Abstract

Colon cancer one among the deadly cancers around the world starts as an abnormal tissue growth in the inner wall of the colon, leads to polyp formation and further leads to tumor growth. Identifying biomarkers with the ability to perceive biological characteristics was therefore a key question for early diagnosis of patients with colon cancer. Here we explored the molecular mechanisms and interactions involved in colon cancers and screened candidate genes that can function as promising biomarkers. Gene expression analysis was performed by investigating GEO Datasets of microarray data and explored DEGs between samples of normal and cancer patients. Later functional enrichment, pathway analysis was performed to investigate feature genes and their mechanistic role in colon cancer progression. Further, protein association network analysis was performed for the retrieval of interaction data. Finally, the data were subjected to Cytoscape for visualization of interaction network and highly connected genes were considered. A total of 16 candidate genes were taken into considerations but furthermore by exploring pathway studies, BRCA1, KNG1, RPL11, AURKB, GAK, TNKS, PIK3CB, KAT2B were differentially expressed and involved in major oncogenic pathways. Targeting these genes could serve not only as potential biomarkers for diagnosis but also for prognostic treatments of colon cancer.

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