‘Transcriptional regulation of metabolism for precision medicine in prostate cancer’

Miguel Unda Urzaiz; Ana Loizaga Iriarte and Aitziber Urgalde Olano, Hospital Universitario de Basurto; Verónica Torrano Moya; Natalia Martín Martín; Lorea Valcárcel Jiménez; Amaia Zabala Letona; Sonia Fernández Ruiz and Ana Rosa Cortázar Ortiz, CIC bioGUNE; María Isabel Loza García and Eduardo Domínguez Medina, University of Santiago de Compostela.

Prostate cancer exhibits high incidence in Western societies. Although the effectiveness of first line therapy (surgery or radiation) is high, tumors that relapse and overcome second-line therapies (chemotherapy or androgen deprivation) acquire aggressive properties that are responsible for a high fraction of the mortality associated to the illness.

In our laboratory we have demonstrated that changes in cell metabolism are crucial for cancer cell survival and progression. Importantly, we have observed that metabolic changes support anabolic growth in distal tissues during the formation of metastasis.

This project is based on the hypothesis that cellular metabolism plays a key role in the acquisition of invasive properties in prostate cancer. We propose that understanding the metabolic requirements of aggressive prostate cancer may result in the identification of therapeutically relevant vulnerabilities for effective treatment.

To address this notion, we propose to study the regulation of metabolism in prostate cancer from a novel perspective. First, we will investigate the contribution of transcriptional programs to the metabolic phenotype, based on previous studies suggesting that transcriptional co-activators contribute to the establishment of metastasis. Second, we will perform a small molecule screen aimed at the identification of compounds with higher activity in prostate cancer with the poor prognosis metabolic signature Third, we will define a prognostic and predictive biomarker based on the aforementioned metabolic program, that will allow the identification of patients at risk of recurrence and potential candidates for novel therapeutic approaches.

We propose that this strategy will allow us to move forward in implementing precision medicine, through the identification of metabolic vulnerabilities that could lead to the identification of effective therapies associated to biomarker-based patient stratification.