Partial least squares regression and Fourier transform infrared (FTIR) microspectroscopy for prediction of resistance in hepatocellular carcinoma HepG2 cells

Publication date: Available online 3 January 2017
Source:Experimental Cell Research
Author(s): Cholpajsorn Junhom, Natthida Weerapreeyakul, Waraporn Tanthanuch, Kanjana Thumanu
We evaluated the feasibility of FTIR microspectroscopy combined with partial least squares regression (PLS-R) for determination of resistance in HepG2 cells. Cell viability testing was performed using neutral red assay for the concentration of cisplatin resulting in 50% antiproliferation (IC50). The resistance index (RI) is the ratio of the IC50 in resistant HepG2 cells vs. parental HepG2 cells. Principal component and unsupervised hierarchical cluster analyses were applied and a differentiation of samples of cells (parental, 1.8RI, 2.3RI, 3.0RI, and 3.5RI) was demonstrated (3000-2800cm⁻¹ in the lipid and 1700-1500cm⁻¹ in the protein regions. The FTIR spectra were preprocessed with several treatments to test the algorithm. PLS-R models were built using the 1170 spectra of the HepG2 cells. Cross-validation was used to evaluate prediction of the RI value using this model. PLS-R models—preprocessed with the second derivative FTIR spectra—yielded the best model (R² = 0.99, RMSEE = 0.095 and RPD = 7.98). Most RI values were predicted with high accuracy (91–100%) such that the linear correlation between the actual and predicted RI values was nearly perfect (slope ~1). FTIR microspectroscopy combined with chemometric analysis using PLS-R offers quick, accurate, and reliable quantitative analysis of HepG2 cell resistance.

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