Multi‑omics identification of a signature based on malignant cell-associated ligand-receptor genes for lung adenocarcinoma.

ABSTRACT:

Purpose

Lung adenocarcinoma (LUAD) significantly contributes to cancer-related mortality worldwide. The heterogeneity of the tumor immune microenvironment in LUAD results in varied prognoses and responses to immunotherapy among patients. Consequently, a clinical stratification algorithm is necessary and inevitable to effectively differentiate molecular features and tumor microenvironments, facilitating personalized treatment approaches.

Methods

We constructed a comprehensive single-cell transcriptional atlas using single-cell RNA sequencing data to reveal the cellular diversity of malignant epithelial cells of LUAD and identified a novel signature through a computational framework coupled with 10 machine learning algorithms. Our study further investigates the immunological c

SUBMITTER: Xu S 

PROVIDER: S-EPMC11395699 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature