The implication of Synemin gene on expression and prognostic significance in gastric cancer based on bioinformatics

Author:

Pan Feng1,Zhang Yong-Qiang2,Zhang Xu-Dong3,Li Xiao-Ning3,Cui Hai-Kang3,Yan Xi3,Yan Lan3,Zhang Wen-Jie3

Affiliation:

1. Nantong First People's Hospital

2. the first Affiliated Hospital, Shihezi University School of Medicine

3. Key Laboratories for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine

Abstract

Abstract Objective:Here, we explored the expression of SYNM by means of Gene Expression Omnibus (GEO) and investigated its prognostic significance as well as potential functions in gastric cancer (GC). Methods:Toward this goal, differential gene expression analysis, univariate Cox regression, Lasso regression, best subset regression, Gene Set Enrichment Analysis (GSEA) and multivariate Cox regression were employed in GEO. For further verification, the pathological tissues of patients with gastric cancer were collected and analyzed. The expression of SYNM in GC tissues was verified by qRT-PCR, Western blotting and immunohistochemistry. Kruskal-Wallis test was used to analyze the correlation between SYNM expression and clinical characteristics. Kaplan-Meier analysis, univariate and multivariate Cox regression analysis were applied to analyzed prognostic. Results:SYNM is underexpressed in GC in public datasets and clinical samples (P <0.01); Its expression was significantly correlated with Lauren typing, T, N, M and clinical staging (P < 0.05). Patients with high SYNM expression had poor prognosis (P < 0.01) and it was an independent prognostic factor for GC (p = 0.01). The high expression of SYNM mRNA was enriched in Extracellular matrix (ECM) receptor interaction, leukocyte transendothelial migration and Transforming growth factor β (TGF – β) signaling pathway, and CD4+ memory T cells resting were abundant. Conclusion:SYNM was low expression in GC and it might promote the malignant development and immune evasion of GC, and patients with high expression of SYNM predicted a good prognosis.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3