Immune landscape of advanced gastric cancer tumor microenvironment identifies immunotherapeutic relevant gene signature.

ABSTRACT:

Background

Advanced gastric cancer (AGC) is a disease with poor prognosis due to the current lack of effective therapeutic strategies. Immune checkpoint blockade treatments have shown effective responses in patient subgroups but biomarkers remain challenging. Traditional classification of gastric cancer (GC) is based on genomic profiling and molecular features. Therefore, it is critical to identify the immune-related subtypes and predictive markers by immuno-genomic profiling.

Methods

Single-sample gene-set enrichment analysis (ssGSEA) and ESTIMATE algorithm were used to identify the immue-related subtypes of AGC in two independent GEO datasets. Weighted gene co-expression network analysis (WGCNA) and Molecular Complex Detection (MCODE) algorithm were applied to identify hub

SUBMITTER: Zhang S 

PROVIDER: S-EPMC8665569 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature