免疫相关细胞死亡指数及其在肝细胞癌中的应用

IF 6.8 1区 医学 Q1 ONCOLOGY
Zhao Sun, Hao Liu, Qian Zhao, Jie-Han Li, San-Fei Peng, Zhen Zhang, Jing-Hua Yang, Yang Fu
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引用次数: 0

摘要

调节性细胞死亡(RCD)在肝细胞癌(HCC)的免疫微环境、发展和恶化中起着至关重要的作用。然而,可靠的免疫相关细胞死亡特征尚未被探索。在这项研究中,我们收集了12种RCD模式(如凋亡、铁凋亡和杯凋亡),包括1078个调控因子,根据HCC免疫亚群鉴定与免疫相关的细胞死亡基因。利用开发的竞争性机器学习框架,筛选出9个基因,构建了免疫相关细胞死亡指数(IRCDI),该指数可在线应用。通过分析多组学数据和临床特征,探索了HCC的恶性异质性。为了验证该模型的有效性,利用了超过 18 个独立队列,包括生存和不同治疗队列和数据集。这些发现通过内部样本和分子生物学实验得到了进一步验证。总之,IRCDI 可广泛应用于个体治疗决策和改善 HCC 患者的预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Immune-related cell death index and its application for hepatocellular carcinoma

Immune-related cell death index and its application for hepatocellular carcinoma

Immune-related cell death index and its application for hepatocellular carcinoma
Regulated cell death (RCD) plays a crucial role in the immune microenvironment, development, and progression of hepatocellular carcinoma (HCC). However, reliable immune-related cell death signatures have not been explored. In this study, we collected 12 RCD modes (e.g., apoptosis, ferroptosis, and cuproptosis), including 1078 regulators, to identify immune-related cell death genes based on HCC immune subgroups. Using a developed competitive machine learning framework, nine genes were screened to construct the immune-related cell death index (IRCDI), which is available for online application. Multi-omics data, along with clinical features, were analyzed to explore the HCC malignant heterogeneity. To validate the efficacy of this model, more than 18 independent cohorts, including survival and diverse treatment cohorts and datasets, were utilized. These findings were further validated using in-house samples and molecular biological experiments. Overall, the IRCDI may have a wide application in individual therapeutic decision-making and improving outcomes for HCC patients.
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来源期刊
CiteScore
9.90
自引率
1.30%
发文量
87
审稿时长
18 weeks
期刊介绍: Online-only and open access, npj Precision Oncology is an international, peer-reviewed journal dedicated to showcasing cutting-edge scientific research in all facets of precision oncology, spanning from fundamental science to translational applications and clinical medicine.
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