The Pharmacogenomics Journal (2013) 13, 159–172 & 2013 Macmillan Publishers Limited. All rights reserved 1470-269X/13 www.nature.com/tpj ORIGINAL ARTICLE

DNA-damage response polymorphisms and therapeutic outcomes in ovarian cancer

E Caiola1, L Porcu2, R Fruscio3, Epithelial ovarian cancer has a poor prognosis owing to late diagnosis and 3 3 2 frequent relapse after first-line therapy. Analysis of individual genetic D Giuliani , R Milani , V Torri , variability could aid in the identification of markers, which could help in 1 1 M Broggini and M Marabese stratifying patients with the aim of optimizing individual therapy. In this study we assessed polymorphisms in three important in drugs’ 1Laboratory of Molecular Pharmacology, Department of Oncology, Istituto di Ricerche response in 97 early and 235 late-stage ovarian cancer patients. The Farmacologiche ‘Mario Negri’, Milan, Italy; Asp1104His polymorphism in xpg, a gene important for removal of platinum 2New Drug Development Strategies Laboratory, adducts, was associated with progression-free survival in early- and late-stage Department of Oncology, Istituto di Ricerche ovarian cancer. Our data indicate that a simple diagnostic analysis such as Farmacologiche ‘Mario Negri’, Milan, Italy and 3Clinic of Obstetrics and Gynecology, University xpg genotyping can help in predicting response, and extension to other of Milan-Bicocca, San Gerardo Hospital, Monza, possibly relevant genotypes could be useful in selecting patients with Italy epithelial ovarian cancer for optimal therapy and hence increase the chance of response. Correspondence: The Pharmacogenomics Journal (2013) 13, 159–172; doi:10.1038/tpj.2011.50; Dr M Marabese, Laboratory of Molecular Pharmacology, Department of Oncology, published online 13 December 2011 Istituto di Ricerche Farmacologiche ‘Mario Negri’, via La Masa 19, Milan 20156, Italy. Keywords: polymorphism; mdm2; ercc1; /xpg; ovarian cancer; SNP E-mail: [email protected]

Introduction

Epithelial ovarian cancer (EOC) has a poor prognosis as the majority of cases are diagnosed in advanced stages. This limits the possibility of a cure and the overall survival (OS) rate at 5 years is less than 30%,1–4 even though the majority of patients respond to a first-line platinum-containing drug. After an initial response, a high percentage of patients relapse, and second- and third-line therapies have only a modest impact on survival.5 As DNA is the target of platinum-containing drug, several studies analyzed DNA-repair patterns, either at the RNA or level. Platinum-induced lesions are mostly repaired by nucleotide excision repair (NER), but also by , mismatch repair and Fanconi anemia.6,7 Evidence indicates that NER is a critical determinant of platinum-containing drug activity in vitro, and cancer cells that have a proficient NER mechanism have a greater likelihood of repairing DNA lesions and surviving when treated. In the clinical setting, however, data are not as clear as in experimental models.8 An increasing amount of evidence indicates that genetic variants of certain genes, even if not associated with changes in the expression levels of the they are encoding for, could alter the functionality of the protein and possibly have an important role in defining patients with a high/low probability of response. Functional variants in genes involved in the DNA-repair pathway could be important determinants of platinum response in women with EOC.9,10 Excision repair cross-complementa- Received 28 July 2011; revised 19 October 11–14 2011; accepted 7 November 2011; published tion group-1 (ERCC1) has a significant role in platinum–DNA adduct repair. online 13 December 2011 Several ercc1 polymorphisms have been identified. The nucleotide 19007 C/T DNA-damage gene polymorphisms in ovarian cancer E Caiola et al 160

polymorphism (rs11615) affects mRNA levels,15 and shows a Genotyping significant association with OS16,17 and tumor response18 in DNA from blood was extracted using the Maxwell 16 DNA . This single-nucleotide polymorphism Purification kit (Promega, Milan, Italy). The rs2279744 (SNP) was not associated with OS in many tumors such as polymorphism was genotyped using primers described by melanoma,19 lung20 and ovarian21 cancer, but was described Ueda et al.36 DNA was amplified using Go Taq Hot Start as an independent predictor of reduced risk of platinum Polymerase (Promega). The other four SNPs were genotyped resistance.21 A second ercc1 SNP, C8092A (rs3212986), using TaqMan SNP Genotyping assays (Applied Biosystems, located in the 30-untranslated region, enhances mRNA Monza, Italy). PCR was performed in 384-well plates stability.22 This SNP was associated with a favorable out- prepared with automatic liquid handling (epMotion 5075; come in head and neck cancer23 and better OS in non-small- Eppendorf, Milan, Italy). cell lung cancer.20 Group-G (XPG), a component RNA isolation and cDNA preparation of the NER pathway, is a structure-specific endonuclease Tissues were homogenized by ultraturrax and total RNA was catalyzing the 30 incision at DNA-damage sites.24,25 The extracted using the SV Total RNA Isolation kit (Promega). non-synonymous SNP in its coding region causes the RNA was then reverse-transcribed using the High Capacity amino-acid change Asp1104His (rs17655). The SNP that is cDNA Reverse kit (Applied Biosystems) and required for the interaction between XPG is located in stored at À80 1C until use. the XPG C-terminus and other components of the NER Primer design machinery.26 The Asp1104His amino-acid change could The primer pairs for mdm2 (for.: 50-TGGCGTGCCAAGC influence the protein–protein interaction and predispose TTCTCTGTG, rev.: 50-TGTACCTGAGTCCGATGATTCCTG individuals to cancer. The SNP 46 His/His of xpg (rs1047768) CTG), ercc1 (for.: 50-CCAACAGCATCATTGTGAGC-30, rev.: is induced by a C–T nucleotide substitution. Although the 50-TCTTGGCCCAGCACATAGTC), xpg (for.: 50-TCTGGAAG real function of this variant is still unknown, different CTGCTGGAGTG, rev.: 50-GACAAAAGGAATGGCAGGAG) studies suggest a role in cancer development and drug and b-actin (for.: 50-TCACCCACA CTGTGCCCATCTACCA, response. XPG has been associated with a good response to rev.: 50-CAGCGGAACCGCTCATTGCCAATGG) were chosen platinum-based chemotherapy in advanced non-small-cell spanning splicing junctions using the PRIMER-3 software lung cancer.27 available online (http://frodo.wi.mit.edu/primer3/). MDM2 is an oncoprotein that binds to and inactivates 28 p53, a key protein involved in DNA-damage response. Real-time reverse transcription-PCR MDM2 can inhibit the transcriptional activity of p53 Relative quantification of xpg, ercc1 and mdm2 gene through direct binding to the N-terminal transactivation expression was performed by real-time reverse transcrip- 29,30 domain and also acts as an E3 ligase, which leads to tion-PCR (ABI 7900; Applied Biosystems). PCR was per- both export of p53 to the cytoplasm and its proteasomal formed by using the GoTaq qPCR Master Mix (Promega). 31 degradation. MDM2 overexpression is associated with Relative quantification of the expression levels of xpg, ercc1 cancer progression and lack of response to therapy in and mdm2 was calculated by using the DDCt method using 32,33 human cancers. b-actin as the internal control gene. A T–G polymorphism in the MDM2 region, at nucleotide 309 (rs2279744), increases the affinity for Statistical methods binding to stimulatory protein-1 and results in higher A consecutive cohort of patients with ovarian cancer for levels of MDM2 expression.34 In humans, MDM2 SNP309 which biological material was available was identified and was associated with increased tumor formation in both retrospectively enrolled in this monocentric study. Baseline hereditary and sporadic cancers.35 covariate distributions were summarized using descriptive The use of genetic tools to predict response to platinum- statistics (median and range for continuous variables, and based chemotherapy and survival in EOC could improve absolute and percentage frequencies for categorical vari- patient outcome. In this context, the aim of this study was ables); non-parametric tests (Wilcoxon–Mann–Whitney test to evaluate associations between the above-mentioned for continuous covariates and Fisher’s exact test for catego- genetic variants in ercc1, xpg and MDM2 genes, and clinical rical covariates) were used to detect statistical association. outcomes. Both progression-free survival (PFS, event: first progression of disease or death by any cause) and OS (event: death by any Materials and methods cause) were calculated considering as starting point the date of diagnosis of ovarian cancer; the time to event outcome Patients and sample collection parameters were estimated by the Kaplan–Meier product- Biopsies and blood specimens were collected at the Clinic of limit method; log-rank test was used to compare survival in Obstetrics and Gynecology, San Gerardo Hospital (Monza, genotype groups; and a Cox proportional hazards model was Italy). Fresh tumor tissues were minced and frozen with adapted to estimate hazard ratios (HRs), to adjust for blood samples at À80 1C. The collection and use of the prognostic factors that influenced time to events and to samples was approved by the local scientific ethics commit- evaluate the statistical power of our study in detecting a tee, and patients gave written informed consent. relevant difference. All statistical tests were two-sided and a

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P-value o0.05 was considered statistically significant. Statis- For the stage-I/II population the median age at diagnosis tical analysis was performed by using the SAS software (SAS was 52.1 years (range: 16.5–81.8 years); 82 (84.5%) patients Institute, Cary, NC, USA) (version 9.2). The statistical had FIGO stage-I; and the predominant histology was serous package Stata (StataCorp, College Station, TX, USA) (version subtype (number of patients: 35, 36.1%) and poorly 11.1) was used for Kaplan–Meier plots and dot plots. differentiated grade (number of patients: 43, 44.3%). Sixty- four patients (66.0%) received an adjuvant cisplatin-based Results therapy. After a median follow-up of 10.0 years, 67 (69.1%) patients were alive, of whom 62 (92.5%) were progression- Clinical and histopathological characteristics free. Age at diagnosis was the only baseline covariate From September 1979 to December 2004, 359 patients with statistically associated to PFS (HR ¼ 1.04, 95% confidence ovarian cancer were identified. A total of 27 (7.5%) patients interval (CI): 1.00–1.07; P ¼ 0.024); age at diagnosis with borderline grading were not considered for the study; (HR ¼ 1.04, 95% CI: 1.01–1.08; P ¼ 0.019) and cancer grad- out of the remaining patients 97 (29.2%) had FIGO stage-I ing (HR(G3vsG1) ¼ 4.39, 95% CI: 1.01–19.10; P ¼ 0.049) were and II disease, and 235 (70.8%) patients had FIGO stage-III baseline covariates statistically associated to OS. and IV disease. For the stage-III/IV population the median age at diagnosis was 54.6 years (range: 13.2–79.1 years); 208 Table 1 Clinical and histopathological characteristics (88.5%) patients had FIGO stage-III disease; residual tumor size was more than 2 cm in 154 (65.5%) patients; and the Early stages n % Late stages n % predominant histology was serous subtype (number of patients: 182, 77.4%) and poorly differentiated grade Age at diagnosis 97 235 Median 52.1 Median 54.6 (number of patients: 155, 66.0%). All patients received Range 16.5–81.8 Range 13.2–79.1 platinum-based therapy. After a median follow-up of 11.3 years, 57 (24.3%) patients were alive, of whom 44 (77.2%) Stage were progression-free; median PFS was 2.2 years (95% CI: I 82 84.5 III 208 88.5 1.8–2.6 years); and median OS was 3.6 years (95% CI: 3.2–4.2 II 15 15.5 IV 27 11.5 years). Age at diagnosis (HR ¼ 1.02, 95% CI: 1.01–1.03; P ¼ 0.004), residual tumor size (HR ¼ 1.75, 95% CI: 1.27– Grading G1 19 19.6 G1 15 6.4 2.40; Pp0.001), histotype (HR(Mucinous vs Serous) ¼ 2.78, 95% G2 35 36.1 G2 65 27.7 CI: 1.36–5.68; P ¼ 0.005) and grading (HR(G2 vs G1) ¼ 2.48, G3 43 44.3 G3 155 66.0 95% CI: 1.18–5.20; P ¼ 0.017/HR(G3 vs G1) ¼ 2.38, 95% CI: 1.16–4.86; P ¼ 0.018) were the baseline covariates statisti- Histotype cally correlated to PFS, globally or at least comparing single Serous 35 36.1 Serous 182 77.4 risk factor categories; the same correlations were detected Endometroid 24 24.7 Endometroid 21 8.9 Clear cell 19 19.6 Clear cell 13 5.5 considering OS as endpoint: age at diagnosis (HR ¼ 1.02, Mucinous 12 12.4 Mucinous 9 3.8 95% CI: 1.01–1.03; Pp0.001), residual tumor size Other 7 7.2 Other 10 4.3 (HR ¼ 2.25, 95% CI: 1.61–3.17; Pp0.001), histotype (HR(Mucinous vs Serous) ¼ 2.20, 95% CI: 1.03–4.70; P ¼ 0.043) Residual tumor and grading (HR(G2 vs G1) ¼ 3.20, 95% CI: 1.37–7.46; Absent o2 cm 81 34.5 P ¼ 0.007/HR(G3 vs G1) ¼ 2.86, 95% CI: 1.26–6.49; P ¼ 0.012). Adjuvant therapy X2 cm 154 65.5 The clinical and histopathological characteristics of the Platinum-based 64 66.0 Platinum- 235 100.0 population are summarized in Table 1; survival estimates are based plotted in Figure 1; and risk estimates of baseline covariates No therapy 33 34.0 are reported in Table 2.

Figure 1 Survival estimate plots for early (left) and late (right)-stage disease.

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Table 2 Prognostic evaluation of clinical and histopathological characteristics

Early stages HR Lower Upper w2 P-value Late stages HR Lower Upper w2 P-value 95% HR 95% HR 95% HR 95% HR

Progression-free survival Age at diagnosis 1.04 1.00 1.07 5.098 0.024 1.02 1.01 1.03 8.177 0.004

Stage I 1 0.265 0.607 III 1 0.861 0.353 II 1.24 0.54 2.85 IV 1.23 0.79 1.90

Histotype Serous 1 4.086 0.394 Serous 1 9.121 0.058 Endometroid 0.46 0.17 1.27 Endometroid 1.12 0.68 1.85 Clear cell 1.14 0.48 2.69 Clear cell 1.22 0.66 2.25 Mucinous 0.59 0.17 2.04 Mucinous 2.78 1.36 5.68 Other 1.37 0.45 4.15 Other 0.73 0.34 1.56

Grading G1 1 3.219a 0.073 G1 1 2.933a 0.087 G2 1.94 0.63 5.97 G2 2.48 1.18 5.20 G3 2.62 0.89 7.77 G3 2.38 1.16 4.86

Residual tumor Absent o 2 cm 1 11.875 o0.001 X2 cm 1.75 1.27 2.40

First-line therapy Untreated 1 0.437 0.509 All treated Treated 0.793 0.399 1,576

Overall survival Age at diagnosis 1.04 1.01 1.08 5.471 0.019 1.02 1.01 1.03 11.520 o0.001

Stage I 1 0.473 0.492 III 1 2.214 0.137 II 1.37 0.56 3.40 IV 1.39 0.90 2.16

Histotype Serous 1 3.126 0.537 Serous 1 5.290 0.259 Endometroid 0.81 0.27 2.36 Endometroid 1.09 0.64 1.85 Clear cell 1.88 0.74 4.78 Clear cell 1.41 0.76 2.61 Mucinous 1.05 0.29 3.85 Mucinous 2.20 1.03 4.70 Other 1.70 0.47 6.19 Other 0.89 0.42 1.91

Grading G1 1 4.126a 0.042 G1 1 2.594a 0.107 G2 3.35 0.74 15.11 G2 3.20 1.37 7.46 G3 4.39 1.01 19.10 G3 2.86 1.26 6.49

Residual tumor Absent o 2 cm 1 22.021 o0.001 X2 cm 2.25 1.61 3.17

First-line therapy Untreated 1 1.458 0.227 All treated Treated 0.632 0.300 1.331

Abbreviation: HR, hazard ratio. aTest for linear trend.

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Table 3 Expected and observed polymorphisms prevalence (%)

Expected Observed

Early stages Late stages

% n % w2 P-value n % w2 P-value mdm2 rs2279744 T/T 45.0 49 50.5 0.593 0.441 119 50.8 1.593 0.207 T/G, G/G 55.0 48 49.5 115 49.2 ercc1 rs11615 T/T 38.4 38 39.6 0.028 0.868 80 34.3 0.768 0.381 T/C, C/C 61.6 58 60.4 153 65.7 rs3212986 A/A 10.2 16 16.5 0.981 0.322 18 7.7 0.260 0.610 C/A, C/C 89.8 81 83.5 215 92.3 xpg rs17655 C/C 6.7 10 10.3 0.314 0.575 14 6.0 0.022 0.883 C/G, G/G 93.3 87 89.7 219 94.0 rs1047768 C/C 32.7 33 34.0 0.033 0.856 89 38.4 1.575 0.210 C/T, T/T 67.3 64 66.0 143 61.6

Correlation between Mdm2 polymorphism, and clinical and patients was as expected based on the available data (Table 3). histopathological characteristics of ovarian cancer patients The rs11615 polymorphism was not statistically signifi- The genotype frequency found in our cohort of patients was cantly correlated to any clinical and histopathological equal to that predicted by the SNP database (http:// characteristic of the early- and advanced-stage patients www.ncbi.nlm.nih.gov/sites/entrez?db ¼ snp) (Table 3). For (Tables 4–6 and Supplementary Figures 2a–d); when com- both the early- and advanced-stage population, genotype pared with the A/A genotype, the group with the rs3212986 was not statistically significantly correlated to any clinical polymorphism C genotype was significantly associated to a and histopathological characteristic (Table 4); in particular major reduction in residual tumor size (P ¼ 0.037) and to genotype did not predict prognosis (survival estimates more differentiated tumors (P ¼ 0.034) in advanced-stage plotted in Supplementary Figures 1a–d, and relative risk patients as reported in Table 4; the group with the C estimates reported in Tables 5 and 6). genotype showed a 40% (95% CI: 63-2%, P ¼ 0.042) For 50 (13.9%) patients randomly sampled we deter- improvement in PFS and a 43% (95% CI: 65-7%, P ¼ 0.025) mined, together with genotype, the expression of mdm2 improvement in OS, but the assumption of proportional mRNA in tumor samples and we correlated gene expression hazard was questionable as we can see from the crossing with genotype. Patients with the T/T genotype had a survival curves, and above all the result was not confirmed significantly lower expression of mdm2 compared with in the multivariate analysis (Table 6, and Figures 3c and d); those with G/G and T/G genotypes (P ¼ 0.003; see Figure 2a). no correlation was detected in early-stage patients (Tables 5, The difference remained statistically significant when the T/ and Figures 3a and b). G and G/G genotypes were grouped and compared with the ercc1 tumor mRNA expression was determined for 85 T/T genotype (P ¼ 0.019; see Figure 2b). These data correlate (23.7%) patients. For both SNPs (P-value for rs11615: 0.156 well with the evidence present in other tumor types that the and P-value for rs3212986: 0.568) we were unable to G-containing genotypes result in a higher transcription of associate the genotype with ercc1 levels (Supplementary the gene. For this reason we decided to combine the G/G Figures 4a–d). and the G/T genotypes in the analysis. Correlation between ERCC5/XPG polymorphism, and clinical and Correlation between ERCC1 polymorphism, and clinical and histopathological characteristics of ovarian cancer patients histopathological characteristics of ovarian cancer patients We analyzed two polymorphisms for this gene, one located For this gene we analyzed two polymorphisms, C8092A at position 335, T335C (rs1047768), and the other at (rs3212986) and C19007T (rs11615), present in the 30- position 3507, G3507C (rs17655). The genotype frequency untranslated region and the coding region of the gene, found in our cohort of patients was what we expected from respectively. The genotype frequency found in our cohort of the available data (Table 3). No statistically significant

The Pharmacogenomics Journal 164 h hraoeoisJournal Pharmacogenomics The Table 4 Correlations between clinical and histopathological parameters and genotypes

Early stages mdm2 ercc1 xpg

rs2279744 rs11615 rs3212986 rs17655 rs1047768

T/T T/G, G/G T/T C/T, C/C A/A C/A, C/C C/C C/G, G/G C/C C/T, T/T

Age at diagnosis n 49 48 38 58 16 81 10 87 33 64 Median 49.5 53.9 52.1 52.1 53.2 51.6 55.0 51.6 52.1 51.9 Range 16.5–80.4 21.1–81.8 30.8–81.8 16.5–68.4 41.0–64.5 16.5–81.8 43.9–67.0 16.5–81.8 31.8–70.8 16.5–81.8 cancer ovarian in polymorphisms gene DNA-damage P-value 0.385 0.645 0.610 0.310 0.888

Stage 1 n 40 42 34 47 14 68 9 73 28 54 % 81.6 87.5 89.5 81.0 87.5 84.0 90.0 83.9 84.8 84.4 2 n 9 6411213114510 % 18.4 12.5 10.5 19.0 12.5 16.0 10.0 16.1 15.2 15.6 P-value 0.576 0.390 1.000 1.000 1.000

Histotype Caiola E Serous n 15 20 13 21 7 28 3 32 14 21 % 30.6 41.7 34.2 36.2 43.8 34.6 30.0 36.8 42.4 32.8 tal et Endometroid n 18 6 12 12 1 23 4 20 9 15 % 36.7 12.5 31.6 20.7 6.3 28.4 40.0 23.0 27.3 23.4 Clear cell n 712514316217613 % 14.3 25.0 13.2 24.1 18.8 19.8 20.0 19.5 18.2 20.3 Mucinous n 6657210111210 % 12.2 12.5 13.2 12.1 12.5 12.3 10.0 12.6 6.1 15.6 Other n 3434340725 % 6.1 8.3 7.9 6.9 18.8 4.9 0.0 8.0 6.1 7.8 P-value 0.081 0.631 0.134 0.838 0.679 Grading G1 n 811613514217613 % 16.3 22.9 15.8 22.4 31.3 17.3 20.0 19.5 18.2 20.3 G2 n 20 15 13 21 5 30 4 31 13 22 % 40.8 31.3 34.2 36.2 31.3 37.0 40.0 35.6 39.4 34.4 G3 n 21 22 19 24 6 37 4 39 14 29 % 42.9 45.8 50.0 41.4 37.5 45.7 40.0 44.8 42.4 45.3 P-value 0.910 0.348 0.332 0.823 0.925

First-line therapy Untreated n 18 15 12 21 5 28 4 29 11 22 % 36.7 31.3 31.6 36.2 31.3 34.6 40.0 33.3 33.3 34.4 Treated n 31 33 26 37 11 53 6 58 22 42 % 63.3 68.8 68.4 63.8 68.8 65.4 60.0 66.7 66.7 65.6 P-value 0.669 0.667 1.000 0.731 1.000 Table 4 Continued

Late stages mdm2 ercc1 xpg

rs2279744 rs11615 rs3212986 rs17655 rs1047768

T/T T/G, G/G T/T C/T, C/C A/A C/A, C/C C/C C/G, G/G C/C C/T, T/T

Age at diagnosis n 119 115 80 153 18 215 14 219 89 143 Median 53.8 55.8 55.3 54.3 54.5 54.5 53.4 54.8 57.8 54.2 Range 13.2–79.1 19.6–77.8 13.2–79.1 19.6–77.8 19.6–77.5 13.2–79.1 32.6–61.9 13.2–79.1 17.8–79.1 13.2–78.8 P-value 0.242 0.804 0.704 0.213 0.172 Stage 3 n 105 102 66 140 18 188 12 194 79 127 % 88.2 88.7 82.5 91.5 100.0 87.4 85.7 88.6 88.8 88.8 4 n 14 13 14 13 0 27 2 25 10 16 % 11.8 11.3 17.5 8.5 0.0 12.6 14.3 11.4 11.2 11.2 P-value 1.000 0.052 0.239 0.669 1.000 Residual tumor o2cm n 38 43 32 48 2 78 6 74 29 51 % 31.9 37.4 40.0 31.4 11.1 36.3 42.9 33.8 32.6 35.7 X2cm n 81 72 48 105 16 137 8 145 60 92 % 68.1 62.6 60.0 68.6 88.9 63.7 57.1 66.2 67.4 64.3 P-value 0.411 0.195 0.037 0.564 0.672 cancer Caiola ovarian E in polymorphisms gene DNA-damage Histotype

Serous n 91 91 62 118 15 165 10 170 70 110 al et % 76.5 79.1 77.5 77.1 83.3 76.7 71.4 77.6 78.7 76.9 Endometroid n 9 12 9 12 2 19 1 20 11 10 % 7.6 10.4 11.3 7.8 11.1 8.8 7.1 9.1 12.4 7.0 Clear cell n 7 621101311258 % 5.9 5.2 2.5 7.2 0.0 6.0 7.1 5.5 5.6 5.6 Mucinous n 6354091827 % 5.0 2.6 6.3 2.6 0.0 4.2 7.1 3.7 2.2 4.9 Other n 6328191918 % 5.0 2.6 2.5 5.2 5.6 4.2 7.1 4.1 1.1 5.6 P-value 0.671 0.257 0.809 0.505 0.241 h hraoeoisJournal Pharmacogenomics The Grading G1 n 9677014113212 % 7.6 5.2 8.8 4.6 0.0 6.5 7.1 5.9 2.3 8.4 G2 n 32 33 21 43 2 62 4 60 27 37 % 26.9 28.7 26.3 28.1 11.1 28.8 28.6 27.4 30.3 25.9 G3 n 78 76 52 103 16 139 9 146 60 94 % 65.5 66.1 65.0 67.3 88.9 64.7 64.3 66.7 67.4 65.7 P-value 0.836 0.589 0.034 0.843 0.574 165 DNA-damage gene polymorphisms in ovarian cancer E Caiola et al 166

Table 5 Correlation between PFS, OS and polymorphisms in early stages

Univariate analysis Multivariate analysisa

HR Lower Upper w2 P-value HR Lower Upper w2 P-value 95% HR 95% HR 95% HR 95% HR

Progression-free survival mdm2 rs2279744 T/T 1 0.016 0.900 1 0.563 0.453 T/G, G/G 0.96 0.49 1.86 0.77 0.39 1.53 ercc1 rs11615 T/T 1 0.016 0.901 1 0.078 0.780 T/C, C/C 1.04 0.53 2.08 1.11 0.54 2.27 rs3212986 A/A 1 0.451 0.502 1 0.074 0.786 C/A, C/C 0.75 0.33 1.73 0.88 0.36 2.16 xpg rs17655 C/C 1 2.785 0.095 1 3.142 0.076 C/G, G/G 0.47 0.19 1.14 0.43 0.17 1.09 rs1047768 C/C 1 0.011 0.917 1 0.010 0.919 C/T, T/T 1.04 0.51 2.12 1.04 0.50 2.14 Overall survival mdm2 rs2279744 T/T 1 0.469 0.493 1 2.050 0.152 T/G, G/G 0.77 0.37 1.61 0.56 0.26 1.24 ercc1 rs11615 T/T 1 0.176 0.675 1 0.036 0.850 T/C, C/C 0.85 0.41 1.79 0.93 0.42 2.03 rs3212986 A/A 1 0.001 0.970 1 0.036 0.850 C/A, C/C 0.98 0.37 2.57 0.91 0.32 2.54 xpg rs17655 C/C 1 4.358 0.037 1 4.194 0.041 C/G, G/G 0.38 0.15 0.94 0.37 0.14 0.96 rs1047768 C/C 1 1.272 0.259 1 0.828 0.363 C/T, T/T 1.63 0.70 3.83 1.49 0.63 3.55

Abbreviations: HR, hazard ratio; OS, overall survival; PFS, progression-free survival. aAdjusted by histotype and grading.

association was detected between the genotypes of category switches between the two endpoints (Figure 4). The rs1047768 polymorphism, and the clinical and histopatho- correlation detected in univariate analysis (OS for early-stage logical characteristics of early- and advanced-stage patients malignancy: HR(C/C vs C/G, G/G) ¼ 0.38, 95% CI: 0.15–0.94; (Tables 4–6 and Supplementary Figures 3a–d). The OS P ¼ 0.037; PFS for late-stage malignancy: HR(C/C vs C/G, G/G) pattern for early-stage and the PFS pattern for late-stage ¼ 1.94, 95% CI: 1.03–3.68; P ¼ 0.041) was substantially disease with the rs17655 polymorphism were significantly confirmed in the multivariate analysis (OS for early-stage different when comparing the genotype containing only C malignancy: HR(C/C vs C/G, G/G) ¼ 0.37, 95% CI: 0.14–0.96; with the C/G and G/G genotypes, although the major risk P ¼ 0.041; PFS for late-stage malignancy: HR(C/C vs C/G, G/G)

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Table 6 Correlation between PFS, OS and polymorphisms in late stages

Univariate analysis Multivariate analysisa

HR Lower Upper w2 P-value HR Lower Upper w2 P-value 95% HR 95% HR 95% HR 95% HR

Progression-free survival mdm2 rs2279744 T/T 1 o0.001 0.988 1 0.379 0.538 T/G, G/G 1.00 0.75 1.33 1.10 0.82 1.47 ercc1 rs11615 T/T 1 0.339 0.561 1 0.106 0.744 T/C, C/C 1.09 0.81 1.48 1.05 0.77 1.44 rs3212986 A/A 1 4.150 0.042 1 2.444 0.118 C/A, C/C 0.60 0.37 0.98 0.67 0.40 1.11 xpg rs17655 C/C 1 4.166 0.041 1 4.966 0.026 C/G, G/G 1.94 1.03 3.68 2.12 1.10 4.12 rs1047768 C/C 1 0.391 0.532 1 0.182 0.669 C/T, T/T 0.91 0.68 1.22 0.94 0.69 1.27

Overall survival mdm2 rs2279744 T/T 1 0.014 0.907 1 0.445 0.505 T/G, G/G 1.02 0.76 1.37 1.11 0.82 1.50 ercc1 rs11615 T/T 1 0.223 0.637 1 0.185 0.667 T/C, C/C 1.08 0.79 1.48 0.93 0.67 1.29 rs3212986 A/A 1 5.033 0.025 1 2.908 0.088 C/A, C/C 0.57 0.35 0.93 0.64 0.39 1.07 xpg rs17655 C/C 1 1.722 0.189 1 1.445 0.229 C/G, G/G 1.53 0.81 2.91 1.50 0.77 2.91 rs1047768 C/C 1 0.057 0.811 1 0.243 0.622 C/T, T/T 1.04 0.76 1.41 1.08 0.79 1.48

Abbreviations: HR, hazard ratio; OS, overall survival; PFS, progression-free survival. aAdjusted by histotype, grading and residual tumor size.

¼ 2.12, 95% CI: 1.10–4.12; P ¼ 0.026). We investigated Discussion whether the different genotypes for both rs1047768 and rs17655 polymorphisms were associated with different The search for biomarkers able to identify patients likely to mRNA levels in 85 (23.7%) tumors. No statistically sig- respond to chemotherapy is a major challenge in oncology. nificant differences were found between the groups (P-value Somatic tumor alterations in gene copy numbers, mutations for rs17655: 0.442 and P-value for rs1047768: 0.612; and or deletions in crucial genes have been associated with Supplementary Figures 4e–h). response in several malignancies, including ovarian cancer.

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Figure 2 Correlation between genotypes and mdm2 mRNA expression in tumor samples (n ¼ 50). In panel a the three genotypes were considered separately, whereas in panel b, the T/G and G/G genotypes were grouped and compared with the T/T genotype.

Figure 3 Kaplan–Meier plots for PFS (a) and OS (b) in early, and PFS (c) and OS (d) in late stages, according to the ercc1 polymorphism (rs3212986).

Another important factor likely to influence response to their ability to repair the lesions that have been induced. treatment is the presence of polymorphic variants of genes. Preclinical evidence indicates that cells with low expression Genetic variants of defined genes have been associated with or with functional defects in DNA-repair genes have a better increased risk of cancer in several case–control studies. response to platinum-based treatments.38–40 Increasing evidence is now correlating the activity and In clinical practice the situation is more complex and toxicity of anticancer agents with these variants, alone or in somewhat conflicting results have been reported. A positive association with somatic tumor alterations.37 correlation between expression of the NER gene ercc1, and In ovarian cancer, first-line chemotherapy includes plati- OS or PFS in ovarian cancer patients has been reported by num-based drugs, which are known to cause DNA damage. some authors but not by others.41–43 Similarly, a positive The response of cells to platinum-based therapy depends on correlation between XPG protein expression and response to

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Figure 4 Kaplan–Meier plots for PFS (a) and OS (b) in early, and PFS (c) and OS (d) in late stages, according to the xpg/ercc5 polymorphism (rs17655). therapy has been published, although in other studies this rs17655 polymorphisms, for which the study was suffi- correlation at the RNA level was not found.44,45 ciently powered (1-b ¼ 0.80) to detect a minimum relative It is not surprising that response to therapy is not risk of 2.14 and 2.35 in the PFS endpoint. Unfortunately as a mediated by a single gene; the concomitant presence of consequence of multiple comparisons the probability that at several alterations could be more informative in this least one spurious association giving P-value o0.05 could be context. The determination of both somatic tumor altera- found was estimated at 23% both for early and late stages; tions and patients’ genetic variants could be more important the 1% significance level could be considered more appro- for the identification of therapeutic response markers. In priate than the 5% one, but the study was definitely this context we tried to assess the role of polymorphisms in underpowered for the rs3212986 and rs17655 polymorph- DNA-repair and response genes as determinants of response isms in advanced stages; our findings should be substan- to therapy in ovarian cancer patients. The cohort of patients tiated by an independent confirmatory study.46 analyzed here includes a large proportion of early-stage The mdm2 variant analyzed here could modulate p53 (stage-I/II) patients, rarely available in other studies. This levels and activity.34 p53 expression has been associated offers, together with the potential for long-term clinical with cellular response to platinum treatment.47 It has been follow-up, the unique possibility to determine the impact, if reported that the mdm2 variant analyzed here is not only any, of the variants analyzed in the different subsets of associated with an increased risk of tumor development for patients on clinical outcome. Although we analyzed a large several types of tumor,36,48,49 but it is also correlated to number of early-stage patients, our study was definitely clinical outcome in non-small-cell lung cancer.50 The underpowered to detect difference in relative risk that could analysis of the data of our cohort of patients does not be clinically interesting (HRClinical of at least 2.00–2.50). We suggest that this polymorphism has a role in determining tested the clinically relevant hypothesis of an HR between PFS and/or OS. Similarly, mdm2 allelic variants were not 2.00 and 2.50: consistent with the obtained estimates, this associated with any clinical parameters in early or advanced range could be rejected for three of the five SNPs investi- stages. gated with an a error of no more than 0.08 for both early- ercc1 has been defined as a possible marker of response in and late-stage disease. For late stages, as reported in Table 7, ovarian cancer patients,51 and polymorphisms have been column ‘Inferior limit HR’, under the assumption of associated with response to platinum-based chemotherapy proportional hazard our study could detect with a power in some studies but not confirmed by others.21,52–54 We of 0.80 a 50% difference in PFS and OS risks among three of found significant correlations between the ercc1 variant the five genotypes we compared; instead statistical signifi- (rs3212986) and clinical parameters in both OS and PFS cance was reached in the other two cases, the rs3212986 and endpoints but only in univariate analysis; we also found a

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Table 7 Study power and clinically relevant hypothesis test the genotype in these two loci is not a determinant of ERCC1 activity. These findings, together with our observa- Inferior limit HRa P-value (a error) tion, would be against a possible role of ERCC1 as biomarker for activity, in spite of the strong connection observed in ‘in PFS OS PFS OS vitro’ systems. It is worth mentioning that a strong correla- tion between ERCC1 and platinum response is observed in HR ¼ 2HR¼ 2.5 HR ¼ 2HR¼ 2.5 isogenic systems differing in the presence/absence of ERCC1.38 When different cell lines with different expres- Early stages mdm2 sions of ercc1 are considered, the correlation is lost. Unless a rs2279744 clear relationship between ERCC1 protein expression and T/T 2.58 2.78 0.055 0.010 0.242 0.077 platinum response is found in clinical practice, we should T/G, G/G consider ERCC1 as a determinant of platinum activity only when it is not present. Small amounts of ERCC1 could be ercc1 sufficient to assure NER function as demonstrated in rs11615 preclinical studies. T/T 2.63 2.85 0.064 0.013 0.157 0.045 T/C, C/C In our retrospective study, we found a statistically significant correlation between the xpg genotype (rs17655) rs3212986 A/A 3.58 3.97 0.335 0.136 0.170 0.068 in stage-I/II and stage-III/IV ovarian cancer with OS and PFS C/A, C/C endpoints, respectively. Although not statistically signifi- cant, point estimates of PFS relative risk for early stages and xpg OS relative risk for late stages are consistent with this result. rs17655 The presence of a G-containing genotype is associated with a C/C 4.75 5.38 0.887 0.727 0.548 0.902 better prognosis in early-stage and with a worst prognosis in C/G, G/G late-stage disease. This SNP is located in the C-terminus of rs1047768 the XPG protein, which is required for the interactions C/C 2.72 2.94 0.072 0.016 0.641 0.327 C/T, T/T between XPG and other components of the NER machinery such as XPB, XPD, p62 and p44 subunits of the transcription Late stages factor IIH in the incision complex of NER. The amino-acid mdm2 change from Asp to His could alter the protein binding and rs2279744 therefore modify NER efficiency. The physiopathology of T/T 1.50 1.52 o0.001 o0.001 o0.001 o0.001 early and late ovarian cancer seems to be different.55 It could T/G, G/G be hypothesized that in early stages the presence of a more ercc1 active NER does not influence the response to treatment, rs11615 most likely because the tumor has been completely T/T 1.53 1.56 o0.001 o0.001 o0.001 o0.001 eradicated during surgery, but rather improves the ability T/C, C/C of damaged cells to repair intrinsic DNA damage, limiting rs3212986 genomic instability. Late-stage ovarian cancer is often not A/A 2.14 2.20 0.463 0.104 0.601 0.158 completely eradicated during surgery and cancer cells are C/A, C/C treated with a platinum-based compound, which is a substrate of NER. The presence of a more active NER would xpg rs17655 determine, in this case, a resistance to cell death in 56,57 C/C 2.35 2.42 0.931 0.440 0.416 0.134 accordance with what is reported in the literature. C/G, G/G xpg expression has been widely reported to be associated 39 rs1047768 with platinum activity in preclinical studies and has been C/C 1.52 1.54 o0.001 o0.001 o0.001 o0.001 suggested as a possible biomarker for ovarian cancer patients C/T, T/T as its protein expression correlates with response to treat-

Abbreviations: HR, hazard ratio; OS, overall survival; PFS, progression-free survival. ment. Our data increase the importance of the xpg gene, aa ¼ 0.05; b ¼ 0.20. especially considering the fact that we have recently demonstrated that in a small but significant proportion of patients (roughly 20%) the xpg gene is methylated at the positive correlation between this polymorphism, and tumor level.58 The combination of genotypes and DNA residual tumor and grading. These correlations explain methylation could be taken as an alternative to the why the ercc1 variant was not selected as an independent determination of XPG protein expression. In fact DNA prognostic factor in multivariate analysis, but the data may analysis is much easier and more reliable than determina- indicate that this particular SNP could favor tumor metas- tion of XPG protein expression. The use of a simple tasis and makes the cancer more difficult to eradicate. These diagnostic analysis such as the xpg genotype and extension results do not rule out a role for ERCC1 in determining to other possibly relevant genotypes could be of use in response to platinum-based therapy, but rather suggest that stratifying patients for therapy.

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