Jichu yixue yu linchuang (Jun 2021)

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

  • WANG Yu-qian, CHEN Ya-mei, YANG Jie, LIN Yuan, LUO Ying-ying, ZHANG Shao-sen, WU Chen

Journal volume & issue
Vol. 41, no. 6
pp. 831 – 836

Abstract

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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.

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