肝细胞癌
免疫疗法
免疫系统
医学
癌症研究
肿瘤微环境
肿瘤科
抗药性
内科学
免疫学
生物
微生物学
作者
Kequan Xu,Caixia Dai,Jialing Yang,Jia Xu,Chuqi Xia,Yueping Liu,Cheng Zhang,Ning Xu,Taihu Wu
标识
DOI:10.1016/j.compbiomed.2024.107930
摘要
Hepatocellular carcinoma (HCC) is associated with a high mortality rate, where resistance to immunotherapy and chemotherapy plays a crucial role. A newly identified form of cell death called disulfidptosis shows promise, but its biological mechanism in HCC remains uncertain. In this study, a prognostic model was developed for Disulfidptosis-related long non-coding RNAs (DRLs) from 370 HCC patients sourced from TCGA-LIHC, utilizing five key features: AC026356.1, AC073254.1, PXN-AS1 expression, AC026412.3, and AC099066.2. High-risk HCC patients had lower survival, CD4+ T cell infiltration, and elevated immune checkpoint gene expression. Furthermore, based on the features of DRLs, HCC was classified into three subtypes. Notably, patients belonging to different subtypes demonstrated varying overall survival rates, immune cell infiltration patterns, and sensitivity to immune therapy. Moreover, the novel DRL AC026412.3 (HR = 40.207) emerged as the most significant prognostic factor, exhibiting high expression across all HCC cells. Elevated expression of AC026412.3 promoted HCC cell proliferation and induced resistance to gefitinib. In conclusion, we have discovered five DRLs and constructed a prognostic risk model. Our findings validate the correlation between DRL-related prognostic models, tumor subtypes, and the HCC immune microenvironment along with its implications for immunotherapy. Moreover, further investigation into the molecular mechanisms of key biomarkers like AC026412.3 in the future will contribute significantly to advancing our comprehension of HCC's pathogenesis and drug resistance mechanisms.
科研通智能强力驱动
Strongly Powered by AbleSci AI