Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma

Author:

Wu Guanlin1ORCID,Guo Weiming2ORCID,Zhu Shuai3ORCID,Fan Gang34ORCID

Affiliation:

1. School of Clinical Medicine, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China

2. The 2nd Affiliated Hospital of South China University, Hengyang 421001, China

3. Department of Urology, The Affiliated Cancer Hospital of Xiangya School of Medicine of Central South University, Hunan Cancer Hospital, Changsha 410013, Hunan, China

4. Department of Urology, Huazhong University of Science and Technology Union Shenzhen Hospital, The 6th Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen 518060, China

Abstract

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.

Funder

Guangdong Medical Research Foundation

Publisher

Hindawi Limited

Subject

Oncology

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