Identification of a seven-gene prognostic model for renal cell carcinoma associated with CD8+T lymphocyte cell
CD8+ T lymphocytes are important elements of the tumor microenvironment, hence their involvement in the development and progression of tumors is complex. Data on the precise tumor-infiltrating lymphocytes gene signature in renal cell carcinoma (RCC) remain limited. Therefore, this study created a tumor-infiltrating lymphocytes-related predictive model for patients with RCC using data from The Cancer Genome Atlas. The most important genes associated with CD8 + T lymphocytes were identified using weighted gene co-expression network analysis. Functional categories of important genes were revealed using gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes signaling pathway analyses. A CD8 + T lymphocyte-related prognostic model with 7 important genes was simultaneously created using the least absolute shrinkage and selection operator, univariate and multivariate Cox regressions, and the 7 genes were expressed particularly in CD8 + T lymphocytes according to single-cell sequencing data obtained from the Gene Expression Omnibus. This study identified a seven-gene prognostic model associated with CD8 + T lymphocytes that may significantly influence risk stratification in patients with RCC. The genes included in the model are apolipoprotein B mRNA editing catalytic polypeptide 3G, CD3 gamma, eomesodermin, protein tyrosine phosphatase, non-receptor type 7, signal regulatory protein gamma, Fas ligand, and T-cell immunoreceptor with Ig and ITIM domains.
Authors
- Jingbang Liu (ORCID: https://orcid.org/0009-0009-7598-356X)
- Tao Jiang (ORCID: https://orcid.org/0000-0002-3263-9971)
Institutions
- Dalian Medical University (CN)
- Second Affiliated Hospital of Dalian Medical University (CN)
Publication Details
- Journal
- Medicine
- Published
- 2024-10-04
- DOI
- https://doi.org/10.1097/md.0000000000039938
- Primary Topic
- Cancer Immunotherapy and Biomarkers
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China