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Gulati GS, D'Silva JP, Liu Y, Wang L, Newman AM. Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics. Nat Rev Mol Cell Biol 2024:10.1038/s41580-024-00768-2. [PMID: 39169166 DOI: 10.1038/s41580-024-00768-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/16/2024] [Indexed: 08/23/2024]
Abstract
Single-cell transcriptomics has broadened our understanding of cellular diversity and gene expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has emerged as a tool to contextualize single cells in multicellular neighbourhoods and to identify spatially recurrent phenotypes, or ecotypes. These technologies have generated vast datasets with targeted-transcriptome and whole-transcriptome profiles of hundreds to millions of cells. Such data have provided new insights into developmental hierarchies, cellular plasticity and diverse tissue microenvironments, and spurred a burst of innovation in computational methods for single-cell analysis. In this Review, we discuss recent advancements, ongoing challenges and prospects in identifying and characterizing cell states and multicellular neighbourhoods. We discuss recent progress in sample processing, data integration, identification of subtle cell states, trajectory modelling, deconvolution and spatial analysis. Furthermore, we discuss the increasing application of deep learning, including foundation models, in analysing single-cell and spatial transcriptomics data. Finally, we discuss recent applications of these tools in the fields of stem cell biology, immunology, and tumour biology, and the future of single-cell and spatial transcriptomics in biological research and its translation to the clinic.
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Affiliation(s)
- Gunsagar S Gulati
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - Yunhe Liu
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Linghua Wang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, TX, USA
| | - Aaron M Newman
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
- Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA.
- Stanford Cancer Institute, Stanford University, Stanford, CA, USA.
- Chan Zuckerberg Biohub - San Francisco, San Francisco, CA, USA.
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2
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Cho Y, Doh J. The extracellular matrix in solid tumor immunotherapy. Trends Immunol 2024:S1471-4906(24)00184-4. [PMID: 39164157 DOI: 10.1016/j.it.2024.07.009] [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: 07/03/2024] [Revised: 07/26/2024] [Accepted: 07/26/2024] [Indexed: 08/22/2024]
Abstract
The extracellular matrix (ECM) of solid tumors impacts the antitumor activities of CD8+ T and natural killer (NK) cells in a variety of ways. Cell motility is restricted by the tumor ECM which creates physical barriers. The tumor ECM directly alter the phenotypes and functions of cytotoxic lymphocytes, and indirectly influences immunological synapse-mediated interactions between cytotoxic lymphocytes and cancer cells. Therefore, strategies to improve solid tumor immunotherapy should be established by considering complex ternary interactions between cytotoxic lymphocytes, cancer cells, and the tumor ECM. Novel bioengineering tools approximating key characteristics of the tumor ECM, such as in vitro reconstituted 3D ECMs and microfluidics are valuable from a fundamental study viewpoint and from a translational perspective, aiming to enable systematic screening approaches.
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Affiliation(s)
- Yongbum Cho
- Research Institute of Advanced Materials (RIAM), Seoul National University, Seoul, South Korea
| | - Junsang Doh
- Research Institute of Advanced Materials (RIAM), Seoul National University, Seoul, South Korea; Department of Materials Science and Engineering, Institute of Engineering Research, BioMAX, Soft Foundry Institute, Seoul National University, Seoul, South Korea.
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3
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Shaikh S, Dhar H, Moorthy M, Bhat V, Basu S, Banerjee D, Mishra DK, Datta S, Mukherjee G. The spatial distribution of intermediate fibroblasts and myeloid-derived cells dictate lymph node metastasis dynamics in oral cancer. J Transl Med 2024; 22:759. [PMID: 39138492 PMCID: PMC11323585 DOI: 10.1186/s12967-024-05511-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 07/15/2024] [Indexed: 08/15/2024] Open
Abstract
BACKGROUND Oral cancer poses a significant health challenge due to limited treatment protocols and therapeutic targets. We aimed to investigate the invasive margins of gingivo-buccal oral squamous cell carcinoma (GB-OSCC) tumors in terms of the localization of genes and cell types within the margins at various distances that could lead to nodal metastasis. METHODS We collected tumor tissues from 23 resected GB-OSCC samples for gene expression profiling using digital spatial transcriptomics. We monitored differential gene expression at varying distances between the tumor and its microenvironvent (TME), and performed a deconvulation study and immunohistochemistry to identify the cells and genes regulating the TME. RESULTS We found that the tumor-stromal interface (a distance up to 200 µm between tumor and immune cells) is the most active region for disease progression in GB-OSCC. The most differentially expressed apex genes, such as FN1 and COL5A1, were located at the stromal ends of the margins, and together with enrichment of the extracellular matrix (ECM) and an immune-suppressed microenvironment, were associated with lymph node metastasis. Intermediate fibroblasts, myocytes, and neutrophils were enriched at the tumor ends, while cancer-associated fibroblasts (CAFs) were enriched at the stromal ends. The intermediate fibroblasts transformed into CAFs and relocated to the adjacent stromal ends where they participated in FN1-mediated ECM modulation. CONCLUSION We have generated a functional organization of the tumor-stromal interface in GB-OSCC and identified spatially located genes that contribute to nodal metastasis and disease progression. Our dataset might now be mined to discover suitable molecular targets in oral cancer.
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Affiliation(s)
- Soni Shaikh
- Tata Medical Center, 14 MAR (E-W), New Town, Rajarhat, Kolkata, WB, 700160, India
- Tata Consultancy Services (TCS), Kolkata, WB, India
| | - Harsh Dhar
- Medica Superspecialty Hospital, 127, Eastern Metropolitan Bypass, Nitai Nagar, Mukundapur, Kolkata, WB, 700099, India
| | - Manju Moorthy
- theraCUES Innovations Pvt Ltd., Bangalore, Karnataka, 560092, India
| | | | - Sangramjit Basu
- Tata Translational Cancer Research Centre (TTCRC), 14 MAR (E-W), New Town, Rajarhat, Kolkata, WB, 700160, India
| | - Devmalya Banerjee
- Narayana Superspeciality Hospital, 120, 1, Andul Rd, Shibpur, Howrah, WB, 711103, India
| | - Deepak Kumar Mishra
- Tata Medical Center, 14 MAR (E-W), New Town, Rajarhat, Kolkata, WB, 700160, India
| | - Sourav Datta
- Medica Superspecialty Hospital, 127, Eastern Metropolitan Bypass, Nitai Nagar, Mukundapur, Kolkata, WB, 700099, India.
| | - Geetashree Mukherjee
- Tata Medical Center, 14 MAR (E-W), New Town, Rajarhat, Kolkata, WB, 700160, India.
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4
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Ren F, Wang L, Wang Y, Wang J, Wang Y, Song X, Zhang G, Nie F, Lin S. Single-cell transcriptome profiles the heterogeneity of tumor cells and microenvironments for different pathological endometrial cancer and identifies specific sensitive drugs. Cell Death Dis 2024; 15:571. [PMID: 39112478 PMCID: PMC11306564 DOI: 10.1038/s41419-024-06960-8] [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: 04/16/2024] [Revised: 07/23/2024] [Accepted: 07/29/2024] [Indexed: 08/10/2024]
Abstract
Endometrial cancer (EC) is a highly heterogeneous malignancy characterized by varied pathology and prognoses, and the heterogeneity of its cancer cells and the tumor microenvironment (TME) remains poorly understood. We conducted single-cell RNA sequencing (scRNA-seq) on 18 EC samples, encompassing various pathological types to delineate their specific unique transcriptional landscapes. Cancer cells from diverse pathological sources displayed distinct hallmarks labeled as immune-modulating, proliferation-modulating, and metabolism-modulating cancer cells in uterine clear cell carcinomas (UCCC), well-differentiated endometrioid endometrial carcinomas (EEC-I), and uterine serous carcinomas (USC), respectively. Cancer cells from the UCCC exhibited the greatest heterogeneity. We also identified potential effective drugs and confirmed their effectiveness using patient-derived EC organoids for each pathological group. Regarding the TME, we observed that prognostically favorable CD8+ Tcyto and NK cells were prominent in normal endometrium, whereas CD4+ Treg, CD4+ Tex, and CD8+ Tex cells dominated the tumors. CXCL3+ macrophages associated with M2 signature and angiogenesis were exclusively found in tumors. Prognostically relevant epithelium-specific cancer-associated fibroblasts (eCAFs) and SOD2+ inflammatory CAFs (iCAFs) predominated in EEC-I and UCCC groups, respectively. We also validated the oncogenic effects of SOD2+ iCAFs in vitro. Our comprehensive study has yielded deeper insights into the pathogenesis of EC, potentially facilitating personalized treatments for its varied pathological types.
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Affiliation(s)
- Fang Ren
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
| | - Lingfang Wang
- Zhejiang Provincial Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuyouye Wang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Jiaxuan Wang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yuanpei Wang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Xiaole Song
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Gong Zhang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Fangfang Nie
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Shitong Lin
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
- Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jiefang Avenue, 430022, Wuhan, Hubei, PR China.
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5
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Guo B, Ling W, Kwon SH, Panwar P, Ghazanfar S, Martinowich K, Hicks SC. Integrating spatially-resolved transcriptomics data across tissues and individuals: challenges and opportunities. ARXIV 2024:arXiv:2408.00367v1. [PMID: 39130195 PMCID: PMC11312629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. As the cost of generating these data decreases, these technologies provide an exciting opportunity to create large-scale atlases that integrate SRT data across multiple tissues, individuals, species, or phenotypes to perform population-level analyses. Here, we describe unique challenges of varying spatial resolutions in SRT data, as well as highlight the opportunities for standardized preprocessing methods along with computational algorithms amenable to atlas-scale datasets leading to improved sensitivity and reproducibility in the future.
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Affiliation(s)
- Boyi Guo
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Wodan Ling
- Division of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, NY, USA
| | - Sang Ho Kwon
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Biochemistry, Cellular, and Molecular Biology Graduate Program, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Pratibha Panwar
- School of Mathematics and Statistics, The University of Sydney, NSW 2006, Australia
- Sydney Precision Data Science Centre, University of Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, NSW 2006, Australia
| | - Shila Ghazanfar
- School of Mathematics and Statistics, The University of Sydney, NSW 2006, Australia
- Sydney Precision Data Science Centre, University of Sydney, NSW 2006, Australia
- Charles Perkins Centre, The University of Sydney, NSW 2006, Australia
| | - Keri Martinowich
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Johns Hopkins Kavli Neuroscience Discovery Institute, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Stephanie C. Hicks
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA
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6
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Schott M, León-Periñán D, Splendiani E, Strenger L, Licha JR, Pentimalli TM, Schallenberg S, Alles J, Samut Tagliaferro S, Boltengagen A, Ehrig S, Abbiati S, Dommerich S, Pagani M, Ferretti E, Macino G, Karaiskos N, Rajewsky N. Open-ST: High-resolution spatial transcriptomics in 3D. Cell 2024; 187:3953-3972.e26. [PMID: 38917789 DOI: 10.1016/j.cell.2024.05.055] [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: 01/04/2024] [Revised: 04/05/2024] [Accepted: 05/30/2024] [Indexed: 06/27/2024]
Abstract
Spatial transcriptomics (ST) methods unlock molecular mechanisms underlying tissue development, homeostasis, or disease. However, there is a need for easy-to-use, high-resolution, cost-efficient, and 3D-scalable methods. Here, we report Open-ST, a sequencing-based, open-source experimental and computational resource to address these challenges and to study the molecular organization of tissues in 2D and 3D. In mouse brain, Open-ST captured transcripts at subcellular resolution and reconstructed cell types. In primary head-and-neck tumors and patient-matched healthy/metastatic lymph nodes, Open-ST captured the diversity of immune, stromal, and tumor populations in space, validated by imaging-based ST. Distinct cell states were organized around cell-cell communication hotspots in the tumor but not the metastasis. Strikingly, the 3D reconstruction and multimodal analysis of the metastatic lymph node revealed spatially contiguous structures not visible in 2D and potential biomarkers precisely at the 3D tumor/lymph node boundary. All protocols and software are available at https://rajewsky-lab.github.io/openst.
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Affiliation(s)
- Marie Schott
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany
| | - Daniel León-Periñán
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany
| | - Elena Splendiani
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany; Department of Experimental Medicine, Sapienza University, Rome, Italy
| | - Leon Strenger
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany
| | - Jan Robin Licha
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany
| | - Tancredi Massimo Pentimalli
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany
| | - Simon Schallenberg
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität Berlin, 10117 Berlin, Germany
| | - Jonathan Alles
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany
| | - Sarah Samut Tagliaferro
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany
| | - Anastasiya Boltengagen
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany
| | - Sebastian Ehrig
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany
| | - Stefano Abbiati
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany; IFOM ETS - The AIRC Institute of Molecular Oncology, Milan, Italy
| | - Steffen Dommerich
- Department of Otorhinolaryngology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, Berlin 13353, Germany
| | - Massimiliano Pagani
- IFOM ETS - The AIRC Institute of Molecular Oncology, Milan, Italy; Department of Medical Biotechnology and Translational Medicine, Università degli Studi, Milan, Italy
| | | | - Giuseppe Macino
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany; Department of Cellular Biotechnologies and Hematology, La Sapienza University of Rome, 00161 Rome, Italy.
| | - Nikos Karaiskos
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany.
| | - Nikolaus Rajewsky
- Laboratory for Systems Biology of Regulatory Elements, Berlin Institute for Medical Systems Biology (BIMSB), Max-Delbrück-Centrum for Molecular Medicine in the Helmholtz Association (MDC), Hannoversche Str. 28, 10115 Berlin, Germany; Charité - Universitätsmedizin, Charitéplatz 1, 10117 Berlin, Germany; German Center for Cardiovascular Research (DZHK), Site Berlin, Berlin, Germany; NeuroCure Cluster of Excellence, Berlin, Germany; German Cancer Consortium (DKTK), Heidelberg, Germany; National Center for Tumor Diseases (NCT), Site Berlin, Berlin, Germany.
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7
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Li JP, Liu YJ, Wang SS, Lu ZH, Ye QW, Zhou JY, Zou X, Chen YG. EBF1-COX4I2 signaling axis promotes a myofibroblast-like phenotype in cancer-associated fibroblasts (CAFs) and is associated with an immunosuppressive microenvironment. Int Immunopharmacol 2024; 139:112666. [PMID: 39002521 DOI: 10.1016/j.intimp.2024.112666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 07/08/2024] [Accepted: 07/08/2024] [Indexed: 07/15/2024]
Abstract
Immunotherapy has limited response rates in colorectal cancer (CRC) due to an immunosuppressive tumor microenvironment (TME). Combining transcriptome sequencing, clinical specimens, and functional experiments, we identified a unique group of CAF subpopulations (COX4I2 + ) with inhibited mitochondrial respiration and enhanced glycolysis. Through bioinformatics predictions and luciferase reporter assays, we determined that EBF1 can upstreamly regulate COX4I2 transcription. COX4I2 + CAFs functionally and phenotypically resemble myofibroblasts, are important for the formation of the fibrotic TME, and are capable of activating the M2 phenotype of macrophages. In vitro experiments demonstrated that COX4I2 + CAFs promote immunosuppressive TME by blocking CD8 + T cell infiltration and inducing CD8 + T cell dysfunction. Using multiple independent cohorts, we also found a strong correlation between the immunotherapy response rate of CRC patients and COX4I2 expression in their tumors. Our results identify a CAF subpopulation characterized by activation of the EBF1-COX4I2 axis, and this group of CAFs can be targeted to improve cancer immunotherapy outcomes.
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Affiliation(s)
- Jie-Pin Li
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China; Jiangsu Province Key Laboratory of Tumor Systems Biology and Chinese Medicine, Nanjing, Jiangsu 210029, China
| | - Yuan-Jie Liu
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China; Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China
| | - Shuang-Shuang Wang
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China; Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China
| | - Zhi-Hua Lu
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China; Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China
| | - Qian-Wen Ye
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China; Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China
| | - Jin-Yong Zhou
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China
| | - Xi Zou
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China; Jiangsu Province Key Laboratory of Tumor Systems Biology and Chinese Medicine, Nanjing, Jiangsu 210029, China; Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China; Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing, Jiangsu 210029, China
| | - Yu-Gen Chen
- Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China; Jiangsu Province Key Laboratory of Tumor Systems Biology and Chinese Medicine, Nanjing, Jiangsu 210029, China; Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China; Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing, Jiangsu 210029, China.
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8
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Nałęcz D, Świętek A, Hudy D, Wiczkowski K, Złotopolska Z, Strzelczyk JK. Assessment of Concentration KRT6 Proteins in Tumor and Matching Surgical Margin from Patients with Head and Neck Squamous Cell Carcinoma. Int J Mol Sci 2024; 25:7356. [PMID: 39000463 PMCID: PMC11242288 DOI: 10.3390/ijms25137356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Revised: 06/28/2024] [Accepted: 07/03/2024] [Indexed: 07/16/2024] Open
Abstract
Head and neck squamous cell carcinomas (HNSCCs) are one of the most frequently detected cancers in the world; not all mechanisms related to the expression of keratin in this type of cancer are known. The aim of this study was to evaluate type II cytokeratins (KRT): KRT6A, KRT6B, and KRT6C protein concentrations in 54 tumor and margin samples of head and neck squamous cell carcinoma (HNSCC). Moreover, we examined a possible association between protein concentration and the clinical and demographic variables. Protein concentrations were measured using enzyme-linked immunosorbent assay (ELISA). Significantly higher KRT6A protein concentration was found in HNSCC samples compared to surgical margins. An inverse relationship was observed for KRT6B and KRT6C proteins. We showed an association between the KRT6C protein level and clinical parameters T and N in tumor and margin samples. When analyzing the effect of smoking and drinking on KRT6A, KRT6B, and KRT6C levels, we demonstrated a statistically significant difference between regular or occasional tobacco and alcohol habits and patients who do not have any tobacco and alcohol habits in tumor and margin samples. Moreover, we found an association between KRT6B and KRT6C concentration and proliferative index Ki-67 and HPV status in tumor samples. Our results showed that concentrations of KRT6s were different in the tumor and the margin samples and varied in relation to clinical and demographic parameters. We add information to the current knowledge about the role of KRT6s isoforms in HNSCC. We speculate that variations in the studied isoforms of the KRT6 protein could be due to the presence and development of the tumor and its microenvironment. It is important to note that the analyses were performed in tumor and surgical margins and can provide more accurate information on the function in normal and cancer cells and regulation in response to various factors.
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Affiliation(s)
- Dariusz Nałęcz
- Department of Otolaryngology and Maxillofacial Surgery, St. Vincent De Paul Hospital, 1 Wójta Radtkego St., 81-348 Gdynia, Poland
| | - Agata Świętek
- Department of Medical and Molecular Biology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, 19 Jordana St., 41-808 Zabrze, Poland
- Silesia LabMed Research and Implementation Centre, Medical University of Silesia in Katowice, 19 Jordana St., 41-808 Zabrze, Poland
| | - Dorota Hudy
- Department of Medical and Molecular Biology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, 19 Jordana St., 41-808 Zabrze, Poland
| | - Karol Wiczkowski
- Department of Medical and Molecular Biology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, 19 Jordana St., 41-808 Zabrze, Poland
- Students' Scientific Association, Department of Medical and Molecular Biology, Medical University of Silesia, Katowice, 19 Jordana St., 41-808 Zabrze, Poland
| | - Zofia Złotopolska
- Department of Otolaryngology and Maxillofacial Surgery, St. Vincent De Paul Hospital, 1 Wójta Radtkego St., 81-348 Gdynia, Poland
| | - Joanna Katarzyna Strzelczyk
- Department of Medical and Molecular Biology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, 19 Jordana St., 41-808 Zabrze, Poland
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9
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Yang F, Niu X, Zhou M, Li W. Development and validation of a novel disulfidptosis-related lncRNAs signature in patients with HPV-negative oral squamous cell carcinoma. Sci Rep 2024; 14:14436. [PMID: 38910181 PMCID: PMC11194273 DOI: 10.1038/s41598-024-65194-y] [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: 04/13/2024] [Accepted: 06/18/2024] [Indexed: 06/25/2024] Open
Abstract
Disulfidptosis is a recently identified mode of regulated cell death. Regulating disulfidptosis in carcinoma is a promising therapeutic approach. Long non-coding RNAs (lncRNAs) have been reported to be related to the occurrence and development of many cancers. Disulfidptosis-related lncRNAs (DRLs) in HPV-negative oral squamous cell carcinoma (OSCC) have not been studied. Based on The Cancer Genome Atlas (TCGA) database, least absolute shrinkage selection operator (LASSO) analysis and Cox regression analysis were used to identify overall survival related DRLs and construct the signature. Kaplan-Meier, time-dependent receiver operating characteristics (ROC) and principal component analyses (PCA) were explored to demonstrate the prediction potential of the signature. Subgroup analysis stratified by different clinicopathological characteristics were conducted. Nomogram was established by DRLs signature and independent clinicopathological characteristics. The calibration plots were performed to reveal the accuracy of nomogram. Immune cell subset infiltration, immunotherapy response, drug sensitivity analysis, and tumor mutation burden (TMB) were conducted. Underlying functions and pathways were explored by Gene Set Enrichment Analysis (GSEA) analysis. Previous lncRNA signatures of OSCC were retrieved from PubMed for further validation. Gene expression omnibus (GEO) datasets (GSE41613 and GSE85446) were merged as an external validation for DRLs signature. Consensus clustering analysis of DRLs signature and experimental validation of DRLs were also explored. This research sheds light on the robust performance of DRLs signature in survival prediction, immune cell infiltration, immune escape, and immunotherapy of HPV-negative OSCC.
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Affiliation(s)
- Fan Yang
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Xinyu Niu
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Mingzhu Zhou
- Department of Otorhinolaryngology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Li
- Department of Geriatrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
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10
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Chen J, Zhou M, Wu W, Zhang J, Li Y, Li D. STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics. ARXIV 2024:arXiv:2406.06393v2. [PMID: 38947920 PMCID: PMC11213178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Recent advances in multi-modal algorithms have driven and been driven by the increasing availability of large image-text datasets, leading to significant strides in various fields, including computational pathology. However, in most existing medical image-text datasets, the text typically provides high-level summaries that may not sufficiently describe sub-tile regions within a large pathology image. For example, an image might cover an extensive tissue area containing cancerous and healthy regions, but the accompanying text might only specify that this image is a cancer slide, lacking the nuanced details needed for in-depth analysis. In this study, we introduce STimage-1K4M, a novel dataset designed to bridge this gap by providing genomic features for sub-tile images. STimage-1K4M contains 1,149 images derived from spatial transcriptomics data, which captures gene expression information at the level of individual spatial spots within a pathology image. Specifically, each image in the dataset is broken down into smaller sub-image tiles, with each tile paired with 15,000 - 30,000 dimensional gene expressions. With 4,293,195 pairs of sub-tile images and gene expressions, STimage-1K4M offers unprecedented granularity, paving the way for a wide range of advanced research in multi-modal data analysis an innovative applications in computational pathology, and beyond.
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Affiliation(s)
| | | | - Wenrong Wu
- University of North Carolina at Chapel Hill
| | | | - Yun Li
- University of North Carolina at Chapel Hill
| | - Didong Li
- University of North Carolina at Chapel Hill
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11
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Cilento MA, Sweeney CJ, Butler LM. Spatial transcriptomics in cancer research and potential clinical impact: a narrative review. J Cancer Res Clin Oncol 2024; 150:296. [PMID: 38850363 PMCID: PMC11162383 DOI: 10.1007/s00432-024-05816-0] [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: 03/19/2024] [Accepted: 05/22/2024] [Indexed: 06/10/2024]
Abstract
Spatial transcriptomics (ST) provides novel insights into the tumor microenvironment (TME). ST allows the quantification and illustration of gene expression profiles in the spatial context of tissues, including both the cancer cells and the microenvironment in which they are found. In cancer research, ST has already provided novel insights into cancer metastasis, prognosis, and immunotherapy responsiveness. The clinical precision oncology application of next-generation sequencing (NGS) and RNA profiling of tumors relies on bulk methods that lack spatial context. The ability to preserve spatial information is now possible, as it allows us to capture tumor heterogeneity and multifocality. In this narrative review, we summarize precision oncology, discuss tumor sequencing in the clinic, and review the available ST research methods, including seqFISH, MERFISH (Vizgen), CosMx SMI (NanoString), Xenium (10x), Visium (10x), Stereo-seq (STOmics), and GeoMx DSP (NanoString). We then review the current ST literature with a focus on solid tumors organized by tumor type. Finally, we conclude by addressing an important question: how will spatial transcriptomics ultimately help patients with cancer?
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Affiliation(s)
- Michael A Cilento
- South Australian Immunogenomics Cancer Institute, The University of Adelaide, Adelaide, SA, Australia.
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia.
- The Queen Elizabeth Hospital, Woodville South, SA, Australia.
| | - Christopher J Sweeney
- South Australian Immunogenomics Cancer Institute, The University of Adelaide, Adelaide, SA, Australia
| | - Lisa M Butler
- South Australian Immunogenomics Cancer Institute, The University of Adelaide, Adelaide, SA, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, Australia
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12
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Cao J, Li C, Cui Z, Deng S, Lei T, Liu W, Yang H, Chen P. Spatial Transcriptomics: A Powerful Tool in Disease Understanding and Drug Discovery. Theranostics 2024; 14:2946-2968. [PMID: 38773973 PMCID: PMC11103497 DOI: 10.7150/thno.95908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 04/25/2024] [Indexed: 05/24/2024] Open
Abstract
Recent advancements in modern science have provided robust tools for drug discovery. The rapid development of transcriptome sequencing technologies has given rise to single-cell transcriptomics and single-nucleus transcriptomics, increasing the accuracy of sequencing and accelerating the drug discovery process. With the evolution of single-cell transcriptomics, spatial transcriptomics (ST) technology has emerged as a derivative approach. Spatial transcriptomics has emerged as a hot topic in the field of omics research in recent years; it not only provides information on gene expression levels but also offers spatial information on gene expression. This technology has shown tremendous potential in research on disease understanding and drug discovery. In this article, we introduce the analytical strategies of spatial transcriptomics and review its applications in novel target discovery and drug mechanism unravelling. Moreover, we discuss the current challenges and issues in this research field that need to be addressed. In conclusion, spatial transcriptomics offers a new perspective for drug discovery.
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Affiliation(s)
- Junxian Cao
- Beijing Key Laboratory of Traditional Chinese Medicine Basic Research on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing 100700, China
- Analysis of Complex Effects of Proprietary Chinese Medicine, Hunan Provincial Key Laboratory, Yongzhou City, Hunan Province, China
| | - Caifeng Li
- Beijing Key Laboratory of Traditional Chinese Medicine Basic Research on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Zhao Cui
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Shiwen Deng
- Beijing Key Laboratory of Traditional Chinese Medicine Basic Research on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing 100700, China
- Analysis of Complex Effects of Proprietary Chinese Medicine, Hunan Provincial Key Laboratory, Yongzhou City, Hunan Province, China
| | - Tong Lei
- Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Wei Liu
- Beijing Key Laboratory of Traditional Chinese Medicine Basic Research on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Hongjun Yang
- Beijing Key Laboratory of Traditional Chinese Medicine Basic Research on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing 100700, China
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
- Analysis of Complex Effects of Proprietary Chinese Medicine, Hunan Provincial Key Laboratory, Yongzhou City, Hunan Province, China
| | - Peng Chen
- Beijing Key Laboratory of Traditional Chinese Medicine Basic Research on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing 100700, China
- Analysis of Complex Effects of Proprietary Chinese Medicine, Hunan Provincial Key Laboratory, Yongzhou City, Hunan Province, China
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13
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Walker CR, Angelo M. Insights and Opportunity Costs in Applying Spatial Biology to Study the Tumor Microenvironment. Cancer Discov 2024; 14:707-710. [PMID: 38587535 DOI: 10.1158/2159-8290.cd-24-0348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
SUMMARY The recent development of high-dimensional spatial omics tools has revealed the functional importance of the tumor microenvironment in driving tumor progression. Here, we discuss practical factors to consider when designing a spatial biology cohort and offer perspectives on the future of spatial biology research.
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Affiliation(s)
- Cameron R Walker
- Department of Pathology, Stanford University School of Medicine, Palo Alto, California
| | - Michael Angelo
- Department of Pathology, Stanford University School of Medicine, Palo Alto, California
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14
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Mulholland EJ, Leedham SJ. Redefining clinical practice through spatial profiling: a revolution in tissue analysis. Ann R Coll Surg Engl 2024; 106:305-312. [PMID: 38555868 PMCID: PMC10981989 DOI: 10.1308/rcsann.2023.0091] [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] [Accepted: 10/25/2023] [Indexed: 04/02/2024] Open
Abstract
Spatial biology, which combines molecular biology and advanced imaging, enhances our understanding of tissue cellular organisation. Despite its potential, spatial omics encounters challenges related to data complexity, computational requirements and standardisation of analysis. In clinical applications, spatial omics has the potential to revolutionise biomarker discovery, disease stratification and personalised treatments. It can identify disease-specific cell patterns, and could help risk stratify patients for clinical trials and disease-appropriate therapies. Although there are challenges in adopting it in clinical practice, spatial omics has the potential to significantly enhance patient outcomes. In this paper, we discuss the recent evolution of spatial biology, and its potential for improving our tissue level understanding and treatment of disease, to help advance precision and effectiveness in healthcare interventions.
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15
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Kehl A, Aupperle-Lellbach H, de Brot S, van der Weyden L. Review of Molecular Technologies for Investigating Canine Cancer. Animals (Basel) 2024; 14:769. [PMID: 38473154 DOI: 10.3390/ani14050769] [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: 12/21/2023] [Revised: 02/09/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
Genetic molecular testing is starting to gain traction as part of standard clinical practice for dogs with cancer due to its multi-faceted benefits, such as potentially being able to provide diagnostic, prognostic and/or therapeutic information. However, the benefits and ultimate success of genomic analysis in the clinical setting are reliant on the robustness of the tools used to generate the results, which continually expand as new technologies are developed. To this end, we review the different materials from which tumour cells, DNA, RNA and the relevant proteins can be isolated and what methods are available for interrogating their molecular profile, including analysis of the genetic alterations (both somatic and germline), transcriptional changes and epigenetic modifications (including DNA methylation/acetylation and microRNAs). We also look to the future and the tools that are currently being developed, such as using artificial intelligence (AI) to identify genetic mutations from histomorphological criteria. In summary, we find that the molecular genetic characterisation of canine neoplasms has made a promising start. As we understand more of the genetics underlying these tumours and more targeted therapies become available, it will no doubt become a mainstay in the delivery of precision veterinary care to dogs with cancer.
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Affiliation(s)
- Alexandra Kehl
- Laboklin GmbH & Co. KG, Steubenstr. 4, 97688 Bad Kissingen, Germany
- School of Medicine, Institute of Pathology, Technical University of Munich, Trogerstr. 18, 81675 München, Germany
| | - Heike Aupperle-Lellbach
- Laboklin GmbH & Co. KG, Steubenstr. 4, 97688 Bad Kissingen, Germany
- School of Medicine, Institute of Pathology, Technical University of Munich, Trogerstr. 18, 81675 München, Germany
| | - Simone de Brot
- Institute of Animal Pathology, COMPATH, University of Bern, 3012 Bern, Switzerland
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16
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Ferri-Borgogno S, Burks JK, Seeley EH, McKee TD, Stolley DL, Basi AV, Gomez JA, Gamal BT, Ayyadhury S, Lawson BC, Yates MS, Birrer MJ, Lu KH, Mok SC. Molecular, Metabolic, and Subcellular Mapping of the Tumor Immune Microenvironment via 3D Targeted and Non-Targeted Multiplex Multi-Omics Analyses. Cancers (Basel) 2024; 16:846. [PMID: 38473208 PMCID: PMC10930466 DOI: 10.3390/cancers16050846] [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: 02/07/2024] [Revised: 02/16/2024] [Accepted: 02/17/2024] [Indexed: 03/14/2024] Open
Abstract
Most platforms used for the molecular reconstruction of the tumor-immune microenvironment (TIME) of a solid tumor fail to explore the spatial context of the three-dimensional (3D) space of the tumor at a single-cell resolution, and thus lack information about cell-cell or cell-extracellular matrix (ECM) interactions. To address this issue, a pipeline which integrated multiplex spatially resolved multi-omics platforms was developed to identify crosstalk signaling networks among various cell types and the ECM in the 3D TIME of two FFPE (formalin-fixed paraffin embedded) gynecologic tumor samples. These platforms include non-targeted mass spectrometry imaging (glycans, metabolites, and peptides) and Stereo-seq (spatial transcriptomics) and targeted seqIF (IHC proteomics). The spatially resolved imaging data in a two- and three-dimensional space demonstrated various cellular neighborhoods in both samples. The collection of spatially resolved analytes in a voxel (3D pixel) across serial sections of the tissue was also demonstrated. Data collected from this analytical pipeline were used to construct spatial 3D maps with single-cell resolution, which revealed cell identity, activation, and energized status. These maps will provide not only insights into the molecular basis of spatial cell heterogeneity in the TIME, but also novel predictive biomarkers and therapeutic targets, which can improve patient survival rates.
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Affiliation(s)
- Sammy Ferri-Borgogno
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA (K.H.L.)
| | - Jared K. Burks
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (D.L.S.); (A.V.B.); (J.A.G.)
| | - Erin H. Seeley
- Department of Chemistry, The University of Texas at Austin, Austin, TX 78712, USA;
| | - Trevor D. McKee
- Pathomics, Inc., Toronto, ON M4C 3K2, Canada; (T.D.M.); (S.A.)
| | - Danielle L. Stolley
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (D.L.S.); (A.V.B.); (J.A.G.)
| | - Akshay V. Basi
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (D.L.S.); (A.V.B.); (J.A.G.)
| | - Javier A. Gomez
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; (D.L.S.); (A.V.B.); (J.A.G.)
| | - Basant T. Gamal
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA (K.H.L.)
| | | | - Barrett C. Lawson
- Department of Anatomical Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Melinda S. Yates
- Department of Pathology and Laboratory Medicine, The University of North Carolina, Chapel Hill, NC 27599, USA
| | - Michael J. Birrer
- Winthrop P. Rockefelle Cancer Institute, The University of Arkanasas for Medical Sciences, Little Rock, AR 72205, USA
| | - Karen H. Lu
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA (K.H.L.)
| | - Samuel C. Mok
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA (K.H.L.)
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17
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Sosa J, Oyelakin A, Sinha S. The Reign of Follistatin in Tumors and Their Microenvironment: Implications for Drug Resistance. BIOLOGY 2024; 13:130. [PMID: 38392348 PMCID: PMC10887188 DOI: 10.3390/biology13020130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 02/10/2024] [Accepted: 02/16/2024] [Indexed: 02/24/2024]
Abstract
Follistatin (FST) is a potent neutralizer of the transforming growth factor-β superfamily and is associated with normal cellular programs and various hallmarks of cancer, such as proliferation, migration, angiogenesis, and immune evasion. The aberrant expression of FST by solid tumors is a well-documented observation, yet how FST influences tumor progression and therapy response remains unclear. The recent surge in omics data has revealed new insights into the molecular foundation underpinning tumor heterogeneity and its microenvironment, offering novel precision medicine-based opportunities to combat cancer. In this review, we discuss these recent FST-centric studies, thereby offering an updated perspective on the protean role of FST isoforms in shaping the complex cellular ecosystem of tumors and in mediating drug resistance.
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Affiliation(s)
- Jennifer Sosa
- Department of Biochemistry, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA
| | - Akinsola Oyelakin
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA 98101, USA
- Ben Towne Center for Childhood Cancer Research, Seattle Children's Research Institute, Seattle Children's Hospital, Seattle, WA 98101, USA
| | - Satrajit Sinha
- Department of Biochemistry, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA
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18
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Yang S, Zhou X. SRT-Server: powering the analysis of spatial transcriptomic data. Genome Med 2024; 16:18. [PMID: 38279156 PMCID: PMC10811909 DOI: 10.1186/s13073-024-01288-6] [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: 05/23/2023] [Accepted: 01/15/2024] [Indexed: 01/28/2024] Open
Abstract
BACKGROUND Spatial resolved transcriptomics (SRT) encompasses a rapidly developing set of technologies that enable the measurement of gene expression in tissue while retaining spatial localization information. SRT technologies and the enabled SRT studies have provided unprecedent insights into the structural and functional underpinnings of complex tissues. As SRT technologies have advanced and an increasing number of SRT studies have emerged, numerous sophisticated statistical and computational methods have been developed to facilitate the analysis and interpretation of SRT data. However, despite the growing popularity of SRT studies and the widespread availability of SRT analysis methods, analysis of large-scale and complex SRT datasets remains challenging and not easily accessible to researchers with limited statistical and computational backgrounds. RESULTS Here, we present SRT-Server, the first webserver designed to carry out comprehensive SRT analyses for a wide variety of SRT technologies while requiring minimal prior computational knowledge. Implemented with cutting-edge web development technologies, SRT-Server is user-friendly and features multiple analytic modules that can perform a range of SRT analyses. With a flowchart-style interface, these different analytic modules on the SRT-Server can be dragged into the main panel and connected to each other to create custom analytic pipelines. SRT-Server then automatically executes the desired analyses, generates corresponding figures, and outputs results-all without requiring prior programming knowledge. We demonstrate the advantages of SRT-Server through three case studies utilizing SRT data collected from two common platforms, highlighting its versatility and values to researchers with varying analytic expertise. CONCLUSIONS Overall, SRT-Server presents a user-friendly, efficient, effective, secure, and expandable solution for SRT data analysis, opening new doors for researchers in the field. SRT-Server is freely available at https://spatialtranscriptomicsanalysis.com/ .
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Affiliation(s)
- Sheng Yang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China.
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, 48109, USA.
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19
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Zheng Y, Pizurica M, Carrillo-Perez F, Noor H, Yao W, Wohlfart C, Marchal K, Vladimirova A, Gevaert O. Digital profiling of cancer transcriptomes from histology images with grouped vision attention. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.28.560068. [PMID: 37808782 PMCID: PMC10557714 DOI: 10.1101/2023.09.28.560068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Cancer is a heterogeneous disease that demands precise molecular profiling for better understanding and management. Recently, deep learning has demonstrated potentials for cost-efficient prediction of molecular alterations from histology images. While transformer-based deep learning architectures have enabled significant progress in non-medical domains, their application to histology images remains limited due to small dataset sizes coupled with the explosion of trainable parameters. Here, we develop SEQUOIA, a transformer model to predict cancer transcriptomes from whole-slide histology images. To enable the full potential of transformers, we first pre-train the model using data from 1,802 normal tissues. Then, we fine-tune and evaluate the model in 4,331 tumor samples across nine cancer types. The prediction performance is assessed at individual gene levels and pathway levels through Pearson correlation analysis and root mean square error. The generalization capacity is validated across two independent cohorts comprising 1,305 tumors. In predicting the expression levels of 25,749 genes, the highest performance is observed in cancers from breast, kidney and lung, where SEQUOIA accurately predicts the expression of 11,069, 10,086 and 8,759 genes, respectively. The accurately predicted genes are associated with the regulation of inflammatory response, cell cycles and metabolisms. While the model is trained at the tissue level, we showcase its potential in predicting spatial gene expression patterns using spatial transcriptomics datasets. Leveraging the prediction performance, we develop a digital gene expression signature that predicts the risk of recurrence in breast cancer. SEQUOIA deciphers clinically relevant gene expression patterns from histology images, opening avenues for improved cancer management and personalized therapies.
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Affiliation(s)
- Yuanning Zheng
- Department of Medicine, Stanford Center for Biomedical Informatics Research (BMIR), Stanford University, Stanford, 94305, USA
| | - Marija Pizurica
- Department of Medicine, Stanford Center for Biomedical Informatics Research (BMIR), Stanford University, Stanford, 94305, USA
- Internet technology and Data science Lab (IDLab), Ghent University, Technologiepark-Zwijnaarde 126, Ghent, 9052, Gent, Belgium
| | - Francisco Carrillo-Perez
- Department of Medicine, Stanford Center for Biomedical Informatics Research (BMIR), Stanford University, Stanford, 94305, USA
| | - Humaira Noor
- Department of Medicine, Stanford Center for Biomedical Informatics Research (BMIR), Stanford University, Stanford, 94305, USA
| | - Wei Yao
- Roche Information Solutions, Roche Diagnostics Corporation, Santa Clara, California, USA
| | | | - Kathleen Marchal
- Internet technology and Data science Lab (IDLab), Ghent University, Technologiepark-Zwijnaarde 126, Ghent, 9052, Gent, Belgium
| | - Antoaneta Vladimirova
- Roche Information Solutions, Roche Diagnostics Corporation, Santa Clara, California, USA
| | - Olivier Gevaert
- Department of Medicine, Stanford Center for Biomedical Informatics Research (BMIR), Stanford University, Stanford, 94305, USA
- Department of Biomedical Data Science, Stanford University, Stanford, 94305, USA
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20
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Lee H, Park S, Yun JH, Seo C, Ahn JM, Cha HY, Shin YS, Park HR, Lee D, Roh J, Heo HJ, Baek SE, Kim EK, Lee HS, Kim CH, Kim YH, Jang JY. Deciphering head and neck cancer microenvironment: Single-cell and spatial transcriptomics reveals human papillomavirus-associated differences. J Med Virol 2024; 96:e29386. [PMID: 38235919 DOI: 10.1002/jmv.29386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 12/18/2023] [Accepted: 12/20/2023] [Indexed: 01/19/2024]
Abstract
Human papillomavirus (HPV) is a major causative factor of head and neck squamous cell carcinoma (HNSCC), and the incidence of HPV- associated HNSCC is increasing. The role of tumor microenvironment in viral infection and metastasis needs to be explored further. We studied the molecular characteristics of primary tumors (PTs) and lymph node metastatic tumors (LNMTs) by stratifying them based on their HPV status. Eight samples for single-cell RNA profiling and six samples for spatial transcriptomics (ST), composed of matched primary tumors (PT) and lymph node metastases (LNMT), were collected from both HPV- negative (HPV- ) and HPV-positive (HPV+ ) patients. Using the 10x Genomics Visium platform, integrative analyses with single-cell RNA sequencing were performed. Intracellular and intercellular alterations were analyzed, and the findings were confirmed using experimental validation and publicly available data set. The HPV+ tissues were composed of a substantial amount of lymphoid cells regardless of the presence or absence of metastasis, whereas the HPV- tissue exhibited remarkable changes in the number of macrophages and plasma cells, particularly in the LNMT. From both single-cell RNA and ST data set, we discovered a central gene, pyruvate kinase muscle isoform 1/2 (PKM2), which is closely associated with the stemness of cancer stem cell-like populations in LNMT of HPV- tissue. The consistent expression was observed in HPV- HNSCC cell line and the knockdown of PKM2 weakened spheroid formation ability. Furthermore, we found an ectopic lymphoid structure morphology and clinical effects of the structure in ST slide of the HPV+ patients and verified their presence in tumor tissue using immunohistochemistry. Finally, the ephrin-A (EPHA2) pathway was detected as important signals in angiogenesis for HPV- patients from single-cell RNA and ST profiles, and knockdown of EPHA2 declined the cell migration. Our study described the distinct cellular composition and molecular alterations in primary and metastatic sites in HNSCC patients based on their HPV status. These results provide insights into HNSCC biology in the context of HPV infection and its potential clinical implications.
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Affiliation(s)
- Hansong Lee
- Medical Research Institute, Pusan National University, Yangsan, South Korea
| | - Sohee Park
- Data Science Center, Insilicogen, Inc., Yongin-si, South Korea
| | - Ju Hyun Yun
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon, South Korea
| | - Chorong Seo
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon, South Korea
| | - Ji Mi Ahn
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon, South Korea
| | - Hyun-Young Cha
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon, South Korea
| | - Yoo Seob Shin
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon, South Korea
| | - Hae Ryoun Park
- Department of Periodontology and Dental Research Institute, Pusan National University Dental Hospital, Yangsan, South Korea
- Periodontal Disease Signaling Network Research Center, School of Dentistry, Pusan National University, Yangsan, South Korea
- Department of Oral Pathology, School of Dentistry, Pusan National University, Yangsan, South Korea
| | - Dongjun Lee
- Department of Convergence Medicine, School of Medicine, Pusan National University, Yangsan, South Korea
| | - Jin Roh
- Department of Pathology, School of Medicine, Ajou University, Suwon, South Korea
| | - Hye Jin Heo
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, South Korea
| | - Seung Eun Baek
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, South Korea
| | - Eun Kyoung Kim
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, South Korea
| | - Hae Seul Lee
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, South Korea
| | - Chul-Ho Kim
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon, South Korea
| | - Yun Hak Kim
- Periodontal Disease Signaling Network Research Center, School of Dentistry, Pusan National University, Yangsan, South Korea
- Department of Anatomy, School of Medicine, Pusan National University, Yangsan, South Korea
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, South Korea
| | - Jeon Yeob Jang
- Department of Otolaryngology, School of Medicine, Ajou University, Suwon, South Korea
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea
- Department of Convergence Healthcare Medicine, Graduate School of Ajou University, Suwon, South Korea
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21
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Liu Q, Sun Y, Long M, Chen X, Zhong S, Huang C, Wei R, Luo JL. DDX5 Functions as a Tumor Suppressor in Tongue Cancer. Cancers (Basel) 2023; 15:5882. [PMID: 38136426 PMCID: PMC10741615 DOI: 10.3390/cancers15245882] [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: 10/24/2023] [Revised: 12/03/2023] [Accepted: 12/05/2023] [Indexed: 12/24/2023] Open
Abstract
DEAD-box polypeptide 5 (DDX5), a DEAD-box RNA helicase, is a multifunctional protein that plays important roles in many physiological and pathological processes. Contrary to its documented oncogenic role in a wide array of cancers, we herein demonstrate that DDX5 serves as a tumor suppressor in tongue cancer. The high expression of DDX5 is correlated with better prognosis for clinical tongue cancer patients. DDX5 downregulates the genes associated with tongue cancer progression. The knockdown of DDX5 promotes, while the overexpression of DDX5 inhibits, tongue cancer proliferation, development, and cisplatin resistance. Furthermore, the expression of DDX5 in tongue cancer is associated with immune cell infiltration in the tumor microenvironment. Specifically, the expression of DDX5 is associated with the reduced infiltration of M2 macrophages and increased infiltration of T cell clusters, which may contribute to anticancer effects in the tumor microenvironment. In this study, we establish DDX5 as a valuable prognostic biomarker and an important tumor suppressor in tongue cancer.
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Affiliation(s)
- Qingqing Liu
- Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China; (Q.L.); (Y.S.); (X.C.)
| | - Yangqing Sun
- Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China; (Q.L.); (Y.S.); (X.C.)
| | - Min Long
- The Cancer Research Institute and the Second Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, China; (M.L.); (S.Z.)
| | - Xueyan Chen
- Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China; (Q.L.); (Y.S.); (X.C.)
| | - Shangwei Zhong
- The Cancer Research Institute and the Second Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, China; (M.L.); (S.Z.)
| | - Changhao Huang
- The Organ Transplant Center, Xiangya Hospital Central South University, Changsha 410000, China;
| | - Rui Wei
- Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China; (Q.L.); (Y.S.); (X.C.)
| | - Jun-Li Luo
- Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China; (Q.L.); (Y.S.); (X.C.)
- The Cancer Research Institute and the Second Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, China; (M.L.); (S.Z.)
- National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hunan Provincial Maternal and Child Health Care Hospital, Changsha 410008, China
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22
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Park YM, Lin DC. Moving closer towards a comprehensive view of tumor biology and microarchitecture using spatial transcriptomics. Nat Commun 2023; 14:7017. [PMID: 37919364 PMCID: PMC10622517 DOI: 10.1038/s41467-023-42960-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/27/2023] [Indexed: 11/04/2023] Open
Affiliation(s)
- Young Min Park
- Center for Craniofacial Molecular Biology, Herman Ostrow School of Dentistry, and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
- Department of Otorhinolaryngology, Yonsei University College of Medicine, Seoul, South Korea
| | - De-Chen Lin
- Center for Craniofacial Molecular Biology, Herman Ostrow School of Dentistry, and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA.
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23
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Zuo W, Sun R, Ji Z, Ma G. Macrophage-driven cardiac inflammation and healing: insights from homeostasis and myocardial infarction. Cell Mol Biol Lett 2023; 28:81. [PMID: 37858035 PMCID: PMC10585879 DOI: 10.1186/s11658-023-00491-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 09/19/2023] [Indexed: 10/21/2023] Open
Abstract
Early and prompt reperfusion therapy has markedly improved the survival rates among patients enduring myocardial infarction (MI). Nonetheless, the resulting adverse remodeling and the subsequent onset of heart failure remain formidable clinical management challenges and represent a primary cause of disability in MI patients worldwide. Macrophages play a crucial role in immune system regulation and wield a profound influence over the inflammatory repair process following MI, thereby dictating the degree of myocardial injury and the subsequent pathological remodeling. Despite numerous previous biological studies that established the classical polarization model for macrophages, classifying them as either M1 pro-inflammatory or M2 pro-reparative macrophages, this simplistic categorization falls short of meeting the precision medicine standards, hindering the translational advancement of clinical research. Recently, advances in single-cell sequencing technology have facilitated a more profound exploration of macrophage heterogeneity and plasticity, opening avenues for the development of targeted interventions to address macrophage-related factors in the aftermath of MI. In this review, we provide a summary of macrophage origins, tissue distribution, classification, and surface markers. Furthermore, we delve into the multifaceted roles of macrophages in maintaining cardiac homeostasis and regulating inflammation during the post-MI period.
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Affiliation(s)
- Wenjie Zuo
- Department of Cardiology, Zhongda Hospital, School of Medicine, Southeast University, No. 87, Dingjiaqiao, Nanjing, 210009, China
| | - Renhua Sun
- Department of Cardiology, Yancheng No. 1 People's Hospital, No. 66 South Renmin Road, Yancheng, 224000, China
| | - Zhenjun Ji
- Department of Cardiology, Zhongda Hospital, School of Medicine, Southeast University, No. 87, Dingjiaqiao, Nanjing, 210009, China
| | - Genshan Ma
- Department of Cardiology, Zhongda Hospital, School of Medicine, Southeast University, No. 87, Dingjiaqiao, Nanjing, 210009, China.
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