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Molecular and epigenetic profiles of BRCA1-like hormone-receptor-positive breast tumors identified with development and application of a copy-number-based classifier.
Chen, Youdinghuan; Wang, Yue; Salas, Lucas A; Miller, Todd W; Mark, Kenneth; Marotti, Jonathan D; Kettenbach, Arminja N; Cheng, Chao; Christensen, Brock C.
Afiliación
  • Chen Y; Department of Epidemiology, Lebanon, USA.
  • Wang Y; Department of Molecular and Systems Biology, Lebanon, USA.
  • Salas LA; Department of Molecular and Systems Biology, Lebanon, USA.
  • Miller TW; Department of Epidemiology, Lebanon, USA.
  • Mark K; Department of Molecular and Systems Biology, Lebanon, USA.
  • Marotti JD; Department of Molecular and Systems Biology, Lebanon, USA.
  • Kettenbach AN; Department of Molecular and Systems Biology, Lebanon, USA.
  • Cheng C; Department of Pathology and Laboratory Medicine, Lebanon, USA.
  • Christensen BC; Department of Molecular and Systems Biology, Lebanon, USA.
Breast Cancer Res ; 21(1): 14, 2019 01 25.
Article en En | MEDLINE | ID: mdl-30683142
ABSTRACT

BACKGROUND:

BRCA1-mutated cancers exhibit deficient homologous recombination (HR) DNA repair, resulting in extensive copy number alterations and genome instability. HR deficiency can also arise in tumors without a BRCA1 mutation. Compared with other breast tumors, HR-deficient, BRCA1-like tumors exhibit worse prognosis but selective chemotherapeutic sensitivity. Presently, patients with triple negative breast cancer (TNBC) who do not respond to hormone endocrine-targeting therapy are given cytotoxic chemotherapy. However, more recent evidence showed a similar genomic profile between BRCA1-deficient TNBCs and hormone-receptor-positive tumors. Characterization of the somatic alterations of BRCA1-like hormone-receptor-positive breast tumors as a group, which is currently lacking, can potentially help develop biomarkers for identifying additional patients who might respond to chemotherapy.

METHODS:

We retrained and validated a copy-number-based support vector machine (SVM) classifier to identify HR-deficient, BRCA1-like breast tumors. We applied this classifier to The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast tumors. We assessed mutational profiles and proliferative capacity by covariate-adjusted linear models and identified differentially methylated regions using DMRcate in BRCA1-like hormone-receptor-positive tumors.

RESULTS:

Of the breast tumors in TCGA and METABRIC, 22% (651/2925) were BRCA1-like. Stratifying on hormone-receptor status, 13% (302/2405) receptor-positive and 69% (288/417) triple-negative tumors were BRCA1-like. Among the hormone-receptor-positive subgroup, BRCA1-like tumors showed significantly increased mutational burden and proliferative capacity (both P < 0.05). Genome-scale DNA methylation analysis of BRCA1-like tumors identified 202 differentially methylated gene regions, including hypermethylated BRCA1. Individually significant CpGs were enriched for enhancer regions (P < 0.05). The hypermethylated gene sets were enriched for DNA and chromatin conformation (all Bonferroni P < 0.05).

CONCLUSIONS:

To provide insights into alternative classification and potential therapeutic targeting strategies of BRCA1-like hormone-receptor-positive tumors we developed and applied a novel copy number classifier to identify BRCA1-like hormone-receptor-positive tumors and their characteristic somatic alteration profiles.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Proteína BRCA1 / Variaciones en el Número de Copia de ADN / Epigenómica / Máquina de Vectores de Soporte Tipo de estudio: Prognostic_studies Límite: Adult / Aged / Female / Humans / Middle aged Idioma: En Revista: Breast Cancer Res Asunto de la revista: NEOPLASIAS Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Proteína BRCA1 / Variaciones en el Número de Copia de ADN / Epigenómica / Máquina de Vectores de Soporte Tipo de estudio: Prognostic_studies Límite: Adult / Aged / Female / Humans / Middle aged Idioma: En Revista: Breast Cancer Res Asunto de la revista: NEOPLASIAS Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos