Identifying a Risk Signature of Methylation-Driven Genes as a Predictor of Survival Outcome for Colon Cancer Patients.

IF 3.1 4区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Applied Biochemistry and Biotechnology Pub Date : 2024-07-01 Epub Date: 2023-10-31 DOI:10.1007/s12010-023-04751-z
Bochao Zhao, Jingchao Wang, Guannan Sheng, Yiming Wang, Tao Yang, Kewei Meng
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Abstract

Aberrant expression of gene is driven by its promoter methylation and is the key molecular basis of carcinogenic processes. This study aimed at identifying a risk signature of methylation-driven (MD) genes and evaluating its prognostic value for colon cancer (CC) patients. The expression profiles of methylation and mRNA in CC samples were obtained from the TCGA database, and the MethylMix algorithm was used to identify MD genes. The relationships between their expression levels and overall survival (OS) of CC patients were analyzed, and a prognostic signature of MD genes was established. The risk score of gene signature was calculated, and the median was used to divide all patients into high (H) and low (L) risk groups. The prognostic value of gene signature was tested by the TCGA cohort and an independent validation cohort (GSE17538 dataset). In total, 69 MD genes were identified, and 7 were associated with OS of CC patients. Ultimately, 4 (TWIST1, LDOC1, EPHX3, and STC2) were screened out to establish a risk signature. The H-risk patients (>0.923) had a worse OS than L-risk patients (≤0.923) in both the TCGA (5-year cumulative survival: 52.9% vs 72.0%, P=0.005) and GSE17538 cohort (49.4% vs 69.3%, P=0.004). The AUC values of MD genes signature for the prediction of 3- and 5-year OS were 0.648 and 0.643 in the TCGA dataset and 0.634 and 0.624 in the GSE17538 dataset, respectively. The risk signature of four MD genes was identified as an independent predictor of OS for CC patients (HR for TCGA dataset: 2.071, 95% CI=1.196-3.586, P=0.009; HR for GSE17538 dataset: 2.021, 95% CI=1.290-3.166, P=0.002). The risk signature of four MD genes might be a useful prognostic tool and help doctors improve the clinical management of CC patients.

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确定甲基化驱动基因的风险特征作为癌症患者生存结果的预测因子。
基因的异常表达是由其启动子甲基化驱动的,是致癌过程的关键分子基础。本研究旨在确定甲基化驱动(MD)基因的风险特征,并评估其对癌症(CC)患者的预后价值。从TCGA数据库中获得CC样品中甲基化和mRNA的表达谱,并使用MethylMix算法鉴定MD基因。分析了它们的表达水平与CC患者总生存期(OS)之间的关系,并建立了MD基因的预后标志。计算基因特征的风险评分,并使用中位数将所有患者分为高(H)和低(L)风险组。通过TCGA队列和独立验证队列(GSE17538数据集)测试基因特征的预后价值。总共鉴定出69个MD基因,其中7个与CC患者的OS相关。最终,筛选出4个(TWIST1、LDOC1、EPHX3和STC2),以建立风险特征。在TCGA(5年累计生存率:52.9%vs 72.0%,P=0.005)和GSE17538队列(49.4%vs 69.3%,P=0.004)中,H风险患者(>0.923)的OS比L风险患者(≤0.923)更差。预测3年和5年OS的MD基因特征的AUC值在TCGA数据集中分别为0.648和0.643,在GSE17558数据集中分别为0.634和0.624。四个MD基因的风险特征被确定为CC患者OS的独立预测因子(TCGA数据集的HR:2.071,95%CI=1.196-3.586,P=0.009;GSE17538数据集的HR:2.021,95%CI=1.290-3166,P=0.002)。四个MD的风险特征可能是一个有用的预后工具,有助于医生改善CC患者的临床管理。
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来源期刊
Applied Biochemistry and Biotechnology
Applied Biochemistry and Biotechnology 工程技术-生化与分子生物学
CiteScore
5.70
自引率
6.70%
发文量
460
审稿时长
5.3 months
期刊介绍: This journal is devoted to publishing the highest quality innovative papers in the fields of biochemistry and biotechnology. The typical focus of the journal is to report applications of novel scientific and technological breakthroughs, as well as technological subjects that are still in the proof-of-concept stage. Applied Biochemistry and Biotechnology provides a forum for case studies and practical concepts of biotechnology, utilization, including controls, statistical data analysis, problem descriptions unique to a particular application, and bioprocess economic analyses. The journal publishes reviews deemed of interest to readers, as well as book reviews, meeting and symposia notices, and news items relating to biotechnology in both the industrial and academic communities. In addition, Applied Biochemistry and Biotechnology often publishes lists of patents and publications of special interest to readers.
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