Dataset Information

OCAC OncoArray data

ABSTRACT: Germline genotype data on 56,479 ovarian cancer cases and controls

PROVIDER: EGAD00010001192 | EGA |

REPOSITORIES: EGA

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Publications

The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers.

Amos Christopher I CI Dennis Joe J Wang Zhaoming Z Byun Jinyoung J Schumacher Fredrick R FR Gayther Simon A SA Casey Graham G Hunter David J DJ Sellers Thomas A TA Gruber Stephen B SB Dunning Alison M AM Michailidou Kyriaki K Fachal Laura L Doheny Kimberly K Spurdle Amanda B AB Li Yafang Y Xiao Xiangjun X Romm Jane J Pugh Elizabeth E Coetzee Gerhard A GA Hazelett Dennis J DJ Bojesen Stig E SE Caga-Anan Charlisse C Haiman Christopher A CA Kamal Ahsan A Luccarini Craig C Tessier Daniel D Vincent Daniel D Bacot François F Van Den Berg David J DJ Nelson Stefanie S Demetriades Stephen S Goldgar David E DE Couch Fergus J FJ Forman Judith L JL Giles Graham G GG Conti David V DV Bickeböller Heike H Risch Angela A Waldenberger Melanie M Brüske-Hohlfeld Irene I Hicks Belynda D BD Ling Hua H McGuffog Lesley L Lee Andrew A Kuchenbaecker Karoline K Soucy Penny P Manz Judith J Cunningham Julie M JM Butterbach Katja K Kote-Jarai Zsofia Z Kraft Peter P FitzGerald Liesel L Lindström Sara S Adams Marcia M McKay James D JD Phelan Catherine M CM Benlloch Sara S Kelemen Linda E LE Brennan Paul P Riggan Marjorie M O'Mara Tracy A TA Shen Hongbing H Shi Yongyong Y Thompson Deborah J DJ Goodman Marc T MT Nielsen Sune F SF Berchuck Andrew A Laboissiere Sylvie S Schmit Stephanie L SL Shelford Tameka T Edlund Christopher K CK Taylor Jack A JA Field John K JK Park Sue K SK Offit Kenneth K Thomassen Mads M Schmutzler Rita R Ottini Laura L Hung Rayjean J RJ Marchini Jonathan J Amin Al Olama Ali A Peters Ulrike U Eeles Rosalind A RA Seldin Michael F MF Gillanders Elizabeth E Seminara Daniela D Antoniou Antonis C AC Pharoah Paul D P PD Chenevix-Trench Georgia G Chanock Stephen J SJ Simard Jacques J Easton Douglas F DF

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20161003 1

<h4>Background</h4>Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic m ...[more]

PMID: 27697780

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Project description:Introduction: Serous ovarian cancer is the leading cause of gynecological cancers, with a 5-year survival rate below 45% due in part to the nonspecific symptoms and lack of accurate screening for early detection. In comparison, patients diagnosed at an early stage have a five-year survival rate of 92%, demonstrating the urgent need for biomarkers for the early detection of disease. Serum from patients with serous ovarian cancer contain antibodies to tumor antigens that are potential biomarkers for early detection. The purpose of this study is to identify a panel of novel serum autoantibody (AAb) biomarkers for the early diagnosis of serous ovarian cancer. Methods: To detect AAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n = 30 cases/ 30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens using cutoff values of 10% sensitivity at 95% specificity and K-value>0.8, as well as visual analysis and evaluated these with an independent set of serous ovarian cancer sera (n = 30 cases/ 30 benign disease controls/ 30 heathy controls). Thirty-nine potential tumor autoantigens were identified with sensitivities ranging from 3 to 39.7% sensitivity at 95% specificity and were retested using an orthogonal programmable ELISA assay. A total of 13 potential tumor antigens were identified for further validation using an independent ovarian cancer sera set (n = 44 cases/ 34 healthy controls). Sensitivities at 95% specificity were calculated and a serous ovarian cancer classifier was constructed. In addition, we evaluated a longitudinal study using blinded serous pre-diagnostic ovarian cancer sera (n = 9 cases/ 90 controls) to examine the value of three (CTAG1, CTAG2, and p53) of these AAb in comparison to CA 125. Results: We identified 11-AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 100% specificity. In our longitudinal analysis, p53- and CTAG-AAb were detected up to 9 months prior to ovarian cancer diagnosis and increased with CA 125 levels. Conclusion: These are potential circulating biomarkers for the early detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts. In addition, p53- and CTAG1/2-AAb are detected in a subset of women with ovarian cancer up to 9 months prior to clinical diagnosis. Their utility as a biomarker for early detection, beyond CA 125, warrant further investigation.

Dataset Information

OCAC OncoArray data

Publications

The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers.

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