RESUMO
Background: Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS). Methods: We analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank Japan. Results: Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding that TP53 3'-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10-9). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62). Conclusions: This study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.
RESUMO
We evaluated the feasibility of an automated tablet computer application providing a family and personal history based cancer risk assessment for hereditary breast, ovarian, endometrial and colorectal cancers. 1,002 women presenting for screening mammography and 1,000 presenting for ultrasound were offered screening. The application calculated the risk of BRCA mutations using BRCAPRO, Myriad and Tyrer-Cuzick risk assessment models. Lifetime risk of breast and ovarian cancer was assessed with the BRCAPRO, Claus and Tyrer-Cuzick models. Colorectal and endometrial cancer risk was calculated via the MMRpro model. Patients were identified as high-risk based on thresholds 10% or greater risk for carrying genetic mutations or 20% or greater lifetime risk of breast or ovarian cancer. The percent of women found to be high-risk by a single risk assessment tool ranged from 0.5 to 5.3%. Combining assessment tools found 9.3% of women to be high-risk. The risk assessments performed similarly for the mammography and ultrasound cohorts with yields (combining assessment tools) of 9.2 and 9.4% respectively. The average ages of all the high-risk women were 45.8 and 39.6 years for the mammography and ultrasound cohorts respectively. Difficulties encountered included a need for software upgrade, wireless network unreliability and hardware theft. Automated family history screening can identify women probably at high-risk for hereditary cancers efficiently. The number of women identified is increased by employing multiple risk assessment models simultaneously. Surveying women in conjunction with ultrasound identified women at increased risk as effectively and at a younger age than with screening mammography.
