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基于同源重组缺陷相关基因鉴定肝细胞癌的分子亚型和预后特征。

Identification of molecular subtypes and prognostic signature for hepatocellular carcinoma based on genes associated with homologous recombination deficiency.

机构信息

Guangxi University of Chinese Medicine, Nanning, 530200, China.

Department of Laboratory, The First Affiliated Hospital of Guangxi University of Chinese Medicine, Nanning, 530023, China.

出版信息

Sci Rep. 2021 Dec 15;11(1):24022. doi: 10.1038/s41598-021-03432-3.

Abstract

Hepatocellular carcinoma (HCC) is a rapidly developing digestive tract carcinoma. The prognosis of patients and side effects caused by clinical treatment should be better improved. Nonnegative matrix factorization (NMF) clustering was performed using 109 homologous recombination deficiency (HRD)-related of HCC genes from The Cancer Genome Atlas (TCGA) database. Limma was applied to analyze subtype differences. Immune scores and clinical characteristics of different subtypes were compared. An HRD signature were built with least absolute shrinkage operator (LASSO) and multivariate Cox analysis. Performance of the signature system was then assessed by Kaplan-Meier curves and receiver operating characteristic (ROC) curves. We identified two molecular subtypes (C1 and C2), with C2 showing a significantly better prognosis than C1. C1 contained 3623 differentially expressed genes. A 4-gene prognostic signature for HCC was established, and showed a high predicting accuracy in validation sets, entire TCGA data set, HCCDB18 and GSE14520 queues. Moreover, the risk score was validated as an independent prognostic marker for HCC. Our research identified two molecular subtypes of HCC, and proposed a novel scoring system for evaluating the prognosis of HCC in clinical practice.

摘要

肝细胞癌 (HCC) 是一种快速发展的消化道癌。应更好地改善患者的预后和临床治疗引起的副作用。使用来自癌症基因组图谱 (TCGA) 数据库的 109 个同源重组缺陷 (HRD) 相关 HCC 基因进行非负矩阵分解 (NMF) 聚类。应用 Limma 分析亚型差异。比较不同亚型的免疫评分和临床特征。使用最小绝对值收缩和选择算子 (LASSO) 和多变量 Cox 分析构建 HRD 特征。然后通过 Kaplan-Meier 曲线和接收者操作特征 (ROC) 曲线评估特征系统的性能。我们确定了两种分子亚型 (C1 和 C2),C2 的预后明显优于 C1。C1 包含 3623 个差异表达基因。建立了 HCC 的 4 基因预后标志物,并在验证集、整个 TCGA 数据集、HCCDB18 和 GSE14520 队列中显示出较高的预测准确性。此外,风险评分被验证为 HCC 的独立预后标志物。我们的研究确定了两种 HCC 分子亚型,并提出了一种新的评分系统,用于评估 HCC 患者的临床预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2def/8674316/00e271006fe9/41598_2021_3432_Fig1_HTML.jpg

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