1
|
Jing ZQ, Luo ZQ, Chen SR, Sun ZJ. Heterogeneity of myeloid cells in common cancers: Single cell insights and targeting strategies. Int Immunopharmacol 2024; 134:112253. [PMID: 38735257 DOI: 10.1016/j.intimp.2024.112253] [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: 03/27/2024] [Revised: 05/02/2024] [Accepted: 05/09/2024] [Indexed: 05/14/2024]
Abstract
Tumor microenvironment (TME), is characterized by a complex and heterogenous composition involving a substantial population of immune cells. Myeloid cells comprising over half of the solid tumor mass, are undoubtedly one of the most prominent cell populations associated with tumors. Studies have unambiguously established that myeloid cells play a key role in tumor development, including immune suppression, pro-inflammation, promote tumor metastasis and angiogenesis, for example, tumor-associated macrophages promote tumor progression in a variety of common tumors, including lung cancer, through direct or indirect interactions with the TME. However, due to previous technological constraints, research on myeloid cells often tended to be conducted as studies with low throughput and limited resolution. For example, the conventional categorization of macrophages into M1-like and M2-like subsets based solely on their anti-tumor and pro-tumor roles has disregarded their continuum of states, resulting in an inadequate analysis of the high heterogeneity characterizing myeloid cells. The widespread adoption of single-cell RNA sequencing (scRNA-seq) in tumor immunology has propelled researchers into a new realm of understanding, leading to the establishment of novel subsets and targets. In this review, the origin of myeloid cells in high-incidence cancers, the functions of myeloid cell subsets examined through traditional and single-cell perspectives, as well as specific targeting strategies, are comprehensively outlined. As a result of this endeavor, we will gain a better understanding of myeloid cell heterogeneity, as well as contribute to the development of new therapeutic approaches.
Collapse
Affiliation(s)
- Zhi-Qian Jing
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Frontier Science Center for Immunology and Metabolism, Taikang Center for Life and Medical Science, Wuhan University, Wuhan 430079, China
| | - Zhi-Qi Luo
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Frontier Science Center for Immunology and Metabolism, Taikang Center for Life and Medical Science, Wuhan University, Wuhan 430079, China
| | - Si-Rui Chen
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Frontier Science Center for Immunology and Metabolism, Taikang Center for Life and Medical Science, Wuhan University, Wuhan 430079, China
| | - Zhi-Jun Sun
- State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Frontier Science Center for Immunology and Metabolism, Taikang Center for Life and Medical Science, Wuhan University, Wuhan 430079, China.
| |
Collapse
|
2
|
Pan X, Feng S, Wang Y, Chen J, Lin H, Wang Z, Hou F, Lu C, Chen X, Liu Z, Li Z, Cui Y, Liu Z. Spatial distance between tumor and lymphocyte can predict the survival of patients with resectable lung adenocarcinoma. Heliyon 2024; 10:e30779. [PMID: 38779006 PMCID: PMC11109847 DOI: 10.1016/j.heliyon.2024.e30779] [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: 11/26/2023] [Revised: 05/02/2024] [Accepted: 05/06/2024] [Indexed: 05/25/2024] Open
Abstract
Background and objective Spatial interaction between tumor-infiltrating lymphocytes (TILs) and tumor cells is valuable in predicting the effectiveness of immune response and prognosis amongst patients with lung adenocarcinoma (LUAD). Recent evidence suggests that the spatial distance between tumor cells and lymphocytes also influences the immune responses, but the distance analysis based on Hematoxylin and Eosin (H&E) -stained whole-slide images (WSIs) remains insufficient. To address this issue, we aim to explore the relationship between distance and prognosis prediction of patients with LUAD in this study. Methods We recruited patients with resectable LUAD from three independent cohorts in this multi-center study. We proposed a simple but effective deep learning-driven workflow to automatically segment different cell types in the tumor region using the HoVer-Net model, and quantified the spatial distance (DIST) between tumor cells and lymphocytes based on H&E-stained WSIs. The association of DIST with disease-free survival (DFS) was explored in the discovery set (D1, n = 276) and the two validation sets (V1, n = 139; V2, n = 115). Results In multivariable analysis, the low DIST group was associated with significantly better DFS in the discovery set (D1, HR, 0.61; 95 % CI, 0.40-0.94; p = 0.027) and the two validation sets (V1, HR, 0.54; 95 % CI, 0.32-0.91; p = 0.022; V2, HR, 0.44; 95 % CI, 0.24-0.81; p = 0.009). By integrating the DIST with clinicopathological factors, the integrated model (full model) had better discrimination for DFS in the discovery set (C-index, D1, 0.745 vs. 0.723) and the two validation sets (V1, 0.621 vs. 0.596; V2, 0.671 vs. 0.650). Furthermore, the computerized DIST was associated with immune phenotypes such as immune-desert and inflamed phenotypes. Conclusions The integration of DIST with clinicopathological factors could improve the stratification performance of patients with resectable LUAD, was beneficial for the prognosis prediction of LUAD patients, and was also expected to assist physicians in individualized treatment.
Collapse
Affiliation(s)
- Xipeng Pan
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
| | - Siyang Feng
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
| | - Yumeng Wang
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, 510080, China
| | - Jiale Chen
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
| | - Huan Lin
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, 510080, China
- School of Medicine, South China University of Technology, Guangzhou, 510006, China
| | - Zimin Wang
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
| | - Feihu Hou
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
| | - Cheng Lu
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, 510080, China
| | - Xin Chen
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 510180, China
| | - Zhenbing Liu
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
| | - Zhenhui Li
- Department of Radiology, The Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Centre, Kunming, 650118, China
| | - Yanfen Cui
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, 510080, China
- Guangdong Cardiovascular Institute, Guangzhou, 510080, China
- Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China
| | - Zaiyi Liu
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou, 510080, China
| |
Collapse
|
3
|
Wang Y, Zhu Z, Luo R, Chen W. Single-cell transcriptome analysis reveals heterogeneity of neutrophils in non-small cell lung cancer. J Gene Med 2024; 26:e3690. [PMID: 38735760 DOI: 10.1002/jgm.3690] [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: 12/23/2023] [Revised: 03/23/2024] [Accepted: 04/07/2024] [Indexed: 05/14/2024] Open
Abstract
BACKGROUND Lung cancer stands out as a highly perilous malignant tumor with severe implications for human health. There has been a growing interest in neutrophils as a result of their role in promoting cancer in recent years. Thus, the present study aimed to investigate the heterogeneity of neutrophils in non-small cell lung cancer (NSCLC). METHODS Single-cell RNA sequencing of tumor-associated neutrophils (TANs) and polymorphonuclear neutrophils sourced from the Gene Expression Omnibus database was analyzed. Moreover, cell-cell communication, differentiation trajectories and transcription factor analyses were performed. RESULTS Neutrophils were found to be closely associated with macrophages. Four major types of TANs were identified: a transitional subcluster that migrated from blood to tumor microenvironment (TAN-0), an inflammatory subcluster (TAN-1), a subpopulation that displayed a distinctive transcriptional signature (TAN-2) and a final differentiation state that promoted tumor formation (TAN-3). Meanwhile, TAN-3 displayed a marked increase in glycolytic activity. Finally, transcription factors were analyzed to uncover distinct TAN cluster-specific regulons. CONCLUSIONS The discovery of the dynamic characteristics of TANs in the present study is anticipated to contribute to yielding a better understanding of the tumor microenvironment and advancing the treatment of NSCLC.
Collapse
Affiliation(s)
- Yunzhen Wang
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Ziyi Zhu
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Raojun Luo
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Wenwen Chen
- Nursing Department, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| |
Collapse
|
4
|
Peng H, Wu X, Cui X, Liu S, Liang Y, Cai X, Shi M, Zhong R, Li C, Liu J, Wu D, Gao Z, Lu X, Luo H, He J, Liang W. Molecular and immune characterization of Chinese early-stage non-squamous non-small cell lung cancer: a multi-omics cohort study. Transl Lung Cancer Res 2024; 13:763-784. [PMID: 38736486 PMCID: PMC11082711 DOI: 10.21037/tlcr-23-800] [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: 12/02/2023] [Accepted: 03/15/2024] [Indexed: 05/14/2024]
Abstract
Background Albeit considered with superior survival, around 30% of the early-stage non-squamous non-small cell lung cancer (Ns-NSCLC) patients relapse within 5 years, suggesting unique biology. However, the biological characteristics of early-stage Ns-NSCLC, especially in the Chinese population, are still unclear. Methods Multi-omics interrogation of early-stage Ns-NSCLC (stage I-III), paired blood samples and normal lung tissues (n=76) by whole-exome sequencing (WES), RNA sequencing, and T-cell receptor (TCR) sequencing were conducted. Results An average of 128 exonic mutations were identified, and the most frequently mutant gene was EGFR (55%), followed by TP53 (37%) and TTN (26%). Mutations in MUC17, ABCA2, PDE4DIP, and MYO18B predicted significantly unfavorable disease-free survival (DFS). Moreover, cytobands amplifications in 8q24.3, 14q13.1, 14q11.2, and deletion in 3p21.1 were highlighted in recurrent cases. Higher incidence of human leukocyte antigen loss of heterozygosity (HLA-LOH), higher tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were identified in ever-smokers than never-smokers. HLA-LOH also correlated with higher TMB, TNB, intratumoral heterogeneity (ITH), and whole chromosomal instability (wCIN) scores. Interestingly, higher ITH was an independent predictor of better DFS in early-stage Ns-NSCLC. Up-regulation of immune-related genes, including CRABP2, ULBP2, IL31RA, and IL1A, independently portended a dismal prognosis. Enhanced TCR diversity of peripheral blood mononuclear cells (PBMCs) predicted better prognosis, indicative of a noninvasive method for relapse surveillance. Eventually, seven machine-learning (ML) algorithms were employed to evaluate the predictive accuracy of clinical, genomic, transcriptomic, and TCR repertoire data on DFS, showing that clinical and RNA features combination in the random forest (RF) algorithm, with area under the curve (AUC) of 97.5% and 83.3% in the training and testing cohort, respectively, significantly outperformed other methods. Conclusions This study comprehensively profiled the genomic, transcriptomic, and TCR repertoire spectrums of Chinese early-stage Ns-NSCLC, shedding light on biological underpinnings and candidate biomarkers for prognosis development.
Collapse
Affiliation(s)
- Haoxin Peng
- Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing, China
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Nanshan School, Guangzhou Medical University, Guangzhou, China
| | - Xiangrong Wu
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Clinical Medicine, Nanshan School, Guangzhou Medical University, Guangzhou, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Xiaoli Cui
- Shenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology Co., Ltd., Shenzhen, China
| | - Shaopeng Liu
- Department of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, China
- Department of Artificial Intelligence Research, Pazhou Lab, Guangzhou, China
| | - Yueting Liang
- Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Xiuyu Cai
- Department of General Internal Medicine, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Cener for Cancer Medicine, Guangzhou, China
| | - Mengping Shi
- Department of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, China
| | - Ran Zhong
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Caichen Li
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jun Liu
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Dongfang Wu
- Shenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology Co., Ltd., Shenzhen, China
| | - Zhibo Gao
- Shenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology Co., Ltd., Shenzhen, China
| | - Xu Lu
- Department of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, China
- Department of Artificial Intelligence Research, Pazhou Lab, Guangzhou, China
| | - Haitao Luo
- Shenzhen Engineering Center for Translational Medicine of Precision Cancer Immunodiagnosis and Therapy, YuceBio Technology Co., Ltd., Shenzhen, China
| | - Jianxing He
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Wenhua Liang
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Medical Oncology, The First People’s Hospital of Zhaoqing, Zhaoqing, China
| |
Collapse
|
5
|
Yehan Z, Sheng Q, Hong Y, Jiayu L, Jun H, Juan J, Min S, Jiaxin Y, Shangzhi H, Yi W, Qifeng W, Xuefeng L, Wenwu H, Xueyan C, Yang L, Zongyao H. To develop a prognostic model for neoadjuvant immunochemotherapy efficacy in esophageal squamous cell carcinoma by analyzing the immune microenvironment. Front Immunol 2024; 15:1312380. [PMID: 38726002 PMCID: PMC11079241 DOI: 10.3389/fimmu.2024.1312380] [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: 10/10/2023] [Accepted: 04/10/2024] [Indexed: 05/12/2024] Open
Abstract
Objective The choice of neoadjuvant therapy for esophageal squamous cell carcinoma (ESCC) is controversial. This study aims to provide a basis for clinical treatment selection by establishing a predictive model for the efficacy of neoadjuvant immunochemotherapy (NICT). Methods A retrospective analysis of 30 patients was conducted, divided into Response and Non-response groups based on whether they achieved major pathological remission (MPR). Differences in genes and immune microenvironment between the two groups were analyzed through next-generation sequencing (NGS) and multiplex immunofluorescence (mIF). Variables most closely related to therapeutic efficacy were selected through LASSO regression and ROC curves to establish a predictive model. An additional 48 patients were prospectively collected as a validation set to verify the model's effectiveness. Results NGS suggested seven differential genes (ATM, ATR, BIVM-ERCC5, MAP3K1, PRG, RBM10, and TSHR) between the two groups (P < 0.05). mIF indicated significant differences in the quantity and location of CD3+, PD-L1+, CD3+PD-L1+, CD4+PD-1+, CD4+LAG-3+, CD8+LAG-3+, LAG-3+ between the two groups before treatment (P < 0.05). Dynamic mIF analysis also indicated that CD3+, CD8+, and CD20+ all increased after treatment in both groups, with a more significant increase in CD8+ and CD20+ in the Response group (P < 0.05), and a more significant decrease in PD-L1+ (P < 0.05). The three variables most closely related to therapeutic efficacy were selected through LASSO regression and ROC curves: Tumor area PD-L1+ (AUC= 0.881), CD3+PD-L1+ (AUC= 0.833), and CD3+ (AUC= 0.826), and a predictive model was established. The model showed high performance in both the training set (AUC= 0.938) and the validation set (AUC= 0.832). Compared to the traditional CPS scoring criteria, the model showed significant improvements in accuracy (83.3% vs 70.8%), sensitivity (0.625 vs 0.312), and specificity (0.937 vs 0.906). Conclusion NICT treatment may exert anti-tumor effects by enriching immune cells and activating exhausted T cells. Tumor area CD3+, PD-L1+, and CD3+PD-L1+ are closely related to therapeutic efficacy. The model containing these three variables can accurately predict treatment outcomes, providing a reliable basis for the selection of neoadjuvant treatment plans.
Collapse
Affiliation(s)
- Zhou Yehan
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Qin Sheng
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yang Hong
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Li Jiayu
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Hou Jun
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Ji Juan
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Shi Min
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yan Jiaxin
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Hu Shangzhi
- Department of Endoscopy Center, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Wang Yi
- Department of Radiotherapy, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Wang Qifeng
- Department of Radiotherapy, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Leng Xuefeng
- Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - He Wenwu
- Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | | | - Liu Yang
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Huang Zongyao
- Department of Pathology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| |
Collapse
|
6
|
Matchett KP, Paris J, Teichmann SA, Henderson NC. Spatial genomics: mapping human steatotic liver disease. Nat Rev Gastroenterol Hepatol 2024:10.1038/s41575-024-00915-2. [PMID: 38654090 DOI: 10.1038/s41575-024-00915-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/28/2024] [Indexed: 04/25/2024]
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD, formerly known as non-alcoholic fatty liver disease) is a leading cause of chronic liver disease worldwide. MASLD can progress to metabolic dysfunction-associated steatohepatitis (MASH, formerly known as non-alcoholic steatohepatitis) with subsequent liver cirrhosis and hepatocellular carcinoma formation. The advent of current technologies such as single-cell and single-nuclei RNA sequencing have transformed our understanding of the liver in homeostasis and disease. The next frontier is contextualizing this single-cell information in its native spatial orientation. This understanding will markedly accelerate discovery science in hepatology, resulting in a further step-change in our knowledge of liver biology and pathobiology. In this Review, we discuss up-to-date knowledge of MASLD development and progression and how the burgeoning field of spatial genomics is driving exciting new developments in our understanding of human liver disease pathogenesis and therapeutic target identification.
Collapse
Affiliation(s)
- Kylie P Matchett
- Centre for Inflammation Research, Institute for Regeneration and Repair, Edinburgh BioQuarter, University of Edinburgh, Edinburgh, UK
| | - Jasmin Paris
- Centre for Inflammation Research, Institute for Regeneration and Repair, Edinburgh BioQuarter, University of Edinburgh, Edinburgh, UK
| | - Sarah A Teichmann
- Wellcome Sanger Institute, Cambridge, UK
- Department of Physics, Cavendish Laboratory, University of Cambridge, Cambridge, UK
| | - Neil C Henderson
- Centre for Inflammation Research, Institute for Regeneration and Repair, Edinburgh BioQuarter, University of Edinburgh, Edinburgh, UK.
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
| |
Collapse
|
7
|
Li X, Zhou N, Yang Y, Lu Z, Gou H. Efficacy and biomarker analysis of second-line nab-paclitaxel plus sintilimab in patients with advanced biliary tract cancer. Cancer Sci 2024. [PMID: 38638055 DOI: 10.1111/cas.16179] [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: 01/12/2024] [Revised: 03/18/2024] [Accepted: 03/26/2024] [Indexed: 04/20/2024] Open
Abstract
Biliary tract cancer (BTC) is a highly aggressive malignancy with limited second-line therapy. We conducted this phase 2 trial to evaluate the efficacy and safety of second-line nab-paclitaxel plus sintilimab in advanced BTC. Histologically confirmed advanced BTC patients with documented disease progression after first-line chemotherapy were enrolled. Subjects received nab-paclitaxel 125 mg/m2 on days 1 and 8 plus sintilimab 200 mg on day 1, administered every 3 weeks. The primary end point was the objective response rate (ORR). The secondary end points were progression-free survival (PFS), overall survival (OS), and adverse reactions. Simultaneously, next-generation sequencing, programmed cell death ligand 1 immunohistochemistry and multiplex immunofluorescence of tumor-infiltrating lymphocytes were applied to explore potential biomarkers. Twenty-six subjects were consecutively enrolled. The ORR was 26.9% (7/26), including two complete responses and five partial responses, which met the primary end point. The disease control rate was 61.5% (16/26). The median PFS was 169 days (about 5.6 months, 95% confidence interval [CI] 60-278 days). The median OS was 442 days (about 14.7 months, 95% CI 298-586 days). Grade 3 treatment-related adverse events (TRAEs) were mainly anemia (27%), leukopenia (23%), neutropenia (19%), and peripheral sensory neuropathy (8%). No grade 4 or 5 TRAEs occurred. Biomarker analysis suggested that positive PD-L1 and high proportions of CD8+ T-cell infiltration were correlated with improved clinical outcome. Nab-paclitaxel plus sintilimab is a potentially effective and tolerable second-line regimen for advanced BTC that deserves to be studied in large-scale trials. PD-L1 status and CD8+ T cell infiltration might be promising biomarkers for efficacy prediction.
Collapse
Affiliation(s)
- Xiaofen Li
- Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Division of Abdominal Tumor Multimodality Treatment, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Nan Zhou
- Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Gastric Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Yu Yang
- Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Division of Abdominal Tumor Multimodality Treatment, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Zijian Lu
- Department of Pathology, West China Hospital, Sichuan University, Chengdu, China
| | - Hongfeng Gou
- Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
- Gastric Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| |
Collapse
|
8
|
Ziółkowska-Suchanek I, Żurawek M. FOXP3: A Player of Immunogenetic Architecture in Lung Cancer. Genes (Basel) 2024; 15:493. [PMID: 38674427 PMCID: PMC11050689 DOI: 10.3390/genes15040493] [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: 03/13/2024] [Revised: 04/05/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024] Open
Abstract
The transcription factor forkhead box protein 3 (FOXP3) is considered to be a prominent component of the immune system expressed in regulatory T cells (Tregs). Tregs are immunosuppressive cells that regulate immune homeostasis and self-tolerance. FOXP3 was originally thought to be a Tregs-specific molecule, but recent studies have pinpointed that FOXP3 is expressed in a diversity of benign tumors and carcinomas. The vast majority of the data have shown that FOXP3 is correlated with an unfavorable prognosis, although there are some reports indicating the opposite function of this molecule. Here, we review recent progress in understanding the FOXP3 role in the immunogenetic architecture of lung cancer, which is the leading cause of cancer-related death. We discuss the prognostic significance of tumor FOXP3 expression, tumor-infiltrating FOXP3-lymphocytes, tumor FOXP3 in tumor microenvironments and the potential of FOXP3-targeted therapy.
Collapse
|
9
|
Diao B, Luo J, Guo Y. A comprehensive survey on deep learning-based identification and predicting the interaction mechanism of long non-coding RNAs. Brief Funct Genomics 2024:elae010. [PMID: 38576205 DOI: 10.1093/bfgp/elae010] [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: 12/06/2023] [Revised: 02/25/2024] [Accepted: 03/14/2024] [Indexed: 04/06/2024] Open
Abstract
Long noncoding RNAs (lncRNAs) have been discovered to be extensively involved in eukaryotic epigenetic, transcriptional, and post-transcriptional regulatory processes with the advancements in sequencing technology and genomics research. Therefore, they play crucial roles in the body's normal physiology and various disease outcomes. Presently, numerous unknown lncRNA sequencing data require exploration. Establishing deep learning-based prediction models for lncRNAs provides valuable insights for researchers, substantially reducing time and costs associated with trial and error and facilitating the disease-relevant lncRNA identification for prognosis analysis and targeted drug development as the era of artificial intelligence progresses. However, most lncRNA-related researchers lack awareness of the latest advancements in deep learning models and model selection and application in functional research on lncRNAs. Thus, we elucidate the concept of deep learning models, explore several prevalent deep learning algorithms and their data preferences, conduct a comprehensive review of recent literature studies with exemplary predictive performance over the past 5 years in conjunction with diverse prediction functions, critically analyze and discuss the merits and limitations of current deep learning models and solutions, while also proposing prospects based on cutting-edge advancements in lncRNA research.
Collapse
Affiliation(s)
- Biyu Diao
- Department of Breast Surgery, The First Affiliated Hospital of Ningbo University, No. 59, Liuting Street, Haishu District, Ningbo 315000, China
| | - Jin Luo
- Department of Breast Surgery, The First Affiliated Hospital of Ningbo University, No. 59, Liuting Street, Haishu District, Ningbo 315000, China
| | - Yu Guo
- Department of Breast Surgery, The First Affiliated Hospital of Ningbo University, No. 59, Liuting Street, Haishu District, Ningbo 315000, China
| |
Collapse
|
10
|
Wen S, Zou R, Du X, Pan R, Li R, Xia J, Xu C, Wang R, Jiang F, Zhou G, Feng J, Zhu M, Wang X, Shen B. Identification of macrophage-related genes correlated with prognosis and immunotherapy efficacy in non-small cell lung cancer. Heliyon 2024; 10:e27170. [PMID: 38500993 PMCID: PMC10945138 DOI: 10.1016/j.heliyon.2024.e27170] [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: 08/01/2023] [Revised: 02/22/2024] [Accepted: 02/26/2024] [Indexed: 03/20/2024] Open
Abstract
Background Malignant tumours, particularly non-small cell lung cancer (NSCLC), pose a significant threat to human health due to their prevalence and lethality. Treatment methods for NSCLC vary greatly among individuals, making it crucial to identify predictive markers. Moreover, during tumour initiation and progression, tumour cells can release signaling molecules to induce polarization of macrophages towards a more tumour friendly M2 phenotype, which can promote tumour growth, metastasis, and drug resistance. Methods We employed a comprehensive approach, combining bulk RNA-seq and single-cell sequencing analysis. Results In our study, we used bulk RNA-seq and single-cell sequencing methods to analyze differential cells in NSCLC and adjacent tissues, searching for relevant marker genes that can predict prognosis and drug efficacy. We scrutinized biological phenomena such as macrophage-related gene methylation, copy number variation, and alternative splicing. Additionally, we utilized a co-culture technique of immune and tumour cells to explore the role of these genes in macrophage polarization. Our findings revealed distinct differences in macrophages between cancerous and adjacent tissues. We identified ANP32A, CCL20, ERAP2, MYD88, TMEM126B, TUBB6, and ZNF655 as macrophage-related genes that correlate with NSCLC patient prognosis and immunotherapy efficacy. Notably, ERAP2, TUBB6, CCL20, and TMEM126B can induce macrophage M0 to M2 polarization, promoting tumour proliferation. Conclusion These findings significantly contribute to our understanding of the NSCLC tumour immune microenvironment. They pave the way for further research into the potential of these genes as targets for regulating tumour occurrence and development.
Collapse
Affiliation(s)
| | | | - Xiaoyue Du
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Rongtian Pan
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Rutao Li
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Jingwei Xia
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Cong Xu
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Ruotong Wang
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Feng Jiang
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Guoren Zhou
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Jifeng Feng
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Miaolin Zhu
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Xin Wang
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| | - Bo Shen
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu, Nanjing 21000, China
| |
Collapse
|
11
|
Serebrovskaya EO, Bryushkova EA, Lukyanov DK, Mushenkova NV, Chudakov DM, Turchaninova MA. Toolkit for mapping the clonal landscape of tumor-infiltrating B cells. Semin Immunol 2024; 72:101864. [PMID: 38301345 DOI: 10.1016/j.smim.2024.101864] [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: 01/06/2024] [Accepted: 01/08/2024] [Indexed: 02/03/2024]
Abstract
Our current understanding of whether B cell involvement in the tumor microenvironment benefits the patient or the tumor - in distinct cancers, subcohorts and individual patients - is quite limited. Both statements are probably true in most cases: certain clonal B cell populations contribute to the antitumor response, while others steer the immune response away from the desired mechanics. To step up to a new level of understanding and managing B cell behaviors in the tumor microenvironment, we need to rationally discern these roles, which are cumulatively defined by B cell clonal functional programs, specificities of their B cell receptors, specificities and isotypes of the antibodies they produce, and their spatial interactions within the tumor environment. Comprehensive analysis of these characteristics of clonal B cell populations is now becoming feasible with the development of a whole arsenal of advanced technical approaches, which include (1) methods of single-cell and spatial transcriptomics, genomics, and proteomics; (2) methods of massive identification of B cell specificities; (3) methods of deep error-free profiling of B cell receptor repertoires. Here we overview existing techniques, summarize their current application for B cells studies and propose promising future directions in advancing B cells exploration.
Collapse
Affiliation(s)
- E O Serebrovskaya
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, Moscow, Russia; Current position: Miltenyi Biotec B.V. & Co. KG, Bergisch Gladbach, Germany
| | - E A Bryushkova
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, Moscow, Russia; Department of Molecular Biology, Lomonosov Moscow State University, Moscow, Russia
| | - D K Lukyanov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, Moscow, Russia; Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - N V Mushenkova
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia; Unicorn Capital Partners, 119049, Moscow, Russia
| | - D M Chudakov
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, Moscow, Russia; Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia; Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
| | - M A Turchaninova
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry RAS, Moscow, Russia
| |
Collapse
|
12
|
Kandathil SA, Peter Truta I, Kadletz-Wanke L, Heiduschka G, Stoiber S, Kenner L, Herrmann H, Huskic H, Brkic FF. Lymphocyte-to-Monocyte Ratio Might Serve as a Prognostic Marker in Young Patients with Tongue Squamous Cell Carcinoma. J Pers Med 2024; 14:159. [PMID: 38392590 PMCID: PMC10890051 DOI: 10.3390/jpm14020159] [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: 12/22/2023] [Revised: 01/21/2024] [Accepted: 01/30/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND Young patients with tongue squamous cell carcinoma (TSCC) mostly lack typical prognostic markers and face a dire prognosis. The aim of this study was to analyze the prognostic relevance of lymphocyte-to-monocyte ratio (LMR) in TSCC patients, with a special emphasis on patients under 45 years. METHODS This retrospective study included all patients primarily treated for TSCC. The prognostic relevance of LMR was investigated in terms of predicting the overallsurvival (OS) and disease-free survival (DFS). RESULTS A total of 74 patients were included and the young cohort (<45 years) comprised 27 individuals. The mortality and recurrence rates were 39.2% (n = 29) and 37.8% (n = 28), respectively. OS and DFS were significantly shorter in the low LMR group within the whole cohort. Furthermore, low LMR was associated with worse prognosis, particularly inferior OS (median OS 1.7 vs. 14.6 years, p = 0.0156) and worse DFS (median DFS 0.8 years vs. not reached, p = 0.0405) in the young patient cohort. CONCLUSIONS Our results reveal that pretreatment LMR might become a prognostic tool for young TSCC patients, especially due to its availability. However, further studies on larger cohorts are necessary to validate our results.
Collapse
Affiliation(s)
- Sam Augustine Kandathil
- Department of Otorhinolaryngology and Head and Neck Surgery, Medical University of Vienna, 1090 Vienna, Austria
- Division of Anatomy, Center for Anatomy and Cell Biology, Medical University of Vienna, 1090 Vienna, Austria
| | - Ina Peter Truta
- Department of Otorhinolaryngology and Head and Neck Surgery, Medical University of Vienna, 1090 Vienna, Austria
| | - Lorenz Kadletz-Wanke
- Department of Otorhinolaryngology and Head and Neck Surgery, Medical University of Vienna, 1090 Vienna, Austria
| | - Gregor Heiduschka
- Department of Otorhinolaryngology and Head and Neck Surgery, Medical University of Vienna, 1090 Vienna, Austria
| | - Stefan Stoiber
- Department of Pathology, Medical University of Vienna, 1090 Vienna, Austria
- Christian Doppler Laboratory for Applied Metabolomics, 1090 Vienna, Austria
| | - Lukas Kenner
- Department of Pathology, Medical University of Vienna, 1090 Vienna, Austria
- Christian Doppler Laboratory for Applied Metabolomics, 1090 Vienna, Austria
- Center for Biomarker Research in Medicine, 8010 Graz, Austria
- Unit for Pathology of Laboratory Animals, University of Veterinary Medicine Vienna, 1210 Vienna, Austria
| | - Harald Herrmann
- Department of Radiation Oncology, Medical University of Vienna, 1090 Vienna, Austria
| | - Harun Huskic
- Department of Radiation Oncology, Medical University of Vienna, 1090 Vienna, Austria
| | - Faris F Brkic
- Department of Otorhinolaryngology and Head and Neck Surgery, Medical University of Vienna, 1090 Vienna, Austria
| |
Collapse
|
13
|
Ji S, Shi Y, Yin B. Macrophage barrier in the tumor microenvironment and potential clinical applications. Cell Commun Signal 2024; 22:74. [PMID: 38279145 PMCID: PMC10811890 DOI: 10.1186/s12964-023-01424-6] [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: 09/19/2023] [Accepted: 12/05/2023] [Indexed: 01/28/2024] Open
Abstract
The tumor microenvironment (TME) constitutes a complex microenvironment comprising a diverse array of immune cells and stromal components. Within this intricate context, tumor-associated macrophages (TAMs) exhibit notable spatial heterogeneity. This heterogeneity contributes to various facets of tumor behavior, including immune response modulation, angiogenesis, tissue remodeling, and metastatic potential. This review summarizes the spatial distribution of macrophages in both the physiological environment and the TME. Moreover, this paper explores the intricate interactions between TAMs and diverse immune cell populations (T cells, dendritic cells, neutrophils, natural killer cells, and other immune cells) within the TME. These bidirectional exchanges form a complex network of immune interactions that influence tumor immune surveillance and evasion strategies. Investigating TAM heterogeneity and its intricate interactions with different immune cell populations offers potential avenues for therapeutic interventions. Additionally, this paper discusses therapeutic strategies targeting macrophages, aiming to uncover novel approaches for immunotherapy. Video Abstract.
Collapse
Affiliation(s)
- Shuai Ji
- Department of Urinary Surgery, The Shengjing Hospital of China Medical University, Shenyang, 110022, China
| | - Yuqing Shi
- Department of Respiratory Medicine, Shenyang 10th People's Hospital, Shenyang, 110096, China
| | - Bo Yin
- Department of Urinary Surgery, The Shengjing Hospital of China Medical University, Shenyang, 110022, China.
| |
Collapse
|
14
|
Yang G, Cai S, Hu M, Li C, Yang L, Zhang W, Sun J, Sun F, Xing L, Sun X. Spatial features of specific CD103 +CD8 + tissue-resident memory T cell subsets define the prognosis in patients with non-small cell lung cancer. J Transl Med 2024; 22:27. [PMID: 38183111 PMCID: PMC10770937 DOI: 10.1186/s12967-023-04839-4] [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: 08/09/2023] [Accepted: 12/26/2023] [Indexed: 01/07/2024] Open
Abstract
BACKGROUND Tissue-resident memory T (TRM) cells can reside in the tumor microenvironment and are considered the primary response cells to immunotherapy. Heterogeneity in functional status and spatial distribution may contribute to the controversial role of TRM cells but we know little about it. METHODS Through multiplex immunofluorescence (mIF) (CD8, CD103, PD-1, Tim-3, GZMB, CK), the quantity and spatial location of TRM cell subsets were recognized in the tissue from 274 patients with NSCLC after radical surgery. By integrating multiple machine learning methods, we constructed a TRM-based spatial immune signature (TRM-SIS) to predict the prognosis. Furthermore, we conducted a CD103-related gene set enrichment analysis (GSEA) and verified its finding by another mIF panel (CD8, CD103, CK, CD31, Hif-1α). RESULTS The density of TRM cells was significantly correlated with the expression of PD-1, Tim-3 and GZMB. Four types of TRM cell subsets was defined, including TRM1 (PD-1-Tim-3-TRM), TRM2 (PD-1+Tim-3-TRM), TRM3 (PD-1-Tim-3+TRM) and TRM4 (PD-1+Tim-3+TRM). The cytotoxicity of TRM2 was the strongest while that of TRM4 was the weakest. Compare with TRM1 and TRM2, TRM3 and TRM4 had better infiltration and stronger interaction with cancer cells. The TRM-SIS was an independent prognostic factor for disease-free survival [HR = 2.43, 95%CI (1.63-3.60), P < 0.001] and showed a better performance than the TNM staging system for recurrence prediction. Furthermore, by CD103-related GSEA and mIF validation, we found a negative association between tumor angiogenesis and infiltration of TRM cells. CONCLUSIONS These findings reveal a significant heterogeneity in the functional status and spatial distribution of TRM cells, and support it as a biomarker for the prognosis of NSCLC patients. Regulating TRM cells by targeting tumor angiogenesis may be a potential strategy to improve current immunotherapy.
Collapse
Affiliation(s)
- Guanqun Yang
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Siqi Cai
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Mengyu Hu
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Chaozhuo Li
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
- School of Clinical Medicine, Weifang Medical University, Weifang, Shandong, China
| | - Liying Yang
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Wei Zhang
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Jujie Sun
- Department of Pathology, Shandong Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, Shandong, China
| | - Fenghao Sun
- Department of Nuclear Medicine, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Ligang Xing
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Xiaorong Sun
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China.
- Department of Nuclear Medicine, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China.
| |
Collapse
|
15
|
Zhao B, Yao L, Ma W. Combined cytotoxic and immune-stimulatory gene therapy for glioma. Lancet Oncol 2023; 24:e455. [PMID: 38039997 DOI: 10.1016/s1470-2045(23)00507-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 09/23/2023] [Accepted: 09/25/2023] [Indexed: 12/03/2023]
Affiliation(s)
- Binghao Zhao
- DKTK Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center, Heidelberg 69120, Germany.
| | - Longping Yao
- Department of Neuroanatomy, Group for Regeneration and Reprogramming, Institute for Anatomy and Cell Biology, Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Wenbin Ma
- Department of Neurosurgery and State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| |
Collapse
|
16
|
Zhang H, Jiang X, Ren F, Gu Q, Yao J, Wang X, Zou S, Gan Y, Gu J, Xu Y, Wang Z, Liu S, Wang X, Wei B. Development and external validation of dual online tools for prognostic assessment in elderly patients with high-grade glioma: a comprehensive study using SEER and Chinese cohorts. Front Endocrinol (Lausanne) 2023; 14:1307256. [PMID: 38075045 PMCID: PMC10702965 DOI: 10.3389/fendo.2023.1307256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 11/07/2023] [Indexed: 12/18/2023] Open
Abstract
Background Elderly individuals diagnosed with high-grade gliomas frequently experience unfavorable outcomes. We aimed to design two web-based instruments for prognosis to predict overall survival (OS) and cancer-specific survival (CSS), assisting clinical decision-making. Methods We scrutinized data from the SEER database on 5,245 elderly patients diagnosed with high-grade glioma between 2000-2020, segmenting them into training (3,672) and validation (1,573) subsets. An additional external validation cohort was obtained from our institution. Prognostic determinants were pinpointed using Cox regression analyses, which facilitated the construction of the nomogram. The nomogram's predictive precision for OS and CSS was gauged using calibration and ROC curves, the C-index, and decision curve analysis (DCA). Based on risk scores, patients were stratified into high or low-risk categories, and survival disparities were explored. Results Using multivariate Cox regression, we identified several prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in elderly patients with high-grade gliomas, including age, tumor location, size, surgical technique, and therapies. Two digital nomograms were formulated anchored on these determinants. For OS, the C-index values in the training, internal, and external validation cohorts were 0.734, 0.729, and 0.701, respectively. We also derived AUC values for 3-, 6-, and 12-month periods. For CSS, the C-index values for the training and validation groups were 0.733 and 0.727, with analogous AUC metrics. The efficacy and clinical relevance of the nomograms were corroborated via ROC curves, calibration plots, and DCA for both cohorts. Conclusion Our investigation pinpointed pivotal risk factors in elderly glioma patients, leading to the development of an instrumental prognostic nomogram for OS and CSS. This instrument offers invaluable insights to optimize treatment strategies.
Collapse
Affiliation(s)
- Hongyu Zhang
- Department of Neurosurgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xinzhan Jiang
- Department of Neurobiology, Harbin Medical University, Harbin, China
| | - Fubin Ren
- Department of Neurosurgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Qiang Gu
- Department of Neurosurgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jiahao Yao
- Department of Neurosurgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xinyu Wang
- Department of Neurosurgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Shuhuai Zou
- Department of Neurosurgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yifan Gan
- Department of Neurosurgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jianheng Gu
- Department of Neurosurgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yongji Xu
- Department of Neurosurgery, Hulin People’s Hospital, Jixi, Heilongjiang, China
| | - Zhao Wang
- Department of Orthopaedic Surgery, Chungnam National University School of Medicine, Daejeon, Republic of Korea
| | - Shuang Liu
- Department of Neurosurgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xuefeng Wang
- Department of Neurosurgery, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Baojian Wei
- School of Nursing, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China
| |
Collapse
|
17
|
Meira DD, de Castro e Caetano MC, Casotti MC, Zetum ASS, Gonçalves AFM, Moreira AR, de Oliveira AH, Pesente F, Santana GM, de Almeida Duque D, Pereira GSC, de Castro GDSC, Pavan IP, Chagas JPS, Bourguignon JHB, de Oliveira JR, Barbosa KRM, Altoé LSC, Louro LS, Merigueti LP, Alves LNR, Machado MRR, Roque MLRO, Prates PS, de Paula Segáua SH, dos Santos Uchiya T, Louro TES, Daleprane VE, Guaitolini YM, Vicente CR, dos Reis Trabach RS, de Araújo BC, dos Santos EDVW, de Paula F, Lopes TJS, de Carvalho EF, Louro ID. Prognostic Factors and Markers in Non-Small Cell Lung Cancer: Recent Progress and Future Challenges. Genes (Basel) 2023; 14:1906. [PMID: 37895255 PMCID: PMC10606762 DOI: 10.3390/genes14101906] [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: 09/01/2023] [Revised: 09/29/2023] [Accepted: 10/01/2023] [Indexed: 10/29/2023] Open
Abstract
Lung cancer is a highly aggressive neoplasm and, despite the development of recent therapies, tumor progression and recurrence following the initial response remains unsolved. Several questions remain unanswered about non-small cell lung cancer (NSCLC): (1) Which patients will actually benefit from therapy? (2) What are the predictive factors of response to MAbs and TKIs? (3) What are the best combination strategies with conventional treatments or new antineoplastic drugs? To answer these questions, an integrative literature review was carried out, searching articles in PUBMED, NCBI-PMC, Google Academic, and others. Here, we will examine the molecular genetics of lung cancer, emphasizing NSCLC, and delineate the primary categories of inhibitors based on their molecular targets, alongside the main treatment alternatives depending on the type of acquired resistance. We highlighted new therapies based on epigenetic information and a single-cell approach as a potential source of new biomarkers. The current and future of NSCLC management hinges upon genotyping correct prognostic markers, as well as on the evolution of precision medicine, which guarantees a tailored drug combination with precise targeting.
Collapse
Affiliation(s)
- Débora Dummer Meira
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Maria Clara de Castro e Caetano
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Matheus Correia Casotti
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Aléxia Stefani Siqueira Zetum
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - André Felipe Monteiro Gonçalves
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - André Rodrigues Moreira
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Augusto Henrique de Oliveira
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Fellipe Pesente
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Gabriel Mendonça Santana
- Centro de Ciências da Saúde, Curso de Medicina, Universidade Federal do Espírito Santo (UFES), Vitória 29090-040, Brazil
| | - Daniel de Almeida Duque
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Gierleson Santos Cangussu Pereira
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Giulia de Souza Cupertino de Castro
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Isabele Pagani Pavan
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - João Pedro Sarcinelli Chagas
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - José Henrique Borges Bourguignon
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Juliana Ribeiro de Oliveira
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Karen Ruth Michio Barbosa
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Lorena Souza Castro Altoé
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Luana Santos Louro
- Centro de Ciências da Saúde, Curso de Medicina, Universidade Federal do Espírito Santo (UFES), Vitória 29090-040, Brazil
| | - Luiza Poppe Merigueti
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Lyvia Neves Rebello Alves
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Marlon Ramos Rosado Machado
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Maria Luísa Rodrigues Oliveira Roque
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Pedro Santana Prates
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Sayuri Honorio de Paula Segáua
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Taissa dos Santos Uchiya
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Thomas Erik Santos Louro
- Escola Superior de Ciências da Santa Casa de Misericórdia de Vitória (EMESCAM), Curso de Medicina, Vitória 29027-502, Brazil
| | - Vinicius Eduardo Daleprane
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Yasmin Moreto Guaitolini
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Creuza Rachel Vicente
- Departamento de Medicina Social, Universidade Federal do Espírito Santo, Vitória 29090-040, Brazil
| | - Raquel Silva dos Reis Trabach
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Bruno Cancian de Araújo
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Eldamária de Vargas Wolfgramm dos Santos
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Flávia de Paula
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| | - Tiago José S. Lopes
- Department of Reproductive Biology, National Center for Child Health and Development Research Institute, Tokyo 157-8535, Japan
| | - Elizeu Fagundes de Carvalho
- Instituto de Biologia Roberto Alcântara Gomes (IBRAG), Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro 20551-030, Brazil
| | - Iúri Drumond Louro
- Núcleo de Genética Humana e Molecular, Centro de Ciências Humanas e Naturais, Departamento de Ciências Biológicas, Universidade Federal do Espírito Santo (UFES), Vitória 29075-910, Brazil (M.C.C.)
| |
Collapse
|
18
|
Guo W, Zhou B, Bie F, Huai Q, Xue X, Guo L, Tan F, Xue Q, Zhao L, Gao S. Single-cell RNA sequencing analysis reveals transcriptional heterogeneity of multiple primary lung cancer. Clin Transl Med 2023; 13:e1453. [PMID: 37846760 PMCID: PMC10580343 DOI: 10.1002/ctm2.1453] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 09/26/2023] [Accepted: 10/05/2023] [Indexed: 10/18/2023] Open
Abstract
INTRODUCTION With the advancements in early diagnosis, more and more patients with multiple primary lung cancer (MPLC) have been identified. However, the progression of MPLC involves complex changes in cell composition and metabolic function, which remains largely controversial. OBJECTIVE Our study aims to comprehensively reveal the cellular characteristics and inter-cellular connections of MPLC. METHODS We performed scRNA-seq from 23 samples of six MPLC patients, combined with bulk whole-exome sequencing. We performed trajectory analysis to investigate the transition of different cell types during the development of MPLC. RESULTS A total of 1 67 397 cells were sequenced derived from tumour and adjacent tissues of MPLC patients, and tumour, normal, immune and stromal cells were identified. Two states of epithelial cells were identified, which were associated with immune response and cell death, respectively. Furthermore, both CD8+ naïve and memory T cells participated in the differentiation of CD8+ T cells. The terminal states of CD8+ T cells were exhausted T cells and cytotoxic T cells, which positively regulated cell death and were implicated in the regulation of cytokine production, respectively. Two main subpopulations of B cells with distinct functions were identified, which participate in the regulation of the immune response and antigen presentation, respectively. In addition, we found a specific type of endothelial cells that were abundant in tumour samples, with an increasing trend from normal to tumour samples. CONCLUSIONS Our study showed the comprehensive landscape of different cells of MPLC, which might reveal the key cellular mechanisms and, therefore, may provide new insights into the early diagnosis and treatment of MPLC.
Collapse
Affiliation(s)
- Wei Guo
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingP. R. China
- Key Laboratory of Minimally Invasive Therapy Research for Lung CancerChinese Academy of Medical SciencesBeijingP. R. China
| | - Bolun Zhou
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingP. R. China
| | - Fenglong Bie
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingP. R. China
- Department of Thoracic SurgeryShandong Provincial Hospital Affiliated to Shandong First Medical UniversityJinanShandongP. R. China
| | - Qilin Huai
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingP. R. China
| | - Xuemin Xue
- Department of PathologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingP. R. China
| | - Lei Guo
- Department of PathologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingP. R. China
| | - Fengwei Tan
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingP. R. China
- Key Laboratory of Minimally Invasive Therapy Research for Lung CancerChinese Academy of Medical SciencesBeijingP. R. China
| | - Qi Xue
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingP. R. China
- Key Laboratory of Minimally Invasive Therapy Research for Lung CancerChinese Academy of Medical SciencesBeijingP. R. China
| | - Liang Zhao
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingP. R. China
| | - Shugeng Gao
- Department of Thoracic SurgeryNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingP. R. China
- Key Laboratory of Minimally Invasive Therapy Research for Lung CancerChinese Academy of Medical SciencesBeijingP. R. China
| |
Collapse
|
19
|
Zhang L, Cheng L, Chen Z, Fang Y, Li C, Chen M, He P, Wu H, Wu J, Chen J. Chemical modification of curcumin increases its potency against hypopharyngeal carcinoma. J Drug Target 2023; 31:867-877. [PMID: 37577780 DOI: 10.1080/1061186x.2023.2247581] [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: 05/08/2023] [Revised: 07/03/2023] [Accepted: 08/06/2023] [Indexed: 08/15/2023]
Abstract
Hypopharyngeal carcinoma is notorious for its poor prognosis among all head and neck cancers, posing a persistent challenge in clinical settings. The continuous hyperactivation of the NFκB signalling pathway has been noted in various cancer types, including hypopharyngeal carcinoma. In our quest to develop a novel drug that targets hypopharyngeal cancer via the NFκB pathway, we employed curcumin, a well-known lead compound, and performed chemical modifications to create a mono-carbonyl analogue called L42H17. This compound exhibited exceptional stability and displayed an enhanced binding affinity to myeloid differentiation protein 2 (MD2). Consistent with expectations, L42H17 demonstrated the ability to inhibit TNF-α-induced phosphorylation of inhibitor of κB (IκB) kinase (IKK), prevent IκB degradation, and subsequently impede NFκB-p65 nuclear translocation in hypopharyngeal cancer cells. Additionally, L42H17 exhibited a remarkable capacity to induce cell cycle arrest at the G2-M phase by inactivating the cdc2-cyclin B1 complex. Moreover, it facilitated cell apoptosis by reducing Bcl-2 levels and augmenting the expression of cle-PARP and cle-caspase3. Importantly, we observed a significant enhancement in the anti-cancer efficacy of L42H17 in a patient-derived tumour xenograft (PDTX) model of hypopharyngeal carcinoma. In conclusion, our findings strongly suggest that L42H17 holds promise as a potential candidate drug for the treatment of hypopharyngeal carcinoma in the future.
Collapse
Affiliation(s)
- Linlin Zhang
- Shanghai Minhang District Dental Clinic, Shanghai, China
| | - Lei Cheng
- ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Zhemeng Chen
- ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Yi Fang
- ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Changjiang Li
- ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Min Chen
- ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Peijie He
- ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Haitao Wu
- ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China
| | - Jianzhang Wu
- School of Ophthalmology & Optometry, The Eye Hospital, Wenzhou Medical University, Wenzhou, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, China
| | - Jian Chen
- ENT Institute and Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China
| |
Collapse
|
20
|
Peng H, Wu X, Liu S, He M, Tang C, Wen Y, Xie C, Zhong R, Li C, Xiong S, Liu J, Zheng H, He J, Lu X, Liang W. Cellular dynamics in tumour microenvironment along with lung cancer progression underscore spatial and evolutionary heterogeneity of neutrophil. Clin Transl Med 2023; 13:e1340. [PMID: 37491740 PMCID: PMC10368809 DOI: 10.1002/ctm2.1340] [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: 04/13/2023] [Revised: 06/21/2023] [Accepted: 07/12/2023] [Indexed: 07/27/2023] Open
Abstract
BACKGROUND The cellular dynamics in the tumour microenvironment (TME) along with non-small cell lung cancer (NSCLC) progression remain unclear. METHODS Multiplex immunofluorescence test detecting 10 immune-related markers on 553 primary tumour (PT) samples of NSCLC was conducted and spatial information in TME was assessed by the StarDist depth learning model. The single-cell transcriptomic atlas of PT (n = 4) and paired tumour-draining lymph nodes (TDLNs) (n = 5 for tumour-invaded, n = 3 for tumour-free) microenvironment was profiled. Various bioinformatics analyses based on Gene Expression Omnibus, TCGA and Array-Express databases were also used to validate the discoveries. RESULTS Spatial distances of CD4+ T cells-CD38+ T cells, CD4+ T cells-neutrophils and CD38+ T cells-neutrophils prolonged and they were replaced by CD163+ macrophages in PT along with tumour progression. Neutrophils showed unique stage and location-dependent prognostic effects. A high abundance of stromal neutrophils improved disease-free survival in the early-stage, whereas high intratumoural neutrophil infiltrates predicted poor prognosis in the mid-to-late-stage. Significant molecular and functional reprogramming in PT and TDLN microenvironments was observed. Diverse interaction networks mediated by neutrophils were found between positive and negative TDLNs. Five phenotypically and functionally heterogeneous subtypes of tumour-associated neutrophil (TAN) were further identified by pseudotime analysis, including TAN-0 with antigen-presenting function, TAN-1 with strong expression of interferon (IFN)-stimulated genes, the pro-tumour TAN-2 subcluster, the classical subset (TAN-3) and the pro-inflammatory subtype (TAN-4). Loss of IFN-stimulated signature and growing angiogenesis activity were discovered along the transitional trajectory. Eventually, a robust six neutrophil differentiation relevant genes-based model was established, showing that low-risk patients had longer overall survival time and may respond better to immunotherapy. CONCLUSIONS The cellular composition, spatial location, molecular and functional changes in PT and TDLN microenvironments along with NSCLC progression were deciphered, highlighting the immunoregulatory roles and evolutionary heterogeneity of TANs.
Collapse
Affiliation(s)
- Haoxin Peng
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
- Deparment of Clinical MedicineNanshan SchoolGuangzhou Medical UniversityGuangzhouChina
- Department of OncologyPeking University Cancer Hospital & InstitutePeking University Health Science Center, Peking UniversityBeijingChina
| | - Xiangrong Wu
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
- Deparment of Clinical MedicineNanshan SchoolGuangzhou Medical UniversityGuangzhouChina
- Department of OncologyShanghai Medical College, Fudan UniversityShanghaiChina
| | - Shaopeng Liu
- Department of Computer ScienceGuangdong Polytechnic Normal UniversityGuangzhouChina
- Department of Artificial Intelligence ResearchPazhou LabGuangzhouChina
| | - Miao He
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
- Deparment of Clinical MedicineNanshan SchoolGuangzhou Medical UniversityGuangzhouChina
| | - Chenshuo Tang
- Department of Computer ScienceGuangdong Polytechnic Normal UniversityGuangzhouChina
| | - Yaokai Wen
- Deparment of Clinical MedicineTongji UniversityShanghaiChina
- Department of Medical OncologyShanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University, School of MedicineShanghaiChina
| | - Chao Xie
- Department of Computer ScienceGuangdong Polytechnic Normal UniversityGuangzhouChina
| | - Ran Zhong
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Caichen Li
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Shan Xiong
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Jun Liu
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Hongbo Zheng
- Medical DepartmentGenecast Biotechnology Co., LtdBeijingChina
| | - Jianxing He
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
| | - Xu Lu
- Department of Computer ScienceGuangdong Polytechnic Normal UniversityGuangzhouChina
- Department of Artificial Intelligence ResearchPazhou LabGuangzhouChina
| | - Wenhua Liang
- Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhouChina
- Department of Medical OncologyThe First People's Hospital of ZhaoqingZhaoqingChina
| |
Collapse
|
21
|
Yang G, Cai S, Hu M, Li C, Yang L, Zhang W, Sun J, Sun F, Xing L, Sun X. Functional status and spatial architecture of tumor-infiltrating CD8+ T cells are associated with lymph node metastases in non-small cell lung cancer. J Transl Med 2023; 21:320. [PMID: 37173705 PMCID: PMC10182600 DOI: 10.1186/s12967-023-04154-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 04/25/2023] [Indexed: 05/15/2023] Open
Abstract
BACKGROUND Anti-PD-(L)1 immunotherapy has been recommended for non-small cell lung cancer (NSCLC) patients with lymph node metastases (LNM). However, the exact functional feature and spatial architecture of tumor-infiltrating CD8 + T cells remain unclear in these patients. METHODS Tissue microarrays (TMAs) from 279 IA-IIIB NSCLC samples were stained by multiplex immunofluorescence (mIF) for 11 markers (CD8, CD103, PD-1, Tim3, GZMB, CD4, Foxp3, CD31, αSMA, Hif-1α, pan-CK). We evaluated the density of CD8 + T-cell functional subsets, the mean nearest neighbor distance (mNND) between CD8 + T cells and neighboring cells, and the cancer-cell proximity score (CCPS) in invasive margin (IM) as well as tumor center (TC) to investigate their relationships with LNM and prognosis. RESULTS The densities of CD8 + T-cell functional subsets, including predysfunctional CD8 + T cells (Tpredys) and dysfunctional CD8 + T cells (Tdys), in IM predominated over those in TC (P < 0.001). Multivariate analysis identified that the densities of CD8 + Tpredys cells in TC and CD8 + Tdys cells in IM were significantly associated with LNM [OR = 0.51, 95%CI (0.29-0.88), P = 0.015; OR = 5.80, 95%CI (3.19-10.54), P < 0.001; respectively] and recurrence-free survival (RFS) [HR = 0.55, 95%CI (0.34-0.89), P = 0.014; HR = 2.49, 95%CI (1.60-4.13), P = 0.012; respectively], independent of clinicopathological factors. Additionally, shorter mNND between CD8 + T cells and their neighboring immunoregulatory cells indicated a stronger interplay network in the microenvironment of NSCLC patients with LNM and was associated with worse prognosis. Furthermore, analysis of CCPS suggested that cancer microvessels (CMVs) and cancer-associated fibroblasts (CAFs) selectively hindered CD8 + T cells from contacting with cancer cells, and were associated with the dysfunction of CD8 + T cells. CONCLUSION Tumor-infiltrating CD8 + T cells were in a more dysfunctional status and in a more immunosuppressive microenvironment in patients with LNM compared with those without LNM.
Collapse
Affiliation(s)
- Guanqun Yang
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Siqi Cai
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Mengyu Hu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Chaozhuo Li
- School of Clinical Medicine, Weifang Medical University, Weifang, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Liying Yang
- Shandong Cancer Hospital and Institute and Shandong Academy of Medical Science, Jinan, Shandong, China
| | - Wei Zhang
- Shandong Cancer Hospital and Institute and Shandong Academy of Medical Science, Jinan, Shandong, China
| | - Jujie Sun
- Department of Pathology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, Shandong, China
| | - Fenghao Sun
- Department of Nuclear Medicine, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, No.440, Jiyan Road, Huaiyin District, Jinan, 250117, Shandong, China
| | - Ligang Xing
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Xiaorong Sun
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China.
- Department of Nuclear Medicine, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital and Institute, No.440, Jiyan Road, Huaiyin District, Jinan, 250117, Shandong, China.
| |
Collapse
|
22
|
Wang P, Wang S, Sun Z, Li H, Zhao Y, Li Y, Yang F, Wang J, Chen K, Qiu M, Li X. Systemic inflammation influences the prognosis of patients with radically resected non-small cell lung cancer and correlates with the immunosuppressive microenvironment. Int J Cancer 2023. [PMID: 37186387 DOI: 10.1002/ijc.34547] [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: 01/03/2023] [Revised: 03/27/2023] [Accepted: 04/11/2023] [Indexed: 05/17/2023]
Abstract
The impact of host condition on prognosis of non-small cell lung cancer (NSCLC) and the interaction between host and NSCLC remain unclear. This study investigated the association between systemic inflammation and prognosis and characteristics of radically resected NSCLC. This study consisted of a cohort study and an exploratory study of institutional prospective databases. All participants underwent video-assisted thoracoscopic lobectomy as the primary treatment. Systemic inflammation was assessed before surgery using the advanced lung cancer inflammation index and the systemic inflammation response index. Next-generation sequencing and multiplex immunofluorescence analysis were conducted to delineate tumor characteristics. In the cohort study including 1507 participants, high inflammation was associated with poor disease-free survival and overall survival before and after propensity score matching and in multivariable analysis. Systemic inflammation showed good prognostic value for stage IA-IB NSCLC, and the prognostic value diminished with upstaging of NSCLC. In the exploratory study including 217 adenocarcinomas, tumor microenvironment of high inflammation group showed a greater abundance of PDL1+ tumor cells and immune cells, which were independent from driver gene mutations and clinicopathological characteristics. Spatial analysis demonstrated a higher frequency of immune-suppressed cellular neighborhood, increased avoidance between immune cells and PDL1- tumor cells and compromised immune killing and presentation in tumor microenvironment of high inflammation group. Systemic inflammation showed limited association with genomic mutations. Systemic inflammation may influence the prognosis of NSCLC at both the systematic level and the local immune response. The correlation between high inflammation and immunosuppressive microenvironment indicates a novel thread for anticancer treatment.
Collapse
Affiliation(s)
- Peiyu Wang
- Thoracic Oncology Institute/Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Shaodong Wang
- Thoracic Oncology Institute/Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Zewen Sun
- Thoracic Oncology Institute/Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Hao Li
- Thoracic Oncology Institute/Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Yaxing Zhao
- Infinity Scope Biotechnology Co. Ltd., Hangzhou, China
| | - Yun Li
- Thoracic Oncology Institute/Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Fan Yang
- Thoracic Oncology Institute/Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Jun Wang
- Thoracic Oncology Institute/Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Kezhong Chen
- Thoracic Oncology Institute/Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Mantang Qiu
- Thoracic Oncology Institute/Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| | - Xiao Li
- Thoracic Oncology Institute/Department of Thoracic Surgery, Peking University People's Hospital, Beijing, China
| |
Collapse
|
23
|
Xue Q, Peng W, Zhang S, Wei X, Ye L, Wang Z, Xiang X, Zhang P, Zhou Q. Promising immunotherapeutic targets in lung cancer based on single-cell RNA sequencing. Front Immunol 2023; 14:1148061. [PMID: 37187731 PMCID: PMC10175686 DOI: 10.3389/fimmu.2023.1148061] [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: 01/19/2023] [Accepted: 04/17/2023] [Indexed: 05/17/2023] Open
Abstract
Immunotherapy has made great strides in the treatment of lung cancer, but a significant proportion of patients still do not respond to treatment. Therefore, the identification of novel targets is crucial to improving the response to immunotherapy. The tumor microenvironment (TME) is a complex niche composed of diverse pro-tumor molecules and cell populations, making the function and mechanism of a unique cell subset difficult to understand. However, the advent of single-cell RNA sequencing (scRNA-seq) technology has made it possible to identify cellular markers and understand their potential functions and mechanisms in the TME. In this review, we highlight recent advances emerging from scRNA-seq studies in lung cancer, with a particular focus on stromal cells. We elucidate the cellular developmental trajectory, phenotypic remodeling, and cell interactions during tumor progression. Our review proposes predictive biomarkers and novel targets for lung cancer immunotherapy based on cellular markers identified through scRNA-seq. The identification of novel targets could help improve the response to immunotherapy. The use of scRNA-seq technology could provide new strategies to understand the TME and develop personalized immunotherapy for lung cancer patients.
Collapse
|