Simin Zhao
- School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, Shandong, China
- Department of Oral and Maxillofacial Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Yan Xu
- Jinan Stomatological Hospital, Jinan, Shandong, China
| | - Yingying Huang
- Department of Oral and Maxillofacial Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Shaopeng Liu
- Department of Stomatology, Shandong Provincial Hospital Affiliated to Shandong First Medical University & Department of Stomatology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Peng Su
- Department of Pathology, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Caijiao Wang
- Department of Pathology, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, Shandong, China
| | - Yahui Li
- Department of Oral and Maxillofacial Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Hao Li
- Department of Oral and Maxillofacial Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Pishan Yang
- Department of Periodontology, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Research Center of Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases, Jinan, Shandong, China
| | - Chengzhe Yang
- Department of Oral and Maxillofacial Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China
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Oh Y, Abid R, Dababneh S, Bakr M, Aslani T, Cook DP, Vanderhyden BC, Park JG, Munshi NV, Hui CC, Kim KH. Transcriptional regulation of the postnatal cardiac conduction system heterogeneity. Nat Commun 2024; 15:6550. [PMID: 39095365 PMCID: PMC11297185 DOI: 10.1038/s41467-024-50849-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 07/23/2024] [Indexed: 08/04/2024] Open
Abstract
The cardiac conduction system (CCS) is a network of specialized cardiomyocytes that coordinates electrical impulse generation and propagation for synchronized heart contractions. Although the components of the CCS, including the sinoatrial node, atrioventricular node, His bundle, bundle branches, and Purkinje fibers, were anatomically discovered more than 100 years ago, their molecular constituents and regulatory mechanisms remain incompletely understood. Here, we demonstrate the transcriptomic landscape of the postnatal mouse CCS at a single-cell resolution with spatial information. Integration of single-cell and spatial transcriptomics uncover region-specific markers and zonation patterns of expression. Network inference shows heterogeneous gene regulatory networks across the CCS. Notably, region-specific gene regulation is recapitulated in vitro using neonatal mouse atrial and ventricular myocytes overexpressing CCS-specific transcription factors, Tbx3 and/or Irx3. This finding is supported by ATAC-seq of different CCS regions, Tbx3 ChIP-seq, and Irx motifs. Overall, this study provides comprehensive molecular profiles of the postnatal CCS and elucidates gene regulatory mechanisms contributing to its heterogeneity.
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Affiliation(s)
- Yena Oh
- University of Ottawa Heart Institute, Ottawa, ON, Canada
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Rimshah Abid
- University of Ottawa Heart Institute, Ottawa, ON, Canada
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Saif Dababneh
- University of Ottawa Heart Institute, Ottawa, ON, Canada
- Department of Cellular and Physiological Sciences, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Marwan Bakr
- University of Ottawa Heart Institute, Ottawa, ON, Canada
- Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa, ON, Canada
| | - Termeh Aslani
- University of Ottawa Heart Institute, Ottawa, ON, Canada
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - David P Cook
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
- Cancer Therapeutics Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Barbara C Vanderhyden
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
- Cancer Therapeutics Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Jin G Park
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Nikhil V Munshi
- Department of Internal Medicine, Division of Cardiology, UT Southwestern Medical Center, Dallas, TX, USA
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, TX, USA
- McDermott Center for Human Growth and Development, UT Southwestern Medical Center, Dallas, TX, USA
- Center for Regenerative Science and Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Chi-Chung Hui
- Program in Developmental & Stem Cell Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Kyoung-Han Kim
- University of Ottawa Heart Institute, Ottawa, ON, Canada.
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
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Guo DZ, Zhang X, Zhang SQ, Zhang SY, Zhang XY, Yan JY, Dong SY, Zhu K, Yang XR, Fan J, Zhou J, Huang A. Single-cell tumor heterogeneity landscape of hepatocellular carcinoma: unraveling the pro-metastatic subtype and its interaction loop with fibroblasts. Mol Cancer 2024; 23:157. [PMID: 39095854 PMCID: PMC11295380 DOI: 10.1186/s12943-024-02062-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 07/05/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND Tumor heterogeneity presents a formidable challenge in understanding the mechanisms driving tumor progression and metastasis. The heterogeneity of hepatocellular carcinoma (HCC) in cellular level is not clear. METHODS Integration analysis of single-cell RNA sequencing data and spatial transcriptomics data was performed. Multiple methods were applied to investigate the subtype of HCC tumor cells. The functional characteristics, translation factors, clinical implications and microenvironment associations of different subtypes of tumor cells were analyzed. The interaction of subtype and fibroblasts were analyzed. RESULTS We established a heterogeneity landscape of HCC malignant cells by integrated 52 single-cell RNA sequencing data and 5 spatial transcriptomics data. We identified three subtypes in tumor cells, including ARG1+ metabolism subtype (Metab-subtype), TOP2A+ proliferation phenotype (Prol-phenotype), and S100A6+ pro-metastatic subtype (EMT-subtype). Enrichment analysis found that the three subtypes harbored different features, that is metabolism, proliferating, and epithelial-mesenchymal transition. Trajectory analysis revealed that both Metab-subtype and EMT-subtype originated from the Prol-phenotype. Translation factor analysis found that EMT-subtype showed exclusive activation of SMAD3 and TGF-β signaling pathway. HCC dominated by EMT-subtype cells harbored an unfavorable prognosis and a deserted microenvironment. We uncovered a positive loop between tumor cells and fibroblasts mediated by SPP1-CD44 and CCN2/TGF-β-TGFBR1 interaction pairs. Inhibiting CCN2 disrupted the loop, mitigated the transformation to EMT-subtype, and suppressed metastasis. CONCLUSION By establishing a heterogeneity landscape of malignant cells, we identified a three-subtype classification in HCC. Among them, S100A6+ tumor cells play a crucial role in metastasis. Targeting the feedback loop between tumor cells and fibroblasts is a promising anti-metastatic strategy.
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Affiliation(s)
- De-Zhen Guo
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Xin Zhang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Sen-Quan Zhang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Shi-Yu Zhang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Xiang-Yu Zhang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Jia-Yan Yan
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - San-Yuan Dong
- Department of Radiology, Zhongshan Hospital, Shanghai Institute of Medical Imaging, Fudan University, Shanghai, 200032, China
| | - Kai Zhu
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Xin-Rong Yang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Jia Fan
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Institute of Biomedical Sciences, Fudan University, Shanghai, 200032, China
| | - Jian Zhou
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China.
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Institute of Biomedical Sciences, Fudan University, Shanghai, 200032, China.
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China.
| | - Ao Huang
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Key Laboratory of Carcinogenesis and Cancer Invasion (Fudan University), Ministry of Education, 136 Yi Xue Yuan Road, Shanghai, 200032, China.
- Shanghai Key Laboratory of Organ Transplantation, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
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Mathys H, Boix CA, Akay LA, Xia Z, Davila-Velderrain J, Ng AP, Jiang X, Abdelhady G, Galani K, Mantero J, Band N, James BT, Babu S, Galiana-Melendez F, Louderback K, Prokopenko D, Tanzi RE, Bennett DA, Tsai LH, Kellis M. Single-cell multiregion dissection of Alzheimer's disease. Nature 2024; 632:858-868. [PMID: 39048816 PMCID: PMC11338834 DOI: 10.1038/s41586-024-07606-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 05/24/2024] [Indexed: 07/27/2024]
Abstract
Alzheimer's disease is the leading cause of dementia worldwide, but the cellular pathways that underlie its pathological progression across brain regions remain poorly understood1-3. Here we report a single-cell transcriptomic atlas of six different brain regions in the aged human brain, covering 1.3 million cells from 283 post-mortem human brain samples across 48 individuals with and without Alzheimer's disease. We identify 76 cell types, including region-specific subtypes of astrocytes and excitatory neurons and an inhibitory interneuron population unique to the thalamus and distinct from canonical inhibitory subclasses. We identify vulnerable populations of excitatory and inhibitory neurons that are depleted in specific brain regions in Alzheimer's disease, and provide evidence that the Reelin signalling pathway is involved in modulating the vulnerability of these neurons. We develop a scalable method for discovering gene modules, which we use to identify cell-type-specific and region-specific modules that are altered in Alzheimer's disease and to annotate transcriptomic differences associated with diverse pathological variables. We identify an astrocyte program that is associated with cognitive resilience to Alzheimer's disease pathology, tying choline metabolism and polyamine biosynthesis in astrocytes to preserved cognitive function late in life. Together, our study develops a regional atlas of the ageing human brain and provides insights into cellular vulnerability, response and resilience to Alzheimer's disease pathology.
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Affiliation(s)
- Hansruedi Mathys
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- University of Pittsburgh Brain Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Carles A Boix
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computational and Systems Biology Program, MIT, Cambridge, MA, USA
| | - Leyla Anne Akay
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Ziting Xia
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Harvard-MIT Health Sciences and Technology Program, MIT, Cambridge, MA, USA
| | | | - Ayesha P Ng
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Xueqiao Jiang
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Ghada Abdelhady
- University of Pittsburgh Brain Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kyriaki Galani
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Julio Mantero
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Neil Band
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Benjamin T James
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sudhagar Babu
- University of Pittsburgh Brain Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Fabiola Galiana-Melendez
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Kate Louderback
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Dmitry Prokopenko
- Genetics and Aging Research Unit, McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Rudolph E Tanzi
- Genetics and Aging Research Unit, McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Li-Huei Tsai
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA.
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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McDermott JG, Goodlett BL, Creed HA, Navaneethabalakrishnan S, Rutkowski JM, Mitchell BM. Inflammatory Alterations to Renal Lymphatic Endothelial Cell Gene Expression in Mouse Models of Hypertension. Kidney Blood Press Res 2024; 49:588-604. [PMID: 38972305 PMCID: PMC11345939 DOI: 10.1159/000539721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 06/02/2024] [Indexed: 07/09/2024] Open
Abstract
INTRODUCTION Hypertension (HTN) is a major cardiovascular disease that can cause and be worsened by renal damage and inflammation. We previously reported that renal lymphatic endothelial cells (LECs) increase in response to HTN and that augmenting lymphangiogenesis in the kidneys reduces blood pressure and renal pro-inflammatory immune cells in mice with various forms of HTN. Our aim was to evaluate the specific changes that renal LECs undergo in HTN. METHODS We performed single-cell RNA sequencing. Using the angiotensin II-induced and salt-sensitive mouse models of HTN, we isolated renal CD31+ and podoplanin+ cells. RESULTS Sequencing of these cells revealed three distinct cell types with unique expression profiles, including LECs. The number and transcriptional diversity of LECs increased in samples from mice with HTN, as demonstrated by 597 differentially expressed genes (p < 0.01), 274 significantly enriched pathways (p < 0.01), and 331 regulons with specific enrichment in HTN LECs. These changes demonstrate a profound inflammatory response in renal LECs in HTN, leading to an increase in genes and pathways associated with inflammation-driven growth and immune checkpoint activity in LECs. CONCLUSION These results reinforce and help to further explain the benefits of renal LECs and lymphangiogenesis in HTN.
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Affiliation(s)
- Justin G. McDermott
- Department of Medical Physiology, Texas A&M University School of Medicine, Bryan, TX 77807
| | - Bethany L. Goodlett
- Department of Medical Physiology, Texas A&M University School of Medicine, Bryan, TX 77807
| | - Heidi A. Creed
- Department of Medical Physiology, Texas A&M University School of Medicine, Bryan, TX 77807
| | | | - Joseph M. Rutkowski
- Department of Medical Physiology, Texas A&M University School of Medicine, Bryan, TX 77807
| | - Brett M. Mitchell
- Department of Medical Physiology, Texas A&M University School of Medicine, Bryan, TX 77807
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Rasetto NB, Giacomini D, Berardino AA, Waichman TV, Beckel MS, Di Bella DJ, Brown J, Davies-Sala MG, Gerhardinger C, Lie DC, Arlotta P, Chernomoretz A, Schinder AF. Transcriptional dynamics orchestrating the development and integration of neurons born in the adult hippocampus. SCIENCE ADVANCES 2024; 10:eadp6039. [PMID: 39028813 PMCID: PMC11259177 DOI: 10.1126/sciadv.adp6039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Accepted: 06/13/2024] [Indexed: 07/21/2024]
Abstract
The adult hippocampus generates new granule cells (aGCs) with functional capabilities that convey unique forms of plasticity to the preexisting circuits. While early differentiation of adult radial glia-like cells (RGLs) has been studied extensively, the molecular mechanisms guiding the maturation of postmitotic neurons remain unknown. Here, we used a precise birthdating strategy to study aGC differentiation using single-nuclei RNA sequencing. Transcriptional profiling revealed a continuous trajectory from RGLs to mature aGCs, with multiple immature stages bearing increasing levels of effector genes supporting growth, excitability, and synaptogenesis. Analysis of differential gene expression, pseudo-time trajectory, and transcription factors (TFs) revealed critical transitions defining four cellular states: quiescent RGLs, proliferative progenitors, immature aGCs, and mature aGCs. Becoming mature aGCs involved a transcriptional switch that shuts down pathways promoting cell growth, such SoxC TFs, to activate programs that likely control neuronal homeostasis. aGCs overexpressing Sox4 or Sox11 remained immature. Our results unveil precise molecular mechanisms driving adult RGLs through the pathway of neuronal differentiation.
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Affiliation(s)
- Natalí B. Rasetto
- Instituto de Investigaciones Biomédicas de Buenos Aires (IIBBA) – CONICET, Buenos Aires, Argentina
- Laboratory of Neuronal Plasticity, Leloir Institute, Buenos Aires, Argentina
| | - Damiana Giacomini
- Instituto de Investigaciones Biomédicas de Buenos Aires (IIBBA) – CONICET, Buenos Aires, Argentina
- Laboratory of Neuronal Plasticity, Leloir Institute, Buenos Aires, Argentina
| | - Ariel A. Berardino
- Instituto de Investigaciones Biomédicas de Buenos Aires (IIBBA) – CONICET, Buenos Aires, Argentina
- Laboratory of Integrative Systems Biology, Leloir Institute, Buenos Aires, Argentina
| | - Tomás Vega Waichman
- Instituto de Investigaciones Biomédicas de Buenos Aires (IIBBA) – CONICET, Buenos Aires, Argentina
- Laboratory of Integrative Systems Biology, Leloir Institute, Buenos Aires, Argentina
| | - Maximiliano S. Beckel
- Instituto de Investigaciones Biomédicas de Buenos Aires (IIBBA) – CONICET, Buenos Aires, Argentina
- Laboratory of Integrative Systems Biology, Leloir Institute, Buenos Aires, Argentina
| | - Daniela J. Di Bella
- Department of Stem Cells and Regenerative Biology, Harvard University and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Juliana Brown
- Department of Stem Cells and Regenerative Biology, Harvard University and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - M. Georgina Davies-Sala
- Instituto de Investigaciones Biomédicas de Buenos Aires (IIBBA) – CONICET, Buenos Aires, Argentina
- Laboratory of Neuronal Plasticity, Leloir Institute, Buenos Aires, Argentina
| | - Chiara Gerhardinger
- Department of Stem Cells and Regenerative Biology, Harvard University and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Dieter Chichung Lie
- Institute of Biochemistry, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Paola Arlotta
- Department of Stem Cells and Regenerative Biology, Harvard University and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ariel Chernomoretz
- Instituto de Investigaciones Biomédicas de Buenos Aires (IIBBA) – CONICET, Buenos Aires, Argentina
- Laboratory of Integrative Systems Biology, Leloir Institute, Buenos Aires, Argentina
- University of Buenos Aires, School of Science, Phys Dept and INFINA (CONICET-UBA), Buenos Aires, Argentina
| | - Alejandro F. Schinder
- Instituto de Investigaciones Biomédicas de Buenos Aires (IIBBA) – CONICET, Buenos Aires, Argentina
- Laboratory of Neuronal Plasticity, Leloir Institute, Buenos Aires, Argentina
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50
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Zhu Z, Huang J, Zhang Y, Hou W, Chen F, Mo YY, Zhang Z. Landscape of tumoral ecosystem for enhanced anti-PD-1 immunotherapy by gut Akkermansia muciniphila. Cell Rep 2024; 43:114306. [PMID: 38819989 DOI: 10.1016/j.celrep.2024.114306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 02/07/2024] [Accepted: 05/15/2024] [Indexed: 06/02/2024] Open
Abstract
Gut Akkermansia muciniphila (Akk) has been implicated in impacting immunotherapy or oncogenesis. This study aims to dissect the Akk-associated tumor immune ecosystem (TIME) by single-cell profiling coupled with T cell receptor (TCR) sequencing. We adopted mouse cancer models under anti-PD-1 immunotherapy, combined with oral administration of three forms of Akk, including live Akk, pasteurized Akk (Akk-past), or its membrane protein Amuc_1100 (Amuc). We show that live Akk is most effective in activation of CD8 T cells by rescuing the exhausted type into cytotoxic subpopulations. Remarkably, only live Akk activates MHC-II-pDC pathways, downregulates CXCL3 in Bgn(+)Dcn(+) cancer-associated fibroblasts (CAFs), blunts crosstalk between Bgn(+)Dcn(+) CAFs and PD-L1(+) neutrophils by a CXCL3-PD-L1 axis, and further suppresses the crosstalk between PD-L1(+) neutrophils and CD8 T cells, leading to the rescue of exhausted CD8 T cells. Together, this comprehensive picture of the tumor ecosystem provides deeper insights into immune mechanisms associated with gut Akk-dependent anti-PD-1 immunotherapy.
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Affiliation(s)
- Zhuxian Zhu
- Department of Nephrology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - Jianguo Huang
- Earle A. Chiles Research Institute, a division of Providence Cancer Institute, Portland, OR 97213, USA
| | - Yanling Zhang
- Department of Emergency Medicine, Tongji University School of Medicine, Shanghai 200065, China
| | - Weiwei Hou
- Department of Clinical Laboratory, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - Fei Chen
- Department of Emergency Medicine, Tongji University School of Medicine, Shanghai 200065, China
| | - Yin-Yuan Mo
- Institute of Clinical Medicine, Zhejiang Provincial People's Hospital of Hangzhou Medical College, Hangzhou 310014 , China.
| | - Ziqiang Zhang
- Department of Respiratory and Critical Care Medicine, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Pudong Hospital of Fudan University, Shanghai 201399, China.
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