Multiplex technologies for the assessment of minimal residual disease and low-level mutation detection in leukaemia: mass spectrometry versus next-generation sequencing.

With the focus of leukaemia management shifting to the implications of low-level disease burden, increasing attention is being paid on the development of highly sensitive methodologies required for detection. There are various techniques capable of identification of measurable residual disease (MRD) either evidencing as relevant mutation detection [e.g. nucleophosmin 1 (NPM1) mutation] or trace levels of leukaemic clonal populations. The vast majority of these methods only permit detection of a single clone or mutation. However, mass spectrometry and next-generation sequencing enable the interrogation of multiple genes simultaneously, facilitating a more complete genomic profile. In the present review, we explore the methodologies of both techniques in conjunction with the important advantages and limitations associated with each assay. We also highlight the evidence and the various instances where either technique has been used and propose future strategies for MRD detection.

ICP-MS Determination of 23 Elements of Potential Health Concern in Liquids of e-Cigarettes. Method Development, Validation, and Application to 37 Real Samples.

The lack of interest in the determination of toxic elements in liquids for electronic cigarettes (e-liquids) has so far been reflected in the scarce number of accurate and validated analytical methods devoted to this aim. Since the strong matrix effects observed for e-liquids constitute an exciting analytical challenge, the main goal of this study was to develop and validate an ICP-MS method aimed to quantify 23 elements in 37 e-liquids of different flavors. Great attention has been paid to the critical phases of sample pre-treatment, as well as to the optimization of the ICP-MS conditions for each element and of the quantification. All samples exhibited a very low amount of the elements under investigation. Indeed, the sum of their average concentration was of ca. 0.6 mg kg-1. Toxic elements were always below a few tens of a µg per kg-1 and, very often, their amount was below the relevant quantification limits. Tobacco and tonic flavors showed the highest and the lowest concentration of elements, respectively. The most abundant elements came frequently from propylene glycol and vegetal glycerin, as confirmed by PCA. A proper choice of these substances could further decrease the elemental concentration in e-liquids, which are probably barely involved as potential sources of toxic elements inhaled by vapers.

Assessment of Breathomics Testing Using High-Pressure Photon Ionization Time-of-Flight Mass Spectrometry to Detect Esophageal Cancer.

Importance: A triage test is needed to increase the detection rate for esophageal cancer. Objective: To investigate whether breathomics can detect esophageal cancer among patients without a previous diagnosis of cancer using high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS). Design, Setting, and Participants: This diagnostic study included participants who planned to receive an upper endoscopy or surgery of the esophagus at a single center in China. Exhaled breath was collected with a self-designed collector and air bags before participants underwent these procedures. Sample collection and analyses were performed by trained researchers following a standardized protocol. Participants were randomly divided into a discovery data set and a validation data set. Data were collected from December 2020 to March 2021. Exposures: Breath samples were analyzed by HPPI-TOFMS, and the support vector machine algorithm was used to construct a detection model. Main Outcomes and Measures: The accuracy of breathomics was measured by the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve. Results: Exhaled breath samples were obtained from 675 patients (216 [32%] with esophageal cancer; 459 [68%] with noncancer diseases). Of all patients, 206 (31%) were women, and the mean (SD) age was 64.0 (11.9) years. In the validation data set, esophageal cancer was detected with an accuracy of 93.33%, sensitivity of 97.83%, specificity of 83.72%, positive predictive value of 94.74%, negative predictive value of 92.78%, and area under the receiver operating characteristic curve of 0.89. Notably, for 16 patients with high-grade intraepithelial neoplasia, 12 (75%) were predicted to have esophageal cancer. Conclusions and Relevance: In this diagnostic study, testing breathomics using HPPI-TOFMS was feasible for esophageal cancer detection and totally noninvasive, which could help to improve the diagnosis of esophageal cancer.

Acoustic Ejection Mass Spectrometry: A Fully Automatable Technology for High-Throughput Screening in Drug Discovery.

Acoustic droplet ejection (ADE)-open port interface (OPI)-mass spectrometry (MS) has recently been introduced as a versatile analytical method that combines fast and contactless acoustic sampling with sensitive and accurate electrospray ionization (ESI)-MS-based analyte detection. The potential of the technology to provide label-free measurements in subsecond analytical cycle times makes it an attractive option for high-throughput screening (HTS). Here, we report the first implementation of ADE-OPI-MS in a fully automated HTS environment, based on the example of a biochemical assay aiming at the identification of small-molecule inhibitors of the cyclic guanosine monophosphate-adenosine monophosphate (GMP-AMP) synthase (cGAS). First, we describe the optimization of the method to enable sensitive and accurate determination of enzyme activity and inhibition in miniaturized 1536-well microtiter plate format. Then we show both results from a validation single-concentration screen using a test set of 5500 compounds, and the subsequent concentration-response testing of selected hits in direct comparison with a previously established matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) readout. Finally, we present the development of an in-line OPI cleaning procedure aiming to match the instrument robustness required for large-scale HTS campaigns. Overall, this work points to critical method development parameters and provides guidance for the establishment of integrated ADE-OPI-MS as HTS-compatible technology for early drug discovery.

Analytical quality by design methodology for botanical raw material analysis: a case study of flavonoids in Genkwa Flos.

The present study introduces a systematic approach using analytical quality by design (AQbD) methodology for the development of a qualified liquid chromatographic analytical method, which is a challenge in herbal medicinal products due to the intrinsic complex components of botanical sources. The ultra-high-performance liquid chromatography-photodiode array-mass spectrometry (UHPLC-PDA-MS) technique for 11 flavonoids in Genkwa Flos was utilized through the entire analytical processes, from the risk assessment study to the factor screening test, and finally in method optimization employing central composite design (CCD). In this approach, column temperature and mobile solvent slope were found to be critical method parameters (CMPs) and each of the eleven flavonoid peaks' resolution values were used as critical method attributes (CMAs) through data mining conversion formulas. An optimum chromatographic method in the design space was calculated by mathematical and response surface methodology (RSM). The established chromatographic condition is as follows: acetonitrile and 0.1% formic acid gradient elution (0-13 min, 10-45%; 13-13.5 min, 45-100%; 13.5-14 min, 100-10%; 14-15 min, 10% acetonitrile), column temperature 28℃, detection wavelength 335 nm, and flow rate 0.35 mL/min using C18 (50 × 2.1 mm, 1.7 µm) column. A validation study was also performed successfully for apigenin 7-O-glucuronide, apigenin, and genkwanin. A few important validation results were as follows: linearity over 0.999 coefficient of correlation, detection limit of 2.87-22.41, quantitation limit of 8.70-67.92, relative standard deviation of precision less than 0.22%, and accuracy between 100.13 and 102.49% for apigenin, genkwanin, and apigenin 7-O-glucuronide. In conclusion, the present design-based approach provide a systematic platform that can be effectively applied to ensure pharmaceutically qualified analytical data from complex natural products based botanical drug.

Comparison of Two Analytical Methods for Busulfan Therapeutic Drug Monitoring.

BACKGROUND AND OBJECTIVES: Busulfan (Bu) is an old drug, but is still well recommended as an alkylating agent during conditioning therapy, before hematopoietic stem cell transplantation. Although its dose administration is standardized and based on patient weight, therapeutic drug monitoring is required in order to maintain its exposure [as area under the concentration-time curve (AUC) from 0 to infinity AUC0-∞] within a narrow therapeutic range and, if necessary, to adjust the dose with as short a lead time as possible. The aim of the study is to evaluate the agreement (as calculated AUC) between a gold standard analytical method and a new one that is faster and easier. METHODS: We analyzed 221 plasma samples from 37 children (0.25-16 years; 4-62.5 kg) and 11 adults (21-59 years; 45-80 kg), corresponding to 52 AUC values (ng h/mL). The drug exposure was calculated, simultaneously, by two validated analytical methods. The reference method was a high-performance liquid chromatography (HPLC) assay combined with an ultraviolet detector (UV). The test method had a triple quadrupole mass spectrometer (MS) as detector; the clean-up procedures of the samples were different and faster. RESULTS: The agreement between the two methods (reference and test) was evaluated in terms of Bu exposure differences based on Lin's concordance correlation coefficient (CCC) and represented by the Bland-Altman plot. The CCC between the AUC of the two methods was excellent (0.868; 95% CI: 0.802-0.935). The precision of the measures (expressed by Pearson's italic "r") was 0.872, and the accuracy (accounted by the bias correction factor) was 0.996. CONCLUSIONS: We can conclude that the HPLC-MS/MS assay represents a very good alternative to the reference.

A Microwave Digestion Technique for the Analysis of Rare Earth Elements, Thorium and Uranium in Geochemical Certified Reference Materials and Soils by Inductively Coupled Plasma Mass Spectrometry.

Two different digestion methods-microwave digestion (Mw) and Savillex digestion (Sx)-were used to evaluate the best quality control for analysis of the rare earth elements, Th and U in the geochemical certified reference material JSd-2, supplied by the Geological Survey of Japan (GSJ). The analysis of trace elements was carried out using inductively coupled plasma mass spectrometry (ICP-MS). The digestion recovery was > 90% for almost all elements by both methods. Mw-4 (four repeats of the microwave digestion) was found to be more effective and faster than Sx. In order to evaluate the efficiency of Mw-4, three other GSJ certified reference materials, JLk-1, JB-1 and JB-3, as well as five different soil samples from Belarus, Japan, Serbia and Ukraine were also analyzed. The Mw-4 method was seen to be promising for complete digestion and recovery of most of the elements. The U/Th ratio showed some heterogeneity for Ukraine and Serbia soils affected by Chernobyl nuclear power plant accident and depleted uranium contamination, respectively. This method can be successfully applied to any type of soils for elemental analyses.

Standardization and harmonization of distributed multi-center proteotype analysis supporting precision medicine studies.

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrate robust, sensitive, and reproducible data generation across eleven international sites on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality.

DIALib-QC an assessment tool for spectral libraries in data-independent acquisition proteomics.

Data-independent acquisition (DIA) mass spectrometry, also known as Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH), is a popular label-free proteomics strategy to comprehensively quantify peptides/proteins utilizing mass spectral libraries to decipher inherently multiplexed spectra collected linearly across a mass range. Although there are many spectral libraries produced worldwide, the quality control of these libraries is lacking. We present the DIALib-QC (DIA library quality control) software tool for the systematic evaluation of a library's characteristics, completeness and correctness across 62 parameters of compliance, and further provide the option to improve its quality. We demonstrate its utility in assessing and repairing spectral libraries for correctness, accuracy and sensitivity.

Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions.

Mass spectrometry based metabolomics is a widely used approach in biomedical research. However, current methods coupling mass spectrometry with chromatography are time-consuming and not suitable for high-throughput analysis of thousands of samples. An alternative approach is flow-injection mass spectrometry (FI-MS) in which samples are directly injected to the ionization source. Here, we show that the sensitivity of Orbitrap FI-MS metabolomics methods is limited by ion competition effect. We describe an approach for overcoming this effect by analyzing the distribution of ion m/z values and computationally determining a series of optimal scan ranges. This enables reproducible detection of ~9,000 and ~10,000 m/z features in metabolomics and lipidomics analysis of serum samples, respectively, with a sample scan time of ~15 s and duty time of ~30 s; a ~50% increase versus current spectral-stitching FI-MS. This approach facilitates high-throughput metabolomics for a variety of applications, including biomarker discovery and functional genomics screens.

High-Precision, Gas-Phase Hydrogen/Deuterium-Exchange Kinetics by Mass Spectrometry Enabled by Exchange Standards.

Mass spectrometry (MS) has become a primary tool for identifying and quantifying biological molecules. In combination with other orthogonal techniques, such as gas-phase hydrogen/deuterium exchange (gHDX), MS is also capable of probing the structure of ions. However, gHDX kinetics can depend strongly on many factors, including laboratory temperature, instrumental conditions, and instrument platform selection. These effects can lead to high variability with gHDX measurements, which has hindered the broader adoption of gHDX for structural MS. Here we introduce an approach for standardizing gHDX measurements using cosampled standards. Quantifying the exchange kinetics for analytes relative to the exchange kinetics of the standards results in greater accuracy and precision than the underlying absolute measurements. The standardization was found to be effective for several types of analytes including small molecules and intact proteins. A subset of analytes showed deviations in their standardized exchange profiles that are attributed to field heating and the concomitant conformational isomerization. Inclusion of helium during the gHDX process for collisional cooling helps mitigate such variations in exchange kinetics related to ion heating. We anticipate that the outcomes of this research will enable the broader use of gHDX in MS-based workflows for molecular identification and isomer differentiation.

Determination of the lanthanides, uranium and plutonium by means of on-line high-pressure ion chromatography coupled with sector field inductively coupled plasma-mass spectrometry to characterize nuclear samples.

High-pressure ion chromatography (HPIC) was coupled with sector field inductively coupled plasma-mass spectrometry (SF-ICP-MS) to separate plutonium (Pu), uranium (U), neodymium (Nd) and gadolinium (Gd) nuclides from isobaric nuclides and to quantify them with high sensitivity. In this study, mixed bed ion exchange columns CG5A and CS5A were used, from which Pu and U were eluted first using 1 M nitric acid. The lanthanides were then separated using a gradient of 0.1-0.15 M oxalic acid with the pH adjusted to 4.5. The HPIC-SF-ICP-MS method was validated using different sample matrices, i.e. spent nuclear fuel and soil. The method was found to be repeatable and gave rise to transient signals suitable for quantification of nuclide-specific concentrations using external calibration. In terms of accuracy, the HPIC-SF-ICP-MS measurement results were in good agreement with those obtained using thermal ionization mass spectrometry (TIMS). Finally, the method provides an improvement in sample throughput (≤60 minutes per sample) and reduces exposure of the operator to radiation compared to off-line gravitational chromatography followed by TIMS.

Discriminant analysis and feature selection in mass spectrometry imaging using constrained repeated random sampling - Cross validation (CORRS-CV).

The identification of biomarkers through Mass spectrometry imaging (MSI) is gaining popularity in the clinical field. However, considering the complexity of spectral and spatial variables faced, data mining of the hyperspectral images can be troublesome. The discovery of markers generally depends on the creation of classification models which should be validated to ensure the statistical significance of the discriminants m/z detected. Internal validation using resampling methods such as cross validation (CV) are widely used for model selection, the estimation of its generalization performance and biomarker discovery when sample sizes are limited and an independent test set is not available. Here, we introduce for first time the use of Constrained Repeated Random Subsampling CV (CORRS-CV) on multi-images for the validation of classification models on MSI. Although several aspects must be taken into account (e.g. image size, CORRS-CV∂value, the similarity across spatially close pixels, the total computation time), CORRS-CV provides more accurate estimates of the model performance than k-fold CV using of biological replicates to define the data split when the number of biological replicates is scarce and holding images back for testing is a waste of valuable information. Besides, the combined use of CORRS-CV and rank products increases the robustness of the selection of discriminant features as candidate biomarkers which is an important issue due to the increased biological, environmental and technical variabilities when analysing multiple images, especially from human tissues collected in clinical studies.

Multifunctional isotopic standards based steroidomics strategy: Exploration of cancer screening model.

Quantitative determination of endogenous compounds in biological samples has still been challenged by the absence of authentic blank matrix. Alternative strategy of surrogate matrix for preparing reference samples are prevalent due to its low cost and high availability. However, the evaluation system of surrogate matrix is not perfect. Herein, a novel multifunctional isotopic standards based steroidomics strategy was developed. Isotope-labeled standards were used not only as internal standards but also for the evaluation the feasibility of surrogate matrix, which improved the accuracy of assessment and could provide a new prospect for the quantitative analysis of endogenous compounds. Based on this approach, a detailed optimization from LC separation, MS detection to extraction conditions for global steroids in the steroidogenesis was firstly carried out. Characteristics and regularities of steroids in LC-MS were summarized to make references for further targeted or untargeted steroidomics study. Then eighteen steroids were quantified with high accuracy and high sensitivity in plasma from four types of cancer patients and healthy subjects using 1% BSA in PBS as surrogate matrix. And multi-steroids indexes with the best discriminating ability for lung, colorectal, breast and gastric cancer in different genders were identified successfully with Student's t-test, PLS-DA and logistic regression- ROC curve analysis. Finally, efficient cancer screening workflow was established by integrating the amine submetabolomics and lipidomics data of our previous studies. Taken together, the integrated steroidomics strategy could shed a light on the guidance for further steroidome as well as other endogenous compounds analysis and may provide a powerful tool for cancer diagnosis.

Analysis of ADCs by Native Mass Spectrometry.

Mass spectrometry performed in nondenaturing conditions (native MS) has proven its utility for the quantitative and qualitative analysis of antibody-drug conjugates (ADCs), especially when ADCs' subunits involve noncovalent interactions (i.e., cysteine-conjugated ADCs). Its hyphenation to ion mobility spectrometry (IM-MS) allows differentiation of gas-phase ions based on their rotationally averaged collision cross section providing an additional dimension of conformational characterization of ADCs. More recently, size exclusion chromatography (SEC) appeared as an interesting technique to perform online buffer exchange in an automated way prior to native MS/IM-MS analysis. Online SEC-native MS/IM-MS allows the global structural characterization of ADCs and the assessment of some critical quality attributes (CQAs) required for ADC release on the market, such as drug load distribution (DLD), drug-to-antibody ratio (DAR), the average DAR (DARav), and the relative amount of unconjugated mAb.

Targeting Endogenous Adduction Level of Serum Albumin by Parallel Reaction Monitoring via Standard Additions and Intact Protein Measurement: Biological Dosimetry of Catechol Estrogens.

Abundant blood proteins adducted by active electrophiles are excellent markers to predict the risk of electrophile-induced toxicity. However, detecting endogenously adducted proteins by bottom-up selective (or parallel) reaction monitoring (SRM/PRM) is challenging because of the high variability in sample preparation and detection as well as low adduction levels. Here, we reported a new approach in developing PRM methods by combining intact protein measurement with standard additions to target optimal conditions for detecting catechol estrogens (CEs)-adducted human serum albumin (HSA). Blood serum was added with multiple amounts of CEs to obtain serum standards. Intact protein measurement revealed two linear ranges of adduction levels (adducted-CE/HSA): 0.34-0.42 (R2 > 0.94) and 0.81-8.54 (R2 > 0.96) against the amount of added CEs, respectively. Six adduction sites were identified by trypsin (K20, C34, K73, K281, H338, K378) or chymotrypsin (K20, C34, K378) digestion. PRM methods targeting all adducted/nonadducted peptide pairs based on chymotrypsin or trypsin digestion were developed, and the data were compared with those obtained by intact protein measurement. Correlation plots indicated that chymotrypsin-PRM leads to poor sensitivity and largely underestimated protein adduction levels. Trypsin-PRM leads to sensitive and highly correlated (R2 > 0.91) protein adduction levels with a detection limit below the endogenous level and relative standard deviation <25%. As a proof of concept, clinical serum samples were examined by trypsin-PRM, and a slightly higher adduction level was observed for the obesity group when compared with the healthy group. This is the first report on determining adduction levels of blood proteins for long-term exposure to CEs. The standard addition approach can be generally applied to protein adductomics with resolvable mass increments by intact protein measurement to accelerate the development of bottom-up methods close to the inherent limit.

Quality control of imbalanced mass spectra from isotopic labeling experiments.

BACKGROUND: Mass spectra are usually acquired from the Liquid Chromatography-Mass Spectrometry (LC-MS) analysis for isotope labeled proteomics experiments. In such experiments, the mass profiles of labeled (heavy) and unlabeled (light) peptide pairs are represented by isotope clusters (2D or 3D) that provide valuable information about the studied biological samples in different conditions. The core task of quality control in quantitative LC-MS experiment is to filter out low-quality peptides with questionable profiles. The commonly used methods for this problem are the classification approaches. However, the data imbalance problems in previous control methods are often ignored or mishandled. In this study, we introduced a quality control framework based on the extreme gradient boosting machine (XGBoost), and carefully addressed the imbalanced data problem in this framework. RESULTS: In the XGBoost based framework, we suggest the application of the Synthetic minority over-sampling technique (SMOTE) to re-balance data and use the balanced data to train the boosted trees as the classifier. Then the classifier is applied to other data for the peptide quality assessment. Experimental results show that our proposed framework increases the reliability of peptide heavy-light ratio estimation significantly. CONCLUSIONS: Our results indicate that this framework is a powerful method for the peptide quality assessment. For the feature extraction part, the extracted ion chromatogram (XIC) based features contribute to the peptide quality assessment. To solve the imbalanced data problem, SMOTE brings a much better classification performance. Finally, the XGBoost is capable for the peptide quality control. Overall, our proposed framework provides reliable results for the further proteomics studies.

Precise co-registration of mass spectrometry imaging, histology, and laser microdissection-based omics.

Mass spectrometry imaging (MSI) is an analytical technique for the unlabeled and multiplex imaging of molecules in biological tissue sections. It therefore enables the spatial and molecular annotations of tissues complementary to histology. It has already been shown that MSI can guide subsequent material isolation technologies such as laser microdissection (LMD) to enable a more in-depth molecular characterization of MSI-highlighted tissue regions. However, with MSI now reaching spatial resolutions at the single-cell scale, there is a need for a precise co-registration between MSI and the LMD. As proof-of-principle, MSI of lipids was performed on a breast cancer tissue followed by a segmentation of the data to detect molecularly distinct segments within its tumor areas. After image processing of the segmentation results, the coordinates of the MSI-detected segments were passed to the LMD system by three co-registration steps. The errors of each co-registration step were quantified and the total error was found to be less than 13 µm. With this link established, MSI data can now accurately guide LMD to excise MSI-defined regions of interest for subsequent extract-based analyses. In our example, the excised tissue material was then subjected to ultrasensitive microproteomics in order to determine predominant molecular mechanisms in each of the MSI-highlighted intratumor segments. This work shows how the strengths of MSI, histology, and extract-based omics can be combined to enable a more comprehensive molecular characterization of in situ biological processes.

Optimization and Standardization of Thermal Treatment as a Plasma Prefractionation Method for Proteomic Analysis.

Prefractionation is a prerequisite step for deep plasma proteomics. Highly abundant proteins, particularly human serum albumin (HSA) and immunoglobulin G (IgG), typically interfere with investigation of proteins with lower abundance. A relatively simple preparation method based on high temperature can precipitate thermolabile proteins, providing a strategic window to access the thermostable plasma subproteome. This study aimed to optimize thermal treatment as a reliable prefractionation method and to compare it with two commercial kits, including HSA and IgG immunodepletion (IMDP) and combinatorial peptide ligand libraries (CPLL), using untreated plasma as a control condition. By varying the temperature and the incubation period, the optimal condition was found as treatment at 95°C for 20 min, which maintained about 1% recovery yield of soluble proteins. Consistency and reproducibility of thermal treatment-derived plasma subproteome were checked by two-dimensional electrophoresis. The coefficient of variation regarding protein spot numbers was less than 10% among three independent specimens. Highly abundant protein depletion of the thermal treatment was evaluated by immunoblotting against HSA and IgG as compared to the untreated plasma, IMDP, and CPLL. Multidimensional comparison based on 489 unique peptides derived from the label-free quantitative mass spectrometry revealed that the thermal treatment, IMDP, and CPLL provided distinct sets of plasma subproteome compared to untreated plasma, and these appeared to be complementary to each other. Comparing the characteristics of the three procedures suggested that thermal treatment was more cost-effective and less time-consuming than IMDP and CPLL. This study proposes the use of thermal treatment as a reliable and cost-effective method for plasma prefractionation which provides benefits to large-scale proteomic projects and biomarker studies.