Ma Di, Yang Yuchen, Cai Qiang, Ye Feng, Deng Xiaxing, Shen Baiyong
Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shanghai Key Laboratory of Translational Reseach for Pancreatic Neoplasms, Research Institute of Pancreatic Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Front Genet. 2022 Sep 14;13:973444. doi: 10.3389/fgene.2022.973444. eCollection 2022.
Pancreatic cancer is one major digestive malignancy with a poor prognosis. Given the clinical importance of lncRNAs, developing a novel molecular panel with lncRNAs for pancreatic cancer has great potential. As a result, an 8-lncRNA-based robust prognostic signature was constructed using a random survival forest model after examing the expression profile and prognostic significance of lncRNAs in the PAAD cohort from TCGA. The efficacy and effectiveness of the lncRNA-based signature were thoroughly assessed. Patients with high- and low-risk defined by the signature underwent significantly distinct OS expectancy. Most crucially the training group's AUCs of ROC approached 0.90 and the testing group similarly had the AUCs above 0.86. The lncRNA-based signature was shown to behave as a prognostic indicator of pancreatic cancer, either alone or simultaneously with other factors, after combined analysis with other clinical-pathological factors in Cox regression and nomogram. Additionally, using GSEA and CIBERSORT scoring methods, the immune landscape and variations in biological processes between high- and low-risk subgroups were investigated. Last but not least, drug databases were searched for prospective therapeutic molecules targeting high-risk patients. The most promising compound were Afatinib, LY-303511, and RO-90-7501 as a result. In conclusion, we developed a novel lncRNA based prognostic signature with high efficacy to stratify high-risk pancreatic cancer patients and screened prospective responsive drugs for targeting strategy.
胰腺癌是一种预后较差的主要消化系统恶性肿瘤。鉴于长链非编码RNA(lncRNAs)的临床重要性,开发一种包含lncRNAs的新型胰腺癌分子标志物具有巨大潜力。因此,在研究了来自TCGA的PAAD队列中lncRNAs的表达谱和预后意义后,使用随机生存森林模型构建了一种基于8个lncRNA的稳健预后特征。对基于lncRNA的特征的有效性和效能进行了全面评估。由该特征定义的高风险和低风险患者的总生存期预期明显不同。最关键的是,训练组的ROC曲线下面积(AUC)接近0.90,测试组的AUC同样高于0.86。在与其他临床病理因素进行Cox回归和列线图联合分析后,基于lncRNA的特征被证明可单独或与其他因素同时作为胰腺癌的预后指标。此外,使用基因集富集分析(GSEA)和CIBERSORT评分方法,研究了高风险和低风险亚组之间的免疫格局和生物学过程变化。最后但同样重要的是,在药物数据库中搜索针对高风险患者的潜在治疗分子。结果显示最有前景的化合物是阿法替尼、LY-303511和RO-90-7501。总之,我们开发了一种基于lncRNA的新型高效预后特征,用于对高风险胰腺癌患者进行分层,并筛选出用于靶向治疗策略的潜在敏感药物。