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解析肝细胞癌中失巢凋亡相关基因与癌症相关成纤维细胞之间的关系。

Unraveling the relationship between anoikis-related genes and cancer-associated fibroblasts in liver hepatocellular carcinoma.

作者信息

Sun Meng, Bai Jiangtao, Wang Haisong, Li Mei, Zhou Long, Li Shanfeng

机构信息

Department of Interventional Vascular Surgery, Affiliated Hospital of Hebei University, Baoding, China.

出版信息

Heliyon. 2024 Jul 29;10(15):e35306. doi: 10.1016/j.heliyon.2024.e35306. eCollection 2024 Aug 15.

Abstract

This study intended to determine the molecular subtypes of liver hepatocellular carcinoma (LIHC) on the strength of anoikis-related genes (ARGs) and to assess their prognostic value and prospective relationship with immune cell infiltration and cancer-associated fibroblasts (CAFs). Univariate Cox regression analysis yielded 66 prognosis-related ARGs and classified LIHC into two distinct subtypes, with subtype A demonstrating overexpression of most prognosis-related ARGs and a significant survival disadvantage. Furthermore, a reliable prediction model was developed using ARGs to evaluate the risk of LIHC patients. This model served as an independent prognostic indicator and a quantitative tool for clinical prognostic prediction. Additionally, subtype-specific differences in immune cell infiltration were observed, and the risk score was potentially linked to immune-related characteristics. Moreover, the study identified a significant association between CAF score and LIHC prognosis, with a low CAF score indicating a favorable patient prognosis. In conclusion, this study reveals the molecular mechanisms underlying the development and progression of LIHC and identifies potential therapeutic targets for the disease.

摘要

本研究旨在基于失巢凋亡相关基因(ARGs)确定肝细胞癌(LIHC)的分子亚型,并评估其预后价值以及与免疫细胞浸润和癌症相关成纤维细胞(CAFs)的潜在关系。单因素Cox回归分析产生了66个与预后相关的ARGs,并将LIHC分为两种不同的亚型,其中A型显示大多数与预后相关的ARGs过表达且具有显著的生存劣势。此外,利用ARGs开发了一个可靠的预测模型来评估LIHC患者的风险。该模型可作为独立的预后指标和临床预后预测的定量工具。此外,观察到免疫细胞浸润存在亚型特异性差异,且风险评分可能与免疫相关特征有关。此外,该研究确定了CAF评分与LIHC预后之间存在显著关联,低CAF评分表明患者预后良好。总之,本研究揭示了LIHC发生发展的分子机制,并确定了该疾病的潜在治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e80/11334810/8e099d2da033/gr1.jpg

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