A Novel Computational Framework for Predicting the Survival of Cancer Patients With PD-1/PD-L1 Checkpoint Blockade Therapy.

ABSTRACT:

Background

Immune checkpoint inhibitors (ICIs) induce durable responses, but only a minority of patients achieve clinical benefits. The development of gene expression profiling of tumor transcriptomes has enabled identifying prognostic gene expression signatures and patient selection with targeted therapies.

Methods

Immune exclusion score (IES) was built by elastic net-penalized Cox proportional hazards (PHs) model in the discovery cohort and validated via four independent cohorts. The survival differences between the two groups were compared using Kaplan-Meier analysis. Both GO and KEGG analyses were performed for functional annotation. CIBERSORTx was also performed to estimate the relative proportion of immune-cell types.

Results

A fifteen-genes immune exclus

SUBMITTER: Su X 

PROVIDER: S-EPMC9271954 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature