Couch, Fergus

1113 Background: Testing for BRCA1/BRCA2 mutations (BRCAm) aids systemic treatment decisions for patients (pts) with metastatic breast cancer (mBC). This retrospective study explored real-world germline/tumor (g/t) BRCA testing patterns and PARP inhibitor (PARPi) use in US pts with mBC. Methods: Data from pts ≥18 years old diagnosed with HER2-negative mBC from 2014–2022 were captured in the nationwide Flatiron Health electronic health record-derived deidentified database. Patterns and timing of prospective or incidental BRCA testing were compared across mBC subtypes (hormone receptor-positive [HR+ mBC]/triple-negative mBC [mTNBC]) and disease stage (recurrent/ de novo). BRCAm prevalence was compared by testing modality and mBC subtype. PARPi initiation was assessed in pts with mBC diagnosed from 2018 onwards and a positive BRCAm test result. Clinical characteristics were compared by receipt of a BRCA test, testing modality, and PARPi initiation. Real-world overall survival (OS) by PARPi use was estimated using the Kaplan-Meier method. Results: Of 15,006 pts (including 12,349 with HR+ mBC; 1998 with mTNBC), 8178 (54.5%) did not receive any type of BRCA test, 4654 (31.0%) received a gBRCA test, 3075 (20.5%) received a tumor tissue DNA (ttDNA) test, and 1418 (9.4%) received a circulating tumor DNA (ctDNA) test. BRCA testing prevalence was numerically higher in pts with mTNBC (n=1164; 58.3%) than in pts with HR+ mBC (n=5323; 43.1%). As expected, testing prevalence was higher with ttDNA than with ctDNA (mTNBC: n=569 [28.5%] vs n=137 [6.9%]; HR+ mBC: n=2339 [18.9%] vs n=1224 [9.9%]). Over 93% of pts (recurrent and de novo) who received a tBRCA test were tested after an mBC diagnosis, and >1/3 were tested after first-line therapy, with median times from diagnosis to a ttDNA and ctDNA test of 127 and 431 days, respectively. Both gBRCA and tBRCA testing rates increased from 2014–2022, and testing occurred earlier in pts with recurrent than de novo disease. Among pts with tBRCAm, 66.0% had HR+ mBC, and 25.6% had mTNBC. BRCA1 mutations were more common in mTNBC (59.0%) than in HR+ mBC (22.9%) tumors. Of 219 pts with tBRCAm tumors who were diagnosed with mBC from 2018 onwards, PARPi was initiated in 39/74 (52.7%) pts with gBRCAm, 15/71 (21.1%) pts who were gBRCAm-negative, and 19/74 (25.7%) pts with gBRCAm status unknown. Among pts with g or tBRCAm and available OS data, median OS was numerically longer in pts who received PARPi (32.3 months [95% CI: 24.2, 47.4], n=128) versus pts who did not (29.0 months [95% CI: 21.9, 31.9], n=204; median follow-up time 23.2 months). Conclusions: While NCCN guidelines recommend gBRCA testing for all pts with mBC, more than half of pts with HER2-negative mBC (56.9% of pts with HR+ mBC) did not receive any BRCA test. Among pts with tBRCAm, ~2/3 had HR+ disease. Despite the potential benefits of PARPi for pts with BRCAm mBC, utilization remained low from 2018–2022.

Abstract Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values<5x10-8 as genome-wide significant, and p-values<1x10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants.Results: None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values<1x105. The strongest evidence was found for rs4674019 (p-value=2.27x10-7), which showed genome-wide significant interaction (p-value=3.8x10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. Conclusions: In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association.

ABSTRACTGenes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene‐environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P‐values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.