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Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis

Introduction: Clear cell renal cell carcinoma (ccRCC) is associated with unfavorable clinical outcomes. To identify viable therapeutic targets, a comprehensive understanding of intratumoral heterogeneity is crucial. In this study, we conducted bioinformatic analysis to scrutinize single-cell RNA seq...

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Autores principales: Wang, Yuxiong, Wang, Yishu, Liu, Bin, Gao, Xin, Li, Yunkuo, Li, Faping, Zhou, Honglan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392130/
https://www.ncbi.nlm.nih.gov/pubmed/37533434
http://dx.doi.org/10.3389/fgene.2023.1207233
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author Wang, Yuxiong
Wang, Yishu
Liu, Bin
Gao, Xin
Li, Yunkuo
Li, Faping
Zhou, Honglan
author_facet Wang, Yuxiong
Wang, Yishu
Liu, Bin
Gao, Xin
Li, Yunkuo
Li, Faping
Zhou, Honglan
author_sort Wang, Yuxiong
collection PubMed
description Introduction: Clear cell renal cell carcinoma (ccRCC) is associated with unfavorable clinical outcomes. To identify viable therapeutic targets, a comprehensive understanding of intratumoral heterogeneity is crucial. In this study, we conducted bioinformatic analysis to scrutinize single-cell RNA sequencing data of ccRCC tumor and para-tumor samples, aiming to elucidate the intratumoral heterogeneity in the ccRCC tumor microenvironment (TME). Methods: A total of 51,780 single cells from seven ccRCC tumors and five para-tumor samples were identified and grouped into 11 cell lineages using bioinformatic analysis. These lineages included tumor cells, myeloid cells, T-cells, fibroblasts, and endothelial cells, indicating a high degree of heterogeneity in the TME. Copy number variation (CNV) analysis was performed to compare CNV frequencies between tumor and normal cells. The myeloid cell population was further re-clustered into three major subgroups: monocytes, macrophages, and dendritic cells. Differential expression analysis, gene ontology, and gene set enrichment analysis were employed to assess inter-cluster and intra-cluster functional heterogeneity within the ccRCC TME. Results: Our findings revealed that immune cells in the TME predominantly adopted an inflammatory suppression state, promoting tumor cell growth and immune evasion. Additionally, tumor cells exhibited higher CNV frequencies compared to normal cells. The myeloid cell subgroups demonstrated distinct functional properties, with monocytes, macrophages, and dendritic cells displaying diverse roles in the TME. Certain immune cells exhibited pro-tumor and immunosuppressive effects, while others demonstrated antitumor and immunostimulatory properties. Conclusion: This study contributes to the understanding of intratumoral heterogeneity in the ccRCC TME and provides potential therapeutic targets for ccRCC treatment. The findings emphasize the importance of considering the diverse functional roles of immune cells in the TME for effective therapeutic interventions.
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spelling pubmed-103921302023-08-02 Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis Wang, Yuxiong Wang, Yishu Liu, Bin Gao, Xin Li, Yunkuo Li, Faping Zhou, Honglan Front Genet Genetics Introduction: Clear cell renal cell carcinoma (ccRCC) is associated with unfavorable clinical outcomes. To identify viable therapeutic targets, a comprehensive understanding of intratumoral heterogeneity is crucial. In this study, we conducted bioinformatic analysis to scrutinize single-cell RNA sequencing data of ccRCC tumor and para-tumor samples, aiming to elucidate the intratumoral heterogeneity in the ccRCC tumor microenvironment (TME). Methods: A total of 51,780 single cells from seven ccRCC tumors and five para-tumor samples were identified and grouped into 11 cell lineages using bioinformatic analysis. These lineages included tumor cells, myeloid cells, T-cells, fibroblasts, and endothelial cells, indicating a high degree of heterogeneity in the TME. Copy number variation (CNV) analysis was performed to compare CNV frequencies between tumor and normal cells. The myeloid cell population was further re-clustered into three major subgroups: monocytes, macrophages, and dendritic cells. Differential expression analysis, gene ontology, and gene set enrichment analysis were employed to assess inter-cluster and intra-cluster functional heterogeneity within the ccRCC TME. Results: Our findings revealed that immune cells in the TME predominantly adopted an inflammatory suppression state, promoting tumor cell growth and immune evasion. Additionally, tumor cells exhibited higher CNV frequencies compared to normal cells. The myeloid cell subgroups demonstrated distinct functional properties, with monocytes, macrophages, and dendritic cells displaying diverse roles in the TME. Certain immune cells exhibited pro-tumor and immunosuppressive effects, while others demonstrated antitumor and immunostimulatory properties. Conclusion: This study contributes to the understanding of intratumoral heterogeneity in the ccRCC TME and provides potential therapeutic targets for ccRCC treatment. The findings emphasize the importance of considering the diverse functional roles of immune cells in the TME for effective therapeutic interventions. Frontiers Media S.A. 2023-07-18 /pmc/articles/PMC10392130/ /pubmed/37533434 http://dx.doi.org/10.3389/fgene.2023.1207233 Text en Copyright © 2023 Wang, Wang, Liu, Gao, Li, Li and Zhou. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Wang, Yuxiong
Wang, Yishu
Liu, Bin
Gao, Xin
Li, Yunkuo
Li, Faping
Zhou, Honglan
Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis
title Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis
title_full Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis
title_fullStr Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis
title_full_unstemmed Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis
title_short Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis
title_sort mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392130/
https://www.ncbi.nlm.nih.gov/pubmed/37533434
http://dx.doi.org/10.3389/fgene.2023.1207233
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