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内质网应激相关特征预测肝细胞癌的预后和免疫特征。

Endoplasmic Reticulum Stress-Related Signature for Predicting Prognosis and Immune Features in Hepatocellular Carcinoma.

机构信息

Department of Blood Transfusion, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Department of Pathology, Zhengzhou YIHE Hospital, Zhengzhou, China.

出版信息

J Immunol Res. 2022 Aug 14;2022:1366508. doi: 10.1155/2022/1366508. eCollection 2022.

Abstract

Hepatocellular carcinoma (HCC) with cancer cells under endoplasmic reticulum (ER) stress has a poor prognosis. This study is aimed at discovering credible biomarkers for predicting the prognosis of HCC based on ER stress-related genes (ERSRGs). We constructed a novel four-ERSRG prognostic risk model, including PON1, AGR2, SSR2, and TMCC1, through a series of bioinformatic approaches, which can accurately predict survival outcomes in HCC patients. Higher risk scores were linked to later grade, recurrence, advanced TNM stage, later T stage, and HBV infection. In addition, 20 fresh frozen tumors and normal tissues from HCC patients were collected and used to validate the genes expressed in the signature by qRT-PCR and immunohistochemical (IHC) assays. Moreover, we found the ER stress-related signature could reflect the infiltration levels of different immune cells in the tumor microenvironment (TME) and forecast the efficacy of immune checkpoint inhibitor (ICI) treatment. Finally, we created a nomogram incorporating this ER stress-related signature. In conclusion, our constructed four-gene risk model associated with ER stress can accurately predict survival outcomes in HCC patients, and the model's risk score is associated with the poor clinical classification.

摘要

肝细胞癌 (HCC) 中的癌细胞处于内质网 (ER) 应激状态时,预后较差。本研究旨在通过 ER 应激相关基因 (ERSRG) 发现可靠的生物标志物,以预测 HCC 的预后。我们通过一系列生物信息学方法构建了一个新的四 ERSRG 预后风险模型,包括 PON1、AGR2、SSR2 和 TMCC1,该模型可准确预测 HCC 患者的生存结局。较高的风险评分与更晚期的分级、复发、更晚期的 TNM 分期、更晚期的 T 分期和 HBV 感染有关。此外,我们收集了 20 例 HCC 患者的新鲜冷冻肿瘤和正常组织,并通过 qRT-PCR 和免疫组织化学 (IHC) 检测验证了该signature 中基因的表达。此外,我们发现 ER 应激相关 signature 可以反映肿瘤微环境 (TME) 中不同免疫细胞的浸润水平,并预测免疫检查点抑制剂 (ICI) 治疗的疗效。最后,我们创建了一个包含这个 ER 应激相关 signature 的列线图。总之,我们构建的与 ER 应激相关的四个基因风险模型可以准确预测 HCC 患者的生存结局,并且该模型的风险评分与较差的临床分级相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/9393196/3a0e071b79cb/JIR2022-1366508.001.jpg

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