Comprehensive analysis of single-cell and bulk RNA sequencing data reveals an EGFR signature for predicting immunotherapy response and prognosis in pan-cancer.

ABSTRACT:

Introduction

Immune checkpoint inhibitors (ICIs) have changed the paradigm of cancer treatment, but their effectiveness in some patients with epidermal growth factor receptor (EGFR) mutations is unsatisfactory. Therefore, it is necessary to develop a new biomarker for combined immunotherapy strategies to maximize the clinical benefits.

Methods

We collected and investigated 34 pan-cancer scRNA-Seq cohorts from The Cancer Genome Atlas (TCGA) and 10 bulk RNA-Seq cohorts utilizing multiple machine learning (ML) algorithms to identify and verify a representative EGFR-related gene signature (EGFR.Sig) as a predictive biomarker for immunotherapy response. Core genes were identified as Hub-EGFR.Sig to predict the prognosis of cancers and to understand the crosstalk between EGFR and

SUBMITTER: Ye C 

PROVIDER: S-EPMC12198250 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature