Multi-omics approaches for diagnosis, prognosis and response to treatment of colorectal cancer.
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Director/sConesa Zamora, Pablo; Naccarati, Alessio
The high heterogeneity of colorectal cancer (CRC) in the disease biology, therapy response, and prognosis has become evident in the recent few years. For this reason, an extensive disease stratification is required. The advent of Big Data analysis in medical research has revolutionized the traditional hypothesis-driven approach. Big Data analysis provides an invaluable opportunity to improve individual and public health. In fact, the availability of large databases to capture and store the genomic landscape of patients with CRC, provides information on the genes that are frequently deregulated in CRC. Moreover, the possibility of using gene-expression profiling and highly sensitive next-generation sequencing analyses to differentiate the subtypes of CRC into prognostic groups can also lead to a better understanding of adequate CRC treatment, improving prognosis and patients’ quality of life. The aim of this study, conducted in collaboration with the Italian Institute for Genomic Medici...