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

Standardization via Post Column Infusion-A Novel and Convenient Quantification Approach for LC-MS/MS

Mass spectrometry (MS) is a widely used analytical technique including medical diagnostics, forensic toxicology, food and water analysis. The gold standard for quantifying compounds involves using stable isotope-labeled internal standards (SIL-IS). However, when these standards are not commercially available, are prohibitively expensive, or are extremely difficult to synthesize, alternative external quantification techniques are employed. We hereby present a novel, convenient and cheap quantification approach-quantification via post column infusion (PCI). As a proof of concept, we demonstrated PCI quantification for the immunosuppressant tacrolimus in whole blood using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The validation results met the criteria according to the guideline on bioanalytical method validation of the European Medicine Agency (EMA), achieving imprecisions and inaccuracies with coefficient of variation and relative bias below 15%. Anonymized and leftover whole blood samples from immunosuppressed patients receiving tacrolimus were used for method comparison (PCI quantification vs. conventional internal standard (IS) quantification). Both methods showed strong agreement with a Pearson correlation coefficient of r = 0.9532. This novel PCI quantification technique (using the target analyte itself) expands the quantification options available in MS, providing reliable results, particularly when internal standards are unavailable or unaffordable. With the current paper, we aim to demonstrate that our innovative PCI technique has great potential to overcome practical issues in quantification and to provide guidance on how to incorporate PCI in existing or new LC-MS methods. Moreover, this study demonstrated a more convenient method for correcting matrix effects in comparison to alternative PCI techniques.

Largescale multicenter study of a serum metabolite biomarker panel for the diagnosis of breast cancer

Breast cancer (BC) is currently the most prevalent malignancy worldwide, and finding effective non-invasive biomarkers for routine clinical detection of BC remains a significant challenge. Here, we performed non-targeted and targeted metabolomics analysis on the screening, training and validation cohorts of serum samples from 1,947 participants. A metabolite biomarker model including glutamate, erythronate, docosahexaenoate, propionylcarnitine, and patient's age was established for detecting BC. This model demonstrated better diagnostic performance than carbohydrate antigen 15-3 (CA15-3) and carcinoembryonic antigen (CEA) alone in discriminating BC from healthy controls both in the training and validation cohorts [area under the curve (AUC), 0.954; sensitivity, 87.1% and specificity, 93.5% for the training cohort and 0.834, 68.3%, and 85.2%, respectively, for the validation cohort 1]. This study has established a noninvasive approach for the detection of BC, which shows potential as a suitable supplement to the clinical screening methods currently employed for BC.

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.

Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces

Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics.

The role of LSM1 in breast cancer: Shaping metabolism and tumor-associated macrophage infiltration

LSM1 is part of the cytoplasmic protein complex Lsm1-7-Pat1 and is likely involved in pre-mRNA degradation by aiding U4/U6 snRNP formation. More research is needed to uncover LSM1's potential in breast cancer (BRCA) clinical pathology, the tumor immune microenvironment, and precision oncology. We discovered LSM1 as a diagnostic marker for advanced BRCA with poor survival, using a multi-omics approach. We studied LSM1 expression across BRCA regions and its link to immune cells through various methods, including spatial transcriptomics and single-cell RNA-sequencing. We also examined how silencing LSM1 affects mitochondrial function and energy metabolism in the tumor environment. These findings were confirmed using 54 BRCA patient biopsies and tissue microarrays. Immunofluorescence and bioinformatics assessed LSM1's connection to clinicopathological features and prognosis. This study uncovers gene patterns linked to breast cancer, with LSM1 linked to macrophage energy processes. Silencing LSM1 in breast cancer cells disrupts mitochondria and energy metabolism. Spatial analysis aligns with previous results, showing LSM1's connection to macrophages. Biopsies confirm LSM1 elevation in advanced breast cancer with increased macrophage presence. To summarize, LSM1 changes may drive BRCA progression, making it a potential diagnostic and prognostic marker. It also influences energy metabolism and the tumor's immune environment during metastasis, showing promise for precision medicine and drug screening in BRCA.

Hydrogen/deuterium exchange mass spectrometry in the world of small molecules

The combined use of hydrogen/deuterium exchange (HDX) and mass spectrometry (MS), referred to as HDX-MS, is a powerful tool for exploring molecular edifices and has been used for over 60 years. Initially for structural and mechanistic investigation of low-molecular weight organic compounds, then to study protein structure and dynamics, then, the craze to study small molecules by HDX-MS accelerated and has not stopped yet. The purpose of this review is to present its different facets with particular emphasis on recent developments and applications. Reversible H/D exchanges of mobilizable protons as well as stable exchanges of non-labile hydrogen are considered whether they are taking place in solution or in the gas phase, or enzymatically in a biological media. Some fundamental principles are restated, especially for gas-phase processes, and an overview of recent applications, ranging from identification to quantification through the study of metabolic pathways, is given.

Phosphoglycerate mutase family member 5 maintains oocyte quality via mitochondrial dynamic rearrangement during aging

Decline in ovarian reserve with aging is associated with reduced fertility and the development of metabolic abnormalities. Once mitochondrial homeostasis is imbalanced, it may lead to poor reproductive cell quality and aging. However, Phosphoglycerate translocase 5 (PGAM5), located in the mitochondrial membrane, is associated with necroptosis, apoptosis, and mitophagy, although the underlying mechanisms associated with ovarian aging remain unknown. Therefore, we attempted to uncover whether the high phosphoglycerate mutant enzyme family member 5 (PGAM5) expression is associated with female infertility in cumulus cells, and aims to find out the underlying mechanism of action of PGAM5. We found that PGAM5 is highly expressed and positively associated with aging, and has the potential to help maintain and regulate mitochondrial dynamics and metabolic reprogramming in aging granulosa cells, ovaries of aged female mice, and elderly patients. PGAM5 undergoes activation in the aging group and translocated to the outer membrane of mitochondria, co‐regulating DRP1; thereby increasing mitochondrial fission. A significant reduction in the quality of mitochondria in the aging group, a serious imbalance, and a significant reduction in energy, causing metabolism shift toward glycolysis, were also reported. Since PGAM5 is eliminated, the mitochondrial function and metabolism of aging cells are partially reversed. A total of 70 patients undergoing in vitro fertilization (IVF) treatment were recruited in this clinical study. The high expression of PGAM5 in the cumulus cells is negatively correlated with the pregnancy rate of infertile patients. Hence, PGAM5 has immense potential to be used as a diagnostic marker.

Investigating the Association of the Biogenic Amine Profile in Urine with Therapeutic Response to Neoadjuvant Chemotherapy in Breast Cancer Patients

Neoadjuvant treatment (NAT) can downstage breast cancer and can be utilized for different clinical applications. However, the response to NAT varies among individuals. Having effective biomarkers is important to optimize the treatment of breast cancer. Concentrations of biogenic amines have been found to show an association with cancer cell proliferation, but their clinical utility remains unclear. This study developed a postcolumn-infused internal standard (PCI-IS)-assisted liquid chromatography combined with tandem mass spectrometry (LC-MS/MS) method for profiling biogenic amines in human urine. Putrescine-d₈ was selected as the PCI-IS to calibrate the errors caused by matrix effects in the urine sample. The optimized method was applied to investigate the association between changes in 14 amines and the therapeutic response to NAT in breast cancer patients. Urine samples were collected before initiation of chemotherapy (n = 60). Our results indicated that the levels of N¹-acetylspermine, spermidine, norepinephrine, and dopamine were significantly higher in the responder group than the nonresponder group. These metabolites were incorporated with clinical factors to identify NAT responders, and the prediction model showed an area under the curve value of 0.949. These observations provide remarkable insights for future studies in elucidating the roles of biogenic amines in breast cancer. Additionally, the PCI-IS-assisted amine profiling method can facilitate these studies.

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.

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.

Metabolomics: a promising diagnostic and therapeutic implement for breast cancer

Breast cancer (BC) is the most commonly diagnosed cancer among women and the leading cause of cancer death. Despite the advent of numerous diagnosis and treatment methods in recent years, this heterogeneous disease still presents great challenges in early diagnosis, curative treatments and prognosis monitoring. Thus, finding promising early diagnostic biomarkers and therapeutic targets and approaches is meaningful. Metabolomics, which focuses on the analysis of metabolites that change during metabolism, can reveal even a subtle abnormal change in an individual. In recent decades, the exploration of cancer-related metabolomics has increased. Metabolites can be promising biomarkers for the screening, response evaluation and prognosis of BC. In this review, we summarized the workflow of metabolomics, described metabolite signatures based on molecular subtype as well as reclassification and then discussed the application of metabolomics in the early diagnosis, monitoring and prognosis of BC to offer new insights for clinicians in breast cancer diagnosis and treatment.