J Breast Cancer.  2017 Sep;20(3):246-253. 10.4048/jbc.2017.20.3.246.

Copy Number Profiling of MammaPrintâ„¢ Genes Reveals Association with the Prognosis of Breast Cancer Patients

• Fatima A
• Tariq F
• Malik MF
• Qasim M
• Haq F

• KMID: 2438991
• DOI: http://doi.org/10.4048/jbc.2017.20.3.246

Abstract

PURPOSE
The MammaPrintâ„¢ gene signature, currently used in clinical practice, provides prognostic information regarding the recurrence and potential metastasis in breast cancer patients. However, the prognostic information of the 70 genes included can only be estimated at the RNA expression level. In this study, we investigated whether copy number information of MammaPrintâ„¢ genes at the DNA level can be used as a prognostic tool for breast cancer, as copy number variations (CNVs) are major contributors to cancer progression.
METHODS
We performed CNV profiling of MammaPrintâ„¢ genes in 59 breast cancer cell lines and 650 breast cancer patients, using publicly available data in The Cancer Genome Atlas (TCGA) database. Statistical analyses including Fisher exact test, chi-square test, and Kaplan-Meier survival analyses were performed.
RESULTS
All MammaPrintâ„¢ genes showed recurrent CNVs, particularly in TCGA cohort. CNVs of 32 and 36 genes showed significant associations with progesterone receptor and estrogen rector, respectively. No genes showed a significant association with human epidermal growth factor receptor 2 status and lymph node status. In addition, only six genes were associated with tumor stages. RFC4, HRASLS, NMU, GPR126, SCUBE2, C20orf46, and EBF4 were associated with reduced survival and RASSF7 and ESM1 were associated with reduced disease-free survival.
CONCLUSION
Based on these findings, a concordance of CNV-based genomic rearrangement with expression profiling of these genes and their putative roles in disease tumorigenesis was established. The results suggested that the CNV profiles of the MammaPrintâ„¢ genes can be used to predict the prognosis of breast cancer patients. In addition, this approach may lead to the development of new cancer biomarkers at the DNA level.

Keyword

Biomarkers; Breast neoplasms; DNA copy number variations; Prognosis

MeSH Terms

Biomarkers
Biomarkers, Tumor
Breast Neoplasms*
Breast*
Carcinogenesis
Cell Line
Cohort Studies
Disease-Free Survival
DNA
DNA Copy Number Variations
Estrogens
Genome
Humans
Lymph Nodes
Neoplasm Metastasis
Prognosis*
Receptor, Epidermal Growth Factor
Receptors, Progesterone
Recurrence
RNA
Biomarkers
Biomarkers, Tumor
DNA
Estrogens
RNA
Receptor, Epidermal Growth Factor
Receptors, Progesterone

Figure

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  Figure 1 Copy number profiling of MammaPrint™ genes in 650 breast cancer patients.

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  Figure 2 Overall survival analysis of MammaPrint™ genes. Genetic alterations in C20orf46 (A), EBF4 (B), GPR126 (C), HRASLS (D), NMU (E), RFC4 (F), and SCUBE2 (G) genes showed reduced overall survival in breast cancer patients.

• 

  Figure 3 Disease-free survival analysis of MammaPrint™ genes. Genetic alterations in ESM1 (A) and RASSF7 (B) genes showed poor disease-free survival in breast cancer patients.

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