In this article the data availability statement was incorrectly given. “EGAS0000100682” should have been “EGAS00001006821”. The correct statement as follows. The datasets generated during and/or analysed during the current study are deposited at the European Genome-phenome Archive (EGA) under the accession numbers EGAS00001006821 and EGAD00001009790. The original article has been corrected.

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Background: Studies have shown that blood platelets contain tumour-specific mRNA profiles tumour-educated platelets (TEPs). Here, we aim to train a TEP-based breast cancer detection classifier. Methods: Platelet mRNA was sequenced from 266 women with stage I–IV breast cancer and 212 female controls from 6 hospitals. A particle swarm optimised support vector machine (PSO-SVM) and an elastic net-based classifier (EN) were trained on 71% of the study population. Classifier performance was evaluated in the remainder (29%) of the population, followed by validation in an independent set (37 cases and 36 controls). Potential confounding was assessed in post hoc analyses. Results: Both classifiers reached an area under the curve (AUC) of 0.85 upon internal validation. Reproducibility in the independent validation set was poor with an AUC of 0.55 and 0.54 for the PSO-SVM and EN classifier, respectively. Post hoc analyses indicated that 19% of the variance in gene expression was associated with hospital. Genes related to platelet activity were differentially expressed between hospitals. Conclusions: We could not validate two TEP-based breast cancer classifiers in an independent validation cohort. The TEP protocol is sensitive to within-protocol variation and revision might be necessary before TEPs can be reconsidered for breast cancer detection.

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Purpose: To assess whether contralateral parenchymal enhancement (CPE) on MRI is associated with gene expression pathways in ER+/HER2-breast cancer, and if so, whether such pathways are related to survival. Methods: Preoperative breast MRIs were analyzed of early ER+/HER2-breast cancer patients eligible for breast-conserving surgery included in a prospective observational cohort study (MARGINS). The contralateral parenchyma was segmented and CPE was calculated as the average of the top-10% delayed enhancement. Total tumor RNA sequencing was performed and gene set enrichment analysis was used to reveal gene expression pathways associated with CPE (N = 226) and related to overall survival (OS) and invasive disease-free survival (IDFS) in multivariable survival analysis. The latter was also done for the METABRIC cohort (N = 1355). Results: CPE was most strongly correlated with proteasome pathways (normalized enrichment statistic = 2.04, false discovery rate =.11). Patients with high CPE showed lower tumor proteasome gene expression. Proteasome gene expression had a hazard ratio (HR) of 1.40 (95% CI = 0.89, 2.16; P =.143) for OS in the MARGINS cohort and 1.53 (95% CI = 1.08, 2.14; P =.017) for IDFS, in METABRIC proteasome gene expression had an HR of 1.09 (95% CI = 1.01, 1.18; P =.020) for OS and 1.10 (95% CI = 1.02, 1.18; P =.012) for IDFS. Conclusion: CPE was negatively correlated with tumor proteasome gene expression in early ER+/HER2-breast cancer patients. Low tumor proteasome gene expression was associated with improved survival in the METABRIC data.

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Background: Better understanding of the molecular biology associated with MRI phenotypes may aid in the diagnosis and treatment of breast cancer. Purpose: To discover the associations between MRI phenotypes of breast cancer and their underlying molecular biology derived from gene expression data. Materials and Methods: This is a secondary analysis of the Multimodality Analysis and Radiologic Guidance in Breast-Conserving Therapy, or MARGINS, study. MARGINS included patients eligible for breast-conserving therapy between November 2000 and December 2008 for preoperative breast MRI. Tumor RNA was collected for sequencing from surgical specimen. Twenty-one computer-generated MRI features of tumors were condensed into seven MRI factors related to tumor size, shape, initial enhancement, late enhancement, smoothness of enhancement, sharpness, and sharpness variation. These factors were associated with gene expression levels from RNA sequencing by using gene set enrichment analysis. Statistical significance of these associations was evaluated by using a sample permutation test and the false discovery rate. Results: Gene expression and MRI data were obtained for 295 patients (mean age, 56 years 6 10.3 [standard deviation]). Larger and more irregular tumors showed increased expression of cell cycle and DNA damage checkpoint genes (false discovery rate,0.25; normalized enrichment statistic [NES], 2.15). Enhancement and sharpness of the tumor margin were associated with expression of ribosomal proteins (false discovery rate,0.25; NES, 1.95). Smoothness of enhancement, tumor size, and tumor shape were associated with expression of genes involved in the extracellular matrix (false discovery rate,0.25; NES, 2.25). Conclusion: Breast cancer MRI phenotypes were related to their underlying molecular biology revealed by using RNA sequencing. The association between enhancements and sharpness of the tumor margin with the ribosome suggests that these MRI features may be imaging biomarkers for drugs targeting the ribosome.

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Invasive lobular carcinoma (ILC) is the second most common breast cancer subtype and accounts for 8–14% of all cases. Although the majority of human ILCs are characterized by the functional loss of E-cadherin (encoded by CDH1), inactivation of Cdh1 does not predispose mice to develop mammary tumors, implying that mutations in additional genes are required for ILC formation in mice. To identify these genes, we performed an insertional mutagenesis screen using the Sleeping Beauty transposon system in mice with mammary-specific inactivation of Cdh1. These mice developed multiple independent mammary tumors of which the majority resembled human ILC in terms of morphology and gene expression. Recurrent and mutually exclusive transposon insertions were identified in Myh9, Ppp1r12a, Ppp1r12b and Trp53bp2, whose products have been implicated in the regulation of the actin cytoskeleton. Notably, MYH9, PPP1R12B and TP53BP2 were also frequently aberrated in human ILC, highlighting these genes as drivers of a novel oncogenic pathway underlying ILC development.@en

Introduction
In triple negative breast cancers (TNBC) the initial response to chemotherapy is often favorable, but relapse and chemotherapy resistance frequently occur in advanced disease. Hence there is an urgent need for targeted treatments in this breast cancer subtype. In the current study we deep sequenced DNA of tumors prior to chemotherapy to search for predictors of response or resistance.
Methods
Next generation sequencing (NGS) was performed for 1,977 genes involved in tumorigenesis. DNA from 56 pre-treatment TNBC-biopsies was sequenced, as well as matched normal DNA. Following their tumor biopsy, patients started neoadjuvant chemotherapy with doxorubicin and cyclophosphamide. We studied associations between genetic alterations and three clinical variables: chemotherapy response, relapse-free survival and BRCA proficiency.
Results
The mutations observed were diverse and few recurrent mutations were detected. Most mutations were in TP53, TTN, and PIK3CA (55 %, 14 %, and 9 %, respectively). The mutation rates were similar between responders and non-responders (average mutation rate 9 vs 8 mutations). No recurrent mutations were associated with chemotherapy response or relapse. Interestingly, PIK3CA mutations were exclusively observed in patients proficient for BRCA1. Samples with a relapse had a higher copy number alteration rate, and amplifications of TTK and TP53BP2 were associated with a poor chemotherapy response.
Conclusions
In this homogenous cohort of TNBCs few recurrent mutations were found. However, PIK3CA mutations were associated with BRCA proficiency, which can have clinical consequences in the near future.
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