Document Type : Research article
Department of Occupational Hygiene, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
cPharmaceutical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran Department of Toxicology and Pharmacology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Toxicity bioassays are important tools to determine biological effects of chemical agents on species. The questions remained on, what effects have been imposed on each of the different molecular site of cells by chemical exposure and how to find a pattern for chemical toxicity.
To address the questions, HepG2 cell lines were exposed to the different concentrations of cisplatin for 24 hours to result cell mortality in the range of one to one hundred percent. Fourier Transform Infrared spectroscopy (FTIR) has been used in this study to analyze the chemical alterations on HepG2 cell line by cisplatin. Partial least square regression (PLS) analysis was then applied to the FTIR spectrum results to search for a biomarker peak and present the desire cellular effects of cisplatin. The comparison of cellular FTIR spectra after exposure to different concentrations of cisplatin confirmed the binding of cisplatin to DNA through direct interaction of platinum to guanine and thymine bases of DNA. Biochemical Index Spectra (BIS) were defined based on the differences between of normal and cisplatin exposed cells. Information from the BIS was subjected to PLS analysis to trigger any particular relationship between the toxicity spectral response and cisplatin concentration. This approach was capable of predicting the concentration of cisplatin for any particular effects observed in the cellular FTIR spectrum (R2=0.968±0.037).
Our work supports the promises that, FTIR can demonstrate the trace of toxicity before the cells dies. Finally, PLS of FTIR data directly predicts the effective concentration of chemicals in particular cellular components.