The Key Laboratory of Adolescent Health Assessment and Exercise Intervention of the Ministry of Education, East China Normal University, 500 Dongchuan Road, Shanghai, 200241, People's Republic of China.
Department of Veterinary Medicine, Shandong Vocational Animal Science and Veterinary College, Weifang, 261071, Shandong, People's Republic of China.
Sci Rep. 2024 Feb 22;14(1):4354. doi: 10.1038/s41598-024-54115-8.
Disulfidptosis a new cell death mode, which can cause the death of Hepatocellular Carcinoma (HCC) cells. However, the significance of disulfidptosis-related Long non-coding RNAs (DRLs) in the prognosis and immunotherapy of HCC remains unclear. Based on The Cancer Genome Atlas (TCGA) database, we used Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression model to construct DRL Prognostic Signature (DRLPS)-based risk scores and performed Gene Expression Omnibus outside validation. Survival analysis was performed and a nomogram was constructed. Moreover, we performed functional enrichment annotation, immune infiltration and drug sensitivity analyses. Five DRLs (AL590705.3, AC072054.1, AC069307.1, AC107959.3 and ZNF232-AS1) were identified to construct prognostic signature. DRLPS-based risk scores exhibited better predictive efficacy of survival than conventional clinical features. The nomogram showed high congruence between the predicted survival and observed survival. Gene set were mainly enriched in cell proliferation, differentiation and growth function related pathways. Immune cell infiltration in the low-risk group was significantly higher than that in the high-risk group. Additionally, the high-risk group exhibited higher sensitivity to Afatinib, Fulvestrant, Gefitinib, Osimertinib, Sapitinib, and Taselisib. In conclusion, our study highlighted the potential utility of the constructed DRLPS in the prognosis prediction of HCC patients, which demonstrated promising clinical application value.
二硫键程序性细胞死亡是一种新的细胞死亡方式,可导致肝癌(HCC)细胞死亡。然而,二硫键程序性细胞死亡相关长非编码 RNA(DRLs)在 HCC 预后和免疫治疗中的意义尚不清楚。本研究基于癌症基因组图谱(TCGA)数据库,采用最小绝对收缩和选择算子(LASSO)和 Cox 回归模型构建基于 DRL 预后特征(DRLPS)的风险评分,并进行基因表达综合数据库外部验证。进行生存分析并构建列线图。此外,我们进行了功能富集注释、免疫浸润和药物敏感性分析。鉴定出 5 个 DRL(AL590705.3、AC072054.1、AC069307.1、AC107959.3 和 ZNF232-AS1)构建预后特征。基于 DRLPS 的风险评分在预测生存方面优于传统临床特征。列线图显示预测生存与观察生存之间具有高度一致性。基因集主要富集在与细胞增殖、分化和生长功能相关的途径中。低风险组的免疫细胞浸润明显高于高风险组。此外,高危组对阿法替尼、氟维司群、吉非替尼、奥希替尼、萨替利昔单抗和塔西利昔单抗的敏感性更高。总之,本研究强调了构建的 DRLPS 在 HCC 患者预后预测中的潜在应用价值,具有有前景的临床应用价值。
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