Validating the concept of mutational signatures with isogenic cell models.

The diversity of somatic mutations in human cancers can be decomposed into individual mutational signatures, patterns of mutagenesis that arise because of DNA damage and DNA repair processes that have occurred in cells as they evolved towards malignancy. Correlations between mutational signatures and environmental exposures, enzymatic activities and genetic defects have been described, but human cancers are not ideal experimental systems-the exposures to different mutational processes in a patient's lifetime are uncontrolled and any relationships observed can only be described as an association. Here, we demonstrate the proof-of-principle that it is possible to recreate cancer mutational signatures in vitro using CRISPR-Cas9-based gene-editing experiments in an isogenic human-cell system. We provide experimental and algorithmic methods to discover mutational signatures generated under highly experimentally-controlled conditions. Our in vitro findings strikingly recapitulate in vivo observations of cancer data, fundamentally validating the concept of (particularly) endogenously-arising mutational signatures

An upper level for what-if analysis

Living in a knowledge-based society, one of the most important tasks of decision makers is to know how to deal with information and knowledge that add value to their activities. Decision makers need to retrieve high-quality sets of information in order to gain competitive advantages in their business world. Otherwise, companies may struggle with several difficulties when it comes to market competition and business reputation. What-If analysis tools can help decision-makers in this matter. This technique allows for simulating hypothetical scenarios without harming the business and helping anticipate future events, by testing hypothesis. Therefore, in this paper, we propose a hybridization approach and develop a hybrid methodology, which aims at discovering the best recommendations for What-If analysis scenarios’ parameters using OLAP usage preferences. We also develop a software platform to illustrate the hybrid methodology with a specific case study. This hybridization process will help the user during the design and implementation of a What-If analysis process, overcoming the pitfalls of the conventional What-If analysis process.This work was supported by Conselho Nacional de Pesquisa (CNPq), COMPETE: POCI01-0145-FEDER-007043, and by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We also thank Instituto Federal de Educação, Ciência e Tecnologia de Goiás (IFG)