Establishment of the Prognostic Signature with Genes Related to G2/M Checkpoint in Hepatocellular Carcinoma.

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Biochemical Genetics Pub Date : 2024-10-15 DOI:10.1007/s10528-024-10931-1
Dapeng Wu, Baiyang Zhu, Zonglong Nie, Qingnuan Kong, Wenjing Zhu
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Abstract

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer mortality in the world. Prognostic indicators such as clinicopathological characteristics and single molecular signature are far from satisfactory in clinical practice. More and more researches have suggested that polygenic prognostic features could predict the prognosis of cancer more precisely than single genes nowadays. In this study, we performed gene set enrichment analysis (GSEA) to identify the sets of TCGA hallmark genes. Univariate Cox regression analysis was used to select preliminary genes, and then multivariate Cox regression analysis was used to identify genes associated with overall survival (OS). We also used Kaplan-Meier analysis and receiver operating characteristic (ROC) analysis to validate the prognostic gene signature. Lastly, qRT-PCR was used to evaluate the expression of these genes in clinical samples, and immunohistochemical staining was performed to confirm the signature. A 12-gene signature was finally built and the risk score was significantly associated with the survival of the patients. Subsequent validation by qRT-PCR and immunohistochemical staining in clinical specimens confirmed the value of the risk score in predicting the prognosis. We developed a 12-gene signature that could predict the prognosis of HCC patients. This signature is of high precision and would help identifying subgroups of HCC patients with high or low risk of unfavorable survival.

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肝细胞癌中与 G2/M 检查点相关基因预后特征的建立
肝细胞癌(HCC)是全球癌症死亡的主要原因之一。在临床实践中,临床病理特征和单一分子特征等预后指标远不能令人满意。越来越多的研究表明,多基因预后特征比单基因能更精确地预测癌症的预后。在本研究中,我们进行了基因组富集分析(GSEA),以确定TCGA标志基因集。利用单变量 Cox 回归分析筛选出初步基因,然后利用多变量 Cox 回归分析确定与总生存期(OS)相关的基因。我们还使用 Kaplan-Meier 分析和接收器操作特征(ROC)分析来验证预后基因特征。最后,我们使用 qRT-PCR 技术评估了这些基因在临床样本中的表达情况,并进行了免疫组化染色以确认特征。最终建立了一个 12 个基因的特征,其风险评分与患者的生存期明显相关。随后在临床样本中通过 qRT-PCR 和免疫组化染色进行了验证,证实了风险评分在预测预后方面的价值。我们建立了一个可以预测 HCC 患者预后的 12 个基因特征。该特征具有很高的精确度,有助于确定HCC患者中生存不利风险高或低的亚组。
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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