Department of Radiation Oncology, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou 350014, China.
Department of Pathology, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou 350014, China.
Comb Chem High Throughput Screen. 2022;25(12):2046-2058. doi: 10.2174/1386207325666220204140925.
Tumorigenesis, metastasis, and treatment response of hepatocellular carcinoma (HCC) are regulated by unfolded protein responses (UPR) signaling pathways, including IRE1a, PERK, and ATF6, but little is known about UPR related genes with HCC prognosis and therapeutic indicators.
We aimed to identify a UPR related prognostic signature (UPRRPS) for HCC and explore the potential effect of the current signature on the existing molecular targeted agents and immune checkpoint inhibitors (ICIs).
We used The Cancer Genome Atlas (TCGA) database to screen candidate UPR genes (UPRGs), which are expressed differentially between hepatocellular carcinoma and normal liver tissue and associated with prognosis. A gene risk score for overall survival prediction was established using the least absolute shrinkage and selection operator (LASSO) regression analysis, which was validated using data from the International Cancer Genome Consortium (ICGC) database and evaluated by the C-index. Then immune and molecular characteristics stratified by the current UPRRPS were analyzed, and the corresponding drug sensitivity was conducted.
Initially, 42 UPRGs from the TCGA database were screened as differentially expressed genes, which were also associated with HCC prognosis. Using the LASSO regression analysis, nine UPRGs (EXTL3, PPP2R5B, ZBTB17, EIF2S2, EIF2S3, HDGF, SRPRB, EXTL2, and TPP1) were used to develop a UPRRPS to predict the OS of HCC patients in the TCGA set with the Cindex of 0.763. The current UPRRPS was also well-validated in the ICGC set with the C-index of 0.700. Multivariate Cox regression analyses also confirmed that the risk score was an independent risk factor for HCC in both the TCGA and ICGC sets (both P<0.05). Functional analyses showed that low-risk score was associated with increased natural killer cells, T helpers, tumor immune dysfunction and exclusion score, microsatellite instability expression, and more benefit from ICIs; the high-risk score was associated with increased active dendritic cells, Tregs, T-cell exclusion score, and less benefit from ICIs. Gene set enrichment analyses showed that the signaling pathways of VEGF, MAPK, and mTOR were enriched in high UPRRPS, and the drug sensitivities of the corresponding inhibitors were all significantly higher in the high UPRRPS subgroup (all P<0.001).
With the current findings, UPRRPS was a promising biomarker for predicting the prognosis of HCC patients. UPRRPS might also be taken as a potential indicator to guide the management of immune checkpoint inhibitors and molecular targeted agents.
肿瘤发生、转移和肝细胞癌（HCC）的治疗反应受未折叠蛋白反应（UPR）信号通路调节，包括 IRE1a、PERK 和 ATF6，但对于与 HCC 预后和治疗指标相关的 UPR 相关基因知之甚少。
本研究旨在鉴定与 HCC 相关的 UPR 预后签名（UPRRPS），并探讨该签名对现有分子靶向药物和免疫检查点抑制剂（ICIs）的潜在影响。
我们使用癌症基因组图谱（TCGA）数据库筛选候选 UPR 基因（UPRGs），这些基因在肝癌和正常肝组织之间表达差异，并与预后相关。使用最小绝对收缩和选择算子（LASSO）回归分析建立用于总体生存预测的基因风险评分，该评分使用国际癌症基因组联盟（ICGC）数据库的数据进行验证，并通过 C 指数进行评估。然后分析当前 UPRRPS 分层的免疫和分子特征，并进行相应的药物敏感性分析。
最初，从 TCGA 数据库中筛选出 42 个 UPRGs 作为差异表达基因，这些基因也与 HCC 预后相关。使用 LASSO 回归分析，使用 9 个 UPRGs（EXTL3、PPP2R5B、ZBTB17、EIF2S2、EIF2S3、HDGF、SRPRB、EXTL2 和 TPP1）开发了一个 UPRRPS 来预测 TCGA 组 HCC 患者的 OS，C 指数为 0.763。当前的 UPRRPS 在 ICGC 组中也得到了很好的验证，C 指数为 0.700。多变量 Cox 回归分析也证实，风险评分是 TCGA 和 ICGC 两组中 HCC 的独立危险因素（均 P<0.05）。功能分析表明，低风险评分与自然杀伤细胞、辅助性 T 细胞、肿瘤免疫功能障碍和排除评分增加、微卫星不稳定性表达增加以及对 ICIs 更有益相关；高风险评分与活性树突状细胞、Tregs、T 细胞排除评分增加以及对 ICIs 获益减少相关。基因集富集分析表明，高 UPRRPS 组中 VEGF、MAPK 和 mTOR 信号通路富集，相应抑制剂的药物敏感性在高 UPRRPS 亚组中均显著升高（均 P<0.001）。
根据目前的研究结果，UPRRPS 是预测 HCC 患者预后的有前途的生物标志物。UPRRPS 也可能作为潜在指标，指导免疫检查点抑制剂和分子靶向药物的管理。
