Related Experiment Video
Updated: May 9, 2026
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Integrated bioinformatics approach to unwind key genes and pathways involved in colorectal cancer
Syeda Anjum Mobeen1, Pallavi Saxena2,3, Arun Kumar Jain2
1Department of Biotechnology and Bioinformatics, Yogi Vemana University, Andhra Pradesh, India.
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.
Insights
This study identified key genes in colorectal cancer (CRC) pathogenesis, revealing ATM, GAPDH, CREB1, VEGFA, and CDH1 as potential therapeutic targets for CRC. These findings offer new insights into CRC molecular oncogenesis and disease monitoring.
Area of Science:
- Genomics and Bioinformatics
- Molecular Oncology
- Cancer Signaling Pathways
Background:
- Colorectal cancer (CRC) is a significant cause of mortality in India, with its pathogenesis and signaling pathways not fully understood.
- Factors like lifestyle, aging, and genetic predispositions are implicated in CRC development.
- Identifying key genes and therapeutic targets is crucial for effective CRC monitoring and treatment.
Purpose of the Study:
- To identify candidate hub genes and potential therapeutic targets for colorectal cancer (CRC) diagnosis and monitoring.
- To elucidate the key genes and signaling pathways involved in CRC pathogenesis.
Main Methods:
- Gene expression analysis integrating two datasets (GSE20916, GSE33113) from the NCBI-GEO database.
- Identification of differentially expressed genes (DEGs) using GEO2R, followed by Gene Ontology and KEGG pathway analysis.
- Protein-protein interaction (PPI) network construction, module detection (MCODE), and hub gene identification using Cytoscape.
Main Results:
- A total of 2221 DEGs were identified, enriched in pathways including NOD-like receptor, FoxO, and AMPK signaling.
- Three key modules and 20 high-priority hub genes were detected.
- Ten hub genes, including ATM, GAPDH, CREB1, VEGFA, and CDH1, showed differential expression in CRC patients.
Conclusions:
- The study proposes five novel therapeutic targets: ATM, GAPDH, CREB1, VEGFA, and CDH1 for colorectal cancer.
- These identified genes may offer new insights into the molecular oncogenesis of CRC.
- The findings support the potential use of these genes for CRC diagnosis and monitoring.
