Characterization and Distribution of the Selected Metals in the Scalp Hair of Cancer Patients in Comparison with Normal Donors |
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Authors: | Qaisara Pasha Salman A. Malik Javed Iqbal Munir H. Shah |
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Affiliation: | (1) Department of Biochemistry, Quaid-i-Azam University, Islamabad, 45320, Pakistan;(2) POF Hospital, Wah Cantt, District Rawalpindi, Pakistan;(3) Department of Chemistry, Quaid-i-Azam University, Islamabad, 45320, Pakistan |
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Abstract: | Eighteen metals were estimated in the scalp hair samples from cancer patients (n = 111) and normal donors (n = 113). Nitric acid–perchloric acid wet digestion procedure was used for the quantification of the selected metals by flame atomic absorption spectrophotometry. In the scalp hair of cancer patients, highest average levels were found for Ca (861 μg/g), followed by Na (672 μg/g), Zn (411 μg/g), Mg (348 μg/g), Fe (154 μg/g), Sr (129 μg/g), and K (116 μg/g), whereas in comparison, the dominant metals in the scalp hair of normal donors were Ca (568 μg/g), Zn (177 μg/g), Mg (154 μg/g), Fe (110 μg/g), and Na (103 μg/g). The concentrations of Ca, Cd, Co, Cr, Fe, K, Mg, Mn, Na, Ni, Pb, Sb, Sr, and Zn were notably higher in the hair of cancer patients as compared with normal donors, which may lead to a number of physiological disorders. Strong positive correlations were found in Mn–Pb (0.83), Cd–Cr (0.82), Cd–Li (0.57), Fe–Pb (0.56), and Fe–Mn (0.55) in the hair of cancer patients whereas Na–Cd, Li–Cr, Li–Co, Co–Cd, Li–Cd, Na–Co, Na–Li, Ca–Mg and Na–Cr exhibited strong relationships (r > 0.50) in the hair of normal donors. Principal Component Analysis (PCA) of the data revealed seven PCs, both for cancer patients and normal donors, but with significantly different loadings. Cluster Analysis (CA) was also used to support the PCA results. The study evidenced significantly different pattern of metal distribution in the hair of cancer patients in comparison with normal donors. The role of trace metals in carcinogenesis was also discussed. |
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Keywords: | Cancer Hair Trace metals Principal component analysis Cluster analysis AAS Pakistan |
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