Integrated bioinformatics approach to unwind key genes and pathways involved in colorectal cancer

Author:

Mobeen Syeda Anjum1,Saxena Pallavi23,Jain Arun Kumar2,Deval Ravi3,Riazunnisa Khateef1,Pradhan Dibyabhaba4

Affiliation:

1. Department of Biotechnology and Bioinformatics, Yogi Vemana University, Andhra Pradesh, India

2. Biomedical Informatics Centre, Indian Council of Medical Research, National Institute of Pathology, New Delhi, India

3. Department of Biotechnology, Invertis University, Bareilly, Uttar Pradesh, India

4. Computational Genomics Centre, ISRM Division, ICMR, New Delhi, India

Abstract

ABSTRACT Background: Colorectal cancer (CRC) is the fifth leading cause of death in India. Until now, the exact pathogenesis concerning CRC signaling pathways is largely unknown; however, the diseased condition is believed to deteriorate with lifestyle, aging, and inherited genetic disorders. Hence, the identification of hub genes and therapeutic targets is of great importance for disease monitoring. Objective: Identification of hub genes and targets for identification of candidate hub genes for CRC diagnosis and monitoring. Materials and Methods: The present study applied gene expression analysis by integrating two profile datasets (GSE20916 and GSE33113) from NCBI-GEO database to elucidate the potential key candidate genes and pathways in CRC. Differentially expressed genes (DEGs) between CRC (195 CRC tissues) and healthy control (46 normal mucosal tissue) were sorted using GEO2R tool. Further, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed using Cluster Profiler in Rv. 3.6.1. Moreover, protein-protein interactions (PPI), module detection, and hub gene identification were accomplished and visualized through the Search Tool for the Retrieval of Interacting Genes, Molecular Complex Detection (MCODE) plug-in of Cytoscape v3.8.0. Further hub genes were imported into ToppGene webserver for pathway analysis and prognostic expression analysis was conducted using Gene Expression Profiling Interactive Analysis webserver. Results: A total of 2221 DEGs, including 1286 up-regulated and 935down-regulated genes mainly enriched in signaling pathways of NOD-like receptor, FoxO, AMPK signalling and leishmaniasis. Three key modules were detected from PPI network using MCODE. Besides, top 20 high prioritized hub genes were selected. Further, prognostic expression analysis revealed ten of the hub genes, namely IL1B, CD44, Glyceraldehyde-3-phosphate dehydrogenase (GAPDH, MMP9, CREB1, STAT1, vascular endothelial growth factor (VEGFA), CDC5 L, Ataxia-telangiectasia mutated (ATM + and CDH1 to be differently expressed in normal and cancer patients. Conclusion: The present study proposed five novel therapeutic targets, i.e., ATM, GAPDH, CREB1, VEGFA, and CDH1 genes that might provide new insights into molecular oncogenesis of CRC.

Publisher

Medknow

Subject

Radiology, Nuclear Medicine and imaging,Oncology,General Medicine

Reference54 articles.

1. Current status and future directions in colorectal cancer;Meyer;Indian J Surg Oncol,2018

2. The molecular characteristics of colorectal cancer:Implications for diagnosis and therapy;Nguyen;Oncol Lett,2018

3. Colorectal cancer epidemiology:Incidence, mortality, survival, and risk factors;Haggar;Clin Colon Rectal Surg,2009

4. Biomarkers in colorectal cancer:Current clinical utility and future perspectives;Vacante;World J Clin Cases,2018

5. Genetic alterations in colorectal cancer;Armaghany;Gastrointest Cancer Res,2012

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