Background
Each year in Canada and the United States, over 25,000 women are diagnosed with ovarian cancer [
1,
2]. Low-grade serous ovarian cancer (LGSC) accounts for 5–10% of these cancers [
3,
4], affecting approximately 2000 women per year. This rare form of ovarian cancer is often diagnosed in pre-menopausal women and frequently found in advanced stages. Although LGSC is considered to be a less aggressive subtype than other ovarian cancers, response rates to chemotherapy are low, ranging from 4 to 25% [
5]. Consequently, long-term fatality rates are high with only 10–20% of women surviving 10 years after diagnosis [
5,
6].
It is now recognized that LGSC has unique clinical, pathological, and molecular characteristics compared to other types of ovarian cancers, such as the high-grade serous ovarian carcinoma (HGSC) [
7,
8]. Molecular studies performed on LGSC tumors revealed that mutations in the
TP53 gene are rare (8% in LGSC versus 96% in HGSC) [
9,
10], and that expression of estrogen (ER) and progesterone (PR) receptors is frequently observed [
11,
12]. LGSC is also characterized by activation of the mitogen-activated protein kinase (MAPK) pathway. Mutations affecting this pathway are seen in
KRAS (20–40%),
NRAS (7–26%) and
BRAF (5–33%) genes [
13‐
20]. Evidence of MAPK pathway activation in LGSC [
21] led to a key clinical trial evaluating the efficacy of the MEK inhibitor (MEKi) selumetinib for the treatment of patients with advanced and/or recurrent LGSC (GOG-0239). The results from this trial, published in 2013, shown a 15% response rate and 65% disease stabilization [
22]. A second clinical trial of the MEKi binimetinib (MILO trial, NCT01849874) was closed at the interim analysis in 2016, because it did not show the anticipated predefined benefits on progression-free survival (PFS). Despite these unexpected results, durable responses to binimetinib were observed in LGSC with MAPK pathway alterations [
23]. Currently, an international randomized phase II/III clinical trial using the MEKi trametinib is ongoing (NCT02101788) and a translational research component to better understand the molecular mechanisms of MEKi efficacy is included.
To date, preclinical laboratory research in LGSC has been limited to tumor tissues. The low frequency and slow growth rate of these tumors have challenged the development of cell lines and animal xenograft models. In the past 5 years, our laboratory has successfully established a collection of patient-derived LGSC cell lines that are now available for pre-clinical drug testing. Previously, we evaluated the effects of four different MEKi (selumetinib, trametinib, binimetinib, refametinib) in eight advanced/recurrent LGSC cell lines. Our results indicated that there were substantial differences in cellular response and on-target drug efficacy between cell lines and drugs [
24]. Encouraged by promising results from MEKi clinical trials in a subset of LGSC patients, we sought to identify biomarkers that could predict response to treatment using LGSC cell lines, by comparing the proteogenomic profiles of MEKi-sensitive (MEKi-Se) and MEKi-resistant (MEKi-Re) LGSC cell lines, and subsequently evaluating the potential therapeutic value of two proteins (EGFR and PKC-alpha) associated with MEKi resistance.
Materials and methods
Tumor samples and clinical information
Advanced or recurrent LGSC samples (tumor and ascites) were obtained from the OvCaRe gynecologic tumor bank (Vancouver General Hospital/British Columbia Cancer Agency (BCCA), and the John and Mary Knight Translational Ovarian Cancer Research Unit (London Regional Cancer Program, London, Ontario, Canada). Tumor bank protocols, cell line derivation, and all research relating to this study was approved by institutional human ethics review boards at BCCA (H14-02859), the University of British Columbia (UBC; R05-0119), and the University of Western Ontario (HSREB 12668E). Clinical information was extracted retrospectively from patient records. Tumor histology was confirmed by a gynecological pathologist.
Patient-derived LGSC cell lines
Low-grade serous ovarian cancer patient-derived cell lines were established through continuous in vitro culture of patient material obtained through OvCaRe or the John and Mary Knight Translational Ovarian Cancer Research Unit (cell line iOvCa241) tumor banks. Cultures were established and maintained in M199:MCDB105 (1:1) media (Cat. No. M5017 and M6395, Sigma-Aldrich, Oakville, Ontario, Canada) supplemented with 10% defined fetal bovine serum (dFBS; Cat. No. SH30070.03, Hyclone, GE Life Sciences, Logan, UT, USA) maintained at 37 °C and 5% CO2. No immortalization methods were used. Doubling time of these cells ranged from 30 to 80 h, with an average of 47 h, reflecting the clinical slow growth rate of LGSC.
Sample authentication (cell line, tumor, buffy coat)
Microsatellite analysis of short tandem repeats (STRs) was performed on LGSC cell lines and corresponding tumor and buffy coat samples for cell line authentication. STR analyses of 10 loci were performed by Genewiz Inc. (South Plainfield, NJ) (Data available upon request). STR results confirm that all LGSC cell lines and buffy coat samples match to corresponding tumor samples.
Genome sequencing
Whole exome sequencing (WES): Agilent SureSelect RNA Library All Exons v6 protocol was performed by Beijing Genome Institute, per manufacturer’s guidelines. Quality and quantity of post-capture libraries were assessed using an Agilent 2100 Bioanalyzer. Libraries were sequenced on an Illumina Hiseq 4000 (PE 100).
Copy number variation (CNV) analysis: Data analysis was performed using Nexus Copy Number Discovery Edition Version 9.0 (BioDiscovery, Inc., El Segundo, CA). Samples were processed using the Nexus NGS functionality (BAM ngCGH) with the FASST2 segmentation. The log ratio thresholds for single copy gain and single copy loss were set at + 0.18 and − 0.18, respectively. The log ratio thresholds for gain of 2 or more copies and for a homozygous loss were set at + 0.6 and − 1.0, respectively. Tumor sample BAM files were processed with corresponding normal tissue BAM files. Probes were normalized to median.
Mutation analysis: Sequence alignment and mutation calling were performed in Partek Flow environment (© 2017 Partek Inc). Sequence reads were aligned to GRCh38/hg38 human genome build using bwa 0.7.2. Variants were called using Strelka 1.0.15 for all cell lines except for VOA-1312 (lacking buffy coat sample). VOA-1312 variant calling was performed using LoFreq 2.1.3.a. The called variants were annotated using the wAnnovar software (reference obtained from:
http://jmg.bmj.com/content/49/7/433.citation-tools). Annotated calls were then filtered to show only protein-changing SNVs that were present in cell line DNA at allele frequencies (AF) greater than 0.1 and coverage higher than 16×. For VOA-1312, all calls not present in dbSNP (version 138) were retained, while of the calls that were present in dbSNP, only calls with (average heterozygocity + aveHet standard error) < 0.1 were retained. These were additionally filtered using the same criteria as for the Strelka calls.
Whole genome sequencing (WGS): Genomic data from LGSC tumors T7 and T11 were obtained from the personalized oncogenomics (POG) program at the BCCA. Methodology has been previously described in detail [
25]. To summarize, genome and transcriptome libraries were sequenced on HiSeq instruments (Illumina, San Diego, California) using V3 or V4 chemistry and paired-end 150 or 125 base reads, respectively. Target depth was 80× coverage for the tumor genome and 40× for the normal genome.
Cell proliferation assays
Assessment of MEKi sensitivity using trametinib (GSK1120212; Sellekchem, Cat. No. S2673) and selumetinib (AZD6244; Cat. No. S1008), were performed as previously described [
24]. Cell proliferation was monitored using IncuCyte™ real-time imaging technology using a non-labeled monolayer confluence approach (Essen Biosciences, Ann Arbor, MI, USA). LGSC cell lines were plated at 15–20% confluence in 96-well plates. After 24 h, cells were treated once with DMSO (control) or differing drug concentrations [erlotinib alone (10 μM and 2.5 μM), in combination (10, 5, 2.5, 1.25, and 0.63 μM), high and low doses of MEKi treatment (1 μM and 0.5 μM selumetinib; 0.1 μM and 0.05 μM trametinib; doses for preclinical MEKi assays as previously published)] [
24]. Trametinib and selumetinib were selected as the MEKi for combination treatments. These two drugs are most commonly used clinically for treating LGSC, and binimetinib may lack efficacy based on results from the MILO clinical trial (NCT01849874). Drug doses of selumetinib and trametinib were chosen based on IC50 results from our previous experiments [
24]. Selected concentrations for these experiments are in keeping with steady state serum levels (selumetinib 2 μM and trametinib 30 nM) reported for these drugs in humans [
26,
27]. Phase contrast images of cells were taken every 6-h for 4–5 days. Each condition was evaluated using four technical replicates and experiments were repeated for verification. Data analysis was performed using IncuCyte™ software. Statistical analyses using the t-test on the final time point values of each assay were performed to compare treatment conditions. Differences were considered significant at a p-value < 0.05.
Cell viability assay
Cell viability was measured using MTS-Cell Titer 96R Aqueous Non-Radioactive Cell Proliferation Assay, following manufacturer recommendations (Cat. No. G5430, Promega, Madison, WI, USA) at endpoint of Incucyte™ proliferation assays. Treatment media was replaced with 100 μL of fresh media and 20 μL of MTS. Plates were incubated for 3.5 h at 37 °C in humidified 5% CO2. Absorbance at 490 nm was measured using a microplate reader (BioTek Epoch SN257811). Viability for each treatment was compared to DMSO treated cells. Wells were subsequently stained with crystal violet (CV) to determine residual cells after treatment. Statistical analysis using t-test were used to compare treatment conditions and differences were considered significant at a p-value < 0.05.
IC50 determination
Erlotinib (Cat. No. S7786) were purchased from Selleck Chemicals (Houston, TX, USA). Dimethylsulfoxide (DMSO; Sigma, Cat. No. D2650) was purchased from Sigma-Aldrich (Oakville, Ontario, Canada). Cells were seeded in 96-well plates at 40–50% confluence and treated after 24 h with DMSO or a range of drug concentrations. The inhibitory concentration (IC50, representing 50% of total cell viability) was determined using crystal violet staining after 72 h drug treatment.
Western blot analysis
Cell lysates were prepared according to previously published protocols [
24], then 20 μg samples were separated on an 8% SDS-PAGE gel, transferred to nitrocellulose membranes and probed with primary antibodies including ERK1/2 (Millipore, Cat. No. 06-182), p-MAPK (p-ERK1/2, Cell Signaling, Cat. No. 4376S), MEK1/2 (Cell Signaling, Cat. No. 9122), p-MEK1/2 (Cell Signaling, Cat. No. 9154), PKC-alpha (Cell Signaling, Cat. No. 2056), EGFR (Santa Cruz, Cat. No. 71032), p-EGFR (Cell Signaling, Cat. No. 2234), PARP (Cell Signaling, Cat. No. 9542), and c-PARP (Cell Signaling, Cat. No. 9541S). Vinculin (V9131, Sigma) was used as a protein loading control. Horseradish peroxidase (HRP)-conjugated secondary antibodies (goat-anti-mouse or goat-anti-rabbit, Sigma Cat. No. A9917 and A0545) were used accordingly. Western blots were imaged using Immobilon HRP reagent (Cat. No. WBKLS0500, Millipore, Etobicoke, ON, Canada) and developed by autoradiograph.
Reverse-phase protein array (RPPA) analysis
Reverse-phase protein array on whole tumor and cell line lysates was performed as previously described [
28,
29]. Proteomic profiles of 8 LGSC cell lines, 2 MEKi-sensitive (VOA-1312, iOvCa241) and 6 MEKi-resistant (VOA-1056, VOA-3993; VOA-3448, VOA-3723; VOA-4627, VOA-4698), were analyzed. LGSC cells were treated for 24 h with 1 μL/mL DMSO or MEKi (trametinib 0.1 μM, selumetinib 1.0 μM) in biological triplicate as previously described [
24,
30]. Antibodies (n = 91) against cell surface growth factor receptors, common signaling pathway proteins, steroid hormone receptors, and other proteins involved in proliferation and apoptosis were used (Additional file
1: Table S1). Data was analyzed using SPSS software (Version 20, Chicago, Illinois). Differentially expressed proteins between cell lines and treatment conditions were determined using the t-test [
31]. The Mann–Whitney U test was used for proteins with non-normally distributed expression levels. False discovery rates were not calculated as putative markers were validated by western blot.
shERWOOD-UltramiR shRNA lentiviral target gene set containing three PRKCA shRNA sequences and one non-target shRNA (Cat. No. TLHVU1401-5578) was purchased from transOMIC Technologies (Huntsville, AL). VOA-3723 and VOA-6406 were plated at 50% confluence in 6-well tissue culture dishes 24 h prior to lentiviral transduction. 199:105 media supplemented with 1% Hyclone dFBS and polybrene (2 µg/mL for VOA-3723, 0.5 µg/mL for VOA-6406) and lentivirus expressing non-targeting shRNA or PRKCA shRNA (multiplicity of infection [MOI] = 26 for VOA-3723, MOI = 1.5 for VOA-6406) in a total volume of 1.5 mL was added. After 24 h, cells were washed with PBS and complete media was added. Successful transduction was confirmed using confocal microscopy. After an additional 24-h recovery, transduced LGSC cells were selected and maintained using puromycin (1.0 µg/mL for VOA3723, 0.5 µg/mL for VOA6406).
Drug synergy analysis
Cell proliferation, viability and crystal violet results from in vitro drug testing (single drug and drug combinations) were used to assess drug synergism using CompuSyn software (
http://www.combosyn.com). This software is based on the median-effect principle and the combination index-isobologram theorem (Chou-Talalay) [
32]. Drug doses (D) and effects (fa) were entered (non-constant ratios) for single drug doses and combinations, and combination indices (CI) were generated. The CI values quantitatively defined synergism (CI < 1), additive effect (CI = 1), and antagonism (CI > 1).
Discussion
Activating mutations affecting the MAPK pathway (RAS/RAF/MEK/ERK) are frequently found in cancer. MAPK pathway inhibitors, such as MEK inhibitors, were developed as targeted therapeutics to potentially treat such cancers [
41,
42]. MEKi as single agents or in combination with other therapies have been studied for the treatment of melanoma, lung and colorectal cancers [
43]. In 2013, the MEKi selumetinib was evaluated in a phase II clinical trial as a treatment for LGSC. Clinical responses (RECIST-1.1) to MEKi were observed in 15% of patients [
22,
44]. While these responses were limited, response rates using conventional chemotherapy in patients with relapsed LGSC are disappointingly low (4%) [
45]. More recently, a number of LGSC cases have been reported, highlighting dramatic and durable responses to MEKi treatment [
22,
23,
46,
47]. Currently, there are no predictive biomarkers of MEKi response for LGSC. Identifying molecular markers which predict MEKi treatment efficacy will allow for pre-selection of patients who would benefit from this treatment, and avoid ineffective treatments and toxicities in those patients unlikely to respond.
In this study, we utilized genomic and proteomic techniques to molecularly characterize a collection of LGSC cell lines and primary cultures (derived from advanced/recurrent LGSC patients), and identify markers that predict response (sensitivity/resistance) to MEKi treatment in vitro. Genomic profiles of two of these cell models were compared with their corresponding tumor samples from the same patient and showed remarkably similar copy number profiles, supporting the utility of these cell models for preclinical research. Subsequent comparisons of genomic profiles from an additional twelve LGSC cell models showed frequent deletion of Chr9p (including loss of
MTAP and
CDKN2A genes) [
48,
49] and oncogenic mutations in
KRAS and
NRAS genes, in agreement with results from previous studies on LGSC tumor tissues [
13‐
15]. Additionally,
RAS mutations were often associated with
RAS copy number gain. As previously reported [
24,
46,
50] we also detected multiple and distinct genomic alterations affecting other genes related to the MAPK cell signaling pathway. It is worth noting that the individual comparison of genomic profiles between LGSC cultures showed substantial variations in the types of gene mutations and copy-number alterations, indicating widespread molecular differences in LGSC tumors between patients.
Further evaluation of mutation profiles in eight LGSC cell lines with different sensitivity to MEKi treatment (two MEKi-Se and six MEKi-Re) showed oncogenic mutations in
KRAS in all four MEKi-Se lines which were absent in all six MEK-Re lines. Previous results from a clinical trial using selumetinib (Farley et al. [
22]) did not find a significant relationship between
RAS mutation status and MEKi response rates in LGSC patients. It is important to note that tumor samples were not available for testing in 35% of the patients (18 of 52) in this study. In agreement with our results, two recent case reports on LGSC patients with remarkable and durable clinical responses (> 5 years) to MEKi therapy have reported oncogenic
KRAS mutations (both G12V) in their tumors [
23,
47]. As LGSC is often an indolent disease, the inclusion of patients with stable disease should also be considered in the future evaluation of
RAS mutation status as a predictive biomarker. It is not unexpected that a single biomarker, such as
KRAS mutation status, will not accurately predict responses to MEKi treatment, recognizing that LGSC harbor other MAPK-pathway gene mutations and significant MAPK copy number changes. Furthermore, KRAS copy-number amplification (described as one activating mechanism) could also play a role in mediating MEKi efficacy [
44].
Using RPPA to compare MEKi-Se and MEKi-Re LGSC cell lines, we found that all MEKi-Re lines had higher levels of EGFR and PKC-alpha expression. These results were subsequently validated in three newly established LGSC cell lines. Using this approach, we also described proteomic changes specific to each MEKi tested (selumetinib or trametinib). The changes we observed may be particularly relevant when evaluating differences in drug efficacy, as MEKi may exhibit differences in MEK isoform specificity or off-target effects [
24]. Interestingly, all MEKi-Re lines expressed higher levels of EGFR activation (p-EGFR Y1068) than the MEKi-Se lines. Although our study was limited to a small number of cell lines, we did not observe an obvious correlation between levels of EGFR and PKC-α protein expression and specific gene mutations or copy number changes in these genes.
In colorectal cancer, preclinical studies with BRAF inhibitors have reported adaptive feedback reactivation of MAPK signaling involving EGFR [
33,
51]. This feedback signaling can be blocked by the addition of a MEKi. We similarly found evidence of MAPK feedback signaling following MEKi treatment that appears to play a role in MEKi resistances. Half of the MEKi-Re cells (2/4 cell lines) were effectively treated with selumetinib in combination with erlotinib, causing complete cell death. Combination therapy was effective in these two cell lines using drug doses that were below those that lacked efficacy as single drug treatments. Drug synergy was demonstrated using CompuSyn analyses in the two cell lines where cell death was demonstrated. In contrast, the other two lines tested continued to proliferate even with higher doses of the drug combination. We were unable to observe any obvious changes in p-EGFR and/or p-ERK that characterized the two combination-therapy resistant cell lines. As seen in our previous study [
24], trametinib appeared to be a more effective inhibitor of ERK phosphorylation and cell proliferation than selumetinib. Based on its enhanced efficacy, it was more difficult to detect drug synergism using the erlotinib/trametinib combination than with the erlotinib/selumetinib combination.
There is a growing body of evidence supporting the use of combining a targeted therapy with other targeted agents or with traditional chemotherapeutic agents [
29,
52]. Combination therapy using erlotinib and selumetinib was studied in a randomized phase II trial in lung cancer [
53]. This drug combination did not prove to be effective in lung cancers irrespective of
KRAS mutant status. Though the treatment was tolerated, significant side effects occurred with combination therapy. If these drug treatment combinations are going to be effective in LGSC, optimal drug dosing will be required in order to minimize side effects without loss of treatment efficacy.
Combination therapy with BRAFi and MEKi has remarkably improved survival in the adjuvant setting for patients with
BRAF mutant melanomas, and combining a BRAFi and an EGFRi has improved tumor regression in
BRAF mutant colorectal cancer xenografts [
51,
54]. In a recent report, binimetinib in combination with paclitaxel was studied in platinum resistant ovarian cancer patients (NCT01649336). Two LGSC patients included in this trial showed response to this drug combination. These cases had also the largest reduction in target lesion size among the 25 ovarian cancer patients studied. MAPK pathway aberrations (
KRAS G12D mutation and a
CUL1:BRAF fusion) were identified in the tumors of both patients [
44]. Additionally, two more LGSC patients with
KRAS G12V [
23,
47] and one with
MEK1 (Q56_V60del) gene mutations experienced disease stabilization in response to this drug treatment combination [
46].
PKC-alpha expression has been implicated in chemotherapy drug resistance in some cancers [
36,
37]. To explore its potential role in MEKi resistance, we inhibited PKC-α expression in two MEKi-Re lines. In the cell line where complete PKC-alpha protein knockdown was achieved, the effect of this treatment combination was not nearly as effective as combining MEKi and EGFRi. In the other line, where only partial knockdown of PKC-alpha protein expression was obtained, no changes in MEKi sensitivity were observed. Of interest, we found that this line contained
PRKCA copy number gain. PKC-alpha knockdown by itself did not affect cell proliferation in either cell line. The results of our experiments suggest that PKC-alpha protein expression appears to be a predictive biomarker but is not a therapeutic target mediating MEKi resistance.
Identifying molecular characteristics to predict drug sensitivity/resistance in individual patients with solid tumors has proved to be challenging. The efficacy of therapies designed to target specific mutations are known to be dependent on the cancer type. For example, while BRAF inhibitors have shown to be effective in melanomas carrying
BRAF mutations, they have demonstrated little effect in the treatment of
BRAF mutant colon cancers [
33,
55,
56]. In advanced LGSC, mutations in
KRAS are more common than in
BRAF [
14,
19,
57,
58]. While MEKi have shown efficacy in some LGSC, still only a minority of patients respond to this treatment. Thus, it is of utmost importance to identify markers of drug treatment efficacy specific for each cancer type. A current clinical trial using the MEKi trametinib to treat patients with LGSC (NCT02101788), will include a translational research component in an attempt to identify predictive biomarkers in patient tumor samples.
Authors’ contributions
MLF performed research conception, design, experimental preparation, data analysis, data interpretation, and manuscript preparation; AD performed experimental preparation, data analysis, and manuscript preparation; JH performed western blot, cell proliferation and viability, drug testing and data analysis; HK performed western blot preparation and data analysis, and clinical data collection; SB performed RPPA experimental sample preparation and data analysis; CS assisted with cell culture work and cell line generation; GD assisted with cell line generation, data interpretation and manuscript revision; TS assisted with cell line generation; MC performed RPPA experimental work and data analysis; BH lead the RPPA experimental work and data analysis; SA performed CNV analysis and figure preparation; SV performed mutation call analysis; CCC assisted with genomic analysis and data interpretation; DGH supervised the conduct of the research, acquisition of data and banked tumor samples; MSC lead this research, developed the research concepts, statistical data analysis, data interpretation, and manuscript preparation and review. All authors read and approved the final manuscript.