The long-term prognostic and predictive capacity of cyclin D1 gene amplification in 2305 breast tumours.


Journal

Breast cancer research : BCR
ISSN: 1465-542X
Titre abrégé: Breast Cancer Res
Pays: England
ID NLM: 100927353

Informations de publication

Date de publication:
28 02 2019
Historique:
received: 05 12 2018
accepted: 14 02 2019
entrez: 2 3 2019
pubmed: 2 3 2019
medline: 23 7 2019
Statut: epublish

Résumé

Use of cyclin D1 (CCND1) gene amplification as a breast cancer biomarker has been hampered by conflicting assessments of the relationship between cyclin D1 protein levels and patient survival. Here, we aimed to clarify its prognostic and treatment predictive potential through comprehensive long-term survival analyses. CCND1 amplification was assessed using SNP arrays from two cohorts of 1965 and 340 patients with matching gene expression array and clinical follow-up data of over 15 years. Kaplan-Meier and multivariable Cox regression analyses were used to determine survival differences between CCND1 amplified vs. non-amplified tumours in clinically relevant patient sets, within PAM50 subtypes and within treatment-specific subgroups. Boxplots and differential gene expression analyses were performed to assess differences between amplified vs. non-amplified tumours within PAM50 subtypes. When combining both cohorts, worse survival was found for patients with CCND1-amplified tumours in luminal A (HR = 1.68; 95% CI, 1.15-2.46), luminal B (1.37; 1.01-1.86) and ER+/LN-/HER2- (1.66; 1.14-2.41) subgroups. In gene expression analysis, CCND1-amplified luminal A tumours showed increased proliferation (P < 0.001) and decreased progesterone (P = 0.002) levels along with a large overlap in differentially expressed genes when comparing luminal A and B-amplified vs. non-amplified tumours. Our results indicate that CCND1 amplification is associated with worse 15-year survival in ER+/LN-/HER2-, luminal A and luminal B patients. Moreover, luminal A CCND1-amplified tumours display gene expression changes consistent with a more aggressive phenotype. These novel findings highlight the potential of CCND1 to identify patients that could benefit from long-term treatment strategies.

Sections du résumé

BACKGROUND
Use of cyclin D1 (CCND1) gene amplification as a breast cancer biomarker has been hampered by conflicting assessments of the relationship between cyclin D1 protein levels and patient survival. Here, we aimed to clarify its prognostic and treatment predictive potential through comprehensive long-term survival analyses.
METHODS
CCND1 amplification was assessed using SNP arrays from two cohorts of 1965 and 340 patients with matching gene expression array and clinical follow-up data of over 15 years. Kaplan-Meier and multivariable Cox regression analyses were used to determine survival differences between CCND1 amplified vs. non-amplified tumours in clinically relevant patient sets, within PAM50 subtypes and within treatment-specific subgroups. Boxplots and differential gene expression analyses were performed to assess differences between amplified vs. non-amplified tumours within PAM50 subtypes.
RESULTS
When combining both cohorts, worse survival was found for patients with CCND1-amplified tumours in luminal A (HR = 1.68; 95% CI, 1.15-2.46), luminal B (1.37; 1.01-1.86) and ER+/LN-/HER2- (1.66; 1.14-2.41) subgroups. In gene expression analysis, CCND1-amplified luminal A tumours showed increased proliferation (P < 0.001) and decreased progesterone (P = 0.002) levels along with a large overlap in differentially expressed genes when comparing luminal A and B-amplified vs. non-amplified tumours.
CONCLUSIONS
Our results indicate that CCND1 amplification is associated with worse 15-year survival in ER+/LN-/HER2-, luminal A and luminal B patients. Moreover, luminal A CCND1-amplified tumours display gene expression changes consistent with a more aggressive phenotype. These novel findings highlight the potential of CCND1 to identify patients that could benefit from long-term treatment strategies.

Identifiants

pubmed: 30819233
doi: 10.1186/s13058-019-1121-4
pii: 10.1186/s13058-019-1121-4
pmc: PMC6394106
doi:

Substances chimiques

Biomarkers, Tumor 0
CCND1 protein, human 0
Receptors, Estrogen 0
Cyclin D1 136601-57-5
ERBB2 protein, human EC 2.7.10.1
Receptor, ErbB-2 EC 2.7.10.1

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

34

Subventions

Organisme : NIEHS NIH HHS
ID : P30 ES010126
Pays : United States
Organisme : NCI Breast SPORE program
ID : R01- CA195754-01
Pays : International
Organisme : NCI NIH HHS
ID : P50 CA058223
Pays : United States
Organisme : Cancer Research UK
Pays : United Kingdom
Organisme : NCI NIH HHS
ID : R01 CA195754
Pays : United States
Organisme : NCI Breast SPORE program
ID : P50-CA58223-09A1
Pays : International

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Auteurs

Arian Lundberg (A)

Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Stockholm, Sweden.

Linda S Lindström (LS)

Department of Biosciences and Nutrition, Karolinska Institutet and University Hospital, Stockholm, Sweden.

Jingmei Li (J)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Human Genetics, Genome Institute of Singapore, Singapore, Singapore.

J Chuck Harrell (JC)

Department of Pathology, Virginia Commonwealth University, Richmond, VA, USA.

Eva Darai-Ramqvist (E)

Department of Pathology and Cytology, Karolinska Institutet and University Hospital, Stockholm, Sweden.

Emmanouil G Sifakis (EG)

Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Stockholm, Sweden.

Theodoros Foukakis (T)

Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Stockholm, Sweden.

Charles M Perou (CM)

Department of Genetics, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Kamila Czene (K)

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Jonas Bergh (J)

Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Stockholm, Sweden.
Department of Public Health, Oxford University, Oxford, UK.

Nicholas P Tobin (NP)

Department of Oncology and Pathology, Karolinska Institutet and University Hospital, Stockholm, Sweden. nick.tobin@ki.se.

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Classifications MeSH