Identifying immune cells-related phenotype to predict immunotherapy and clinical outcome in gastric cancer.

ABSTRACT:

Background

The tumor microenvironment is mainly composed of tumor-infiltrating immune cells (TIICs), fibroblast, extracellular matrix, and secreted factors. TIICs are often associated with sensitivity to immunotherapy and the prognosis of multiple cancers, yet the predictive role of individual cells on tumor prognosis is limited.

Methods

Based on single-sample gene set enrichment analysis, we combined three Gene Expression Omnibus (GEO) cohorts to build a TIIC model for risk stratification and prognosis prediction. The performance of the TIIC model was validated using our clinical cohort and the TCGA cohort. To assess the predictive power of the TIIC model for immunotherapy, we plotted the receiver operating characteristic curve with the IMvigor210 and GSE135222 cohorts.

SUBMITTER: Jiang S 

PROVIDER: S-EPMC9402937 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature