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Zinc is known to play an important role in many cellular processes, and the levels of zinc are controlled by specific transporters from the ZIP (SLC39A) influx transporter group and the ZnT (SLC30A) efflux transporter group. The distribution of zinc was measured in 59 samples of invasive ductal carcinoma of breast using synchrotron radiation micro probe x-ray fluorescence facilities. The samples were formalin fixed paraffin embedded tissue micro arrays (TMAs) enabling a high throughput of samples and allowing us to correlate the distribution of trace metals with tumour cell distribution and, for the first time, important biological variables. The samples were divided into two classes, 34 oestrogen receptor positive (ER+ve) and 25 oestrogen receptor negative (ER-ve) based on quantitative immunohistochemistry assessment. The overall levels of zinc (i.e. in tumour and surrounding tissue) in the ER+ve samples were on average 60% higher than those in the ER-ve samples. The zinc levels were higher in the ER+ve tumour areas compared to the ER-ve tumour areas with the mean levels in the ER+ve samples being approximately 80% higher than the mean ER-ve levels. However, the non-tumour tissue regions of the samples contained on average the same levels of zinc in both types of breast cancers. The relative levels of zinc in tumour areas of the tissue were compared with levels in areas of non-tumour surrounding tissue. There was a significant increase in zinc in the tumour regions of the ER+ve samples compared to the surrounding regions (P < 0.001) and a non-significant increase in the ER-ve samples. When comparing the increase in zinc in the tumour regions expressed as a percentage of the surrounding non-tumour tissue zinc level in the same sample, a significant difference between the ER+ve and ER-ve samples was found (P < 0.01).

Original publication

DOI

10.1088/0031-9155/54/13/016

Type

Journal article

Journal

Phys Med Biol

Publication Date

07/07/2009

Volume

54

Pages

4213 - 4223

Keywords

Biomarkers, Tumor, Carcinoma, Ductal, Breast, Computer Simulation, Female, Humans, Models, Biological, Models, Statistical, Receptors, Estrogen, Statistics as Topic, Zinc