A comprehensive analysis of vasculogenic mimicry related genes to predict the survival rate of HCC and its influence on the tumor microenvironment.

IF 2.8 3区生物学 Q2 GENETICS & HEREDITY Frontiers in Genetics Pub Date : 2024-12-19 eCollection Date: 2024-01-01 DOI:10.3389/fgene.2024.1437715

Jingyun Wang, Rong Gao, Jian Qi, Yingru Xing, Bo Hong, Hongzhi Wang, Jinfu Nie

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Abstract

Objectives: Investigate the predictive value of Vasculogenic mimicry (VM) related genes for the survival and prognosis of Hepatocellular carcinoma (HCC) patients and its role in the tumor microenvironment (TME).

Methods: VM-related genes were obtained from previous literature, the expression profiles, single-cell data and clinical information of HCC patients were downloaded from public databases. The HCC patients were divided into different clusters by unsupervised clustering, the differences in prognosis and immune characteristics of VM-related clusters were analyzed. A prognostic model related to VM (VM Score) was constructed based on LASSO regression and univariate and multivariate Cox regression, the correlation between this model and chemotherapy drugs and immunotherapy was studied. Seurat package was used to standardize single-cell data for single-cell level analysis. The expression of risk factors in VM Score was verified by RT-qPCR.

Results: VM Score composed of SPP1, ADAMTS5 and ZBP1 was constructed and validated. VM Score was an independent prognostic factor for HCC. Through the analysis of single cell data further reveals the VM Score influence on TME. In addition, VM Score could provide ideas for the selection of immunotherapy and chemotherapy drugs. RT-qPCR showed that the expression of risk factors was different in HCC cell lines.

Conclusion: Our results suggest that VM Score may serve as a promising prognostic biomarker for HCC and provide new ideas for immunotherapy in HCC patients.

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综合分析血管生成模拟相关基因预测肝癌生存率及其对肿瘤微环境的影响。

研究目的研究血管生成模仿（VM）相关基因对肝细胞癌（HCC）患者生存和预后的预测价值及其在肿瘤微环境（TME）中的作用：方法：从以前的文献中获取 VM 相关基因，从公共数据库中下载 HCC 患者的表达谱、单细胞数据和临床信息。通过无监督聚类将 HCC 患者分为不同的群组，分析 VM 相关群组的预后差异和免疫特征。基于 LASSO 回归、单变量和多变量 Cox 回归，构建了与 VM 相关的预后模型（VM 评分），并研究了该模型与化疗药物和免疫疗法之间的相关性。采用Seurat软件包对单细胞数据进行标准化处理，以进行单细胞水平分析。通过 RT-qPCR 验证了 VM Score 中危险因素的表达：结果：构建并验证了由 SPP1、ADAMTS5 和 ZBP1 组成的 VM 评分。VM Score是HCC的一个独立预后因素。通过对单细胞数据的分析，进一步揭示了 VM Score 对 TME 的影响。此外，VM Score 还能为免疫疗法和化疗药物的选择提供思路。RT-qPCR显示，危险因素在HCC细胞系中的表达存在差异：我们的研究结果表明，VM 评分可作为一种有前景的 HCC 预后生物标志物，并为 HCC 患者的免疫治疗提供新思路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Frontiers in Genetics Biochemistry, Genetics and Molecular Biology-Molecular Medicine

CiteScore

5.50

自引率

8.10%

发文量

3491

审稿时长

14 weeks

期刊介绍： Frontiers in Genetics publishes rigorously peer-reviewed research on genes and genomes relating to all the domains of life, from humans to plants to livestock and other model organisms. Led by an outstanding Editorial Board of the world’s leading experts, this multidisciplinary, open-access journal is at the forefront of communicating cutting-edge research to researchers, academics, clinicians, policy makers and the public. The study of inheritance and the impact of the genome on various biological processes is well documented. However, the majority of discoveries are still to come. A new era is seeing major developments in the function and variability of the genome, the use of genetic and genomic tools and the analysis of the genetic basis of various biological phenomena.