Published Paper Details:

Despite the known genetic, epigenetic, and transcriptomic alterations, colorectal cancer (CRC) is still one of the major causes of cancer death throughout the world. Recent progress in the field of transcriptome has greatly promoted our understanding regarding the molecular mechanism at the molecular level during CRC progression, which identified several key core genes, such as KRAS, MYC, TP53 and APC, that control oncogenic pathways such as Wnt/?-catenin, PI3K-AKT, inflammatory signaling, etc. The conjoining of transcriptomics with the epigenomics, especially the DNA methylation and histone modifications, has shed more light on tumor suppressor gene silencing and oncogene activation that can serve as potential biomarkers for the early detecting and prognosis of the disease as well as the selection of the therapies. Since much of their development into personalized medicine has been internalized by pharmaceutical companies for proprietary reasons, these markers have not been extracted. New therapeutic interventions involving reversal of the abnormal expression pattern of genes using epigenetic drugs running the gamut of histone deacetylase inhibitors (HDACi's) and DNA methyltransferase inhibitors (DNMTi's) are under investigation. Finally, artificial intelligence (AI) and machine learning is also having a huge role in analyzing large scale transcriptomic data and it is transforming biomarker discovery, treatment selection and predicting patient outcomes, transcriptomic research will lead the personalized view of CRC and will provide a new hope for the early detection, prognosis, and personalized targeted therapy. As such, continuous multi-omics integration, computational biology and clinical validation efforts will be a crucial component in furthering CRC transformation into a renowned disease for which simple management strategies, improved survival and treatment efficacy can all be attained.