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基于网络的 II 期结直肠癌复发风险预测基因表达谱。

A network-based predictive gene expression signature for recurrence risks in stage II colorectal cancer.

机构信息

Department of Oncology, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China.

Department of Biochemistry and Molecular Biology, Capital Medical University, Beijing, China.

出版信息

Cancer Med. 2020 Jan;9(1):179-193. doi: 10.1002/cam4.2642. Epub 2019 Nov 14.

Abstract

The current criteria for defining the recurrence risks of stage II colorectal cancer (CRC) are not robust; therefore, we aimed to explore novel gene signatures to predict recurrence risks and to reveal the underlying mechanisms of stage II CRC. First, the gene expression profiles of 124 patients with stage II CRC from The Cancer Genome Atlas (TCGA) database were obtained to screen differentially expressed genes (DEGs). A total of 202 DEGs, including 128 upregulated and 74 downregulated, were identified in the recurrence group (n = 24) compared to the nonrecurrence group (n = 100). Furthermore, the top 5 DEGs (ZNF561, WFS1, SLC2A1, MFI2, and PTGR1) were identified by random forest variable hunting, and four (ZNF561, WFS1, SLC2A1, and PTGR1) were selected to create a four-gene recurrent model (GRM), with an area under the curve (AUC) of 0.882 according to the receiver operating characteristic curve, and the robust diagnostic effectiveness of the GRM was further validated with another gene expression profiling dataset (GSE12032), with an AUC of 0.943. The diagnostic effectiveness of the GRM regarding recurrence was associated with poor disease-free survival in all stages of CRC. In addition, gene ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed 18 enriched functions and 6 enriched pathways. Four genes, ABCG2, CACNA1F, CYP19A1, and TF, were identified as hub genes by the protein-protein interaction network, which further validated that these genes were correlated with a poor pathologic stage and overall survival in all stages of CRC. In conclusion, the GRM can effectively classify stage II CRC into groups of high and low risks of recurrence, thereby making up for the prognostic value of the traditional clinicopathological risk factors defined by the National Comprehensive Cancer Network guidelines. The hub genes may be useful therapeutic targets for recurrence. Thus, the GRM and hub genes could offer clinical value in directing individualized and precision therapeutic regimens for stage II CRC patients.

摘要

目前定义 II 期结直肠癌(CRC)复发风险的标准并不稳健;因此,我们旨在探索新的基因特征来预测复发风险,并揭示 II 期 CRC 的潜在机制。首先,从癌症基因组图谱(TCGA)数据库中获取了 124 例 II 期 CRC 患者的基因表达谱,以筛选差异表达基因(DEGs)。与非复发组(n=100)相比,复发组(n=24)中鉴定出 202 个 DEGs,其中 128 个上调,74 个下调。此外,通过随机森林变量搜索确定了前 5 个 DEGs(ZNF561、WFS1、SLC2A1、MFI2 和 PTGR1),并选择其中 4 个(ZNF561、WFS1、SLC2A1 和 PTGR1)创建了一个 4 基因复发模型(GRM),根据受试者工作特征曲线,该模型的曲线下面积(AUC)为 0.882,并且该 GRM 的稳健诊断效果通过另一个基因表达谱数据集(GSE12032)进一步验证,AUC 为 0.943。GRM 对复发的诊断效果与 CRC 所有分期的无病生存不良相关。此外,基因本体功能注释和京都基因与基因组百科全书通路富集分析显示了 18 个富集功能和 6 个富集通路。通过蛋白质-蛋白质相互作用网络鉴定了 4 个基因(ABCG2、CACNA1F、CYP19A1 和 TF)为核心基因,这进一步验证了这些基因与 CRC 所有分期的不良病理分期和总生存相关。总之,GRM 可以有效地将 II 期 CRC 分为复发风险高低的两组,从而弥补了美国国家综合癌症网络指南定义的传统临床病理危险因素的预后价值。核心基因可能是复发的有价值的治疗靶点。因此,GRM 和核心基因可为指导 II 期 CRC 患者个体化和精准治疗方案提供临床价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9729/6943157/900e877c2a8c/CAM4-9-179-g001.jpg

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