Lauren S. Fink

Resistance to BET Bromodomain Inhibitors Is Mediated by Kinome Reprogramming in Ovarian Cancer

Small-molecule BET bromodomain inhibitors (BETis) are actively being pursued in clinical trials for the treatment of a variety of cancers, but the mechanisms of resistance to BETis remain poorly understood. Using a mass spectrometry approach that globally measures kinase signaling at the proteomic level, we evaluated the response of the kinome to targeted BETi treatment in a panel of BRD4-dependent ovarian carcinoma (OC) cell lines. Despite initial inhibitory effects of BETi, OC cells acquired resistance following sustained treatment with the BETi JQ1. Through application of multiplexed inhibitor beads (MIBs) and mass spectrometry, we demonstrate that BETi resistance is mediated by adaptive kinome reprogramming, where activation of compensatory pro-survival kinase networks overcomes BET protein inhibition. Furthermore, drug combinations blocking these kinases may prevent or delay the development of drug resistance and enhance the efficacy of BETi therapy.

Pharmacological profiling of kinase dependency in cell lines across triple-negative breast cancer subtypes

Triple-negative breast cancers (TNBC), negative for estrogen receptor, progesterone receptor, and ERBB2 amplification, are resistant to standard targeted therapies and exhibit a poor prognosis. Furthermore, they are highly heterogeneous with respect to genomic alterations, and common therapeutic targets are lacking though substantial evidence implicates dysregulated kinase signaling. Recently, six subtypes of TNBC were identified based on gene expression and were proposed to predict sensitivity to a variety of therapeutic agents including kinase inhibitors. To test this hypothesis, we screened a large collection of well-characterized, small molecule kinase inhibitors for growth inhibition in a panel of TNBC cell lines representing all six subtypes. Sensitivity to kinase inhibition correlated poorly with TNBC subtype. Instead, unsupervised clustering segregated TNBC cell lines according to clinically relevant features including dependence on epidermal growth factor signaling and mutation of the PTEN tumor suppressor. We further report the discovery of kinase inhibitors with selective toxicity to these groups. Overall, however, TNBC cell lines exhibited diverse sensitivity to kinase inhibition consistent with the lack of common driver mutations in this disease. Although our findings support specific kinase dependencies in subsets of TNBC, they are not associated with gene expression–based subtypes. Instead, we find that mutation status can be an effective predictor of sensitivity to inhibition of particular kinase pathways for subsets of TNBC. Mol Cancer Ther; 14(1); 298–306. ©2014 AACR.

Identifying three-dimensional structures of autophosphorylation complexes in crystals of protein kinases

Structural bioinformatics reveals autophosphorylation complexes hidden in published crystals of protein kinases. Autophosphorylation sites revealed Three-dimensional structural data from crystals of protein kinases have aided the development of drugs and provided insights into kinase regulation and substrate recognition. Many protein kinases trans-autophosphorylate; one kinase phosphorylates another molecule of the same kinase. Anticipating that published crystallographic data may include undescribed information, Xu et al. developed a bioinformatics method to analyze the crystals of kinases for the presence of complexes representing the conformation of kinases during autophosphorylation. The authors identified 15 autophosphorylation complexes in the Protein Data Bank, including five that had not been previously described. With this additional information, structural motifs involved in autophosphorylation become identifiable, which may aid in rational drug design and understanding disease-associated mutations. Protein kinase autophosphorylation is a common regulatory mechanism in cell signaling pathways. Crystal structures of several homomeric protein kinase complexes have a serine, threonine, or tyrosine autophosphorylation site of one kinase monomer located in the active site of another monomer, a structural complex that we call an “autophosphorylation complex.” We developed and applied a structural bioinformatics method to identify all such autophosphorylation complexes in x-ray crystallographic structures in the Protein Data Bank (PDB). We identified 15 autophosphorylation complexes in the PDB, of which five complexes had not previously been described in the publications describing the crystal structures. These five complexes consist of tyrosine residues in the N-terminal juxtamembrane regions of colony-stimulating factor 1 receptor (CSF1R, Tyr561) and ephrin receptor A2 (EPHA2, Tyr594), tyrosine residues in the activation loops of the SRC kinase family member LCK (Tyr394) and insulin-like growth factor 1 receptor (IGF1R, Tyr1166), and a serine in a nuclear localization signal region of CDC-like kinase 2 (CLK2, Ser142). Mutations in the complex interface may alter autophosphorylation activity and contribute to disease; therefore, we mutated residues in the autophosphorylation complex interface of LCK and found that two mutations impaired autophosphorylation (T445V and N446A) and mutation of Pro447 to Ala, Gly, or Leu increased autophosphorylation. The identified autophosphorylation sites are conserved in many kinases, suggesting that, by homology, these complexes may provide insight into autophosphorylation complex interfaces of kinases that are relevant drug targets.

A high-content screening assay for small-molecule modulators of oncogene-induced senescence.

Cellular senescence is a state of stable cell growth arrest. Activation of oncogenes such as RAS in mammalian cells typically triggers cellular senescence. Oncogene-induced senescence (OIS) is an important tumor suppression mechanism, and suppression of OIS contributes to cell transformation. Oncogenes trigger senescence through a multitude of incompletely understood downstream signaling events that frequently involve protein kinases. To identify target proteins required for RAS-induced senescence, we developed a small-molecule screen in primary human fibroblasts undergoing senescence induced by oncogenic RAS (H-RasG12V). Using a high-content imaging system to monitor two hallmarks of senescence, senescence-associated β-galactosidase activity expression and inhibition of proliferation, we screened a library of known small-molecule kinase inhibitors for those that suppressed OIS. Identified compounds were subsequently validated and confirmed using a third marker of senescence, senescence-associated heterochromatin foci. In summary, we have established a novel high-content screening platform that may be useful for elucidating signaling pathways mediating OIS by targeting critical pathway components.

Metabolite Profiling Reveals the Glutathione Biosynthetic Pathway as a Therapeutic Target in Triple-Negative Breast Cancer

Cancer cells can exhibit altered dependency on specific metabolic pathways and targeting these dependencies is a promising therapeutic strategy. Triple-negative breast cancer (TNBC) is an aggressive and genomically heterogeneous subset of breast cancer that is resistant to existing targeted therapies. To identify metabolic pathway dependencies in TNBC, we first conducted mass spectrometry–based metabolomics of TNBC and control cells. Relative levels of intracellular metabolites distinguished TNBC from nontransformed breast epithelia and revealed two metabolic subtypes within TNBC that correlate with markers of basal-like versus non-basal–like status. Among the distinguishing metabolites, levels of the cellular redox buffer glutathione were lower in TNBC cell lines compared to controls and markedly lower in non-basal–like TNBC. Significantly, these cell lines showed enhanced sensitivity to pharmacologic inhibition of glutathione biosynthesis that was rescued by N-acetylcysteine, demonstrating a dependence on glutathione production to suppress ROS and support tumor cell survival. Consistent with this, patients whose tumors express elevated levels of γ-glutamylcysteine ligase, the rate-limiting enzyme in glutathione biosynthesis, had significantly poorer survival. We find, further, that agents that limit the availability of glutathione precursors enhance both glutathione depletion and TNBC cell killing by γ-glutamylcysteine ligase inhibitors in vitro. Importantly, we demonstrate the ability to this approach to suppress glutathione levels and TNBC xenograft growth in vivo. Overall, these findings support the potential of targeting the glutathione biosynthetic pathway as a therapeutic strategy in TNBC and identify the non-basal-like subset as most likely to respond. Mol Cancer Ther; 17(1); 264–75. ©2017 AACR.

Network modeling of kinase inhibitor polypharmacology reveals pathways targeted in chemical screens

Small molecule screens are widely used to prioritize pharmaceutical development. However, determining the pathways targeted by these molecules is challenging, since the compounds are often promiscuous. We present a network strategy that takes into account the polypharmacology of small molecules in order to generate hypotheses for their broader mode of action. We report a screen for kinase inhibitors that increase the efficacy of gemcitabine, the first-line chemotherapy for pancreatic cancer. Eight kinase inhibitors emerge that are known to affect 201 kinases, of which only three kinases have been previously identified as modifiers of gemcitabine toxicity. In this work, we use the SAMNet algorithm to identify pathways linking these kinases and genetic modifiers of gemcitabine toxicity with transcriptional and epigenetic changes induced by gemcitabine that we measure using DNaseI-seq and RNA-seq. SAMNet uses a constrained optimization algorithm to connect genes from these complementary datasets through a small set of protein-protein and protein-DNA interactions. The resulting network recapitulates known pathways including DNA repair, cell proliferation and the epithelial-to-mesenchymal transition. We use the network to predict genes with important roles in the gemcitabine response, including six that have already been shown to modify gemcitabine efficacy in pancreatic cancer and ten novel candidates. Our work reveals the important role of polypharmacology in the activity of these chemosensitizing agents.

Abstract A73: Metabolite profiling reveals the glutathione biosynthetic pathway as a therapeutic target in triple negative breast cancers

Identifying metabolic pathway alterations that are critical to support cancer growth is a key hurdle for developing therapeutic strategies that exploit these pathways. We have applied metabolomic and pharmacological approaches to identify targetable pathways in triple negative breast cancer (TNBC). TNBC is an aggressive and genomically heterogeneous subset of breast cancer that is resistant to existing targeted therapies. To identify dysregulated metabolic pathways in TNBC, we conducted mass spectrometry-based metabolomics of TNBC and control cells. The relative steady-state levels of 155 intracellular metabolites distinguished TNBC from non-transformed breast epithelia, and revealed two metabolic subtypes within TNBC that, unexpectedly, correlate with markers of basal-like versus non-basal-like status. Distinguishing metabolites included amino acids, lipids and the cellular redox buffer glutathione. Levels of glutathione were generally lower in TNBC cell lines compared to controls, and markedly lower in the metabolic subtype containing non-basal-like TNBC. Further, these cell lines showed enhanced sensitivity to inhibition of glutathione biosynthesis, demonstrating a dependence on glutathione production for survival. These findings demonstrate the potential of targeting the glutathione biosynthetic pathway as a therapeutic strategy in TNBC, and suggest that existing clinical biomarkers may provide a means for stratifying TNBC tumors to identify likely responders to anti-glutathione therapy. Note: This abstract was not presented at the conference. Citation Format: Alexander Beatty, Lauren Fink, Alexander Strigun, Ulrike Rennefahrt, Erik Peter, Regina Reszka, Hajo Schiewe, Jeffrey R. Peterson. Metabolite profiling reveals the glutathione biosynthetic pathway as a therapeutic target in triple negative breast cancers. [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr A73.

Abstract 4333: Metabolite profiling reveals druggable metabolic distinctions between basal-like and non-basal-like triple-negative breast cancers

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer that represents about 15-20% of all breast cancers. Because TNBC tumors do not express the estrogen or progesterone receptor and lack HER2 amplification, the disease is not responsive to current targeted therapies. The development of therapeutic approaches specific for TNBC is hindered by genetic heterogeneity, and significant efforts are being made to subtype the disease. To this end, we performed metabolite profiling (metabolomics) to characterize metabolic fingerprints within TNBC in order to define metabolic subtypes, and identify molecular drivers for the development of targeted therapies. We profiled twelve well-characterized TNBC-derived cell lines as well as a non-transformed, immortalized breast cell line and two primary human mammary epithelial cell lines. Those cancer cell lines recapitulate all 7 genetic subtypes of TNBC which were proposed recently based on mRNA gene expression profiles (1). Our approaches used and data generated have implications for drug target discovery. Hierarchical clustering based on high quality intracellular metabolites clearly and reproducibly segregated the TNBC cell lines from the non-transformed lines. Alterations in energy utilization, lipid metabolism, and other pathways of importance to highly proliferative cells differed significantly from the control cell line MCF-10A. In addition, TNBC cell lines segregated into two discrete groups, suggesting the existence of two major metabolic subtypes of TNBC, which correlated with basal-like vs. non-basal-like gene expression. Metabolites like glutamate and glutamine, serine, glycine, trans-4-hydroxyproline, 5-oxoproline, several complex lipids (phosphatidylcholines and sphingomyelins), myo-inositol, polyamines spermidine and putrescine represented metabolites differing significantly between TNBC metabolic subtypes. Ongoing studies are evaluating whether these differences represent dependencies with therapeutic relevance. Metabolite profiling was also used to identify potential metabolic liabilities generated by treatment with clinical kinase inhibitors. Response of the metabolome to treatment with rapamycin, sorafenib, imatinib, and lapatinib in four genetically diverse TNBC cell lines and MCF-10A control cell lines revealed specific drug-induced metabolic alterations. Co-targeting kinases and metabolic targets may offer an approach to synthetic lethality with a reduced likelihood for the development of drug resistance. (1) (Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest. 2011;121) Citation Format: Alexander Beatty, Lauren Fink, Ulrike Rennefahrt, Alexander Strigun, Erik Peter, Hajo Schiewe, Regina Reszka, Jeffrey R. Peterson. Metabolite profiling reveals druggable metabolic distinctions between basal-like and non-basal-like triple-negative breast cancers. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4333. doi:10.1158/1538-7445.AM2014-4333

Abstract 4370: Protein kinase inhibitor screening uncovers differential kinase dependencies in triple negative breast cancer (TNBC).

Triple-negative breast cancer (TNBC) constitutes approximately 20% of all breast cancer and disproportionately affects younger women and African-American women. These tumors, negative for estrogen receptor, progesterone receptor, and Her2 amplification, are resistant to standard targeted treatments, and the need for new therapeutic targets for this tumor type is urgent. Within the TNBC patient population, there is variability in response to treatment, and it is unclear what molecular features of the disease lead to this heterogeneity. Protein kinases are often amplified and/or mutated in human cancers, and they are attractive therapeutic targets due to their enzymatic activity and widespread expression. We have screened a library of small-molecule kinase inhibitors against a panel of 12 TNBC cell lines and 3 control cell lines in duplicate in cell viability assays. We generated dose-response curves and half maximal inhibitory concentration (IC50) values for each compound-cell line pair. The results support a heterogeneous dependence of different TNBC cell lines on specific kinases. Statistical analysis identifies significantly over-represented kinase targets and pathways in subsets of TNBC cell lines following inhibitor treatment. A number of compounds show selective toxicity for TNBC cell lines and suggest targetable kinase dependencies. Kinase inhibitor sensitivity in TNBC does not appear to correlate with gene expression patterns, suggesting alternative mechanisms for TNBC heterogeneity. Sequencing data and other biomarkers databases will be mined for correlations with sensitivity to kinase inhibition in TNBC. Thus this study will identify new potential therapeutic targets and biomarkers for TNBC. Citation Format: Lauren S. Fink, Alexander Beatty, Karthik Devarajan, Suraj Peri, Jeffrey R. Peterson. Protein kinase inhibitor screening uncovers differential kinase dependencies in triple negative breast cancer (TNBC). [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4370. doi:10.1158/1538-7445.AM2013-4370

Abstract 3222: Broad spectrum metabolite profiling reveals metabolic finger and footprinting which correlate to gene expression signatures of triple-negative breast cancer (TNBC).

TNBC constitutes ∼20% of all breast cancers and disproportionately affects younger women and African-American women. This genomically heterogeneous disease is defined by the lack of expression of estrogen and progesterone receptors and the lack of amplification of HER2/neu. TNBC is resistant to standard breast cancer therapies. Due to the lack of a predominant genetic lesion associated with the disease, identification of metabolic fingerprints within TNBC is a critical first step for identification of molecular drivers and development of targeted therapies. Metabolite profiling (metabolomics) of a wide range of metabolites can be used to globally profile the metabolic state of cancer cells. Nine widely used TNBC-derived cell lines already characterized by gene expression signatures were analyzed by metabolomics. Two different approaches were combined: (i) untargeted, broad profiling including LC-MS/MS and GC-MS, and (ii) targeted UPLC-MS/MS Energy platform technology which covers polar key metabolites mainly reflecting energy status and nucleotide biosynthesis. Finally, 239 high quality metabolites were statistically evaluated in cell lysates and 128 metabolites in spent media samples collected from all cell lines. Using innovative bioinformatics and data mining tools we identified metabolic alterations in energy utilization, lipid synthesis, and other pathways of importance to highly proliferative cells that differ significantly from an untransformed control cell line (MCF-10A). Major metabolic changes combining results of metabolic fingerprinting and footprinting and their biological relevance will be discussed. Citation Format: Alexander Beatty, Lauren Fink, Alexander Strigun, Ulrike Rennefahrt, Oliver Schmitz, Hajo Schiewe, Niels Moeller, Patricia R. Noppinger, Regina Reszka, Jeffrey R. Peterson. Broad spectrum metabolite profiling reveals metabolic finger and footprinting which correlate to gene expression signatures of triple-negative breast cancer (TNBC). [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3222. doi:10.1158/1538-7445.AM2013-3222