S-Score tools in the study of the cancer and a proposition to use it in cancer's simulation development
Cancer. SKCM. S-Score. Data analyzes. Cancer simulation
Cancer is characterized by being a dynamic and systemic disease that affects thousands of people around the world. Among the several factors that are related to its development are the mutations of the somatic types, which confer advantages on clonal selectivity and are linked to oncogenesis. This type of mutation corresponds to the insertions, deletions and rearrangements of genes are known as mutations drivers. Such mutations are sub-divided into two groups: oncongenic and suppressive. In order to better understand and study this disease approaches are found in the literature. Exploiting the data generated by next generation sequencing is one of these. However, although the data set generated is expressive, good methodologies are necessary to exhaust the generated data. Here, a tool called sscore-tools using the methodology developed by S-Score, which tries to infer the potentiality of a gene to be oncogenic or suppressor, was implemented and optimized for the purpose of exploring the public data of the TCGA in a approach in width and depth. Skin cancer (SKCM) was chosen to analyze the data generated by the tool where, by cross-referencing S-Score data from various tissues against SKCM, it was possible to observe common genes with similar characteristics in S-score values with oncogenic and suppressor potential linked to the analyzed tissues. In the second part of this work we intend to use the data generated by this tool in the study of tumor cell progression and other simulations involving the S-Score methodology.