Quantification of target analytes in various biofluids using a postcolumn infused-internal standard method combined with matrix normalization factors in liquid chromatography-electrospray ionization mass spectrometry

Post column infusion of an internal standard into LC-FT-ICR MS enables semi-quantitative comparison of dissolved organic matter in original samples

Ultrahigh resolution mass spectrometry hyphenated with liquid chromatography (LC) is an emerging tool to explore the isomeric composition of dissolved organic matter (DOM). However, matrix effects limit the potential for semi-quantitative comparison of DOM molecule abundances across samples. We introduce a post-column infused internal standard (PCI-IS) for reversed-phase LC-FT-ICR MS measurements of DOM and systematically evaluate matrix effects, detector linearity and the precision of mass peak intensities. Matrix effects for model compounds spiked into freshwater DOM samples ranging from a headwater stream to a major river were reduced by 5-10% for PCI-IS corrected mass peak intensities as compared to raw (i.e., untransformed) intensities. A linear regression of PCI-IS corrected DOM mass peak intensities across a typical DOM concentration range (2-15 mg dissolved organic carbon L-1) in original, non-extracted freshwater samples demonstrates excellent linearity of the detector response (r2 > 0.9 for 98% of detected molecular formulas across retention times). Importantly, PCI-IS could compensate for 80% of matrix effects across an environmental gradient of DOM composition from groundwater to surface water. This enabled studying the ionization efficiency of DOM isomers and linking the observed differences to the biogeochemical sources. With PCI-IS original, non-extracted DOM samples can be analysed by LC-FT-ICR MS without carbon load adjustment, and mass peak intensities can be reliably used to semi-quantitatively compare isomer abundances between compositionally similar DOM samples.

Using post-column infused internal standard assisted quantitative metabolomics for establishing prediction models for breast cancer detection

RATIONALE

Breast cancer is one of the most common cancers among women and its associated mortality is on the rise. Metabolomics is a potential strategy for breast cancer detection. The post-column infused internal standard (PCI-IS)-assisted liquid chromatography/tandem mass spectrometry (LC/MS/MS) method has been demonstrated as an effective strategy for quantitative metabolomics. In this study, we evaluated the performance of targeted metabolomics with the PCI-IS quantification method to identify women with breast cancer.

METHODS

We used metabolite profiling to identify 17 dysregulated metabolites in breast cancer patients. Two LC/MS/MS methods in combination with the PCI-IS strategy were developed to quantify these metabolites in plasma samples. Detection models were built through the analysis of plasma samples from 176 subjects consisting of healthy volunteers and breast cancer patients.

RESULTS

Three isotope standards were selected as the PCI-ISs for the metabolites. The accuracy was within 82.8-114.16%, except for citric acid and lactic acid at high concentration levels. The repeatability and intermediate precision were all lower than 15% relative standard deviation. We have identified several metabolites that indicate the presence of breast cancer. The area under the receiver operating characteristics (AUROC) curve, sensitivity and specificity of the linear combinations of metabolite concentrations and age with the highest AUROC were 0.940 (0.889-0.992), 88.4% and 94.2% for pre-menopausal woman, respectively, and 0.828 (0.734-0.922), 73.5% and 85.1% for post-menopausal women, respectively.

CONCLUSIONS

The targeted metabolomics with PCI-IS quantification method successfully established prediction models for breast cancer detection. Further study is essential to validate these proposed markers.

Post-column infused internal standard assisted lipidomics profiling strategy and its application on phosphatidylcholine research

Various lipidomics studies have revealed the potential of using phospholipids as disease biomarkers for conditions such as Alzheimer's disease, cancer, and sepsis. Establishing accurate quantification methods for targeted phospholipid analysis is important for making these potential markers more clinically relevant. Although a stable isotope labelled-internal standard method can provide good quantification accuracy for endogenous metabolite quantification, there are limited isotope labelled phosphatidylcholines (PCs) commercially available. For this reason, this study proposed a postcolumn infused-internal standard (PCI-IS) method for the accurate quantification of PCs. To demonstrate the quantification accuracy of the PCI-IS method combined with the matrix normalization factor (MNF), 2 LPCs and 6 PCs have been quantified in the human plasma specimens, and the results showed that the PCI-IS combined with MNF method can provide quantification results as accurate as those of the standard addition method (SAM) but without the need for the labor-intensive SAM procedure. We additionally applied the PCI-IS method for improving the PC profiling accuracy, and the results indicated that the biased estimation of the PC composition caused by the MEs can be resolved by PCI-IS correction. Finally, the method was applied to investigate drug resistance in lung cancer cells. Decreased levels of PCs in drug resistant cells disclose the potential role of PCs in drug resistance. We anticipate that the PCI-IS strategy could help quantitative lipidomics move forward and further contribute to various clinical and biomedical studies.

Zacharis C. Automated Post-Column Sample Manipulation Prior to Detection in Liquid Chromatography: A Review of Pharmaceutical and Bioanalytical Applications

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Automated post-column sample manipulation is undoubtedly one of the most challenging approaches in liquid chromatography for the improvement of method selectivity and sensitivity. With the post-column analyte derivatization being the most-abundant approach approach of this category, other strategies typically comprise post-column infusion of internal standard or other reagents prior to mass spectrometric detection to enhance the ionization efficiency of the analyte or to compensate the ion suppression/enhancement.

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In this review, on-line post column methodologies focused on the quality control of pharmaceuticals and biomedical applications will be presented and discussed. Emphasis will be given on the automation capabilities of such systems.

Mass spectrometry in the pharmacokinetic studies of anticancer natural products

In the history of medicine, nature has represented the main source of medical products. Indeed, the therapeutic use of plants certainly goes back to the Sumerian and Hippocrates and nowadays nature still represents the major source for new drugs discovery. Moreover, in the cancer treatment, drugs are either natural compounds or have been developed from naturally occurring parent compounds firstly isolated from plants and microbes from terrestrial and marine environment. A critical element of an anticancer drug is represented by its severe toxicities and, after administration, the drug concentrations have to remain in an appropriate range to be effective. Anyway, the drug dosage defined during the clinical studies could be inappropriate for an individual patient due to differences in drug absorption, metabolism and excretion. For this reason, personalized medicine, based on therapeutic drug monitoring (TDM), represents one of most important challenges in cancer therapy. Mass spectrometry sensitivity, specificity and fastness lead to elect this technique as the Golden Standard for pharmacokinetics and drug metabolism studies therefore for TDM. This review focuses on the mass spectrometry-based methods developed for pharmacokinetic quantification in human plasma of anticancer drugs derived from natural sources and already used in clinical practice. Particular emphasis was placed both on the pre-analytical and analytical steps, such as: sample preparation procedures, sample size required by the analysis and the limit of quantification of drugs and metabolites to give some insights on the clinical practice applicability. © 2015 Wiley Periodicals, Inc. Mass Spec Rev. 36:213-251, 2017.

Development of a Postcolumn Infused-Internal Standard Liquid Chromatography Mass Spectrometry Method for Quantitative Metabolomics Studies

Quantitative metabolomics has become much more important in clinical research in recent years. Individual differences in matrix effects (MEs) and the injection order effect are two major factors that reduce the quantification accuracy in liquid chromatography-electrospray ionization-mass spectrometry-based (LC-ESI-MS) metabolomics studies. This study proposed a postcolumn infused-internal standard (PCI-IS) combined with a matrix normalization factor (MNF) strategy to improve the analytical accuracy of quantitative metabolomics. The PCI-IS combined with the MNF method was applied for a targeted metabolomics study of amino acids (AAs). D8-Phenylalanine was used as the PCI-IS, and it was postcolumn-infused into the ESI interface for calibration purposes. The MNF was used to bridge the AA response in a standard solution with the plasma samples. The MEs caused signal changes that were corrected by dividing the AA signal intensities by the PCI-IS intensities after adjustment with the MNF. After the method validation, we evaluated the method applicability for breast cancer research using 100 plasma samples. The quantification results revealed that the 11 tested AAs exhibit an accuracy between 88.2 and 110.7%. The principal component analysis score plot revealed that the injection order effect can be successfully removed, and most of the within-group variation of the tested AAs decreased after the PCI-IS correction. Finally, targeted metabolomics studies on the AAs showed that tryptophan was expressed more in malignant patients than in the benign group. We anticipate that a similar approach can be applied to other endogenous metabolites to facilitate quantitative metabolomics studies.

Advances in mass spectrometry-based clinical biomarker discovery

The greatest unmet needs in biomarker discovery are those discoveries that lead to the development of clinical diagnostic tests. These clinical diagnostic tests can provide early intervention when a patient would present otherwise healthy (e.g., cancer or cardiovascular disease) and aid clinical decision making with improved clinical outcomes. The past two decades have seen significant technological improvements in the analytical capabilities of mass spectrometers. Mass spectrometers are unique in that they can directly analyze any biological molecule susceptible to ionization. The biological studies of human metabolites and proteins using contemporary mass spectrometry technology (metabolomics and proteomics, respectively) has been ongoing for over a decade. Some of these studies have resulted in exciting insights into human biology. However, relatively few biomarkers have been translated into clinical tests. This review will discuss some key technological developments that have occurred over this time with an emphasis on technologies that will create new avenues for biomarker discovery.