Zhang Shuqiao, Li Xinyu, Zheng Yilu, Hu Hao, Liu Jiahui, Zhang Shijun, Tang Chunzhi, Mo Zhuomao, Kuang Weihong
First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Medical College of Acupuncture-Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Curr Protein Pept Sci. 2023;24(8):666-683. doi: 10.2174/1389203724666230816090504.
To reveal the prognostic role of unfolded protein response (UPR) -related genes in hepatocellular carcinoma (HCC).
Hepatocellular carcinoma is a genetically heterogeneous tumor, and the prediction of its prognosis remains a challenge. Studies elucidating the molecular mechanisms of UPR have rapidly increased. However, the UPR molecular subtype characteristics of the related genes in HCC progression have yet to be thoroughly studied.
Conducting a comprehensive assessment of the prognostic signature of genes related to the UPR in patients with HCC can advance our understanding of the cellular processes contributing to the progression of HCC and offer innovative strategies in precise therapy.
Based on the gene expression profiles associated with UPR in HCC, we explored the molecular subtypes mediated by UPR-related genes and constructed a UPR-related genes signature that could precisely predict the prognosis for HCC.
Using microarray data of HCC patients, differentially expressed UPR-related genes (DEGs) were discovered in malignancies and normal tissues. The HCC was classified into two molecular subtypes by the NMF algorithm based on DEGs modification of the UPR. Moreover, we developed a UPR-related model for predicting HCC patients' prognosis. The robustness of the UPR- related model was confirmed in external validation. Moreover, we analyzed immune responses in different risk groups. Analysis of immune functions revealed that Treg, Macrophages, aDCs, and MHC class-I were significantly up-regulated in high-risk HCC. At the same time, cytolytic activity and type I and II INF response were higher in a low-risk subgroup.
This study identified two UPR molecular subtypes of HCC and developed a ten-gene HCC prognostic signature model (EXTL3, PPP2R5B, ZBTB17, CCT3, CCT4, CCT5, GRPEL2, HSP90AA1, PDRG1, and STC2), which can robustly forecast the progression of HCC.
揭示未折叠蛋白反应（UPR）相关基因在肝细胞癌（HCC）中的预后作用。
肝细胞癌是一种基因异质性肿瘤，其预后预测仍然是一项挑战。阐明UPR分子机制的研究迅速增加。然而，HCC进展中相关基因的UPR分子亚型特征尚未得到充分研究。
对HCC患者中与UPR相关基因的预后特征进行全面评估，可增进我们对导致HCC进展的细胞过程的理解，并为精准治疗提供创新策略。
基于HCC中与UPR相关的基因表达谱，我们探索了由UPR相关基因介导的分子亚型，并构建了一个能够精确预测HCC预后的UPR相关基因特征。
利用HCC患者的微阵列数据，在恶性肿瘤和正常组织中发现了差异表达的UPR相关基因（DEGs）。基于UPR的DEGs修饰，通过非负矩阵分解（NMF）算法将HCC分为两种分子亚型。此外，我们开发了一种用于预测HCC患者预后的UPR相关模型。UPR相关模型的稳健性在外部验证中得到证实。此外，我们分析了不同风险组中的免疫反应。免疫功能分析显示，高危HCC中调节性T细胞（Treg）、巨噬细胞、浆细胞样树突状细胞（aDCs）和MHC I类分子显著上调。同时，低风险亚组中的细胞溶解活性以及I型和II型干扰素反应更高。
本研究确定了HCC的两种UPR分子亚型，并开发了一种十基因的HCC预后特征模型（EXTL3、PPP2R5B、ZBTB17、CCT3、CCT4、CCT5、GRPEL2、HSP90AA1、PDRG1和STC2），该模型能够可靠地预测HCC的进展。
