Kelyon's commitment in the field of oncology is constantly renewed, with the aim to ensure access to personalized treatment paths that, in line with the patient's genetic profile, can effectively reduce healing times with high performance results. Accordingly, we are aware that investment in research and digital innovation are the key drivers for the implementation of the new frontier of precision medicine, increasingly oriented to Next Generation Sequencing (NGS) technologies, which have revolutionized genomic research.
In this light, we are proud to highlight the collaboration of our research team, especially of our bioengineer and machine learning researcher Marco Benedetto and our technical director Stefano Tagliaferri, with the University of Salerno, IRCCS (Istituto Nazionale Tumori) “Fondazione G. Pascale”, CROM (Centro Ricerche Oncologiche Mercogliano) and CNR (Consiglio Nazionale delle Ricerche), which has led to a notable study on how multiple network analysis can be applied in clinical practice to investigate and exploit the interaction of different genetic mutations on the behavior and drug treatment of cancer. Specifically, the results of the study, published and available on Briefings in Bioinformatics, show that, by using our pipeline based on a multiple network approach, it has been possible to demonstrate and validate what are the joint effects and changes of the molecular profile that occur in patients with metastatic colorectal carcinoma (mCRC) carrying mutations in multiple genes.
Based on Kelyon's experience in oncology, the results obtained are applied for the development of Oncoterapie in collaboration with 23 partners, among others the University of Salerno, the University of Naples “Federico II”, CNR (Consiglio Nazionale delle Ricerche), Telethon, Ebris (European Biomedical Research Institute of Salerno, IRCCS (Istituto Nazionale Tumori) “Fondazione G. Pascale”. The strategy behind Oncoterapie is focused on multiple network analysis to improve cancer diagnostics using biological networks and generate statistical inference predictive models to probe regulatory relationships between molecular components. The pipeline implemented in Oncoterapie is characterized by a multistep design, which includes different biological-molecular networks: disease-disease, gene-disease, gene-variant-disease, gene-gene, protein-protein interaction, and multilayer drugs networks.
We firmly believe in the value of multidisciplinary research and innovation, which we constantly transfer into our solutions, and we will strive day after day to shape the future of oncology by creating new, sustainable models of care.
Read the full article on Briefings in Bioinformatics