Here, we investigate the potential role of the PARP inhibitor rucaparib (CO-338, formerly known as AG014699 and PF-01367338) for the treatment of sporadic ovarian cancer. We studied the growth inhibitory effects of rucaparib in a panel of 39 ovarian cancer cell lines that were each characterized for mutation and methylation status of BRCA1/2, baseline gene expression signatures, copy number variations of selected genes, PTEN status, and sensitivity to platinum-based chemotherapy. To study interactions with chemotherapy, we used multiple drug effect analyses and assessed apoptosis, DNA fragmentation, and γH2AX formation. Concentration-dependent antiproliferative effects of rucaparib were seen in 26 of 39 (67%) cell lines and were not restricted to cell lines with BRCA1/2 mutations. Low expression of other genes involved in homologous repair (e.g., BCCIP, BRCC3, ATM, RAD51L1), amplification of AURKA or EMSY, and response to platinum-based chemotherapy was associated with sensitivity to rucaparib. Drug interactions with rucaparib were synergistic for topotecan, synergistic, or additive for carboplatin, doxorubicin or paclitaxel, and additive for gemcitabine. Synergy was most pronounced when rucaparib was combined with topotecan, which resulted in enhanced apoptosis, DNA fragmentation, and γH2AX formation. Importantly, rucaparib potentiated chemotherapy independent of its activity as a single agent. PARP inhibition may be a useful therapeutic strategy for a wider range of ovarian cancers bearing deficiencies in the homologous recombination pathway other than just BRCA1/2 mutations. These results support further clinical evaluation of rucaparib either as a single agent or as an adjunct to chemotherapy for the treatment of sporadic ovarian cancer. Mol Cancer Ther; 12(6); 1002–15. ©2013 AACR.

Ovarian cancer is the second most common gynecologic malignancy in the United States (1). Despite radical surgery and initial high response rates to platinum- and taxane-based chemotherapy, most patients experience a relapse, with a median progression-free survival of only 18 months (2). Thus, advances in the understanding of the molecular pathogenesis of ovarian cancer coupled with the development of novel-targeted therapies are needed to improve outcomes. Patients with ovarian cancer with germline mutations in either BRCA1 or BRCA2 genes exhibit impaired ability to repair DNA double-strand breaks (DSB) via homologous recombination, and show a heightened sensitivity to inhibitors of a second DNA repair pathway, the base excision repair (BER) pathway (3). PARP is a nuclear protein that senses and binds to DNA single-strand breaks (SSB) and subsequently activates the BER pathway by recruiting additional repair factors (4). When PARP is inhibited, persistent SSBs become DNA DSB during DNA synthesis via collapsed replication forks (5, 6). To repair DSBs, the cell preferentially uses homologous recombination, which is usually considered error proof. If the cell cannot initiate homologous recombination, as is the case with BRCA1/2-mutant tumors, it resorts to more error-prone pathways, such as nonhomologous end joining or single-strand annealing, which can cause gross chromosomal mutations, growth inhibition, and eventual cell death (3).

Clinical studies have confirmed the activity of PARP inhibitors in patients with ovarian cancer with germline BRCA1/2 mutations (7, 8). However, recent clinical data indicate that a subset of patients with sporadic ovarian cancer (with wild-type BRCA1/2) may also respond to PARP inhibition, suggesting that BRCA1/2 mutations may not be the sole predictors of response (8, 9). These clinical findings clearly support the hypothesis that PARP inhibitors may also be effective in ovarian cancers bearing other deficiencies in homologous recombination, which may occur in a high proportion of sporadic epithelial ovarian cancer cases (10). In this context, compromised activity of ATM or other proteins involved in homologous recombination (11), overexpression of AURKA (12), or loss of PTEN function (13), has been described to lead to enhanced sensitivity to PARP inhibitors. Furthermore, it has been proposed that amplification of EMSY, which is capable of silencing BRCA2, may also lead to enhanced sensitivity to PARP inhibitors (14). However, the role of these markers in predicting response to PARP inhibitors remains controversial and preclinical studies are limited (15, 16).

Rucaparib (CO-338, formerly known as AG014699 and PF-01367338) is a highly selective inhibitor of PARP1 and PARP2 proteins (with an inhibition constant of <5 nmol/L), which has recently shown oral bioavailability (17). An earlier report shows antiproliferative activity of rucaparib in breast and pancreas cancer cell lines as well as an immortalized ovarian surface epithelial cell line each harboring either methylation or mutations of BRCA1/2 (18). Here, we show that rucaparib may also be useful for the treatment of sporadic ovarian cancer lacking BRCA1/2 silencing through methylation or mutations. Moreover, rucaparib was able to potentiate the cytotoxicity of DNA-damaging chemotherapeutic agents independent of its activity as single agent. To show this, we tested the in vitro effects of rucaparib against a panel of 39 ovarian cancer cell lines, representing all histologic subtypes of the disease. We then sought to validate known and identify novel response markers. For this purpose, cell lines were characterized for BRCA1/2 promoter methylation and mutational status. Other potential response predictors such as those known to be directly implicated in DNA repair, but also PTEN, AURKA, and EMSY were studied using gene expression profiling, Western blot analysis, and array comparative genomic hybridization (CGH). Cells were also characterized for their sensitivity to platinum-based chemotherapy. Multiple drug effect/combination index isobologram analysis was conducted to study drug interactions between rucaparib and chemotherapeutic agents commonly used for the treatment of ovarian cancer. This was done both using cell lines that were either sensitive or resistant to single-agent rucaparib. To better understand observed synergies, we finally studied the effect of rucaparib on chemotherapy-induced apoptosis, DNA fragmentation, and γH2AX formation.

Cell lines, cell culture, and reagents

The effects of rucaparib and chemotherapeutics on growth inhibition were studied in a panel of 39 established human ovarian cancer cell lines. Individuality of each cell line was checked by mitochondrial DNA sequencing once obtained from the source. Cell lines were passaged for less than 3 months after authentication. The cell lines were obtained from American Type Culture Collection (CAOV3, ES-2, OV90, OVCAR3, TOV112D, TOV21G), the European Collection of Cell Cultures (A2780, OAW28, OAW42), the German Tissue Repository, DSMZ (COLO704, EFO21, EFO27), Dr. Viji Shridhar, Mayo Clinic, (Rochester, MN; DOV13, HEYC2, OV167, OV177, OV207, OVCAR5), Dr. David T. Curiel, University of Alabama at Birmingham [Birmingham, AL (HEY)], Dr. Hiroaki Itamochi, Department of Obstetrics and Gynecology, Tottori University School of Medicine (Tottori, Japan; KK and KOC-7c), Dr. Beth Karlan, Cedars Sinai (Los Angeles, CA; OV2008, OVCA420, OVCA429, OVCA432, SKOV3), the Japanese Health Science Research Resources Bank, (Osaka, Japan; KURAMOCHI, MCAS, OVISE, OVKATE, OVMANA, OVSAHO, OVTOKO, RMG1, RMUGS, TYK-nu), and Dr. Simon P. Langdon, Edinburgh Cancer Research Center, University of Edinburgh (Edinburgh, United Kingdom; PE014, PEA2, PEO6). Detailed information on culture media and reagents is provided in the Supplementary Materials and Methods (Supplemental Table S1).

Growth inhibition assay

Cells were plated into 24-well tissue culture plates at a density of 5 to 20 × 103 and grown with or without increasing concentrations of rucaparib (ranging between 10 μmol/L and 0.005 μmol/L). Cells were counted on day 1 and 6 using a Coulter Z2 particle counter (Beckman Coulter Inc.). Growth inhibition was calculated as a function of the number of generations inhibited in the presence of rucaparib versus the number of generations over the same time course in the absence of the drug. To study the inhibition of anchorage-independent growth, soft agar assays were conducted. A 0.5% agar solution (Difco Agar Noble, BD) was placed on the bottom of a 24-well plate. Cells were seeded in quadruplicates of 5 × 103 and mixed into the 0.3% agar top layer that had been prepared with or without 1 μmol/L rucaparib. Culture plates were stored at 37°C, 5% CO2 for up to 5 weeks. Colonies were stained with Neutral Red solution (Sigma-Aldrich). All assays were conducted at least 3 times in duplicate for each cell line.

BRCA1/2 Sequencing

Sanger sequencing was used to screen the entire BRCA1/2 gene for mutations. The coding region of BRCA1 and BRCA2 were amplified by PCR. The pairs of primer sequences used have been reported previously (19). Sequencing was carried out as previously described by Beckman Coulter Genomics (20). Mutation surveyor software (SoftGenetics) was used to visually analyze sequencing traces for mutations and all potential variants were confirmed by an independent PCR and sequencing reaction. In addition, all cell lines with initially detected BRCA1/2 variants were reordered from the original supplier and authenticated by short tandem repeat sequencing in addition to the preceding mitochondrial DNA sequencing. Mutations were then confirmed in these cell lines by an independent third PCR and sequencing reaction. Missense variants were analyzed for their functional significance using the 2 programs SIFT (21) and Polyphen (22). Accession number used for BRCA1 is NM_007294.3 and for BRCA2 is NM_000059.3.

Bisulfite PCR and pyrosequencing

BRCA1 and BRCA2 promoter methylation was measured by bisulfite PCR and pyrosequencing. Assays are described in detail in the Supplementary Materials and Methods. CpG islands examined are shown in Supplementary Fig. S1.

Gene expression profiling of ovarian cell lines

Microarray hybridisations of 39 ovarian cell lines were conducted using the Agilent Human genome 44K array chip, as described previously (23). The original data are available online with the Gene Expression Omnibus accession number GSE26805.

DNA Isolation and array CGH

Genomic DNA was extracted from frozen cells using the DNeasy Blood and Tissue Kit (Qiagen). Labeling, hybridisation, and analysis of Agilent 105K oligonucleotide CGH arrays were conducted according to the manufacturer's protocol (Human Genome CGH 105A Oligo Microarray Kit, version 5.0, Agilent Technologies) and have been described previously (24). Log2 ratios more than 1 were considered to be amplified (2-fold increase).

Mutational analysis of PTEN

The relevant exons of the PTEN gene in each cell line were PCR amplified, sequenced, and assessed for potential sequence alterations using approaches previously described (20). The nucleotide sequences were analyzed using the Mutation Surveyor program (Soft Genetics LLC) and through visual inspection. All somatic mutations were confirmed by independent PCR and sequencing reactions.

Western blot analysis

Western blot analysis for PTEN was conducted as previously described (25). PTEN expression was detected, using a monoclonal anti-PTEN antibody (PTEN 7974; Santa Cruz Biotechnology).

Multiple drug effect analysis

Multiple drug effect analysis using rucaparib in combination with carboplatin, doxorubicin, topotecan, paclitaxel, and gemcitabine was conducted as described previously (26). Combination index values were derived from variables of the median effect plots, and statistical tests were applied to determine whether the mean combination index values at multiple effect levels (IC20–IC80) were significantly different from combination index = 1. In this analysis, synergy is defined as combination index values significantly lower than 1.0, antagonism as combination index values significantly higher than 1.0, and additivity as combination index values equal to 1.0.

Annexin V and propidium iodide flow cytometry

Effects of rucaparib on apoptosis were conducted using an Annexin V-FITC Apoptosis Detection Kit (MBL) and flow cytometry. Cells were exposed to 5 μmol/L of rucaparib alone or in combination with 10 nmol/L topotecan. After 3 days, samples were analyzed using the Cell Lab Quanta SC flow cytometer (Beckman Coulter Inc.).

Single-cell gel electrophoresis (comet assay)

To detect single- and double-strand DNA breaks in cell lines exposed to rucaparib alone or in combination with topotecan a comet assay was conducted in accordance to the manufacturer's instructions (Trevigen). In brief, control and treated cells were mixed with LMagarose and spread on to comet slides. The comet slides were immersed in the lysis solution and incubated for 60 minutes at 4°C. Following lysis the slides were immersed in freshly prepared alkaline buffer for 60 minutes in the dark. Electrophoresis was conducted at a set voltage (21V for 30 minutes), dehydrated in 70% ethanol, and stained with DNA-bound SYBR Green I fluorescence stain. For visualization of DNA damage images were captured using a confocal microscope at 494/521 nm wavelength.

Immunofluorescence and confocal microcopy

HEY, MCAS, and MDA-MB436 (BRCA1 deficient breast cancer cell line) were seeded on sterile cover slips in 12-well plates and treated with 3μmol/L rucaparib or 30 nmol/L topotecan or the combination of both. After 24 hours, cells were washed with PBS, fixed with 4% paraformaldehyde for 20 minutes, and permeabilized with 70% ethanol for 5 minutes at −20°C. Cells were stained with the primary antibody against Rad51 (H-92, Santa Cruz Biotechnology) or γH2AX (Ser139, Cell Signaling) and incubated for 1 hour with the secondary antibody Alexa 488 or Alexa 594 (Invitrogen) for Rad51 or γH2AX, respectively. After washing with PBS, a drop of Prolong Gold antifade reagent with 4,6-diamidino-2-phenylindole Invitrogen) was applied for counterstaining. Images from random fields were taken using a Nikon Eclipse E 800 microscope with an attached camera and using Spot Software from Diagnostic Instruments (Diagnostic Instruments).

Statistical analysis

Associations between biomarkers and in vitro sensitivity were analyzed using Spearman rho correlation, and a bootstrapping procedure was implemented to improve statistical robustness. In addition a Resolver system ANOVA was conducted on the ovarian cancer cell lines classified by response to rucaparib across a DNA repair gene set of 683 sequences on the Agilent Whole Human Genome platform classified as “DNA damage and repair.” We used a statistical value for sequences of 1.75 change in at least 3 experiments and a P < 0.05. Differences between subgroups were compared using the Student t test, χ2 test, and Mann–Whitney U test. To analyze which chemotherapeutic agent was potentiated the most by rucaparib and at which chemotherapy concentration the greatest effect was seen, a multivariate ANOVA model was conducted. Interaction terms were included to model differences between cell lines, chemotherapeutic agents, and specific drug concentrations. All reported P values are 2 sided, and statistical significance was reached at P values less than 0.05.

Activity of rucaparib in ovarian cancer cells

The in vitro effects of rucaparib on human ovarian cancer cells were evaluated using a panel of 39 established human ovarian cancer cell lines. These cells lines were selected to be representative of a range of histologic ovarian cancer subtypes (Table 1). The effective dose range (IC20–IC80) was identified using a wide range of rucaparib concentrations (10–0.005 μmol/L). The IC50 values varied significantly between individual cell lines and ranged from 2.5 μmol/L for COLO704 to more than 15 μmol/L in 13 of the 39 investigated cell lines (Table 1 and Fig. 1). There was no statistically significant correlation between the histologic subtype and sensitivity to rucaparib (data not shown). Next, we studied the effect of rucaparib on anchorage-independent growth using soft agar assays. Of the 39 tested cell lines, 22 ovarian cancer cell lines formed colonies in soft agar (Supplementary Fig. S2). The inhibition of colony formation varied significantly between individual cell lines when treated with 1 μmol/L rucaparib and ranged between 80% in sensitive lines and no growth inhibition in resistant cell lines. Importantly, the observed response toward rucaparib in the 3-dimensional soft agar experiments correlated well with that seen in the 2-dimensional anchorage-dependent growth assay (accuracy 82%, P = 0.009).

Figure 1.

The log of the fractional growth inhibition was plotted against the log of the drug concentration and the IC50 values were interpolated from the resulting linear regression curve fit and actual IC50 values are reported up to a concentration of 15 μmol/L. Cell lines are ordered left to right according to increasing IC50 values. Error bars indicate the SE of the mean value. Mean is derived from at least 3 replicate experiments. Colored bars denote cell lines with BRCA2 (orange) and BRCA1 (blue) gene variations. A BRCA2 nonsense mutation was identified in the ovarian cancer cell line KURAMOCHI. Two BRCA1 missense mutations were found in the human ovarian cancer cell line KOC-7c. BRCA2 missense mutations were found in the human ovarian cancer cell lines MCAS, OVCA420, and OVMANA.

Figure 1.

The log of the fractional growth inhibition was plotted against the log of the drug concentration and the IC50 values were interpolated from the resulting linear regression curve fit and actual IC50 values are reported up to a concentration of 15 μmol/L. Cell lines are ordered left to right according to increasing IC50 values. Error bars indicate the SE of the mean value. Mean is derived from at least 3 replicate experiments. Colored bars denote cell lines with BRCA2 (orange) and BRCA1 (blue) gene variations. A BRCA2 nonsense mutation was identified in the ovarian cancer cell line KURAMOCHI. Two BRCA1 missense mutations were found in the human ovarian cancer cell line KOC-7c. BRCA2 missense mutations were found in the human ovarian cancer cell lines MCAS, OVCA420, and OVMANA.

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Table 1.

IC50 values for rucaparib and carboplatin and cell line characteristics

Cell linePF-01367338 IC50 μmol/L ± SDHistologyPTEN MutationsPTEN Expression (% of BT474)AURKA AmplificationEMSY AmplificationCarboplatin IC50 μmol/L ± SEa
COLO704 2.52 ± 0.67 Undifferentiated Yes   1.18 ± 0.19 
OVMANAb 2.58 ± 0.38 Clear cell  29 1.16  0.40 ± 0.10 
OV177 2.78 ± 0.71 Serous  25 1.15 1.08 0.74 ± 0.16 
OAW28 3.61 ± 0.28 Serous  19   0.49 ± 0.11 
OVSAHO 3.64 ± 0.33 Serous  97 1.50  0.60 ± 0.09 
OVKATE 3.64 ± 1.79 Serous  42   4.34 ± 0.63 
OVCAR3 3.74 ± 0.40 Serous  45  2.62 0.45 ± 0.06 
PEO14 3.84 ± 0.76 Serous  38   0.74 ± 0.20 
A2780 3.94 ± 0.25 Undifferentiated Yes 15   2.02 ± 0.13 
OVTOKO 4.14 ± 1.53 Clear cell  44  1.09 2.64 ± 0.72 
KURAMOCHIb 4.34 ± 0.29 Undifferentiated  66 1.08  0.76 ± 0.10 
TOV21G 5.07 ± 1.30 Clear cell Yes   0.26 ± 0.09 
OVISE 5.68 ± 0.23 Clear cell  18   1.51 ± 0.41 
KK 6.15 ± 1.42 Clear cell  77   1.20 ± 0.17 
RMUGS 7.03 ± 1.83 Mucinous  56   2.40 ± 0.01 
PEO6 7.06 ± 0.74 Serous  46   3.96 ± 0.40 
OVCA429 8.29 ± 1.64 Clear cell  12   >10 
OV167 8.33 ± 1.18 Serous  34  1.05 1.55 ± 0.23 
RMG1 9.32 ± 2.36 Clear cell  17   >10 
OVCAR5 9.50 ± 2.59 Undifferentiated  30   2.62 ± 0.15 
EFO21 9.92 ± 1.87 Serous  15   3.04 ± 0.18 
ES2 10.12 ± 1.23 Clear cell  34   >10 
Tyk-nu 10.20 ± 1.12 Undifferentiated  38   0.80 ± 0.08 
CAOV3 10.37 ± 0.87 Serous  31   3.05 ± 0.17 
OV207 12.27 ± 0.32 Clear cell  50   3.36 ± 0.04 
HEY 13.01 ± 0.75 Serous  93   >10 
DOV13 >15 Serous  68   >10 
EFO27 >15 Mucinous   3.70 ± 0.65 
HEY C2 >15 Serous  59   >10 
KOC-7cc >15 Clear cell   >10 
MCASb >15 Mucinous  43   4.41 ± 0.31 
OAW42 >15 Serous  34 1.37  1.42 ± 0.37 
OV2008 >15 Endometrioid  14 1.03  1.81 ± 0.01 
OV90 >15 Serous  77   1.32 ± 0.21 
OVCA420b >15 Serous  30   >10 
OVCA432 >15 Serous  15   1.34 ± 0.14 
PEA2 >15 Serous  67   4.57 ± 0.31 
SKOV3 >15 Serous  45   >10 
TOV112D >15 Endometrioid  56   3.22 ± 0.36 
Cell linePF-01367338 IC50 μmol/L ± SDHistologyPTEN MutationsPTEN Expression (% of BT474)AURKA AmplificationEMSY AmplificationCarboplatin IC50 μmol/L ± SEa
COLO704 2.52 ± 0.67 Undifferentiated Yes   1.18 ± 0.19 
OVMANAb 2.58 ± 0.38 Clear cell  29 1.16  0.40 ± 0.10 
OV177 2.78 ± 0.71 Serous  25 1.15 1.08 0.74 ± 0.16 
OAW28 3.61 ± 0.28 Serous  19   0.49 ± 0.11 
OVSAHO 3.64 ± 0.33 Serous  97 1.50  0.60 ± 0.09 
OVKATE 3.64 ± 1.79 Serous  42   4.34 ± 0.63 
OVCAR3 3.74 ± 0.40 Serous  45  2.62 0.45 ± 0.06 
PEO14 3.84 ± 0.76 Serous  38   0.74 ± 0.20 
A2780 3.94 ± 0.25 Undifferentiated Yes 15   2.02 ± 0.13 
OVTOKO 4.14 ± 1.53 Clear cell  44  1.09 2.64 ± 0.72 
KURAMOCHIb 4.34 ± 0.29 Undifferentiated  66 1.08  0.76 ± 0.10 
TOV21G 5.07 ± 1.30 Clear cell Yes   0.26 ± 0.09 
OVISE 5.68 ± 0.23 Clear cell  18   1.51 ± 0.41 
KK 6.15 ± 1.42 Clear cell  77   1.20 ± 0.17 
RMUGS 7.03 ± 1.83 Mucinous  56   2.40 ± 0.01 
PEO6 7.06 ± 0.74 Serous  46   3.96 ± 0.40 
OVCA429 8.29 ± 1.64 Clear cell  12   >10 
OV167 8.33 ± 1.18 Serous  34  1.05 1.55 ± 0.23 
RMG1 9.32 ± 2.36 Clear cell  17   >10 
OVCAR5 9.50 ± 2.59 Undifferentiated  30   2.62 ± 0.15 
EFO21 9.92 ± 1.87 Serous  15   3.04 ± 0.18 
ES2 10.12 ± 1.23 Clear cell  34   >10 
Tyk-nu 10.20 ± 1.12 Undifferentiated  38   0.80 ± 0.08 
CAOV3 10.37 ± 0.87 Serous  31   3.05 ± 0.17 
OV207 12.27 ± 0.32 Clear cell  50   3.36 ± 0.04 
HEY 13.01 ± 0.75 Serous  93   >10 
DOV13 >15 Serous  68   >10 
EFO27 >15 Mucinous   3.70 ± 0.65 
HEY C2 >15 Serous  59   >10 
KOC-7cc >15 Clear cell   >10 
MCASb >15 Mucinous  43   4.41 ± 0.31 
OAW42 >15 Serous  34 1.37  1.42 ± 0.37 
OV2008 >15 Endometrioid  14 1.03  1.81 ± 0.01 
OV90 >15 Serous  77   1.32 ± 0.21 
OVCA420b >15 Serous  30   >10 
OVCA432 >15 Serous  15   1.34 ± 0.14 
PEA2 >15 Serous  67   4.57 ± 0.31 
SKOV3 >15 Serous  45   >10 
TOV112D >15 Endometrioid  56   3.22 ± 0.36 

aSensitivity to carboplatin was significantly correlated with sensitivity to rucaparib, r = 0.61, P < 0.001.

bBRCA2 variant; PTEN mutations: COLO704 (89682884C>T:130R>X), A2780 (89682879_89682887delAGGGACGAA), TOV21G (89682921het_delG 89707755het_delA+), EFO27 (89707755delA), KOC-7c (89707652C>CT:233R>R/X, 89710792het_delA). Gene copies are reported as log2 ratios. Log2 ratios more than 1 were considered to be amplified (2-fold increase).

cBRCA1 variant.

BRCA1 and 2 mutation status and sensitivity to rucaparib

Preclinical and clinical evidence indicates that ovarian cancer cells with BRCA1/2 mutations are sensitive toward PARP inhibitors (6, 7, 27). To better understand the predictive role of BRCA1/2 mutations in ovarian cancer, we sequenced the BRCA1 and BRCA2 genes in each of the 39 cell lines. Five ovarian cancer cell lines showed BRCA1/2 gene variations (Table 2). A deleterious BRCA2 nonsense mutation (c.6952C>T, p.R2318X) was identified in the cell line KURAMOCHI and 2 BRCA1 missense mutations were found in the cell line KOC-7c (c.39T>A, p.N13K and c.395A>C, p.N132T). Furthermore, BRCA2 missense mutations were found in the cell lines MCAS (c.964A>C, p.K322Q), OVCA420 (c.6131G>A,pG2044D), and OVMANA (c.2275C>G, p.L759V). Because it is difficult to interpret the functional significance of missense mutations, we further characterized the predicted functional significance of these using both prediction software programs SIFT and Polyphen (21, 22). The BRCA1 missense mutations in KOC-7c cells were predicted to be damaging by both programs. The BRCA2 variants in OVMANA and OVCA420 cells were deemed to be benign using both the programs, and the third variant (c.964A>C, p.K322Q) in MCAS cells was considered to be damaging by SIFT and benign by Polyphen. In summary, of the 2 human ovarian cancer cell lines with deleterious BRCA1/2 mutations, one line was sensitive (KURAMOCHI, IC50 <5 μmol/L) and one was resistant (KOC-7c, IC50 >15 μmol/L) to treatment with single-agent rucaparib. These findings confirm the clinically observed activity of PARP inhibitors in hereditary ovarian cancer caused by germline mutations in BRCA1/2, but also suggest that the presence of a mutation may not suffice to ensure activity of a PARP inhibitor. Most importantly, however, these correlative studies clearly indicate that multiple cell lines with wild-type BRCA1/2 showed in vitro sensitivity comparable with that seen in the BRCA2-mutated KURAMOCHI cell line (Fig. 1).

Table 2.

BRCA1 and BRCA2 mutations detected in the present panel of 39 established human ovarian cancer cell lines

Cell lineIC50 (μmol/L)GeneNucleotide (genomic)Nucleotide (cDNA)Amino acidMutation typeSIFTPolyphenReported in BIC
OVMANA 2.58 ± 0.38 BRCA2 chr13:32910767 C>G NM_000059.3 c.2275C>G p.L759V Missense Tolerated Benign No 
KURAMOCHI 4.34 ± 0.29 BRCA2 chr13:32920978 C>T NM_000059.3 c.6952C>T p.R2318X Nonsense − − Yes (5x; mainly in Asians) rs80358920 (dbSNP) 
KOC-7C >15 BRCA1 chr17:41276075 T>A NM_007294.3 c.39T>A p.N13K Missense Damaging (low confidence) Damaging No 
   chr17:41256185 A>C NM_007294.3 c.395A>C p.N132T Missense Damaging (low confidence) Damaging No 
MCAS >15 BRCA2 chr13:32906579 A>C NM_000059.3 c.964A>C p.K322Q Missense Damaging (low confidence) Benign Yes (11x; mainly in Asians) rs11571640 (dbSNP) 
OVCA420 >15 BRCA2 chr13:32914623 G>A NM_000059.3 c.6131G>A p.G2044D Missense Tolerated Benign No 
Cell lineIC50 (μmol/L)GeneNucleotide (genomic)Nucleotide (cDNA)Amino acidMutation typeSIFTPolyphenReported in BIC
OVMANA 2.58 ± 0.38 BRCA2 chr13:32910767 C>G NM_000059.3 c.2275C>G p.L759V Missense Tolerated Benign No 
KURAMOCHI 4.34 ± 0.29 BRCA2 chr13:32920978 C>T NM_000059.3 c.6952C>T p.R2318X Nonsense − − Yes (5x; mainly in Asians) rs80358920 (dbSNP) 
KOC-7C >15 BRCA1 chr17:41276075 T>A NM_007294.3 c.39T>A p.N13K Missense Damaging (low confidence) Damaging No 
   chr17:41256185 A>C NM_007294.3 c.395A>C p.N132T Missense Damaging (low confidence) Damaging No 
MCAS >15 BRCA2 chr13:32906579 A>C NM_000059.3 c.964A>C p.K322Q Missense Damaging (low confidence) Benign Yes (11x; mainly in Asians) rs11571640 (dbSNP) 
OVCA420 >15 BRCA2 chr13:32914623 G>A NM_000059.3 c.6131G>A p.G2044D Missense Tolerated Benign No 

NOTE: The clinical significance of these mutations was assessed through a search in the Breast Cancer Information Core (http://research.nhgri.nih.gov/projects/bic). Nucleotide position based on (GRCh37/hg19) Assembly, BRCA1 – NM_007294.3, BRCA2 – NM_000059.3.

Abbreviation: BIC, Breast Cancer Information Core.

BRCA1 and BRCA2 promoter methylation status and rucaparib response

A recent study found the breast cancer cell line UACC3199, which shows epigenetic silencing of BRCA1, to be sensitive to rucaparib (18). To elucidate whether BRCA1/2 promoter methylation would be associated with response to rucaparib in human ovarian cancer cell lines, we sought to quantify BRCA1 and BRCA2 CpG island methylation in each of the cell lines. This was done by bisulfite pyrosequencing of CpG sites relevant to transcription control (Supplementary Fig. S1). Importantly, we did not find high-level methylation of BRCA1 or BRCA2 promoter regions in any of the 39 examined ovarian cancer cell lines. The highest average methylation level of 10 CpG islands in the BRCA1 promoter region was seen in the RMG1 cell line (average 18%, maximum 34% in CpG7). The highest average methylation level of 7 CpG islands in the BRCA2 promoter region was seen in OVISE cells (average 17%, maximum 31% in CpG7; data not shown).

Expression of DNA repair genes and sensitivity to rucaparib

Preclinical and preliminary clinical evidence suggests that loss of other proteins involved in DNA DSB repair other than BRCA1/2 may be associated with sensitivity to PARP inhibition (8, 9, 11). Gene expression profiles for the cell line panel were generated using the Agilent 44K chips. A correlation analysis between gene expression levels and rucaparib in vitro sensitivity was restricted to 683 genes involved in DNA damage and repair, as defined by the Gene Ontology Annotation database (http://www.ebi.ac.uk/goa). Of these, 71 genes were significantly correlated with the IC50 values for rucaparib (P < 0.05; Table 3). As such, cell lines with low expression of ATM, RAD51L1, RAD50, MSH5, or MLH1 showed lower IC50 values when compared with cell lines with higher gene expression (ATM, r = 0.42, P = 0.009; RAD51L1, r = 0.38, P = 0.018; RAD50, r = 0.320, P = 0.049; MSH5, r = 0.349, P = 0.032; and MLH1, r = 0.325, P = 0.046; Table 3 and Supplementary Fig. S3). In addition, low expression of BCCIP (BRCA2- and CDKN1A-interacting protein) or BRCA1–BRCA2-containing complex, subunit 3 (BRCC3) was significantly correlated with sensitivity toward rucaparib (r = 0.47, P = 0.003, r = 0.34, P = 0,036), respectively. By conducting ANOVA classified by response to rucaparib (sensitive cell lines, IC50 < 10 μmol/L; resistant cell lines, IC50 > 10 μmol/L) across the 683 genes involved in DNA damage and repair, a set of 57 differentially-expressed genes was identified confirming the significance of the majority of the response predictors that had been initially identified using a Spearman correlation (Table 3).

Table 3.

Spearman rho correlation and ANOVA between in vitro growth inhibition (IC50) following rucaparib treatment and the relative expression of genes implicated in gene repair mechanisms in the ovarian cancer cell line panel

SpearmannSpearmannANOVA
NameSymbolProbe numberRPP
Mitochondrial ribosomal protein S11 MRPS11 A_24_P913666 0.67 <0.001a <0.001 
Alkylation repair homolog 8 ALKBH8 A_23_P371876 0.58 <0.001a 0.002 
General transcription factor IIH, polypeptide 1 GTF2H1 A_23_P36183 0.57 <0.001a 0.006 
Apoptosis antagonizing transcription factor AATF A_24_P262395 0.53 0.001a 0.003 
Interferon, γ-inducible protein 16 IFI16 A_23_P217866 0.52 0.001a 0.017 
Inhibitor of kappa light polypeptide gene enhancer in B cells, kinase γ IKBKG A_23_P159920 0.47 0.003a 0.003 
BRCA2 and CDKN1A interacting protein BCCIP A_24_P30206 0.47 0.003a <0.001 
TAF9 RNA polymerase II TAF9 A_23_P41604 0.46 0.003 0.006 
Polymerase (DNA directed), γ POLG A_23_P3355 0.46 0.004a 0.002 
BRCA1/BRCA2-containing complex, subunit 3 BRCC3 A_24_P144504 0.46 0.004 0.018 
Chromosome 9 open reading frame 102 C9orf102 A_23_P323488 0.46 0.004a 0.029 
STE20-like kinase SLK A_24_P146670 0.44 0.006a 0.007 
Casein kinase 1 CSNK1E A_23_P40664 0.44 0.006a 0.004 
Non-SMC element 1 homolog NSMCE1 A_23_P95823 0.44 0.006a 0.008 
Sterile alpha motif and leucine zipper containing kinase AZK ZAK A_23_P318300 0.43 0.007a 0.009 
Unknown Unknown A_24_P902091 0.43 0.008  
Ligase IV LIG4 A_24_P415845 0.42 0.009a 0.003 
Ataxia telangiectasia mutated ATM A_23_P374812 0.42 0.009 0.004 
CDC14 cell division cycle 14 homolog B CDC14B A_23_P20622 0.40 0.012a  
General transcription factor IIH, polypeptide 5 GTF2H5 A_24_P196117 0.40 0.014a 0.045 
SP100 nuclear antigen SP100 A_23_P209712 0.40 0.014  
V-yes-1 Yamaguchi sarcoma viral related oncogene homolog LYN A_23_P147431 0.39 0.015a  
SMG1 homolog SMG1 A_32_P142881 0.39 0.017 0.026 
X-linked inhibitor of apoptosis XIAP A_23_P22460 0.38 0.017 0.022 
RAD51-like 1 RAD51L1 A_23_P48481 0.38 0.018a 0.015 
Protein phosphatase 2, regulatory subunit B', γ PPP2R5C A_23_P205236 0.38 0.020a 0.025 
Senataxin SETX A_24_P95273 0.37 0.023a  
Unknown Unknown A_24_P922182 0.37 0.023 0.026 
Homeodomain interacting protein kinase 2 HIPK2 A_24_P500621 0.37 0.024a  
Protein phosphatase 1, regulatory (inhibitor) subunit 15A PPP1R15A A_23_P90172 0.37 0.024 0.015 
Fizzy/cell division cycle 20 related 1 FZR1 A_24_P944291 0.36 0.026  
Xeroderma pigmentosum, complementation group A XPA A_23_P60283 0.36 0.026  
Malignant T-cell amplified sequence 1 MCTS1 A_23_P114282 0.36 0.027a 0.047 
Structural maintenance of chromosomes 5 SMC5 A_32_P126609 0.36 0.028a 0.013 
REV1 homolog REV1 A_24_P256325 0.36 0.029  
MutS homolog 3 MSH3 A_23_P122001 0.35 0.030 0.036 
MutS homolog 5 MSH5 A_24_P3804 0.35 0.032a  
SNF2 histone linker PHD RING helicase SHPRH A_24_P153576 0.35 0.032  
Caspase 3 CASP3 A_23_P92410 0.35 0.033  
Gene homolog 1 GEN1 A_24_P177585 0.35 0.033a 0.042 
Cullin 4B CUL4B A_23_P422178 0.34 0.034a 0.023 
F-box protein 31 FBXO31 A_23_P395566 0.34 0.036  
Calcium and integrin binding 1 CIB1 A_24_P44514 0.34 0.036a  
Cyclin H CCNH A_23_P30338 0.34 0.038 0.011 
Ubiquitin-specific peptidase 10 USP10 A_32_P26330 0.34 0.038  
Ubiquitin-specific peptidase 3 USP3 A_32_P3602 0.34 0.038  
Abelson murine leukemia viral oncogene homolog 1 ABL1 A_24_P393711 0.34 0.040a  
Tumor protein p63 TP63 A_24_P273756 0.34 0.040a  
Tyrosyl-DNA phosphodiesterase 2 TTRAP A_23_P8311 0.33 0.041a  
Polymerase (DNA directed), γ POLK A_23_P386450 0.33 0.045a 0.041 
MutL homolog 1, colon cancer, nonpolyposis type 2 MLH1 A_23_P69058 0.33 0.046a  
Mortality factor 4 like 1 MORF4L1 A_23_P37579 0.32 0.048  
RAD50 homolog RAD50 A_23_P250404 0.32 0.049  
      
Uracil-DNA glycosylase UNG A_24_P398585 −0.32 0.049a 0.026 
Eyes absent homolog 2 EYA2 A_23_P319859 −0.32 0.048a  
RAD21 homolog RAD21 A_23_P20463 −0.32 0.047a  
Eyes absent homolog 1 EYA1 A_23_P502363 −0.33 0.042a  
Growth arrest and DNA damage inducible, γ GADD45G A_24_P120934 −0.34 0.038a 0.025 
MUS81 endonuclease homolog MUS81 A_24_P412238 −0.34 0.036a 0.028 
Multiple endocrine neoplasia I MEN1 A_23_P75453 −0.37 0.023a  
Protein arginine meth PRMT6 A_23_P12336 −0.39 0.017a 0.021 
Timeless homolog TIMELESS A_23_P53276 −0.39 0.016a  
APEX nuclease 1 APEX1 A_23_P151653 −0.39 0.016a  
RAD9 homolog RAD9A A_24_P21715 −0.39 0.014a 0.004 
MutS homolog 2, colon cancer, nonpolyposis type 1 MSH2 A_23_P102471 −0.41 0.010a 0.033 
8-oxoguanine DNA glycosylase OGG1 A_24_P414183 −0.43 0.007a 0.017 
Chromosome 19 open reading frame 62 C19orf62 A_23_P119714 −0.43 0.007a  
Dual specificity tyrosine-(Y)-phosphorylation-regulated kinase 2 DYRK2 A_23_P204048 −0.46 0.005a 0.005 
Cryptochrome 2 CRY2 A_23_P127394 −0.46 0.004a 0.003 
Tetratricopeptide repeat domain 5 TTC5 A_23_P88280 −0.48 0.002a 0.025 
BTG family, member 2 BTG2 A_23_P62901 −0.49 0.002a 0.001 
SpearmannSpearmannANOVA
NameSymbolProbe numberRPP
Mitochondrial ribosomal protein S11 MRPS11 A_24_P913666 0.67 <0.001a <0.001 
Alkylation repair homolog 8 ALKBH8 A_23_P371876 0.58 <0.001a 0.002 
General transcription factor IIH, polypeptide 1 GTF2H1 A_23_P36183 0.57 <0.001a 0.006 
Apoptosis antagonizing transcription factor AATF A_24_P262395 0.53 0.001a 0.003 
Interferon, γ-inducible protein 16 IFI16 A_23_P217866 0.52 0.001a 0.017 
Inhibitor of kappa light polypeptide gene enhancer in B cells, kinase γ IKBKG A_23_P159920 0.47 0.003a 0.003 
BRCA2 and CDKN1A interacting protein BCCIP A_24_P30206 0.47 0.003a <0.001 
TAF9 RNA polymerase II TAF9 A_23_P41604 0.46 0.003 0.006 
Polymerase (DNA directed), γ POLG A_23_P3355 0.46 0.004a 0.002 
BRCA1/BRCA2-containing complex, subunit 3 BRCC3 A_24_P144504 0.46 0.004 0.018 
Chromosome 9 open reading frame 102 C9orf102 A_23_P323488 0.46 0.004a 0.029 
STE20-like kinase SLK A_24_P146670 0.44 0.006a 0.007 
Casein kinase 1 CSNK1E A_23_P40664 0.44 0.006a 0.004 
Non-SMC element 1 homolog NSMCE1 A_23_P95823 0.44 0.006a 0.008 
Sterile alpha motif and leucine zipper containing kinase AZK ZAK A_23_P318300 0.43 0.007a 0.009 
Unknown Unknown A_24_P902091 0.43 0.008  
Ligase IV LIG4 A_24_P415845 0.42 0.009a 0.003 
Ataxia telangiectasia mutated ATM A_23_P374812 0.42 0.009 0.004 
CDC14 cell division cycle 14 homolog B CDC14B A_23_P20622 0.40 0.012a  
General transcription factor IIH, polypeptide 5 GTF2H5 A_24_P196117 0.40 0.014a 0.045 
SP100 nuclear antigen SP100 A_23_P209712 0.40 0.014  
V-yes-1 Yamaguchi sarcoma viral related oncogene homolog LYN A_23_P147431 0.39 0.015a  
SMG1 homolog SMG1 A_32_P142881 0.39 0.017 0.026 
X-linked inhibitor of apoptosis XIAP A_23_P22460 0.38 0.017 0.022 
RAD51-like 1 RAD51L1 A_23_P48481 0.38 0.018a 0.015 
Protein phosphatase 2, regulatory subunit B', γ PPP2R5C A_23_P205236 0.38 0.020a 0.025 
Senataxin SETX A_24_P95273 0.37 0.023a  
Unknown Unknown A_24_P922182 0.37 0.023 0.026 
Homeodomain interacting protein kinase 2 HIPK2 A_24_P500621 0.37 0.024a  
Protein phosphatase 1, regulatory (inhibitor) subunit 15A PPP1R15A A_23_P90172 0.37 0.024 0.015 
Fizzy/cell division cycle 20 related 1 FZR1 A_24_P944291 0.36 0.026  
Xeroderma pigmentosum, complementation group A XPA A_23_P60283 0.36 0.026  
Malignant T-cell amplified sequence 1 MCTS1 A_23_P114282 0.36 0.027a 0.047 
Structural maintenance of chromosomes 5 SMC5 A_32_P126609 0.36 0.028a 0.013 
REV1 homolog REV1 A_24_P256325 0.36 0.029  
MutS homolog 3 MSH3 A_23_P122001 0.35 0.030 0.036 
MutS homolog 5 MSH5 A_24_P3804 0.35 0.032a  
SNF2 histone linker PHD RING helicase SHPRH A_24_P153576 0.35 0.032  
Caspase 3 CASP3 A_23_P92410 0.35 0.033  
Gene homolog 1 GEN1 A_24_P177585 0.35 0.033a 0.042 
Cullin 4B CUL4B A_23_P422178 0.34 0.034a 0.023 
F-box protein 31 FBXO31 A_23_P395566 0.34 0.036  
Calcium and integrin binding 1 CIB1 A_24_P44514 0.34 0.036a  
Cyclin H CCNH A_23_P30338 0.34 0.038 0.011 
Ubiquitin-specific peptidase 10 USP10 A_32_P26330 0.34 0.038  
Ubiquitin-specific peptidase 3 USP3 A_32_P3602 0.34 0.038  
Abelson murine leukemia viral oncogene homolog 1 ABL1 A_24_P393711 0.34 0.040a  
Tumor protein p63 TP63 A_24_P273756 0.34 0.040a  
Tyrosyl-DNA phosphodiesterase 2 TTRAP A_23_P8311 0.33 0.041a  
Polymerase (DNA directed), γ POLK A_23_P386450 0.33 0.045a 0.041 
MutL homolog 1, colon cancer, nonpolyposis type 2 MLH1 A_23_P69058 0.33 0.046a  
Mortality factor 4 like 1 MORF4L1 A_23_P37579 0.32 0.048  
RAD50 homolog RAD50 A_23_P250404 0.32 0.049  
      
Uracil-DNA glycosylase UNG A_24_P398585 −0.32 0.049a 0.026 
Eyes absent homolog 2 EYA2 A_23_P319859 −0.32 0.048a  
RAD21 homolog RAD21 A_23_P20463 −0.32 0.047a  
Eyes absent homolog 1 EYA1 A_23_P502363 −0.33 0.042a  
Growth arrest and DNA damage inducible, γ GADD45G A_24_P120934 −0.34 0.038a 0.025 
MUS81 endonuclease homolog MUS81 A_24_P412238 −0.34 0.036a 0.028 
Multiple endocrine neoplasia I MEN1 A_23_P75453 −0.37 0.023a  
Protein arginine meth PRMT6 A_23_P12336 −0.39 0.017a 0.021 
Timeless homolog TIMELESS A_23_P53276 −0.39 0.016a  
APEX nuclease 1 APEX1 A_23_P151653 −0.39 0.016a  
RAD9 homolog RAD9A A_24_P21715 −0.39 0.014a 0.004 
MutS homolog 2, colon cancer, nonpolyposis type 1 MSH2 A_23_P102471 −0.41 0.010a 0.033 
8-oxoguanine DNA glycosylase OGG1 A_24_P414183 −0.43 0.007a 0.017 
Chromosome 19 open reading frame 62 C19orf62 A_23_P119714 −0.43 0.007a  
Dual specificity tyrosine-(Y)-phosphorylation-regulated kinase 2 DYRK2 A_23_P204048 −0.46 0.005a 0.005 
Cryptochrome 2 CRY2 A_23_P127394 −0.46 0.004a 0.003 
Tetratricopeptide repeat domain 5 TTC5 A_23_P88280 −0.48 0.002a 0.025 
BTG family, member 2 BTG2 A_23_P62901 −0.49 0.002a 0.001 

NOTE: For the confirmatory ANOVA analysis, genes were classified by response to rucaparib (sensitive cell lines, IC50 < 10 μmol/L; resistant cell lines, IC50>10 μmol/L). Shading denotes the genes that are inversely correlated (negative correlation) to the IC50 values. The results of the Spearman rho correlation were validated by a bootstrapping technique.

aSignificance has been validated by bootstrapping technique.

Next, we sought to study additional biomarkers that have previously been suggested to predict response to PARP inhibitors. Amplification of AURKA was associated with low IC50 values (IC50 < 5μmol/L, χ2 test, P = 0.023; Table 1). Similarly, amplification of EMSY was associated with low IC50 values (IC50 < 5 μmol/L, χ2 test, P = 0.023; Table 1). PTEN mutations were found in 5 of 39 ovarian cancer cell lines, and each was associated with low-protein expression. However, PTEN mutations were not statistically significantly associated with low IC50 values (IC50 < 5 μmol/L, χ2 test, P = 0.530; IC50 < 10 μmol/L, χ2 test, P = 0.768; Table 1).

Correlations with platinum and olaparib sensitivity

Recent clinical data in recurrent ovarian cancer suggest that patients with platinum-sensitive recurrent sporadic ovarian cancer may particularly benefit from single-agent PARP inhibitor treatment or maintenance therapy (8, 9). To validate whether preclinical platinum sensitivity is associated with response to rucaparib, we determined the IC50 concentrations for carboplatin in each cell line. Statistical analysis comparing the growth-inhibitory effects of rucaparib (IC50s) with the growth-inhibitory effects of carboplatin reveals a statistically significant positive correlation between in vitro sensitivity to rucaparib and carboplatin (r = 0.61, P < 0.001; Table 1) confirming that the assessment of platinum sensitivity in ovarian cancer may be a clinically useful enrichment strategy for selection of patients most likely to respond to PARP inhibitor therapy (8, 9). A recent chemical compound profiling study using differential scanning fluorimetry showed that the 2 PARP inhibitors rucaparib and olaparib have comparable binding selectivity for the catalytic domains of PARP 1, 2, 3, and 4 (28). In vitro rucaparib and olaparib showed comparable efficacy across the present ovarian cancer cell line panel [mean IC50 (range) for rucaparib was 9.4 μmol/L (2.5 >15 μmol/L) and for olaparib was 10.4 μmol/L (1.2 >15 μmol/L), r = 0.68, P < 0.001].

Drug interactions between rucaparib and chemotherapeutic agents

Multiple drug effect analyses were conducted to determine the nature of interactions between rucaparib and 5 chemotherapeutic agents most commonly used for the treatment of ovarian cancer: carboplatin, paclitaxel, doxorubicin, topotecan, and gemcitabine (Supplementary Fig. S4). These studies were conducted using 5 ovarian cancer cell lines with varying degrees of sensitivity toward single-agent rucaparib with IC50 values ranging between 3.9 μmol/L in A2780 and more than 15 μmol/L in MCAS or OV2008 cells. Synergistic interactions were observed when rucaparib was combined with topotecan in all of the 5 cell lines examined [mean combination index values ranged between 0.53 [95% confidence interval (CI), 0.36–0.70, P < 0.001] and 0.72 (95% CI, 0.59–0.85, P < 0.001); Fig. 2A]. Importantly, synergistic drug interactions with topotecan were seen in rucaparib-sensitive cells (A2780, KK) but also in cell lines that were less (HEY) or not sensitive to single-agent rucaparib (MCAS and OV2008; Fig. 2B). Synergistic interactions were also observed when rucaparib was combined with doxorubicin in 4 of 5 lines [mean combination index values ranged between 0.69 (95% CI, 0.56–0.82, P < 0.001) and 0.82 (95% CI, 0.49–1.15, P = 0.500); Fig. 2A]. Synergistic and additive interactions were observed when rucaparib was combined with carboplatin [mean combination index values ranged between 0.45 (95% CI, 0.22–0.68, P = 0.001) and 1.07 (95% CI, 0.94–1.20, P = 0.240)] and paclitaxel [mean combination index values ranged between 0.73 (95% CI, 0.59–0.85, P < 0.001) and 1.00 (95% CI, 0.65–1.35, P = 0.980)]. In contrast, additive interactions were observed when rucaparib was combined with gemcitabine in each of the 5 lines examined [mean combination index values ranged between 0.98 (95% CI, 0.81–1.15, P = 0.820) and 1.22 (95% CI, 0.95–1.49, P = 0.104); Fig. 2A]. By using a multivariate ANOVA model (accounting for type of chemotherapy, cell line, and drug concentration as single factors), we analyzed the benefit of adding rucaparib to chemotherapy in more detail. Using this multivariate approach, we were able to show that the drug interactions differed significantly between individual chemotherapeutic agents (P = 0.010). When adding rucaparib to chemotherapy, the benefit was most pronounced for topotecan, less so for doxorubicin or carboplatin, and the least for paclitaxel or gemcitabine (Supplementary Fig. S5). Moreover, when combining rucaparib with topotecan, synergistic interactions were observed across the entire concentration range (IC20–IC80). Importantly, however, the largest increase in rucaparib-induced enhanced growth inhibition was seen at lower topotecan concentrations (P = 0.018; Supplementary Fig. S6). We believe this is an important observation as data from a recent clinical trial show that due to an enhanced myelosuppression dose reductions are necessary in the clinical setting when combining topotecan with the PARP inhibitor olaparib (29). Nonetheless, these preclinical data suggest that significant antitumor activity may still be achievable despite a clinically necessary reduction in the dose of chemotherapy.

Figure 2.

A, mean combination index values for chemotherapeutic drug–rucaparib combinations in 5 different established human ovarian cancer cell lines. Error bars indicate the 95% confidence interval of the mean value derived from 3 replicates spanning clinically relevant concentration ranges sufficient to inhibit growth of control cells by 20 to 80%. Combination index values that are statistically significantly less than 1 indicate synergistic interactions. Values that are statistically significantly more than 1 indicate antagonistic interactions. Values equal to (or not statistically significantly different from) 1 indicate additive interactions. B, dose–response curves show the effect of rucaparib (dashed line), topotecan (squares), or the combination of both (triangles). Synergistic drug interactions with topotecan were seen in rucaparib-sensitive cells (A2780, KK) but also in those lines that were less sensitive to single-agent rucaparib (HEY, MCAS, and OV2008), suggesting that rucaparib potentiates chemotherapy independent of its activity as a single agent.

Figure 2.

A, mean combination index values for chemotherapeutic drug–rucaparib combinations in 5 different established human ovarian cancer cell lines. Error bars indicate the 95% confidence interval of the mean value derived from 3 replicates spanning clinically relevant concentration ranges sufficient to inhibit growth of control cells by 20 to 80%. Combination index values that are statistically significantly less than 1 indicate synergistic interactions. Values that are statistically significantly more than 1 indicate antagonistic interactions. Values equal to (or not statistically significantly different from) 1 indicate additive interactions. B, dose–response curves show the effect of rucaparib (dashed line), topotecan (squares), or the combination of both (triangles). Synergistic drug interactions with topotecan were seen in rucaparib-sensitive cells (A2780, KK) but also in those lines that were less sensitive to single-agent rucaparib (HEY, MCAS, and OV2008), suggesting that rucaparib potentiates chemotherapy independent of its activity as a single agent.

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Effects of rucaparib and topotecan on survival, DNA fragmentation and formation of γH2AX and RAD51 foci

Synergistic drug interactions were not restricted to rucaparib-sensitive ovarian cancer cell lines but were also seen in cell lines considered to be less sensitive or resistant to single-agent rucaparib such as HEY (IC50 > 10 μmol/L) and MCAS (IC50 > 15μmol/LM) cells. To better understand these synergistic interactions observed in lines with low sensitivity or even resistance toward rucaparib as single agent, we compared the effects of rucaparib, topotecan, and the combination of both on apoptosis, DNA fragmentation, and the formation of DNA DSBs using the HEY and MCAS cells known to be resistant to PARP inhibition as a single agent. Rucaparib alone did not induce apoptosis in these cell lines. However, adding rucaparib to topotecan did lead to an increase in the fraction of cells undergoing apoptosis when compared with treatment with topotecan alone (Fig. 3A). Next, we conducted single-cell gel electrophoresis to study DNA fragmentation, which can be visualized by the size of a cell's comet tail in the depicted fluorescent electrophoresis image (Fig. 3B). Rucaparib alone only mildly increased DNA fragmentation, however, adding rucaparib to topotecan drastically increased DNA fragmentation when compared with topotecan alone (Fig. 3B). Subsequently, we investigated the effects of rucaparib and topotecan on the formation of DNA DSBs by staining for γH2AX formation, which accumulates and becomes phosphorylated at sites of broken DNA DSBs, and for RAD51 expression, which aids in DNA DSB repair and serves as a marker of the cells ability to repair DNA DSBs. Importantly, γH2AX foci formation, a marker of DNA DSBs, only slightly increased following treatment with rucaparib alone, and markedly increased following treatment with topotecan alone. Nonetheless, γH2AX foci formation seemed to be most pronounced when both drugs were combined (Fig. 4). In summary, despite a relative insensitivity of HEY and MCAS ovarian cancer cells to single-agent rucaparib, treatment with the respective PARP inhibitor did seem to enhance topotecan-induced apoptosis, DNA fragmentation, and γH2AX formation. These results are consistent with the observed synergy between rucaparib and topotecan in HEY and MCAS cells and support the premise that PARP inhibitors may potentiate the cytotoxicity of DNA-damaging agents independent of their activity as a single agent.

Figure 3.

A, detection of apoptotic subpopulations was achieved by labeling phosphatidylserine residues of the cell surface with Annexin V-FITC and staining cells with propidium iodide. Cells were incubated with 5 μmol/L of rucaparib or 10 nmol/L topotecan or the combination of both for 3 days. Error bars indicate the SE of the mean value. B, representative results of single-cell gel electrophoresis (comet-assay) of MCAS and HEY cells. DNA fragmentation is depicted by the size of a cell's comet tail.

Figure 3.

A, detection of apoptotic subpopulations was achieved by labeling phosphatidylserine residues of the cell surface with Annexin V-FITC and staining cells with propidium iodide. Cells were incubated with 5 μmol/L of rucaparib or 10 nmol/L topotecan or the combination of both for 3 days. Error bars indicate the SE of the mean value. B, representative results of single-cell gel electrophoresis (comet-assay) of MCAS and HEY cells. DNA fragmentation is depicted by the size of a cell's comet tail.

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Figure 4.

Immunflourescence of yH2AX and RAD51 focus formation in MCAS and HEY cell lines. BRCA1-deficient MDA-MB436 breast cancer cells were used as controls. Cells were treated for 24 hours with 3 μmol/L rucaparib, 30 nmol/L topotecan, or with a combination of both agents.

Figure 4.

Immunflourescence of yH2AX and RAD51 focus formation in MCAS and HEY cell lines. BRCA1-deficient MDA-MB436 breast cancer cells were used as controls. Cells were treated for 24 hours with 3 μmol/L rucaparib, 30 nmol/L topotecan, or with a combination of both agents.

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Clinical proof-of-principal synthetic lethality with PARP inhibitors has been shown in hereditary ovarian cancer caused by germline mutations in BRCA1/2 (7). However, the potential of these drugs for the treatment of ovarian cancer beyond BRCA mutation carriers has yet to be defined. Results of 2 recent clinical studies suggest that patients with recurrent ovarian cancer without BRCA1/2 germline mutations may benefit from treatment with a single-agent PARP inhibitor (8, 9). Consistent, with these clinical observations, we found activity of the potent PARP inhibitor rucaparib not to be restricted to ovarian cancer cells harboring BRCA1/2 mutations. These findings may be explained by the results of a recently published comprehensive molecular characterization of high-grade serous papillary ovarian cancer, which identified multiple aberrations in genes involved in DNA DSB repair in addition to those seen in BRCA1/2 (10). Of 316 patients with high-grade serous papillary ovarian cancer, 154 (49%) had aberrations in genes that may affect homologous recombination. Although 20% of the patients had germline or somatic BRCA1/2 mutations, an additional 11%, 6%, and 5% of the patients had epigenetic silencing of BRCA1, amplification of EMSY, or loss of PTEN expression, respectively. Moreover, an additional 7% of the patients had mutations in RAD51C, ATM, ATR, or Fanconi anemia genes (10). It is, however, currently not clear whether these aberrations all lead to a decrease in homologous recombination sufficient enough to cause sensitization of tumor cells toward PARP inhibitors. Indeed, the results of our preclinical studies support the hypothesis that some of these aberrations may be synthetically lethal when combined with PARP inhibition. In line with earlier studies, we are able to confirm that low expression of ATM or RAD50 as well as amplification of AURKA are associated with in vitro sensitivity to PARP inhibition (11, 12, 30). Moreover, we also show, that among other genes low expression of RAD51L, BCCIP (cofactor for BRCA2), and BRCC3 as well as MSH5 or MLH1 were significantly associated with PARP inhibitor sensitivity. Although deficiency of BRCC3 or BCCIP has not been associated with PARP inhibitor response so far, it is likely to be the case due to their important function in homologous recombination (31, 32). EMSY maps to the 11q13-q14 region, is commonly amplified in ovarian cancer, and has been identified as a BRCA2-binding partner (14). It has been proposed that EMSY plays a role in homologous recombination-mediated repair of DNA DSBs; however, this has been a controversial issue. Our results confirm a significant association between amplification of EMSY and sensitivity to rucaparib and support the hypothesis that EMSY amplification may be a mechanism of BRCA2 pathway inactivation in sporadic ovarian cancers. Recent studies have shown a distinct role for PTEN in the maintenance of chromosomal integrity and repair of DNA DSBs (33). Although it has been reported that loss of PTEN sensitizes cancer cell lines to PARP inhibitors, our preclinical results do not confirm these findings (13, 34). PTEN mutations were not statistically significantly associated with in vitro sensitivity to rucaparib using the current cell line panel of 39 established human ovarian cancer cell lines. Earlier preclinical studies suggest that epigenetic silencing of the BRCA1 promoter region in the UACC3199 breast cancer cell line may be associated with sensitivity to rucaparib (18). In the current ovarian cancer cell line panel, however, we were not able to detect methylation of BRCA1/2 promoter regions. This seems to contrast clinical studies where epigenetic silencing of BRCA1 has been described to occur in approximately 10% of serous papillary ovarian cancers (10). Nevertheless, our findings do mirror earlier preclinical studies using breast cancer models, which similar to our study did not find BRCA1/2 methylation in a panel of 21 established breast cancer cell lines (35). Taken together, both of these studies suggest that BRCA1/2 promoter methylation is rarely found in established breast or ovarian cancer cell lines.

Recent clinical data indicate that patients with platinum-sensitive recurrent sporadic ovarian cancer may benefit from single-agent PARP inhibitor therapy (8, 9). In one of these studies, objective responses were seen in 10 of 20 (50%) patients with platinum-sensitive recurrent sporadic ovarian cancer, as opposed to only in 1 of 26 (4%) patients with platinum-resistant recurrent ovarian cancer (8). This association is supported by our findings, which show a statistically significant positive correlation between sensitivity to carboplatin and sensitivity to rucaparib.

It has been proposed that PARP inhibitors can potentiate the cytotoxicity of DNA-damaging agents by preventing DNA repair (36, 37). Here, we show that drug interactions with rucaparib were synergistic for topotecan, carboplatin, or doxorubicin in ovarian cancer cells both sensitive and resistant to single-agent rucaparib. As such, despite a relative insensitivity of HEY, MCAS, or OV2008 ovarian cancer cells to single-agent rucaparib, treatment with rucaparib did potentiate chemotherapy. Data from our group as well as others (36, 37) suggest that even in the presence of a functional homologous recombination pathway and a cell's ability to conduct DNA DSB repair, the homologous recombination pathway may only be able to repair part of the additional damage introduced by PARP inhibition in homologous recombination proficient cells treated with a DNA-damaging agent, but not all and thus result in enhanced cytotoxicity. Synergy was most pronounced when rucaparib was combined with topotecan, which resulted in an increase in apoptosis, DNA fragmentation, and yH2AX formation. The effect of topo-I inhibition is the induction of DNA SSBs (38), which are primarily repaired by the PARP-dependent BER pathway. In addition, it has been suggested that PARP inhibitors can enhance topo-I activity, which could sensitize cells to topoisomerase I poisons (39). The combination of topotecan with the PARP inhibitor olaparib has recently been tested in a clinical phase I study in patients with advanced solid tumors (29). This trial showed enhanced topotecan-induced myelosuppression when combined with olaparib. Of note, our data also indicate that the most pronounced synergy was seen at low topotecan drug concentrations in vitro, which may imply that efficacy can be maintained even if a dose reduction of topotecan is required (29). Taken together, the present studies suggest that rucaparib sensitivity is not restricted to ovarian cancer with BRCA1/2 mutations and, furthermore, confirms the notion that PARP inhibitors may be able to potentiate cytotoxic treatment independent of their activity as single agent. These findings support further clinical evaluation of rucaparib either as single agent or as adjunct to chemotherapy in the treatment of sporadic ovarian cancer.

S. Jones is employed as a scientist in Personal Genome Diagnostics and has ownership interest (including patents) in stock options in PGDX. V.E. Velculescu is on the board of directors and is CSO of Personal Genome Diagnostics, has ownership interest (including patents) in Personal Genome Diagnostics and Inostics, and is a consultant/advisory board member of Inostics. D.J. Slamon has a honoraria from speakers' bureau from Genentech, Sanofi-Aventis, and GlaxoSmithKline, has ownership interest (including patents) in Amgen, and is a consultant/advisory board member of Novartis Pharmaceuticals. No potential conflicts of interest were disclosed by the other authors.

Conception and design: M. Ihnen, F. Janicke, G. Los, D.J. Slamon, G.E. Konecny

Development of methodology: J. Qi, M. Chalukya, C. Ginther, V.E Velculescu, D.J. Slamon, G.E. Konecny

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): M. Ihnen, T. Kolarova, J. Qi, K. Manivong, L. Anderson, C. Ginther, A. Meuter, B. Winterhoff, S. Jones, V.E Velculescu, S. Dandekar, D.J. Slamon, G.E. Konecny

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): M. Ihnen, C. zu Eulenburg, T. Kolarova, J. Qi, K. Manivong, M. Chalukya, J. Dering, L. Anderson, S. Jones, N. Udar, D.J. Slamon, G.E. Konecny

Writing, review, and/or revision of the manuscript: M. Ihnen, C. zu Eulenburg, T. Kolarova, B. Winterhoff, S. Dandekar, N. Udar, F. Janicke, G. Los, D.J. Slamon, G.E. Konecny

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): M. Ihnen, J. Qi, M. Chalukya, S. Jones, N. Venkatesan, H.-M. Rong, D.J. Slamon, G.E. Konecny

Study supervision: M. Ihnen, G.E. Konecny

G.E. Konecny has been supported in part by the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, the Thelma L. Culverson Endowed Cancer Research Fund, and the Stranahan Foundation for Translational Cancer Research and Advanced Clinical Cancer Research.

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.

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Supplementary data