 Detecting driver mutations in colorectal cancer through big data analysisAmna Amin Sethi, Saad Khan, Fatima Hashmi and Saim Ali Akber International Journal of Data Mining, Modelling and Management, 2024, vol. 16, issue 4, 420-442 Abstract: Colorectal cancer (CRC) is a complex disease causing a significant challenge to global health with profound impacts on morbidity and mortality. There is a need to identify genetic biomarkers for early diagnosis of disease. In this study, a comprehensive analysis of CRC genomes was conducted to identify consistent mutations in both coding and non-coding highlighting their pivotal role in CRC pathogenesis. The results of this study revealed consistent mutations in coding regions that validated known CRC driver genes. The consistent non-coding mutations were also identified within transcription factors binding sites (TFBS) in CRC cell lines. The statistical significance of these mutations suggests their potential impact on gene regulation leading to the development and progression of CRC. They might act as potential biomarkers for early diagnosis of the disease. To conclude, the findings of this study might provide novel therapeutic targets and diagnostic markers for personalised medicine. Keywords: colorectal cancer; CRC; driver mutations; driver genes; biomarkers; transcription factors binding sites; TFBS. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijdmmm:v:16:y:2024:i:4:p:420-442 Access Statistics for this article More articles in International Journal of Data Mining, Modelling and Management from Inderscience Enterprises Ltd |
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