LAUSR

Prostate cancer (PCa) is the fifth cause of death by cancer worldwide, second in the male population. In the European Union (EU), PCa exhibits the highest incidence among cancer types in men, and represents the third cause of death by cancer in the gender. Despite the good response to current standard of care, a fraction of patients exhibit recurrence and develop metastatic disease after the failure of subsequent therapeutic regimens. In this respect, the molecular aspects related to disease progression and therapy response remain elusive. Our group has integrated computational biology, mouse modeling and high throughput OMICs to report a new molecular hub at the core of PCa aggressiveness. We searched for genes that would cooperate with transcription factors to remodel the transcriptional landscape of metabolic enzymes. The analysis of up to 5 independent patient datasets revealed that PGC1a dominated the list of 23 transcriptional co-regulators, with a strong down-regulation in PCa and a significant association to poor prognosis. Genetically engineered mouse models provided proof of the causal association between PGC1a and PCa progression. We first observed that loss of Pgc1a was not an initiation event, which was demonstrated by the analysis of murine tissues from prostate conditional Pgc1a knockouts alone or in combination with Pten heterozygosity. In the context of complete Pten loss, which results in cancerous lesions, we observed that Pgc1a deleted mice exhibited sings of metastatic disease. This data reflects the complexity of genetic interactions in cancer, whereby cancer genes may play a critical role only in discrete stages of the disease. We opted for the use of PCa cell lines as a discovery platform for the molecular deconstruction of the effects downstream PGC1a. We failed to detect any protein produced with commercial antibodies to the best of our efforts. It is worth noting that the reagents for the detection of this protein are yet underdeveloped, and the manipulation of the culture conditions and stimuli could modify the detection capabilities. This result encouraged us to develop inducible lentiviral systems to titrate and control PGC1a ectopic expression. Both in vitro and in vivo, we could demonstrate that the cell lines replicated the results derived from patient and genetic mouse model analysis. Of importance, we could consistently revert the pre-existing metastatic capacity of PCa cells by expressing PGC1a. We employed whole genome transcriptomics and high resolution metabolomics to characterize the molecular changes elicited by this co-regulator. The suppressive activity of PGC1a was accompanied by a metabolic rewiring, hence favoring a catabolic state at the expense of anabolism. The transcriptional analysis pointed at the Estrogen-related receptor alpha (ERRa) as the major executioner of the gene expression program elicited by PGC1a, which allowed us to build a gene expression signature based on the PGC1aERRa complex that was validated in cell lines, murine samples and patient datasets. The relevance of ERRa for the anti-metastatic properties of the transcriptional co-regulator was demonstrated through 2 independent experimental approaches. On the one hand, gene silencing of the transcription factor abolished the gene expression changes and metastasis-suppressive activity of PGC1a. On the other hand, the gene expression signature that was built based on the common PGC1a-ERRa targets recapitulated the prognostic potential of the transcriptional co-regulator. This “gene signature” could therefore be used to as a prognostic tool and to stratify prostate cancer patients at risk of developing aggressive PCa. PGC1a expands the list of genes that regulate PCa progression through the regulation of metabolism, an emerging hallmark of cancer. Lipid synthesis supports the development and progression of PCa, which has been tightly associated to the increase in Fatty Acid Synthase (FASN). In addition, recent reports support the notion that classical oncogenes promote changes in PCa metabolism. AKT and MYC status determines the metabolic state of PCa cells. AKT1 activation is associated with the activation of aerobic glycolysis and the production of lactate, and MYC over-expression leads to a deregulation of lipid metabolism. In addition, compound Pten and Tp53 in PCa leads to the up-regulation of Hexokinase 2 (HK2), and the consequent activation of aerobic glycolysis.