Activity Detail
Seminar
Advances in network-based algorithms to predict metabolic vulnerabilities in cancer
Francisco J. Planes
Cancer cells undergo metabolic reprogramming to meet their high energy demands and biosynthetic needs. Understanding these adjustments can provide novel targeted therapies that could disrupt and impair proliferation of cancerous cells. Genome-scale metabolic models (GEMs) constitute a relevant strategy to address this problem. Based on GEMs, we introduced the genetic Minimal Cut Set (gMCS) approach (Apaolaza et al. 2017) and, more recently, gmctool (Valcarcel et al. 2024), a computational tool that exploits the concept of synthetic lethality to predict metabolic vulnerabilities in cancer based on transcriptomics data. In this talk, we summarize the gMCS approach and the capabilities of gmctool, including their application to multiple myeloma and supportive experimental validation. Moreover, we present new research areas and extensions of gmctool to consider nutritional perturbations and regulatory pathways.
Professor Francisco J. Planes is principal investigator in the Computational Biology group at the School of Engineering of the University of Navarra, Tecnun. His research has focused on the development of new algorithms, mainly based on optimization and statistical techniques, for the analysis of molecular networks in the context of high-thorughput technologies ("omics" data), with varied applications, but mainly in cancer and personalized nutrition. He has participated in 15 research projects related with metabolism and health, in order to identify novel therapeutic strategies and biomarkers. He has published more than 50 scientific articles in high-impact journals, such as Nature Communications, Nature Protocols, Genome Biology, PLoS Computational Biology or Bioinformatics.