Establishment of liquid-liquid phase separation-related prognostic model in lung adenocarcinoma and systematic analysis of its clinical significance.

Abstract

Purpose: To detect the prognostic importance of liquid-liquid phase separation (LLPS) in lung adenocarcinoma.

Methods: The gene expression files, copy number variation data, and clinical data were downloaded from The Cancer Genome Atlas cohort. LLPS-related genes were acquired from the DrLLPS website. The prognostic model based on LLPS was constructed by the Cox regression and LASSO regression analyses after the identification of LLPS-related differentially expressed genes (DEGs). Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed. The LLPS-related prognostic risk score was validated by GSE31210 and GSE72094. The overall survival of lung adenocarcinoma patients was predicted by plotting a nomogram. The biological features of the high-risk lung adenocarcinoma were evaluated by the CIBERSORT, ESTIMATE, Gene Set Variation Analysis, and Genomics of Drug Sensitivity in Cancer. Reverse transcription-quantitative polymerase chain reaction detected hub gene expression.

Results: A total of 91 DEGs were screened out in LLPS, among which 9 genes were discovered as prognostic biomarkers of lung adenocarcinoma. GRIA1, CRTAC1, MAGEA4, and MAPK4 were identified as hub genes by the LASSO Cox regression analysis. High-risk and low-risk groups were divided according to the risk index, with the high-risk group displaying a markedly worse outcome. CRTAC1 expression was significantly decreased, MAGEA4 and MAPK4 expressions were increased, while GRIA1 expression was altered in lung adenocarcinoma cells. Tumor microenvironment, signaling pathway enrichment, and drug sensitivity significantly differed between different risk groups.

Conclusions: This work proposed a prognostic tool based on the LLPS-related gene signature to offer prospective and effective biomarkers for lung adenocarcinoma prognosis.