The study analysed the transcriptome data and clinical data of LUAD patients in The Cancer Genome Atlas (TCGA) database, gene co-expression, and univariate Cox regression methods were used to screen for DRGs-lncRNAs related to prognosis. The risk score model of lncRNA was established by univariate and multivariate Cox regression models. TIMER, CIBERSORT, CIBERSORT-ABS, and other methods were used to analyze immune infiltration and further evaluate immune function analysis, immune checkpoints, and drug sensitivity. Real-time polymerase chain reaction (RT-PCR) was performed to detect the expression of DRGs-lncRNAs in LUAD cell lines.
A total of 108 lncRNAs significantly associated with disulfidptosis were identified. A prognostic model was constructed by screening 10 lncRNAs with independent prognostic significance through single-factor Cox regression analysis, LASSO regression analysis, and multiple-factor Cox regression analysis. Survival analysis of patients through the prognostic model showed that there were obvious survival differences between the high- and low-risk groups. The risk score of the prognostic model can be used as an independent prognostic factor independent of other clinical traits, and the risk score increases with stage. Further analysis showed that the prognostic model was also different from tumor immune cell infiltration, immune function, and immune checkpoint genes in the high- and low-risk groups. Chemotherapy drug susceptibility analysis showed that high-risk patients were more sensitive to Paclitaxel, 5-Fluorouracil, Gefitinib, Docetaxel, Cytarabine, and Cisplatin. Additionally, RT-PCR analysis demonstrated differential expression of DRGs-lncRNAs between LUAD cell lines and the human bronchial epithelial cell line.
The prognostic model of DRGs-lncRNAs constructed in this study has certain accuracy and reliability in predicting the survival prognosis of LUAD patients, and provides clues for the interaction between disulfidptosis and LUAD immunotherapy.
方法:该研究分析了癌症基因组图谱(TCGA)数据库中LUAD患者的转录组数据和临床数据,基因共表达,和单变量Cox回归方法用于筛选与预后相关的DRGs-lncRNAs。通过单因素和多因素Cox回归模型建立lncRNA的风险评分模型。TIMER,CIBERSORT,CIBERSORT-ABS,等方法进行免疫浸润分析,进一步评价免疫功能,免疫检查点,和药物敏感性。进行实时聚合酶链反应(RT-PCR)以检测LUAD细胞系中DRGs-lncRNAs的表达。
结果:共鉴定出108个与二硫键凋亡显著相关的lncRNAs。通过单因素Cox回归分析筛选10个具有独立预后意义的lncRNAs构建预后模型,LASSO回归分析,和多因素Cox回归分析。通过预后模型对患者进行生存分析,结果显示高危组和低危组之间存在明显的生存差异。预后模型的风险评分可以作为独立于其他临床特征的独立预后因素,风险分数随着阶段的增加而增加。进一步分析表明,预后模型也不同于肿瘤免疫细胞浸润,免疫功能,以及高危和低危人群的免疫检查点基因。化疗药物敏感性分析显示高危患者对紫杉醇较敏感,5-氟尿嘧啶,吉非替尼,多西他赛,阿糖胞苷,和顺铂。此外,RT-PCR分析证明了LUAD细胞系和人支气管上皮细胞系之间DRGs-lncRNAs的差异表达。
结论:本研究构建的DRGs-lncRNAs预后模型在预测LUAD患者生存预后方面具有一定的准确性和可靠性。并为二硫键增多症与LUAD免疫治疗之间的相互作用提供线索。