Unraveling heterogeneity in LUAD via multi-omics integration: molecular classification and therapeutic implications.

ABSTRACT: Lung adenocarcinoma (LUAD) displays significant morphological and molecular heterogeneity both within and between tumors. This heterogeneity, coupled with the complexities of the tumor microenvironment (TME), notably influences LUAD progression and patient prognosis. Integrating mass-spectrometry-based proteomic data from human tumors with corresponding multi-omics data opens significant opportunities for comprehensive and systematic cancer proteogenomic analyses. In our study, we analyzed LUAD proteogenomic data from the Cancer Proteome Atlas Program (CPTAC) to conduct a systematic molecular classification by integrating multi-omics data (genomic, transcriptomic, and proteomic) using ten clustering algorithms. This approach successfully identified three distinct molecular subtypes with no

SUBMITTER: Zhen S 

PROVIDER: S-EPMC12923723 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature