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DNA-Damage Response Gene Polymorphisms and Therapeutic Outcomes in Ovarian Cancer

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DNA-Damage Response Gene Polymorphisms and Therapeutic Outcomes in Ovarian Cancer 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 gene 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 genes 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; ercc5/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 gene expression patterns, either at the RNA or protein level. Platinum-induced lesions are mostly repaired by nucleotide excision repair (NER), but also by homologous recombination, 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 proteins 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 colorectal cancer. 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 Xeroderma pigmentosum 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 Transcription 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 promoter 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 The Pharmacogenomics Journal DNA-damage gene polymorphisms in ovarian cancer E Caiola et al 161 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%).
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