A novel c-Met inhibitor, MK8033, synergizes with carboplatin plus paclitaxel to inhibit ovarian cancer cell growth

Elevated serum levels of hepatocyte growth factor (HGF) and high tumor expression of c-Met are both indicators of poor overall survival from ovarian cancer (OVCA). In the present study, we evaluated the role of the HGF signaling pathway in OVCA cell line chemoresistance and OVCA patient overall survival as well as the influence of HGF/c-Met signaling inhibition on the sensitivity of OVCA cells to combinational carboplatin plus paclitaxel therapy. The prevalence of the HGF receptor, c-Met, was determined by immunohistochemistry in primary OVCA samples (n=79) and OVCA cell lines (n=41). The influence of the c-Met-specific inhibitor MK8033 on OVCA cell sensitivity to combinations of carboplatin plus paclitaxel was examined in a subset of OVCA cells (n=8) by CellTiter-Blue cell viability assays. Correlation tests were used to identify genes associated with response to MK8033 and carboplatin plus paclitaxel. Identified genes were evaluated for influence on overall survival from OVCA using principal component analysis (PCA) modeling in an independent clinical OVCA dataset (n=218). Immunohistochemistry analysis indicated that 83% of OVCA cells and 92% of primary OVCA expressed the HGF receptor, c-Met. MK8033 exhibited significant anti-proliferative effects against a panel of human OVCA cell lines. Combination index values determined by the Chou-Talalay isobologram equation indicated synergistic activity in combinations of MK8033 and carboplatin plus paclitaxel. Pearson's correlation identified a 47-gene signature to be associated with MK8033-carboplatin plus paclitaxel response. PCA modeling indicated an association of this 47-gene response signature with overall survival from OVCA (P=0.013). These data indicate that HGF/c-Met pathway signaling may influence OVCA chemosensitivity and overall patient survival. Furthermore, HGF/c-Met inhibition by MK8033 represents a promising new therapeutic avenue to increase OVCA sensitivity to carboplatin plus paclitaxel.


Introduction
Ovarian cancer (OVCA) is the fifth leading cause of cancerrelated mortality among women in the United States and Western Europe, with the highest mortality rate of all gynecologic malignancies. Approximately 75% of patients with OVCA are diagnosed at an advanced stage (III/IV) with disseminated intraperitoneal metastases (1). Although the majority of patients initially experience a complete clinical response to primary surgery followed by platinum/ taxane-based chemotherapy, most patients eventually develop platinum/taxane-resistant persistent or recurrent disease. These patients have a poor prognosis. Despite cytoreductive surgery and aggressive chemotherapy, the majority of patients with OVCA succumb to the disease within 5 years (2). These dismal statistics highlight the need for research into the cellular basis of platinum response, as well as the design of targeted therapeutic strategies.
The hepatocyte growth factor (HGF) signaling pathway may be a viable target for the development of directed therapeutic regimens for the treatment of OVCA. HGF is the only known ligand of the HGF receptor (c-Met), which is expressed in approximately 70% of OVCAs (3,4). Overexpression of HGF and/or c-Met has been associated with poor clinical outcome in OVCA (5)(6)(7), whereas c-Met overexpression has further been associated with a chemo-resistant subset of ovarian clearcell adenocarcinomas (8,9). The targeted inhibition of c-Met has been shown to reduce c-Met expression, block OVCA cell proliferation, and reduce tumor burden in pre-clinical mouse models (10)(11)(12).

Materials and methods
Staining and scoring of c-Met expression in OVCA. Slides were stained using a Ventana Discovery XT automated system as per the manufacturer's protocol with proprietary reagents (Ventana Medical Systems, Tucson, AZ, USA). Briefly, slides were deparaffinized on the automated system with EZ Prep solution (Ventana). The heat-induced antigen retrieval method was used in Cell Conditioning 1 (Ventana). The mouse monoclonal antibody that reacts to c-Met (#18-7366; Invitrogen) was used at a 1:2,000 concentration in PSS antibody diluent (Ventana) and incubated for 60 min. The Ventana OmniMap anti-mouse secondary antibody was used for 16 min. The detection system used was the Ventana ChromoMap kit, and slides were counterstained with hematoxylin. Slides were then dehydrated and coverslipped as per normal laboratory protocol. The c-Met expression score was defined as the product of intensity and cellularity, where an intensity of 1 was weak; 2, moderate; 3, strong, and a cellularity of 1 ≤33%, 2 =34-65% and 3 ≥66%.
RNA extraction and microarray expression analysis. RNA extraction and microarray expression analyses were performed as previously described (13). Briefly, RNA was extracted using the RNeasy kit following the manufacturer's recommenda-tions (Qiagen, Valencia, CA, USA). Quality of the RNA was measured using an Agilent 2100 Bioanalyzer. The targets for Affymetrix DNA microarray analysis were prepared according to the manufacturer's instructions. For OVCA cell lines (n=41), targets were hybridized to customized Human Affymetrix HuRSTA gene chips (HuRSTA-2a520709) [GEO accession number GSE34615 (14)].
Statistical analyses. Expression data were subjected to background correction and normalization using the Robust Multichip Average algorithm in the Affymetrix Expression Console (http://www.affymetrix.com/products/software/ specific/expression_console_software.affx). Pearson's correlation test was performed on individual gene expression and IC 50 values. Probe sets with P<0.001 were considered to have significant correlations with IC 50 values.
Cell viability assays. For cells cultured in the presence of cisplatin, resistance was quantified using MTT proliferation assay, in accordance with manufacturer's instructions (Promega, Madison, WI, USA). Cells (5,000/well) were seeded in 96-well plates, allowed to adhere, and incubated with increasing doses of cisplatin for 48 h at 37˚C. Following drug incubation, plates were read at 570 nm using a SpectraMax 190 microplate reader (Molecular Devices, USA). For drug combination experiments, CellTiter-Blue cell viability assays were performed using 384-well plates and an automated pipetting station. Briefly, for these assays, 1.2x10 3 cells (24-µl volume) were plated in each well and allowed to adhere overnight at 37˚C and 5% CO 2 . Drug dilutions were then added using the same pipetting station, and the plate was incubated for 72 h. Following drug incubation, fluorescence was measured using a Synergy 4 microplate reader (Bio-Tek Instruments, Inc.). The fluorescence data were transferred to a spreadsheet program to calculate the percent viability relative to untreated cells. Experiments were repeated a minimum of three times.
Synergism analyses. Drug combination experiments were analyzed for synergistic, additive, or antagonistic effects using the combination index method developed by Chou and Talalay. For the application of this method, the drug concentration dilutions of the drugs were used at fixed dose ratios based on the IC 50 values of each drug obtained from preliminary experiments (e.g., 50:1, 2:5, 1:250). Briefly, the dose-effect curve for each drug alone is determined based on experimental observations using the median-effect principle and is compared to the effect achieved with a combination of the two drugs to derive a combination index value. This method involves plotting dose-effect curves, for each agent and their combination, using the following median-effect equation: fa/fu = (D/Dm)m, where D is the dose of the drug, Dm is the dose required for a 50% effect (equivalent to IC 50   (Dx)2 in the denominators are the doses (or concentrations) for D1 (drug 1) and D2 (drug 2) alone that gives x% inhibition, whereas (D)1 and (D)2 in the numerators are the doses of drugs 1 and 2 in combination that also inhibited x% (i.e., isoeffective). Combination indices <1, equal to 1, and >1 indicate synergism, additive effects and antagonism, respectively.
Building signatures. The PCA methodology was used to derive a gene expression signature with a corresponding score. First, the data were reduced into a small set of uncorrelated principal components. This set of principal components was generated based on its ability to account for variation. The first principal component (1st PCA) is used to represent the overall variability in the data. The gene expression score is equal to ∑w i x i , a weighted average expression among the differentially expressed genes, where x i represents gene i expression level, w i is the corresponding weight (loading coefficient) with ∑w 2 i = 1, and the w i values maximize the variance of ∑w i x i . Directional signs of PCA scores are recognized to be arbitrary and can vary between software and the algorithm used to calculate the PCA model (15); however, this does not affect the interpretation of the PCA model and can be easily solved by multiplying both scores and loadings by -1, a 180˚ rotation. Details of this methodology have been reported by our group previously (13).
Associations with overall survival from OVCA. PCA models were then explored for associations with overall survival from OVCA (using median PC1 score as the threshold to define high vs. low pathway score) using a dataset for which both gene expression and overall survival data were available, the publicly available Australian (Aus) Dataset (Affymetrix U133Plus GeneChips, n=218).

c-Met is significantly expressed in OVCA.
Since overexpression of HGF has been associated with poor clinical outcome in OVCA (5-7), we evaluated the expression of c-Met, the only known HGF receptor, in OVCA cells and primary OVCA tumor samples. Pathological scoring of c-Met immunostains (cellularity x intensity) in 79 primary OVCA samples and  (Table II) of samples, respectively. c-Met expression in primary OVCA did not appear to be associated with stage, response to primary platinum therapy, or CA125 levels ( Table I).

Inhibition of HGF/c-Met signaling has in vitro anti-proliferative effects on OVCA cells and synergizes with combination carboplatin plus paclitaxel.
To determine whether HGF signaling influenced OVCA cell line chemosensitivity, we evaluated the activity of MK8033, an inhibitor of HGF/c-Met signaling. MK8033 exhibited strong anti-proliferative effects against a panel of OVCA cell lines (Fig. 1). Furthermore, when combined in constant molar ratio of 1 with carboplatin plus paclitaxel (molar ratio of 20,000:1), MK8033 significantly lowered the carboplatin-paclitaxel IC 50 in the majority of cell lines tested (Fig. 1). Combination index values calculated using the Chou-Talalay isobologram equation indicated synergistic activity between MK8033 and carboplatin-paclitaxel for almost all OVCA cell lines tested, as indicated by combination index values of <0.7 (Fig. 1).  (Table III). PCA modeling of these genes indicated that the expression signature was associated with overall survival from OVCA (AUS dataset, n=218, P=0.013) (Fig. 2).
The products of several of these genes have previously been implicated in the development and/or progression of cancer. For example, the product of the HFE gene, hemochromatosis protein, is involved in the regulation of iron absorption (46). Mutations in HFE and deregulation of iron absorption have been linked to liver cirrhosis and colon cancer risk (47,48). Ubiquilin 1, encoded by the UBQLN1 gene, has been shown to be associated with lung adenocarcinoma (49)    UBQLN1  HDAC3  LOC653441  RNF207  NDOR1  CLTCL1  PHC1  ABCC8  IGHM  PPIL4  MATR3  DNASE1L1  FBXO4  REST  CLYBL  ACD  PRKAA1  LPHN3  MLLT4  NUP155  RIPK4  DKFZp667 EFCBP2  FAM91A2  TASP1  ACTN2  KIAA0528  FAM91A1  ADRBK2  OSBPL6  PPM1J  MGC5566  FAM46C  STAR  TMEFF1  MRPL30  ITIH4  FUNDC2  SGK269  MAGIX  C1orf164  RAB15  LOC389634  HFE  IL17RD  EDA and may affect OVCA response to metallodrugs (50). CLTCL1 encodes the heavy chain of clathrin, and the expression and/ or activity of clathrin has been found to be associated with bladder cancer (51), TRAIL-resistant breast cancer (52), and uptake of some chemotherapeutic agents (53). Furthermore, the oxysterol binding protein (OSBP)-related protein 6, encoded by the OSBPL6 gene, belongs to a family of proteins recently identified as receptors for several natural products, including cephalostatin-1, ritterazine B, schweinfurthin A and OSW-1 (54).
In summary, we showed that targeted inhibition of HGF/c-Met signaling using the c-Met specific inhibitor, MK8033, worked synergistically with combinations of carboplatin plus paclitaxel to induce OVCA cell growth arrest. Furthermore, we demonstrated that genes associated with response to MK8033 plus carboplatin-paclitaxel may influence overall survival from OVCA, based on PCA modeling. The results of this study suggest that the inhibition of HGF/c-Met signaling may be a beneficial addition to the OVCA standard of care regimen of carboplatin plus paclitaxel therapy.