Signatures of Multi-Omics Reveal Distinct Tumor Immune Microenvironment Contributing to Immunotherapy in Lung Adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) contains a variety of genomic and epigenomic abnormalities; the effective tumor markers related to these abnormalities need to be further explored.
Methods: Clustering analysis was performed based on DNA methylation (MET), DNA copy number variation (CNV), and mRNA expression data, and the differences in survival and tumor immune microenvironment (TIME) between subtypes were compared. Further, we evaluated the signatures in terms of both prognostic value and immunological characteristics.
Results: There was a positive correlation between MET and CNV in LUAD. Integrative analysis of multi-omics data from 443 samples determined molecular subtypes, iC1 and iC2. The fractions of CD8+ T cells and activated CD4+ T cells were higher, the fraction of Tregs was lower, and the expression level of programmed death-ligand 1 (PD-L1) was higher in iC2 with a poor prognosis showing a higher TIDE score. We selected PTTG1 , SLC2A1 , and FAM83A as signatures of molecular subtypes to build a prognostic risk model and divided patients into high-risk group and low-risk group representing poor prognosis and good prognosis, respectively, which were validated in 180 patients with LUAD. Further, the low-risk group with lower TIDE score had more infiltrating immune cells. In 100 patients with LUAD, the high-risk group with an immunosuppressive state had a higher expression of PD-L1 and lower counts of CD8+ T cells and dendritic cells.
Conclusions: These findings demonstrated that combined multi-omics data could determine molecular subtypes with significant differences of prognosis and TIME in LUAD and suggested potent utility of the signatures to guide immunotherapy.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2021 Huang, Li, Guo, Wu, Kou and Yang.)