Richard Wooster

Subtype and pathway specific responses to anticancer compounds in breast cancer

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.

Analysis of glutamine dependency in non-small cell lung cancer: GLS1 splice variant GAC is essential for cancer cell growth

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.

A Tale of Two Subunits: How the Neomorphic R132H IDH1 Mutation Enhances Production of αHG

Heterozygously expressed single-point mutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2, respectively) render these dimeric enzymes capable of producing the novel metabolite α-hydroxyglutarate (αHG). Accumulation of αHG is used as a biomarker for a number of cancer types, helping to identify tumors with similar IDH mutations. With IDH1, it has been shown that one role of the mutation is to increase the rate of conversion from αKG to αHG. To improve our understanding of the function of this mutation, we have detailed the kinetics of the normal (isocitrate to αKG) and neomorphic (αKG to αHG) reactions, as well as the coupled conversion of isocitrate to αHG. We find that the mutant IDH1 is very efficient in this coupled reaction, with the ability to form αHG from isocitrate and NADP(+). The wild type/wild type IDH1 is also able to catalyze this conversion, though it is much more sensitive to concentrations of isocitrate. This difference in behavior can be attributed to the competitive binding between isocitrate and αKG, which is made more favorable for αKG by the neomorphic mutation at arginine 132. Thus, each partial reaction in the heterodimer is functionally isolated from the other. To test whether there is a cooperative effect resulting from the two subunits being in a dimer, we selectively inactivated each subunit with a secondary mutation in the NADP/H binding site. We observed that the remaining, active subunit was unaffected in its associated activity, reinforcing the notion of each subunit being functionally independent. This was further demonstrated using a monomeric form of IDH from Azotobacter vinelandii, which can be shown to gain the same neomorphic reaction when a homologous mutation is introduced into that protein.

Quinoline 3-sulfonamides inhibit lactate dehydrogenase A and reverse aerobic glycolysis in cancer cells

BackgroundMost 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.MethodsHigh 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.Results3-((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.ConclusionsRapid 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.

Integrated analysis of breast cancer cell lines reveals unique signaling pathways

BackgroundCancer 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.ResultsWe 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.ConclusionsAll together, our results support the utility of symbolic system biology models for identification of therapeutic approaches that will be effective against breast cancer subsets.

Systematic analysis of genotype-specific drug responses in cancer

A systematic understanding of genotype‐specific sensitivity or resistance to anticancer agents is required to provide improved patient therapy. The availability of an expansive panel of annotated cancer cell lines enables comparative surveys of associations between genotypes and compounds of various target classes. Thus, one can better predict the optimal treatment for a specific tumor. Here, we present a statistical framework, cell line enrichment analysis (CLEA), to associate the response of anticancer agents with major cancer genotypes. Multilevel omics data, including transcriptome, proteome and phosphatome data, were integrated with drug data based on the genotypic classification of cancer cell lines. The results reproduced known patterns of compound sensitivity associated with particular genotypes. In addition, this approach reveals multiple unexpected associations between compounds and mutational genotypes. The mutational genotypes led to unique protein activation and gene expression signatures, which provided a mechanistic understanding of their functional effects. Furthermore, CLEA maps revealed interconnections between TP53 mutations and other mutations in the context of drug responses. The TP53 mutational status appears to play a dominant role in determining clustering patterns of gene and protein expression profiles for major cancer genotypes. This study provides a framework for the integrative analysis of mutations, drug responses and omics data in cancers.

Mitogen-activated protein kinase (MEK/ERK) inhibition sensitizes cancer cells to centromere-associated protein E inhibition

Inhibition of centromere‐associated protein‐E (CENP‐E) has demonstrated preclinical anti‐tumor activity in a number of tumor types including neuroblastoma. A potent small molecule inhibitor of the kinesin motor activity of CENP‐E has recently been developed (GSK923295). To identify an effective drug combination strategy for GSK923295 in neuroblastoma, we performed a screen of siRNAs targeting a prioritized set of genes that function in therapeutically tractable signaling pathways. We found that siRNAs targeted to extracellular signal‐related kinase 1 (ERK1) significantly sensitized neuroblastoma cells to GSK923295‐induced growth inhibition (p = 0.01). Inhibition of ERK1 activity using pharmacologic inhibitors of mitogen‐activated ERK kinase (MEK1/2) showed significant synergistic growth inhibitory activity when combined with GSK923295 in neuroblastoma, lung, pancreatic and colon carcinoma cell lines. Synergistic growth inhibitory activity of combined MEK/ERK and CENP‐E inhibition was a result of increased mitotic arrest and apoptosis. There was a significant correlation between ERK1/2 phosphorylation status in neuroblastoma cell lines and GSK923295 growth inhibitory activity (r = 0.823, p = 0.0006). Consistent with this result we found that lung cancer cell lines harboring RAS mutations, which leads to oncogenic activation of MEK/ERK signaling, were significantly more resistant than cell lines with wild‐type RAS to GSK923295‐induced growth inhibition (p = 0.047). Here we have identified (MEK/ERK) activity as a potential biomarker of relative GSK923295 sensitivity and have shown the synergistic effect of combinatorial MEK/ERK pathway and CENP‐E inhibition across different cancer cell types including neuroblastoma.

High-Content Analysis of Cancer Genome DNA Alterations

New technologies as well as concerted brute-force approaches have increased the content (number of genes) that can be characterized for genomic DNA alterations. Recent advances include the detection of activating point mutations in key kinase genes (BRAF, EGFR, and PIK3CA) in multiple cancer types: preliminary insight into the entire repertoire of genes that can be mutated in cancer; the discovery of new oncogenes by high-resolution profiling of DNA copy number alterations; and the bioinformatic-driven discovery of oncogenic gene fusions. High-content promoter methylation detection systems have been used to discover additional methylated genes and have provided evidence for a stem cell origin for certain tumors. Some of these advances have had significant impact on the development and clinical testing of new therapeutics.

High chromosome number in hematological cancer cell lines is a negative predictor of response to the inhibition of Aurora B and C by GSK1070916.

BackgroundAurora kinases play critical roles in mitosis and are being evaluated as therapeutic targets in cancer. GSK1070916 is a potent, selective, ATP competitive inhibitor of Aurora kinase B and C. Translation of predictive biomarkers to the clinic can benefit patients by identifying the tumors that are more likely to respond to therapies, especially novel inhibitors such as GSK1070916.Methods59 Hematological cancer-derived cell lines were used as models for response where in vitro sensitivity to GSK1070916 was based on both time and degree of cell death. The response data was analyzed along with karyotype, transcriptomics and somatic mutation profiles to determine predictors of response.Results20 cell lines were sensitive and 39 were resistant to treatment with GSK1070916. High chromosome number was more prevalent in resistant cell lines (p-value = 0.0098, Fisher Exact Test). Greater resistance was also found in cell lines harboring polyploid subpopulations (p-value = 0.00014, Unpaired t-test). A review of NOTCH1 mutations in T-ALL cell lines showed an association between NOTCH1 mutation status and chromosome number (p-value = 0.0066, Fisher Exact Test).ConclusionsHigh chromosome number associated with resistance to the inhibition of Aurora B and C suggests cells with a mechanism to bypass the high ploidy checkpoint are resistant to GSK1070916. High chromosome number, a hallmark trait of many late stage hematological malignancies, varies in prevalence among hematological malignancy subtypes. The high frequency and relative ease of measurement make high chromosome number a viable negative predictive marker for GSK1070916.

Catalogue, cause, complexity and cure; the many uses of cancer genome sequence.

DNA sequence and bioinformatics technology have enabled the analysis of the cancer genome, revealing the vast genetic complexity of this disease. The patterns of somatic mutations are a rich archaeological record of the insults received by the genome that have added to our understanding of the mutagenic process. However, very few frequently mutated genes have been identified with the majority of somatic mutational events occurring infrequently. These infrequent mutations, however, have been shown to effect well-defined biological pathways that are critical in driving the development and progression of human tumours, for example the MAPK and PI3K pathways. Current cancer sequencing studies are now providing somatic mutation data for distinct tumour types and subtypes, leading to the identification of disease-specific alterations and potential therapeutic targets.