Research Projects

Colorectal cancer (CRC) is a prevalent malignancy worldwide, with only 11% of individuals who have progressed to other body regions surviving five years after diagnosis. Early-stage detection through routine screening is crucial to avoid disease lethality. Colonoscopy, a routine procedure, is prone to errors due to the subjective variance in adenoma detection rates (ADRs). AI-based tools have been developed to improve the accuracy of these models, but their widespread application is limited by their development at a single institution with a unique patient population. This study aims to develop a prediction model for early-stage colorectal cancer diagnosis using colonoscopy image data and validate it using images from different studies. Gene expression profiling will be used to detect transcriptional changes in CRC, which can be used as an early biomarker to identify molecules with desirable therapeutic endpoints. The study aims to identify novel genes using next-generation sequencing and microarray data, overlapping genes from both datasets to determine associated biological processes, cellular components, and molecular functions. Crucial pathways and protein-protein networks will be explored to better understand cellular activities and biological processes. After identifying targets, the next objective is to screen suitable molecules using a drug repurposing approach to find potential drugs targeting vital genes/proteins. Docking studies will be performed to validate the drugs predicted by the drug-repurposing analysis.