Identification of a Prognostic Model Based on Immune Cell Signatures in Clear Cell Renal Cell Carcinoma.

ABSTRACT:

Background

Accumulating evidence substantiated that the immune cells were intricately intertwined with the prognosis and therapy of clear cell renal cell carcinoma (ccRCC). We aimed to construct an immune cell signatures (ICS) score model to predict the prognosis of ccRCC patients and furnish guidance for finding appropriate treatment strategies.

Methods

Based on The Cancer Genome Atlas (TCGA) database, the normalized enrichment score (NES) of 184 ICSf was calculated using single-sample gene set enrichment analysis (ssGSEA). An ICS score model was generated in light of univariate Cox regression and Least absolute shrinkage and selection operator (Lasso)-Cox regression, which was independently validated in ArrayExpress database. In addition, we appraised the predictive power

SUBMITTER: Shi X 

PROVIDER: S-EPMC9427244 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature