The prospect of discovering new biomarkers for ovarian cancer based on current knowledge of susceptibility loci and genetic variation (Review)

Christophersen,Mikael   Kronborg; Høgdall,Claus; Høgdall,Estrid

doi:10.3892/ijmm.2019.4352

The prospect of discovering new biomarkers for ovarian cancer based on current knowledge of susceptibility loci and genetic variation (Review)

Authors:
- Mikael Kronborg Christophersen
- Claus Høgdall
- Estrid Høgdall
View Affiliations

Affiliations: Molecular Unit, Department of Pathology, Herlev and Gentofte Hospital, Copenhagen University Hospital, 2730 Herlev, Denmark, The Juliane Marie Centre, Department of Gynaecology, Rigshospitalet, Copenhagen University Hospital, 2100 Copenhagen, Denmark
Published online on: September 26, 2019 https://doi.org/10.3892/ijmm.2019.4352
Pages: 1599-1608

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

Ovarian cancer is the most lethal gynaecological malignancy. The cancer initially presents with non‑specific symptoms; thus, it is typically not discovered until the patient has reached the late, considerably more lethal, stages of the disease. Research focus is currently on finding novel biomarkers, especially for early detection and stratification of the disease. One promising approach has been to focus on mutations or variations in the genetic code that are associated with the risk of developing ovarian cancer. A certain heritable component is already known regarding genes such as BRCA1/2, TP53, MSH6, BRIP1 and RAD51C, yet these are estimated to only account for ~3.1% of the total risk. Recent advances in sequencing technologies have enabled the investigation of hundreds of thousands of genetic variants in genome‑wide association studies in tens of thousands of patients, which has led to the discovery of 108 (39 loci with P<5.0x10‑8) novel susceptibility loci for ovarian cancer, presented in this review. Using the published variants in a patient cohort screening, together with variants identified in our ongoing whole exome sequencing project, future aims are to ascertain whether certain of the novel variants could be used as biomarkers for early diagnosis and/or treatment decisions.

View Figures

View References

1	Stewart BW and Wild CP: World Cancer Report 2014. 2014.
2	Danish Gynecologic Cancer Group: Annual Report of the Danish Gynecologic Cancer Database 2016-17. Danish Gynecol Cancer Database. 2017.
3	Goff BA, Mandel LS, Drescher CW, Urban N, Gough S, Schurman KM, Patras J, Mahony BS and Andersen MR: Development of an ovarian cancer symptom index: Possibilities for earlier detection. Cancer. 109:221–227. 2007. View Article : Google Scholar
4	Hamilton W, Peters TJ, Bankhead C and Sharp D: Risk of ovarian cancer in women with symptoms in primary care: Population based case-control study. BMJ. 339:b29982009. View Article : Google Scholar : PubMed/NCBI
5	Sundar S, Neal RD and Kehoe S: Diagnosis of ovarian cancer. BMJ. 351:h44432015. View Article : Google Scholar : PubMed/NCBI
6	Köbel M, Kalloger SE, Boyd N, McKinney S, Mehl E, Palmer C, Leung S, Bowen NJ, Ionescu DN, Rajput A, et al: Ovarian carcinoma subtypes are different diseases: Implications for biomarker studies. PLoS Med. 5:e2322008. View Article : Google Scholar : PubMed/NCBI
7	Prat J: Ovarian carcinomas: Five distinct diseases with different origins, genetic alterations, and clinicopathological features. Virchows Arch. 460:237–249. 2012. View Article : Google Scholar : PubMed/NCBI
8	Vaughan S, Coward JI, Bast RC Jr, Berchuck A, Berek JS, Brenton JD, Coukos G, Crum CC, Drapkin R, Etemadmoghadam D, et al: Rethinking ovarian cancer: Recommendations for improving outcomes. Nat Rev Cancer. 11:719–725. 2011. View Article : Google Scholar : PubMed/NCBI
9	Bast RC Jr, Klug TL, St John E, Jenison E, Niloff JM, Lazarus H, Berkowitz RS, Leavitt T, Griffiths CT, Parker L, et al: A radioim-munoassay using a monoclonal antibody to monitor the course of epithelial ovarian cancer. N Engl J Med. 309:883–887. 1983. View Article : Google Scholar : PubMed/NCBI
10	Hellström I, Raycraft J, Hayden-Ledbetter M, Ledbetter JA, Schummer M, McIntosh M, Drescher C, Urban N and Hellström KE: The HE4 (WFDC2) protein is a biomarker for ovarian carcinoma. Cancer Res. 63:3695–3700. 2003.PubMed/NCBI
11	Karlsen MA, Fagö-Olsen C, Høgdall E, Schnack TH, Christensen IJ, Nedergaard L, Lundvall L, Lydolph MC, Engelholm SA and Høgdall C: A novel index for preoperative, non-invasive prediction of macro-radical primary surgery in patients with stage IIIC-IV ovarian cancer-a part of the Danish prospective pelvic mass study. Tumor Biol. 37:12619–12626. 2016. View Article : Google Scholar
12	Jacobs I, Oram D, Fairbanks J, Turner J, Frost C and Grudzinskas JG: A risk of malignancy index incorporating CA 125, ultrasound and menopausal status for the accurate preoperative diagnosis of ovarian cancer. Br J Obstet Gynaecol. 97:922–929. 1990. View Article : Google Scholar : PubMed/NCBI
13	Moore RG, McMeekin DS, Brown AK, DiSilvestro P, Miller MC, Allard WJ, Gajewski W, Kurman R, Bast RC Jr and Skates SJ: A novel multiple marker bioassay utilizing HE4 and CA125 for the prediction of ovarian cancer in patients with a pelvic mass. Gynecol Oncol. 112:40–46. 2009. View Article : Google Scholar
14	Skates SJ: Ovarian cancer screening: Development of the risk of ovarian cancer algorithm (ROCA) and ROCA screening trials. Int J Gynecol Cancer. 22(Suppl 1): S24–S26. 2012. View Article : Google Scholar : PubMed/NCBI
15	Ueland FR, Desimone CP, Seamon LG, Miller RA, Goodrich S, Podzielinski I, Sokoll L, Smith A, van Nagell JR Jr and Zhang Z: Effectiveness of a multivariate index assay in the preoperative assessment of ovarian tumors. Obstet Gynecol. 117:1289–1297. 2011. View Article : Google Scholar : PubMed/NCBI
16	Karlsen MA, Sandhu N, Høgdall C, Christensen IJ, Nedergaard L, Lundvall L, Engelholm SA, Pedersen AT, Hartwell D, Lydolph M, et al: Evaluation of HE4, CA125, risk of ovarian malignancy algorithm (ROMA) and risk of malignancy index (RMI) as diagnostic tools of epithelial ovarian cancer in patients with a pelvic mass. Gynecol Oncol. 127:379–383. 2012. View Article : Google Scholar : PubMed/NCBI
17	Jacobs IJ and Menon U: Progress and challenges in screening for early detection of ovarian cancer. Mol Cell Proteomics. 3:355–366. 2004. View Article : Google Scholar : PubMed/NCBI
18	Norquist BM, Harrell MI, Brady MF, Walsh T, Lee MK, Gulsuner S, Bernards SS, Casadei S, Yi Q, Burger RA, et al: Inherited mutations in women with ovarian carcinoma. JAMA Oncol. 2:482–490. 2016. View Article : Google Scholar : PubMed/NCBI
19	Ramus SJ, Song H, Dicks E, Tyrer JP, Rosenthal AN, Intermaggio MP, Fraser L, Gentry-Maharaj A, Hayward J, Philpott S, et al: Germline mutations in the BRIP1, BARD1, PALB2, and NBN genes in women with ovarian cancer. J Natl Cancer Inst. 107:djv2142015. View Article : Google Scholar : PubMed/NCBI
20	Kuchenbaecker KB, Ramus SJ, Tyrer J, Lee A, Shen HC, Beesley J, Lawrenson K, McGuffog L, Healey S, Lee JM, et al: Identification of six new susceptibility loci for invasive epithelial ovarian cancer. Nat Genet. 47:164–171. 2015. View Article : Google Scholar : PubMed/NCBI
21	Moher D, Liberati A, Tetzlaff J and Altman DG; PRISMA Group: Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med. 6:e10000972009. View Article : Google Scholar : PubMed/NCBI
22	International Human Genome Sequencing Consortium: Finishing the euchromatic sequence of the human genome. Nature. 431:931–945. 2004. View Article : Google Scholar : PubMed/NCBI
23	The 1000 Genomes Project Consortium; Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA and Abecasis GR: A global reference for human genetic variation. Nature. 526:68–74. 2015. View Article : Google Scholar : PubMed/NCBI
24	Metzker ML: Sequencing technologies-the next generation. Nat Rev Genet. 11:31–46. 2010. View Article : Google Scholar
25	Ashley EA: Towards precision medicine. Nat Rev Genet. 17:507–522. 2016. View Article : Google Scholar : PubMed/NCBI
26	Goodwin S, McPherson JD and McCombie WR: Coming of age: Ten years of next-generation sequencing technologies. Nat Rev Genet. 17:333–351. 2016. View Article : Google Scholar : PubMed/NCBI
27	Blum A, Wang P and Zenklusen JC: SnapShot: TCGA-analyzed tumors. Cell. 173:5302018. View Article : Google Scholar : PubMed/NCBI
28	Cancer Genome Atlas Research Network: Integrated genomic analyses of ovarian carcinoma. Nature. 474:609–615. 2011. View Article : Google Scholar : PubMed/NCBI
29	Amos CI, Dennis J, Wang Z, Byun J, Schumacher FR, Gayther SA, Casey G, Hunter DJ, Sellers TA, Gruber SB, et al: The oncoarray consortium: A network for understanding the genetic architecture of common cancers. Cancer Epidemiol Biomarkers Prev. 26:126–135. 2017. View Article : Google Scholar :
30	Sakoda LC, Jorgenson E and Witte JS: Turning of COGS moves forward findings for hormonally mediated cancers. Nat Genet. 45:345–348. 2013. View Article : Google Scholar : PubMed/NCBI
31	Phelan CM, Kuchenbaecker KB, Tyrer JP, Kar SP, Lawrenson K, Winham SJ, Dennis J, Pirie A, Riggan MJ, Chornokur G, et al: Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer. Nat Genet. 49:680–691. 2017. View Article : Google Scholar : PubMed/NCBI
32	Michailidou K, Beesley J, Lindstrom S, Canisius S, Dennis J, Lush MJ, Maranian MJ, Bolla MK, Wang Q, Shah M, et al: Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer. Nat Genet. 47:373–380. 2015. View Article : Google Scholar : PubMed/NCBI
33	McKay JD, Hung RJ, Han Y, Zong X, Carreras-Torres R, Christiani DC, Caporaso NE, Johansson M, Xiao X, Li Y, et al: Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes. Nat Genet. 49:1126–1132. 2017. View Article : Google Scholar : PubMed/NCBI
34	Schumacher FR, Al Olama AA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, Dadaev T, Leongamornlert D, Anokian E, Cieza-Borrella C, et al: Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci. Nat Genet. 50:928–936. 2018. View Article : Google Scholar : PubMed/NCBI
35	Melin BS, Barnholtz-Sloan JS, Wrensch MR, Johansen C, Il'yasova D, Kinnersley B, Ostrom QT, Labreche K, Chen Y, Armstrong G, et al: Genome-wide association study of glioma subtypes identifies specific differences in genetic susceptibility to glioblastoma and non-glioblastoma tumors. Nat Genet. 49:789–794. 2017. View Article : Google Scholar : PubMed/NCBI
36	Shen H, Fridley BL, Song H, Lawrenson K, Cunningham JM, Ramus SJ, Cicek MS, Tyrer J, Stram D, Larson MC, et al: Epigenetic analysis leads to identification of HNF1B as a subtype-specific susceptibility gene for ovarian cancer. Nat Commun. 4:16282013. View Article : Google Scholar : PubMed/NCBI
37	Pharoah PD, Tsai YY, Ramus SJ, Phelan CM, Goode EL, Lawrenson K, Buckley M, Fridley BL, Tyrer JP, Shen H, et al: GWAS meta‑analysis and replication identifies three new susceptibility loci for ovarian cancer. Nat Genet. 45:362–370. 2013. View Article : Google Scholar
38	Kelemen LE, Lawrenson K, Tyrer J, Li Q, Lee JM, Seo JH, Phelan CM, Beesley J, Chen X, Spindler TJ, et al: Genome-wide significant risk associations for mucinous ovarian carcinoma. Nat Genet. 47:888–897. 2015. View Article : Google Scholar : PubMed/NCBI
39	Tsuchiya A, Sakamoto M, Yasuda J, Chuma M, Ohta T, Ohki M, Yasugi T, Taketani Y and Hirohashi S: Expression profiling in ovarian clear cell carcinoma: Identification of hepatocyte nuclear factor-1beta as a molecular marker and a possible molecular target for therapy of ovarian clear cell carcinoma. Am J Pathol. 163:2503–2512. 2003. View Article : Google Scholar : PubMed/NCBI
40	Gudmundsson J, Sulem P, Steinthorsdottir V, Bergthorsson JT, Thorleifsson G, Manolescu A, Rafnar T, Gudbjartsson D, Agnarsson BA, Baker A, et al: Two variants on chromosome 17 confer prostate cancer risk and the one in TCF2 protects against type 2 diabetes. Nat Genet. 39:977–983. 2007. View Article : Google Scholar : PubMed/NCBI
41	Sun J, Zheng SL, Wiklund F, Isaacs SD, Purcell LD, Gao Z, Hsu FC, Kim ST, Liu W, Zhu Y, et al: Evidence for two independent prostate cancer risk-associated loci in the HNF1B gene at 17q12. Nat Genet. 40:1153–1155. 2008. View Article : Google Scholar : PubMed/NCBI
42	Thomas G, Jacobs KB, Yeager M, Kraft P, Wacholder S, Orr N, Yu K, Chatterjee N, Welch R, Hutchinson A, et al: Multiple loci identified in a genome‑wide association study of prostate cancer. Nat Genet. 40:310–315. 2008. View Article : Google Scholar : PubMed/NCBI
43	Spurdle AB, Thompson DJ, Ahmed S, Ferguson K, Healey CS, O'Mara T, Walker LC, Montgomery SB, Dermitzakis ET; Australian National Endometrial Cancer Study Group; et al: Genome-wide association study identifies a common variant associated with risk of endometrial cancer. Nat Genet. 43:451–455. 2011. View Article : Google Scholar : PubMed/NCBI
44	Painter JN, O'Mara TA, Batra J, Cheng T, Lose FA, Dennis J, Michailidou K, Tyrer JP, Ahmed S, Ferguson K, et al: Fine‑mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk. Hum Mol Genet. 24:1478–1492. 2015. View Article : Google Scholar
45	Setiawan VW, Haessler J, Schumacher F, Cote ML, Deelman E, Fesinmeyer MD, Henderson BE, Jackson RD, Vöckler JS, Wilkens LR, et al: HNF1B and endometrial cancer risk: Results from the PAGE study. PLoS One. 7:e303902012. View Article : Google Scholar : PubMed/NCBI
46	Ross-Adams H, Ball S, Lawrenson K, Halim S, Russell R, Wells C, Strand SH, Ørntoft TF, Larson M, Armasu S, et al: HNF1B variants associate with promoter methylation and regulate gene networks activated in prostate and ovarian cancer. Oncotarget. 7:74734–74746. 2016. View Article : Google Scholar : PubMed/NCBI
47	Pooley KA, Bojesen SE, Weischer M, Nielsen SF, Thompson D, Amin Al Olama A, Michailidou K, Tyrer JP, Benlloch S, Brown J, et al: A genome-wide association scan (GWAS) for mean telomere length within the COGS project: Identified loci show little association with hormone-related cancer risk. Hum Mol Genet. 22:5056–5064. 2013. View Article : Google Scholar : PubMed/NCBI
48	Bojesen SE, Pooley KA, Johnatty SE, Beesley J, Michailidou K, Tyrer JP, Edwards SL, Pickett HA, Shen HC, Smart CE, et al: Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer. Nat Genet. 45:371–384. 2013. View Article : Google Scholar : PubMed/NCBI
49	Vinagre J, Almeida A, Pópulo H, Batista R, Lyra J, Pinto V, Coelho R, Celestino R, Prazeres H, Lima L, et al: Frequency of TERT promoter mutations in human cancers. Nat Commun. 4:21852013. View Article : Google Scholar : PubMed/NCBI
50	Bolton KL, Tyrer J, Song H, Ramus SJ, Notaridou M, Jones C, Sher T, Gentry-Maharaj A, Wozniak E, Tsai YY, et al: Common variants at 19p13 are associated with susceptibility to ovarian cancer. Nat Genet. 42:880–884. 2010. View Article : Google Scholar : PubMed/NCBI
51	Shao G, Patterson-Fortin J, Messick TE, Feng D, Shanbhag N, Wang Y and Greenberg RA: MERIT40 controls BRCA1-Rap80 complex integrity and recruitment to DNA double-strand breaks. Genes Dev. 23:740–754. 2009. View Article : Google Scholar : PubMed/NCBI
52	Wang B, Hurov K, Hofmann K and Elledge SJ: NBA1, a new player in the Brca1 A complex, is required for DNA damage resistance and checkpoint control. Genes Dev. 23:729–739. 2009. View Article : Google Scholar : PubMed/NCBI
53	Feng L, Huang J and Chen J: MERIT40 facilitates BRCA1 localization and DNA damage repair. Genes Dev. 23:719–728. 2009. View Article : Google Scholar : PubMed/NCBI
54	Lawrenson K, Kar S, McCue K, Kuchenbaeker K, Michailidou K, Tyrer J, Beesley J, Ramus SJ, Li Q, Delgado MK, et al: Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus. Nat Commun. 7:126752016. View Article : Google Scholar : PubMed/NCBI
55	Kar SP, Tyrer JP, Li Q, Lawrenson K, Aben KK, Anton-Culver H, Antonenkova N, Chenevix-Trench G; Australian Cancer Study; Australian Ovarian Cancer Study Group; et al: Network-based integration of GWAS and gene expression identifies a HOX-Centric network associated with serous ovarian cancer risk. Cancer Epidemiol Biomarkers Prev. 24:1574–1584. 2015. View Article : Google Scholar : PubMed/NCBI
56	Lawrenson K, Li Q, Kar S, Seo JH, Tyrer J, Spindler TJ, Lee J, Chen Y, Karst A, Drapkin R, et al: Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer. Nat Commun. 6:82342015. View Article : Google Scholar : PubMed/NCBI
57	Ghoussaini M, Song H, Koessler T, Al Olama AA, Kote-Jarai Z, Driver KE, Pooley KA, Ramus SJ, Kjaer SK, Hogdall E, et al: Multiple loci with different cancer specificities within the 8q24 gene desert. J Natl Cancer Inst. 100:962–966. 2008. View Article : Google Scholar : PubMed/NCBI
58	Panagiotou OA, Evangelou E and Ioannidis JP: Genome-wide significant associations for variants with minor allele frequency of 5% or less-an overview: A HuGE review. Am J Epidemiol. 172:869–889. 2010. View Article : Google Scholar : PubMed/NCBI
59	Stephens M and Balding DJ: Bayesian statistical methods for genetic association studies. Nat Rev Genet. 10:681–690. 2009. View Article : Google Scholar : PubMed/NCBI
60	International HapMap Consortium: A haplotype map of the human genome. Nature. 437:1299–1320. 2005. View Article : Google Scholar : PubMed/NCBI
61	Pe'er I, Yelensky R, Altshuler D and Daly MJ: Estimation of the multiple testing burden for genomewide association studies of nearly all common variants. Genet Epidemiol. 32:381–385. 2008. View Article : Google Scholar : PubMed/NCBI
62	Fadista J, Manning AK, Florez JC and Groop L: The (in)famous GWAS P-value threshold revisited and updated for low-frequency variants. Eur J Hum Genet. 24:1202–1205. 2016. View Article : Google Scholar : PubMed/NCBI
63	Kar SP, Berchuck A, Gayther SA, Goode EL, Moysich KB, Pearce CL, Ramus SJ, Schildkraut JM, Sellers TA and Pharoah PDP: Common genetic variation and susceptibility to ovarian cancer: Current insights and future directions. Cancer Epidemiol Biomarkers Prev. 27:395–404. 2018. View Article : Google Scholar
64	Jones MR, Kamara D, Karlan BY, Pharoah PDP and Gayther SA: Genetic epidemiology of ovarian cancer and prospects for poly-genic risk prediction. Gynecol Oncol. 147:705–713. 2017. View Article : Google Scholar : PubMed/NCBI
65	Elmas A, Ou Yang TH, Wang X and Anastassiou D: Discovering genome-wide tag SNPs based on the mutual information of the variants. PLoS One. 11:e01679942016. View Article : Google Scholar : PubMed/NCBI
66	Johnson GC, Esposito L, Barratt BJ, Smith AN, Heward J, Di Genova G, Ueda H, Cordell HJ, Eaves IA, Dudbridge F, et al: Haplotype tagging for the identification of common disease genes. Nat Genet. 29:233–237. 2001. View Article : Google Scholar : PubMed/NCBI
67	Earp M, Winham SJ, Larson N, Permuth JB, Sicotte H, Chien J, Anton-Culver H, Bandera EV, Berchuck A, Cook LS, et al: A targeted genetic association study of epithelial ovarian cancer susceptibility. Oncotarget. 7:7381–7389. 2016. View Article : Google Scholar : PubMed/NCBI
68	Song H, Ramus SJ, Tyrer J, Bolton KL, Gentry-Maharaj A, Wozniak E, Anton-Culver H, Chang-Claude J, Cramer DW, DiCioccio R, et al: A genome‑wide association study identifies a new ovarian cancer susceptibility locus on 9p22.2. Nat Genet. 41:996–1000. 2009. View Article : Google Scholar : PubMed/NCBI
69	Goode EL, Chenevix-Trench G, Song H, Ramus SJ, Notaridou M, Lawrenson K, Widschwendter M, Vierkant RA, Larson MC, Kjaer SK, et al: A genome-wide association study identifies susceptibility loci for ovarian cancer at 2q31 and 8q24. Nat Genet. 42:874–879. 2010. View Article : Google Scholar : PubMed/NCBI
70	Permuth-Wey J, Lawrenson K, Shen HC, Velkova A, Tyrer JP, Chen Z, Lin HY, Chen YA, Tsai YY, Qu X, et al: Identification and molecular characterization of a new ovarian cancer susceptibility locus at 17q21.31. Nat Commun. 4:16272013. View Article : Google Scholar : PubMed/NCBI
71	Chen K, Ma H, Li L, Zang R, Wang C, Song F, Shi T, Yu D, Yang M, Xue W, et al: Genome-wide association study identifies new susceptibility loci for epithelial ovarian cancer in Han Chinese women. Nat Commun. 5:46822014. View Article : Google Scholar : PubMed/NCBI
72	Romano RA, Li H, Tummala R, Maul R and Sinha S: Identification of Basonuclin2, a DNA‑binding zinc‑finger protein expressed in germ tissues and skin keratinocytes. Genomics. 83:821–833. 2004. View Article : Google Scholar : PubMed/NCBI
73	Buckley MA, Woods NT, Tyrer JP, Mendoza-Fandiño G, Lawrenson K, Hazelett DJ, Najafabadi HS, Gjyshi A, Carvalho RS, Lyra PC Jr, et al: Functional analysis and fine mapping of the 9p22.2 ovarian cancer susceptibility locus. Cancer Res. 79:467–481. 2019. View Article : Google Scholar
74	Wentzensen N, Black A, Jacobs K, Yang HP, Berg CD, Caporaso N, Peters U, Ragard L, Buys SS, Chanock S and Hartge P: Genetic variation on 9p22 is associated with abnormal ovarian ultrasound results in the prostate, lung, colorectal, and ovarian cancer screening trial. PLoS One. 6:e217312011. View Article : Google Scholar : PubMed/NCBI
75	Vigorito E, Kuchenbaecker KB, Beesley J, Adlard J, Agnarsson BA, Andrulis IL, Arun BK, Barjhoux L, Belotti M, Benitez J, et al: Fine‑scale mapping at 9p22.2 identifies candidate causal variants that modify ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. PLoS One. 11:e01588012016. View Article : Google Scholar
76	Carter H, Marty R, Hofree M, Gross AM, Jensen J, Fisch KM, Wu X, DeBoever C, Van Nostrand EL, Song Y, et al: Interaction landscape of inherited polymorphisms with somatic events in cancer. Cancer Discov. 7:410–423. 2017. View Article : Google Scholar : PubMed/NCBI
77	Permuth JB, Pirie A, Ann Chen Y, Lin HY, Reid BM, Chen Z, Monteiro A, Dennis J, Mendoza-Fandino G; AOCS Study Group; et al: Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk. Hum Mol Genet. 25:3600–3612. 2016. View Article : Google Scholar : PubMed/NCBI
78	Fong PC, Boss DS, Yap TA, Tutt A, Wu P, Mergui-Roelvink M, Mortimer P, Swaisland H, Lau A, O'Connor MJ, et al: Inhibition of poly(ADP-Ribose) polymerase in tumors from BRCA mutation carriers. N Engl J Med. 361:123–134. 2009. View Article : Google Scholar : PubMed/NCBI
79	Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, Smith HO, Yandell M, Evans CA, Holt RA, et al: The sequence of the human genome. Science. 291:1304–1351. 2001. View Article : Google Scholar : PubMed/NCBI
80	Vaser R, Adusumalli S, Leng SN, Sikic M and Ng PC: SIFT missense predictions for genomes. Nat Protoc. 11:1–9. 2016. View Article : Google Scholar
81	Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS and Sunyaev SR: A method and server for predicting damaging missense mutations. Nat Methods. 7:248–249. 2010. View Article : Google Scholar : PubMed/NCBI
82	Kang UB, Ahn Y, Lee JW, Kim YH, Kim J, Yu MH, Noh DY and Lee C: Differential profiling of breast cancer plasma proteome by isotope‑coded affinity tagging method reveals biotinidase as a breast cancer biomarker. BMC Cancer. 10:1142010. View Article : Google Scholar
83	Huang L, Zheng M, Zhou QM, Zhang MY, Jia WH, Yun JP and Wang HY: Identification of a gene‑expression signature for predicting lymph node metastasis in patients with early stage cervical carcinoma. Cancer. 117:3363–3373. 2011. View Article : Google Scholar : PubMed/NCBI
84	Sun X, Frierson HF, Chen C, Li C, Ran Q, Otto KB, Cantarel BL, Vessella RL, Gao AC, Petros J, et al: Frequent somatic mutations of the transcription factor ATBF1 in human prostate cancer. Nat Genet. 37:407–412. 2005. View Article : Google Scholar : PubMed/NCBI
85	Walker CJ, Miranda MA, O'Hern MJ, McElroy JP, Coombes KR, Bundschuh R, Cohn DE, Mutch DG and Goodfellow PJ: Patterns of CTCF and ZFHX3 mutation and associated outcomes in endo-metrial cancer. J Natl Cancer Inst. 107:djv2492015. View Article : Google Scholar
86	Rafnar T, Gudbjartsson DF, Sulem P, Jonasdottir A, Sigurdsson A, Jonasdottir A, Besenbacher S, Lundin P, Stacey SN, Gudmundsson J, et al: Mutations in BRIP1 confer high risk of ovarian cancer. Nat Genet. 43:1104–1107. 2011. View Article : Google Scholar : PubMed/NCBI
87	Landrum MJ, Lee JM, Benson M, Brown GR, Chao C, Chitipiralla S, Gu B, Hart J, Hoffman D, Jang W, et al: ClinVar: Improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 46:D1062–D1067. 2018. View Article : Google Scholar :
88	Henderson BE and Feigelson HS: Hormonal carcinogenesis. Carcinogenesis. 21:427–433. 2000. View Article : Google Scholar : PubMed/NCBI
89	Henderson BE, Ross RK, Pike MC and Casagrande JT: Endogenous hormones as a major factor in human cancer. Cancer Res. 42:3232–3239. 1982.PubMed/NCBI
90	Couch FJ, Wang X, McGuffog L, Lee A, Olswold C, Kuchenbaecker KB, Soucy P, Fredericksen Z, Barrowdale D, Dennis J, et al: Genome-wide association study in BRCA1 mutation carriers identifies novel loci associated with breast and ovarian cancer risk. PLoS Genet. 9:e10032122013. View Article : Google Scholar : PubMed/NCBI
91	Al Olama AA, Kote-Jarai Z, Berndt SI, Conti DV, Schumacher F, Han Y, Benlloch S, Hazelett DJ, Wang Z, Saunders E, et al: A meta‑analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer. Nat Genet. 46:1103–1109. 2014. View Article : Google Scholar : PubMed/NCBI
92	Kar SP, Beesley J, Amin Al Olama A, Michailidou K, Tyrer J, Kote-Jarai Z, Lawrenson K, Lindstrom S, Ramus SJ, Thompson DJ, et al: Genome-wide meta-analyses of breast, ovarian, and prostate cancer association studies identify multiple new susceptibility loci shared by at least two cancer types. Cancer Discov. 6:1052–1067. 2016. View Article : Google Scholar : PubMed/NCBI
93	Schildkraut JM, Goode EL, Clyde MA, Iversen ES, Moorman PG, Berchuck A, Marks JR, Lissowska J, Brinton L, Peplonska B, et al: Single nucleotide polymorphisms in the TP53 region and susceptibility to invasive epithelial ovarian cancer. Cancer Res. 69:2349–2357. 2009. View Article : Google Scholar : PubMed/NCBI
94	Johnatty SE, Tyrer JP, Kar S, Beesley J, Lu Y, Gao B, Fasching PA, Hein A, Ekici AB, Beckmann MW, et al: Genome-wide analysis identifies novel loci associated with ovarian cancer outcomes: Findings from the ovarian cancer association consortium. Clin Cancer Res. 21:5264–5276. 2015. View Article : Google Scholar : PubMed/NCBI
95	Lu Y, Beeghly-Fadiel A, Wu L, Guo X, Li B, Schildkraut JM, Im HK, Chen YA, Permuth JB, Reid BM, et al: A transcrip-tome-wide association study among 97,898 women to identify candidate susceptibility genes for epithelial ovarian cancer risk. Cancer Res. 78:5419–5430. 2018. View Article : Google Scholar : PubMed/NCBI