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Distribution of breast cancer subtypes among Jordanian women and correlation with histopathological grade: molecular subclassification study
OBJECTIVE: To evaluate the hormone receptor status and human epidermal growth factor receptor 2 (HER2)/neu gene expression among Jordanian women with breast cancer. To classify our patients into molecular subtypes and to correlate the results with age of the patients and tumour grade. DESIGN: Evalua...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3831862/ https://www.ncbi.nlm.nih.gov/pubmed/24319578 http://dx.doi.org/10.1177/2042533313490516 |
Sumario: | OBJECTIVE: To evaluate the hormone receptor status and human epidermal growth factor receptor 2 (HER2)/neu gene expression among Jordanian women with breast cancer. To classify our patients into molecular subtypes and to correlate the results with age of the patients and tumour grade. DESIGN: Evaluation of estrogen receptor (ER), PR and HER2/neu was done by standard immunohistochemical technique and subclassification into molecular subtypes. SETTING: Jordan University Hospital, Amman, Jordan. PARTICIPANTS: One hundred and ninety-three cases of breast cancer diagnosed at Jordan University Hospital. MAIN OUTCOME MEASURES: Molecular subtypes of breast cancer, age and tumour grade. RESULTS: All the cases were divided into two groups: the young age group less or equal 50 years of age and the older age group more than 50 years of age. The cases were subclassified into luminal A, luminal B, basal cell like (BCL) and Her2/neu+. In older age group, the most common subtype was luminal A (72%). In this age group, most of the cases (48%) were of grade II. In younger age group, 47% of the cases were of luminal A subclass. In this age group, 42% were of grade I. CONCLUSIONS: Molecular subtyping of breast cancer is an essential predicting factor of tumour response to hormonal therapy. This fact puts increased stress on the urgent need for the development of reliable and reproducible classification systems. |
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