分析鉴定胃食管交界处腺癌发生与进展的关键基因

基础医学与临床 ›› 2021, Vol. 41 ›› Issue (6): 831-836.

分析鉴定胃食管交界处腺癌发生与进展的关键基因

王雨芊¹, 陈亚玫¹, 杨洁¹, 林媛², 骆盈盈¹, 张少森¹, 吴晨^1*

1.国家癌症中心国家肿瘤临床医学研究中心中国医学科学院北京协和医学院肿瘤医院分子肿瘤学国家重点实验室病因及癌变研究室癌发生及预防分子机理北京市重点实验室, 北京 100021;
2.北京大学北京未来基因诊断高精尖创新中心生物医学前沿创新中心, 北京 100871

收稿日期:2021-03-24 修回日期:2021-04-16 出版日期:2021-06-05 发布日期:2021-05-31
通讯作者: ^*chenwu@cicams.ac.cn
基金资助:
国家自然科学基金(81988101)

Identification and analysis of key genes in association with development and progression of adenocarcinoma at the gastroesophageal junction

WANG Yu-qian¹, CHEN Ya-mei¹, YANG Jie¹, LIN Yuan², LUO Ying-ying¹, ZHANG Shao-sen¹, WU Chen^1*

1. State Key Laboratory of Molecular Oncology, Department of Etiology & Carcinogenesis, Beijing Key Laboratory for Carcinogenesis and Cancer Prevention, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021;
2. Beijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC),Peking University, Beijing 100871, China

Received:2021-03-24 Revised:2021-04-16 Online:2021-06-05 Published:2021-05-31
Contact: ^*chenwu@cicams.ac.cn

摘要/Abstract

摘要： 目的探究中国人群胃食管交界处腺癌(ACGEJ)在基因组与转录组水平的改变,挖掘肿瘤发生和进展过程中的关键基因。方法研究纳入58例于林州肿瘤医院和林州食管癌医院收集的ACGEJ患者的肿瘤组织及癌旁组织样本,通过转录组测序对样本进行基因表达水平的差异分析和 GSVA通路富集分析。使用LASSO回归对差异基因与患者的预后进行关联分析,并且构建nomogram生存预测模型。结果发现在ACGEJ的癌与癌旁组织中共有737个基因差异表达(｜log2FC｜＞1.2, Q＜0.05),这些基因富集在肿瘤生长、转移、代谢等通路上。其中有9个基因(ASF1B、ACTN1、KNL1、SAPCD2、TP53I11、DMBT1、CNFN、ID2和DPT)与患者预后显著相关。基于这9个基因共表达模式构建了ACGEJ患者的生存预测模型并可将患者分为高、低风险两组,且低风险组生存时间显著高于高风险组(P＜0.01)。结合患者年龄、肿瘤临床分期和预后关联基因集构建了预测性良好的nomogram生存预测模型。结论研究鉴定出多个与ACGEJ进展和预后相关的关键失调基因,这些鉴定出的关键基因有望成为治疗的潜在靶点和预后预测的生物标志物。

关键词: 胃食管交界处腺癌, 转录组测序, 关键基因, 生存预测

Abstract: Objective To explore the transcriptomic changes of adenocarcinoma at the gastroesophageal junction (ACGEJ) and identify key genes in the occurrence and progression. Methods RNA sequencing data of ACGEJ tumors and adjacent normal tissues samples from 58 patients who were recruited at the Linzhou Cancer Hospital and Linzhou Esophageal Cancer Hospital. The gene expression level of paired ACGEJ and adjacent normal tissue samples were compared to identify dysregulated genes. And the enriched pathways of these genes were analyzed by using gene set variation analysis (GSVA). LASSO regression model was used to test the association between the expression of dysregulated genes and the prognosis of ACGEJ patients, and the clinical features and prognosis associated gene set were applied to establish the nomogram model. Results Through transcriptomic profiling of tumor and non-tumor ACGEJ samples, 737 significantly differentially expression genes (DEGs) in ACGEJ were identified(｜log2FC｜＞1.2, Q＜0.05). The DEGs were related to tumor proliferation, growth, metastasis and metabolism. Among these DEGs, a total of 9 genes (ASF1B,ACTN1,KNL1,SAPCD2,TP53I11,DMBT1,CNFN,ID2,DPT) were identified to associate with the prognosis of ACGEJ patients by LASSO regression model. These 9 genes were further selected to build a prognostic model. The patients could be divided into two groups by this prognostic model, and the overall survival (OS) of the low-risk group was significantly higher than that of the high-risk group (P＜0.01). A nomogram was established which included the age, clinical stage and prognosis associated gene set for eventual clinical translation. Conclusions Several genes associated with the occurrence and progression of ACGEJ are identified. These genes may be potential treatment targets and prognostic biomarkers of this disease.

Key words: adenocarcinoma at the gastroesophageal junction (ACGEJ), RNA sequencing, key genes, prognosis prediction

中图分类号:

R735

王雨芊, 陈亚玫, 杨洁, 林媛, 骆盈盈, 张少森, 吴晨. 分析鉴定胃食管交界处腺癌发生与进展的关键基因[J]. 基础医学与临床, 2021, 41(6): 831-836.

WANG Yu-qian, CHEN Ya-mei, YANG Jie, LIN Yuan, LUO Ying-ying, ZHANG Shao-sen, WU Chen. Identification and analysis of key genes in association with development and progression of adenocarcinoma at the gastroesophageal junction[J]. Basic & Clinical Medicine, 2021, 41(6): 831-836.

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