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Guo CK, Xia CR, Peng G, Cao ZJ, Gao G. Learning Phenotype Associated Signature in Spatial Transcriptomics with PASSAGE. SMALL METHODS 2025; 9:e2401451. [PMID: 39905872 DOI: 10.1002/smtd.202401451] [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: 09/06/2024] [Revised: 12/31/2024] [Indexed: 02/06/2025]
Abstract
Spatially resolved transcriptomics (SRT) is poised to advance the understanding of cellular organization within complex tissues under various physiological and pathological conditions at unprecedented resolution. Despite the development of numerous computational tools that facilitate the automatic identification of statistically significant intra-/inter-slice patterns (like spatial domains), these methods typically operate in an unsupervised manner, without leveraging sample characteristics like physiological/pathological states. Here PASSAGE (Phenotype Associated Spatial Signature Analysis with Graph-based Embedding), a rationally-designed deep learning framework is presented for characterizing phenotype-associated signatures across multiple heterogeneous spatial slices effectively. In addition to its outstanding performance in systematic benchmarks, PASSAGE's unique capability in calling sophisticated signatures has been demonstrated in multiple real-world cases. The full package of PASSAGE is available at https://github.com/gao-lab/PASSAGE.
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Affiliation(s)
- Chen-Kai Guo
- Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, University of Chinese Academy of Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Chen-Rui Xia
- State Key Laboratory of Gene Function and Modulation Research, School of Life Sciences, Biomedical Pioneering Innovative Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), Peking University, Beijing, 100871, China
- Changping Laboratory, Beijing, 102206, 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-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, University of Chinese Academy of Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhi-Jie Cao
- State Key Laboratory of Gene Function and Modulation Research, School of Life Sciences, Biomedical Pioneering Innovative Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), Peking University, Beijing, 100871, China
- Changping Laboratory, Beijing, 102206, China
| | - Ge Gao
- State Key Laboratory of Gene Function and Modulation Research, School of Life Sciences, Biomedical Pioneering Innovative Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), Peking University, Beijing, 100871, China
- Changping Laboratory, Beijing, 102206, China
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Bao X, Bai X, Liu X, Shi Q, Zhang C. Spatially informed graph transformers for spatially resolved transcriptomics. Commun Biol 2025; 8:574. [PMID: 40188303 PMCID: PMC11972348 DOI: 10.1038/s42003-025-08015-w] [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: 09/12/2024] [Accepted: 03/28/2025] [Indexed: 04/07/2025] Open
Abstract
Spatially resolved transcriptomics (SRT) has emerged as a powerful technique for mapping gene expression landscapes within spatial contexts. However, significant challenges persist in effectively integrating gene expression with spatial information to elucidate the heterogeneity of biological tissues. Here, we present a Spatially informed Graph Transformers framework, SpaGT, which leverages both node and edge channels to model spatially aware graph representation for denoising gene expression and identifying spatial domains. Unlike conventional graph neural networks, which rely on static, localized convolutional aggregation, SpaGT employs a structure-reinforced self-attention mechanism that iteratively evolves topological structural information and transcriptional signal representation. By replacing graph convolution with global self-attention, SpaGT enables the integration of both global and spatially localized information, thereby improving the detection of fine-grained spatial domains. We demonstrate that SpaGT achieves superior performance in identifying spatial domains and denoising gene expression data across diverse platforms and species. Furthermore, SpaGT facilitates the discovery of spatially variable genes with significant prognostic potential in cancer tissues. These findings establish SpaGT as a powerful tool for unraveling the complexities of biological tissues.
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Affiliation(s)
- Xinyu Bao
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China
| | - Xiaosheng Bai
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China
| | - Xiaoping Liu
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China.
| | - Qianqian Shi
- Hubei Engineering Technology Research Center of Agricultural Big Data, Huazhong Agricultural University, Wuhan, China.
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China.
| | - Chuanchao Zhang
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China.
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3
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Grech L, Grech CA, Calleja-Agius J, Pace NP. Biobanking and gynecologic oncology - Special considerations, challenges and opportunities. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2025; 51:109713. [PMID: 40348475 DOI: 10.1016/j.ejso.2025.109713] [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: 12/23/2024] [Revised: 02/17/2025] [Accepted: 02/18/2025] [Indexed: 05/14/2025]
Abstract
Biobanks of gynecological tissues occupy a critical niche in oncologic research. They are essential components of contemporary research strategies on gynecologic malignancy by integrating clinical, molecular and longitudinal biospecimen data. They also implement protocols for quality control, regulate sample and data sharing, provide ethical and regulatory oversight, and establish governance mechanisms to regulate their function. Gynecologic tissue biobanks also face some unique challenges. The broad heterogeneity of disease entities encompassed under this domain include common and rare malignancies, each with unique molecular subtypes that must be integrated into biobank information systems. Specimen acquisition extends beyond conventional tissues to include cervicovaginal microbiomes and ascitic fluid. Thus, gynecologic tissue biobanks should develop tailored collection strategies and the establishment of dedicated gynecologic tissue repositories that enable the aggregation of rare specimens through collaborative networks. This article emphasizes the need for high-quality annotation of biospecimens, the incorporation of multi-omics approaches to enhance the translational approaches, challenges associated with integration of high dimensional datasets, the role of biobank networks, and various ethical and cultural considerations concerning gynecologic biobanks. Emerging technologies that integrate multi omics, spatial biology and liquid biopsies now offer enhanced opportunities that augment classical specimen collection and should be integrated into standardized protocols.
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Affiliation(s)
- Laura Grech
- Department of Applied Biomedical Sciences, Faculty of Health Sciences, University of Malta, Msida, Malta; Centre for Molecular Medicine and Biobanking, University of Malta, Msida, Malta.
| | - Celine Ann Grech
- Department of Anatomy, Faculty of Medicine and Surgery, University of Malta, Msida, Malta.
| | - Jean Calleja-Agius
- Department of Anatomy, Faculty of Medicine and Surgery, University of Malta, Msida, Malta; Centre for Molecular Medicine and Biobanking, University of Malta, Msida, Malta.
| | - Nikolai Paul Pace
- Department of Anatomy, Faculty of Medicine and Surgery, University of Malta, Msida, Malta; Centre for Molecular Medicine and Biobanking, University of Malta, Msida, Malta.
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4
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An J, Lu Y, Chen Y, Chen Y, Zhou Z, Chen J, Peng C, Huang R, Peng F. Spatial transcriptomics in breast cancer: providing insight into tumor heterogeneity and promoting individualized therapy. Front Immunol 2024; 15:1499301. [PMID: 39749323 PMCID: PMC11693744 DOI: 10.3389/fimmu.2024.1499301] [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: 09/20/2024] [Accepted: 12/05/2024] [Indexed: 01/04/2025] Open
Abstract
A comprehensive understanding of tumor heterogeneity, tumor microenvironment and the mechanisms of drug resistance is fundamental to advancing breast cancer research. While single-cell RNA sequencing has resolved the issue of "temporal dynamic expression" of genes at the single-cell level, the lack of spatial information still prevents us from gaining a comprehensive understanding of breast cancer. The introduction and application of spatial transcriptomics addresses this limitation. As the annual technical method of 2020, spatial transcriptomics preserves the spatial location of tissues and resolves RNA-seq data to help localize and differentiate the active expression of functional genes within a specific tissue region, enabling the study of spatial location attributes of gene locations and cellular tissue environments. In the context of breast cancer, spatial transcriptomics can assist in the identification of novel breast cancer subtypes and spatially discriminative features that show promise for individualized precise treatment. This article summarized the key technical approaches, recent advances in spatial transcriptomics and its applications in breast cancer, and discusses the limitations of current spatial transcriptomics methods and the prospects for future development, with a view to advancing the application of this technology in clinical practice.
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Affiliation(s)
- Junsha An
- West China School of Pharmacy, Sichuan University, Chengdu, China
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Cardiovascular Department, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yajie Lu
- West China School of Pharmacy, Sichuan University, Chengdu, China
| | - Yuxi Chen
- West China School of Pharmacy, Sichuan University, Chengdu, China
| | - Yuling Chen
- West China School of Pharmacy, Sichuan University, Chengdu, China
| | - Zhaokai Zhou
- Department of Clinical Medicine, Zhengzhou University, Zhengzhou, China
| | - Jianping Chen
- School of Chinese Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Cheng Peng
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Ruizhen Huang
- Cardiovascular Department, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Fu Peng
- West China School of Pharmacy, Sichuan University, Chengdu, China
- Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry, Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Center for Drug Precision Industrial Technology, Sichuan University, Chengdu, China
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Croizer H, Mhaidly R, Kieffer Y, Gentric G, Djerroudi L, Leclere R, Pelon F, Robley C, Bohec M, Meng A, Meseure D, Romano E, Baulande S, Peltier A, Vincent-Salomon A, Mechta-Grigoriou F. Deciphering the spatial landscape and plasticity of immunosuppressive fibroblasts in breast cancer. Nat Commun 2024; 15:2806. [PMID: 38561380 PMCID: PMC10984943 DOI: 10.1038/s41467-024-47068-z] [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: 08/01/2023] [Accepted: 03/19/2024] [Indexed: 04/04/2024] Open
Abstract
Although heterogeneity of FAP+ Cancer-Associated Fibroblasts (CAF) has been described in breast cancer, their plasticity and spatial distribution remain poorly understood. Here, we analyze trajectory inference, deconvolute spatial transcriptomics at single-cell level and perform functional assays to generate a high-resolution integrated map of breast cancer (BC), with a focus on inflammatory and myofibroblastic (iCAF/myCAF) FAP+ CAF clusters. We identify 10 spatially-organized FAP+ CAF-related cellular niches, called EcoCellTypes, which are differentially localized within tumors. Consistent with their spatial organization, cancer cells drive the transition of detoxification-associated iCAF (Detox-iCAF) towards immunosuppressive extracellular matrix (ECM)-producing myCAF (ECM-myCAF) via a DPP4- and YAP-dependent mechanism. In turn, ECM-myCAF polarize TREM2+ macrophages, regulatory NK and T cells to induce immunosuppressive EcoCellTypes, while Detox-iCAF are associated with FOLR2+ macrophages in an immuno-protective EcoCellType. FAP+ CAF subpopulations accumulate differently according to the invasive BC status and predict invasive recurrence of ductal carcinoma in situ (DCIS), which could help in identifying low-risk DCIS patients eligible for therapeutic de-escalation.
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Affiliation(s)
- Hugo Croizer
- Institut Curie, Stress and Cancer Laboratory, Equipe Labélisée par la Ligue Nationale Contre le Cancer, PSL Research University, 26, Rue d'Ulm, F-75248, Paris, France
- Inserm, U830, 26, Rue d'Ulm, F-75005, Paris, France
| | - Rana Mhaidly
- Institut Curie, Stress and Cancer Laboratory, Equipe Labélisée par la Ligue Nationale Contre le Cancer, PSL Research University, 26, Rue d'Ulm, F-75248, Paris, France
- Inserm, U830, 26, Rue d'Ulm, F-75005, Paris, France
| | - Yann Kieffer
- Institut Curie, Stress and Cancer Laboratory, Equipe Labélisée par la Ligue Nationale Contre le Cancer, PSL Research University, 26, Rue d'Ulm, F-75248, Paris, France
- Inserm, U830, 26, Rue d'Ulm, F-75005, Paris, France
| | - Geraldine Gentric
- Institut Curie, Stress and Cancer Laboratory, Equipe Labélisée par la Ligue Nationale Contre le Cancer, PSL Research University, 26, Rue d'Ulm, F-75248, Paris, France
- Inserm, U830, 26, Rue d'Ulm, F-75005, Paris, France
| | - Lounes Djerroudi
- Institut Curie, Stress and Cancer Laboratory, Equipe Labélisée par la Ligue Nationale Contre le Cancer, PSL Research University, 26, Rue d'Ulm, F-75248, Paris, France
- Inserm, U830, 26, Rue d'Ulm, F-75005, Paris, France
- Department of Diagnostic and Theragnostic Medicine, Institut Curie Hospital Group, 26, Rue d'Ulm, F-75248, Paris, France
| | - Renaud Leclere
- Department of Diagnostic and Theragnostic Medicine, Institut Curie Hospital Group, 26, Rue d'Ulm, F-75248, Paris, France
| | - Floriane Pelon
- Institut Curie, Stress and Cancer Laboratory, Equipe Labélisée par la Ligue Nationale Contre le Cancer, PSL Research University, 26, Rue d'Ulm, F-75248, Paris, France
- Inserm, U830, 26, Rue d'Ulm, F-75005, Paris, France
| | - Catherine Robley
- Institut Curie, Stress and Cancer Laboratory, Equipe Labélisée par la Ligue Nationale Contre le Cancer, PSL Research University, 26, Rue d'Ulm, F-75248, Paris, France
- Inserm, U830, 26, Rue d'Ulm, F-75005, Paris, France
| | - Mylene Bohec
- Institut Curie, PSL Research University, ICGex Next-Generation Sequencing Platform, 75005, Paris, France
- Institut Curie, PSL Research University, Single Cell Initiative, 75005, Paris, France
| | - Arnaud Meng
- Institut Curie, Stress and Cancer Laboratory, Equipe Labélisée par la Ligue Nationale Contre le Cancer, PSL Research University, 26, Rue d'Ulm, F-75248, Paris, France
- Inserm, U830, 26, Rue d'Ulm, F-75005, Paris, France
| | - Didier Meseure
- Department of Diagnostic and Theragnostic Medicine, Institut Curie Hospital Group, 26, Rue d'Ulm, F-75248, Paris, France
| | - Emanuela Romano
- Department of Medical Oncology, Center for Cancer Immunotherapy, Institut Curie, 26, Rue d'Ulm, F-75248, Paris, France
| | - Sylvain Baulande
- Institut Curie, PSL Research University, ICGex Next-Generation Sequencing Platform, 75005, Paris, France
- Institut Curie, PSL Research University, Single Cell Initiative, 75005, Paris, France
| | - Agathe Peltier
- Institut Curie, Stress and Cancer Laboratory, Equipe Labélisée par la Ligue Nationale Contre le Cancer, PSL Research University, 26, Rue d'Ulm, F-75248, Paris, France
- Inserm, U830, 26, Rue d'Ulm, F-75005, Paris, France
| | - Anne Vincent-Salomon
- Department of Diagnostic and Theragnostic Medicine, Institut Curie Hospital Group, 26, Rue d'Ulm, F-75248, Paris, France
| | - Fatima Mechta-Grigoriou
- Institut Curie, Stress and Cancer Laboratory, Equipe Labélisée par la Ligue Nationale Contre le Cancer, PSL Research University, 26, Rue d'Ulm, F-75248, Paris, France.
- Inserm, U830, 26, Rue d'Ulm, F-75005, Paris, France.
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Wang G, Yang C, Zeng D, Wang J, Mao H, Xu Y, Jiang C, Wang Z. Case report: Successful treatment of a rare HER2-positive advanced breast squamous cell carcinoma. Front Pharmacol 2024; 15:1332574. [PMID: 38455963 PMCID: PMC10917954 DOI: 10.3389/fphar.2024.1332574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 02/05/2024] [Indexed: 03/09/2024] Open
Abstract
Background: Breast squamous cell carcinoma (SCC) is an uncommon and highly aggressive variant of metaplastic breast cancer. Despite its rarity, there is currently no consensus on treatment guidelines for this specific subtype. Previous studies have demonstrated that chemotherapy alone has limited efficacy in treating breast SCC. However, the potential for targeted therapy in combination with chemotherapy holds promise for future treatment options. Case presentation: In this case report, we present a patient with advanced HER2-positive breast SCC, exhibiting a prominent breast mass, localized ulcers, and metastases in the lungs and brain. Our treatment approach involved the administration of HER2-targeted drugs in conjunction with paclitaxel, resulting in a sustained control of tumor growth. Conclusion: This case represents a rare occurrence of HER2-positive breast SCC, with limited available data on the efficacy of previous HER2-targeted drugs in treating such patients. Our study presents the first application of HER2-targeted drugs in this particular case, offering novel therapeutic insights for future considerations. Additionally, it is imperative to conduct further investigations to assess the feasibility of treatment options in a larger cohort of patients.
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Affiliation(s)
- Gui Wang
- Department of General Surgery, Longquan People’s Hospital, Lishui, China
- Department of Breast Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chenghui Yang
- Department of Breast Surgery, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Donglin Zeng
- Department of General Surgery, Longquan People’s Hospital, Lishui, China
| | - Jihao Wang
- Department of General Surgery, Longquan People’s Hospital, Lishui, China
| | - Huaxin Mao
- Department of General Surgery, Longquan People’s Hospital, Lishui, China
| | - Yu Xu
- Department of General Surgery, Longquan People’s Hospital, Lishui, China
| | - Chao Jiang
- Academy of Chinese Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, China
| | - Zhen Wang
- Department of Breast Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Tumor Microenvironment and Immune Therapy of Zhejiang Province, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Cancer Center, Zhejiang University, Hangzhou, China
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