The histone deactylase SIRT6 is a novel tumor suppressor that regulates cancer metabolism.

Report for the scientific sojourn carried out at the University of Aarhus, Denmark, from 2010 to 2012. Reprogramming of cellular metabolism is a key process during tumorigenesis. This metabolic adaptation is required in order to sustain the energetic and anabolic demands of highly proliferative cancer cells. Despite known for decades (Warburg effect), the precise molecular mechanisms regulating this switch remained unexplored. We have identify SIRT6 as a novel tumor suppressor that regulates aerobic glycolysis in cancer cells. Importantly, loss of this sirtuin in non-transformed cells leads to tumor formation without activation of known oncogenes, indicating that SIRT6 functions as a first-hit tumor suppressor. Furthermore, transformed SIRT6-deficient cells display increased glycolysis and tumor growth in vivo, suggesting that SIRT6 plays a role in both establishment and maintenance of cancer. We provide data demonstrating that the glycolytic switch towards aerobic glycolysis is the main driving force for tumorigenesis in SIRT6-deficient cells, since inhibition of glycolysis in these cells abrogates their tumorigenic potential. By using a conditional SIRT6-targeted allele, we show that deletion of SIRT6 in vivo increases the number, size and aggressiveness of tumors, thereby confirming a role of SIRT6 as a tumor suppressor in vivo. In addition, we describe a new role for SIRT6 as a regulator of ribosome biogenesis by co-repressing MYC transcriptional activity. Therefore, by repressing glycolysis and ribosomal gene expression, SIRT6 inhibits tumor establishment and progression. Further validating these data, SIRT6 is selectively downregulated in several human cancers, and expression levels of SIRT6 predict both prognosis and tumor-free survival rates, highlighting SIRT6 as a critical modulator of cancer metabolism. Our results provide a potential Achilles’ hill to tackle cancer metabolism.

Human synthetic lethal inference as potential anti-cancer target gene detection

Background: Two genes are called synthetic lethal (SL) if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism's fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the identification of these mutated genes' SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods. Results: In the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes) in order to reconstruct the phylogenetically-inferred SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases) as well as on existent approved drugs (DrugBank database) supports our selection of cancer-therapy candidates.Conclusions: Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology.