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Evidence linking coding germline variants in breast cancer (BC)-susceptibility genes other than BRCA1, BRCA2, and CHEK2 with contralateral breast cancer (CBC) risk and breast cancer-specific survival (BCSS) is scarce. The aim of this study was to assess the association of protein-truncating variants (PTVs) and rare missense variants (MSVs) in nine known (ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53) and 25 suspected BC-susceptibility genes with CBC risk and BCSS. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated with Cox regression models. Analyses included 34,401 women of European ancestry diagnosed with BC, including 676 CBCs and 3,449 BC deaths; the median follow-up was 10.9 years. Subtype analyses were based on estrogen receptor (ER) status of the first BC. Combined PTVs and pathogenic/likely pathogenic MSVs in BRCA1, BRCA2, and TP53 and PTVs in CHEK2 and PALB2 were associated with increased CBC risk [HRs (95% CIs): 2.88 (1.70-4.87), 2.31 (1.39-3.85), 8.29 (2.53-27.21), 2.25 (1.55-3.27), and 2.67 (1.33-5.35), respectively]. The strongest evidence of association with BCSS was for PTVs and pathogenic/likely pathogenic MSVs in BRCA2 (ER-positive BC) and TP53 and PTVs in CHEK2 [HRs (95% CIs): 1.53 (1.13-2.07), 2.08 (0.95-4.57), and 1.39 (1.13-1.72), respectively, after adjusting for tumor characteristics and treatment]. HRs were essentially unchanged when censoring for CBC, suggesting that these associations are not completely explained by increased CBC risk, tumor characteristics, or treatment. There was limited evidence of associations of PTVs and/or rare MSVs with CBC risk or BCSS for the 25 suspected BC genes. The CBC findings are relevant to treatment decisions, follow-up, and screening after BC diagnosis., Competing Interests: Declaration of interests B.D. is a stockholder of Roche, Vaccitech and EQRx. P.A.F. conducts research funded by Amgen, Novartis, and Pfizer outside the submitted work. He received honoraria from Roche, Novartis, and Pfizer outside the submitted work. D.F.E. is an associate editor at The American Journal of Human Genetics (AJHG)., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: To compare standard versus extended duration of bevacizumab treatment in combination with front-line chemotherapy in women with newly diagnosed stage IIB-IV ovarian cancer., Methods: In this multicenter, open-label, randomized phase III trial (ClinicalTrials.gov identifier: NCT01462890), patients with newly diagnosed International Federation of Gynecology and Obstetrics stage IIB-IV epithelial ovarian, fallopian tube, or peritoneal cancer underwent primary cytoreductive surgery followed by six cycles of chemotherapy (paclitaxel 175 mg/m 2 plus carboplatin area under the curve 5 once every 3 weeks) and bevacizumab (15 mg/kg once every 3 weeks). Patients were randomly assigned 1:1 to receive bevacizumab for either 15 or 30 months, stratified by International Federation of Gynecology and Obstetrics stage/residual tumor. The primary end point was investigator-assessed progression-free survival (PFS) according to RECIST version 1.1. Secondary end points included overall survival (OS), safety, and tolerability., Results: Between November 11, 2011, and August 6, 2013, 927 women were randomly assigned. There was no difference in PFS between treatment arms (hazard ratio, 0.99; 95% CI, 0.85 to 1.15; unstratified log-rank P = .90). Median PFS was 24.2 versus 26.0 months with standard versus extended duration of bevacizumab, respectively; restricted mean PFS was 39.5 versus 39.3 months, respectively. There was no OS difference between treatment arms (hazard ratio, 1.04; 95% CI, 0.87 to 1.23; P = .68). Serious/nonserious adverse events of special interest occurred in 29% versus 34% of patients in the standard versus experimental arms, respectively, and were consistent with the known safety profile of standard bevacizumab., Conclusion: Longer treatment duration with bevacizumab for up to 30 months did not improve PFS or OS in patients with primary epithelial ovarian, fallopian tube, or peritoneal cancer. A bevacizumab treatment duration of 15 months remains the standard of care.

Purpose: The identification of a robust IHC marker to predict the response to antiangiogenic bevacizumab in ovarian cancer is of high clinical interest. VEGF-A, the molecular target of bevacizumab, is expressed as multiple isoforms with pro- or antiangiogenic properties, of which VEGF-A165b is the most dominant antiangiogenic isoform. The balance of VEGF-A isoforms is closely related to the angiogenic capacity of a tumor and may define its vulnerability to antiangiogenic therapy. We investigated whether the expression of VEGF-A165b could be related to the effect of bevacizumab in advanced ovarian cancer patients., Experimental Design: Formalin-fixed paraffin-embedded tissues from 413 patients of the ICON7 multicenter phase III trial, treated with standard platinum-based chemotherapy with or without bevacizumab, were probed for VEGF-A165b expression by IHC., Results: In patients with low VEGF-A165b expression, the addition of bevacizumab to standard platinum-based chemotherapy significantly improved progression-free (HR: 0.727; 95% CI, 0.538-0.984; P = 0.039) and overall survival (HR: 0.662; 95% CI, 0.458-0.958; P = 0.029). Multivariate analysis showed that the addition of bevacizumab in low VEGF-A165b-expressing patients conferred significant improvements in progression-free survival (HR: 0.610; 95% CI, 0.446-0.834; P = 0.002) and overall survival (HR: 0.527; 95% CI, 0.359-0.775; P = 0.001), independently from established risk factors., Conclusions: We demonstrate for the first time that bevacizumab may differentially improve the prognosis of advanced ovarian cancer patients with low expression of VEGF-A165b, an antiangiogenic VEGF-A splice variant. We envision that this novel biomarker could be implemented into routine diagnostics and may have direct clinical implications for guiding bevacizumab-related treatment decisions in advanced ovarian cancer patients., (©2022 American Association for Cancer Research.)

Background: In the SOLO2 trial (ENGOT Ov-21; NCT01874353), maintenance olaparib in patients with platinum-sensitive relapsed ovarian cancer (PSROC) and BRCA mutation significantly improved progression-free survival (PFS) and prolonged overall survival (OS). Following disease progression on olaparib, efficacy of subsequent chemotherapy remains unknown., Patients and Methods: We conducted a post-hoc hypothesis-generating analysis of SOLO2 data to determine the efficacy of different chemotherapy regimens following RECIST disease progression in patients who received olaparib or placebo. We evaluated time to second progression (TTSP) calculated from the date of RECIST progression to the next progression/death., Results: The study population comprised 147 patients who received chemotherapy as their first subsequent treatment after RECIST progression. Of these, 69 (47%) and 78 (53%) were originally randomized to placebo and olaparib arms, respectively. In the placebo-treated cohort, 27/69 and 42/69 received non-platinum and platinum-based chemotherapy, respectively, compared with 24/78 and 54/78, respectively, in the olaparib-treated cohort. Among patients treated with chemotherapy (N = 147), TTSP was significantly longer in the placebo than in the olaparib arm: 12.1 versus 6.9 months [hazard ratio (HR) 2.17, 95% confidence interval (CI) 1.47-3.19]. Similar result was obtained on multivariable analysis adjusting for prognostic factors at RECIST progression (HR 2.13, 95% CI 1.41-3.22). Among patients treated with platinum-based chemotherapy (n = 96), TTSP was significantly longer in the placebo arm: 14.3 versus 7.0 months (HR 2.89, 95% CI 1.73-4.82). Conversely, among patients treated with non-platinum-based chemotherapy (n = 51), the TTSP was comparable in the placebo and olaparib arms: 8.3 versus 6.0 months (HR 1.58, 95% CI 0.86-2.90)., Conclusions: Following progression from maintenance olaparib in the recurrent setting, the efficacy of platinum-based subsequent chemotherapy seems to be reduced in BRCA1/2-mutated patients with PSROC compared to patients not previously receiving poly (ADP-ribose) polymerase inhibitors (PARPi). The optimal strategy for patients who relapse after PARPi is an area of ongoing research., Competing Interests: Disclosure JSF reports personal fees from Roche Genentech, personal fees and non-financial support from Seattle Genetics, Novartis, Pfizer, Lilly, Novartis, GSK, Clovis oncology, AstraZeneca, Daiichi Sankyo, Gilead, MSD, Pierre Fabre, and Amgen, outside the submitted work. PP reports non-financial support from GSK, AstraZeneca, Clovis Oncology outside the submitted work. JAL reports personal fees from Pfizer, AstraZeneca, GSK, MSD, Clovis Oncology, Eisai, Bristol Myers Squibb, Artios Pharma, VBL Therapeutics, Neopharm, outside the submitted work. RTP reports personal fees from AbbVie, AstraZeneca, Eisai, Genentech / Roche, GSK Inc., Merck & Co, Sutro Biopharma, Vascular Biogenics Ltd, outside the submitted work. SP reports personal fees from, AstraZeneca, MSD; ROCHE, Clovis, GSK, Pfizer, PharmaMar, outside the submitted work. NC reports personal fees from AstraZeneca, Esai, Genentech, GSK, Merck, Pfizer, Regeneron pharmaceutical, outside the submitted work. TWPS reports personal fee from AstraZeneca, Tesaro, GSK, outside the submitted work. GSS has received grant from Agendia, AstraZeneca, Merck, Novartis, Roche, Seagen, outside the submitted work. CKL reports personal fee from AstraZeneca, Amgen, Takeda, Boehringer Ingelheim, Pfizer, Yuhan, Merck KGA, Roche, MSD, outside the submitted work. EPL reports grants and personal fees from AstraZeneca, Merck, GSK, Roche, Incyte, ARCAGY Research, outside the submitted work. All other authors have declared no conflicts of interest., (Copyright © 2022. Published by Elsevier Ltd.)

The recommendations of the AGO Breast Committee on the surgical therapy of breast cancer were last updated in March 2022 (www.ago-online.de). Since surgical therapy is one of several partial steps in the treatment of breast cancer, extensive diagnostic and oncological expertise of a breast surgeon and good interdisciplinary cooperation with diagnostic radiologists is of great importance. The most important changes concern localization techniques, resection margins, axillary management in the neoadjuvant setting and the evaluation of the meshes in reconstructive surgery. Based on meta-analyses of randomized studies, the level of recommendation of an intraoperative breast ultrasound for the localization of non-palpable lesions was elevated to "++". Thus, the technique is considered to be equivalent to wire localization, provided that it is a lesion which can be well represented by sonography, the surgeon has extensive experience in breast ultrasound and has access to a suitable ultrasound device during the operation. In invasive breast cancer, the aim is to reach negative resection margins ("no tumor on ink"), regardless of whether an extensive intraductal component is present or not. Oncoplastic operations can also replace a mastectomy in selected cases due to the large number of existing techniques, and are equivalent to segmental resection in terms of oncological safety at comparable rates of complications. Sentinel node excision is recommended for patients with cN0 status receiving neoadjuvant chemotherapy after completion of chemotherapy. Minimally invasive biopsy is recommended for initially suspect lymph nodes. After neoadjuvant chemotherapy, patients with initially 1 - 3 suspicious lymph nodes and a good response (ycN0) can receive the targeted axillary dissection and the axillary dissection as equivalent options., Competing Interests: Conflict of Interest/Interessenkonflikt Maggie Banys-Paluchowski received fees for lectures and consultancy activities from Roche, Novartis, Pfizer, pfm, Eli Lilly, Onkowissen, Seagen, AstraZeneca, Eisai, AstraZeneca, Amgen, Samsung, MSD, GSK, Daiichi Sankyo, Gilead, Sirius Pintuition, Pierre Fabre and study support from EndoMag, Mammotome, MeritMedical. Marcus Schmidt reports that he received personal fees for lectures and consulting activities from AstraZeneca, BioNTech, Daiichi Sankyo, Eisai, Lilly, MSD, Novartis, Pantarhei Bioscience, Pfizer, Roche and SeaGen, which are not related to this publication. Jens Huober: Research support: Celgene, Novartis, Hexal, Lilly. Lecture activity: Lilly, Novartis, Roche, Pfizer, AstraZeneca, MSD, Celgene; Eisai, Abbvie, Seagen, Gilead. Consultancy: Lilly, Novartis, Roche, Pfizer, Hexal, AstraZeneca, MSD, Celgene, Abbvie. Travel expenses: Roche, Pfizer, Novartis, Celgene, Daiichi Sankyo. Peter Dall: Lecture fees: Novartis, Pfizer, AstraZeneca, Roche, Lilly. Ad Boards: Novartis, Seagen, Daiichi Sankyo, AstraZeneca, Roche, Gilead. David Krug: honoraria from Merck Sharp & Dohme and Pfizer as well as research funding from Merck KGaA. Other authors do not indicate any conflicts of interest./ Maggie Banys-Paluchowski erhielt Honorare für Vorträge und beratende Tätigkeiten von Roche, Novartis, Pfizer, pfm, Eli Lilly, Onkowissen, Seagen, AstraZeneca, Eisai, AstraZeneca, Amgen, Samsung, MSD, GSK, Daiichi Sankyo, Gilead, Sirius Pintuition, Pierre Fabre und Studienunterstützung von EndoMag, Mammotome, MeritMedical. Marcus Schmidt berichtet, persönliche Honorare für Vorträge und Beratungstätigkeiten von AstraZeneca, BioNTech, Daiichi Sankyo, Eisai, Lilly, MSD, Novartis, Pantarhei Bioscience, Pfizer, Roche und SeaGen erhalten zu haben, die nicht im Zusammenhang mit der vorliegenden Publikation stehen. Jens Huober: Forschungsunterstützung: Celgene, Novartis, Hexal, Lilly. Vortragstätigkeit: Lilly, Novartis, Roche, Pfizer, AstraZeneca, MSD, Celgene; Eisai, Abbvie, Seagen, Gilead. Beratertätigkeit: Lilly, Novartis, Roche, Pfizer, Hexal, AstraZeneca, MSD, Celgene, Abbvie. Reisekosten: Roche, Pfizer, Novartis, Celgene, Daiichi Sankyo. Peter Dall: Vortragshonorare: Novartis, Pfizer, AstraZeneca, Roche, Lilly. Ad-Boards: Novartis, Seagen, Daiichi Sankyo, AstraZeneca, Roche, Gilead. David Krug: honoraria from Merck Sharp & Dohme and Pfizer as well as research funding from Merck KGaA. Weitere AutorInnen geben keine Interessenkonflikte an., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).)

Background: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2)., Method: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance., Results: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10 -6 ) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted., Conclusion: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Up to 40% of patients with metastatic human epidermal growth factor receptor 2 (HER2)-positive breast cancer develop brain metastases (BMs). Understanding of clinical features of these patients with HER2-positive breast cancer and BMs is vital., Patients and Methods: A total of 2948 patients from the Brain Metastases in Breast Cancer registry were available for this analysis, of whom 1311 had primary tumors with the HER2-positive subtype., Results: Patients with HER2-positive breast cancer and BMs were-when compared with HER2-negative patients-slightly younger at the time of breast cancer and BM diagnosis, had a higher pathologic complete response rate after neoadjuvant chemotherapy and a higher tumor grade. Furthermore, extracranial metastases at the time of BM diagnosis were less common in HER2-positive patients, when compared with HER2-negative patients. HER2-positive patients had more often BMs in the posterior fossa, but less commonly leptomeningeal metastases. The median overall survival (OS) in all HER2-positive patients was 13.2 months (95% confidence interval 11.4-14.4). The following factors were associated with shorter OS (multivariate analysis): older age at BM diagnosis [≥60 versus <60 years: hazard ratio (HR) 1.63, P < 0.001], lower Eastern Cooperative Oncology Group status (2-4 versus 0-1: HR 1.59, P < 0.001), higher number of BMs (2-3 versus 1: HR 1.30, P = 0.082; ≥4 versus 1: HR 1.51, P = 0.004; global P = 0.015), BMs in the fossa anterior (HR 1.71, P < 0.001), leptomeningeal metastases (HR 1.63, P = 0.012), symptomatic BMs at diagnosis (HR 1.35, P = 0.033) and extracranial metastases at diagnosis of BMs (HR 1.43, P = 0.020). The application of targeted therapy after the BM diagnosis (HR 0.62, P < 0.001) was associated with longer OS. HER2-positive/hormone receptor-positive patients showed longer OS than HER2-positive/hormone receptor-negative patients (median 14.3 versus 10.9 months; HR 0.86, P = 0.03), but no differences in progression-free survival were seen between both groups., Conclusions: We identified factors associated with the prognosis of HER2-positive patients with BMs. Further research is needed to understand the factors determining the longer survival of HER2-positive/hormone receptor-positive patients., Competing Interests: Disclosure MT serves on the advisory board for Amgen, AstraZeneca, AURIKAMED, Becton/Dickinson, Biom‘Up, Celgene, ClearCut, Clovis, Daiichi Sankyo, Eisai, Exact Sciences, Gilead Science, Lilly, MSD, Norgine, NeoDynamics, Novartis, Onkowissen, Pfizer, pfm Medical, Pierre-Fabre, Roche, RTI Surgical, Seagen and Sysmex; reports manuscript support from Amgen, Celgene, ClearCut, pfm medical, Roche and Servier; support for travel expenses from Amgen, Art Tempi, AstraZeneca, Celgene, Cleracut, Clovis, Connect Medica, Daiichi Sankyo, Eisai, Exact Sciences, Hexal, I-Med-Institute, Lilly, MCI, Medtronic, MSD, Norgine, Novartis, OmniaMed, Pfizer, pfm medical, Roche and RTI Surgical; support for congress expenses from Amgen, AstraZeneca, Celgene, Daiichi Sankyo, Hexal, NeoDynamics, Novartis, Pfizer and Roche; support for speech expenses: Amgen, Art Tempi, AstraZeneca, Celgene, Clovis, Connect Medica, Eisai, Exact Sciences, Gilead Science, Hexal, I-Med-Institute, Jörg Eickeler, Lilly, MCI, Medtronic, MSD, Novartis, OmniaMed, Pfizer, pfm Medical, Roche, RTI Surgical, Seagen, Sysmex, Vifor and Viatris; trial funding support from Endomag and Exact Sciences. All remaining authors have declared no conflicts of interest., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Cancer patients are at risk of secondary therapy-related myeloid neoplasms (t-MNs). Acquired blood-specific mutations in clonal hematopoiesis (CH)-associated genes are t-MN risk factors, and their occurrence associated with cancer therapy and age. Patients with ovarian cancer (OC) showed a particularly high prevalence of CH-associated gene mutations, which may additionally be explained by the high proportion of a hereditary disease cause in this cancer entity., Methods: We performed a retrospective analysis of 448 OC patients enrolled in the AGO-TR1 study; 249 were enrolled at primary diagnosis and 199 at platinum-sensitive recurrence. Analyses included the most frequently altered CH-associated genes (ASXL1, DNMT3A, GNAS, JAK2, PPM1D, SF3B1, SH2B3, SRSF2, TET2, TP53). Results were analyzed according to the BRCA1/2 germline (gBRCA1/2) mutation status. All statistical tests were 2-sided., Results: Advanced age at blood draw and a high number of prior platinum-based chemotherapy lines were risk factors to acquire CH-associated gene mutations, with gene-specific effects observed. Binomial logistic regression suggested increased probabilities for gBRCA1/2 mutation carriers to acquire CH-associated PPM1D and TP53 gene mutations (PPM1D: odds ratio = 4.30, 95% confidence interval = 1.48 to 12.46, P = .007; TP53: odds ratio = 6.20, 95% confidence interval = 0.98 to 53.9, P = .06). This observation was due to a statistically significantly increased number of platinum-based chemotherapy lines in gBRCA1/2 mutation carriers vs noncarriers (PPM1D: mean [SD] = 2.04 [1.27] vs 1.04 [0.99], P < .001; TP53: mean [SD] = 2.83 [1.33] vs 1.07 [1.01], P < .001). No interaction between platinum-based chemotherapy and gBRCA1/2 mutation status with the occurrence of CH-associated gene mutations was observed., Conclusions: A positive gBRCA1/2 mutation status is not a risk factor to acquire CH-associated gene mutations. OC patients may benefit from monitoring CH-associated gene mutations, especially following carboplatin exposure. Future clinical studies are required to assess whether treatment regimen should be adapted according to individual t-MN risks., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Breast cancer is the most frequent malignancy among women in both developed and developing countries. Although several genes have been identified to harbor germline variants contributing to breast cancer risk, much of the heritability for breast cancer is yet undefined. In the present study, we have performed exome sequencing to detect susceptibility genes in an Iranian family with five first-degree family members affected with breast cancer. We identified novel candidate variants with predicted pathogenicity in RASSF1, KLK3 and FAM81B. The RASSF1 and KLK3 variants, but not the FAM81B variant, partially co-segregated with disease in the investigated pedigree and were not found in additional screenings outside the specific family. RASSF1 p.S135F is a missense substitution abolishing the ATM phosphorylation site, and KLK3 variant p.M1? is a deletion at the initiation codon that is predicted to abolish translation to the functional kallikrein protease, PSA. Our study suggests germline variation in RASSF1 and KLK3 as potential candidate contributors to familial breast cancer predisposition and illustrates the difficulties to determine the causal genetic risk factor among novel variants restricted to a single family., (Copyright © 2022 Elsevier Masson SAS. All rights reserved.)

Importance: Rare germline genetic variants in several genes are associated with increased breast cancer (BC) risk, but their precise contributions to different disease subtypes are unclear. This information is relevant to guidelines for gene panel testing and risk prediction., Objective: To characterize tumors associated with BC susceptibility genes in large-scale population- or hospital-based studies., Design, Setting, and Participants: The multicenter, international case-control analysis of the BRIDGES study included 42 680 patients and 46 387 control participants, comprising women aged 18 to 79 years who were sampled independently of family history from 38 studies. Studies were conducted between 1991 and 2016. Sequencing and analysis took place between 2016 and 2021., Exposures: Protein-truncating variants and likely pathogenic missense variants in ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, RAD51D, and TP53., Main Outcomes and Measures: The intrinsic-like BC subtypes as defined by estrogen receptor, progesterone receptor, and ERBB2 (formerly known as HER2) status, and tumor grade; morphology; size; stage; lymph node involvement; subtype-specific odds ratios (ORs) for carrying protein-truncating variants and pathogenic missense variants in the 9 BC susceptibility genes., Results: The mean (SD) ages at interview (control participants) and diagnosis (cases) were 55.1 (11.9) and 55.8 (10.6) years, respectively; all participants were of European or East Asian ethnicity. There was substantial heterogeneity in the distribution of intrinsic subtypes by gene. RAD51C, RAD51D, and BARD1 variants were associated mainly with triple-negative disease (OR, 6.19 [95% CI, 3.17-12.12]; OR, 6.19 [95% CI, 2.99-12.79]; and OR, 10.05 [95% CI, 5.27-19.19], respectively). CHEK2 variants were associated with all subtypes (with ORs ranging from 2.21-3.17) except for triple-negative disease. For ATM variants, the association was strongest for the hormone receptor (HR)+ERBB2- high-grade subtype (OR, 4.99; 95% CI, 3.68-6.76). BRCA1 was associated with increased risk of all subtypes, but the ORs varied widely, being highest for triple-negative disease (OR, 55.32; 95% CI, 40.51-75.55). BRCA2 and PALB2 variants were also associated with triple-negative disease. TP53 variants were most strongly associated with HR+ERBB2+ and HR-ERBB2+ subtypes. Tumors occurring in pathogenic variant carriers were of higher grade. For most genes and subtypes, a decline in ORs was observed with increasing age. Together, the 9 genes were associated with 27.3% of all triple-negative tumors in women 40 years or younger., Conclusions and Relevance: The results of this case-control study suggest that variants in the 9 BC risk genes differ substantially in their associated pathology but are generally associated with triple-negative and/or high-grade disease. Knowing the age and tumor subtype distributions associated with individual BC genes can potentially aid guidelines for gene panel testing, risk prediction, and variant classification and guide targeted screening strategies.

Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance., (© 2022. The Author(s).)

Background: Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear., Methods: Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes., Results: Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions., Conclusion: This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction., (© 2021. The Author(s).)

Drainage of the arterial wall via adventitial lymphatic vessels has been shown to play a pivotal role for vessel wall homeostasis. Also, retrograde cholesterol transport is ensured via this route, but no studies exist to demonstrate that lymphatic stasis would represent a mechanism to initiate atherosclerotic lesion formation in human arteries. To test this hypothesis, we embarked on a simple clinical experiment, assessing wall thickness in limb arteries with lymphedema after surgical intervention, with the contralateral limb serving as control. Using ultrasound imaging, the differential thickness was assessed separately for the three arterial wall layers. The potential of disease progression by lymphostasis was addressed by depiction of longitudinal results according to the time after lymph dissection.

Breast cancer metastasis accounts for most of the deaths from breast cancer. Identification of germline variants associated with survival in aggressive types of breast cancer may inform understanding of breast cancer progression and assist treatment. In this analysis, we studied the associations between germline variants and breast cancer survival for patients with distant metastases at primary breast cancer diagnosis. We used data from the Breast Cancer Association Consortium (BCAC) including 1062 women of European ancestry with metastatic breast cancer, 606 of whom died of breast cancer. We identified two germline variants on chromosome 1, rs138569520 and rs146023652, significantly associated with breast cancer-specific survival (P = 3.19 × 10 -8 and 4.42 × 10 -8 ). In silico analysis suggested a potential regulatory effect of the variants on the nearby target genes SDE2 and H3F3A. However, the variants showed no evidence of association in a smaller replication dataset. The validation dataset was obtained from the SNPs to Risk of Metastasis (StoRM) study and included 293 patients with metastatic primary breast cancer at diagnosis. Ultimately, larger replication studies are needed to confirm the identified associations., (© 2021. The Author(s).)

Background: Although immigrant health is an important issue in national health policy, there is a serious shortage of data in many countries. Most studies lack information on educational status, which is a major limitation. This prospective cross-sectional study analyzed a real-world breast cancer population on the influence of immigration background and educational status on participation in breast cancer early detection programs in the federal state of Lower Saxony, Germany., Methods: Data collection was conducted from 2012 to 2016 in six certified breast cancer centers using a standardized questionnaire for patients' interview and tumor-specific data from the patients' medical records., Results: 2,145/3,047 primary breast cancer cases were analyzed. 17.5% of our patients had a history of immigration, including n = 202 first-generation immigrants and n = 168 second-generation immigrants. Most of them were citizens of EU27 member states. No significant difference was seen in age, tumor stage, histology, grading, Ki-67, Her2/neu-status, and hormone receptor status compared to the native cohort. 100% participation rate in the breast cancer early detection programs were seen in patients with no school graduation. With regards to the national mammography screening program, participation decreased significantly with educational status ( p = 0.0003)., Conclusions: No tumor biological differences were seen between immigrants and German natives. In first-generation immigrants, early detection programs were well accepted despite sociocultural and language differences. Participation rate decreased significantly with higher education levels irrespective of country of origin. Immigration background does not have a negative effect on the participation in breast cancer screening. This mainly relates to immigrants from EU27 member states., Competing Interests: The authors declare that they have no conflict of interest., (Copyright © 2020 by S. Karger AG, Basel.)

For many decades, the standard procedure to treat breast cancer included complete dissection of the axillary lymph nodes. The aim was to determine histological node status, which was then used as the basis for adjuvant therapy, and to ensure locoregional tumour control. In addition to the debate on how to optimise the therapeutic strategies of systemic treatment and radiotherapy, the current discussion focuses on improving surgical procedures to treat breast cancer. As neoadjuvant chemotherapy is becoming increasingly important, the surgical procedures used to treat breast cancer, whether they are breast surgery or axillary dissection, are changing. Based on the currently available data, carrying out SLNE prior to neoadjuvant chemotherapy is not recommended. In contrast, surgical axillary management after neoadjuvant chemotherapy is considered the procedure of choice for axillary staging and can range from SLNE to TAD and ALND. To reduce the rate of false negatives during surgical staging of the axilla in pN+ CNB stage before NACT and ycN0 after NACT, targeted axillary dissection (TAD), the removal of > 2 SLNs (SLNE, no untargeted axillary sampling), immunohistochemistry to detect isolated tumour cells and micro-metastases, and marking positive lymph nodes before NACT should be the standard approach. This most recent update on surgical axillary management describes the significance of isolated tumour cells and micro-metastasis after neoadjuvant chemotherapy and the clinical consequences of low volume residual disease diagnosed using SLNE and TAD and provides an overview of this year's AGO recommendations for surgical management of the axilla during primary surgery and in relation to neoadjuvant chemotherapy., Competing Interests: Conflict of Interest/Interessenkonflikt PD DR Banys-Paluchowski: Honoraria for lectures and advisory role from Lilly, Pfizer, Roche, Amgen, Eisai, Astra Zeneca, Daiichi Sankyo, Novartis, GSK and study support from Endomag, Merit Medical and Mammotome. Prof. Dr. V. Müller: VM received speaker honoraria from Amgen, Astra Zeneca, Daiichi Sankyo, Eisai, GSK, Pfizer, MSD, Novartis, Roche, Teva, Seagen and consultancy honoraria from Genomic Health, Hexal, Roche, Pierre Fabre, Amgen, ClinSol, Novartis, MSD, Daiichi Sankyo, Eisai, Lilly, Seagen. Institutional research support from Novartis, Roche, Seagen, Genentech. Travel grants: Roche, Pfizer, Daiichi Sankyo./ Vortragshonorare: Amgen, Astra Zeneca, Daiichi Sankyo, Eisai, Pfizer, MSD, Novartis, Roche, Teva, Seattle Genetics, GSK, Seagen. Beratertätigkeit: Genomic Health, Hexal, Roche, Pierre Fabre, Amgen, ClinSol, Novartis, MSD, Daiichi Sankyo, Eisai, Lilly, GSK, Tesaro, Seagen und Nektar. Forschungsuntersützung an den Arbeitgeber: Novartis, Roche, Seattle Genetics, Genentech. Reisekosten: Roche, Pfizer, Daiichi Sankyo., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).)

Background: Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk., Methods: We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy., Results: Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10 -2 ), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect., Conclusion: Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers., (© 2021. The Author(s).)

Background: Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients., Methods: We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15)., Results: Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy., Conclusions: We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast cancer-specific survival might be limited., (© 2021. The Author(s).)

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10 -31 )., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Competing Interests: N. Ditsch: MSD, Novartis, Pfizer, Roche, AstraZeneca, Teva, Mentor, MCI. M. Untch: Presentations and travel grants, all paid to his institution by Abbvie, Amgen GmbH München, AstraZeneca, BMS, Celgene GmbH München, Daiichi Sankyo, Eisai GmbH München, Janssen Cilag, Johnson & Johnson, Lilly Deutschland, Lilly Int., MSD, Mundipharma, Myriad Genetics GmbH Zürich, Odonate, Pfizer GmbH Berlin, PUMA Biotechnology, Riemser, Roche Pharma AG Grenzach-Wyhlen, Sanofi Aventis Deutschland GmbH, Sividon Diagnostics Köln, Teva Pharmaceuticals Ind. Ltd. Berlin. C. Kolberg-Liedtke: Advisory boards: Phaon Scientific, Novartis, Pfizer, SurgVision, Carl Zeiss Meditec, Amgen, Onkowissen. Lectures: Roche, Novartis, Pfizer, Lilly, Genomic Health, Amgen, AstraZeneca, Riemser, Carl Zeiss Meditec, Teva, Theraclion Janssen-Cilag, GSK, LIV Pharma, Theramex. Travel expenses: Carl Zeiss Meditec, LIV Pharma, Novartis, Amgen, Pfizer, Daiichi Sankyo. D. Krug: MSD. M. Friedrich: Roche, Pfizer, AstraZeneca, Novartis. W. Janni: Research grants and/or honoraria: Sanofi-Aventis, Novartis, Roche, Pfizer, AstraZeneca, Chugai, GSK, Eisai, Celgene, Lilly, Janssen, Menarini. V. Müller: Speaker honoraria: Amgen, AstraZeneca, Daiichi Sankyo, Eisai, Pfizer, MSD, Novartis, Roche, Teva, Seattle Genetics. Consultancy honoraria: Genomic Health, Hexal, Roche, Pierre Fabre, Amgen, ClinSol, Novartis, MSD, Daiichi Sankyo, Eisai, Lilly, Tesaro, Nektar. Institutional research support: Novartis, Roche, Seattle Genetics, Genentech. U.-S. Albert: Lectures and/or consulting: Medexo GmbH, Institut für Versiche­rungsmedizin, Pfizer. M. Banys-Paluchowski: Advisory board: Eisai. Lectures: AstraZeneca. Study support: Mammotome, EndoMag, MeritMedical. I. Bauerfeind: No conflicts of interest. J.-U. Blohmer: Honoraria: Amgen, AstraZeneca, Genomic Health, MSD Oncology, Myriad Genetics, Novartis, Pfizer, Roche, Sonoscape. Travel and accommodation expenses: Pfizer, Roche. W. Budach: No conflicts of interest. P. Dall: Advisory boards: Olympus, Roche, Novartis, Tesaro. Congress support: Roche. Lectures: Amgen, Roche. E.M. Fallenberg: GE Healthcare, Siemens, ECR, EUSOBI, ESOR, KCR, DFG. P.A. Fasching: Grants: Novartis, BioNTech, Cepheid. Personal fees: Novartis, Roche, Pfizer, Celgene, Daiichi Sankyo, AstraZeneca, MSD, Myelo Therapeutics, Macrogenics, Eisai, Puma, Lilly. T. Fehm: AstraZeneca, Celgene, Pfizer, Novartis, Roche, Teva, Daiichi Sankyo. B. Gerber: No conflicts of interest. O. Gluz: Lecture and consulting fees: Celgene, Roche, Genomic Health, Amgen, Pfizer, Novartis, Lilly, Nanostring, Eisai, MSD. Travel expenses: Celgene, Roche, Daiichi Sankyo. N. Harbeck: Lecture and/or consulting fees: Agendia, Amgen, AstraZeneca, BMS, Celgene, Daiichi Sankyo, Genomic Health, Lilly, MSD, Novartis, Odonate, Pierre Fabre, Pfizer, Roche, Sandoz/Hexal, Seattle Genetics. Minority share holder: Westdeutsche Studiengruppe. J. Heil: No conflicts of interest. J. Huober: Research support: Celgene, Novartis, Hexal. Lectures: Lilly, Novartis, Roche, Pfizer, AstraZeneca, MSD, Celgene, Eisai, Abbvie. Consulting: Lilly, Novartis, Roche, Pfizer, Hexal, AstraZeneca, MSD, Celgene, Abbvie. Travel expenses: Roche, Pfizer, Novartis, Celgene, Daiichi Sankyo. C. Jackisch: Advisory boards: Amgen, AstraZeneca, Novartis, Pierre Fabre, Exact Sciences, Roche, Lilly, Pfizer. Travel grants: Roche, Novartis, Pfizer, Exact Sciences, Amgen. Lectures: Amgen, AstraZeneca, Daiichi Sankyo, Novartis, Pierre Fabre, Exact Sciences, Roche, Lilly, Pfizer. H.-H. Kreipe: Reimbursement for attending symposia: Ventana. Other expenses (advisory boards, lectures): Amgen, AstraZeneca, Genomic Health, Lilly, Roche Pharma. T. Kühn: Celgene, Roche, Pfizer. S. Kümmel: Roche, Genentech, Novartis, AstraZeneca, Amgen, Celgene, SOMATEX, Daiichi Sankyo, Puma Biotechnology, pfm medical, Pfizer, MSD Oncology. S. Loibl: Advisory boards/lectures: Abbvie, Amgen, AstraZeneca, Celgene, Novartis, Pfizer, Roche, Seattle Genetics, PriME/Medscape, Daiichi Sankyo, Lilly, Samsung, Eirgenix, BMS, Puma, MSD, Merck, Pierre Fabre. D. Lüftner: Advisory boards/oral presentations: Amgen, AstraZeneca, GSK, Eli Lilly, L'Oréal, MSD, Mundipharma, Mylan, Novartis, Pfizer, Roche, Teva. M.P. Lux: Advisory boards, lectures, travel support: Lilly, Pfizer, Roche, MSD, Hexal, Novartis, AstraZeneca, Eisai, medac, Genomic Health. N. Maass: No conflicts of interest. C. Mundhenke: Not specified. U. Nitz: Not specified. T.-W. Park-Simon: Advisory role or expert testimony and lecture honoraria: Roche, AstraZeneca, Tesaro, Pfizer, Daiichi Sankyo, Lilly, MSD. Participation in clinical trials: Roche, AstraZeneca, Tesaro, Pfizer, Daiichi Sankyo, Lilly, MSD, Novartis, Seattle Genetics. Other financial relationships such as travel: Roche, AstraZeneca, Tesaro, Pfizer, Lilly, MSD, Novartis. T. Reimer: Grants: German Cancer Aid, Else Kröner-Fresenius-Stiftung. Personal fees. Pfizer, Roche, Novartis, AstraZeneca outside the submitted work. K. Rhiem: AstraZeneca, Tesaro, Pfizer, Roche. A. Rody: Roche, Pfizer, Novartis, Celgene, Novartis, Genomic Health/Exact Sciences, AstraZeneca, Eisai, MSD, Hexal, Amgen. M. Schmidt: Personal fees: AstraZeneca, Roche, Lilly, SeaGen, MSD, Eisai. Grants: Pierre Fabre, Pantarhei Bioscience, BioNTech, Genentech outside the submitted work. Patent issued for EP 2390370 B1 and EP 2951317 B1. A. Schneeweiss: Grants: Celgene, Roche, Abbvie, Molecular Partner. Personal fees: Roche, AstraZe­neca, Celgene, Pfizer, Novartis, MSD, Tesaro, Lilly. F. Schütz: Amgen, AstraZeneca, Lilly, Hexal, MSD, Novartis, Pfizer, Roche, Onkozert, Eickeler Kongressorganisation. H.-P. Sinn: No conflicts of interest related to the submitted manuscript. C. Solbach: Travel, accommodations: Roche, Novartis, AstraZeneca, Amgen, Celgene, Hexal, Daiichi Sankyo, Dialog Service GmbH, Lilly, Pfizer, MSD Oncology, ESAI, Gedon Richter, Mylan, Tesaro. E.-F. Solomayer: Roche, AstraZeneca, Pfizer, Amgen, Celgene, Tesaro, AstraZeneca, Storz, Erbe, Gedeon Richter, Eisai, Medac, MSD, Vifor, Teva, Ethikon. E. Stickeler: Counseling: Novartis, Pfizer, AstraZeneca, Roche, Tesoro. Fees: Novartis, Pfizer, AstraZeneca, Roche. C. Thomssen: Advisory boards and lectures: Amgen, AstraZeneca, Celgene, Daiichi Sankyo, Eisai, Lilly, MSD, Mylan, Nanostring, Novartis, Pfizer, Pierre Fabre, Puma, Roche, Vifor. Research support (by discount prizes): American Diagnostica, Affymetrix, Nanostring. I. Witzel: Not specified. A. Wöckel: Amgen, AstraZeneca, Aurikamed, Celgene, Eisai, Lilly, Novartis, Pfizer, Roche, Tesaro, Sirtex, MSD, Genomic Health, Pierre Fabre, Clovis. M. Thill: Advisory boards: Amgen, AstraZeneca, Celgene, ClearCut, Clovis, Daiichi Sankyo, Exact Sciences, Lilly, MSD, Neodynamics, Novartis, Pfizer, pfm medical, Pierre Fabre, Roche, Tesaro. Manuscript support: Amgen, Celgene, Roche. Travel expenses: Amgen, Art Tempi, AstraZeneca, Celgene, Clovis, Connect Medica, Daiichi Sankyo, Exact Sciences, Hexal, I-Med Institute, Lilly, MCI, MSD, Novartis, Pfizer, pfm medical, Roche, Tesaro. Congress fees: Amgen, AstraZeneca, Celgene, Daiichi Sankyo, Hexal, Novartis, Pfizer, Roche. Lectures: Amgen, Art Tempi, AstraZeneca, Celgene, Clovis, Connect Medica, Exact Sciences, Hexal, I-Med Institute, Lilly, MCI, MSD, Novartis, OnkoLive, Pfizer, pfm medical, Roche. Trial funding: Exact Sciences.

Competing Interests: M. Thill: Advisory boards: Amgen, AstraZeneca, Celgene, ClearCut, Clovis, Daiichi Sankyo, Exact Sciences, GSK, Lilly, MSD, Neodynamics, Novartis, Pfizer, pfm medical, Pierre Fabre, Roche, Sysmex, Tesaro. Manuscript support: Amgen, Celgene, Clearcut, Roche. Travel reimbursement: Amgen, art tempi, AstraZeneca, Celgene, Clovis, Connect Medica, Daiichi Sankyo, Eisai, Exact Sciences, Hexal, I-Med Institute, Lilly, MCI, Medtronic, MSD, Novartis, Pfizer, pfm medical, Roche, Sysmex, Tesaro. Congress support: Amgen, AstraZeneca, Celgene, Daiichi Sankyo, Hexal, Novartis, Pfizer, Roche. Lectures: Amgen, art tempi, AstraZeneca, Celgene, Clovis, Connect Medica, Daiichi Sankyo, Exact Sciences, Hexal, I-Med Institute, Lilly, MCI, Medtronic, MSD, Novartis, Pfizer, pfm medical, Roche, Seagen, Sysmex, Tesaro, Vifor. Trial funding: Endomagnetics, Exact Sciences. M. Friedrich: Roche, Pfizer, AstraZeneca, Novartis. C. Kolberg-Liedtke: Advisory boards: Phaon Scientific, Novartis, Pfizer, SurgVision, Carl Zeiss Meditec, Amgen, Onkowissen. Lectures: Roche, Novartis, Pfizer, Lilly, Genomic Health, Amgen, AstraZeneca, Riemser, Carl Zeiss Meditec, TEVA, Theraclion, Janssen-Cilag, GSK, LIV Pharma, Theramex. Travel grants: Carl Zeiss Meditec, LIV Pharma, Novartis, Amgen, Pfizer, Daiichi Sankyo. U.-S. Albert: Lectures and/or consulting: Medexo GmbH, Institut für Versicherungsmedizin, Pfizer. M. Banys-Paluchowski: Pfizer, Roche, Novartis, Eli Lilly. I. Bauerfeind: Aurikamed, J. Eickeler. J.-U. Blohmer: Honoraria: Amgen, AstraZeneca, Genomic Health Recipient, MSD Oncology, Myriad Genetics, Novartis, Pfizer, Roche, Sonoscape. Travel, accommodations, expenses: Pfizer, Roche. W. Budach: No conflicts of interest. P. Dall: Advisory boards: Olympus, Roche, Novartis, Tesaro. Congress support: Roche. Lectures: Amgen, Roche. E.M. Fallenberg: GE Healthcare, Siemens, ECR, EUSOBI, ESOR, KCR, Esor, DFG. P.A. Fasching: Grants: Novartis, BioNTech, Cepheid. Personal fees: Novartis, Roche, Pfizer, Celgene, Daiichi Sankyo, AstraZeneca, MSD, Myelo Therapeutics, Macrogenics, Eisai, Puma, Lilly. T. Fehm: AstraZeneca, Celgene, Pfizer, Novartis, Roche, Teva, Daiichi Sankyo. B. Gerber: No conflicts of interest. O. Gluz: Advisory boards/lectures: Celgene, Roche, Genomic Health, Amgen, Pfizer, Novartis, Lilly, Nanostring, Eisai, MSD Travel. Grants: Celgene, Roche, Daiichi Sankyo. N. Harbeck: Honoraria for lectures and/or consulting: Agendia, Amgen, Astra Zeneca, BMS, Celgene, Daiichi Sankyo, Genomic Health, Lilly, MSD, Novartis, Odonate, Pierre Fabre, Pfizer, Roche, Sandoz/Hexal, Seattle Genetics. Minority share holder: Westdeutsche Studiengruppe. J. Heil: No conflicts of interest. J. Huober: Trial funding: Celgene, Novartis, Hexal. Lectures: Lilly, Novartis, Roche, Pfizer, AstraZeneca, MSD, Celgene, Eisai, Abbvie. Advisory boards: Lilly, Novartis, Roche, Pfizer, Hexal, AstraZeneca, MSD, Celgene, Abbvie. Travel expenses: Roche, Pfizer, Novartis, Celgene, Daiichi Sankyo. C. Jackisch: Roche, AstraZeneca, Novartis. H.-H. Kreipe: Reimbursement for attending symposia: Ventana. Other expenses (advisory boards, lectures): Amgen, AstraZeneca, Genomic Health, Lilly, Roche. D. Krug: MSD. T. Kühn: Celgene, Roche, Pfizer. S. Kümmel: Roche, Genentech, Novartis, AstraZeneca, Amgen, Celgene, SOMATEX, Daiichi Sankyo, Puma Biotechnology, pfm medical, Pfizer, MSD Oncology. S. Loibl: Abbvie, Amgen, AstraZeneca, Celgene, Novartis, Pfizer, Roche, Seattle Genetics, PriME/Medscape, Chugai, Teva, Vifor, Daiichi Sankyo, Lilly, Samsung, Eirgenix, BMS, Puma, MSD, Immunomedics. D. Lüftner: Advisory boards/lectures: Amgen, AstraZeneca, Celgene, GSK, Lilly, L'Oréal, MSD, Mundi­pharma, Mylan, Novartis, Pfizer, Roche, Teva, Tesaro. M.P. Lux: Advisory boards, lectures, travel support: Lilly, Pfizer, Roche, MSD, Hexal, Novartis, AstraZeneca, Eisai, medac, Genomic Health. N. Maass: No conflicts of interest. C. Mundhenke: Not specified. U. Nitz: Not specified. T.-W. Park-Simon: Advisory role or expert testimony and lecture honoraria: Roche, AstraZeneca, Tesaro, Pfizer, Daiichi Sankyo, Lilly, MSD. Participation in clinical trials: Roche, AstraZeneca, Tesaro, Pfizer, Daiichi Sankyo, Lilly, MSD, Novartis, Seattle Genetics. Other financial relationships such as travel: Roche, AstraZeneca, Tesaro, Pfizer, Lilly, MSD, Novartis. T. Reimer: Grants: German Cancer Aid, Else Kröner-Fresenius-Stiftung. Personal fees: Pfizer, Roche, Novartis, AstraZeneca, outside the submitted work. K. Rhiem: AstraZeneca, Tesaro, Pfizer, Roche. A. Rody: Roche, Pfizer, Novartis, Celgen, Genomic Health/Exact Sciences, AstraZeneca, Eisai, MSD, Hexal, Amgen. M. Schmidt: Personal fees: AstraZeneca, Roche, Lilly, SeaGen, MSD, Eisai. Grants: Pierre Fabre, Pantarhei Bioscience, BioNTech, Genentech outside the submitted work. Patent issued for EP 2390370 B1 and EP 2951317 B1. A. Schneeweiss: Grants: Celgene, Roche, Abbvie, Molecular Partner. Personal fees: Roche, AstraZeneca, Celgene, Pfizer, Novartis, MSD, Tesaro, Lilly. F. Schütz: Amgen, AstraZeneca, Lilly, Hexal, MSD, Novartis, Pfizer, Roche, Onkozert, Eickeler Kongressorganisation. H.-P. Sinn: No conflicts of interest related to the submitted manuscript. C. Solbach: Travel, accommodation: Roche, Novartis, AstraZeneca, Amgen, Celgene, Hexal, Daiichi Sankyo, Dialog Service GmbH, Lilly, Pfizer, MSD Oncology, ESAI, Gedon Richter, Mylan, Tesaro. E.-F. Solomayer: Roche, AstraZeneca, Pfizer, Amgen, Celgen, Tesaro, Storz, Erbe, Gedeon Richter, Eisai, Medac, MSD, Vifor, Teva, Ethikon. E. Stickeler: Advisory boards: Novartis, Pfizer, AstraZeneca, Roche, Tesoro. Fees: Novartis, Pfizer, AstraZeneca, Roche. C. Thomssen: Advisory boards, lectures: Amgen, AstraZeneca, Celgen, Daiichi Sankyo, Eisai, Lilly, MSD, Mundipharma, Medapharm, Novartis, Pfizer, Pierre Fabre, Roche, Tesaro, Vifor. M. Untch: presentations, travel grants, all paid to his institution by Abbvie, Amgen, AstraZe­neca, BMS, Celgene, Daiichi Sankyo, Eisai, Janssen Cilag, Johnson & Johnson, Lilly Deutschland, Lilly Int., MSD, Mundipharma, Myriad Genetics GmbH Zürich, Odonate, Pfizer GmbH Berlin, Puma Biotechnology, Riemser, Roche, Sanofi Aventis Deutschland GmbH, Sividon Diagnostics Köln, TEVA Pharmaceuticals Ind. Ltd. Berlin. I. Witzel: Not specified. A. Wöckel: Amgen, AstraZeneca, Aurikamed, Celgene, Eisai, Lilly, Novartis, Pfizer, Roche, Tesaro. V. Müller: Speaker honoraria: Amgen, AstraZeneca, Daiichi Sankyo, Eisai, Pfizer, MSD, Novartis, Roche, Teva, Seattle Genetics Consultancy honoraria: Genomic Health, Hexal, Roche, Pierre Fabre, Amgen, ClinSol, Novartis, MSD, Daiichi Sankyo, Eisai, Lilly, Tesaro, Nektar. Institutional research support: Novartis, Roche, Seattle Genetics, Genentech. W. Janni: Research grants and/or honoraria: Sanofi-Aventis, Novartis, Roche, Pfizer, AstraZeneca, Chugai, GSK, Eisai, Celgene, Lilly, Janssen, Menarini. N. Ditsch: MSD, Novartis, Pfizer, Roche, AstraZeneca, TEVA, Mentor, MCI Healthcare.

Background: Olaparib, a poly (ADP-ribose) polymerase (PARP) inhibitor, has previously been shown to extend progression-free survival versus placebo when given to patients with relapsed high-grade serous or endometrioid ovarian cancer who were platinum sensitive and who had a BRCA1 or BRCA2 (BRCA1/2) mutation, as part of the SOLO2/ENGOT-Ov21 trial. The aim of this final analysis is to investigate the effect of olaparib on overall survival., Methods: This double-blind, randomised, placebo-controlled, phase 3 trial was done across 123 medical centres in 16 countries. Eligible patients were aged 18 years or older, had an Eastern Cooperative Oncology Group performance status at baseline of 0-1, had histologically confirmed, relapsed, high-grade serous or high-grade endometrioid ovarian cancer, including primary peritoneal or fallopian tube cancer, and had received two or more previous platinum regimens. Patients were randomly assigned (2:1) to receive olaparib tablets (300 mg in two 150 mg tablets twice daily) or matching placebo tablets using an interactive web or voice-response system. Stratification was by response to previous chemotherapy and length of platinum-free interval. Treatment assignment was masked to patients, treatment providers, and data assessors. The primary endpoint of progression-free survival has been reported previously. Overall survival was a key secondary endpoint and was analysed in all patients as randomly allocated. Safety was assessed in all patients who received at least one treatment dose. This trial is registered with ClinicalTrials.gov, NCT01874353, and is no longer recruiting patients., Findings: Between Sept 3, 2013 and Nov 21, 2014, 295 patients were enrolled. Patients were randomly assigned to receive either olaparib (n=196 [66%]) or placebo (n=99 [34%]). One patient, randomised in error, did not receive olaparib. Median follow-up was 65·7 months (IQR 63·6-69·3) with olaparib and 64·5 months (63·4-68·7) with placebo. Median overall survival was 51·7 months (95% CI 41·5-59·1) with olaparib and 38·8 months (31·4-48·6) with placebo (hazard ratio 0·74 [95% CI 0·54-1·00]; p=0·054), unadjusted for the 38% of patients in the placebo group who received subsequent PARP inhibitor therapy. The most common grade 3 or worse treatment-emergent adverse event was anaemia (which occurred in 41 [21%] of 195 patients in the olaparib group and two [2%] of 99 patients in the placebo group). Serious treatment-emergent adverse events were reported in 50 (26%) of 195 patients receiving olaparib and eight (8%) of 99 patients receiving placebo. Treatment-emergent adverse events with a fatal outcome occurred in eight (4%) of the 195 patients receiving olaparib, six of which were judged to be treatment-related (attributed to myelodysplastic syndrome [n=3] and acute myeloid leukaemia [n=3])., Interpretation: Olaparib provided a median overall survival benefit of 12·9 months compared with placebo in patients with platinum-sensitive, relapsed ovarian cancer and a BRCA1/2 mutation. Although statistical significance was not reached, these findings are arguably clinically meaningful and support the use of maintenance olaparib in these patients., Funding: AstraZeneca and Merck., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Purpose: This study explores the sociodemographic, medical and work-related factors leading to a participation in an in-house rehabilitation measure after primary treatment for breast cancer., Methods: The prospective multi-center study is based on a written survey with employed breast cancer patients who were recruited at 11 breast cancer centers in Lower Saxony, Germany. Predictors of participation were examined by logistic regression, predictors of the time period before starting the rehabilitation by linear regression., Results: 409 patients returned their questionnaires at all three time-points. Response rates were 80,1% 3 weeks after surgery (t0), 95,2% 6 months after surgery (t1) and 89,9% one year after surgery (t2). Altogether, 294 patients (72%) participated in the rehabilitation measure. Respondents, 90% of whom participated in rehabilitation before returning to work, began their rehabilitation on average 21 weeks after primary surgery. They showed an increased probability of participation if they had indicated the need to clarify their job situation (OR=2,74, p<0,01), or if their answers displayed a detrimental relation between effort and reward at work (OR=3,89, p<0,05). At the same time, higher age, a higher level of school education (OR=4,23) and reduced physical health (OR=0,94, p<0,01) increased the chance for breast cancer patients to take part in oncological rehabilitation. The starting point of rehabilitation was only predictable by medical treatments: adjuvant chemotherapy (β=0,492, p≤0,001), additional surgery (β=0,112, p<0,05), and radiation therapy within the second half year after primary surgery (β=0,20; p<0,001) led to a postponement., Conclusion: This study shows that an increased need of breast cancer patients for medical and socio-psychological support leads to their participation in an in-house rehabilitation and thus underlines the necessity of these institutions. Women with an impaired psychological health should be given extra attention., Competing Interests: Die Autorinnen/Autoren geben an, dass kein Interessenkonflikt besteht., (Thieme. All rights reserved.)

Background: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype., Methods: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype., Results: There was no evidence of heterogeneous associations between risk factors and mortality by subtype ( P adj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m 2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0-<5 years versus ≥10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking., Conclusions: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype., Impact: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care., (©2021 American Association for Cancer Research.)

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10 -8 , at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers.

Several scores have been developed in order to estimate the prognosis of patients with brain metastases (BM) by objective criteria. The aim of this analysis was to validate all three published graded-prognostic-assessment (GPA)-scores in a subcohort of 882 breast cancer (BC) patients with BM in the Brain Metastases in the German Breast Cancer (BMBC) registry. The median age at diagnosis of BM was 57 years. All in all, 22.3% of patients ( n = 197) had triple-negative, 33.4% ( n = 295) luminal A like, 25.1% ( n = 221) luminal B/HER2-enriched like and 19.2% ( n = 169) HER2 positive like BC. Age ≥60 years, evidence of extracranial metastases (ECM), higher number of BM, triple-negative subtype and low Karnofsky-Performance-Status (KPS) were all associated with worse overall survival (OS) in univariate analysis ( p < 0.001 each). All three GPA-scores were associated with OS. The breast-GPA showed the highest probability of classifying patients with survival above 12 months in the best prognostic group (specificity 68.7% compared with 48.1% for the updated breast-GPA and 21.8% for the original GPA). Sensitivities for predicting 3 months survival were very low for all scores. In this analysis, all GPA-scores showed only moderate diagnostic accuracy in predicting the OS of BC patients with BM.

Background: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk., Methods: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry., Results: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10 -18 ); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10 -8 )., Conclusions: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.

Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers., Methods: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data., Results: Genetic correlation analysis revealed significant genetic correlation between the two cancers ( r G = 0.43, P = 2.66 × 10 -5 ). We found seven loci associated with risk for both cancers ( P Bonferroni < 2.4 × 10 -9 ). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified ( P < 5 × 10 -7 ). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation., Conclusions: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis., Impact: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings., (©2020 American Association for Cancer Research.)

Epithelial ovarian carcinoma (EOC) is a genetically heterogeneous disease that is partly driven by molecular defects in mismatch repair (MMR) or homology-directed DNA repair (HDR). Ribonuclease H2 serves to remove mis-incorporated ribonucleotides from DNA which alleviates HDR mechanisms and guides the MMR machinery. Although Ribonuclease H2 has been implicated in cancer, the role of germline variants for ovarian cancer is unknown. In the present case-control study, we sequenced the coding and flanking untranslated regions of the RNASEH2A, RNASEH2B and RNASEH2C genes, encoding all three subunits of Ribonuclease H2, in a total of 602 German patients with EOC and of 940 healthy females from the same population. We identified one patient with a truncating variant in RNASEH2B, p.C44X, resulting in a premature stop codon. This patient had high-grade serous EOC with an 8 years survival after platinum/taxane-based therapy. Subsequent analysis of TCGA data similarly showed a significantly longer progression-free survival in ovarian cancer patients with low RNASEH2B or RNASEH2C expression levels. In conclusion, loss-of-function variants in Ribonuclease H2 genes are not common predisposing factors in ovarian cancer but the possibility that they modulate therapeutic platinum response deserves further investigation.

Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS 313 ) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS 313 was quantified using Cox regression analyses. We assessed PRS 313 interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS 313 was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS 313 was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10 th percentile and 20.5% at the 90 th percentile of PRS 313 . We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS 313 alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS 313 is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies., (Copyright © 2020 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Background: Limited evidence exists to support CA-125 as a valid surrogate biomarker for progression in patients with ovarian cancer on maintenance PARP inhibitor (PARPi) therapy. We aimed to assess the concordance between CA-125 and Response Evaluation Criteria in Solid Tumours (RECIST) criteria for progression in patients with BRCA mutations on maintenance PARPi or placebo., Methods: We extracted data on progression as defined by Gynecologic Cancer InterGroup CA-125, investigator- and independent central-assessed RECIST from the SOLO2/ENGOT-ov21(NCT01874353) trial. We excluded those with progression other than by RECIST, progression on date of randomisation, and no repeat CA-125 beyond baseline. We evaluated the concordance between CA-125 progression and RECIST progression, and assessed the negative (NPV) and positive predictive value (PPV)., Results: Of 295 randomised patients, 275 (184 olaparib, 91 placebo) were included. 171 patients had investigator-assessed RECIST progression. Of 80 patients with CA-125 progression, 77 had concordant RECIST progression (PPV 96%, 95% confidence interval 90-99%). Of 195 patients without CA-125 progression, 94 had RECIST progression (NPV 52%, 45-59%). Within treatment arms, PPV was similar (olaparib: 95% [84-99%], placebo: 97% [87-100%]) but NPV was lower in patients on placebo (olaparib: 60% [52-68%], placebo: 30% [20-44%]). Of 94 patients with RECIST but without CA-125 progression, 64 (68%) had CA-125 that remained within normal range. We observed similar findings using independent-assessed RECIST., Conclusions: Almost half the patients without CA-125 progression had RECIST progression, and most of these had CA-125 within the normal range. Regular computed tomography imaging should be considered as part of surveillance in patients treated with or without maintenance olaparib rather than relying on CA-125 alone., Competing Interests: Conflict of interest statement AT, CKL, MF, JAL, RTP, AMO, JYL, KF and GSS report institutional research funding from AstraZeneca. MF, LG, JAL, RTP, NC, TWPS and EPL have received honoraria from AstraZeneca. MF and LM been involved in a Speakers' bureau for AstraZeneca. CKL has received honoraria and research funding from AstraZeneca. CKL, MF, JAL, RTP, JK, LM, CP, NC, TWPS, KF, IV and EPL have provided a consulting or advisory role to AstraZeneca. JYL has received grant support from AstraZeneca and delivered lectures for AstraZeneca. AT, CKL, MF, RTP, AMO, TWPS, IV and EPL have received travel and accommodation funding from AstraZeneca. AMO discloses other relationship with AstraZeneca. EPL discloses other relationship with ARCAGY RESEARCH. All remaining authors have declared no conflicts of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background : Brain metastases (BM) have become a major challenge in patients with metastatic breast cancer. Methods : The aim of this analysis was to characterize patients with asymptomatic BM ( n = 580) in the overall cohort of 2589 patients with BM from our Brain Metastases in Breast Cancer Network Germany (BMBC) registry. Results : Compared to symptomatic patients, asymptomatic patients were slightly younger at diagnosis (median age: 55.5 vs. 57.0 years, p = 0.01), had a better performance status at diagnosis (Karnofsky index 80-100%: 68.4% vs. 57%, p < 0.001), a lower number of BM (>1 BM: 56% vs. 70%, p = 0.027), and a slightly smaller diameter of BM (median: 1.5 vs. 2.2 cm, p < 0.001). Asymptomatic patients were more likely to have extracranial metastases (86.7% vs. 81.5%, p = 0.003) but were less likely to have leptomeningeal metastasis (6.3% vs. 10.9%, p < 0.001). Asymptomatic patients underwent less intensive BM therapy but had a longer median overall survival (statistically significant for a cohort of HER2-positive patients) compared to symptomatic patients (10.4 vs. 6.9 months, p < 0.001). Conclusions : These analyses show a trend that asymptomatic patients have less severe metastatic brain disease and despite less intensive local BM therapy still have a better outcome (statistically significant for a cohort of HER2-positive patients) than patients who present with symptomatic BM, although a lead time bias of the earlier diagnosis cannot be ruled out. Our analysis is of clinical relevance in the context of potential trials examining the benefit of early detection and treatment of BM.

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer., (© 2020 The Authors. Genetic Epidemiology published by Wiley Periodicals, Inc.)

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype 1-3 . To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10 -8 ), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

Competing Interests: Prof. Dr. med. Nina Ditsch: MSD, Roche, AstraZeneca, TEVA, Mentor, and MCI Healthcare. Prof. Dr. med. Michael Untch: Presentations, travel grants, all paid to his institution from: Abbvie, Amgen GmbH München, AstraZeneca, BMS, Celgene GmbH München, Daiji Sankyo, Eisai GmbH München, Janssen Cilag, Johnsen & Johnsen, Lilly Deutschland, Lilly Int., MSD Merck, Mundipharma, Myriad Genetics GmbH Zürich, Odonate, Pfizer GmbH Berlin, PUMA Biotechnology, Riemser, Roche Pharma AG, Grenzach Wyhlen, Sanofi Aventis Deutschland GmbH, Sividon Diagnostics Köln, TEVA Pharmaceuticals Ind. Ltd., and Berlin Pharmaceutical Industry. Prof. Dr. med. Cornelia Kolberg-Liedtke: Consulting: Phaon Scientific, Novartis, Pfizer, Pfizer, Novartis, SurgVision, Carl Zeiss Meditec, Amgen, and Onkowissen; presentations: Roche, Novartis, Pfizer, Lilly, Pfizer, Novartis, Roche, Genomic Health, Amgen, AstraZeneca, Riemser, Carl Zeiss Meditec, TEVA, Theraclion Janssen-Cilag, GSK, LIV Pharma, and Theramex; travel grants: Carl Zeiss Meditec, LIV Pharma, Novartis, Amgen, Pfizer, and Daiichi Sankyo. Prof. Dr. med. Christian Jackisch: Roche, AstraZeneca, and Novartis. Dr. David Krug: Merck Sharp & Dome. Prof. Dr. med. Michael Friedrich: Roche, Pfizer, AstraZeneca, and Novartis. Prof. Dr.med. Wolfgang Janni: Research grants and/or honoraria from: Sanofi-Aventis, Novartis, Roche, Pfizer, AstraZeneca, Chugai, GSK, Eisai, Cellgene, Lilly, Janssen, and Menarini. Prof. Dr. med. Volkmar Müller: Speaker honoraria from Amgen, AstraZeneca, Daiichi-Sankyo, Eisai, Pfizer, MSD, Novartis, Roche, Teva, and Seattle Genetics; consultancy honoraria from Genomic Health, Hexal, Roche, Pierre Fabre, Amgen, ClinSol, Novartis, MSD, Daiichi-Sankyo, Eisai, Lilly, Tesaro, and Nektar; institutional research support from Novartis, Roche, Seattle Genetics, and Genentech. Prof. Dr. med. Ute-Susann Albert: Lectures and/or consulting: Medexo GmbH, Institut für Versicherungsmedizin (IMV), and Pfizer. PD Dr. Malgorzata Banys-Paluchowski: Pfizer, Roche, Novartis, and Eli Lilly. Dr. med. Ingo Bauerfeind: Aurikamed and J. Eickeler. Prof. Dr. med. Jens-Uwe Blohmer: Honoraria: Amgen, AstraZeneca, Genomic Health Recipient, MSD Oncology, Myriad Genetics, Novartis, Pfizer, Roche, and Sonoscape; travel, accommodations, expenses: Pfizer and Roche. Prof. Dr. med. Wilfried Budach: No conflicts of interest. Prof. Dr. med. Peter Dall: Advisory boards: Olympus, Roche, Novartis, and Tesaro; congress support: Roche; lecture fees: Amgen and Roche. Prof. Dr. med. Ingo Diel: No conflicts of interest regarding this manuscript. PD Dr. med. Eva Maria Fallenberg: GE-Healthcare, Siemens, ECR, EUSOBI, ESOR, KCR, and DFG. Prof. Dr. med. Peter A. Fasching: Grants from Novartis, Biontech, and Cepheid; personal fees from Novartis, Roche, Pfizer, Celgene, Daiichi-Sankyo, AstraZeneca, Merck Sharp & Dohme, Myelo Therapeutics, Macrogenics, Eisai, Puma, and Lilly. Prof. Dr. med. Tanja Fehm: AstraZeneca, Celegene, Pfizer, Novartis, Roche, Teva, and Daichii Sankyo. Prof. Dr. med. Bernd Gerber: No conflicts of interest. PD Dr. med. Oleg Gluz: Honoraria for lectures and/or consulting: Celgene, Roche, Genomic Health, Amgen, Pfizer, Novartis, Lilly, Nanostring, Eisai, and MSD; travel grants: Celgene, Roche, and Daiichi Sankyo. Prof. Dr. Volker Hanf: No conflicts of interest regarding this manuscript. Prof. Dr. med. Nadia Harbeck: Honoraria for lectures and/or consulting: Agendia, Amgen, AstraZeneca, BMS, Celgene, Daiichi-Sankyo, Genomic Health, Lilly, MSD, Novartis, Odonate, Pierre Fabre, Pfizer, Roche, Sandoz/Hexal, and Seattle Genetics; Minority shareholder: Westdeutsche Studiengruppe (WSG). Prof. Dr. med. Jörg Heil: No conflicts of interest. Prof. Dr. med. Jens Huober: Research grants: Celgene, Novartis, and Hexal; lecture honoraria: Lilly, Novartis, Roche, Pfizer, AstraZeneca, MSD, Celgene, Eisai, and Abbvie; consulting: Lilly, Novartis, Roche, Pfizer, Hexal, AstraZeneca, MSD, Celgene, and Abbvie; travel expenses: Roche, Pfizer, Novartis, Celgene, and Daiichi. Herr Prof. Dr. med. habil. Hans H. Kreipe: Reimbursement for attending symposia: Ventana; other expenses (advisory boards, lectures): AMGEN, AstraZeneca, Genomic Health, Lilly, and Roche Pharma. Prof. Dr.med. Thorsten Kühn: Celgene, Roche, and Pfizer. Prof. Dr. med. Sherko Kümmel: Roche, Genentech, Novartis, AstraZeneca, Amgen, Celegene, SOMATEX, Daiichi Sankyo, Puma Biotechnologx, pfm medical, Pfizer, and MSD Oncology. Prof. Dr. med. Sibylle Loibl: Abbvie, Amgen, AstraZeneca, Celgene, Novartis, Pfizer, Roche, Seattle Genetics, PriME/Medscape, Chugai, Teva, Vifor, Daiichi-Sankyo, Lilly, Samsung, Eirgenix, BMS, Puma, MSD, and Immunomedics. Prof. Dr. med. Diana Lüftner: Advisory boards/oral presentations: Amgen, AstraZeneca, Celegene, Lilly, Loreal, MSD, Mundipharma, Mylan, Novartis, Pfizer, Roche, Teva, and Tesaro. Prof. Dr. med. Michael Lux: Lilly, Pfizer, Roche, MSD, Hexal, Novartis, AstraZeneca, Eisai, Medac, and Genomic Health for advisory boards, lectures, and travel support. Prof. Dr. med. Nicolai Maass: No conflicts of interest. Prof. Dr. med. Volker Moebus: Amgen, Celegene, Roche, Myelotherapeutics, Roche, and Amgen. Prof. Dr. med. Christoph Mundhenke: Not specified. Prof. Dr. Tjoung-Won Park-Simon: Advisory role or expert testimony and lecture honoraria: Roche, AstraZeneca, Tesaro, Pfizer, Daichii, Lilly, and MSD; participation in clinical trials: Roche, AstraZeneca, Tesaro, Pfizer Daichii, Lilly, MSD, Novartis, and Seattle Genetics; other financial relationships, e.g., travel: Roche, AstraZeneca, Tesaro, Pfizer, Lilly, MSD, and Novartis. Prof. Dr. med. Toralf Reimer: grants from German Cancer Aid and Else Kroener-Fresenius-Stiftung; personal fees from Pfizer, Roche, Novartis, and AstraZeneca, outside the submitted work. PD. Dr. med. Kerstin Rhiem: AstraZeneca, Tesaro, Pfizer, and Roche. Prof. Dr. med. Achim Rody: Roche, Pfizer, Novartis, Celgen, Novartis, Genomic Health/Exact Sciences, AstraZeneca, Eisai, MSD, Hexal, and Amgen. Prof. Dr. med. Markus Schmidt: Honoraria: AstraZeneca, Novartis, Pfizer, and Roche; consulting or advisory role: AMGEN, AstraZeneca, BioNTech, Eisai, Lilly, Myelo Therapeutics, Novartis, Pantarhei Bioscience, Pfizer, and Roche; travel, accommodations, expenses: BioNTech, Pantarhei Bioscience, Pfizer, and Roche; patents, royalties, other intellectual property: Patent issued EP2951317. Prof. Dr. med. Andreas Schneeweiss: Grants: Celgene, Roche, Abbvie, and Molecular Partner; personal fees: Roche, AstraZeneca, Celgene, Pfizer, Novartis, MSD, Tesaro, and Lilly. Prof. Dr. med. Christine Solbach: Travel, accommodations: Roche, Novartis, AstraZeneca, Amgen, Celgene, Hexal, Daiichi Sankyo, Dialog Service GmbH, Lilly, Pfizer, MSD Oncology, ESAI, Gedon Richter, Mylan, and Tesaro. Prof. Dr. med. Erich-Franz Solomayer: Roche, AstraZeneca, Pfizer Roche, Amgen, Celgen, Tesaro, AstraZeneca, Pfizer, Storz, Erbe, Gedeon Richter, Eisai, Medac, MSD, Vifor, Teva, and Ethikon. Prof. Dr. med. Elmar Stickeler: Consulting: Novartis, Pfizer, AstraZeneca, Roche, and Tesoro; honoraria: Novartis, Pfizer, AstraZeneca, and Roche. Prof. Dr. med. Christoph Thomssen: Advisory boards, lectures: Amgen, AstraZeneca, Celgen, Daiichi-Sankyo, Eisai, Lilly, MSD, Mundipharma, Medapharm, Novartis, Pfizer, Pierre-Fabre, Roche, Tesaro, and Vifor. PD Dr. Isabell Witzel: Not specified. Prof. Dr. med. Achim Wöckel: Amgen, AstraZeneca, Aurikamed, Celgene, Eisai, Lilly, Novartis, Pfizer, Roche, and Tesaro. PD. Dr. med. Marc Thill: Advisory board: Amgen, AstraZeneca, Celgene, ClearCut, Clovis, Daiichi Sankyo, Exact Sciences, Lilly, MSD, Neodynamics, Novartis, Pfizer, pfm Medical, Pierre-Fabre, Roche, and Tesaro; manuscript support: Amgen, Celgene, and Roche; travel expenses: Amgen, Art Tempi, AstraZeneca, Celgene, Clovis, Connect Medica, Daiichi Sankyo, Exact Sciences, Hexal, I-Med-Institute, Lilly, MCI, MSD, Novartis, Pfizer, pfm Medical, Roche, and Tesaro; congress costs: Amgen, AstraZeneca, Celgene, Daiichi Sanyko, Hexal, Novartis, Pfizer, and Roche; lectures: Amgen, Art Tempi, AstraZeneca, Celgene, Clovis, Connect Medica, Exact Sciences, Hexal, I-Med-Institute, Lilly, MCI, MSD, Novartis, OnkoLive, Pfizer, pfm Medical, and Roche; trial funding: Exact Sciences.

Background: State-of-the art therapy for recurrent ovarian cancer suitable for platinum-based re-treatment includes bevacizumab-containing combinations (eg, bevacizumab combined with carboplatin-paclitaxel or carboplatin-gemcitabine) or the most active non-bevacizumab regimen: carboplatin-pegylated liposomal doxorubicin. The aim of this head-to-head trial was to compare a standard bevacizumab-containing regimen versus carboplatin-pegylated liposomal doxorubicin combined with bevacizumab., Methods: This multicentre, open-label, randomised, phase 3 trial, was done in 159 academic centres in Germany, France, Australia, Austria, and the UK. Eligible patients (aged ≥18 years) had histologically confirmed epithelial ovarian, primary peritoneal, or fallopian tube carcinoma with first disease recurrence more than 6 months after first-line platinum-based chemotherapy, and an Eastern Cooperative Oncology Group performance status of 0-2. Patients were stratified by platinum-free interval, residual tumour, previous antiangiogenic therapy, and study group language, and were centrally randomly assigned 1:1 using randomly permuted blocks of size two, four, or six to receive six intravenous cycles of bevacizumab (15 mg/kg, day 1) plus carboplatin (area under the concentration curve [AUC] 4, day 1) plus gemcitabine (1000 mg/m 2 , days 1 and 8) every 3 weeks or six cycles of bevacizumab (10 mg/kg, days 1 and 15) plus carboplatin (AUC 5, day 1) plus pegylated liposomal doxorubicin (30 mg/m 2 , day 1) every 4 weeks, both followed by maintenance bevacizumab (15 mg/kg every 3 weeks in both groups) until disease progression or unacceptable toxicity. There was no masking in this open-label trial. The primary endpoint was investigator-assessed progression-free survival according to Response Evaluation Criteria in Solid Tumors version 1.1. Efficacy data were analysed in the intention-to-treat population. Safety was analysed in all patients who received at least one dose of study drug. This completed study is registered with ClinicalTrials.gov, NCT01837251., Findings: Between Aug 1, 2013, and July 31, 2015, 682 eligible patients were enrolled, of whom 345 were randomly assigned to receive carboplatin-pegylated liposomal doxorubicin-bevacizumab (experimental group) and 337 were randomly assigned to receive carboplatin-gemcitabine-bevacizumab (standard group). Median follow-up for progression-free survival at data cutoff (July 10, 2018) was 12·4 months (IQR 8·3-21·7) in the experimental group and 11·3 months (8·0-18·4) in the standard group. Median progression-free survival was 13·3 months (95% CI 11·7-14·2) in the experimental group versus 11·6 months (11·0-12·7) in the standard group (hazard ratio 0·81, 95% CI 0·68-0·96; p=0·012). The most common grade 3 or 4 adverse events were hypertension (88 [27%] of 332 patients in the experimental group vs 67 [20%] of 329 patients in the standard group) and neutropenia (40 [12%] vs 73 [22%]). Serious adverse events occurred in 33 (10%) of 332 patients in the experimental group and 28 (9%) of 329 in the standard group. Treatment-related deaths occurred in one patient in the experimental group (<1%; large intestine perforation) and two patients in the standard group (1%; one case each of osmotic demyelination syndrome and intracranial haemorrhage)., Interpretation: Carboplatin-pegylated liposomal doxorubicin-bevacizumab is a new standard treatment option for platinum-eligible recurrent ovarian cancer., Funding: F Hoffmann-La Roche., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

Background: For individuals with ovarian cancer (OC), therapy options mainly depend on BRCA1/2 germline status. What is the prevalence of deleterious somatic variants, that is, does genetic tumour testing identify subgroups of individuals who also might benefit from targeted therapy?, Methods: Paired analysis of tumour-derived versus blood-derived DNA to determine the prevalence of deleterious somatic variants in OC predisposition genes ( ATM , BRCA1/2, BRIP1 , MSH2/6 , PALB2 , RAD51C/D and TP53 ) and the PIK3CA and PTEN genes in individuals with OC (AGO-TR1 study, NCT02222883). Results were complemented by BRCA1 , PALB2 and RAD51C promoter methylation analyses and stratified by histological subtype; 473 individuals were included., Results: The combined analyses revealed that deleterious germline variants in established OC predisposition genes (all: 125/473, 26.4%; BRCA1/2 : 97/473, 20.5%), deleterious somatic variants in established OC predisposition genes excluding TP53 (all: 39/473, 8.2%; BRCA1/2 : 30/473, 6.3%) and promoter methylation (all: 67/473, 14.2%; BRCA1 : 57/473, 12.1%; RAD51C : 10/473, 2.1%; PALB2 : 0/473) were mutually exclusive, with a few exceptions. The same holds true for deleterious somatic PIK3CA and/or PTEN variants (33/473, 7.0%) found to be enriched in endometrioid and clear cell OC (16/35, 45.7%); 84.3 % of the deleterious single-nucleotide/indel germline variants in established OC predisposition genes showed significantly higher variant fractions (VFs) in the tumour-derived versus blood-derived DNA, indicating a loss of the wild-type alleles., Conclusion: Tumour sequencing of the BRCA1, BRCA2, PIK3CA and PTEN genes along with BRCA1 and RAD51C promoter methylation analyses identified large subgroups of germline mutation-negative individuals who may be addressed in interventional studies using PARP or PI3K/AKT/mTOR inhibitors., Trial Registration Number: NCT02222883., Competing Interests: Competing interests: EH: honoraria: AstraZeneca; consulting or advisory role: AstraZeneca; research funding: Astra Zeneca (Inst). SS: honoraria: Roche; consulting or advisory role: Tesaro. KK: honoraria: Roche, Pfizer and AstraZeneca. JP: honoraria: Roche Pharma AG; consulting or advisory role: Amgen, AstraZeneca, Coherus Bioscience, DeciBio, F. Hoffmann-La Roche, Pharmamar, Shield Therapeutics, Simon Kucher & Partner, Taylor Wessing LLP and Tesaro; research funding: Astra Zeneca, Hoffmann-La Roche and Tesaro; travel, accommodations and expenses: Amgen, Astra Zeneca, F. Hoffmann-La Roche and Tesaro. AS: honoraria: TEVA and Gedeon Richter; consulting or advisory role: Astra Zeneca and Roche. SK: honoraria: AstraZeneca and Roche; consulting or advisory role: Roche. KP: travel and research funding: Medac Oncology; honoraria: AstraZeneca and Roche. DD is a consultant for AJ Innuscreen GmbH (Berlin, Germany), a 100% daughter company of Analytik Jena AG (Jena, Germany) and receives royalties from product sales (innuCONVERT kits). AdB: consulting or advisory role: AstraZeneca, Pfizer, Pharmamar, Roche/Genentech, Advaxis, Tesaro, Genmab, Clovis and Biocad. RKS: honoraria: AstraZeneca; consulting or advisory role: AstraZeneca; research funding: AstraZeneca (Inst); patents, royalties, other intellectual property: University of Cologne. CK: consulting and advisory role: AstraZeneca and Roche/Genentech. PH: consulting or advisory role: AstraZeneca, Roche/Genentech, Tesaro, Clovis, Pharmamar Lilly and Sotio; research funding: AstraZeneca (Inst); travel, accommodations and expenses: Medac., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.

Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.

Background: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry., Methods: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP)., Results: We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10 -8 . For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10 -7 , hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84-0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10 -7 , HR = 1.27, 95% CI = 1.16-1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster., Conclusions: We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

We report recent progress in the development of a precision test for individualized use of the VEGF-A targeting drug bevacizumab for treating ovarian cancer. We discuss the discovery model stage (i.e., past feasibility modeling and before conversion to the production test). Main results: (a) Informatics modeling plays a critical role in supporting driving clinical and health economic requirements. (b) The novel computational models support the creation of a precision test with sufficient predictivity to reduce healthcare system costs up to $30 billion over 10 years, and make the use of bevacizumab affordable without loss of length or quality of life., ((c) Connecting development of precision medicine tests to Randomized Clinical Trials enhances the robustness of computational modeling, accelerates development and validation of the precision test by 5-10 years, is highly generalizable and scalable, and should thus be considered as a high-priority design for similar precision medicine efforts.)

Purpose To investigate the safety and clinical activity of comprehensive human epidermal growth factor receptor (HER) family receptor inhibition using lumretuzumab (anti-HER3) and pertuzumab (anti-HER2) in combination with paclitaxel in patients with metastatic breast cancer (MBC). Methods This phase Ib study enrolled 35 MBC patients (first line or higher) with HER3-positive and HER2-low (immunohistochemistry 1+ to 2+ and in-situ hybridization negative) tumors. Patients received lumretuzumab (1000 mg in Cohort 1; 500 mg in Cohorts 2 and 3) plus pertuzumab (840 mg loading dose [LD] followed by 420 mg in Cohorts 1 and 2; 420 mg without LD in Cohort 3) every 3 weeks, plus paclitaxel (80 mg/m 2 weekly in all cohorts). Patients in Cohort 3 received prophylactic loperamide treatment. Results Diarrhea grade 3 was a dose-limiting toxicity of Cohort 1 defining the maximum tolerated dose of lumretuzumab when given in combination with pertuzumab and paclitaxel at 500 mg every three weeks. Grade 3 diarrhea decreased from 50% (Cohort 2) to 30.8% (Cohort 3) with prophylactic loperamide administration and omission of the pertuzumab LD, nonetheless, all patients still experienced diarrhea. In first-line MBC patients, the objective response rate in Cohorts 2 and 3 was 55% and 38.5%, respectively. No relationship between HER2 and HER3 expression or somatic mutations and clinical response was observed. Conclusions Combination treatment with lumretuzumab, pertuzumab and paclitaxel was associated with a high incidence of diarrhea. Despite the efforts to alter dosing, the therapeutic window remained too narrow to warrant further clinical development., Trial Registration: on ClinicalTrials.gov with the identifier NCT01918254 first registered on 3rd July 2013.

Background: Observational studies suggest greater height is associated with increased ovarian cancer risk, but cannot exclude bias and/or confounding as explanations for this. Mendelian randomisation (MR) can provide evidence which may be less prone to bias., Methods: We pooled data from 39 Ovarian Cancer Association Consortium studies (16,395 cases; 23,003 controls). We applied two-stage predictor-substitution MR, using a weighted genetic risk score combining 609 single-nucleotide polymorphisms. Study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted height and risk were pooled using random-effects meta-analysis., Results: Greater genetically predicted height was associated with increased ovarian cancer risk overall (pooled-OR (pOR) = 1.06; 95% CI: 1.01-1.11 per 5 cm increase in height), and separately for invasive (pOR = 1.06; 95% CI: 1.01-1.11) and borderline (pOR = 1.15; 95% CI: 1.02-1.29) tumours., Conclusions: Women with a genetic propensity to being taller have increased risk of ovarian cancer. This suggests genes influencing height are involved in pathways promoting ovarian carcinogenesis.

F-box proteins participate in multiple cellular processes through ubiquitylation and subsequent degradation of target proteins, such as cyclin D1 as target of FBXW8. To investigate the spectrum of FBXW8 germ-line mutations in patients with breast cancer and healthy controls, we analyzed the whole FBXW8 coding region and flanking untranslated portions in germ-line DNA samples of 91 breast cancer patients and 277 healthy controls using next-generation amplicon sequencing. Five missense variants, one splice site variant, one frameshift variant, one synonymous variant, and one variant in the 3'-UTR were identified. Frameshift mutation FBXW8 c.1312&#95;1313delGT was considered functionally relevant and was investigated for its potential association with breast cancer risk through subsequent genotyping in two hospital-based breast cancer case-control series from Belarus and Germany, respectively, comprising a total of 2740 breast cancer cases and 2174 controls. The mutation was found in 30 cases and 23 controls with an adjusted Odds Ratio 1.02 (95% CI 0.59-1.77; p = 0.94) in the combined analysis. There was no statistically significant difference when patients were stratified by ER status, PR status, age at diagnosis, ductal histology, contralateral status, family history or tumor grade. Altogether, our data exclude clinically actionable breast cancer risks above two-fold for the FBXW8 c.1312&#95;1313delGT mutation, although larger studies would be needed to exclude low-penetrance associations., (Copyright © 2017. Published by Elsevier Inc.)

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10 -8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.