The advent of next generation sequencing can greatly extend the characterization of genes not yet employed in the clinical practice. Therefore, a wide range of informations will be shortly available to the oncologists to improve the prognostic stratification and define the best therapeutic choice for colorectal cancer (CRC) patients.
Taking advantage of the IT-PGM sequencing applied to the routine predictive characterization of metastatic CRC cases for responsiveness to anti-EGFR therapy, we determined the mutational status of 128 CRC samples with respect to 22 genes including, but not limited to, KRAS, NRAS and BRAF. This revealed the non-random co-occurrence of specific mutation associations, many of which reached statistical significance. Based on the mutational asset, the 128 mCRC cases could be classified in four specific Mutation Association Patterns (MAP1-4).
We now propose to validate our results in a much larger series of primary CRC samples. Moreover, clinicopathological association studies will be performed to define whether these patterns could be useful for prognostic and therapeutic stratification of CRC. We expect that our results will help improving the prognostic stratification of CRC patients, allow the identification of new predictive biomarkers for currently used molecular therapies (i.e., anti-EGFR, anti-VEGF) and indicate new actionable targets, through a Next Generation Sequencing approach easily deliverable to the routine diagnostics for CRC.
The advent of third-generation sequencing instruments is greatly expanding the mutational characterization of genes that are not currently employed in the clinical practice. By this mean, a wide range of novel informations is becoming available to define the best prognostic stratification and the best therapeutic options for mCRC patients. Indeed, by performing the routine clinical analysis of RAS/BRAF genes via IT-PGM approach, we can gain additional information useful for patient stratification. Following this approach, our project will immediately bring to the patient bedside the use of advanced sequencing technology, and, at the same time, gain information from the clinical routine which might direct new biological investigation for potentially novel therapeutic approaches in specific cancer patient subset. In fact, based on our preliminary results, we are confident our work will immediately contribute to improving the prognostic stratification of mCRC patients and to identify new biomarkers for predictive therapies currently in use (anti-EGFR, anti-VEGF), or still largely underemployed (anti-PI3K), as well as provide information on new actionable targets.