Abstract
Survival in epithelial ovarian cancer (EOC) is influenced by the host immune response, yet the key genetic determinants of inflammation and immunity that affect prognosis are not known. The nuclear factor-κB (NF-κB) transcription factor family plays an important role in many immune and inflammatory responses, including the response to cancer. We studied common inherited variation in 210 genes in the NF-κB family in 10,084 patients with invasive EOC (5,248 high-grade serous, 1,452 endometrioid, 795 clear cell, and 661 mucinous) from the Ovarian Cancer Association Consortium. Associations between genotype and overall survival were assessed using Cox regression for all patients and by major histology, adjusting for known prognostic factors and correcting for multiple testing (threshold for statistical significance, P < 2.5 × 10−5). Results were statistically significant when assessed for patients of a single histology. Key associations were with caspase recruitment domain family, member 11 (CARD11) rs41324349 in patients with mucinous EOC [HR, 1.82; 95% confidence interval (CI), 1.41–2.35; P = 4.13 × 10−6] and tumor necrosis factor receptor superfamily, member 13B (TNFRSF13B) rs7501462 in patients with endometrioid EOC (HR, 0.68; 95% CI, 0.56–0.82; P = 2.33 × 10−5). Other associations of note included TNF receptor–associated factor 2 (TRAF2) rs17250239 in patients with high-grade serous EOC (HR, 0.84; 95% CI, 0.77–0.92; P = 6.49 × 10−5) and phospholipase C, gamma 1 (PLCG1) rs11696662 in patients with clear cell EOC (HR, 0.43; 95% CI, 0.26–0.73; P = 4.56 × 10−4). These associations highlight the potential importance of genes associated with host inflammation and immunity in modulating clinical outcomes in distinct EOC histologies. Cancer Epidemiol Biomarkers Prev; 23(7); 1421–7. ©2014 AACR.
Introduction
Epithelial ovarian cancer (EOC) is the sixth leading cause of cancer death among women in developed countries (1), with a 5-year survival rate of only 37% in the United States (2). A key cause of poor survival is a lack of specific symptoms and screening methods; as such, the majority of patients with EOC present with distant spread of disease. A number of features in addition to stage are known to impact clinical outcome, including age at diagnosis (3), extent of residual disease following initial cytoreductive surgery (optimal vs. suboptimal; ref. 4), and baseline performance status (5). Genetic polymorphisms may also influence EOC survival (6, 7). Understanding the totality of potential prognostic factors is key to discerning pathogenic mechanisms that underlie carcinogenesis and progression in EOC. Inflammation is known to play a role tumorigenesis (8); inflammation from multiple causes, including talc use (9) and endometriosis (9, 10), and the presence of nonspecific inflammatory markers such as C-reactive protein (CRP) are associated with increased EOC risk (11). Furthermore, the presence of an ongoing inflammatory response, measured by CRP and hypoalbuminemia, has been shown to independently predict poor prognosis in advanced EOC (12).
The nuclear factor-κB (NF-κB) family of transcription factors regulates the transcription of multiple proteins, including cytokines, chemokines, acute-phase reactants, complement factors, adhesion molecules, and other proteins involved in inflammation, apoptosis, and cell division (13). In canonical NF-κB signaling, binding of NF-κB–associated receptors leads to phosphorylation and activation of the inhibitor of κB kinase (IKK) complex, which leads to phosphorylation and proteosomal degradation of the inhibitor of κB (IκB), thus releasing NF-κB transcription factors into the nucleus to regulate gene transcription (14). Alternatively, receptor binding and IKK activation can lead to processing of the p100 protein into active p52, which binds the NF-κB family member Rel-B, translocates to the nucleus, and regulates gene transcription (14). To assess the role of genetic variation in NF-κB signaling on EOC survival, we evaluated common inherited single nucleotide polymorphisms (SNP) in key genes, which mediate NF-κB activation, inhibit NF-κB function, assist degradation, or regulate nuclear function among patients from the Ovarian Cancer Association Consortium (OCAC).
Materials and Methods
Study participants
A total of 10,084 women with invasive EOC (37,171 person-years follow-up) and greater than 90% estimated European ancestry were analyzed as described previously (15, 16). Participants were from 28 OCAC studies (Supplementary Table S1) based in Europe, North America, and Australia, which conducted follow-up for vital status, including 12 studies (AUS, BAV, HAW, HSK, LAX, MAL, MAY, NCO, NEC, ORE, PVD, and SRO) followed for disease recurrence or progression.
SNP selection
We identified 210 key genes (Supplementary Table S2) known to encode NF-κB subunits or molecules key to NF-κB activation (in signaling cascade), inhibition (inhibitory role), degradation (involved in proteasomal degradation), and nuclear function (nuclear proteins involved in transcription; ref. 6). TagSNPs within 5 kb based on r2 ≥0.8, minor allele frequency (MAF) ≥0.05 in Europeans were identified using the most informative source for each gene from among HapMap Phase II Release 24 (http://www.hapmap.org), the 1000 Genomes Project Low-Coverage Pilot (http://www.1000genomes.org/), SeattleSNPs (http://pga.gs.washington.edu/), Innate Immunity PGA (http://innateimmunity.net/), and NIEHS SNPs (http://egp.gs.washington.edu; ref. 17). Additional putative-functional SNPs were also included, regardless of linkage disequilibrium, with European MAF ≥0.05, which were 1 kb upstream, nonsynonymous, or resided in a 3′-untranslated region (UTR), 5′-UTR, splice site, or miRNA binding site (http://www.microrna.org/microrna/home.do, http://www.targetscan.org/). Finally, SNPs with an Illumina design score <0.4 or in linkage disequilibrium (r2 > 0.80) with a SNP found to be null (P > 0.05) in a small prior analysis (16) were excluded. With this approach, 76% of significant SNPs with MAF ≥ 0.05 were adequately tagged if we used HapMap as our reference.
Genotyping and quality control
Germline genotyping was conducted using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS; ref. 16). Centralized genotyping used raw intensity data files and a cluster file generated with HapMap2 European, African, and Asian samples. Samples were excluded with (i) conversion rate <95%, (ii) heterozygosity > 5 SDs from the European mean heterozygosity, (iii) ambiguous sex, (iv) lowest call rate from an observed first-degree relative pair, or (v) duplicate samples that were nonconcordant for genotype or genotypic duplicates that were not concordant for phenotype. SNPs were excluded with (i) no genotype call, (ii) monomorphism, (iii) call rate <95% with MAF >0.05 or call rate <99% with MAF <0.05, (iv) deviation from Hardy–Weinberg equilibrium (P < 10−7), or (v) >2% duplicate discordance.
SNP imputation
Imputation to the 1000 Genomes (1000G) Phase I Integrated Release Version 3 haplotypes was carried out in MaCH (18) using all 1,092 1000G samples and excluding monomorphic and singleton sites.
Statistical methods
HapMap2 genotypes were used to define intercontinental ancestry; among Europeans (>90% European ancestry), we used 37,000 unlinked non-NF-κB markers in population stratification principal components analysis (16). Cox regression accounting for left truncation and right censoring at 10 years estimated hazard ratios (HR) and 95% confidence intervals (CI) for association with overall survival (OS), defined as time to death from any cause. Censoring at 10 years was performed to minimize competing causes of mortality, which become more common after 10 years from EOC diagnosis. HRs were calculated based on the ordinal number of copies of the minor allele for all genotyped SNPs and allele dosage variables for all imputed SNPs. Analyses were conducted overall and within the 4 most common histologic subtypes (high-grade serous, mucinous, endometrioid, and clear cell). Analyses adjusted for study site and the first 5 population substructure principal components, as well as the following covariates, which associated with survival in these data (P < 0.05; Supplementary Table S3): age (continuous), tumor stage summarized from FIGO or SEER stage (localized, regional, distant), tumor grade (well, moderately, poorly, or undifferentiated), oral contraceptive use (ever, never), and, for analysis of all cases only, histology (serous, mucinous, endometrioid, clear cell, mixed cell, undifferentiated, unknown). Sensitivity analyses included covariates only for age, 5 population substructure principal components, and study site. Analyses were also conducted with a recurrence endpoint defined as time to disease recurrence or death (377 additional events), among cases that were optimally debulked in cytoreductive surgery (2,078 cases having no residual deposits of cancer that were >1 cm) and among cases where surgical debulking was suboptimal (1,215 cases with >1 cm residual disease).
To address multiple testing concerns, we used spectral decomposition of the observed genotype matrix (19) to account for observed linkage disequilibrium and estimated that the effective number of independent tests for each analysis was 2,000. As a result, only SNPs with P-values <2.50 × 10−5 (0.05/2,000) were considered statistically significant. We used SAS (SAS Institute Inc.) and R (R Foundation for Statistical Computing), and, in regions of interest, LocusZoom (Standalone Version; ref. 20) and Haploreg v2 (21) for plotting and annotation, respectively.
Results
We analyzed 2,254 SNPs in 210 genes for clinical outcome among 10,084 EOC cases. The strongest survival association in any of the histology subgroups was seen in 661 mucinous EOC with the CARD11 intronic SNP rs41324349 (HR, 1.82; P = 4.13 × 10−6; Table 1). In addition, 5 of the 56 genotyped CARD11 SNPs were associated at P < 0.005, including 2 independent SNPs (r2 < 0.20) with P < 0.001 (Table 1). The distribution of P-values and correlation with rs41324349 across CARD11 are shown in Fig. 1 for both directly genotyped and imputed SNPs. Imputation revealed that the CARD11 SNP rs2527513, which was in strong linkage disequilibrium with rs41324349, was highly correlated with survival. For 1,452 patients with endometrioid EOC, the TNFRSF13B 3′-UTR SNP rs7501462 showed the strongest association (HR, 0.68; P = 2.33 × 10−5). Of 18 additional TNFRSF13B SNPs, 2 others (rs7212800 and rs11078362) showed association (P < 0.005) in patients with endometrioid EOC; these additional SNPs were in moderate linkage disequilibrium with rs7501462 (r2 = 0.26 and 0.76, respectively).
Strength of association between CARD11 genotypes and survival of women with mucinous EOC (N = 661). Adjusted for study site, first 5 European ancestry population substructure principal components, age at diagnosis, tumor stage, tumor grade, and oral contraceptive use.
SNP association with EOC OS (P < 0.001, r2 < 0.20)
For 5,248 patients with high-grade serous EOC, the TRAF2 SNP rs17250239 showed the most significant association (HR, 0.84; P = 6.49 × 10−5), although this was just beyond our pathway-wide threshold for statistical significance (P < 2.50 × 10−5). The rs17250239 SNP is located in an intronic sequence within the TRAF2 gene. In 795 patients with clear cell EOC, PLCG1 rs11696662 showed the most significant association (HR, 0.43; P = 4.56 × 10−4), but this was not within our pathway-wide threshold for statistical significance. Finally, among all cases, the SNPs rs61764220 and rs518162 (within the genes MAPK3 and PGR, respectively) had the strongest survival associations (HR, 0.81;P = 6.50 × 10−4 and HR, 0.87; P = 8.11 × 10−4, respectively; Table 1). However, these results did not meet our threshold for statistical significance taking into account multiple comparisons (P < 2.50 × 10−5), and so there were not clear associations between polymorphisms in MAPK3 and PGR and survival in EOC.
In addition to OS, we performed sensitivity analyses for time to recurrence, examined results from minimally adjusted analyses, and assessed optimally debulked and suboptimally debulked patients separately. The HRs for recurrence were similar to HRs for survival with and without full covariate adjustment for each of the SNPs that we had considered to have the most significant associations with survival (P < 0.0001) and among optimally debulked compared with suboptimally debulked patients (available on one-third of participants; data not shown).
Discussion
In this pooled analysis of more than 10,000 patients with EOC enrolled in 28 different studies within OCAC, we evaluated associations between NF-κB–related SNPs with survival. We did not identify SNPs associating with OS among all patients with EOC that met our corrected threshold for statistical significance. However, we identified 3 SNPs, rs41324349, rs2527513, and rs7501462, which associated with OS and time to recurrence for EOC subtypes accounting for known prognostic factors. The CARD11 intronic SNPs rs41324349 and rs2527513 were in high linkage disequilibrium with each other and were associated with shortened survival in patients with mucinous EOC, whereas TNFRSF13B 3′-UTR rs7501462 associated with improved outcome among patients with endometrioid EOC. Sensitivity analyses showed concordance between HRs for OS and time to recurrence, and among optimally debulked patients.
CARD11, also known as Carma 1, is an adapter protein that functions as a molecular scaffold in leukocytes (22). CARD11 interacts with the proapoptotic protein BCL10, and overexpression of CARD11 leads to increased NF-κB activation (23). Oncogenic mutations in CARD11 have been reported in association with several types of lymphoma (24). The expression of CARD11 in leukocytes suggests that it may influence immune/inflammatory responses to EOC. rs41324349 lies within 7 regulatory motifs that would be altered by the base change, which could potentially alter transcription; however, this SNP is not in a conserved domain. Six additional intronic and 1 synonymous SNPs located in regulatory motifs were correlated with this SNP (r2 ≥ 0.6). Primary mucinous EOC is relatively uncommon, and mechanisms responsible for tumorigenesis, invasion, and metastasis that are specific for mucinous subtype have not yet been clearly demonstrated. Thus, it is not clear how a change in expression or function of CARD11 would affect survival specifically in this subgroup.
TNFRSF13B, more commonly known as transmembrane activator and calcium-modulating cyclophilin ligand interactor (TACI), is a member of the tumor necrosis factor (TNF) receptor superfamily and is found on B lymphocytes (25). TACI interacts with the TNF family members B-cell–activating factor (BAFF) and a proliferation-inducing ligand (APRIL) to activate NF-κB and other transcription factors in B cells. It is not known whether rs7501462 affects TNFRSF13B expression, and it is not located in an evolutionarily conserved domain; however, it falls in a strong enhancer region and POL2 binding site in B-lymphoblastoid cell lines. As the primary pathologic process associated with endometrioid ovarian carcinomas is endometriosis, alterations in TNFRSF13B that affect inflammatory responses to endometriosis may modulate the aggressiveness of endometriosis-associated carcinomas.
Interestingly, although SNPs associated with survival were identified for relatively rare histologies (mucinous and endometrioid histologies), there were no SNP associations identified for the most common EOC histology (high-grade serous). This may simply reflect underdetection of SNPs because of a relatively stringent statistical threshold for significance, as there were several SNPs, most notably rs17250239 (HR, 0.84; P = 6.49 × 10−5), which had survival associations not quite meeting our prespecified threshold for significance (P < 2.5 × 10−5). However, this may also reflect that survival high-grade serous EOC, which is characterized by dramatic alterations in DNA macrostructure, may be more closely associated with certain amplified or deleted regions of DNA rather than alterations at the single nucleotide level.
The search for inherited variants associated with EOC outcome has proven challenging, with no published variants reaching genome-wide significance to date (15, 26). Here, by testing a candidate pathway within a consortium, we identified 2 SNPs from NF-κB–related genes that associated with survival in patients with distinct histologic subtypes of EOC using a pathway-wide statistical significance threshold. Strengths of this report include large sample size and use of centralized genotyping; limitations include missing data on surgical debulking status. For example, analysis by debulking status classified patients based on whether <1 cm or ≥1 cm residual disease was present, as opposed to complete debulking (no visible residual disease); thus, association in certain patient subsets may have been overlooked. In addition, for some population-based studies, there was possible over-enrollment of women with longer survival; this could also bias results to the null if NF-κB SNPs associate only with very poor survival time.
As additional outcome-associated variants come to light, further work will address the potential prognostic utility of a broad panel of outcome-associated SNPs. For now, we provide evidence that the genetics of the immune/inflammatory response to EOC may impact clinical outcome and suggest that characterization of functional mechanisms will be a key next step to understanding this deadly disease.
Disclosure of Potential Conflicts of Interest
B. Charbonneau is an employee at Eli Lilly and Company and also has ownership interest (including patents) in the same. U. Menon has ownership interest (including patents) in Abcodia. No potential conflicts of interest were disclosed by the other authors.
Authors' Contributions
Conception and design: G. Chenevix-Trench, H.A. Culver, B.Y. Karlan, L.A. Brinton, A. Ziogas, S.A. Gayther, A. Berchuck, K.L. Knutson, K.R. Kalli, B.L. Fridley, E.L. Goode
Development of methodology: M.S. Block, R.A. Vierkant, G. Chenevix-Trench, L.A. Brinton, E.L. Goode
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): P.D.P. Pharoah, G. Chenevix-Trench; M.A. Rossing, D. Cramer, C.L. Pearce, J. Schildkraut, U. Menon, S.K. Kjaer, D.A. Levine, J. Gronwald, H.A. Culver, A.S. Whittemore, B.Y. Karlan, D. Lambrechts, N. Wentzensen, J. Kupryjanczyk, J. Chang-Claude, E.V. Bandera, F. Heitz, S.B. Kaye, P.A. Fasching, I. Campbell, M.T. Goodman, T. Pejovic, Y.T. Bean, L.E. Hays, G. Lurie, D. Eccles, A. Hein, M.W. Beckmann, A.B. Ekici, J. Paul, R. Brown, J.M. Flanagan, P. Harter, A. du Bois, C.K. Hogdall, S.H. Olson, I. Orlow, L.E. Paddock, A. Rudolph, U. Eilber, A. Dansonka-Mieszkowska, I.K. Rzepecka, I. Ziolkowska-Seta, L.A. Brinton, M. Garcia-Closas, E. Despierre, S. Lambrechts, I. Vergote, C.S. Walsh, J. Lester, W. Sieh, V. McGuire, J.H. Rothstein, A. Ziogas, J. Lubiński, C. Cybulski, J. Menkiszak, A. Jensen, S.A. Gayther, S.J. Ramus, A. Gentry-Maharaj, A.H. Wu, M.C. Pike, D. Van Den Berg, K.L. Terry, S.M. Ramirez, D.N. Rider, J.A. Doherty, S.E. Johnatty, A. deFazio, H. Song, K.R. Kalli, J.M. Cunningham
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): M.S. Block, B. Charbonneau, R.A. Vierkant, Z. Fogarty, W.R. Bamlet, M.A. Rossing, D. Cramer, C.L. Pearce, U. Menon, B.Y. Karlan, D. Lambrechts, N. Wentzensen, A. du Bois, H. Yang, I. Vergote, W. Sieh, A. Berchuck, D.N. Rider, K.L. Knutson, J. Tyrer, B.L. Fridley
Writing, review, and/or revision of the manuscript: M.S. Block, B. Charbonneau, R.A. Vierkant, W.R. Bamlet, P.D.P. Pharoah, G. Chenevix-Trench, J. Schildkraut, U. Menon, S.K. Kjaer, J. Gronwald, H.A. Culver, A.S. Whittemore, B.Y. Karlan, D. Lambrechts, N. Wentzensen, J. Chang-Claude, E.V. Bandera, E. Hogdall, F. Heitz, P.A. Fasching, I. Campbell, M.T. Goodman, D. Eccles, A.B. Ekici, R. Brown, P. Harter, A. du Bois, C.K. Hogdall, S.H. Olson, I. Orlow, L.E. Paddock, A. Rudolph, L.A. Brinton, H. Yang, M. Garcia-Closas, I. Vergote, J. Lester, W. Sieh, V. McGuire, A. Ziogas, J. Lubiński, A. Jensen, S.A. Gayther, S.J. Ramus, A. Berchuck, A.H. Wu, K.L. Terry, D.N. Rider, K.L. Knutson, T.A. Sellers, C.M. Phelan, J.A. Doherty, S.E. Johnatty, A. deFazio, H. Song, J. Tyrer, K.R. Kalli, B.L. Fridley, J.M. Cunningham, E.L. Goode
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): D.A. Levine, D. Lambrechts, E. Hogdall, P.A. Fasching, D. Eccles, M.W. Beckmann, A.B. Ekici, J. Paul, R. Brown, I. Schwaab, C.K. Hogdall, L. Lundvall, A. Rudolph, A. Dansonka-Mieszkowska, E. Despierre, C. Cybulski, J. Menkiszak, S.J. Ramus, A. Berchuck, M.C. Pike, A.F. Vitonis, S.M. Ramirez, D.N. Rider, E.L. Goode
Study supervision: P.D.P. Pharoah, S.K. Kjaer, D. Lambrechts, N. Wentzensen, S. Lambrechts, C.S. Walsh, A. Berchuck
Grant Support
This study was supported by funding from several sources including the Ovarian Cancer Research Fund thanks to donations by the family and friends of K.S. Smith (PPD/RPCI.07); the Genetic Associations and Mechanisms in Oncology (GAME-ON): an NCI Cancer Post-GWAS Initiative (U19-CA148112 and U19-CA148537); the European Community's Seventh Framework Programme under grant agreement No. 223175 (HEALTH-F2-2009-223175); the Canadian Institutes for Health Research (CIHR) MOP-86727 and the CIHR Team in Familial Risks of Breast Cancer; the American Cancer Society (CRTG-00-196-01-CCE); the California Cancer Research Program (00-01389V-20170, N01-CN25403, 2II0200); the Canadian Institutes for Health Research; Cancer Council Victoria; Cancer Council Queensland; Cancer Council New South Wales; Cancer Council South Australia; Cancer Council Tasmania; Cancer Foundation of Western Australia; the Cancer Institute of New Jersey; Cancer Research UK (C490/A6187, C490/A10119, C490/A10124, C536/A13086, C536/A6689, C1287/A10118, C1287/A 10710, C12292/A11174, C5047/A8384, C5047/A15007, C5047/A10692); the Celma Mastry Ovarian Cancer Foundation; the Danish Cancer Society (94-222-52); the ELAN Program of the University of Erlangen-Nuremberg; the Eve Appeal; the Helsinki University Central Hospital Research Fund; Helse Vest; Imperial Experimental Cancer Research Centre (C1312/A15589); the Norwegian Cancer Society; the Norwegian Research Council; the Ovarian Cancer Research Fund; National Kankerplan of Belgium; the L. & S. Milken Foundation; the Polish Ministry of Science and Higher Education; the US National Cancer Institute (K07-CA095666, K07-CA143047, K22-CA138563, N01-CN55424, N01-PC067010, N01-PC035137, P01-CA017054, P01-CA087696, P20-GM103418, P30-CA072720, P30-CA15083, P30-CA168524, P50-CA105009, P50-CA136393, R01-CA014089, R01-CA016056, R01-CA017054, R01-CA049449, R01-CA050385, R01-CA054419, R01-CA058598, R01-CA058860, R01-CA061107, R01-CA061132, R01-CA063682, R01-CA064277, R01-CA067262, R01-CA071766, R01-CA074850, R01-CA076016, R01-CA080742, R01-CA080978, R01-CA128978, R01-CA083918, R01-CA087538, R01-CA092044, R01-095023, R01-CA106414, R01-CA122443, R01-CA61107, R01-CA112523, R01-CA114343, R01-CA126841, R01-CA136924, R01-CA149429, R03-CA113148, R03-CA115195, R21-GM86689, R37-CA070867, R37-CA70867, U01-CA069417, U01-CA071966, and Intramural research funds); the US Army Medical Research and Material Command (DAMD17-98-1-8659, DAMD17-01-1-0729, DAMD17-02-1-0666, DAMD17-02-1-0669, W81XWH-10-1-0280, W81XWH-10-1-0341); the National Health and Medical Research Council of Australia (199600, 400413, and 400281); the German Federal Ministry of Education and Research of Germany Programme of Clinical Biomedical Research (01 GB 9401); the state of Baden-Württemberg through Medical Faculty of the University of Ulm (P.685); the Minnesota Ovarian Cancer Alliance; the Mayo Foundation; the Fred C. and Katherine B. Andersen Foundation; the Lon V. Smith Foundation (LVS-39420); the Polish Committee for Scientific Research (4P05C 028 14 and 2P05A 068 27); the Oak Foundation; the OHSU Foundation; the Mermaid I project; the Rudolf-Bartling Foundation; the UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; Imperial College London; University College Hospital “Womens Health Theme” and the Royal Marsden Hospital; WorkSafeBC; Komen Foundation for the Cure; and the Breast Cancer Research Foundation. G. Chenevix-Trench and P.M. Webb are supported by the Australian National Health and Medical Research Council, B. Karlan holds an American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN), and A. Berchuck holds the Barbara Thomason Ovarian Cancer Research Professorship from the American Cancer Society (SIOP-06-090-06).
Footnotes
Note: Supplementary data for this article are available at Cancer Epidemiology, Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).
- Received September 23, 2013.
- Revision received March 27, 2014.
- Accepted April 9, 2014.
- ©2014 American Association for Cancer Research.
References
Volume 23, Issue 7
