Chen Yan, Huang Cheng, Wei Wei
Department of Respiratory and Critical Care Medicine, Anyue County People's Hospital, Anyue, China.
Int J Biol Markers. 2025 Mar;40(1):12-23. doi: 10.1177/03936155241310887. Epub 2025 Jan 10.
PurposeTo detect the prognostic importance of liquid-liquid phase separation (LLPS) in lung adenocarcinoma.MethodsThe 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.ResultsA total of 91 DEGs were screened out in LLPS, among which 9 genes were discovered as prognostic biomarkers of lung adenocarcinoma. , , , and 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.ConclusionsThis work proposed a prognostic tool based on the LLPS-related gene signature to offer prospective and effective biomarkers for lung adenocarcinoma prognosis.
检测液-液相分离（LLPS）在肺腺癌中的预后重要性。
从癌症基因组图谱队列下载基因表达文件、拷贝数变异数据和临床数据。LLPS相关基因从DrLLPS网站获取。在鉴定出LLPS相关差异表达基因（DEG）后，通过Cox回归和LASSO回归分析构建基于LLPS的预后模型。进行基因本体功能和京都基因与基因组百科全书富集分析。通过GSE31210和GSE72094验证LLPS相关的预后风险评分。通过绘制列线图预测肺腺癌患者的总生存期。通过CIBERSORT、ESTIMATE、基因集变异分析和癌症药物敏感性基因组学评估高危肺腺癌的生物学特征。逆转录定量聚合酶链反应检测枢纽基因表达。
在LLPS中共筛选出91个DEG，其中9个基因被发现为肺腺癌的预后生物标志物。通过LASSO Cox回归分析鉴定出 、 、 和 为枢纽基因。根据风险指数分为高危组和低危组，高危组预后明显较差。CRTAC1表达在肺腺癌细胞中显著降低，MAGEA4和MAPK4表达增加，而GRIA1表达发生改变。不同风险组之间的肿瘤微环境、信号通路富集和药物敏感性存在显著差异。
本研究基于LLPS相关基因特征提出了一种预后工具，为肺腺癌预后提供前瞻性和有效的生物标志物。
