Lux, Michael P

PURPOSE Among patients with metastatic breast cancer (mBC), the frequency of germline mutations in cancer susceptibility genes and the clinical relevance of these mutations are unclear. In this study, a prospective cohort of patients with mBC was used to determine mutation rates for breast cancer (BC) predisposition genes, to evaluate the clinical characteristics of patients with mutations, and to assess the influence of mutations on patient outcome. PATIENTS AND METHODS Germline DNA from 2,595 patients with mBC enrolled in the prospective PRAEGNANT registry was evaluated for mutations in cancer predisposition genes. The frequencies of mutations in known BC predisposition genes were compared with results from a prospective registry of patients with nonmetastatic BC sequenced using the same QIAseq method and with public reference controls. Associations between mutation status and tumor characteristics, progression-free survival, and overall survival were assessed. RESULTS Germline mutations in 12 established BC predisposition genes (including BRCA1 and BRCA2) were detected in 271 (10.4%) patients. A mutation in BRCA1 or BRCA2 was seen in 129 patients (5.0%). BRCA1 mutation carriers had a higher proportion of brain metastasis (27.1%) compared with nonmutation carriers (12.8%). Mutations were significantly enriched in PRAEGNANT patients with mBC compared with patients with nonmetastatic BC (10.4% v 6.6%, P < .01). Mutations did not significantly modify progression-free survival or overall survival for patients with mBC. CONCLUSION Multigene panel testing may be considered in all patients with mBC because of the high frequency of germline mutations in BRCA1/2 and other BC predisposition genes. Although the prognosis of mutation carriers and nonmutation carriers with mBC was similar, differences observed in tumor characteristics have implications for treatment and for future studies of targeted therapies.

AbstractLarge-scale genotyping studies have identified over 70 single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. However, knowledge regarding genetic risk factors associated with the prognosis is limited. The aim of this study was therefore to investigate the prognostic effect of nine known breast cancer risk SNPs. BC patients (n = 1687) randomly sampled in an adjuvant, randomized phase III trial (SUCCESS A study) were genotyped for nine BC risk SNPs: rs17468277(CASP8), rs2981582(FGFR2), rs13281615(8q24), rs3817198(LSP1), rs889312(MAP3K1), rs3803662(TOX3), rs13387042(2q35), rs4973768(SLC4A7), rs6504950(COX11). Cox proportional hazards models were used to test the SNPsʼ association with overall survival (OS) and progression-free survival (PFS). Additional analyses were carried out for molecular subgroups. rs3817198 in LSP1 (lymphocyte-specific protein 1) was the only SNP that significantly influenced OS (p = 0.01) and PFS (p < 0.01) in the likelihood ratio test comparing the genetic survival model with the clinical survival model. In the molecular subgroups, triple-negative patients with two minor alleles in rs3817198 had a much better prognosis relative to OS (adjusted HR 0.03; 95% CI 0.002 – 0.279) and PFS (HR 0.09; 95% CI 0.02 – 0.36) than patients with the common alleles. The same effect on PFS was shown for patients with luminal A tumors (HR 0.19; 95% CI 0.05 – 0.84), whereas patients with luminal B tumors had a poorer PFS with two minor alleles (HR 2.13; 95% CI 1.02 – 4.40). The variant in rs3817198 has a prognostic effect particularly in the subgroup of patients with triple-negative BC, suggesting a possible link with immunomodulation and BC.

Although mammography screening programs do not include ultrasound examinations, some diagnostic units do provide women with both mammography and ultrasonography. This article is concerned with estimating the risk of a breast cancer patient diagnosed in a hospital‐based mammography unit having a tumor that is visible on ultrasound but not on mammography. A total of 1,399 women with invasive breast cancer from a hospital‐based diagnostic mammography unit were included in this retrospective study. For inclusion, mammograms from the time of the primary diagnosis had to be available for computer‐assisted assessment of percentage mammographic density (PMD), as well as Breast Imaging Reporting and Data System (BIRADS) assessment of mammography. In addition, ultrasound findings were available for the complete cohort as part of routine diagnostic procedures, regardless of any patient or imaging characteristics. Logistic regression analyses were conducted to identify predictors of mammography failure, defined as BIRADS assessment 1 or 2. The probability that the visibility of a tumor might be masked at diagnosis was estimated using a regression model with the identified predictors. Tumors were only visible on ultrasound in 107 cases (7.6%). PMD was the strongest predictor for mammography failure, but age, body mass index and previous breast surgery also influenced the risk, independently of the PMD. Risk probabilities ranged from 1% for a defined low‐risk group up to 40% for a high‐risk group. These findings might help identify women who should be offered ultrasound examinations in addition to mammography.