Desarrollo de estrategias de priorización de fármacos para tratar los genomas de cáncer en la medicina de precisión

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Bioquímica. Fecha de lectura: 28-04-2021Precision oncology requires the definition of a distinctive molecular fingerprint of the patient, as well as a pharmacological arsenal with the agents capable of reversing the associated pathogenic phenotype. One of the tools for molecular characterization is massive genomic sequencing, used with different objectives, including to provide evidence to identify specific and effective treatments. However, this technology entails several difficulties in its management, for example, distinguishing between harmful and benign alterations, as well as pointing out those that may indicate treatment guidelines. On the other hand, the available pharmacological arsenal is limited, so strategies are required to maximize its utility and the integration of available experimental compounds. The methodology of in silico prescription developed in this thesis, which we have named PanDrugs, has been conceived to contribute to overcoming these difficulties. For this purpose, we have built an extensive database of drug-gene associations as a search basis and a double prioritization system: (i) of genomic events according to their oncological impact and consequent therapeutic potential, (ii) and of drugs according to their availability and suitability in the detected molecular context. In order to determine its capabilities, it has been analyzed in several scenarios using different combinations of molecular evidence. In order to characterize in general terms the potential spectrum of therapeutic action in the different types of tumors, it has been systematically applied to several cases of the TCGA (The Cancer Genome Atlas). It has also been used in individual patients at a higher resolution, dissecting the proposed therapeutic suggestions at a molecular level, where it has been able to prioritize coherent options both at the level of sensitivity and resistance. It has demonstrated its potential for proposing therapeutic alternatives to conventional treatments in a clinical study of acute lymphoblastic T-cell leukemia with previous therapeutic failure. And finally, it has shown predictive capacity in the response to EGFR inhibitors in cases with available clinical informatio