ArticleCancer management and research2019
Identification of hub genes and outcome in colon cancer based on bioinformatics analysis.
Article in Cancer management and research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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22 citing papers in PubMed, 41 citations in OpenAlex.
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- An Immune-Related Prognostic Risk Model in Colon Cancer by Bioinformatics Analysis.Evidence-based complementary and alternative medicine : eCAM · 2022Article
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- Prognostic biomarkers and therapeutic targets in oral squamous cell carcinoma: a study based on cross-database analysis.Hereditas · 2021Article
- MicroRNA‑642a‑5p inhibits colon cancer cell migration and invasion by targeting collagen type I α1.Oncology reports · 2021Article
- GNG4 Promotes Tumor Progression in Colorectal Cancer.Journal of oncology · 2021Article
- A New Oxaliplatin Resistance-Related Gene Signature With Strong Predicting Ability in Colon Cancer Identified by Comprehensive Profiling.Frontiers in oncology · 2021Article
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- Molecular heterogeneity of guanine nucleotide binding-protein γ subunit 4 in left- and right-sided colon cancer.Oncology letters · 2020Article
- Important players in carcinogenesis as potential targets in cancer therapy: an update.Oncotarget · 2020Review
- Unraveling LGALS1 as a Potential Immune Checkpoint and a Predictor of the Response to Anti-PD1 Therapy in Clear Cell Renal Carcinoma.Pathology oncology research : POR · 2020Article
- Identification of key genes and pathways in syphilis combined with diabetes: a bioinformatics study.AMB Express · 2020Article
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundColon cancer is one of the leading malignant neoplasms worldwide. Until now, the concrete mechanisms of colonic cancerogenesis are largely unknown; identification of driven genes and pathways is, therefore, of great importance for monitoring and conquering this disease. This study aims to explore the potential biomarkers and therapeutic targets for colon cancer treatment.
methodsThe gene expression profile of GSE44076 from Gene Expression Omnibus database, including 98 primary colon cancers and 98 normal distant colon mucosa, was deeply analyzed. GEO2R tool was used to screen the differentially expressed genes (DEGs) between colon cancer tissues and normal samples. Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed for screening DEGs using Database for Annotation, Visualization and Integrated Discovery database and Panther database. Moreover, Search Tool for the Retrieval of Interacting Genes, Cytoscape software, and Molecular Complex Detection plug-in were used to visualize the protein-protein interaction of these DEGs.
resultsA total of 497 DEGs were obtained, including 129 upregulated genes mainly enriched in Hippo signaling pathway, Wnt signaling pathway, and cytokine-cytokine receptor interaction and 368 downregulated genes enriched in retinol metabolism, steroid hormone biosynthesis, drug metabolism, and chemical carcinogenesis. Using Molecular Complex Detection software, three important modules were selected from the protein-protein interaction network. Moreover, 20 hub genes with high degree of connectivity were selected, including COL1A1, CXCL5, GNG4, TIMP1, and so on. The Kaplan-Meier analysis for overall survival and correlation analysis were applied among the hub genes.
conclusionTaken together, DEGs, especially the hub genes such as COL1A1, might be the driven genes in colon cancer progression. More importantly, they might be the novel biomarkers for diagnosis and guiding therapeutic strategies of colon cance
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