Molecular Insights into the Classification of Luminal Breast Cancers: The Genomic Heterogeneity of Progesterone-Negative Tumors.


Journal

International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791

Informations de publication

Date de publication:
25 Jan 2019
Historique:
received: 20 12 2018
revised: 22 01 2019
accepted: 23 01 2019
entrez: 30 1 2019
pubmed: 30 1 2019
medline: 5 6 2019
Statut: epublish

Résumé

Estrogen receptor (ER)-positive progesterone receptor (PR)-negative breast cancers are infrequent but clinically challenging. Despite the volume of genomic data available on these tumors, their biology remains poorly understood. Here, we aimed to identify clinically relevant subclasses of ER+/PR- breast cancers based on their mutational landscape. The Cancer Genomics Data Server was interrogated for mutational and clinical data of all ER+ breast cancers with information on PR status from The Cancer Genome Atlas (TCGA), Memorial Sloan Kettering (MSK), and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) projects. Clustering analysis was performed using gplots, ggplot2, and ComplexHeatmap packages. Comparisons between groups were performed using the Student's t-test and the test of Equal or Given Proportions. Survival curves were built according to the Kaplan⁻Meier method; differences in survival were assessed with the log-rank test. A total of 3570 ER+ breast cancers (PR- n = 959, 27%; PR+ n = 2611, 73%) were analyzed. Mutations in well-known cancer genes such as TP53, GATA3, CDH1, HER2, CDH1, and BRAF were private to or enriched for in PR- tumors. Mutual exclusivity analysis revealed the presence of four molecular clusters with significantly different prognosis on the basis of PIK3CA and TP53 status. ER+/PR- breast cancers are genetically heterogeneous and encompass a variety of distinct entities in terms of prognostic and predictive information.

Identifiants

pubmed: 30691046
pii: ijms20030510
doi: 10.3390/ijms20030510
pmc: PMC6386970
pii:
doi:

Substances chimiques

Antigens, CD 0
CDH1 protein, human 0
Cadherins 0
GATA3 Transcription Factor 0
GATA3 protein, human 0
Receptors, Progesterone 0
TP53 protein, human 0
Tumor Suppressor Protein p53 0
Class I Phosphatidylinositol 3-Kinases EC 2.7.1.137
PIK3CA protein, human EC 2.7.1.137
ERBB2 protein, human EC 2.7.10.1
Receptor, ErbB-2 EC 2.7.10.1
BRAF protein, human EC 2.7.11.1
Proto-Oncogene Proteins B-raf EC 2.7.11.1

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Gianluca Lopez (G)

Division of Pathology, Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, 20122 Milan, Italy. gianluca.lopez@unimi.it.
School of Pathology, University of Milan, 20122, Milan, Italy. gianluca.lopez@unimi.it.

Jole Costanza (J)

Research Laboratory Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122, Milan, Italy. jole.costanza@policlinico.mi.it.

Matteo Colleoni (M)

Division of Pathology, Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, 20122 Milan, Italy. matteo.colleoni1@studenti.unimi.it.

Laura Fontana (L)

Medical Genetics, Department of Pathophysiology and Transplantation, University of Milan, 20122, Milan, Italy. laura.fontana@unimi.it.

Stefano Ferrero (S)

Division of Pathology, Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, 20122 Milan, Italy. stefano.ferrero@unimi.it.
Pathology, Department of Biomedical, Surgical, and Dental Sciences, University of Milan, 20122, Milan, Italy. stefano.ferrero@unimi.it.

Monica Miozzo (M)

Research Laboratory Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122, Milan, Italy. monica.miozzo@unimi.it.
Medical Genetics, Department of Pathophysiology and Transplantation, University of Milan, 20122, Milan, Italy. monica.miozzo@unimi.it.

Nicola Fusco (N)

Division of Pathology, Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, 20122 Milan, Italy. nicola.fusco@unimi.it.
Pathology, Department of Biomedical, Surgical, and Dental Sciences, University of Milan, 20122, Milan, Italy. nicola.fusco@unimi.it.

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Classifications MeSH