Pan-cancer analysis reveals CCL5/CSF2 as potential predictive biomarkers for immune checkpoint inhibitors.

ABSTRACT:

Background

Currently, there are no optimal biomarkers available for distinguishing patients who will respond to immune checkpoint inhibitors (ICIs) therapies. Consequently, the exploration of novel biomarkers that can predict responsiveness to ICIs is crucial in the field of immunotherapy.

Methods

We estimated the proportions of 22 immune cell components in 10 cancer types (6,128 tumors) using the CIBERSORT algorithm, and further classified patients based on their tumor immune cell proportions in a pan-cancer setting using k-means clustering. Differentially expressed immune genes between the patient subgroups were identified, and potential predictive biomarkers for ICIs were explored. Finally, the predictive value of the identified biomarkers was verified in patients with ur

SUBMITTER: Chen YC 

PROVIDER: S-EPMC11389493 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature