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Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma
Traditional studies mostly focus on the role of single gene in regulating clear cell renal cell carcinoma (ccRCC), while it ignores the impact of tumour heterogeneity on disease progression. The purpose of this study is to construct a prognostic risk model for ccRCC by analysing the differential mar...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10014191/ https://www.ncbi.nlm.nih.gov/pubmed/36925653 http://dx.doi.org/10.1155/2023/5355269 |
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author | Wu, Guanlin Guo, Weiming Zhu, Shuai Fan, Gang |
author_facet | Wu, Guanlin Guo, Weiming Zhu, Shuai Fan, Gang |
author_sort | Wu, Guanlin |
collection | PubMed |
description | Traditional studies mostly focus on the role of single gene in regulating clear cell renal cell carcinoma (ccRCC), while it ignores the impact of tumour heterogeneity on disease progression. The purpose of this study is to construct a prognostic risk model for ccRCC by analysing the differential marker genes related to immune cells in the single-cell database to provide help in clinical diagnosis and targeted therapy. Single-cell data and ligand-receptor relationship pair data were downloaded from related publications, and ccRCC phenotype and expression profile data were downloaded from TCGA and CPTAC. Based on the DEGs of each cluster acquired from single-cell data, immune cell marker genes, and ligand-receptor gene data, we constructed a multilayer network. Then, the genes in the network and the genes in TCGA were used to construct the WGCNA network, which screened out prognosis-associated genes for subsequent analysis. Finally, a prognostic risk scoring model was obtained, and CPTAC data showed that the effectiveness of this model was good. A nomogram based on the predictive model for predicting the overall survival was established, and internal validation was performed well. Our findings suggest that the predictive model built and based on the immune cell scRNA-seq will enable us to judge the prognosis of patients with ccRCC and provide more accurate directions for basic relevant research and clinical practice. |
format | Online Article Text |
id | pubmed-10014191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-100141912023-03-15 Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma Wu, Guanlin Guo, Weiming Zhu, Shuai Fan, Gang J Oncol Research Article Traditional studies mostly focus on the role of single gene in regulating clear cell renal cell carcinoma (ccRCC), while it ignores the impact of tumour heterogeneity on disease progression. The purpose of this study is to construct a prognostic risk model for ccRCC by analysing the differential marker genes related to immune cells in the single-cell database to provide help in clinical diagnosis and targeted therapy. Single-cell data and ligand-receptor relationship pair data were downloaded from related publications, and ccRCC phenotype and expression profile data were downloaded from TCGA and CPTAC. Based on the DEGs of each cluster acquired from single-cell data, immune cell marker genes, and ligand-receptor gene data, we constructed a multilayer network. Then, the genes in the network and the genes in TCGA were used to construct the WGCNA network, which screened out prognosis-associated genes for subsequent analysis. Finally, a prognostic risk scoring model was obtained, and CPTAC data showed that the effectiveness of this model was good. A nomogram based on the predictive model for predicting the overall survival was established, and internal validation was performed well. Our findings suggest that the predictive model built and based on the immune cell scRNA-seq will enable us to judge the prognosis of patients with ccRCC and provide more accurate directions for basic relevant research and clinical practice. Hindawi 2023-03-07 /pmc/articles/PMC10014191/ /pubmed/36925653 http://dx.doi.org/10.1155/2023/5355269 Text en Copyright © 2023 Guanlin Wu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wu, Guanlin Guo, Weiming Zhu, Shuai Fan, Gang Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma |
title | Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma |
title_full | Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma |
title_fullStr | Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma |
title_full_unstemmed | Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma |
title_short | Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma |
title_sort | single-cell and transcriptome-based immune cell-related prognostic model in clear cell renal cell carcinoma |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10014191/ https://www.ncbi.nlm.nih.gov/pubmed/36925653 http://dx.doi.org/10.1155/2023/5355269 |
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