rsg2sec on CCOMPUTO – COLLABORATIVE COMPUTATIONAL TOOLS FOR DUTCH MOLECULAR TUMOR BOARDS
Juliana F Vilacha M R Santos, Rick Oerlemanns and Matthew R. Groves
Advances in genomics techniques allowed the analysis of big sets of cancer patients what lead to the identification of mutations, showing a pattern shared by cancer patients. These mutations are often responsible for drive signaling pathways essential for malignant cells’ survival. Within the large number of patients who benefit from these genomics techniques, individuals harboring Non-Small Cell Lung Cancer (NSCLC) are the most favored by, due to the presence of mutations on enzymes such as the Epidermal Growth Factor Receptor, Anaplastic Lymphoma Kinase, Kirsten Rat Sarcoma GTPase or the BRAF serve as a biomarker for treatment regiments with kinase inhibitors.
The success of kinase inhibitors is linked to the presence or absence of a specific subset of mutations widely described in the literature. However, medical times are often challenged with mutation of unknown significance and/or impact on drug binding. Seeking to provide fast identification of mutational impact in the available treatments, Dutch University Medical Centers assembled Molecular Tumor Boards (MTB) where challenging patients flaunting novel mutations can be analyzed under the lights of a personalized medicine approach. Besides involving medical doctors and geneticists, the MTB from the University Medical Center of Groningen (UMCG) also relies on the use of computational biology for rapid assessment of such mutational landscape.
In this work, we present how classical tools from computational biology are applied daily in the context of drug screening in the presence of novel mutations and the impact this approach has on patient survival.