Analysis of Genomic and Transcriptomic Variations as Prognostic Signature for Lung Adenocarcinoma

TL;DR

This study developed a 12-gene prognostic signature for lung adenocarcinoma using integrated genomic and transcriptomic data, effectively predicting patient survival and stratifying risk groups.

Contribution

It introduces a novel multi-omics based 12-gene signature for LUAD prognosis, validated across datasets, enhancing personalized risk assessment.

Findings

The 12-gene signature significantly differentiates high-risk and low-risk patient groups.

Patients classified as high-risk have notably shorter survival times.

The signature serves as a potential tool for clinical prognosis in LUAD.

Abstract

Lung cancer is the leading cause of the largest number of deaths worldwide and lung adenocarcinoma (LUAD) is the most common form of lung cancer. In this study, we carried out an integrated meta-analysis of the mutations including single-nucleotide variations (SNVs), the copy number variations (CNVs), RNA-seq and clinical data of patients with LUAD downloaded from The Cancer Genome Atlas (TCGA). We integrated significant SNV and CNV genes, differentially expressed genes (DEGs) and the DEGs in active subnetworks to construct a prognosis signature. Cox proportional hazards model (LOOCV) with Lasso penalty was used to identify the best gene signature among different gene categories. The patients in both training and test data were clustered into high-risk and low-risk groups by using risk scores of the patients calculated based on selected gene signature. We generated a 12-gene signature (DEPTOR, ZBTB16, BCHE, MGLL, MASP2, TNNI2, RAPGEF3, SGK2, MYO1A, CYP24A1, PODXL2, CCNA1) for overall survival prediction. The survival time of high-risk and low-risk groups was significantly different. This 12-gene signature could predict prognosis and they are potential predictors for the survival of the patients with LUAD.