Bonnie Liu

RAF inhibitors prime wild-type RAF to activate the MAPK pathway and enhance growth

Activating mutations in KRAS and BRAF are found in more than 30% of all human tumours and 40% of melanoma, respectively, thus targeting this pathway could have broad therapeutic effects. Small molecule ATP-competitive RAF kinase inhibitors have potent antitumour effects on mutant BRAF(V600E) tumours but, in contrast to mitogen-activated protein kinase kinase (MEK) inhibitors, are not potent against RAS mutant tumour models, despite RAF functioning as a key effector downstream of RAS and upstream of MEK. Here we show that ATP-competitive RAF inhibitors have two opposing mechanisms of action depending on the cellular context. In BRAF(V600E) tumours, RAF inhibitors effectively block the mitogen-activated protein kinase (MAPK) signalling pathway and decrease tumour growth. Notably, in KRAS mutant and RAS/RAF wild-type tumours, RAF inhibitors activate the RAF–MEK–ERK pathway in a RAS-dependent manner, thus enhancing tumour growth in some xenograft models. Inhibitor binding activates wild-type RAF isoforms by inducing dimerization, membrane localization and interaction with RAS–GTP. These events occur independently of kinase inhibition and are, instead, linked to direct conformational effects of inhibitors on the RAF kinase domain. On the basis of these findings, we demonstrate that ATP-competitive kinase inhibitors can have opposing functions as inhibitors or activators of signalling pathways, depending on the cellular context. Furthermore, this work provides new insights into the therapeutic use of ATP-competitive RAF inhibitors.

ERK Inhibition Overcomes Acquired Resistance to MEK Inhibitors

The RAS/RAF/MEK pathway is activated in more than 30% of human cancers, most commonly via mutation in the K-ras oncogene and also via mutations in BRAF. Several allosteric mitogen-activated protein/extracellular signal–regulated kinase (MEK) inhibitors, aimed at treating tumors with RAS/RAF pathway alterations, are in clinical development. However, acquired resistance to these inhibitors has been documented both in preclinical and clinical samples. To identify strategies to overcome this resistance, we have derived three independent MEK inhibitor–resistant cell lines. Resistance to allosteric MEK inhibitors in these cell lines was consistently linked to acquired mutations in the allosteric binding pocket of MEK. In one cell line, concurrent amplification of mutant K-ras was observed in conjunction with MEK allosteric pocket mutations. Clonal analysis showed that both resistance mechanisms occur in the same cell and contribute to enhanced resistance. Importantly, in all cases the MEK-resistant cell lines retained their addiction to the mitogen-activated protein kinase (MAPK) pathway, as evidenced by their sensitivity to a selective inhibitor of the ERK1/2 kinases. These data suggest that tumors with acquired MEK inhibitor resistance remain dependent on the MAPK pathway and are therefore sensitive to inhibitors that act downstream of the mutated MEK target. Importantly, we show that dual inhibition of MEK and ERK by small molecule inhibitors was synergistic and acted to both inhibit the emergence of resistance, as well as to overcome acquired resistance to MEK inhibitors. Therefore, our data provide a rationale for cotargeting multiple nodes within the MAPK signaling cascade in K-ras mutant tumors to maximize therapeutic benefit for patients. Mol Cancer Ther; 11(5); 1143–54. ©2012 AACR.

Metabolite profiling stratifies pancreatic ductal adenocarcinomas into subtypes with distinct sensitivities to metabolic inhibitors

Significance Targeting cancer metabolism requires personalized diagnostics for clinical success. Pancreatic ductal adenocarcinoma (PDAC) is characterized by metabolism addiction. To identify metabolic dependencies within PDAC, we conducted broad metabolite profiling and identified three subtypes that showed distinct metabolite profiles associated with glycolysis, lipogenesis, and redox pathways. Importantly, these profiles significantly correlated with enriched sensitivity to a variety of metabolic inhibitors including inhibitors targeting glycolysis, glutaminolysis, lipogenesis, and redox balance. In primary PDAC tumor samples, the lipid subtype was strongly associated with an epithelial phenotype, whereas the glycolytic subtype was strongly associated with a mesenchymal phenotype, suggesting functional relevance in disease progression. Our findings will provide valuable predictive utility for a number of metabolic inhibitors currently undergoing phase I testing. Although targeting cancer metabolism is a promising therapeutic strategy, clinical success will depend on an accurate diagnostic identification of tumor subtypes with specific metabolic requirements. Through broad metabolite profiling, we successfully identified three highly distinct metabolic subtypes in pancreatic ductal adenocarcinoma (PDAC). One subtype was defined by reduced proliferative capacity, whereas the other two subtypes (glycolytic and lipogenic) showed distinct metabolite levels associated with glycolysis, lipogenesis, and redox pathways, confirmed at the transcriptional level. The glycolytic and lipogenic subtypes showed striking differences in glucose and glutamine utilization, as well as mitochondrial function, and corresponded to differences in cell sensitivity to inhibitors of glycolysis, glutamine metabolism, lipid synthesis, and redox balance. In PDAC clinical samples, the lipogenic subtype associated with the epithelial (classical) subtype, whereas the glycolytic subtype strongly associated with the mesenchymal (QM-PDA) subtype, suggesting functional relevance in disease progression. Pharmacogenomic screening of an additional ∼200 non-PDAC cell lines validated the association between mesenchymal status and metabolic drug response in other tumor indications. Our findings highlight the utility of broad metabolite profiling to predict sensitivity of tumors to a variety of metabolic inhibitors.

Pyrazolopyridine Inhibitors of B-Raf(V600E). Part 1: The Development of Selective, Orally Bioavailable, and Efficacious Inhibitors.

The V600E mutation of B-Raf kinase results in constitutive activation of the MAPK signaling pathway and is present in approximately 7% of all cancers. Using structure-based design, a novel series of pyrazolopyridine inhibitors of B-Raf(V600E) was developed. Optimization led to the identification of 3-methoxy pyrazolopyridines 17 and 19, potent, selective, and orally bioavailable agents that inhibited tumor growth in a mouse xenograft model driven by B-Raf(V600E) with no effect on body weight. On the basis of their in vivo efficacy and preliminary safety profiles, 17 and 19 were selected for further preclinical evaluation.

Phosphoproteome analysis of the MAPK pathway reveals previously undetected feedback mechanisms

The RAS‐RAF‐MEK‐ERK (MAPK) pathway is prevalently perturbed in cancer. Recent large‐scale sequencing initiatives profiled thousands of tumors providing insight into alterations at the DNA and RNA levels. These efforts confirmed that key nodes of the MAPK pathway, in particular KRAS and BRAF, are among the most frequently altered proteins in cancer. The establishment of targeted therapies, however, has proven difficult. To decipher the underlying challenges, it is essential to decrypt the phosphorylation network spanned by the MAPK core axis. Using mass spectrometry we identified 2241 phosphorylation sites on 1020 proteins, and measured their responses to inhibition of MEK or ERK. Multiple phosphorylation patterns revealed previously undetected feedback, as upstream signaling nodes, including receptor kinases, showed changes at the phosphorylation level. We provide a dataset rich in potential therapeutic targets downstream of the MAPK cascade. By integrating TCGA (The Cancer Genome Atlas) data, we highlight some downstream phosphoproteins that are frequently altered in cancer. All MS data have been deposited in the ProteomeXchange with identifier PXD003908 (http://proteomecentral.proteomexchange.org/dataset/PXD003908).

A transcriptional MAPK Pathway Activity Score (MPAS) is a clinically relevant biomarker in multiple cancer types

KRAS- and BRAF-mutant tumors are often dependent on MAPK signaling for proliferation and survival and thus sensitive to MAPK pathway inhibitors. However, clinical studies have shown that MEK inhibitors are not uniformly effective in these cancers indicating that mutational status of these oncogenes does not accurately capture MAPK pathway activity. A number of transcripts are regulated by this pathway and are recurrently identified in genome-based MAPK transcriptional signatures. To test whether the transcriptional output of only 10 of these targets could quantify MAPK pathway activity with potential predictive or prognostic clinical utility, we created a MAPK Pathway Activity Score (MPAS) derived from aggregated gene expression. In vitro, MPAS predicted sensitivity to MAPK inhibitors in multiple cell lines, comparable to or better than larger genome-based statistical models. Bridging in vitro studies and clinical samples, median MPAS from a given tumor type correlated with cobimetinib (MEK inhibitor) sensitivity of cancer cell lines originating from the same tissue type. Retrospective analyses of clinical datasets showed that MPAS was associated with the sensitivity of melanomas to vemurafenib (HR: 0.596) and negatively prognostic of overall or progression-free survival in both adjuvant and metastatic CRC (HR: 1.5 and 1.4), adrenal cancer (HR: 1.7), and HER2+ breast cancer (HR: 1.6). MPAS thus demonstrates potential clinical utility that warrants further exploration.Biomarker: Gene signature predicts drug responses and patient outcomesA clinical score based on the activity of genes that regulate cell signaling can predict drug sensitivity and patient outcomes across a range of cancer types. Marie-Claire Wagle, Daniel Kirouac and their colleagues at Genentech in South San Francisco, California, USA developed an index that aggregates expression levels of 10 genes involved in modulating the mitogen-activated protein kinase (MAPK) pathway. This “MAPK Pathway Activity Score”, or MPAS, performed as well or better than other more complicated, genome-based tools at predicting whether drugs that inhibit MAPK-related enzymes were active against tumor cell lines. Retrospective analyses of clinical datasets also showed that MPAS correlated with survival outcomes in patients with melanoma, colon cancer, and breast cancer. The authors suggest that MPAS should be evaluated more broadly and perhaps implemented as a clinically informative biomarker.

Abstract 417: A novel predictive biomarker model for MEK sensitivity

KRAS mutations occur in approximately 25% of NSCLC (1). Tumors with these mutations are predicted to be sensitive to MEK inhibition due to activation of MAPK signaling. However, MEK inhibitors in multiple clinical trials, either as a monotherapy or in combination with chemotherapies, have not shown superior efficacy in the KRAS mutant subgroup when compared to the KRAS wild-type subgroup, indicating a limitation of utilizing KRAS mutation status as a predictive biomarker of efficacy to MEK inhibition (2, 3). Furthermore, stratification based on KRAS mutation status may inadvertently miss wild-type KRAS tumors that could be addicted to MAPK signaling regardless of KRAS mutation status, thus denying patients potential benefit from MEK inhibitors. Here we describe a novel predictive model that more accurately forecasts the sensitivity of the KRAS wild-type NSCLC subpopulation to MEK inhibitors such as cobimetinib and trametinib. Cell viability data from cobimetinib or trametinib-treated cells, with concomitant gene expression data (RNAseq), from 46 colon, 106 lung, and 37 pancreatic cell lines were used to create an elastic net regression model trained on gene expression features (alpha = 0.5 and optimal lambda chosen by 5-fold cross validation) (4). From the model, we established two distinct predictive gene lists: (1) a longer low cross-validation list, and (2) a shorter low error list. Initial analysis of the model demonstrated that predicted mean viabilities of the cell lines used to create the model correlated well with their actual mean viabilities (R: 0.65-0.7 for trametinib and cobimetinib respectively). Predicted mean viabilities of 40 previously unscreened NSCLC cell lines were then generated by the model based on their expression features (RNAseq). The 40 cell lines were categorized either as sensitive or resistant by the median of predicted mean viabilities derived from the model. Subsequently, the actual experimental GI50 values of cobimetinib were obtained for each of these cell lines. We found that KRAS mutational status predicted that only 8 of the 40 cell lines screened would be sensitive to MEK inhibition. In contrast, our model predicted that 15 of the 40 cell lines screened would be sensitive. Experimentally, we demonstrated that 24 of the cell lines were sensitive to MEK inhibition with a measured GI50 References (1) Blumenschein GR. et al., (2015) Annal Oncol. 26(5):894-901. (2) Gandara DL et al., (2013) J Clin Oncol 31, (suppl; abstr 8028). (3) Laethem JLV et al, (2014) J Clin Oncol 32:5s, (suppl; abstr 4025). (4) Barretina J. et al. (2012) Nature 483, 603-607. Citation Format: Marie Wagle, Christiaan Klijn, Bonnie Liu, Shilpi Mahajan, Peter Haverty, John Moffat, Mark Merchant, Bob Yauch, Garret Hampton, Lukas Amler, Mark Lackner, Shih-Min A. Huang. A novel predictive biomarker model for MEK sensitivity. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 417.

Abstract 4257: Gene expression and genomic drift comparative analysis between patient-derived conditionally reprogrammed cells and original tumors

First two authors contributed equally Last two authors contributed equally Recent studies have shown that ex vivo propagation of normal tissues or patient-derived tumor cells in presence of irradiated fibroblast feeder cells and ROCK inhibitor can rapidly establish conditionally reprogramed cells (CRCs). In case of normal tissues, the induction of CRCs was reversible when the ROCK inhibitor and the feeder cells were removed, resulting in CRCs differentiating to its tissue origin (Liu et al.2012). Previous publications suggested that the establishment of such cell models provides new strategies to understand acquired resistance during treatment (Crystal et al 2015) and to predict treatment response (Liu et al. 2014). However, gene expression modulations and genomic drifting during the establishment of CRC propagation have not been thoroughly studied. The primary goal of this study is to molecularly characterize alterations between the original tumor tissues and the derived models growing with or without ROCK inhibitor. Understanding in-depth molecular fluctuations in this patient-derived ex vivo system will facilitate its appropriate use for tumor biology experimentation. Herein, tumors from prostate cancer and breast cancer patients were surgical removed and cryopreserved at the clinical site then processed and cultured as previously described (Liu et al. 2012). Gene expression profiling and next-generation sequencing were carried out on the original tumor tissues and cellular models passaged during the CRC propagation in the presence or absence of ROCK inhibitor. Gene expression analysis of the prostate cancer cells and the breast cancer cells were carried out using a 93-gene prostate cancer-focused Fluidigm panel and a 800 gene NanoString breast cancer-focused panel, respectively. Cancer hotspot mutations were analyzed using the Ion Torrent Cancer Hotspot v2 NGS assay. Through aforementioned genomic and transcriptomic interrogations, we demonstrated the extent of indication-relevant gene expression modulation during establishment and propagation of these cells. We also characterize cancer hotspot mutations in the primary tumor cells and the stability of those mutations during ex vivo propagation. These results should begin to inform the appropriate use of the CRC model for tumor biology experimentation. Citation Format: Jessica Li, Bonnie Liu, Rin Nakamura, Heidi Savage, Shoji Ikeda, Timothy Wilson, Teiko Sumiyoshi, Garret Hampton, Lukas Amler, Mark Lackner, Shih-Min A. Huang, Walter C. Darbonne. Gene expression and genomic drift comparative analysis between patient-derived conditionally reprogrammed cells and original tumors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4257.

Abstract 1423: Resistance to LDHA inhibitors requires signaling through the AMPK/mTOR/S6K pathway leading to increased oxidative phosphorylation

Lactate Dehydrogenase A (LDHA) is an attractive candidate for targeting glycolysis-addicted tumors. However, due to the inherent plasticity of metabolic networks in cells, there is concern that the benefit of targeting LDHA may be transient and that resistance will quickly emerge. To identify predictive features of LHDA inhibitor sensitivity and to understand how cells adapt to long-term LHDA inhibition, we screened a large panel (∼500) of tumor cell lines with GNE-140, a newly developed LHDA inhibitor. We found that approximately 15% of lines were inherently sensitive to the LDHA inhibitor, with sensitivity correlating with increased expression of glycolysis genes and inversely correlating with expression of oxidative phosphorylation genes. Despite the metabolic plasticity of cells, the timing of acquired resistance to LDHA inhibitors was comparable with other targeted agents. Under long-term LDHAi treatment, glycolytic cells acquired resistance by increased oxidative phosporylation (OX-PHOS) in a mechanism dependent on the AMPK stress response pathway; targeting either AMPK, downstream kinases, or OX-PHOS using tool compounds synergized with and prevented acquired resistance to GNE-140. Taken together, our data suggests that targeting anaerobic glycolysis may benefit a subset of patients across indications and that combinations with agents that block AMPK signaling or the mitochondria will be effective at delaying tumor relapse. Citation Format: Aaron Boudreau, David Peterson, John Moffat, Bonnie Liu, Mandy Kwong, Min Gao, Hans Purkey, Thomas O9Brien, Georgia Hatzivassiliou, Anneleen Daemen, Marie Evangelista. Resistance to LDHA inhibitors requires signaling through the AMPK/mTOR/S6K pathway leading to increased oxidative phosphorylation. [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 1423. doi:10.1158/1538-7445.AM2014-1423

Abstract 4618: Elucidating the role of distinct glutaminase isoforms in cancer.

Glutaminase is a key enzyme for the conversion of glutamine to glutamate with subsequent use as a fuel in the TCA cycle, glutathione production and protein synthesis. A subset of tumor cells shows preferential dependency on glutamine and glutaminase for cell proliferation and survival, consistent with “metabolic addiction” to this pathway. Between two glutaminase loci in the genome, the gene for kidney-type glutaminase (Gls1) has 2 alternatively spliced products (KGA and GAC), with distinct regulation and expression from liver-type glutaminase (Gls2). Furthermore, based on distinct C-termini and enzymatic properties, it has been proposed that the Gls1 alternatively spliced isoforms (KGA and GAC) may themselves have distinct functions. Our data further elucidates the role of glutaminase in cancer by addressing the following key questions: a) what is the major role of glutaminase in cells most sensitive to its inhibition? b) is GAC interchangeable with KGA in its expression pattern and role in tumor cells? c) how do tumors adapt to glutaminase inhibition? By generating and using a panel of GAC and KGA isoform-selective reagents we show that the two isoforms have distinct patterns of expression and distinct roles in cell proliferation, migration and tumor growth in vivo. In addition, based on metabolomics, functional and complementation assays, we propose a mechanistic basis for tumor cell dependency on glutaminase and the tumor adaptive response to glutaminase inhibition. Our data reveal the basis for the addiction of tumor subsets to glutaminase and elucidate the role of distinct isoforms of kidney-type glutaminase isoforms in cancer. Citation Format: Bonnie Liu, Kyung Song, Mandy Kwong, Min Gao, Rebecca Hong, Michelle Nannini, Deepak Sampath, Marcia Belvin, David Peterson, Marie Evangelista, Anneleen Daemen, Ron Firestein, Georgia Hatzivassiliou. Elucidating the role of distinct glutaminase isoforms in cancer. [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 4618. doi:10.1158/1538-7445.AM2013-4618