Search

Castrate-resistant prostate cancer (CRPC) is poorly characterized and heterogeneous and while the androgen receptor (AR) is of singular importance, other factors such as c-Myc and the E2F family also play a role in later stage disease. HES6 is a transcription co-factor associated with stem cell characteristics in neural tissue. Here we show that HES6 is up-regulated in aggressive human prostate cancer and drives castration-resistant tumour growth in the absence of ligand binding by enhancing the transcriptional activity of the AR, which is preferentially directed to a regulatory network enriched for transcription factors such as E2F1. In the clinical setting, we have uncovered a HES6-associated signature that predicts poor outcome in prostate cancer, which can be pharmacologically targeted by inhibition of PLK1 with restoration of sensitivity to castration. We have therefore shown for the first time the critical role of HES6 in the development of CRPC and identified its potential in patient-specific therapeutic strategies.

Background: Most normal cells in the presence of oxygen utilize glucose for mitochondrial oxidative phosphorylation. In contrast, many cancer cells rapidly convert glucose to lactate in the cytosol, a process termed aerobic glycolysis. This glycolytic phenotype is enabled by lactate dehydrogenase (LDH), which catalyzes the inter-conversion of pyruvate and lactate. The purpose of this study was to identify and characterize potent and selective inhibitors of LDHA., Methods: High throughput screening and lead optimization were used to generate inhibitors of LDHA enzymatic activity. Effects of these inhibitors on metabolism were evaluated using cell-based lactate production, oxygen consumption, and 13C NMR spectroscopy assays. Changes in comprehensive metabolic profile, cell proliferation, and apoptosis were assessed upon compound treatment., Results: 3-((3-carbamoyl-7-(3,5-dimethylisoxazol-4-yl)-6-methoxyquinolin-4-yl) amino) benzoic acid was identified as an NADH-competitive LDHA inhibitor. Lead optimization yielded molecules with LDHA inhibitory potencies as low as 2 nM and 10 to 80-fold selectivity over LDHB. Molecules in this family rapidly and profoundly inhibited lactate production rates in multiple cancer cell lines including hepatocellular and breast carcinomas. Consistent with selective inhibition of LDHA, the most sensitive breast cancer cell lines to lactate inhibition in hypoxic conditions were cells with low expression of LDHB. Our inhibitors increased rates of oxygen consumption in hepatocellular carcinoma cells at doses up to 3 microM, while higher concentrations directly inhibited mitochondrial function. Analysis of more than 500 metabolites upon LDHA inhibition in Snu398 cells revealed that intracellular concentrations of glycolysis and citric acid cycle intermediates were increased, consistent with enhanced Krebs cycle activity and blockage of cytosolic glycolysis. Treatment with these compounds also potentiated PKM2 activity and promoted apoptosis in Snu398 cells., Conclusions: Rapid chemical inhibition of LDHA by these quinoline 3-sulfonamids led to profound metabolic alterations and impaired cell survival in carcinoma cells making it a compelling strategy for treating solid tumors that rely on aerobic glycolysis for survival.

One of the hallmarks of cancer is metabolic deregulation. Many tumors display increased glucose uptake and breakdown through the process of aerobic glycolysis, also known as the Warburg effect. Less studied in cancer development and progression is the importance of the glutamine (Gln) pathway, which provides cells with a variety of essential products to sustain cell proliferation, such as ATP and macromolecules for biosynthesis. To this end Gln dependency was assessed in a panel of non-small cell lung cancer lines (NSCLC). Gln was found to be essential for the growth of cells with high rates of glutaminolysis, and after exploring multiple genes in the Gln pathway, GLS1 was found to be the key enzyme associated with this dependence. This dependence was confirmed by observing the rescue of decreased growth by exogenous addition of downstream metabolites of glutaminolysis. Expression of the GLS1 splice variant KGA was found to be decreased in tumors compared with normal lung tissue. Transient knock down of GLS1 splice variants indicated that loss of GAC had the most detrimental effect on cancer cell growth. In conclusion, NSCLC cell lines depend on Gln for glutaminolysis to a varying degree, in which the GLS1 splice variant GAC plays an essential role and is a potential target for cancer metabolism-directed therapy.

Breast cancers are comprised of molecularly distinct subtypes that may respond differently to pathway-targeted therapies now under development. Collections of breast cancer cell lines mirror many of the molecular subtypes and pathways found in tumors, suggesting that treatment of cell lines with candidate therapeutic compounds can guide identification of associations between molecular subtypes, pathways, and drug response. In a test of 77 therapeutic compounds, nearly all drugs showed differential responses across these cell lines, and approximately one third showed subtype-, pathway-, and/or genomic aberration-specific responses. These observations suggest mechanisms of response and resistance and may inform efforts to develop molecular assays that predict clinical response.

Centromere-associated protein-E (CENP-E) is a kinetochore-associated mitotic kinesin that is thought to function as the key receptor responsible for mitotic checkpoint signal transduction after interaction with spindle microtubules. We have identified GSK923295, an allosteric inhibitor of CENP-E kinesin motor ATPase activity, and mapped the inhibitor binding site to a region similar to that bound by loop-5 inhibitors of the kinesin KSP/Eg5. Unlike these KSP inhibitors, which block release of ADP and destabilize motor-microtubule interaction, GSK923295 inhibited release of inorganic phosphate and stabilized CENP-E motor domain interaction with microtubules. Inhibition of CENP-E motor activity in cultured cells and tumor xenografts caused failure of metaphase chromosome alignment and induced mitotic arrest, indicating that tight binding of CENP-E to microtubules is insufficient to satisfy the mitotic checkpoint. Consistent with genetic studies in mice suggesting that decreased CENP-E function can have a tumor-suppressive effect, inhibition of CENP-E induced tumor cell apoptosis and tumor regression.

Background: Cancer is a heterogeneous disease resulting from the accumulation of genetic defects that negatively impact control of cell division, motility, adhesion and apoptosis. Deregulation in signaling along the EgfR-MAPK pathway is common in breast cancer, though the manner in which deregulation occurs varies between both individuals and cancer subtypes., Results: We were interested in identifying subnetworks within the EgfR-MAPK pathway that are similarly deregulated across subsets of breast cancers. To that end, we mapped genomic, transcriptional and proteomic profiles for 30 breast cancer cell lines onto a curated Pathway Logic symbolic systems model of EgfR-MAPK signaling. This model was composed of 539 molecular states and 396 rules governing signaling between active states. We analyzed these models and identified several subtype-specific subnetworks, including one that suggested Pak1 is particularly important in regulating the MAPK cascade when it is over-expressed. We hypothesized that Pak1 over-expressing cell lines would have increased sensitivity to Mek inhibitors. We tested this experimentally by measuring quantitative responses of 20 breast cancer cell lines to three Mek inhibitors. We found that Pak1 over-expressing luminal breast cancer cell lines are significantly more sensitive to Mek inhibition compared to those that express Pak1 at low levels. This indicates that Pak1 over-expression may be a useful clinical marker to identify patient populations that may be sensitive to Mek inhibitors., Conclusions: All together, our results support the utility of symbolic system biology models for identification of therapeutic approaches that will be effective against breast cancer subsets.