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KMID : 1134120170200030246
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Journal of Breast Cancer
2017 Volume.20 No. 3 p.246 ~ p.253
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Copy Number Profiling of MammaPrint™ Genes Reveals Association with the Prognosis of Breast Cancer Patients
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Fatima Areej
Tariq Fomaz
Malik Muhammad Faraz Arshad
Haq Farhan
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Abstract
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Purpose: The MammaPrint™ 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 MammaPrint™ 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 MammaPrint™ 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 MammaPrint™ 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 MammaPrint™ 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.
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KEYWORD
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Biomarkers, Breast neoplasms, DNA copy number variations, Prognosis
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