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Background Combining immune-checkpoint inhibitors with chemotherapy yielded an increased response rates in patients with metastatic triple-negative breast cancer (TNBC). Therefore, we evaluated the addition of durvalumab to standard neoadjuvant chemotherapy (NACT) in primary TNBC. Patients and methods GeparNuevo is a randomised phase II double-blind placebo-controlled study randomising patients with TNBC to durvalumab or placebo given every 4 weeks in addition to nab-paclitaxel followed by standard EC. In the window-phase durvalumab/placebo alone was given 2 weeks before start of nab-paclitaxel. Randomisation was stratified by stromal tumour-infiltrating lymphocyte (sTILs). Patients with primary cT1b-cT4a-d disease, centrally confirmed TNBC and sTILs were included. Primary objective was pathological complete response (pCR) (ypT0 ypN0). Results A total of 174 patients were randomised, 117 participated in the window-phase. Median age was 49.5 years (range 23–76); 47 patients (27%) were younger than 40 years; 113 (65%) had stage ≥IIA disease, 25 (14%) high sTILs, 138 of 158 (87%) were PD-L1-positive. pCR rate with durvalumab was 53.4% (95% CI 42.5% to 61.4%) versus placebo 44.2% (95% CI 33.5% to 55.3%; unadjusted continuity corrected χ 2 P  =   0.287), corresponding to OR = 1.45 (95% CI 0.80–2.63, unadjusted Wald P  =   0.224). Durvalumab effect was seen only in the window cohort (pCR 61.0% versus 41.4%, OR = 2.22, 95% CI 1.06–4.64, P  =   0.035; interaction P  =   0.048). In both arms, significantly increased pCR (P  <   0.01) were observed with higher sTILs. There was a trend for increased pCR rates in PD-L1-positive tumours, which was significant for PD-L1-tumour cell in durvalumab (P  =   0.045) and for PD-L1-immune cell in placebo arm (P  =   0.040). The most common immune-related adverse events were thyroid dysfunction any grade in 47%. Conclusions Our results suggest that the addition of durvalumab to anthracycline-/taxane-based NACT increases pCR rate particularly in patients treated with durvalumab alone before start of chemotherapy. Trial registration ClinicalTrials.gov number: NCT02685059. [ABSTRACT FROM AUTHOR]

Background The proliferation marker Ki67 has been suggested as a promising cancer biomarker. As Ki67 needs an exact quantification, this marker is a prototype of a new generation of tissue-based biomarkers. In this study, we have systematically evaluated different cut points for Ki67 using three different clinical end points in a large neoadjuvant study cohort. Patients and methods We have evaluated pretherapeutic Ki67 levels by immunohistochemistry in 1166 breast cancer core biopsies from the neoadjuvant GeparTrio trial. We used the standardized cutoff-finder algorithm for three end points [response to neoadjuvant chemotherapy (pCR), disease-free (DFS) and overall-survival (OS)]. The analyses were stratified for hormone receptor (HR) and HER2 status by molecular subtype radar diagrams (MSRDs). Results A wide range of Ki67 cut points between 3%–94% (for pCR), 6%–46% (for DFS) and 4%–58% (for OS) were significant. The three groups of Ki67 ≤ 15% versus 15.1%–35% versus >35% had pCR-rates of 4.2%, 12.8%, and 29.0% (P < 0.0005), this effect was also present in six of eight molecular subtypes. In MSRD, Ki67 was significantly linked to prognosis in uni- and multivariate analysis in the complete cohort and in HR-positive, but not triple-negative tumors. Conclusions Ki67 is a significant predictive and prognostic marker over a wide range of cut points suggesting that data-derived cut point optimization might not be possible. Ki67 could be used as a continuous marker; in addition, the scientific community could define standardized cut points for Ki67. Our analysis explains the variability observed for Ki67 cut points in previous studies; however, this should not be seen as weakness, but as strength of this marker. MSRDs are an easy new approach for visualization of biomarker effects on outcome across molecular subtypes in breast cancer. The experience with Ki67 could provide important information regarding the development and implementation of other quantitative biomarkers. [ABSTRACT FROM AUTHOR]

Background: Different endogenous and exogenous mutational processes act over the evolutionary history of a malignant tumor, driven by abnormal DNA editing, mutagens or age-related DNA alterations, among others, to generate the specific mutational landscape of each individual tumor. The signatures of these mutational processes can be identified in large genomic datasets. We investigated the hypothesis that genomic patterns of mutational signatures are associated with the clinical behavior of breast cancer, in particular chemotherapy response and survival, with a particular focus on therapy-resistant disease., Patients and Methods: Whole exome sequencing was carried out in 405 pretherapeutic samples from the prospective neoadjuvant multicenter GeparSepto study. We analyzed 11 mutational signatures including biological processes such as APOBEC-mutagenesis, homologous recombination deficiency (HRD), mismatch repair deficiency and also age-related or tobacco-induced alterations., Results: Different subgroups of breast carcinomas were defined mainly by differences in HRD-related and APOBEC-related mutational signatures and significant differences between hormone-receptor (HR)-negative and HR-positive tumors as well as correlations with age, Ki-67 and immunological parameters were observed. We could identify mutational processes that were linked to increased pathological complete response rates to neoadjuvant chemotherapy with high significance. In univariate analyses for HR-positive tumors signatures, S3 (HRD, P < 0.001) and S13 (APOBEC, P = 0.001) as well as exonic mutation rate (P = 0.002) were significantly correlated with increased pathological complete response rates. The signatures S3 (HRD, P = 0.006) and S4 (tobacco, P = 0.011) were prognostic for reduced disease-free survival of patients with chemotherapy-resistant tumors., Conclusion: The results of this investigation suggest that the clinical behavior of a tumor, in particular, response to neoadjuvant chemotherapy and disease-free survival of therapy-resistant tumors, could be predicted by the composition of mutational signatures as an indicator of the individual genomic history of a tumor. After additional validations, mutational signatures might be used to identify tumors with an increased response rate to neoadjuvant chemotherapy and to define therapy-resistant subgroups for future therapeutic interventions., Competing Interests: Disclosure CD reports personal fees from Novartis, personal fees and travel support from Roche, personal fees from MSD Oncology, from Daiichi Sankyo, grants from Myriad Genetics and GBG, other from Sividon Diagnostics/Myriad, outside the submitted work. In addition, CD has a patent EP18209672 pending, a patent EP20150702464 pending and a patent Software (VMscope digital pathology) pending. MU reports personal fees and non-financial support from Abbvie, personal fees and non-financial support from Amgen GmbH, personal fees and non-financial support from AstraZeneca, personal fees from Bristol Myers Squibb (BMS), personal fees and non-financial support from Celgene GmbH, personal fees and non-financial support from Daiji Sankyo, personal fees and non-financial support from Eisai GmbH, personal fees from Lilly Deutschland, personal fees and non-financial support from Lilly Int., personal fees and non-financial support from MSD Merck, personal fees and non-financial support from Mundipharma, personal fees and non-financial support from Myriad Genetics, personal fees and non-financial support from Odonate, personal fees and non-financial support from Pfizer GmbH, personal fees from PUMA Biotechnology, personal fees and non-financial support from Roche Pharma AG, personal fees and non-financial support from Sanofi Aventis Deutschland GmbH, personal fees and non-financial support from TEVA Pharmaceuticals Ind Ltd, personal fees and non-financial support from Novartis, personal fees from Pierre Fabre, personal fees and non-financial support from Clovis Oncology, outside the submitted work. SB reports other from NantOmics, LLC, during the conduct of the study; other from NantOmics, LLC, outside the submitted work; and Employee of NantOmics, LLC with equity interest. AS reports grants from Celgene, grants from Roche, grants from AbbVie, grants from Molecular Partner, personal fees from Roche, personal fees from AstraZeneca, personal fees from Celgene, personal fees from Roche, personal fees from Celgene, personal fees from Pfizer, personal fees from AstraZeneca, personal fees from Novartis, personal fees from MSD, personal fees from Tesaro, personal fees from Lilly, other from Roche, outside the submitted work. CJ reports personal fees from Roche, personal fees from Celgene, personal fees from Amgen, during the conduct of the study. TL reports non-financial support from Pharma Mar, non-financial support from Daiichi Sankyo, personal fees and non-financial support from MSD, personal fees from Amgen, personal fees and non-financial support from Pfizer, personal fees from Novartis, personal fees from Teva, personal fees from Tesaro, personal fees and non-financial support from Roche, personal fees and non-financial support from Clovis, non-financial support from Celgene, outside the submitted work. WDS reports grants from German Breast Group, during the conduct of the study; personal fees from AstraZeneca, outside the submitted work. VM reports grants and personal fees from Roche, during the conduct of the study; personal fees from Amgen, Astra Zeneca, Daiichi-Sankyo, Eisai, Pfizer, MSD, Novartis, Roche, Teva, Seattle Genetics and consultancy honoraria from Genomic Health, Hexal, Roche, Pierre Fabre, Amgen, ClinSol, Novartis, MSD, Daiichi-Sankyo, Eisai, Lilly, Tesaro, Nektar, personal fees from Genomic Health, Hexal, Roche, Pierre Fabre, Amgen, ClinSol, Novartis, MSD, Daiichi-Sankyo, Eisai, Lilly, Tesaro and Nektar, other from I Novartis, Roche, Seattle Genetics, Genentech, outside the submitted work. PSS is the CEO of NantOmics and reports non-financial support from NantOmics, outside the submitted work. MvM reports honoraria from Roche, Amgen, Genomic Health, Astra Zeneca, as well as travel support from Lilly and Novartis. PAF reports grants from Novartis, grants from BioNTech, personal fees from Novartis, personal fees from Roche, personal fees from Pfizer, personal fees from Celgene, personal fees from Daiichi-Sankyo, personal fees from AstraZeneca, personal fees from Merck Sharp & Dohme, personal fees from Eisai, personal fees from Puma, grants from Cepheid, personal fees from Lilly, personal fees from Seattle Genetics, during the conduct of the study. SR is the Chief Scientific Officer for NantOmics and reports non-financial support from NantOmics, outside the submitted work. SL reports grants and other from Celgene, grants and other from Roche, during the conduct of the study; grants and other from Abbvie, grants and other from Amgen, grants and other from AstraZeneca, grants and other from Novartis, grants and other from Pfizer, other from Seattle Genetics, other from PriME/Medscape, personal fees from Chugai, grants from Teva, grants from Vifor, grants and other from Daiichi-Sankyo, other from Lilly, other from Samsung, other from Eirgenix, other from BMS, other from Puma, other from MSD, grants from Immunomedics, outside the submitted work. In addition, SL has a patent EP14153692.0 pending. All other authors have declared no conflicts of interest., (Copyright © 2021 European Society for Medical Oncology. Published by Elsevier Ltd. All rights reserved.)

Background: The efficacy and toxicity of olaparib as combination therapy in early breast cancer (BC) patients with homologous recombinant deficiency (HRD) [score high and/or germline (g) or tumour (t) BRCA1/2 mutation] is not well described. GeparOLA (ClinicalTrials.gov, NCT02789332) investigated olaparib in combination with paclitaxel in HER2-negative early BC with HRD., Patients and Methods: Patients with untreated primary HER2-negative cT2-cT4a-d or cT1c with either cN+ or pNSLN+ or cT1c and triple-negative breast cancer (TNBC) or cT1c and Ki-67>20% BC with HRD were randomised either to paclitaxel (P) 80 mg/m 2 weekly plus olaparib (O) 100 mg twice daily for 12 weeks or P plus carboplatinum (Cb) area under the curve 2 weekly for 12 weeks, both followed by epirubicin/cyclophosphamide (EC). Stratification factors were hormone receptor (HR) status (HR+ versus HR-) and age (<40 versus ≥40 years). The primary endpoint was pathological complete response (pCR; ypT0/is ypN0). A two-sided one-group χ 2 -test was planned to exclude a pCR rate of ≤55% in the PO-EC arm. Secondary end points were other pCR definitions, breast conservation rate, clinical/imaging response, tolerability and safety., Results: A total of 107 patients were randomised between September 2016 and July 2018; 106 (PO N = 69; PCb N = 37) started treatment. Median age was 47.0 years (range 25.0-71.0); 36.2% had cT1, 61.0% cT2, 2.9% cT3, and 31.8% cN-positive tumours; grade 3 tumours: 86.8%; Ki-67>20%: 89.6%; TNBC: 72.6%; confirmed gBRCA1/2 mutation: 56.2%. The pCR rate with PO was 55.1% [90% confidence interval (CI) 44.5% to 65.3%] versus PCb 48.6% (90% CI 34.3% to 63.2%). Analysis for the stratified subgroups showed higher pCR rates with PO in the cohorts of patients <40 years and HR+ patients., Conclusion: GeparOLA could not exclude a pCR rate of ≤55% in the PO arm. PO was significantly better tolerated and the combination merits further evaluation., Competing Interests: Disclosure PAF reports grants from Novartis, BioNtech, personal fees from Novartis, Roche, Pfizer, Celgene, Daiichi Sankyo, AstraZeneca, MacroGenics, Eisai, Merck Sharp & Dohme, grants from Cepheid, personal fees from Lilly, during the conduct of the study. TL reports non-financial support from Pharma Mar, Daiichi Sankyo, Celgene; personal fees and non-financial support from MSD, Pfizer, Roche, Clovis; personal fees from Amgen, Novartis, Teva, Tesaro. AS reports grants from Celgene, Roche, AbbVie, Molecular Partners, expert testimony from Roche and AstraZeneca; travel expenses from Celgene, Roche and Pfizer, honoraria from Roche, Celgene, Pfizer, Novartis, AstraZeneca, MSD, Tesaro and Lilly, outside the submitted work. CJ reports personal fees from AstraZeneca and Roche during the conduct of the study. JH reports personal fees and travel expenses from Pfizer, Roche, AstraZeneca; personal fees from Lilly, Celgene, MSD, AbbVie, Eisai; grants from Hexal, Celgene; grants and personal fees from Novartis, travel expenses from Daiichi Sankyo, outside the submitted work. WDS reports grants from German Breast Group, during the conduct of the study; personal fees from AstraZeneca, outside the submitted work. SaS reports other from AstraZeneca during the conduct of the study; personal fees and advisory boards from Amgen, Hexal, Roche, Mundipharma; travel expenses from Novartis, outside the submitted work. CD reports personal fees from Novartis, Roche, MSD Oncology, Daiichi Sankyo, grants from Myriad Genetics, other from Sividon Diagnostics/Myriad outside the submitted work and has a patent EP18209672 pending, a patent EP20150702464 pending, and a patent software (VMscope digital pathology) pending. CH reports personal fees from Roche, Celgene, Pfizer, Lilly, AstraZeneca, Novartis outside the submitted work. KR reports personal fees from AstraZeneca, Tesaro, Pfizer outside the submitted work. RS reports grants from Cologne Furtune during the conduct of the study. J-UB reports personal fees from Amgen, AstraZeneca, MSD, Novartis, Pfizer, Roche, SonoScape, outside the submitted work. MU reports personal fees and non-financial support to the institute from AbbVie, Amgen GmbH, AstraZeneca, Celgene GmbH, Daiichi Sankyo, Eisai GmbH, MSD, Mundipharma, Myriad Genetics, Odonate, Pfizer GmbH, Roche, Sanofi Aventis Deutschland GmbH; Teva Pharmaceuticals Ind Ltd, Novartis, Clovis Oncology; personal fees and others from BMS, Lilly; personal fees from Puma Biotechnology, Pierre Fabre outside the submitted work. SL reports grants and honoraria from AstraZeneca during the conduct of the study; grants and honoraria from AbbVie, Amgen, Celgene, Novartis, Pfizer, Roche, other from Seattle Genetics, PriME/ Medscape; personal fees and lecture honoraria from Chugai, grants from Teva, Vifor, Immunomedics grants and honoraria from Daiichi Sankyo, honoraria from Lilly, Samsung, Eirgenix, BMS, Puma, MSD, outside the submitted work and has a patent EP14153692.0 pending. All other authors declare no conflict of interest., (Copyright © 2020 European Society for Medical Oncology. Published by Elsevier Ltd. All rights reserved.)

Background: The predictive value of tumor mutational burden (TMB), alone or in combination with an immune gene expression profile (GEP), for response to neoadjuvant therapy in early triple negative breast cancer (TNBC) is currently not known, either for immune checkpoint blockade (ICB) or conventional chemotherapy., Patients and Methods: We obtained both whole exome sequencing and RNA-Seq data from pretreatment samples of 149 TNBC of the recent neoadjuvant ICB trial, GeparNuevo. In a predefined analysis, we assessed the predictive value of TMB and a previously developed immune GEP for pathological complete remission (pCR)., Results: Median TMB was 1.52 mut/Mb (range 0.02-7.65) and was significantly higher in patients with pCR (median 1.87 versus 1.39; P = 0.005). In multivariate analysis, odds ratios for pCR per mut/Mb were 2.06 [95% confidence intervals (CI) 1.33-3.20, P = 0.001] among all patients, 1.77 (95% CI 1.00-3.13, P = 0.049) in the durvalumab treatment arm, and 2.82 (95% CI 1.21-6.54, P = 0.016) in the placebo treatment arm, respectively. We also found that both continuous TMB and immune GEP (or tumor infiltrating lymphocytes) independently predicted pCR. When we stratified patients in groups based on the upper tertile of TMB and median GEP, we observed a pCR rate of 82% (95% CI 60% to 95%) in the group with both high TMB and GEP in contrast to only 28% (95% CI 16% to 43%) in the group with both low TMB and GEP., Conclusions: TMB and immune GEP add independent value for pCR prediction. Our results recommend further analysis of TMB in combination with immune parameters to individually tailor therapies in breast cancer., Competing Interests: Disclosure This work was supported by grants and non-financial support from Astra Zeneca and other from Celgene during the conduct of the study, grants from Teva and Vifor, grants and other from AbbVie; Amgen; AstraZeneca; Celgene; Novartis; Pfizer; Roche; and Daiichi-Sankyo, other from Seattle Genetics; PriME/Medscape; Lilly; Samsung; and Eirgenix, and personal fees from Chugai outside the submitted work to SL. In addition, SL has a patent EP18209672 pending. CD reports personal fees from Teva; Novartis; Pfizer; Roche; Amgen; MSD; Celgene; and AstraZeneca; outside the submitted work, CD has patents EP20150702464 issued and EP18209672 pending and is a co-founder of Sividon Diagnostics. KEW had shares from Sividon Diagnostics, received employee inventor remuneration from a patent on the EndoPredict test, and has a patent EP18209672 pending. TK has a patent EP18209672 pending. CH reports personal fees from Roche; Novartis; Lilly; Amgen; AstraZeneca; and Pfizer outside the submitted work. BWH reports being an employee of and owning stock in AstraZeneca. JH reports grants from Celgene; Novartis; Hexal; and personal fees from Lilly; Novartis; Roche; Pfizer; AstraZeneca; MSD; Celgene; Eisai; AbbVie; Hexal; and Daichi outside the submitted work. JB reports personal fees from Amgen; AstraZeneca; Genomic Health; MSD; Myriad; Novartis; Pfizer; Roche; and SonoScape outside the submitted work. FM reports personal fees from Roche; AstraZeneca; Pfizer; Tesaro; Novartis; Amgen; PharmaMar; Genomic Health; CureVac; Eisai; Clovis; and Celgene outside the submitted work. WDS reports personal fees from AstraZeneca outside the submitted work. SW reports that he is an employee and shareholder of AstraZeneca. MvM reports personal fees from Amgen; AstraZeneca; Genomic Health; Novartis; and Lilly outside the submitted work. VM reports grants, personal fees, and other from Roche, personal fees and other from Novartis; Pfizer; and Nektar, and personal fees from Amgen; Astra Zeneca; Daiichi-Sankyo; Eisai; Teva; Tesaro; Hexal; and Novartis outside the submitted work. PAF reports grants from Novartis and BioNtech and personal fees from Novartis; Roche; Pfizer; Celgene; Daiichi-Sankyo; Teva; AstraZeneca; Merck Sharp & Dohme; Myelo Therapeutics; MacroGenics; Eisai; Puma; Cepheid; and Lilly during the conduct of the study. CJ reports personal fees from Roche and Celgene outside the submitted work. MU reports personal fees and non-financial support from Odonate and Puma Biotechnology and personal fees and non-financial support to his institution from Lilly; MSD; Mundipharma; Myriad; Pfizer; Roche; Sanovi; Teva; Novartis; Pierre Fabre; and Clovis outside the submitted work. AS reports grants from Celgene; Roche; AbbVie; and Molecular Partner and personal fees from Roche; AstraZeneca; Celgene; Pfizer; Novartis; MSD; Tesaro; and Lilly outside the submitted work. All remaining authors have declared no conflicts of interest., (Copyright © 2020 European Society for Medical Oncology. Published by Elsevier Ltd. All rights reserved.)