Purpose: Epithelial ovarian cancer (EOC) is usually detected at an advanced stage and is frequently lethal. Although many patients respond to initial surgery and standard chemotherapy consisting of a platinum-based agent and a taxane, most experience recurrence and eventually treatment-resistant disease. Although there have been numerous efforts to apply protein-targeted agents in EOC, these studies have so far documented little efficacy. Our goal was to identify broadly susceptible signaling proteins or pathways in EOC.

Experimental Design: As a new approach, we conducted data-mining meta-analyses integrating results from multiple siRNA screens to identify gene targets that showed significant inhibition of cell growth. On the basis of this meta-analysis, we established that many genes with such activity were clients of the protein chaperone HSP90. We therefore assessed ganetespib, a clinically promising second-generation small-molecule HSP90 inhibitor, for activity against EOC, both as a single agent and in combination with cytotoxic and targeted therapeutic agents.

Results: Ganetespib significantly reduced cell growth, induced cell-cycle arrest and apoptosis in vitro, inhibited growth of orthotopic xenografts and spontaneous ovarian tumors in transgenic mice in vivo, and inhibited expression and activation of numerous proteins linked to EOC progression. Importantly, paclitaxel significantly potentiated ganetespib activity in cultured cells and tumors. Moreover, combined treatment of cells with ganetespib and siRNAs or small molecules inhibiting genes identified in the meta-analysis in several cases resulted in enhanced activity.

Conclusion: These results strongly support investigation of ganetespib, a single-targeted agent with effects on numerous proteins and pathways, in augmenting standard EOC therapies. Clin Cancer Res; 19(18); 5053–67. ©2013 AACR.

This article is featured in Highlights of This Issue, p. 4903

Translational Relevance

Epithelial ovarian cancer (EOC) is typically diagnosed at an advanced stage. Although many protein-targeted therapeutic agents have been evaluated in clinical trials, few have shown efficacy. A likely reason for this is that advanced-stage ovarian carcinomas exhibit a high degree of tumor heterogeneity and generally lack pronounced, drug-targetable oncogenic driver mutations. Our findings show that targeted inhibition of HSP90 results in broad inhibition of several oncogenic signaling proteins and/or pathways in EOC. In addition, our results suggest that targeted inhibition of HSP90 with ganetespib combined with chemotherapeutic and/or protein-targeted agents may be an effective therapeutic strategy for treatment of patients with ovarian cancer. Because it mediates the activity of multiple targets and pathways that are relevant to EOC, therapeutic targeting of HSP90 is predicted to be a more productive clinical strategy for treatment of highly heterogeneous advanced-stage ovarian cancers.

Epithelial ovarian cancer (EOC) is the most common form of ovarian cancer and occurs with few or no distinct symptoms. Because of this, most women are diagnosed when disease has spread beyond the ovaries to other organs in the abdominal cavity. After initial diagnosis, patients undergo aggressive surgery to remove all visible tumors and are treated with standard combination chemotherapy consisting of a taxane and a platinum-based agent. Most patients respond well to surgery and chemotherapy, but the majority experience disease recurrence. Although additional chemotherapy may be effective for a time, recurrent disease ultimately becomes resistant to standard treatment. For these patients, there are few effective treatment options, underscoring the persistent unmet need to identify therapeutics that target pathways involved in tumor progression. Over the past two decades, significant effort has been devoted to identifying protein-targeted agents and evaluating these alone and in combination with standard cytotoxic chemotherapies.

Overexpression of individual cancer-associated proteins in patient tumors has been taken to suggest that targeting these proteins may have clinical efficacy. However, this surrogate biomarker strategy has not always been successful in clinical trials. For example, although EGF receptor (EGFR) is commonly overexpressed in EOC, numerous clinical trials with different classes of targeted inhibitors of this pathway have failed to show therapeutic efficacy in patients (1). Similarly, trials of single agents targeting HER2, RAF, c-KIT/PDGFR, mTOR, PKC, and SRC have failed to show clinical efficacy (2–9). Among the reasons for the overall lack of success, EOCs differ between individual patients in their development, histologic subtype, genetic makeup, protein expression, and pathway activation. Genomic analyses have revealed that high-grade serous carcinomas, the most common type of EOC, are commonly characterized by overexpression and/or amplification of numerous (>30) growth-stimulatory genes (10). High levels of genetic instability in these cancers may result in heterogeneity within tumors that contributes to escape from individual targeted therapeutic agents. These factors predict that monotherapy trials of agents targeting a single protein or pathway will remain unsuccessful; however, the ability to predict effective combinations of agents that will reliably inhibit EOC growth remains elusive.

Prior work from our group has shown the potential for using bioinformatics to develop target-centered signaling networks that can be used as a basis for siRNA screens designed to identify proteins regulating sensitivity to targeted therapies (11). Observations from this dataset about interactions of sensitizing proteins with catalytic partners that are the targets of existing drugs were useful in predicting therapeutic combinations that were effective in preclinical in vivo studies (11). Given the known challenges of treating EOC and the urgent need for new treatment modalities, in the present study, we have developed this initially productive strategy into a more comprehensive approach. We conducted meta-analyses of five independent siRNA screens involving different combinations of cell lines and drugs to identify the most consistently sensitizing targets. We then modeled interactions among the sensitizing dataset to identify connections to therapeutic targets.

In this extended analysis, multiple proteins directly interacting with HSP90 emerged as potent sensitizers of EOC cells to drug-induced cell death. HSP90 is an ATP-dependent molecular chaperone protein that affects the maturation, stability, and activation of a number of diverse client proteins (12). Although abundantly expressed in normal cells, its overexpression in malignant cells promotes persistent activation of many cellular kinases and transcription factors, and buffers cells from malignancy-induced cellular stresses (12). Because it mediates multiple target and pathway effects, HSP90 is an attractive therapeutic target. As an ATP-dependent chaperone, druggability of HSP90 was established in the mid-late 1990s with the natural products geldanamycin and radicicol. These agents exhibited selective toxicity for cancer cells (13), and although too toxic for clinical use, provided the chemical framework for development of additional agents. Among these, ganetespib is a particularly promising agent that does not suffer from the toxicity issues associated with earlier-generation HSP90 inhibitors and exhibits increased potency compared with first- and other second-generation agents (14–17). In our study, we show that ganetespib is a potentially valuable agent for augmenting the activity of cytotoxic therapies commonly used in EOC, both in vitro and in vivo, and that depletion of a group of proteins physically interacting with HSP90 sensitizes EOC cells to ganetespib, suggesting directions for future combination therapies.

Network analysis

Data for drug sensitization profiles for 638 genes encompassed in the siRNA library, corresponding to a receptor tyrosine kinase/cancer signaling network (detailed in ref. 11), were pooled from five independent screens of cancer cell lines. These data included sensitization of HCT116 to irinotecan or erlotinib (see Supplementary Methods), A431 cells to irinotecan or erlotinib (11), and H1155 cells to paclitaxel (18). Validated sensitizing siRNAs were sorted by rank for each screen, and assigned a value from 638 (most sensitizing) to 1 (least sensitizing). Comparison of the rank across screens nominated 171 siRNAs that were among the 20% strongest sensitizers in two or more screens. The proteins depleted by these siRNAs were imported into Cytoscape (19) and a protein–protein interaction network constructed. The network was expanded using the MiMi plugin (20) to include nearest neighbors shared by at least two proteins in the initial gene set. Analysis in Ingenuity (http://www.ingenuity.com/index.html) and DrugBank (21) was used to identify drugs targeting genes in the expanded protein set. The cumulative group of 130 drug targets was queried against the original group of 171 sensitivity-regulating proteins, and topological parameters of the network were calculated in Cytoscape. The degrees (the total interactions of each protein in this subnetwork) of each node were used to calculate the number of connections of each of the 130 drug targets to the initial set of 171 most sensitizing genes. After HSP90 was identified as of particular interest, combined application of Ingenuity and STRING (Search Tool for the Retrieval of Interacting Genes/Proteins, ref. 22), together with manual inspection of data included in ref. (23), and the database of the HSP90 machine interactome [ref. (24) and http://www.picard.ch/Hsp90Int/index.php] to capture all known interactions. The prevalence of proteins from this extended dataset among the subsets of genes with varying sensitization levels was used to calculate the enrichment of HSP90 targets in each subset compared with the whole library, using hypergeometric distribution.

Antibodies and drugs used

Antibodies used and commercial sources are as follows: JAK2, pJAK2Y1007/1008, STAT3, pSTAT3Y705, STAT5, pSTAT5Y694, pSRCY416, S6, pS6Ser235/236, pCDK1Y15, AKT, pAKTSer473, c-MYC, BCL-XL, EGFR, MCL-1, NF-κB p105/p50, PKCα, PKCϵ, PKCδ, PKCζ, MEK1, PI3K p100β, FYN, CK2α, RIP1, PDK1, N-WASP, and caspase-3 (Cell Signaling Technology); cyclin D1, CDK1, HSC70, and β-actin (Santa Cruz Biotechnology); SRC and p53 (EMD Millipore); β-actin (Sigma-Aldrich); HIP1 and Ki-67 (Abcam); EGFR (BD Biosciences); HSP70 (Enzo Life Sciences), and PARP (RayBiotech). Drugs used and their commercial sources are as follows: ganetespib (Synta Pharmaceuticals Corp.); paclitaxel and cisplatin [Fox Chase Cancer Center (FCCC) Pharmacy, Philadelphia, PA]; dasatinib, alisertib, and ruxolitinib (Selleck Chemicals); erlotinib (LC laboratories); and GSK2334470 (Sigma-Aldrich).

Cell culture

Human OVCAR-5, OVCAR-8, and A1847 EOC cell lines were grown in RPMI (Life Technologies), with 10% FBS (Atlanta Biologicals), 2 mmol/L l-glutamine, penicillin/streptomycin [100 U/mL and 100 μg/mL, respectively; Life Technologies (Invitrogen)], and 0.25 units/mL insulin (Novo Nordisk). SKOV-3 cells were grown in McCoy's 5A (Life Technologies) supplemented with 10% FBS, 2 mmol/L l-glutamine, penicillin/streptomycin, and 0.25 U/mL insulin. OVCAR-5 and A1847 cells were transduced with a retroviral firefly luciferase construct (pWZL-Luc; a gift from Dr. Maureen Murphy, The Wistar Institute, Philadelphia, PA) using standard methods (25) and selected in the presence of 75 μg/mL hygromycin B (Life Technologies).

Cell viability, apoptosis, and cell-cycle assays

Cell viability was determined in ganetespib-treated cells (0.1–1,000 nmol/L) using the CellTiter-Blue Cell Viability Assay (Promega) according to the manufacturer's instructions. Apoptosis was evaluated by Annexin V staining (Guava Nexin Reagent; Millipore) in cells treated with 0–100 nmol/L ganetespib for 24, 48 or 72 hours. Briefly, 1 × 105 cells were harvested and centrifuged at 300 × g for 5 minutes at room temperature. Cells were washed in PBS and suspended in 100 μL of serum-containing medium and 100 μL of Guava Nexin Reagent was added to each sample. The samples were stained for 20 minutes at room temperature in the dark and analyzed on the Guava EasyCyte PCA-96 system and the accompanying Cytosoft 3.6.1 software (EMD Millipore). Annexin V–PE (+)/(−) cells were identified in the early stages of apoptosis and Annexin V–PE (+)/7-AAD (+) cells were identified in the late stages. For cell-cycle analysis, cells seeded at 2.5 × 105 cells per well in a 6-well plate were exposed to 0, 5, 25, and 50 nmol/L ganetespib or 100 μmol/L etoposide as a positive control. After 24 and 48 hours, cells were harvested and stained with propidium iodide (Sigma-Aldrich), analyzed on the Guava EasyCyte System (EMD Millipore) according to the manufacturer's instructions.

Drug synergy testing

Ganetespib, paclitaxel, cisplatin, dasatinib, erlotinib, GSK2334470, alisertib, and ruxolitinib were tested individually or in combination. A1847 and OVCAR5 cells were plated at 3,000 cells per well in 96-well plates. After 24 hours of incubation, cells were treated with serial dilutions of individual drugs or combinations of two drugs at a constant molar ratio. After 72 hours of incubation, cell viability was measured with CellTiter-Blue (Promega) using an EnVision Plate Reader (PerkinElmer). Combination index (CI) values were established by the Chou–Talalay method (26, 27) calculated using the CompuSyn software package (ComboSyn).

Immunoblot assays and analysis

Cells and tumor tissue were lysed in Mammalian Protein Extraction Reagent (MPER) and Tissue Protein Extraction Reagent (TPER), respectively (Thermo Scientific). Lysis buffer was supplemented with Halt Phosphatase Inhibitor Cocktail (Thermo Scientific) and Complete Mini Protease Inhibitor Cocktail (Roche Diagnostics), and protein concentrations were determined using the BCA assay (Thermo Scientific). Proteins were resolved on 4% to 12% gradient SDS-PAGE gels (Life Technologies) and transferred to polyvinylidene difluoride (PVDF) membrane (EMD Millipore). Membranes were blocked in nonfat dry milk, incubated overnight at 4°C in primary antibody, followed by horseradish peroxidase–conjugated secondary antibody (GE Healthcare) and signal was detected with SuperSignal West Pico Chemiluminescent Substrate (Thermo Scientific). Immunoblots were quantified using ImageJ as described previously (28). Briefly, a rectangle region of interest (ROI) was drawn to outline each lane. The Analyze Gels function was used to create a plot of the average pixel intensity over the length of the ROI. A straight line was then used to close each peak and the area under the curve was measured and the density relative to β-actin was calculated for each band.

Mouse models and in vivo imaging

All procedures involving mice were approved by the FCCC Institutional Animal Care and Use Committee (IACUC). Female C.B-17 severe combined immunodeficient (SCID) mice (FCCC Laboratory Animal Facility) were used for intrabursal injections as described previously (29, 30). Mice were given unilateral intrabursal (left side) injections of OVCAR-5-Luc or A1487-Luc cells (8 × 105) suspended in 5 μg/μL final concentration of BD Matrigel Matrix High Concentration (BD Biosciences). Baseline bioluminescent imaging (BLI) scans were acquired using the IVIS Spectrum (PerkinElmer, Caliper Life Sciences) as described previously (29, 30) to confirm the presence of tumors. Transgenic TgMISIIR-TAg mice and in vivo MRI and volumetrics analysis have been described previously (31–33). Ganetespib, 125 mg/kg formulated in 10/18 DRD (10% DMSO, 18% Cremophor RH 40, 3.6% dextrose, and 68.4% water), or 10/18 DRD (vehicle), was administered once weekly by tail vein injection. Paclitaxel was diluted in PBS and 5 mg/kg was administered once weekly by intraperitoneal injection. Mice with OVCAR-5-Luc and A1487-Luc xenografts were treated for 3 and 6 weeks, respectively, and tumor growth was monitored by weekly BLI. Briefly, ROI of identical size encompassing the luminescent signal were assigned, and the total flux was calculated for each mouse using Living Image software (PerkinElmer; Caliper Life Sciences). Statistical analyses were conducted by subjecting pairs of datasets to the Wilcoxon two-sample test; P < 0.05 was considered significant.

ELISA assay

Levels of HSP70 and pSTAT3Y705 (activated STAT3) present in tumor protein lysates isolated 6 or 24 hours after vehicle- or ganetespib-treatment were assayed using an enhanced chemiluminescent ELISA assay (MesoScale Discovery) according to the manufacturer's instructions.

Reverse phase protein array

Triplicate samples of OVCAR-5 cells were treated with vehicle, 30 nmol/L ganetespib, 1 nmol/L paclitaxel, or 30 nmol/L ganetespib + 1 nmol/L paclitaxel for 24 hours. Following standard protocols of the RPPA (reverse phase protein array) Core Facility at MD Anderson Cancer Center (Houston, TX), cells were lysed on ice, and lysates cleared by centrifugation and denatured in SDS sample buffer, then submitted for analysis as described previously (34, 35). Data were visualized using the MultiExperiment Viewer (MeV) program (http://www.tm4.org/mev/) and analyzed by one-way ANOVA and Tukey multiple comparison test using GraphPad Prism version 5.04.

Tissue preparation and immunohistochemistry

Mice were euthanized, necropsied, and examined for the presence and location of primary tumors and tumor nodules. Reproductive tracts were removed and primary tumors were weighed and caliper measurements of length (l) and width (w) were made to determine tumor volume (l × w2 × 0.5). Tumor nodules present in the abdomen were counted. Individual portions of tumors were snap-frozen in liquid nitrogen for preparation of protein lysates, and fixed in 10% (v/v) neutral buffered formalin and paraffin embedded for staining with hematoxylin and eosin. Custom tumor tissue microarrays (TMA) were constructed by arraying duplicate cores from primary OVCAR-5 and A1847 tumors isolated from mice at 6 and 24 hours after treatment with vehicle or ganetespib. Immunohistochemical staining was conducted as described previously (30, 31) with the following antibodies at the indicated dilutions: Ki-67 (1:100), caspase-3 (1:300), PARP (1:100), STAT3 (1:400), and pSTAT3 (1:25). Stained TMAs were scanned and analyzed using the Vectra imaging system (PerkinElmer; Caliper Life Sciences,). Images of immunohistochemical staining were acquired on a CCD camera and Nikon Eclipse E600 microscope with NIS-Elements D3.0 software (Nikon) at identical exposure times.

Sensitization testing for siRNAs

For the set of siRNAs defined in Results, sensitization to ganetespib was conducted essentially as described in detail for library screening (Supplementary Methods). Two independent siRNA duplexes independently prevalidated for each target were used in A1847 and OVCAR5 cells, using optimized reverse transfection conditions to introduce siRNAs into 3,000 cells arrayed in 96-well microtiter plates, in duplicate. Plates were treated with ganetespib at a previously established IC30 concentration, or DMSO, after 24 hours, and viability assessed with CellTiter-Blue 96 hours after transfection, using an EnVision Plate Reader.

Network analysis identifies HSP90 as a candidate for evaluation in EOC

To identify genes that consistently sensitized tumor cells to drug treatment, we conducted meta-analysis of results from five independent siRNA drug sensitization screens that queried 638 genes in a signaling network enriched for many targets relevant to EOC pathology, including the previously assessed HER2, RAF, SRC, and mTOR; their physically interacting partners and downstream effectors; the TGF-β effector cascades, which have been associated with drug resistance and aggressive tumor phenotypes; and others [(11, 18); details of cell line selection and analysis are described in Supplementary Fig. S1 and Supplementary Table S1]. To identify siRNAs with the most consistent sensitizing activity, we sought those active in more than one cell line, and/or active against at least two of three drugs with different modes of activity: the topoisomerase inhibitor irinotecan, the microtubule-targeting agent paclitaxel, and the EGFR inhibitor erlotinib. By these criteria, 171 genes were identified as among the 20% scoring highest for mediating resistance to drug treatment, including 15 encoding proteins that are targets of drugs in preclinical development or clinical use (Fig. 1A).

Figure 1.

Network analysis identifies HSP90 as a candidate for evaluation in EOC treatment. A, 638 genes assessed in five independent sensitization screens, subdivided in three tiers reflecting number of screens in which gene-targeting siRNAs fell among the 20% most potent drug sensitizers (in 0, 1, or 2–5 screens), and further sorted by rank (averaged for all five screens) within each subset. Genes encoding drug targets are shown in brown. B, right, a network encompassing 171 proteins in the most sensitizing subset of the library (diamonds), augmented with 130 additional drug target proteins connected to 171 protein set by no less than two interactions (circles). Brown fill indicates drug target (130 drug targets total); blue, not drug target; purple outline, HSP90 interactors, including clients. Only the largest connected component, comprising 260 proteins, is shown. Left, bar graph indicates degree distribution (reflecting number of connections to most sensitizing subset of the library) for each drug target in the network. Drugs targeting proteins with the highest degree are indicated. Clients of HSP90 are indicated in brown. JAK, Janus-activated kinase.

Figure 1.

Network analysis identifies HSP90 as a candidate for evaluation in EOC treatment. A, 638 genes assessed in five independent sensitization screens, subdivided in three tiers reflecting number of screens in which gene-targeting siRNAs fell among the 20% most potent drug sensitizers (in 0, 1, or 2–5 screens), and further sorted by rank (averaged for all five screens) within each subset. Genes encoding drug targets are shown in brown. B, right, a network encompassing 171 proteins in the most sensitizing subset of the library (diamonds), augmented with 130 additional drug target proteins connected to 171 protein set by no less than two interactions (circles). Brown fill indicates drug target (130 drug targets total); blue, not drug target; purple outline, HSP90 interactors, including clients. Only the largest connected component, comprising 260 proteins, is shown. Left, bar graph indicates degree distribution (reflecting number of connections to most sensitizing subset of the library) for each drug target in the network. Drugs targeting proteins with the highest degree are indicated. Clients of HSP90 are indicated in brown. JAK, Janus-activated kinase.

Close modal

We next used this dataset to identify commonalities in signaling among the set of most sensitizing genes. Numerous studies of synthetic lethality have established that close physical interactions between proteins predict common functionalities that can be exploited for cell killing (36, 37). From the starting gene set, we constructed an interaction network in Cytoscape among their encoded proteins, which we augmented to include additional “nearest neighbor” interactors shared by at least two proteins in the initial group of 171 proteins. In the resulting expanded network of 1,391 proteins, 130 are drug targets (Supplementary Table S2). We then conducted a topological analysis of the network, and extracted the number of direct connections between each of the 130 drug targets and the 171 proteins regulating sensitization. From this analysis, we identified a subset of drug targets as particularly densely connected to proteins in the sensitizing network (Fig. 1B). Within the subset of targets of the top 10 drugs, we observed that the two subunits of HSP90 (HSP90AA1 and HSP90AB1) were among the most densely connected to proteins in the sensitizing set (Fig. 1B; Supplementary Fig. S2; Supplementary Table S2). We also identified a statistically significant enrichment of HSP90-interacting proteins among the 20% most sensitizing siRNAs in two or more screens (P = 0.03), and under-representation among the group of siRNAs that were never among the most sensitizing 20% (P = 0.04). Moreover, many of the drug targets densely connected to the sensitizing set were themselves clients or interactors of HSP90. These included STAT3, EGFR, ERBB2 (HER2), ESR1 (estrogen receptor-α), and multiple SRC family kinases, each of which is already implicated in EOC pathogenesis (Fig. 1B; refs. 38–48).

Ganetespib inhibits EOC cell viability and HSP90 clients in vitro and in vivo

HSP90 has been reported as the tumor-associated antigen targeted by antibodies in the ascites of patients with late-stage EOC (49), whereas separate studies have shown that elevated HSP90 levels are common in peritoneal and pleural effusions of patients with advanced-stage EOC (50). On the basis of these reports, and the strong connections of EOC to many HSP90 client proteins, we directly assessed ganetespib, a small-molecule inhibitor of HSP90 (17), in commonly studied EOC cell lines, including OVCAR-5, OVCAR-8, A1847, and SKOV-3 cells. Ganetespib treatment resulted in dose-dependent inhibition of cell viability with IC50 values at 72 hours ranging from 9 to 48 nmol/L (Fig. 2A). Treatment of cells within the IC50 range (e.g., 5–50 nmol/L) of ganetespib for 48 hours resulted in a significant increase in the percentage of apoptotic cells, whereas increasing the dose (10–100 nmol/L) and duration (72 hours) of exposure increased the percentage of apoptotic cells further (Fig. 2B). Exposure to ganetespib (25–50 nmol/L) also resulted in the accumulation of cells in the G2–M phase of the cell cycle (Fig. 2C). In addition, comparable concentrations of ganetespib (i.e., 25–50 nmol/L) reduced the expression of canonical HSP90 clients including total and phosphorylated (p) proteins, including JAK2, pJAK2, pSTAT3, and pSRC (Fig. 2D and E).

Figure 2.

Ganetespib treatment affects cell viability, apoptosis, cell-cycle distribution, and HSP90 client proteins in EOC cells. A, OVCAR-5, OVCAR-8, A1847, and SKOV-3 cells were treated with increasing concentrations (0, 0.1, 0.5, 1, 5, 10, 50, 100, 500, and 1,000 nmol/L) of ganetespib for 72 hours and cell viability was assessed by CellTiter Blue Cell Viability Assay. Data indicate the mean percentage viability calculated from triplicate samples from three independent experiments (±SE). B, OVCAR-5, OVCAR-8, and A1847 cells were treated with 0, 10, 25, or 50 nmol/L ganetespib for 48 hours and analyzed for the presence of Annexin V–PE(+)/7-AAD(−) cells (early apoptosis) and Annexin V–PE (+)/7-AAD (+) cells (late apoptosis). Data shown are the mean values (±SE) from three independent experiments. Statistically significant differences were determined by two-way ANOVA, followed by Bonferroni posttests (*, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001). Analysis of OVCAR-5 and A1847 cells was extended to include a broader dose range (0, 10, 50, 80, and 100) and duration of the assay (72 hours) and showed increased apoptosis at higher concentrations of drug and after longer exposure. C, OVCAR-5, OVCAR-8, and A1847 cells were treated with 0, 10, 25, or 50 nmol/L ganetespib for 24 or 48 hours, stained with propidium iodide and analyzed for cell-cycle distribution. Data shown are the mean values (±SE) from three independent experiments. D, ovarian carcinoma cells (OVCAR-5, OVCAR-8, A1847, and SKOV-3) were treated with increasing doses of ganetespib for 24 hours and protein lysates were subjected to immunoblot analysis with the indicated antibodies. E, densitometric analysis of the immunoblots (D) was conducted using ImageJ 1.44 (NIH) to quantify pJAK, JAK, pSTAT3Y705, STAT3, pSRCY416, and SRC levels relative to β-actin. Etop, etoposide.

Figure 2.

Ganetespib treatment affects cell viability, apoptosis, cell-cycle distribution, and HSP90 client proteins in EOC cells. A, OVCAR-5, OVCAR-8, A1847, and SKOV-3 cells were treated with increasing concentrations (0, 0.1, 0.5, 1, 5, 10, 50, 100, 500, and 1,000 nmol/L) of ganetespib for 72 hours and cell viability was assessed by CellTiter Blue Cell Viability Assay. Data indicate the mean percentage viability calculated from triplicate samples from three independent experiments (±SE). B, OVCAR-5, OVCAR-8, and A1847 cells were treated with 0, 10, 25, or 50 nmol/L ganetespib for 48 hours and analyzed for the presence of Annexin V–PE(+)/7-AAD(−) cells (early apoptosis) and Annexin V–PE (+)/7-AAD (+) cells (late apoptosis). Data shown are the mean values (±SE) from three independent experiments. Statistically significant differences were determined by two-way ANOVA, followed by Bonferroni posttests (*, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001). Analysis of OVCAR-5 and A1847 cells was extended to include a broader dose range (0, 10, 50, 80, and 100) and duration of the assay (72 hours) and showed increased apoptosis at higher concentrations of drug and after longer exposure. C, OVCAR-5, OVCAR-8, and A1847 cells were treated with 0, 10, 25, or 50 nmol/L ganetespib for 24 or 48 hours, stained with propidium iodide and analyzed for cell-cycle distribution. Data shown are the mean values (±SE) from three independent experiments. D, ovarian carcinoma cells (OVCAR-5, OVCAR-8, A1847, and SKOV-3) were treated with increasing doses of ganetespib for 24 hours and protein lysates were subjected to immunoblot analysis with the indicated antibodies. E, densitometric analysis of the immunoblots (D) was conducted using ImageJ 1.44 (NIH) to quantify pJAK, JAK, pSTAT3Y705, STAT3, pSRCY416, and SRC levels relative to β-actin. Etop, etoposide.

Close modal

We next used orthotopic xenograft and transgenic mouse models of EOC to assess the in vivo efficacy of ganetespib monotherapy. Drug treatment was well tolerated in both models, with no apparent toxicities. For the xenograft model, OVCAR-5-Luc cells were implanted by injection into the intrabursal space surrounding the ovary. Mice were monitored in vivo by longitudinal BLI from the stably integrated luciferase (Luc; Fig. 3A and B). The BLI data indicated statistically significant inhibition (P < 0.01) of xenograft growth rate, and endpoint assessments confirmed this observation, showing significantly decreased final tumor volume, weight, and dissemination of tumor nodules following 3 weeks of treatment with 125 mg/kg ganetespib (Fig. 3B). In ovarian tumor-bearing transgenic mice, tumor growth was monitored and quantified by MRI (29), and it similarly showed decreased tumor growth rate in ganetespib-treated mice (Fig. 3C).

Figure 3.

Ganetespib (gan) exhibits single-agent activity in an orthotopic xenograft and a transgenic mouse model of EOC. A, OVCAR-5-Luc cells were implanted as orthotopic xenografts in SCID mice (n = 15 per group) and mice were treated weekly with vehicle (veh) or 125 mg/kg ganetespib (gan) for 3 weeks. A, the presence of tumors was confirmed in baseline BLI scans 10 days after tumor implantation, and tumor growth was monitored in vivo weekly thereafter by BLI (scans 1–3). B, average radiance (photons/s) was measured weekly showing significant differences (**, P < 0.01) in ganetespib-treated mice compared with vehicle-treated controls. Primary tumor volume, weight, and the number of abdominal tumor nodules were determined at necropsy, and showed significant inhibition (*, P < 0.05, **, P < 0.01) in ganetespib-treated mice compared with vehicle-treated controls. C, a separate experiment evaluated the effects of ganetespib in a transgenic mouse model of EOC, in which tumor growth rate was monitored and quantified by MRI and volumetrics analysis. Mice treated weekly with 125 mg/kg ganetespib exhibited significantly decreased tumor growth compared with vehicle (n = 12)–treated controls. Combination of ganetespib with paclitaxel (pac) was evaluated in orthotopic OVCAR-5-Luc xenografts in SCID mice (n = 12 per group) treated weekly with vehicle, 125 mg/kg ganetespib, 6 mg/kg paclitaxel, or 125 mg/kg ganetespib + 6 mg/kg paclitaxel. D, tumor growth was monitored weekly in vivo by BLI (scans 1–3), showing significant differences (***, P < 0.001, ****, P < 0.0001) in mice treated with ganetespib or paclitaxel as single agents or in combination compared with vehicle-treated controls. Average radiance was significantly lower in combination-treated mice compared with mice treated with ganetespib or paclitaxel alone. E, primary tumor volume; F, tumor weight; and G, tumor nodules. Differences among groups were compared by the Mann–Whitney test with P < 0.05 considered significant (*, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001).

Figure 3.

Ganetespib (gan) exhibits single-agent activity in an orthotopic xenograft and a transgenic mouse model of EOC. A, OVCAR-5-Luc cells were implanted as orthotopic xenografts in SCID mice (n = 15 per group) and mice were treated weekly with vehicle (veh) or 125 mg/kg ganetespib (gan) for 3 weeks. A, the presence of tumors was confirmed in baseline BLI scans 10 days after tumor implantation, and tumor growth was monitored in vivo weekly thereafter by BLI (scans 1–3). B, average radiance (photons/s) was measured weekly showing significant differences (**, P < 0.01) in ganetespib-treated mice compared with vehicle-treated controls. Primary tumor volume, weight, and the number of abdominal tumor nodules were determined at necropsy, and showed significant inhibition (*, P < 0.05, **, P < 0.01) in ganetespib-treated mice compared with vehicle-treated controls. C, a separate experiment evaluated the effects of ganetespib in a transgenic mouse model of EOC, in which tumor growth rate was monitored and quantified by MRI and volumetrics analysis. Mice treated weekly with 125 mg/kg ganetespib exhibited significantly decreased tumor growth compared with vehicle (n = 12)–treated controls. Combination of ganetespib with paclitaxel (pac) was evaluated in orthotopic OVCAR-5-Luc xenografts in SCID mice (n = 12 per group) treated weekly with vehicle, 125 mg/kg ganetespib, 6 mg/kg paclitaxel, or 125 mg/kg ganetespib + 6 mg/kg paclitaxel. D, tumor growth was monitored weekly in vivo by BLI (scans 1–3), showing significant differences (***, P < 0.001, ****, P < 0.0001) in mice treated with ganetespib or paclitaxel as single agents or in combination compared with vehicle-treated controls. Average radiance was significantly lower in combination-treated mice compared with mice treated with ganetespib or paclitaxel alone. E, primary tumor volume; F, tumor weight; and G, tumor nodules. Differences among groups were compared by the Mann–Whitney test with P < 0.05 considered significant (*, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001).

Close modal

In separate pharmacodynamic studies, mice with established orthotopic OVCAR-5 tumors were treated acutely with ganetespib and tumors collected 6 or 24 hours later for evaluation of protein expression levels by immunoblot analyses of total and phosphorylated forms of more than 25 proteins (antibodies listed in Materials and Methods). Among the proteins affected by ganetespib-treatment, there were many established HSP90 clients, with some more predominantly inhibited at 6 hours posttreatment (pJAK2, pSTAT3, total and pS6, and pAKT), some at 24 hours (pSTAT5, total and pCDK1, and AKT), and some inhibited at both time points (total JAK2 and c-MYC; Fig. 4A and B). Consistent with the previously described HSF1-mediated induction of heat shock response elicited by HSP90 inhibitors, that is, tanespimycin and radicicol derivatives (51), levels of HSP70 protein were increased in tumors 6 and 24 hours after ganetespib treatment (Fig. 4A and B). Independent ELISA analyses confirmed the significant induction of HSP70 (2-fold at 6 hours and 2.4-fold at 24 hours) and inhibition of pSTAT3 (2.6-fold decreased at 6 hours) in tumors from ganetespib-treated mice (Fig. 4C and D). Immunohistochemical staining revealed no significant differences in Ki-67, caspase-3, PARP, or total STAT3 levels at 6 or 24 hours postdosing (not shown), but further confirmed significantly reduced levels of pSTAT3 present in tumor tissues 6 hours after ganetespib treatment (Fig. 4E). These results suggested that there are differences in the timing and duration of client inhibition in vivo, and that the mechanisms of tumor inhibition likely involve multiple signaling pathways with variable kinetics. The observed single-agent activity of ganetespib in EOC cells, an orthotopic xenograft model, and transgenic mice predicted that this agent may be promising for the treatment of patients, but also suggested that maximum clinical advantage might be gained by combining ganetespib with other therapeutic agents in standard use or development for EOC.

Figure 4.

Ganetespib (gan)-treatment inhibits HSP90 client protein expression and activation in tumors. A, pharmacodynamic analysis was conducted on tumors isolated from mice treated with vehicle (veh) or ganetespib at 6 and 24 hours posttreatment (n = 4 mice/group/time point). Protein lysates were prepared and subjected to immunoblot analysis with the indicated antibodies. B, immunoblots were subjected to densitometric analysis using ImageJ 1.44 (NIH) to quantify each target protein levels relative to β-actin. Statistically significant differences were determined by two-way ANOVA, followed by Bonferroni posttests (*, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001). Detection of HSP70 (C) and pSTAT3Y705 (D) levels present protein lysates by enhanced chemiluminescent ELISA assay (***, P < 0.001). E, immunohistochemical detection of pSTAT3Y705 in tumors. Data are presented as the H score (**, P < 0.01), considering both staining intensity and the percentage of positively staining cells with representative micrographs of pSTAT3Y705 staining in tumor tissue isolated 6 and 24 hours after vehicle or ganetespib treatment (scale bar, 50 μm). F, heatmap of RPPA analysis showing proteins with significantly decreased (blue) and increased (yellow) protein expression following treatment with ganetespib, paclitaxel, or ganetespib + paclitaxel.

Figure 4.

Ganetespib (gan)-treatment inhibits HSP90 client protein expression and activation in tumors. A, pharmacodynamic analysis was conducted on tumors isolated from mice treated with vehicle (veh) or ganetespib at 6 and 24 hours posttreatment (n = 4 mice/group/time point). Protein lysates were prepared and subjected to immunoblot analysis with the indicated antibodies. B, immunoblots were subjected to densitometric analysis using ImageJ 1.44 (NIH) to quantify each target protein levels relative to β-actin. Statistically significant differences were determined by two-way ANOVA, followed by Bonferroni posttests (*, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001). Detection of HSP70 (C) and pSTAT3Y705 (D) levels present protein lysates by enhanced chemiluminescent ELISA assay (***, P < 0.001). E, immunohistochemical detection of pSTAT3Y705 in tumors. Data are presented as the H score (**, P < 0.01), considering both staining intensity and the percentage of positively staining cells with representative micrographs of pSTAT3Y705 staining in tumor tissue isolated 6 and 24 hours after vehicle or ganetespib treatment (scale bar, 50 μm). F, heatmap of RPPA analysis showing proteins with significantly decreased (blue) and increased (yellow) protein expression following treatment with ganetespib, paclitaxel, or ganetespib + paclitaxel.

Close modal

In vitro assessment of ganetespib combination potential in EOC cells

Few targeted agents are effective as monotherapy in EOC. For example, erlotinib (inhibiting EGFR) and dasatinib (inhibiting SRC family kinases) have each been evaluated in patients with EOC, but neither drug showed single-agent activity (7, 52). However, given the close connection of the HSP90 clients EGFR and SRC to the sensitization network (Fig. 1), we assessed erlotinib and dasatinib for combination with ganetespib. For this purpose, we conducted Chou–Talalay analysis (53), combining each compound with ganetespib at different ratios in cultured cells. Ganetespib combined with either of these agents inhibited the growth of both A1847 and OVCAR-5 cells much more significantly than either drug administered independently (Supplementary Table S3). We next investigated the effect of combining ganetespib with paclitaxel and cisplatin, standard first-line cytotoxic agents used to treat patients with EOC (54–56). Notably, the combination of ganetespib was synergistic with both cisplatin and paclitaxel at all ratios tested in A1847 cells, and at some ratios in OVCAR-5 cells (Supplementary Table S3 and Supplementary Fig. S3).

Combination of ganetespib with paclitaxel potently inhibits orthotopic ovarian xenograft growth in vivo

To confirm the in vitro findings showing ganetespib-mediated sensitization to paclitaxel, the effects of single agent and combination therapy with ganetespib and paclitaxel were evaluated in two human ovarian carcinoma xenograft models (Fig. 3D–G and Supplementary Fig. S4). Treatment of mice bearing orthotopic OVCAR-5-Luc cell xenografts with ganetespib or paclitaxel alone resulted in significantly (P < 0.001) reduced in vivo tumor growth and final tumor volume and weight determined at necropsy (Fig. 3D–F). The overall tumor growth inhibition (TGI) observed was 57% and 61% for ganetespib- and paclitaxel-treated mice, respectively. Importantly, 85% TGI and 77% fewer tumor nodules were observed in mice treated with the combination therapy compared with vehicle-treated mice. The observed TGI and reduction in tumor nodules was significantly greater (P < 0.01) in mice treated with the combination therapy than with either drug used as a single agent (Fig. 3D–G). Similarly, treatment of mice harboring orthotopic A1847-Luc xenografts with either ganetespib or paclitaxel significantly inhibited tumor growth rate and primary tumor volume and weight (Supplementary Fig. S4A–S4C). As with OVCAR-5-Luc tumors, inhibition of several HSP90 client proteins (e.g., JAK2, pSTAT3, total and pS6, pAKT, c-MYC, cyclin D1, and survivin) was confirmed in mice bearing A1847-Luc tumors treated with ganetespib (Supplementary Fig. S4D–S4F). Combination of ganetespib + paclitaxel was significantly better than ganetespib alone (77% TGI compared with 43% TGI, respectively). Mice with A1847 xenografts exhibited greater sensitivity to paclitaxel alone than mice with OVCAR-5 xenografts (72% vs. 61% TGI); therefore, while combination therapy in A1847 xenografts resulted in 77% TGI, the difference between single-agent paclitaxel and combination therapy was not significant (P = 0.12) due to the potent effect of paclitaxel. Taken together, these data suggest that the combination of ganetespib with paclitaxel may be a promising clinical therapeutic strategy.

To identify potential mechanisms underlying the ganetespib-mediated sensitization to paclitaxel, we compared the effects of treatment of OVCAR-5 cells with ganetespib and paclitaxel as single agents or in combination by RPPA analysis. Results of this experiment supported the immunoblot analyses (Figs. 2D and 4A and B), and identified additional proteins that were significantly affected in cells treated with ganetespib alone or combined with paclitaxel (Fig. 4F and Supplementary Table S4). This analysis showed significant depletion of AKT/mTOR and mitogen-activated protein kinase (MAPK) signaling pathway proteins, kinases, and transcription factors, as well as increased levels of apoptotic proteins and E-cadherin (Fig. 4F and Supplementary Table S4). However, the analysis did not reveal proteins that were significantly more affected by the combination of ganetespib and paclitaxel compared with either drug alone.

HSP90-interacting proteins sensitize EOC cells to ganetespib

In sum, the preceding data suggested considerable potential for supplementing standard paclitaxel regimens for EOC with ganetespib. As noted earlier, a number of members of the original group of HSP90-interacting proteins that led us to nominate HSP90 as a target have previously been linked to EOC pathogenesis, and in some cases been explored as drug inhibition targets in EOC. Among this group, some [including the genes PDPK1 (encoding PDK1), PRKCE (PKCϵ), RIPK (encoding RIP1), HIP1, and PRKCD (PKCδ)] were rapidly degraded following treatment of EOC cell lines or tumors with ganetespib (Fig. 5A and B).

Figure 5.

HSP90-interacting proteins sensitize EOC cells to ganetespib. A, Western blot analysis with indicated antibodies shows loss of HSP90 clients following ganetespib-treated A1847 and OVCAR-5 cells in vitro, and in ganetespib-treated OVCAR-5 xenograft tumors, 6 hours after administration of drug. B, quantification of data in (A) indicates ratios of indicated proteins in ganetespib- versus vehicle-treated samples. Data reflect average of three independent experiments; error bars, SD (*, P < 0.05, **, P < 0.01, ***, P < 0.001). C, graphic representation of relative degree of sensitization to ganetespib by siRNA depletion of HSP90-interacting genes in A1847 (inner ring) and OVCAR-5 (outer ring). More intense gray shading reflects greater sensitization; precise values are listed in Supplementary Table S4.

Figure 5.

HSP90-interacting proteins sensitize EOC cells to ganetespib. A, Western blot analysis with indicated antibodies shows loss of HSP90 clients following ganetespib-treated A1847 and OVCAR-5 cells in vitro, and in ganetespib-treated OVCAR-5 xenograft tumors, 6 hours after administration of drug. B, quantification of data in (A) indicates ratios of indicated proteins in ganetespib- versus vehicle-treated samples. Data reflect average of three independent experiments; error bars, SD (*, P < 0.05, **, P < 0.01, ***, P < 0.001). C, graphic representation of relative degree of sensitization to ganetespib by siRNA depletion of HSP90-interacting genes in A1847 (inner ring) and OVCAR-5 (outer ring). More intense gray shading reflects greater sensitization; precise values are listed in Supplementary Table S4.

Close modal

To gain additional insights into the functional relationship of these proteins in HSP90 activity, we assessed whether their depletion affected sensitization to ganetespib in OVCAR-5 and A1847 cells. This identified a group of 20 siRNAs, targeting RAF1, PDPK1, RIPK1, FGR, STAT3, AURKA, and others, that increased the sensitivity of cells to ganetespib in both cell lines (Fig. 5C; Supplementary Fig. S5; and Supplementary Table S5). We therefore directly tested whether drug inhibition of AURKA (with alisertib), JAK2 (an upstream activator of STAT3, with ruxolitinib), or PDK1 (with GSK2334470) enhanced ganetespib activity. Chou–Talalay analysis indicated significant synergy between each of these agents (alisertib, ruxolitinib, and GSK2334470) and ganetespib at several different combination ratios in OVCAR-5 and A1847 cells (Table 1 and Fig. 6). Collectively, these findings suggest the capacity of ganetespib to sensitize ovarian carcinoma cells to a broad range of cytotoxic and targeted therapeutic agents.

Figure 6.

Synergistic reduction of ovarian carcinoma cell viability with ganetespib (gan) in combination with alisertib or ruxolitinib. Cell viability in OVCAR-5 (A) and A1847 (B) treated with ganetespib (gan), alisertib (ali), or gan:ali; molar ratio 20:1, showing strong synergy. Cell viability in OVCAR-5 (C) and A1847 (D) treated with gan, ruxolitinib (rux), and gan:rux; molar ratio 10:1, showing strong synergy. Viability curves shown represent the average of three independent experiments; error bars, SDs.

Figure 6.

Synergistic reduction of ovarian carcinoma cell viability with ganetespib (gan) in combination with alisertib or ruxolitinib. Cell viability in OVCAR-5 (A) and A1847 (B) treated with ganetespib (gan), alisertib (ali), or gan:ali; molar ratio 20:1, showing strong synergy. Cell viability in OVCAR-5 (C) and A1847 (D) treated with gan, ruxolitinib (rux), and gan:rux; molar ratio 10:1, showing strong synergy. Viability curves shown represent the average of three independent experiments; error bars, SDs.

Close modal
Table 1.

Combination index (CI) values of ganetespib and targeted therapeutic agents alisertib, ruxolitinib, and GSK2334470 in OVCAR-5 and A1847 cells

Combination index, CIa (±SD)
Cell lineMolar ratioED50ED75ED95
OVCAR-5 Ganetespib:alisertib 
  80:1 0.24 ± 0.23 0.16 ± 0.23 0.11 ± 0.16 
  40:1 0.49 ± 0.08 0.39 ± 0.42 0.57 ± 0.87 
  20:1 0.42 ± 0.16 0.38 ± 0.43 0.57 ± 0.81 
  5:1 0.79 ± 0.27 1.11 ± 0.82 1.10 ± 0.85 
  1:1 1.04 ± 0.38 1.22 ± 0.31 1.70 ± 0.76 
  1:5 0.60 ± 0.22 0.64 ± 0.40 1.32 ± 1.14 
  1:20 0.94 ± 0.32 0.85 ± 0.18 0.80 ± 0.22 
  1:40 1.15 ± 0.19 0.64 ± 0.31 0.15 ± 0.06 
  1:80 2.46 ± 1.17 0.82 ± 0.53 0.14 ± 0.11 
 Ganetespib:ruxolitinib 
  50:1 0.46 ± 0.06 0.43 ± 0.05 0.38 ± 0.04 
  10:1 0.46 ± 0.06 0.45 ± 0.13 0.47± 0.30 
  1:1 0.95 ± 0.13 0.85 ± 0.25 0.75 ± 0.39 
  1:5 0.82 ± 0.14 0.60 ± 0.14 0.36 ± 0.12 
  1:50 0.93 ± 0.12 0.92 ± 0.44 1.18 ± 1.04 
  1:100 0.95 ± 0.17 1.09 ± 0.30 1.85 ± 0.93 
 Ganetespib:GSK2334470 
  100:1 0.21 ± 0.15 0.08 ± 0.05 0.03 ± 0.02 
  10:1 0.20 ± 0.11 0.07 ± 0.04 0.03 ± 0.02 
  1:1 0.79 ± 0.24 0.77 ± 0.18 0.73 ± 0.31 
  1:5 1.03 ± 0.33 0.87 ± 0.35 0.65 ± 0.27 
  1:20 1.42 ± 0.42 1.34 ± 0.44 1.22 ± 0.38 
  1:50 7.39 ± 2.10 5.48 ± 1.88 3.32 ± 0.89 
A1847 Ganetespib:alisertib 
  80:1 0.46 ± 0.01 0.47 ± 0.27 0.49 ± 0.01 
  40:1 0.52 ± 0.03 0.80 ± 0.04 1.75 ± 0.40 
  20:1 0.44 ± 0.27 0.53 ± 0.06 0.80 ± 0.10 
  5:1 0.68 ± 0.16 0.70 ± 0.35 0.85 ± 0.82 
  1:1 1.01 ± 0.35 1.37 ± 1.03 2.95 ± 3.06 
  1:5 0.30 ± 0.10 0.41 ± 0.18 1.74 ± 1.69 
  1:20 0.39 ± 0.08 0.59 ± 0.09 2.80 ± 1.88 
  1:40 0.62 ± 0.26 0.60 ± 0.13 1.16 ± 0.85 
  1:80 0.91 ± 0.46 0.71 ± 0.06 0.98 ± 0.68 
 Ganetespib:ruxolitinib 
  50:1 0.45 ± 0.07 0.50 ± 0.29 0.77 ± 0.92 
  10:1 0.47 ± 0.05 0.47 ± 0.08 0.49 ± 0.24 
  1:1 0.86 ± 0.27 0.79 ± 0.37 0.74 ± 0.56 
  1:5 0.74 ± 0.17 0.70 ± 0.29 0.72 ± 0.63 
  1:50 1.05 ± 0.15 1.22 ± 0.41 1.83 ± 1.15 
  1:100 1.04 ± 0.01 1.05 ± 0.20 1.15 ± 0.58 
 Ganetespib:GSK2334470 
  100:1 0.71 ± 0.32 0.69 ± 0.28 0.65 ± 0.29 
  10:1 0.64 ± 0.25 0.61 ± 0.33 0.56 ± 0.20 
  1:1 0.53 ± 0.24 0.40 ± 0.19 0.26 ± 0.15 
  1:5 1.18 ± 0.38 1.23 ± 0.31 1.33 ± 0.40 
  1:20 1.28 ± 0.31 0.91 ± 0.41 0.51 ± 0.39 
  1:50 3.06 ± 1.08 2.75 ± 0.79 2.32 ± 0.88 
Combination index, CIa (±SD)
Cell lineMolar ratioED50ED75ED95
OVCAR-5 Ganetespib:alisertib 
  80:1 0.24 ± 0.23 0.16 ± 0.23 0.11 ± 0.16 
  40:1 0.49 ± 0.08 0.39 ± 0.42 0.57 ± 0.87 
  20:1 0.42 ± 0.16 0.38 ± 0.43 0.57 ± 0.81 
  5:1 0.79 ± 0.27 1.11 ± 0.82 1.10 ± 0.85 
  1:1 1.04 ± 0.38 1.22 ± 0.31 1.70 ± 0.76 
  1:5 0.60 ± 0.22 0.64 ± 0.40 1.32 ± 1.14 
  1:20 0.94 ± 0.32 0.85 ± 0.18 0.80 ± 0.22 
  1:40 1.15 ± 0.19 0.64 ± 0.31 0.15 ± 0.06 
  1:80 2.46 ± 1.17 0.82 ± 0.53 0.14 ± 0.11 
 Ganetespib:ruxolitinib 
  50:1 0.46 ± 0.06 0.43 ± 0.05 0.38 ± 0.04 
  10:1 0.46 ± 0.06 0.45 ± 0.13 0.47± 0.30 
  1:1 0.95 ± 0.13 0.85 ± 0.25 0.75 ± 0.39 
  1:5 0.82 ± 0.14 0.60 ± 0.14 0.36 ± 0.12 
  1:50 0.93 ± 0.12 0.92 ± 0.44 1.18 ± 1.04 
  1:100 0.95 ± 0.17 1.09 ± 0.30 1.85 ± 0.93 
 Ganetespib:GSK2334470 
  100:1 0.21 ± 0.15 0.08 ± 0.05 0.03 ± 0.02 
  10:1 0.20 ± 0.11 0.07 ± 0.04 0.03 ± 0.02 
  1:1 0.79 ± 0.24 0.77 ± 0.18 0.73 ± 0.31 
  1:5 1.03 ± 0.33 0.87 ± 0.35 0.65 ± 0.27 
  1:20 1.42 ± 0.42 1.34 ± 0.44 1.22 ± 0.38 
  1:50 7.39 ± 2.10 5.48 ± 1.88 3.32 ± 0.89 
A1847 Ganetespib:alisertib 
  80:1 0.46 ± 0.01 0.47 ± 0.27 0.49 ± 0.01 
  40:1 0.52 ± 0.03 0.80 ± 0.04 1.75 ± 0.40 
  20:1 0.44 ± 0.27 0.53 ± 0.06 0.80 ± 0.10 
  5:1 0.68 ± 0.16 0.70 ± 0.35 0.85 ± 0.82 
  1:1 1.01 ± 0.35 1.37 ± 1.03 2.95 ± 3.06 
  1:5 0.30 ± 0.10 0.41 ± 0.18 1.74 ± 1.69 
  1:20 0.39 ± 0.08 0.59 ± 0.09 2.80 ± 1.88 
  1:40 0.62 ± 0.26 0.60 ± 0.13 1.16 ± 0.85 
  1:80 0.91 ± 0.46 0.71 ± 0.06 0.98 ± 0.68 
 Ganetespib:ruxolitinib 
  50:1 0.45 ± 0.07 0.50 ± 0.29 0.77 ± 0.92 
  10:1 0.47 ± 0.05 0.47 ± 0.08 0.49 ± 0.24 
  1:1 0.86 ± 0.27 0.79 ± 0.37 0.74 ± 0.56 
  1:5 0.74 ± 0.17 0.70 ± 0.29 0.72 ± 0.63 
  1:50 1.05 ± 0.15 1.22 ± 0.41 1.83 ± 1.15 
  1:100 1.04 ± 0.01 1.05 ± 0.20 1.15 ± 0.58 
 Ganetespib:GSK2334470 
  100:1 0.71 ± 0.32 0.69 ± 0.28 0.65 ± 0.29 
  10:1 0.64 ± 0.25 0.61 ± 0.33 0.56 ± 0.20 
  1:1 0.53 ± 0.24 0.40 ± 0.19 0.26 ± 0.15 
  1:5 1.18 ± 0.38 1.23 ± 0.31 1.33 ± 0.40 
  1:20 1.28 ± 0.31 0.91 ± 0.41 0.51 ± 0.39 
  1:50 3.06 ± 1.08 2.75 ± 0.79 2.32 ± 0.88 

aValues indicate: CI > 1, antagonism; CI = 1, additive effects; CI < 0.9, synergy; and CI < 0.5 strong synergy.

Early efforts to target HSP90 with natural product antibiotics with antitumor activity such as geldanamycin and its analogs, including tanespimycin (17-AAG) and alvespimycin (17-DMAG), showed promising activity in clinical trials, particularly in cancers that are highly dependent on key HSP90 clients (e.g., HER2+ breast cancer) or that are sensitive to proteotoxic stress (e.g., multiple myeloma; refs. 57, 58). Some assessments with these first-generation agents were conducted in EOC cells or tumors (59, 60) and showed antiproliferative and proapoptotic effects suggesting possible clinical benefit (60–63). Despite these encouraging data, these first-generation agents suffered from limitations related to hepatic toxicity, issues related to solubility and formulation, and consequently the inability to achieve sufficient doses required for sustained client depletion (12, 64), and clinical development of these agents was ceased.

The results of our meta-analysis emphasizing the importance of HSP90 in EOC were well-timed to benefit from intensive efforts focused on the development of second-generation small-molecule synthetic inhibitors of HSP90 with favorable biologic and clinical properties. Ganetespib (formerly STA-9090) is a highly promising anticancer agent (17). In preclinical studies, ganetespib exhibited potent in vitro cytotoxicity, degradation of client proteins, superior activity to tanespimycin, and in vivo antitumor activity in several solid tumor models including non–small cell lung carcinoma (NSCLC), melanoma, prostate, and gastric cancers (17, 65–68). In the clinic, ganetespib has been given to more than 700 patients and is well tolerated, with the most common side effects including fatigue, diarrhea, constipation, nausea, vomiting, anorexia, and abdominal pain. Single-agent clinical activity has been seen in patients with advanced breast cancer, NSCLC, gastrointestinal stromal tumor, colorectal cancers, and melanoma (http://www.syntapharma.com). Comparisons between ganetespib and other HSP90 inhibitors including 17-DMAG and AT13387 also emphasized the greater potency of ganetespib (14–17).

In our study, we show that ganetespib significantly reduced EOC cell viability and cell-cycle progression, increased apoptosis, and decreased client protein expression and stability in vitro. Ganetespib also significantly reduced tumor growth and dissemination in vivo, in the absence of any observed drug-related toxicities. Mechanistically, using both a candidate approach and RPPA-mediated screens, we found that ganetespib limited expression and/or activation of client proteins, with many linked to EOC pathogenesis, including JAK2, pSTAT3, EGFR, SRC, S6, AKT, mTOR, NF-κB, and c-MYC. Pharmacodynamic analysis conducted both in vitro and in vivo showed that ganetespib treatment resulted in depression of many targets for 24 hours; enough to interrupt the cycle of continuous utilization of proliferative pathways required for the viability of transformed cells, and to trigger an apoptotic response. The stronger responses to ganetespib observed in pure populations of cultured tumor cells than in tumors likely reflects the more heterogeneous cell population in the primary tumor, as well as the presence of drug-metabolizing enzymes; nevertheless, there was clear evidence for a significant depression of known HSP90 clients in tumor tissue.

As with most targeted therapeutics, there is concern over intrinsic or acquired resistance. Therefore, continued preclinical work directed at identification, analysis, and validation of additional targets that sensitize EOC to ganetespib is warranted to understand mechanisms of resistance and potential ways to circumvent it. Our return to network analysis led us to investigate whether siRNAs and small-molecule inhibitors of proteins from the original dataset that nominated HSP90 as a target were themselves sensitizing to ganetespib. Some of these interactors are known to be commonly activated and/or overexpressed in EOC, including AURKA and JAK2/STAT3, and we found both siRNA and small-molecule inhibitors enhanced ganetespib activity (30, 41, 45, 46, 69–71). Others, such as the SRC-related kinase FGR, the inflammation associated kinase RIPK, and the PTEN/AKT pathway kinase PDK1, have been little studied in EOC. In this study, we found that both siRNA and a small-molecule inhibitor of PDK1 enhanced ganetespib action, suggesting new directions for further evaluation of drug combinations for use in EOC.

The essential strategy of combining targeted therapeutics with first-line cytotoxic agents is to target different mechanisms of action and minimize potential for overlapping toxicity. Of particular importance for clinical practice, ganetespib potently sensitized EOC cells to the effects of standard cytotoxic chemotherapy agents used for patients with EOC (e.g., cisplatin and paclitaxel) in vitro, suggesting potential benefit of combining ganetespib with standard therapy in patients. In vivo, sensitization to paclitaxel was confirmed in two independent orthotopic xenograft models. Although the underlying mechanism for this sensitization was not revealed by the RPPA analysis, we previously reported the synergistic activity of ganetespib with taxanes in NSCLC models (72). The observed synergy may be related to disruption of cell-cycle checkpoints and spindle function and will require additional studies. These results are particularly promising, as patients with recurrent and platinum-refractory disease are frequently treated with paclitaxel (83). These encouraging results established evaluation of the combination of ganetespib and paclitaxel in the clinical setting as an obvious next step.

D.A. Proia is employed as Director, Cancer Biology in Synta Pharmaceuticals Corp. No potential conflicts of interest were disclosed by the other authors.

Conception and design: I.G. Serebriiskii, E.A. Golemis, D.C. Connolly

Development of methodology: H. Liu, F. Xiao, I. Astsaturov, E.A. Golemis, D.C. Connolly

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): H. Liu, F. Xiao, S.W. O'Brien, M.A. Maglaty, D.A. Proia, D.C. Connolly

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): H. Liu, F. Xiao, I.G. Serebriiskii, S. Litwin, L.P. Martin, D.A. Proia, E.A. Golemis, D.C. Connolly

Writing, review, and/or revision of the manuscript: H. Liu, F. Xiao, I.G. Serebriiskii, L.P. Martin, D.A. Proia, E.A. Golemis, D.C. Connolly

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): D.C. Connolly

Study supervision: E.A. Golemis, D.C. Connolly

This work was supported by the FCCC Laboratory Animal, Transgenic, High Throughput Screening, Cell Culture, Biosample Repository, Biomedical Imaging, Histopathology and Biostatistics, and Bioinformatics Facilities. The authors thank the technical assistance of Dr. Dong-Hua Yang and Ms. Meghan Livingstone of the FCCC Biosample Repository Facility for construction, staining, and analysis of mouse tumor TMAs and Mr. Xiang Hua in the Transgenic Facility for assistance with intrabursal injections.

This work was supported by the FCCC, University of Pennsylvania Ovarian SPORE P50 CA083638 (Project 4; to D.C. Connolly, E.A. Golemis, and L.P. Martin); R01 CA136596 (to D.C. Connolly); R01 CA63366 and a grant from the Sandy Rollman Ovarian Cancer Foundation (to E.A. Golemis); an SASS Foundation for Medical Research Fellowship and an Ovarian Cancer Research Fund Ann Schreiber Program of Excellence Award (to H. Liu), and the FCCC Core Grant NCI P30 CA006927.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Siwak
DR
,
Carey
M
,
Hennessy
BT
,
Nguyen
CT
,
McGahren Murray
MJ
,
Nolden
L
, et al
Targeting the epidermal growth factor receptor in epithelial ovarian cancer: current knowledge and future challenges
.
J Oncol
2010
;
2010
:
568938
.
2.
Behbakht
K
,
Sill
MW
,
Darcy
KM
,
Rubin
SC
,
Mannel
RS
,
Waggoner
S
, et al
Phase II trial of the mTOR inhibitor, temsirolimus and evaluation of circulating tumor cells and tumor biomarkers in persistent and recurrent epithelial ovarian and primary peritoneal malignancies: a Gynecologic Oncology Group study
.
Gynecol Oncol
2011
;
123
:
19
26
.
3.
Bodnar
L
,
Górnas
M
,
Szczylik
C
. 
Sorafenib as a third line therapy in patients with epithelial ovarian cancer or primary peritoneal cancer: a phase II study
.
Gynecol Oncol
2011
;
123
:
33
6
.
4.
Garcia
AA
,
Sill
MW
,
Lankes
HA
,
Godwin
AK
,
Mannel
RS
,
Armstrong
DK
, et al
A phase II evaluation of lapatinib in the treatment of persistent or recurrent epithelial ovarian or primary peritoneal carcinoma: a gynecologic oncology group study
.
Gynecol Oncol
2012
;
124
:
569
74
.
5.
Matei
D
,
Sill
MW
,
Lankes
HA
,
DeGeest
K
,
Bristow
RE
,
Mutch
D
, et al
Activity of sorafenib in recurrent ovarian cancer and primary peritoneal carcinomatosis: a Gynecologic Oncology Group Trial
.
J Clin Oncol
2011
;
29
:
69
75
.
6.
Noguera
IR
,
Sun
CC
,
Broaddus
RR
,
Branham
D
,
Levenback
CF
,
Ramirez
PT
, et al
Phase II trial of imatinib mesylate in patients with recurrent platinum- and taxane-resistant low-grade serous carcinoma of the ovary, peritoneum, or fallopian tube
.
Gynecol Oncol
2012
;
125
:
640
5
.
7.
Schilder
RJ
,
Brady
WE
,
Lankes
HA
,
Fiorica
JV
,
Shahin
MS
,
Zhou
XC
, et al
Phase II evaluation of dasatinib in the treatment of recurrent or persistent epithelial ovarian or primary peritoneal carcinoma: a Gynecologic Oncology Group study
.
Gynecol Oncol
2012
;
127
:
70
4
.
8.
Schilder
RJ
,
Sill
MW
,
Lee
RB
,
Shaw
TJ
,
Senterman
MK
,
Klein-Szanto
AJ
, et al
Phase II evaluation of imatinib mesylate in the treatment of recurrent or persistent epithelial ovarian or primary peritoneal carcinoma: a Gynecologic Oncology Group study
.
J Clin Oncol
2008
;
26
:
3418
25
.
9.
Usha
L
,
Sill
MW
,
Darcy
KM
,
Benbrook
DM
,
Hurteau
JA
,
Michelin
DP
, et al
A Gynecologic Oncology Group phase II trial of the protein kinase C-beta inhibitor, enzastaurin and evaluation of markers with potential predictive and prognostic value in persistent or recurrent epithelial ovarian and primary peritoneal malignancies
.
Gynecol Oncol
2011
;
121
:
455
61
.
10.
TCGA
. 
Integrated genomic analyses of ovarian carcinoma
.
Nature
2011
;
474
:
609
15
.
11.
Astsaturov
I
,
Ratushny
V
,
Sukhanova
A
,
Einarson
MB
,
Bagnyukova
T
,
Zhou
Y
, et al
Synthetic lethal screen of an EGFR-centered network to improve targeted therapies
.
Sci Signal
2010
;
3
:
ra67
.
12.
Neckers
L
,
Workman
P
. 
Hsp90 molecular chaperone inhibitors: are we there yet?
Clin Cancer Res
2012
;
18
:
64
76
.
13.
Workman
P
. 
Altered states: selectively drugging the Hsp90 cancer chaperone
.
Trends Mol Med
2004
;
10
:
47
51
.
14.
Kang
MH
,
Reynolds
CP
,
Houghton
PJ
,
Alexander
D
,
Morton
CL
,
Kolb
EA
, et al
Initial testing (Stage 1) of AT13387, an HSP90 inhibitor, by the pediatric preclinical testing program
.
Pediatr Blood Cancer
2012
;
59
:
185
8
.
15.
Lock
RB
,
Carol
H
,
Maris
JM
,
Kang
MH
,
Reynolds
CP
,
Kolb
EA
, et al
Initial testing (stage 1) of ganetespib, an Hsp90 inhibitor, by the pediatric preclinical testing program
.
Pediatr Blood Cancer
2013
;
60
:
E42
E5
.
16.
Shimamura
T
,
Perera
SA
,
Foley
KP
,
Sang
J
,
Rodig
SJ
,
Inoue
T
, et al
Ganetespib (STA-9090), a nongeldanamycin HSP90 inhibitor, has potent antitumor activity in in vitro and in vivo models of non–small cell lung cancer
.
Clin Cancer Res
2012
;
18
:
4973
85
.
17.
Ying
W
,
Du
Z
,
Sun
L
,
Foley
KP
,
Proia
DA
,
Blackman
RK
, et al
Ganetespib, a unique triazolone-containing Hsp90 inhibitor, exhibits potent antitumor activity and a superior safety profile for cancer therapy
.
Mol Cancer Ther
2012
;
11
:
475
84
.
18.
Whitehurst
AW
,
Bodemann
BO
,
Cardenas
J
,
Ferguson
D
,
Girard
L
,
Peyton
M
, et al
Synthetic lethal screen identification of chemosensitizer loci in cancer cells
.
Nature
2007
;
446
:
815
9
.
19.
Smoot
ME
,
Ono
K
,
Ruscheinski
J
,
Wang
PL
,
Ideker
T
. 
Cytoscape 2.8: new features for data integration and network visualization
.
Bioinformatics
2011
;
27
:
431
2
.
20.
Jayapandian
M
,
Chapman
A
,
Tarcea
VG
,
Yu
C
,
Elkiss
A
,
Ianni
A
, et al
Michigan Molecular Interactions (MiMI): putting the jigsaw puzzle together
.
Nucleic Acids Res
2007
;
35
:
D566
71
.
21.
Wishart
DS
,
Knox
C
,
Guo
AC
,
Shrivastava
S
,
Hassanali
M
,
Stothard
P
, et al
DrugBank: a comprehensive resource for in silico drug discovery and exploration
.
Nucleic Acids Res
2006
;
34
:
D668
72
.
22.
Szklarczyk
D
,
Franceschini
A
,
Kuhn
M
,
Simonovic
M
,
Roth
A
,
Minguez
P
, et al
The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored
.
Nucleic Acids Res
2011
;
39
:
D561
8
.
23.
Taipale
M
,
Jarosz
DF
,
Lindquist
S
. 
HSP90 at the hub of protein homeostasis: emerging mechanistic insights
.
Nat Rev Mol Cell Biol
2010
;
11
:
515
28
.
24.
Echeverría
PC
,
Bernthaler
A
,
Dupuis
P
,
Mayer
B
,
Picard
D
. 
An interaction network predicted from public data as a discovery tool: application to the Hsp90 molecular chaperone machine
.
PLoS ONE
2011
;
6
:
e26044
.
25.
Swift
S
,
Lorens
J
,
Achacoso
P
,
Nolan
GP
. 
Rapid production of retroviruses for efficient gene delivery to mammalian cells using 293T cell–based systems
.
Curr Protoc Immunol
2001
;
Chapter 10:Unit 10.17C
.
26.
Chou
TC
,
Talalay
P
. 
Quantitative analysis of dose–effect relationships: the combined effects of multiple drugs or enzyme inhibitors
.
Adv Enzyme Regul
1984
;
22
:
27
55
.
27.
Chou
T-C
,
Talalay
P
. 
Analysis of combined drug effects: a new look at a very old problem
.
Trends Pharmacol Sci
1983
;
4
:
450
4
.
28.
Ferreira
T
,
Rasband
W
. 
ImageJ user guide; 2012
.
Available from
: http://imagej.nih.gov/ij/docs/guide
29.
Connolly
DC
,
Hensley
HH
. 
Xenograft and transgenic mouse models of epithelial ovarian cancer and non-invasive imaging modalities to monitor ovarian tumor growth in situ: applications in evaluating novel therapeutic agents
.
Curr Protoc Pharmacol
2009
;
Chapter 14:Unit 14.12
.
30.
Do
TV
,
Xiao
F
,
Bickel
LE
,
Klein-Szanto
AJ
,
Pathak
HB
,
Hua
X
, et al
Aurora kinase A mediates epithelial ovarian cancer cell migration and adhesion
.
Oncogene
. 
2013 Jan 21
. [Epub ahead of print].
31.
Connolly
DC
,
Bao
R
,
Nikitin
AY
,
Stephens
KC
,
Poole
TW
,
Hua
X
, et al
Female mice chimeric for expression of the SV40 TAg under control of the MISIIR promoter develop epithelial ovarian cancer
.
Cancer Res
2003
;
63
:
1389
97
.
32.
Connolly
DC
. 
Animal models of ovarian cancer
.
Cancer Treat Res
2009
;
149
:
353
91
.
33.
Hensley
H
,
Quinn
BA
,
Wolf
RL
,
Litwin
SL
,
Mabuchi
S
,
Williams
SJ
, et al
Magnetic resonance imaging for detection and determination of tumor volume in a genetically engineered mouse model of ovarian cancer
.
Cancer Biol Ther
2007
;
6
:
1717
25
.
34.
Iadevaia
S
,
Lu
Y
,
Morales
FC
,
Mills
GB
,
Ram
PT
. 
Identification of optimal drug combinations targeting cellular networks: integrating phospho-proteomics and computational network analysis
.
Cancer Res
2010
;
70
:
6704
14
.
35.
Tibes
R
,
Qiu
Y
,
Lu
Y
,
Hennessy
B
,
Andreeff
M
,
Mills
GB
, et al
Reverse phase protein array: validation of a novel proteomic technology and utility for analysis of primary leukemia specimens and hematopoietic stem cells
.
Mol Cancer Ther
2006
;
5
:
2512
21
.
36.
Bandyopadhyay
S
,
Kelley
R
,
Krogan
NJ
,
Ideker
T
. 
Functional maps of protein complexes from quantitative genetic interaction data
.
PLoS Comput Biol
2008
;
4
:
e1000065
.
37.
Zhong
W
,
Sternberg
PW
. 
Genome-wide prediction of C. elegans genetic interactions
.
Science
2006
;
311
:
1481
4
.
38.
Berns
EM
,
Klijn
JG
,
Henzen-Logmans
SC
,
Rodenburg
CJ
,
van der Burg
ME
,
Foekens
JA
. 
Receptors for hormones and growth factors and (onco)-gene amplification in human ovarian cancer
.
Int J Cancer
1992
;
52
:
218
24
.
39.
Han
LY
,
Landen
CN
,
Trevino
JG
,
Halder
J
,
Lin
YG
,
Kamat
AA
, et al
Antiangiogenic and antitumor effects of SRC inhibition in ovarian carcinoma
.
Cancer Res
2006
;
66
:
8633
9
.
40.
Henzen-Logmans
SC
,
Fieret
EJ
,
Berns
EM
,
van der Burg
ME
,
Klijn
JG
,
Foekens
JA
. 
Ki-67 staining in benign, borderline, malignant primary and metastatic ovarian tumors: correlation with steroid receptors, epidermal-growth-factor receptor and cathepsin D
.
Int J Cancer
1994
;
57
:
468
72
.
41.
Huang
M
,
Page
C
,
Reynolds
RK
,
Lin
J
. 
Constitutive activation of stat 3 oncogene product in human ovarian carcinoma cells
.
Gynecol Oncol
2000
;
79
:
67
73
.
42.
Ito
K
,
Sasano
H
,
Ozawa
N
,
Sato
S
,
Silverberg
SG
,
Yajima
A
. 
Immunolocalization of epidermal growth factor receptor and c-erbB-2 oncogene product in human ovarian carcinoma
.
Int J Gynecol Pathol
1992
;
11
:
253
7
.
43.
Nilsson
MB
,
Langley
RR
,
Fidler
IJ
. 
Interleukin-6, secreted by human ovarian carcinoma cells, is a potent proangiogenic cytokine
.
Cancer Res
2005
;
65
:
10794
800
.
44.
Pengetnze
Y
,
Steed
M
,
Roby
KF
,
Terranova
PF
,
Taylor
CC
. 
Src tyrosine kinase promotes survival and resistance to chemotherapeutics in a mouse ovarian cancer cell line
.
Biochem Biophys Res Commun
2003
;
309
:
377
83
.
45.
Savarese
TM
,
Campbell
CL
,
McQuain
C
,
Mitchell
K
,
Guardiani
R
,
Quesenberry
PJ
, et al
Coexpression of oncostatin M and its receptors and evidence for STAT3 activation in human ovarian carcinomas
.
Cytokine
2002
;
17
:
324
34
.
46.
Silver
DL
,
Naora
H
,
Liu
J
,
Cheng
W
,
Montell
DJ
. 
Activated signal transducer and activator of transcription (STAT) 3: localization in focal adhesions and function in ovarian cancer cell motility
.
Cancer Res
2004
;
64
:
3550
8
.
47.
van Dam
PA
,
Vergote
IB
,
Lowe
DG
,
Watson
JV
,
van Damme
P
,
van der Auwera
JC
, et al
Expression of c-erbB-2, c-myc, and c-ras oncoproteins, insulin-like growth factor receptor I, and epidermal growth factor receptor in ovarian carcinoma
.
J Clin Pathol
1994
;
47
:
914
9
.
48.
Wang
DP
,
Konishi
I
,
Koshiyama
M
,
Nanbu
Y
,
Iwai
T
,
Nonogaki
H
, et al
Immunohistochemical localization of c-erbB-2 protein and epidermal growth factor receptor in normal surface epithelium, surface inclusion cysts, and common epithelial tumours of the ovary
.
Virchows Arch A Pathol Anat Histopathol
1992
;
421
:
393
400
.
49.
Vidal
CI
,
Mintz
PJ
,
Lu
K
,
Ellis
LM
,
Manenti
L
,
Giavazzi
R
, et al
An HSP90-mimic peptide revealed by fingerprinting the pool of antibodies from ovarian cancer patients
.
Oncogene
2004
;
23
:
8859
67
.
50.
Elstrand
MB
,
Stavnes
HT
,
Trope
CG
,
Davidson
B
. 
Heat shock protein 90 is a putative therapeutic target in patients with recurrent advanced-stage ovarian carcinoma with serous effusions
.
Hum Pathol
2012
;
43
:
529
35
.
51.
Bagatell
R
,
Paine-Murrieta
GD
,
Taylor
CW
,
Pulcini
EJ
,
Akinaga
S
,
Benjamin
IJ
, et al
Induction of a heat shock factor 1-dependent stress response alters the cytotoxic activity of Hsp90-binding agents
.
Clin Cancer Res
2000
;
6
:
3312
8
.
52.
Gordon
AN
,
Finkler
N
,
Edwards
RP
,
Garcia
AA
,
Crozier
M
,
Irwin
DH
, et al
Efficacy and safety of erlotinib HCl, an epidermal growth factor receptor (HER1/EGFR) tyrosine kinase inhibitor, in patients with advanced ovarian carcinoma: results from a phase II multicenter study
.
Int J Gynecol Cancer
2005
;
15
:
785
92
.
53.
Chou
TC
. 
Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies
.
Pharmacol Rev
2006
;
58
:
621
81
.
54.
Bookman
MA
. 
First-line chemotherapy in epithelial ovarian cancer
.
Clin Obstet Gynecol
2012
;
55
:
96
113
.
55.
McGuire
WP
,
Rowinsky
EK
,
Rosenshein
NB
,
Grumbine
FC
,
Ettinger
DS
,
Armstrong
DK
, et al
Taxol: a unique antineoplastic agent with significant activity in advanced ovarian epithelial neoplasms
.
Ann Intern Med
1989
;
111
:
273
9
.
56.
Young
RC
,
Von Hoff
DD
,
Gormley
P
,
Makuch
R
,
Cassidy
J
,
Howser
D
, et al
cis-Dichlorodiammineplatinum(II) for the treatment of advanced ovarian cancer
.
Cancer Treat Rep
1979
;
63
:
1539
44
.
57.
Modi
S
,
Stopeck
A
,
Linden
H
,
Solit
D
,
Chandarlapaty
S
,
Rosen
N
, et al
HSP90 inhibition is effective in breast cancer: a phase II trial of tanespimycin (17-AAG) plus trastuzumab in patients with HER2-positive metastatic breast cancer progressing on trastuzumab
.
Clin Cancer Res
2011
;
17
:
5132
9
.
58.
Richardson
PG
,
Chanan-Khan
AA
,
Lonial
S
,
Krishnan
AY
,
Carroll
MP
,
Alsina
M
, et al
Tanespimycin and bortezomib combination treatment in patients with relapsed or relapsed and refractory multiple myeloma: results of a phase 1/2 study
.
Br J Haematol
2011
;
153
:
729
40
.
59.
Sain
N
,
Krishnan
B
,
Ormerod
MG
,
De Rienzo
A
,
Liu
WM
,
Kaye
SB
, et al
Potentiation of paclitaxel activity by the HSP90 inhibitor 17-allylamino-17-demethoxygeldanamycin in human ovarian carcinoma cell lines with high levels of activated AKT
.
Mol Cancer Ther
2006
;
5
:
1197
208
.
60.
Jiao
Y
,
Ou
W
,
Meng
F
,
Zhou
H
,
Wang
A
. 
Targeting HSP90 in ovarian cancers with multiple receptor tyrosine kinase coactivation
.
Mol Cancer
2011
;
10
:
125
.
61.
Banerji
U
,
Walton
M
,
Raynaud
F
,
Grimshaw
R
,
Kelland
L
,
Valenti
M
, et al
Pharmacokinetic-pharmacodynamic relationships for the heat shock protein 90 molecular chaperone inhibitor 17-allylamino, 17-demethoxygeldanamycin in human ovarian cancer xenograft models
.
Clin Cancer Res
2005
;
11
:
7023
32
.
62.
Hendrickson
AE
,
Oberg
AL
,
Glaser
G
,
Camoriano
JK
,
Peethambaram
PP
,
Colon-Otero
G
, et al
A phase II study of gemcitabine in combination with tanespimycin in advanced epithelial ovarian and primary peritoneal carcinoma
.
Gynecol Oncol
2012
;
124
:
210
5
.
63.
Jhaveri
K
,
Miller
K
,
Rosen
L
,
Schneider
B
,
Chap
L
,
Hannah
A
, et al
A phase I dose-escalation trial of trastuzumab and alvespimycin hydrochloride (KOS-1022; 17 DMAG) in the treatment of advanced solid tumors
.
Clin Cancer Res
2012
;
18
:
5090
8
.
64.
Taldone
T
,
Sun
W
,
Chiosis
G
. 
Discovery and development of heat shock protein 90 inhibitors
.
Bioorg Med Chem
2009
;
17
:
2225
35
.
65.
Proia
DA
,
Foley
KP
,
Korbut
T
,
Sang
J
,
Smith
D
,
Bates
RC
, et al
Multifaceted intervention by the Hsp90 inhibitor ganetespib (STA-9090) in cancer cells with activated JAK/STAT signaling
.
PLoS ONE
2011
;
6
:
e18552
.
66.
Proia
DA
,
Sang
J
,
He
S
,
Smith
DL
,
Sequeira
M
,
Zhang
C
, et al
Synergistic activity of the Hsp90 inhibitor ganetespib with taxanes in non–small cell lung cancer models
.
Invest New Drugs
2012
;
30
:
2201
9
.
67.
Sang
J
,
Acquaviva
J
,
Friedland
JC
,
Smith
DL
,
Sequeira
M
,
Zhang
C
, et al
Targeted inhibition of the molecular chaperone Hsp90 overcomes ALK inhibitor resistance in non–small cell lung cancer
.
Cancer Discov
2013
;
3
:
430
43
.
68.
Wu
X
,
Marmarelis
ME
,
Hodi
FS
. 
Activity of the heat shock protein 90 inhibitor ganetespib in melanoma
.
PLoS ONE
2013
;
8
:
e56134
.
69.
Gritsko
TM
,
Coppola
D
,
Paciga
JE
,
Yang
L
,
Sun
M
,
Shelley
SA
, et al
Activation and overexpression of centrosome kinase BTAK/Aurora-A in human ovarian cancer
.
Clin Cancer Res
2003
;
9
:
1420
6
.
70.
Hsu
LC
,
Kapali
M
,
DeLoia
JA
,
Gallion
HH
. 
Centrosome abnormalities in ovarian cancer
.
Int J Cancer
2005
;
113
:
746
51
.
71.
Landen
CN
 Jr
,
Lin
YG
,
Immaneni
A
,
Deavers
MT
,
Merritt
WM
,
Spannuth
WA
, et al
Overexpression of the centrosomal protein Aurora-A kinase is associated with poor prognosis in epithelial ovarian cancer patients
.
Clin Cancer Res
2007
;
13
:
4098
104
.
72.
Thigpen
JT
,
Blessing
JA
,
Ball
H
,
Hummel
SJ
,
Barrett
RJ
. 
Phase II trial of paclitaxel in patients with progressive ovarian carcinoma after platinum-based chemotherapy: a Gynecologic Oncology Group study
.
J Clin Oncol
1994
;
12
:
1748
53
.

Supplementary data