Multi-omics integration and machine learning identify NPC2 as a prognostic and treatment-responsive regulator in lung adenocarcinoma.

ABSTRACT:

Background

This study aims to define a novel molecular subtype of LUAD by integrating multiple omics data. Additionally, we develop and validate an Artificial Intelligence Derived Prognostic Index (AIDPI) that predicts the prognosis of LUAD patients, identifies potential therapeutic targets.

Methods

This study employed ten clustering algorithms from the R package "MOVICS" to integrate multi-omics data of LUAD sourced from TCGA database for molecular typing. Subsequently, an Artificial Intelligence Derived Prognostic Index (AIDPI) was constructed as the most effective indicator for predicting the overall survival rate of LUAD patients. The biological functions and mechanisms of NPC2 in lung adenocarcinoma were elucidated through both in vitro and in vivo experim

SUBMITTER: Li A 

PROVIDER: S-EPMC12855401 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature