Exploiting metabolic vulnerabilities to overcome resistance to targeted therapies in colorectal cancer

Colorectal cancer (CRC) is the third most frequent type of solid tumor worldwide (1). Despite great advances in the knowledge of the genetic bases of CRC, a more comprehensive understanding of the mechanisms accounting for tumor initiation, progression and resistance to therapy is still needed. Recently, the deregulation of cellular metabolism has emerged as a key hallmark of cancer (2, 3). Metabolic reprogramming represents indeed a key process to provide CRC cells with the energy substrates, anaplerotic precursors and reducing equivalents required to fuel tumor growth and survival in stressing settings. In addition, treatment with targeted therapies can further trigger a metabolic rewiring to adapt to the novel growth conditions and to allow CRC to cope with the downregulation of oncogenes that supports cell growth. In this regard, metabolism direct impact on epigenetics (4) needs to be considered in CRC studies as an additional mechanism of stress condition adaptation. In this research proposal, we aim at providing key evidence regarding the metabolic makeup of colorectal tumors displaying representative types of genomic profiles and their corresponding pairs with acquired resistance to commonly used targeted therapies. The project is divided in five main work packages (WPs) with the following objectives: WP1, WP2 and WP3 will respectively identify metabolic, proteomic and epigenetic vulnerabilities of CRC preclinical models; WP4 will exploit findings gathered from the previous WPs to devise novel therapeutic strategies. Finally, the integration of WPs will take place by translationally validating data in a platform of patient-derived organoids (PDOs) already available or de novo generated in WP5. The elucidation of pathways underlying metabolic reprogramming will have a tremendous impact by shedding light on therapeutic targets useful for developing new translational clinical approaches and overcoming resistance to currently employed targeted therapies. A PDO biobank will represent a valuable tool for predicting patient responses to therapy and identifying alternative treatment regimens for resistant patients. The results are expected to improve our knowledge of the CRC metabolic landscape, unveiling diverse pathways and new vulnerabilities for treating patients.