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Background: Therapeutic regimens designed to augment the immunological response of a patient with breast cancer (BC) to tumor tissue are critically informed by tumor mutational burden and the antigenicity of expressed neoepitopes. Herein we describe a neoepitope and cognate neoepitope-reactive T-cell identification and validation program that supports the development of next-generation immunotherapies., Methods: Using GPS Cancer, NantOmics research, and The Cancer Genome Atlas databases, we developed a novel bioinformatic-based approach which assesses mutational load, neoepitope expression, human leukocyte antigen (HLA)-binding prediction, and in vitro confirmation of T-cell recognition to preferentially identify targetable neoepitopes. This program was validated by application to a BC cell line and confirmed using tumor biopsies from two patients with BC enrolled in the Tumor-Infiltrating Lymphocytes and Genomics (TILGen) study., Results: The antigenicity and HLA-A2 restriction of the BC cell line predicted neoepitopes were determined by reactivity of T cells from HLA-A2-expressing healthy donors. For the TILGen subjects, tumor-infiltrating lymphocytes (TILs) recognized the predicted neoepitopes both as peptides and on retroviral expression in HLA-matched Epstein-Barr virus-lymphoblastoid cell line and BC cell line MCF-7 cells; PCR clonotyping revealed the presence of T cells in the periphery with T-cell receptors for the predicted neoepitopes. These high-avidity immune responses were polyclonal, mutation-specific and restricted to either HLA class I or II. Interestingly, we observed the persistence and expansion of polyclonal T-cell responses following neoadjuvant chemotherapy., Conclusions: We demonstrate our neoepitope prediction program allows for the successful identification of neoepitopes targeted by TILs in patients with BC, providing a means to identify tumor-specific immunogenic targets for individualized treatment, including vaccines or adoptively transferred cellular therapies., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

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: Previous studies have identified and validated a risk-associated Active transcriptome phenotype commonly expressed in the cancer-adjacent and histologically normal epithelium, stroma, and adipose containing peritumor microenvironment of clinically established invasive breast cancers, conferring a 2.5- to 3-fold later risk of dying from recurrent breast cancer. Expression of this Active transcriptome phenotype has not yet been evaluated in normal breast tissue samples unassociated with any benign or malignant lesions; however, it has been associated with increased peritumor adipocyte composition., Methods: Detailed histologic and transcriptomic (RNAseq) analyses were performed on normal breast biopsy samples from 151 healthy, parous, non-obese (mean BMI = 29.60 ± 7.92) women, ages 27-66 who donated core breast biopsy samples to the Komen Tissue Bank, and whose average breast cancer risk estimate (Gail score) at the time of biopsy (1.27 ± 1.34) would not qualify them for endocrine prevention therapy., Results: Full genome RNA sequencing (RNAseq) identified 52% (78/151) of these normal breast samples as expressing the Active breast phenotype. While Active signature genes were found to be most variably expressed in mammary adipocytes, donors with the Active phenotype had no difference in BMI but significantly higher Gail scores (1.46 vs. 1.18; p = 0.007). Active breast samples possessed 1.6-fold more (~ 80%) adipocyte nuclei, larger cross-sectional adipocyte areas (p < 0.01), and 0.5-fold fewer stromal and epithelial cell nuclei (p < 1e-6). Infrequent low-level expression of cancer gene hotspot mutations was detected but not enriched in the Active breast samples. Active samples were enriched in gene sets associated with adipogenesis and fat metabolism (FDR q ≤ 10%), higher signature scores for cAMP-dependent lipolysis known to drive breast cancer progression, white adipose tissue browning (Wilcoxon p < 0.01), and genes associated with adipocyte activation (leptin, adiponectin) and remodeling (CAV1, BNIP3), adipokine growth factors (IGF-1, FGF2), and pro-inflammatory fat signaling (IKBKG, CCL13)., Conclusions: The risk-associated Active transcriptome phenotype first identified in cancer-adjacent breast tissues also occurs commonly in healthy women without breast disease who do not qualify for breast cancer chemoprevention, and independently of breast expressed cancer-associated mutations. The risk-associated Active phenotype appears driven by a pro-tumorigenic adipocyte microenvironment that can predate breast cancer development.