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. 2017 Oct 9;8(58):98660-98676.
doi: 10.18632/oncotarget.21720. eCollection 2017 Nov 17.

Increased single-strand annealing rather than non-homologous end-joining predicts hereditary ovarian carcinoma

Miriam Deniz  1 , Tatiana Romashova  1 , Sarah Kostezka  1 , Anke Faul  1 , Theresa Gundelach  1 , Maria Moreno-Villanueva  2 , Wolfgang Janni  1 , Thomas W P Friedl  1 , Lisa Wiesmüller  1
Affiliations

Increased single-strand annealing rather than non-homologous end-joining predicts hereditary ovarian carcinoma

Miriam Deniz et al. Oncotarget. .

Abstract

Mutations in genes encoding DNA double-strand break (DSB) repair components, especially homologous recombination (HR) proteins, were found to predispose to breast and ovarian cancer. Beyond high penetrance risk gene mutations underlying monogenic defects, low risk gene mutations generate polygenic defects, enlarging the fraction of individuals with a predisposing phenotype. DSB repair dysfunction opens new options for targeted therapies; poly (ADP-ribose) polymerase (PARP) inhibitors have been approved for BRCA-mutated and platinum-responsive ovarian cancers. In this work, we performed functional analyses in peripheral blood lymphocytes (PBLs) using a case-control design. We examined 38 women with familial history of breast and/or ovarian cancer, 40 women with primary ovarian cancer and 34 healthy controls. Using a GFP-based test we analyzed error-prone DSB repair mechanisms which are known to compensate for HR defects and to generate chromosomal instabilities. While non-homologous end-joining (NHEJ) did not discriminate between cases and controls, we found increases of single-strand annealing (SSA) in women with familial risk vs. controls (P=0.016) and patients with ovarian cancer vs. controls (P=0.002). Consistent with compromised HR we also detected increased sensitivities to carboplatin in PBLs from high-risk individuals (P<0.0001) as well as patients (P=0.0011) compared to controls. Conversely, neither PARP inhibitor responses nor PARP activities were altered in PBLs from the case groups, but PARP activities increased with age in high-risk individuals, providing novel clues for differential drug mode-of-action. Our findings indicate the great potential of detecting SSA activities to deliver an estimate of ovarian cancer susceptibility and therapeutic responsiveness beyond the limitations of genotyping.

Keywords: PARP activity; early-onset ovarian cancer; error-prone DNA repair; functional biomarker; ovarian cancer risk.

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Conflict of interest statement

CONFLICTS OF INTEREST None of the authors has any conflicts of interest. L.W. is an inventor of a patent on a test system for determining genotoxicities, which is owned by L.W.

Figures

Figure 1
Figure 1. Outline of the study design
After retrieval of heparinized blood samples from donors (38 high risk individuals, 40 breast cancer patients and 34 healthy controls) PBLs were isolated by Ficoll gradient centrifugation within 24h [19]. PBLs were transferred to liquid nitrogen and gently thawed according to the SOPs developed for the MARK-AGE EU project [28]. While PARP activities were determined in PBL aliquots immediately after de-freezing, the majority of cells were cultivated for 72h. For NHEJ and homologous repair (mostly SSA) measurements PBLs were nucleofected with the GFP-based DSB repair substrates EJ5SceGFP [29] and HR-EGFP/3´EGFP [69], respectively, and DSB repair was quantified by FACS analysis of the fraction of green fluorescent cells (corrected for individual transfection efficiencies) 24h later. I-SceI-mediated cleavage at two recognition sites formula image initiated NHEJ deleting the spacer sequence (grey bar) between the promoter (kinked arrow) and GFP coding region (green bar) in EJ5SceGFP. Cleavage within internally mutated HR-EGFP triggered homologous repair with N-terminally mutated 3´EGFP in substrate HR-EGFP/3´EGFP. Remaining PBLs were subjected to the analysis of drug sensitivities using MTT assay, whereby IC50-values were determined after carboplatin and PARP inhibitor (IQD) treatment.
Figure 2
Figure 2. Association of elevated SSA frequencies with case status
DSB repair, i.e. (A) NHEJ and (B) SSA, frequencies were determined in triplicates per individual in high-risk individuals (NHEJ: n=28, SSA: n=37) versus controls (NHEJ: n=18, SSA=20; corresponding age subgroup of >=30 and <65 years) and ovarian cancer patients (NHEJ: n=19, SSA: n=30) versus controls (NHEJ: n=27, SSA=32; corresponding age subgroup of >35 years). Mean values were individually corrected for nucleofection efficiencies (determined in triplicates), normalized to data from reference PBLs (internal standard for experimental day) and log10 transformed for normal distribution after transformation. For further details see Table 2. *P<0.05; **P<0.01; n.s., non-significant.
Figure 3
Figure 3. ROC curves for SSA values in cases versus controls
ROC curves of SSA values for cases and controls, adjusted for internal standard and log10 transformed. (A) ROC curve for high-risk individuals (n=37) and controls (n=20). Area under the curve: 0.69, P=0.022. (B) ROC curve for ovarian cancer patients (n=30) and controls (n=32). Area under the curve: 0.70, P=0.006.
Figure 4
Figure 4. PARP activities as a function of age
PARP activities (basal and following oligonucleotide plus NAD+ activation) were determined in thawed PBL samples, normalized to reference PBL values and graphically presented as a function of each proband´s age (high-risk individuals: n=38; ovarian cancer patients: n=39; controls: n=32). Spearman´s rho (rs) correlation coefficient and two-tailed significance were calculated as indicated.
Figure 5
Figure 5. Drug sensitivities in cases versus controls
Cell viabilities were assessed by use of MTT assay after 7d of PARP inhibitor (IQD) treatment (A) and 48h of carboplatin treatment (B), respectively. Mean survival curves of PBLs derived from high-risk individuals (IQD: n=25; carboplatin: n=29) versus controls from the corresponding age subgroup of >=30 and <65 years (IQD: n=15; carboplatin: n=16) and ovarian cancer patients (IQD: n=23; carboplatin: n=26) versus controls from the corresponding age subgroup of >35 years (IQD: n=25; carboplatin: n=27) are graphically presented. Calculation of IC50 values and statistical tests for differences between survival curves were performed using GraphPad Prism software.
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