Generic Enrichment Method for Liquid Chromatography-Multiple Reaction Monitoring-Mass Spectrometry Assay for Quantitative Measurement of Biological Therapeutics in Serum.

PURPOSE: The study aims to leverage the capabilities of Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry (LC-MRM), a key technique in quantifying therapeutic proteins in pharmacokinetic studies. The focus is on demonstrating an enrichment method using ProteoMiner beads, which can be integrated with LC-MRM to detect low-abundance biotherapeutics in serum, such as monoclonal antibodies and gene therapy products. METHODS: The ProteoMiner enrichment method was employed and integrated with LC-MRM. The lower limit of quantification of serum drug substance concentrations was compared with that achievable with immuno-enrichment. The method used commercially available reagents, eliminating the need for assay-specific antibodies and reducing potential bias and development time. RESULTS: The ProteoMiner enrichment method showed comparable performance to immuno-enrichment, meeting traditional assay requirements in terms of precision, accuracy, and specificity. CONCLUSIONS: The ProteoMiner enrichment method, when combined with LC-MRM, offers a reliable and efficient alternative to immuno-enrichment for detecting and quantifying low-abundance biotherapeutics in serum. This approach, which uses commercially available reagents, can eliminate the bias and time associated with the development of assay-specific antibodies. It holds significant potential for accelerating pharmacokinetic analysis in both early and late stages of pharmaceutical development.

Multiple Reaction Monitoring-Mass Spectrometry Enables Robust Quantitation of Plasma Proteins Regardless of Whole Blood Processing Delays That May Occur in the Clinic.

Plasma is an important biofluid for clinical research and diagnostics. In the clinic, unpredictable delays-from minutes to hours-between blood collection and plasma generation are often unavoidable. These delays can potentially lead to protein degradation and modification and might considerably affect intact protein measurement methods such as sandwich enzyme-linked immunosorbent assays that bind proteins on two epitopes to increase specificity, thus requiring largely intact protein structures. Here, we investigated, using multiple reaction monitoring mass spectrometry (MRM-MS), how delays in plasma processing affect peptide-centric "bottom-up" proteomics. We used validated assays for proteotypic peptide surrogates of 270 human proteins to analyze plasma generated after whole blood had been kept at room temperature from 0 to 40 h to mimic delays that occur in the clinic. Moreover, we evaluated the impact of different plasma-thawing conditions on MRM-based plasma protein quantitation. We demonstrate that >90% of protein concentration measurements were unaffected by the thawing procedure and by up to 40-h delayed plasma generation, reflected by relative standard deviations (RSDs) of <30%. Of the 159 MRM assays that yielded quantitative results in 60% of the measured time points, 139 enabled a stable protein quantitation (RSD <20%), 14 showed a slight variation (RSD 20-30%), and 6 appeared unstable/irreproducible (RSD > 30%). These results demonstrate the high robustness and thus the potential for MRM-based plasma-protein quantitation to be used in a clinical setting. In contrast to enzyme-linked immunosorbent assay, peptide-based MRM assays do not require intact three-dimensional protein structures for an accurate and precise quantitation of protein concentrations in the original sample.

Quantitative Proteomic Approach for Discriminating Major Depressive Disorder and Bipolar Disorder by Multiple Reaction Monitoring-Mass Spectrometry.

Because major depressive disorder (MDD) and bipolar disorder (BD) manifest with similar symptoms, misdiagnosis is a persistent issue, necessitating their differentiation through objective methods. This study was aimed to differentiate between these disorders using a targeted proteomic approach. Multiple reaction monitoring-mass spectrometry (MRM-MS) analysis was performed to quantify protein targets regarding the two disorders in plasma samples of 270 individuals (90 MDD, 90 BD, and 90 healthy controls (HCs)). In the training set (72 MDD and 72 BD), a generalizable model comprising nine proteins was developed. The model was evaluated in the test set (18 MDD and 18 BD). The model demonstrated a good performance (area under the curve (AUC) >0.8) in discriminating MDD from BD in the training (AUC = 0.84) and test sets (AUC = 0.81) and in distinguishing MDD from BD without current hypomanic/manic/mixed symptoms (90 MDD and 75 BD) (AUC = 0.83). Subsequently, the model demonstrated excellent performance for drug-free MDD versus BD (11 MDD and 10 BD) (AUC = 0.96) and good performance for MDD versus HC (AUC = 0.87) and BD versus HC (AUC = 0.86). Furthermore, the nine proteins were associated with neuro, oxidative/nitrosative stress, and immunity/inflammation-related biological functions. This proof-of-concept study introduces a potential model for distinguishing between the two disorders.

Clinical Application of Multiple Reaction Monitoring-Mass Spectrometry to Human Epidermal Growth Factor Receptor 2 Measurements as a Potential Diagnostic Tool for Breast Cancer Therapy.

BACKGROUND: Human epidermal growth factor receptor 2 (HER2) is often overexpressed in breast cancer and correlates with a worse prognosis. Thus, the accurate detection of HER2 is crucial for providing the appropriate measures for patients. However, the current techniques used to detect HER2 status, immunohistochemistry and fluorescence in situ hybridization (FISH), have limitations. Specifically, FISH, which is mandatory for arbitrating 2+ cases, is time-consuming and costly. To address this shortcoming, we established a multiple reaction monitoring-mass spectrometry (MRM-MS) assay that improves on existing methods for differentiating HER2 status. METHODS: We quantified HER2 expression levels in 210 breast cancer formalin-fixed paraffin-embedded (FFPE) tissue samples by MRM-MS. We aimed to improve the accuracy and precision of HER2 quantification by simplifying the sample preparation through predicting the number of FFPE slides required to ensure an adequate amount of protein and using the expression levels of an epithelial cell-specific protein as a normalization factor when measuring HER2 expression levels. RESULTS: To assess the correlation between MRM-MS and IHC/FISH data, HER2 quantitative data from MRM-MS were divided by the expression levels of junctional adhesion molecule A, an epithelial cell-specific protein, prior to statistical analysis. The normalized HER2 amounts distinguished between HER2 2+/FISH-negative and 2+/FISH-positive groups (AUROC = 0.908), which could not be differentiated by IHC. In addition, all HER2 status were discriminated by MRM-MS. CONCLUSIONS: This MRM-MS assay yields more accurate HER2 expression levels relative to immunohistochemistry and should help to guide clinicians toward the proper treatment for breast cancer patients, based on their HER2 expression.

Drug response prediction model using a hierarchical structural component modeling method.

BACKGROUND: Component-based structural equation modeling methods are now widely used in science, business, education, and other fields. This method uses unobservable variables, i.e., "latent" variables, and structural equation model relationships between observable variables. Here, we applied this structural equation modeling method to biologically structured data. To identify candidate drug-response biomarkers, we first used proteomic peptide-level data, as measured by multiple reaction monitoring mass spectrometry (MRM-MS), for liver cancer patients. MRM-MS is a highly sensitive and selective method for proteomic targeted quantitation of peptide abundances in complex biological samples. RESULTS: We developed a component-based drug response prediction model, having the advantage that it first combines collapsed peptide-level data into protein-level information, facilitating subsequent biological interpretation. Our model also uses an alternating least squares algorithm, to efficiently estimate both coefficients of peptides and proteins. This approach also considers correlations between variables, without constraint, by a multiple testing problem. Using estimated peptide and protein coefficients, we selected significant protein biomarkers by permutation testing, resulting in our model for predicting liver cancer response to the tyrosine kinase inhibitor sorafenib. CONCLUSIONS: Using data from a cohort of liver cancer patients, we then "fine-tuned" our model to successfully predict drug responses, as demonstrated by a high area under the curve (AUC) score. Such drug response prediction models may eventually find clinical translation in identifying individual patients likely to respond to specific therapies.

Targeted Proteomics Predicts a Sustained Complete-Response after Transarterial Chemoembolization and Clinical Outcomes in Patients with Hepatocellular Carcinoma: A Prospective Cohort Study.

This study was aimed to identify blood-based biomarkers to predict a sustained complete response (CR) after transarterial chemoembolization (TACE) using targeted proteomics. Consecutive patients with HCC who had undergone TACE were prospectively enrolled (training (n = 100) and validation set (n = 80)). Serum samples were obtained before and 6 months after TACE. Treatment responses were evaluated using the modified Response Evaluation Criteria in Solid Tumors (mRECIST). In the training set, the MRM-MS assay identified five marker candidate proteins (LRG1, APCS, BCHE, C7, and FCN3). When this five-marker panel was combined with the best-performing clinical variables (tumor number, baseline PIVKA, and baseline AFP), the resulting ensemble model had the highest area under the receiver operating curve (AUROC) value in predicting a sustained CR after TACE in the training and validation sets (0.881 and 0.813, respectively). Furthermore, the ensemble model was an independent predictor of rapid progression (hazard ratio (HR), 2.889; 95% confidence interval (CI), 1.612-5.178; P value < 0.001) and overall an unfavorable survival rate (HR, 1.985; 95% CI, 1.024-3.848; P value = 0.042) in the entire population by multivariate analysis. Targeted proteomics-based ensemble model can predict clinical outcomes after TACE. Therefore, this model can aid in determining the best candidates for TACE and the need for adjuvant therapy.

Profiling of urinary bile acids in piglets by a combination of enzymatic deconjugation and targeted LC-MRM-MS.

We present a method using a combination of enzymatic deconjugation and targeted LC-multiple reaction monitoring (MRM)-MS analysis for analyzing all common bile acids (BAs) in piglet urine, and in particular, for detecting conjugated BAs either in the absence of their standards, or when present in low concentrations. Initially, before enzymatic deconjugation, 19 unconjugated BAs (FBAs) were detected where the total concentration of the detected FBAs was 9.90 µmol/l. Sixty-seven conjugated BAs were identified by LC-MRM-MS analysis before and after enzymatic deconjugation. Four enzymatic assays were used to deconjugate the BA conjugates. FBAs in urine after cholylglycine hydrolase/sulfatase treatment were 33.40 µmol/l, indicating the urinary BAs were comprised of 29.75% FBAs and 70.25% conjugated BAs in single and multiple conjugated forms. For the conjugates in single form, released FBAs from cholylglycine hydrolase deconjugation indicated that the conjugates with amino acids were 14.54% of urinary BAs, 16.27% glycosidic conjugates were found by ß-glucuronidase treatment, and sulfatase with glucuronidase inhibitor treatment liberated FBAs that constituted 16.67% of urinary BAs. Notably, chenodeoxycholic acid (CDCA) was initially detected only in trace amounts in urine, but was found at significant levels after the enzymatic assays above. These results support that CDCA is a precursor of γ-muricholic acid in BA biosynthesis in piglets.

Evaluating kinase ATP uptake and tyrosine phosphorylation using multiplexed quantification of chemically labeled and post-translationally modified peptides.

Cancer biologists and other healthcare researchers face an increasing challenge in addressing the molecular complexity of disease. Biomarker measurement tools and techniques now contribute to both basic science and translational research. In particular, liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) for multiplexed measurements of protein biomarkers has emerged as a versatile tool for systems biology. Assays can be developed for specific peptides that report on protein expression, mutation, or post-translational modification; discovery proteomics data rapidly translated into multiplexed quantitative approaches. Complementary advances in affinity purification enrich classes of enzymes or peptides representing post-translationally modified or chemically labeled substrates. Here, we illustrate the process for the relative quantification of hundreds of peptides in a single LC-MRM experiment. Desthiobiotinylated peptides produced by activity-based protein profiling (ABPP) using ATP probes and tyrosine-phosphorylated peptides are used as examples. These targeted quantification panels can be applied to further understand the biology of human disease.

Profiling of Oxylipins as Markers of Oxidative Stress in Biological Samples.

Oxylipins are oxidized metabolites of polyunsaturated fatty acids (PUFAs). They represent a class of risk markers and/or therapeutic targets for diseases associated with inflammation, including cardiovascular disease and brain disorders. Because the biological activities of free PUFAs and oxylipins depend on their chemical structures and concentrations, monitoring PUFAs and oxylipin levels in biological systems is critical for understanding their roles in health and disease. Traditionally, accurate quantification of free PUFAs and oxylipins in biological samples was performed separately, as PUFAs are often 1000-fold more abundant than the derived oxidized fatty acids (oxylipins). This article describes a liquid chromatography multiple reaction monitoring tandem mass spectrometry method for the quantitative analysis of five free PUFAs and 88 oxylipins in various biological fluids, including plasma, platelet supernatants, and tissues. The same approach can also be used in conjunction with an alkaline hydrolysis step to quantify total oxylipins in fish oils. We observed that in some samples, linoleic acid levels in plasma and eicosapentaenoic acid and arachidonic acid levels in brain tissue were above the upper limit of quantification. To address this issue, we developed a data analysis method to obtain PUFA and oxylipin concentrations in these samples without additional sample preparation, thus significantly saving time and labor. © 2024 Wiley Periodicals LLC. Basic Protocol: Quantification of polyunsaturated fatty acids (PUFAs) and oxylipins using liquid chromatography multiple reaction monitoring tandem mass spectrometry Support Protocol 1: Preparation of internal standard mixed working solution Support Protocol 2: Preparation of standard mixed stock solution Support Protocol 3: Preparation of standard mixed working solution Alternate Protocol 1: Extraction and quantitation of free PUFAs and oxylipins from mouse brain tissue Alternate Protocol 2: Extraction and quantitation of total PUFAs and oxylipins from fish oil.

Integrating site-specific peptide reporters and targeted mass spectrometry enables rapid substrate-specific kinase assay at the nanogram cell level.

Dysregulation of phosphorylation-mediated signaling drives the initiation and progression of many diseases. A substrate-specific kinase assay capable of quantifying the altered site-specific phosphorylation of its phenotype-dependent substrates provides better specificity to monitor a disease state. We report a sensitive and rapid substrate-specific kinase assay by integrating site-specific peptide reporter and multiple reaction monitoring (MRM)-MS platform for relative and absolute quantification of substrate-specific kinase activity at the sensitivity of nanomolar kinase and nanogram cell lysate. Using non-small cell lung cancer as a proof-of-concept, three substrate peptides selected from constitutive phosphorylation in tumors (HDGF-S165, RALY-S135, and NRD1-S94) were designed to demonstrate the feasibility. The assay showed good accuracy (<15% nominal deviation) and reproducibility (<15% CV). In PC9 cells, the measured activity for HDGF-S165 was 3.2 ± 0.2 fmol µg-1 min-1, while RALY-S135 and NRD1-S94 showed 4- and 20-fold higher activity at the sensitivity of 25 ng and 5 ng lysate, respectively, suggesting different endogenous kinases for each substrate peptide. Without the conventional shotgun phosphoproteomics workflow, the overall pipeline from cell lysate to MS data acquisition only takes 3 h. The multiplexed analysis revealed differences in the phenotype-dependent substrate phosphorylation profiles across six NSCLC cell lines and suggested a potential association of HDGF-S165 and NRD1-S94 with TKI resistance. With the ease of design, sensitivity, accuracy, and reproducibility, this approach may offer rapid and sensitive assays for targeted quantification of the multiplexed substrate-specific kinase activity of small amounts of sample.

Hordein Accumulation in Developing Barley Grains.

The temporal pattern of accumulation of hordein storage proteins in developing barley grains was studied by enzyme-linked immunosorbent assay (ELISA), western blot and liquid chromatography tandem mass spectrometry (LC-MS/MS). Hordein accumulation was compared to the pattern seen for two abundant control proteins, serpin Z4 (an early accumulator) and lipid transferase protein (LTP1, a late accumulator). Hordeins were detected from 6 days post-anthesis (DPA) and peaked at 30 DPA. Changes in fresh weight indicate that desiccation begins at 20 DPA and by 37 DPA fresh weight had decreased by 35%. ELISA analysis of hordein content, expressed on a protein basis, increased to a maximum at 30 DPA followed by a 17% decrease by 37 DPA. The accumulation of 39 tryptic and 29 chymotryptic hordein peptides representing all classes of hordein was studied by LC-MS/MS. Most peptides increased to a maximum at 30 DPA, and either remained at the maximum or did not decrease significantly. Only five tryptic peptides, members of the related B1- and γ1-hordeins decreased significantly by 21-51% at 37 DPA. Thus, the concentration of some specific peptides was reduced while remaining members of the same family were not affected. The N-terminal signal region was removed by proteolysis during co-translation. In addition to a suite of previously characterized hordeins, two novel barley B-hordein isoforms mapping to wheat low molecular weight glutenins (LMW-GS-like B-hordeins), and two avenin-like proteins (ALPs) sharing homology with wheat ALPs, were identified. These identified isoforms have not previously been mapped in the barley genome. Cereal storage proteins provide significant nutritional content for human consumption and seed germination. In barley, the bulk of the storage proteins comprise the hordein family and the final hordein concentration affects the quality of baked and brewed products. It is therefore important to study the accumulation of hordeins as this knowledge may assist plant breeding for improved health outcomes (by minimizing triggering of detrimental immune responses), nutrition and food processing properties.

Quantitative measurement of a candidate serum biomarker peptide derived from α2-HS-glycoprotein, and a preliminary trial of multidimensional peptide analysis in females with pregnancy-induced hypertension.

Purpose We previously attempted to develop quantitative enzyme-linked immunosorbent assay (ELISA) systems for the PDA039/044/071 peptides, potential serum disease biomarkers (DBMs) of pregnancy-induced hypertension (PIH), primarily identified by a peptidomic approach (BLOTCHIP®-mass spectrometry (MS)). However, our methodology did not extend to PDA071 (cysteinyl α2-HS-glycoprotein341-367), due to difficulty to produce a specific antibody against the peptide. The aim of the present study was to establish an alternative PDA071 quantitation system using liquid chromatography-multiple reaction monitoring (LC-MRM)/MS, to explore the potential utility of PDA071 as a DBM for PIH. Methods We tested heat/acid denaturation methods in efforts to purify serum PDA071 and developed an LC-MRM/MS method allowing for specific quantitation thereof. We measured serum PDA071 concentrations, and these results were validated including by three-dimensional (3D) plotting against PDA039 (kininogen-1439-456)/044 (kininogen-1438-456) concentrations, followed by discriminant analysis. Results PDA071 was successfully extracted from serum using a heat denaturation method. Optimum conditions for quantitation via LC-MRM/MS were developed; the assayed serum PDA071 correlated well with the BLOTCHIP® assay values. Although the PDA071 alone did not significantly differ between patients and controls, 3D plotting of PDA039/044/071 peptide concentrations and construction of a Jackknife classification matrix were satisfactory in terms of PIH diagnostic precision. Conclusions Combination analysis using both PDA071 and PDA039/044 concentrations allowed PIH diagnostic accuracy to be attained, and our method will be valuable in future pathophysiological studies of hypertensive disorders of pregnancy.

Variability Assessment of 90 Salivary Proteins in Intraday and Interday Samples from Healthy Donors by Multiple Reaction Monitoring-Mass Spectrometry.

PURPOSE: Saliva is an attractive sample source for the biomarker-based testing of several diseases, especially oral cancer. Here, we sought to apply multiplexed LC-MRM-MS to precisely quantify 90 disease-related proteins and assess their intra- and interindividual variability in saliva samples from healthy donors. EXPERIMENTAL DESIGN: We developed two multiplexed LC-MRM-MS assays for 122 surrogate peptides representing a set of disease-related proteins. Saliva samples were collected from 10 healthy volunteers at three different time points (Day 1 morning and afternoon, and Day 2 morning). Each sample was spiked with a constant amount of a 15 N-labeled protein and analyzed by MRM-MS in triplicate. Quantitative results from LC-MRM-MS were calculated by single-point quantification with reference to a known amount of internal standard (heavy peptide). RESULTS: The CVs for assay reproducibility and technical variation were 13 and 11%, respectively. The average concentrations of the 99 successfully quantified proteins ranged from 0.28 ± 0.58 ng mL-1 for profilin-2 (PFN2) to 8.55 ±8.96 µg mL-1 for calprotectin (S100A8). For the 90 proteins detectable in >50% of samples, the average CVs for intraday, interday, intraindividual, and interindividual samples were 38%, 43%, 45%, and 69%, respectively. The fluctuations of most target proteins in individual subjects were found to be within ± twofold. CONCLUSIONS AND CLINICAL RELEVANCE: Our study elucidated the intra- and interindividual variability of 90 disease-related proteins in saliva samples from healthy donors. The findings may facilitate the further development of salivary biomarkers for oral and systemic diseases.

Multiplexed Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry Quantification of Cancer Signaling Proteins.

Quantitative evaluation of protein expression across multiple cancer-related signaling pathways (e.g., Wnt/ß-catenin, TGF-ß, receptor tyrosine kinases (RTK), MAP kinases, NF-κB, and apoptosis) in tumor tissues may enable the development of a molecular profile for each individual tumor that can aid in the selection of appropriate targeted cancer therapies. Here, we describe the development of a broadly applicable protocol to develop and implement quantitative mass spectrometry assays using cell line models and frozen tissue specimens from colon cancer patients. Cell lines are used to develop peptide-based assays for protein quantification, which are incorporated into a method based on SDS-PAGE protein fractionation, in-gel digestion, and liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM/MS). This analytical platform is then applied to frozen tumor tissues. This protocol can be broadly applied to the study of human disease using multiplexed LC-MRM assays.

An isotope-labeled chemical derivatization method for the quantitation of short-chain fatty acids in human feces by liquid chromatography-tandem mass spectrometry.

Short-chain fatty acids (SCFAs) are produced by anaerobic gut microbiota in the large bowel. Qualitative and quantitative measurements of SCFAs in the intestinal tract and the fecal samples are important to understand the complex interplay between diet, gut microbiota and host metabolism homeostasis. To develop a new LC-MS/MS method for sensitive and reliable analysis of SCFAs in human fecal samples, 3-nitrophenylhydrazine (3NPH) was employed for pre-analytical derivatization to convert ten C2-C6 SCFAs to their 3-nitrophenylhydrazones under a single set of optimized reaction conditions and without the need of reaction quenching. The derivatives showed excellent in-solution chemical stability. They were separated on a reversed-phase C18 column and quantitated by negative-ion electrospray ionization - multiple-reaction monitoring (MRM)/MS. To achieve accurate quantitation, the stable isotope-labeled versions of the derivatives were synthesized in a single reaction vessel from (13)C6-3NPH, and were used as internal standard to compensate for the matrix effects in ESI. Method validation showed on-column limits of detection and quantitation over the range from low to high femtomoles for the ten SCFAs, and the intra-day and inter-day precision for determination of nine of the ten SCFAs in human fecal samples was ≤8.8% (n=6). The quantitation accuracy ranged from 93.1% to 108.4% (CVs≤4.6%, n=6). This method was used to determine the SCFA concentrations and compositions in six human fecal samples. One of the six samples, which was collected from a clinically diagnosed type 2 diabetes patient showed a significantly high molar ratio of branch-chain SCFAs to straight-chain SCFAs than the others. In summary, this work provides a new LC-MS/MS method for precise and accurate quantitation of SCFAs in human feces.

Strategies for differentiation of isobaric flavonoids using liquid chromatography coupled to electrospray ionization mass spectrometry.

Flavonoids are a class of secondary plant metabolites existing in great variety in nature. Due to this variety, identification can be difficult, especially as overlapping compounds in both chromatographic separations and mass spectrometric detection are common. Methods for distinguishing isobaric flavonoids using MS(2) and MS(3) have been developed. Chromatographic separation of various plant extracts was done with RP-HPLC and detected with positive ESI-MS operated in information-dependent acquisition (IDA) mode. Two methods for the determination of flavonoid identity and substitution pattern, both featuring IDA criteria, were used together with the HPLC equipment. A third method where the collision energy was ramped utilized direct infusion. With the developed strategies, it is possible to differentiate between many isobaric flavonoids. Various classes of flavonoids were found in all of the plant extracts, in the red onion extract 45 components were detected and for 29 of them the aglycone was characterized, while the substituents were tentatively identified for 31 of them. For the strawberry extract, those numbers were 66, 30 and 60, and for the cherry extract 99, 56 and 71. The great variety of flavonoids, several of them isobaric, found in each of the extracts highlights the need for reliable methods for flavonoid characterization. Methods capable of differentiating between most of the isobars analyzed have been developed.

Sweat: a sample with limited present applications and promising future in metabolomics.

Sweat is a biofluid with present scant use as clinical sample. This review tries to demonstrate the advantages of sweat over other biofluids such as blood or urine for routine clinical analyses and the potential when related to metabolomics. With this aim, critical discussion of sweat samplers and equipment for analysis of target compounds in this sample is made. Well established routine analyses in sweat as is that to diagnose cystic fibrosis, and the advantages and disadvantages of sweat versus urine or blood for doping control have also been discussed. Methods for analytes such as essential metals and xenometals, ethanol and electrolytes in sweat in fact constitute target metabolomics approaches or belong to any metabolomics subdiscipline such as metallomics, ionomics or xenometabolomics. The higher development of biomarkers based on genomics or proteomics as omics older than metabolomics is discussed and also the potential role of metabolomics in systems biology taking into account its emergent implementation. Normalization of the volume of sampled sweat constitutes a present unsolved shortcoming that deserves investigation. Foreseeable trends in this area are outlined.

Subunit-specific mass spectrometry method identifies haptoglobin subunit alpha as a diagnostic marker in non-small cell lung cancer.

Haptoglobin (Hp) subunits have been suggested as a potential serum marker for lung cancer. Research is intense on the application of Hp subunits to predict the cancer earlier. Nevertheless, it remains difficult to accurately measure the content of Hp subunits. We developed stable isotope dilution-multiple reaction monitoring mass spectrometry (SID-MRM-MS) capable of measuring Hp subunits (alpha and beta chains). Three isotopic analogs (NPANPVQ, TEGDGVYTLNDK and ILGGHLDAK for alpha, alpha2 and beta chain, respectively) were used as internal standard (IS) for SID-MRM-MS. Serum levels of each Hp subunit were measured in 210 clinical samples using SID-MRM-MS. A concentration ratio of each Hp subunit to total Hp was investigated. Secretion levels of alpha and beta chains were significantly increased in non-small cell lung cancer (NSCLC) compared to controls (P<0.0001). Alterations of the alpha chain ratio were more apparent than beta chain between controls and NSCLC (P=0.0001 and 0.338 for alpha and beta chains, respectively). In conclusion, this study provides not only an efficient quantitative method to determine each Hp subunit in crude sera, but also evidence that Hp alpha chain is a more prospective biomarker to diagnose NSCLC than beta chain. BIOLOGICAL SIGNIFICANCE: Recent several studies have reported Hp as a potential biomarker for diagnosis of lung cancer. However a successful evaluation of the value of Hp subunits was not achieved on clinical samples. To evaluate the diagnostic performance of each Hp subunit, the development of an accurate quantitative assay of Hp subunits is necessary. In this regard, we employed a new analytical method using stable isotope dilution-multiple reaction monitoring mass spectrometry (SID-MRM-MS), capable of measuring Hp subunits in 210 clinical specimens. In this article, we measured the Hp subunit concentrations and Hp subunits/total Hp ratios in patients with NSCLC using SID-MRM-MS. This is the first report on the evaluation of each Hp subunit as a lung cancer marker using SID-MRM-MS. Consequently, we evaluated specific three tryptic peptides (e.g. NPANPVQ, TEGDGVYTLNDK and ILGGHLDAK for alpha, alpha2 and beta chain, respectively) with high specificity and sensitivity for determination of Hp subunits. Through future large prospective cohort studies, the clinical application of Hp subunits as complementary markers, especially Hp alpha, would be useful for the diagnosis of NSCLC.