Sequencing of breast cancer stem cell populations indicates a dynamic conversion between differentiation states in vivo

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The dyslexia candidate gene DYX1C1 is a potential marker of poor survival in breast cancer

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Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers

Sequencing-based breast cancer diagnostics have the potential to replace routine biomarkers and provide molecular characterization that enable personalized precision medicine. Here we investigate the concordance between sequencing-based and routine diagnostic biomarkers and to what extent tumor sequencing contributes clinically actionable information. We applied DNA- and RNA-sequencing to characterize tumors from 307 breast cancer patients with replication in up to 739 patients. We developed models to predict status of routine biomarkers (ER, HER2,Ki-67, histological grade) from sequencing data. Non-routine biomarkers, including mutations in BRCA1, BRCA2 and ERBB2(HER2), and additional clinically actionable somatic alterations were also investigated. Concordance with routine diagnostic biomarkers was high for ER status (AUC = 0.95;AUC(replication) = 0.97) and HER2 status (AUC = 0.97;AUC(replication) = 0.92). The transcriptomic grade model enabled classification of histological grade 1 and histological grade 3 tumors with high accuracy (AUC = 0.98;AUC(replication) = 0.94). Clinically actionable mutations in BRCA1, BRCA2 and ERBB2(HER2) were detected in 5.5% of patients, while 53% had genomic alterations matching ongoing or concluded breast cancer studies. Sequencing-based molecular profiling can be applied as an alternative to histopathology to determine ER and HER2 status, in addition to providing improved tumor grading and clinically actionable mutations and molecular subtypes. Our results suggest that sequencing-based breast cancer diagnostics in a near future can replace routine biomarkersNonePublishe

A genome-wide association scan on estrogen receptor-negative breast cancer.

INTRODUCTION: Breast cancer is a heterogeneous disease and may be characterized on the basis of whether estrogen receptors (ER) are expressed in the tumour cells. ER status of breast cancer is important clinically, and is used both as a prognostic indicator and treatment predictor. In this study, we focused on identifying genetic markers associated with ER-negative breast cancer risk. METHODS: We conducted a genome-wide association analysis of 285,984 single nucleotide polymorphisms (SNPs) genotyped in 617 ER-negative breast cancer cases and 4,583 controls. We also conducted a genome-wide pathway analysis on the discovery dataset using permutation-based tests on pre-defined pathways. The extent of shared polygenic variation between ER-negative and ER-positive breast cancers was assessed by relating risk scores, derived using ER-positive breast cancer samples, to disease state in independent, ER-negative breast cancer cases. RESULTS: Association with ER-negative breast cancer was not validated for any of the five most strongly associated SNPs followed up in independent studies (1,011 ER-negative breast cancer cases, 7,604 controls). However, an excess of small P-values for SNPs with known regulatory functions in cancer-related pathways was found (global P = 0.052). We found no evidence to suggest that ER-negative breast cancer shares a polygenic basis to disease with ER-positive breast cancer. CONCLUSIONS: ER-negative breast cancer is a distinct breast cancer subtype that merits independent analyses. Given the clinical importance of this phenotype and the likelihood that genetic effect sizes are small, greater sample sizes and further studies are required to understand the etiology of ER-negative breast cancers.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

A genome-wide association scan on estrogen receptor-negative breast cancer

Introduction: Breast cancer is a heterogeneous disease and may be characterized on the basis of whether estrogen receptors (ER) are expressed in the tumour cells. ER status of breast cancer is important clinically, and is used both as a prognostic indicator and treatment predictor. In this study, we focused on identifying genetic markers associated with ER-negative breast cancer risk.Methods: We conducted a genome-wide association analysis of 285,984 single nucleotide polymorphisms (SNPs) genotyped in 617 ER-negative breast cancer cases and 4,583 controls. We also conducted a genome-wide pathway analysis on the discovery dataset using permutation-based tests on pre-defined pathways. The extent of shared polygenic variation between ER-negative and ER-positive breast cancers was assessed by relating risk scores, derived using ER-positive breast cancer samples, to disease state in independent, ER-negative breast cancer cases.Results: Association with ER-negative breast cancer was not validated for any of the five most strongly associated SNPs followed up in independent studies (1,011 ER-negative breast cancer cases, 7,604 controls). However, an excess of small P-values for SNPs with known regulatory functions in cancer-related pathways was found (global P = 0.052). We found no evidence to suggest that ER-negative breast cancer share

Estrogen Receptor beta as a Therapeutic Target in Breast Cancer Stem Cells

Background: Breast cancer cells with tumor-initiating capabilities (BSCs) are considered to maintain tumor growth and govern metastasis. Hence, targeting BSCs will be crucial to achieve successful treatment of breast cancer. Methods: We characterized mammospheres derived from more than 40 cancer patients and two breast cancer cell lines for the expression of estrogen receptors (ERs) and stem cell markers. Mammosphere formation and proliferation assays were performed on cells from 19 cancer patients and five healthy individuals after incubation with ER-subtype selective ligands. Transcriptional analysis was performed to identify pathways activated in ER beta-stimulated mammospheres and verified using in vitro experiments. Xenograft models (n = 4 or 5 per group) were used to study the role of ERs during tumorigenesis. Results: We identified an absence of ERa but upregulation of ER beta in BSCs associated with phenotypic stem cell markers and responsible for the proliferative role of estrogens. Knockdown of ER beta caused a reduction of mammosphere formation in cell lines and in patient-derived cancer cells (40.7%, 26.8%, and 39.1%, respectively). Gene set enrichment analysis identified glycolysis-related pathways (false discovery rate amp;lt; 0.001) upregulated in ER beta-activated mammospheres. We observed that tamoxifen or fulvestrant alone was insufficient to block proliferation of patient-derived BSCs while this could be accomplished by a selective inhibitor of ER beta (PHTPP; 53.7% in luminal and 45.5% in triple-negative breast cancers). Furthermore, PHTPP reduced tumor initiation in two patient-derived xenografts (75.9% and 59.1% reduction in tumor volume, respectively) and potentiated tamoxifen-mediated inhibition of tumor growth in MCF7 xenografts. Conclusion: We identify ER beta as a mediator of estrogen action in BSCs and a novel target for endocrine therapy.Funding Agencies|Swedish Society of Medicine; Swedish Society for Medical Research (SSMF); Magnus Bergvalls Stiftelse; Karolinska Institutes Theme Center in Breast Cancer (BRECT); Linnecenter for Prevention of Breast and Prostate cancer (CRisP); Swedish Cancer Society; Stockholm Cancer Society; King Gustav V Jubilee Fund; Karolinska Institutet; Stockholm County Council Research Strategy Committee; Swedish Breast Cancer Association; Science for Life-Astra Zeneca; Marie Curie Actions via the VINNOVA program Mobility for Growth [291795]</p