Dataset Information

Consortium analysis of 7 candidate SNPs for ovarian cancer.

ABSTRACT: The Ovarian Cancer Association Consortium selected 7 candidate single nucleotide polymorphisms (SNPs), for which there is evidence from previous studies of an association with variation in ovarian cancer or breast cancer risks. The SNPs selected for analysis were F31I (rs2273535) in AURKA, N372H (rs144848) in BRCA2, rs2854344 in intron 17 of RB1, rs2811712 5' flanking CDKN2A, rs523349 in the 3' UTR of SRD5A2, D302H (rs1045485) in CASP8 and L10P (rs1982073) in TGFB1. Fourteen studies genotyped 4,624 invasive epithelial ovarian cancer cases and 8,113 controls of white non-Hispanic origin. A marginally significant association was found for RB1 when all studies were included [ordinal odds ratio (OR) 0.88 (95% confidence interval (CI) 0.79-1.00) p = 0.041 and dominant OR 0.87 (95% CI 0.76-0.98) p = 0.025]; when the studies that originally suggested an association were excluded, the result was suggestive although no longer statistically significant (ordinal OR 0.92, 95% CI 0.79-1.06). This SNP has also been shown to have an association with decreased risk in breast cancer. There was a suggestion of an association for AURKA, when one study that caused significant study heterogeneity was excluded [ordinal OR 1.10 (95% CI 1.01-1.20) p = 0.027; dominant OR 1.12 (95% CI 1.01-1.24) p = 0.03]. The other 5 SNPs in BRCA2, CDKN2A, SRD5A2, CASP8 and TGFB1 showed no association with ovarian cancer risk; given the large sample size, these results can also be considered to be informative. These null results for SNPs identified from relatively large initial studies shows the importance of replicating associations by a consortium approach.

SUBMITTER: Ramus SJ

PROVIDER: S-EPMC2667795 | biostudies-literature | 2008 Jul

REPOSITORIES: biostudies-literature

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Consortium analysis of 7 candidate SNPs for ovarian cancer.

Ramus Susan J SJ Vierkant Robert A RA Johnatty Sharon E SE Pike Malcolm C MC Van Den Berg David J DJ Wu Anna H AH Pearce Celeste Leigh CL Menon Usha U Gentry-Maharaj Aleksandra A Gayther Simon A SA DiCioccio Richard A RA McGuire Valerie V Whittemore Alice S AS Song Honglin H Easton Douglas F DF Pharoah Paul D P PDP Garcia-Closas Montserrat M Chanock Stephen S Lissowska Jolanta J Brinton Louise L Terry Kathryn L KL Cramer Daniel W DW Tworoger Shelley S SS Hankinson Susan E SE Berchuck Andrew A Moorman Patricia G PG Schildkraut Joellen M JM Cunningham Julie M JM Liebow Mark M Kjaer Susanne Krüger SK Hogdall Estrid E Hogdall Claus C Blaakaer Jan J Ness Roberta B RB Moysich Kirsten B KB Edwards Robert P RP Carney Michael E ME Lurie Galina G Goodman Marc T MT Wang-Gohrke Shan S Kropp Silke S Chang-Claude Jenny J Webb Penelope M PM Chen Xiaoqing X Beesley Jonathan J Chenevix-Trench Georgia G Goode Ellen L EL

International journal of cancer 20080701 2

The Ovarian Cancer Association Consortium selected 7 candidate single nucleotide polymorphisms (SNPs), for which there is evidence from previous studies of an association with variation in ovarian cancer or breast cancer risks. The SNPs selected for analysis were F31I (rs2273535) in AURKA, N372H (rs144848) in BRCA2, rs2854344 in intron 17 of RB1, rs2811712 5' flanking CDKN2A, rs523349 in the 3' UTR of SRD5A2, D302H (rs1045485) in CASP8 and L10P (rs1982073) in TGFB1. Fourteen studies genotyped 4, ...[more]

PMID: 18431743

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Project description:BACKGROUND:Few biomarkers of ovarian cancer prognosis have been established, partly because subtype-specific associations might be obscured in studies combining all histopathological subtypes. We examined whether tumour expression of the progesterone receptor (PR) and oestrogen receptor (ER) was associated with subtype-specific survival. METHODS:12 studies participating in the Ovarian Tumor Tissue Analysis consortium contributed tissue microarray sections and clinical data to our study. Participants included in our analysis had been diagnosed with invasive serous, mucinous, endometrioid, or clear-cell carcinomas of the ovary. For a patient to be eligible, tissue microarrays, clinical follow-up data, age at diagnosis, and tumour grade and stage had to be available. Clinical data were obtained from medical records, cancer registries, death certificates, pathology reports, and review of histological slides. PR and ER statuses were assessed by central immunohistochemistry analysis done by masked pathologists. PR and ER staining was defined as negative (<1% tumour cell nuclei), weak (1 to <50%), or strong (?50%). Associations with disease-specific survival were assessed. FINDINGS:2933 women with invasive epithelial ovarian cancer were included: 1742 with high-grade serous carcinoma, 110 with low-grade serous carcinoma, 207 with mucinous carcinoma, 484 with endometrioid carcinoma, and 390 with clear-cell carcinoma. PR expression was associated with improved disease-specific survival in endometrioid carcinoma (log-rank p<0·0001) and high-grade serous carcinoma (log-rank p=0·0006), and ER expression was associated with improved disease-specific survival in endometrioid carcinoma (log-rank p<0·0001). We recorded no significant associations for mucinous, clear-cell, or low-grade serous carcinoma. Positive hormone-receptor expression (weak or strong staining for PR or ER, or both) was associated with significantly improved disease-specific survival in endometrioid carcinoma compared with negative hormone-receptor expression, independent of study site, age, stage, and grade (hazard ratio 0·33, 95% CI 0·21-0·51; p<0·0001). Strong PR expression was independently associated with improved disease-specific survival in high-grade serous carcinoma (0·71, 0·55-0·91; p=0·0080), but weak PR expression was not (1·02, 0·89-1·18; p=0·74). INTERPRETATION:PR and ER are prognostic biomarkers for endometrioid and high-grade serous ovarian cancers. Clinical trials, stratified by subtype and biomarker status, are needed to establish whether hormone-receptor status predicts response to endocrine treatment, and whether it could guide personalised treatment for ovarian cancer. FUNDING:Carraresi Foundation and others.

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Consortium analysis of 7 candidate SNPs for ovarian cancer.

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Consortium analysis of 7 candidate SNPs for ovarian cancer.

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