Clinical significance of a microRNA signature for the identification and predicting prognosis in colorectal cancers with mucinous differentiation

Use of Personalized Biomarkers in Metastatic Colorectal Cancer and the Impact of AI

Colorectal cancer is a major cause of cancer-related death worldwide and is correlated with genetic and epigenetic alterations in the colonic epithelium. Genetic changes play a major role in the pathophysiology of colorectal cancer through the development of gene mutations, but recent research has shown an important role for epigenetic alterations. In this review, we try to describe the current knowledge about epigenetic alterations, including DNA methylation and histone modifications, as well as the role of non-coding RNAs as epigenetic regulators and the prognostic and predictive biomarkers in metastatic colorectal disease that can allow increases in the effectiveness of treatments. Additionally, the intestinal microbiota's composition can be an important biomarker for the response to strategies based on the immunotherapy of CRC. The identification of biomarkers in mCRC can be enhanced by developing artificial intelligence programs. We present the actual models that implement AI technology as a bridge connecting ncRNAs with tumors and conducted some experiments to improve the quality of the model used as well as the speed of the model that provides answers to users. In order to carry out this task, we implemented six algorithms: the naive Bayes classifier, the random forest classifier, the decision tree classifier, gradient boosted trees, logistic regression and SVM.

Genomic and epigenomic biomarkers in colorectal cancer: From diagnosis to therapy

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the United States. Despite ongoing efforts aimed at increasing screening for CRC and early detection, and development of more effective therapeutic regimens, the overall morbidity and mortality from this malignancy remains a clinical challenge. Therefore, identifying and developing genomic and epigenomic biomarkers that can improve CRC diagnosis and help predict response to current therapies are of paramount importance for improving survival outcomes in CRC patients, sparing patients from toxicity associated with current regimens, and reducing the economic burden associated with these treatments. Although efforts to develop biomarkers over the past decades have achieved some success, the recent availability of high-throughput analytical tools, together with the use of machine learning algorithms, will likely hasten the development of more robust diagnostic biomarkers and improved guidance for clinical decision-making in the coming years. In this chapter, we provide a systematic and comprehensive overview on the current status of genomic and epigenomic biomarkers in CRC, and comment on their potential clinical significance in the management of patients with this fatal malignancy, including in the context of precision medicine.