Integrated Analysis of MATH-Based Subtypes Reveals a Novel Screening Strategy for Early-Stage Lung Adenocarcinoma.

ABSTRACT: Lung adenocarcinoma (LUAD) is a frequently diagnosed cancer type, and many patients have already reached an advanced stage when diagnosed. Thus, it is crucial to develop a novel and efficient approach to diagnose and classify lung adenocarcinoma at an early stage. In our study, we combined in silico analysis and machine learning to develop a new five-gene-based diagnosis strategy, which was further verified in independent cohorts and in vitro experiments. Considering the heterogeneity in cancer, we used the MATH (mutant-allele tumor heterogeneity) algorithm to divide patients with early-stage LUAD into two groups (C1 and C2). Specifically, patients in C2 had lower intratumor heterogeneity and higher abundance of immune cells (including B cell, CD4 T cell, CD8 T cell, macropha

SUBMITTER: Li C 

PROVIDER: S-EPMC8861524 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature