Discrimination and quantification of methotrexate in the presence of its metabolites in patient serum using SERS mapping, assisted by multivariate spectral data analysis

Abstract

Therapeutic drug monitoring (TDM) of methotrexate (MTX), an anticancer drug, is critical since MTX therapy can lead to severe adverse effects if not monitored to ensure clearance. Discriminating and quantifying MTX among its metabolites is challenging, time consuming, and not universally available. Therefore, we propose a surface-enhanced Raman scattering (SERS) based method as a rapid and easy-to-use alternative to complex standard methods. We implemented a solid phase extraction (SPE) process in a syringe filter holder (μ-SPE-SFH), suitable for the extraction of MTX and compatible with nanopillar assisted separation (NPAS) and SERS-based detection. All of the parameters related to the extraction, desorption, and NPAS procedure were investigated and optimized. The SERS spectra from maps were analyzed with partial least squares as regression (PLSR) and as a discrimination analysis (PLS-DA) to enable, for the first time with SERS, the identification and quantification of MTX in the presence of its metabolites (7-hydroxy-methotrexate (7-OH MTX) and 2,4-diamino-N(10)-methylpteroic acid (DAMPA)). PLSR facilitated MTX quantification in patient samples in the presence of drugs that could be co-administered during MTX therapy. We found the detection limit to be 0.15 μM while the limit of quantification was 0.55 μM. In addition, for the PLSR, the accuracy, precision, analytical sensitivity, and inverse of analytical sensitivity were 0.66 μM, 0.5 μM, 10.5 μM−1, and 0.1 μM respectively. Furthermore, when quantifying MTX from patient samples, we found a good agreement between calculated MTX concentration with the developed method and reference assay, showing the potential of the sensor in clinical application.