Zhang Facai, Feng Dechao, Wang Xiaoming, Gu Yiwei, Shen Zhiyong, Yang Yubo, Wang Jiahao, Zhong Quliang, Li Dengxiong, Hu Huan, Han Ping
Department of Urology/Institute of Urology, West China Hospital, Sichuan University, Sichuan, China.
Department of Urology, the Affiliated Hospital of Guizhou Medical University, Guizhou, China.
Front Mol Biosci. 2021 Dec 23;8:780329. doi: 10.3389/fmolb.2021.780329. eCollection 2021.
The unfolded protein response (UPR) plays a significant role in maintaining protein hemostasis in tumor cells, which are crucial for tumor growth, invasion, and resistance to therapy. This study aimed to develop a UPR-related signature and explore its correlation with immunotherapy and chemotherapy in bladder cancer. The differentially expressed UPR-related genes were put into Lasso regression to screen out prognostic genes, which constituted the UPR signature, and were incorporated into multivariate Cox regression to generate risk scores. Subsequently, the predictive performance of this signature was estimated by receiver operating characteristic (ROC) curves. The CIBERSORTx, the maftool, and Gene set enrichment analysis (GSEA) were applied to explore infiltrated immune cells, tumor mutational burden (TMB), and enriched signaling pathways in both risk groups, respectively. Moreover, The Cancer Immunome Atlas (TCIA) and Genomics of Drug Sensitivity in Cancer (GDSC) databases were used to predict responses to chemotherapy and immunotherapy. Twelve genes constituted the UPR-related signature. Patients with higher risk scores had worse overall survival (OS) in training and three validation sets. The UPR-related signature was closely correlated with clinicopathologic parameters and could serve as an independent prognostic factor. M0 macrophages showed a significantly infiltrated difference in both risk groups. TMB analysis showed that the risk score in the wild type and mutation type of FGFR3 was significantly different. GSEA indicated that the immune-, extracellular matrix-, replication and repair associated pathways belonged to the high risk group and metabolism-related signal pathways were enriched in the low risk group. Prediction of immunotherapy and chemotherapy revealed that patients in the high risk group might benefit from chemotherapy, but had a worse response to immunotherapy. Finally, we constructed a predictive model with age, stage, and UPR-related risk score, which had a robustly predictive performance and was validated in GEO datasets. We successfully constructed and validated a novel UPR-related signature in bladder cancer, which could robustly predict survival outcomes and closely correlate with the response to immunotherapy and chemotherapy in bladder cancer.
未折叠蛋白反应(UPR)在维持肿瘤细胞内蛋白质稳态中发挥着重要作用,而蛋白质稳态对肿瘤生长、侵袭及治疗抵抗至关重要。本研究旨在构建一个与UPR相关的特征,并探究其与膀胱癌免疫治疗和化疗的相关性。将差异表达的UPR相关基因进行Lasso回归分析以筛选出预后基因,这些基因构成了UPR特征,并纳入多因素Cox回归分析以生成风险评分。随后,通过受试者工作特征(ROC)曲线评估该特征的预测性能。应用CIBERSORTx、maftool和基因集富集分析(GSEA)分别探究两个风险组中浸润的免疫细胞、肿瘤突变负荷(TMB)及富集的信号通路。此外,利用癌症免疫图谱(TCIA)和癌症药物敏感性基因组学(GDSC)数据库预测化疗和免疫治疗反应。12个基因构成了UPR相关特征。在训练集和3个验证集中,风险评分较高的患者总生存期(OS)较差。UPR相关特征与临床病理参数密切相关,可作为独立的预后因素。M0巨噬细胞在两个风险组中均表现出显著的浸润差异。TMB分析显示,FGFR3野生型和突变型中的风险评分存在显著差异。GSEA表明,免疫、细胞外基质、复制和修复相关通路属于高风险组,而代谢相关信号通路在低风险组中富集。免疫治疗和化疗预测显示,高风险组患者可能从化疗中获益,但对免疫治疗反应较差。最后,我们构建了一个包含年龄、分期和UPR相关风险评分的预测模型,该模型具有强大的预测性能,并在GEO数据集中得到验证。我们成功构建并验证了一种新型的膀胱癌UPR相关特征,该特征能够可靠地预测生存结果,并与膀胱癌免疫治疗和化疗反应密切相关。