Proteomic Analysis of Whole Blood Using Volumetric Absorptive Microsampling for Precision Medicine Biomarker Studies.

Microsampling of patient blood promises several benefits over conventional phlebotomy practices to facilitate precision medicine studies. These include at-home patient blood collection, supporting telehealth monitoring, minimal postcollection processing, and compatibility with nonrefrigerated transport and storage. However, for proteomic biomarker studies, mass spectrometry of whole blood has generally been avoided in favor of using plasma or serum obtained from venepuncture. We evaluated the use of a volumetric absorptive microsampling (VAMS) device as a sample preparation matrix to enable LC-MS proteomic analyses of dried whole blood. We demonstrated the detection and robust quantitation of up to 1600 proteins from single-shot shotgun-LC-MS analysis of dried whole blood, greatly enhancing proteome depth compared with conventional single-shot LC-MS analyses of undepleted plasma. Some proteins not previously reported in blood were detected using this approach. Various washing reagents were used to demonstrate that proteins can be preferentially removed from VAMS devices prior to downstream analyses. We provide a demonstration that archival frozen blood cell pellets housed under long-term storage (exceeding 5 years) are compatible with VAMS to enable quantitation of potential biomarker proteins from biobank repositories. These demonstrations are important steps in establishing viable analysis workflows to underpin large-scale precision medicine studies. Data are available via ProteomeXchange with the identifier PXD028605.

Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins.

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Pollen development in cotton (Gossypium hirsutum) is highly sensitive to heat exposure during the tetrad stage.

The development of gametes in plants is acutely susceptible to heatwaves as brief as a few days, adversely affecting pollen maturation and reproductive success. Pollen in cotton (Gossypium hirsutum) was differentially affected when tetrad and binucleate stages were exposed to heat, revealing new insights into the interaction between heat and pollen development. Squares were tagged and exposed to 36/25°C (day/night, moderate heat) or 40/30°C (day/night, extreme heat) for 5 days. Mature pollen grains and leaves were collected for physiological and proteomic responses. While photosynthetic competence was not compromised even at 40°C, leaf tissues became leakier. In contrast, pollen grains were markedly smaller after the tetrad stage was exposed to 40°C and boll production was reduced by 65%. Sugar levels in pollen grains were elevated after exposure to heat, eliminating carbohydrate deficits as a likely cause of poor reproductive capacity. Proteomic analysis of pure pollen samples revealed a particularly high abundance of 70-kDa heat shock (Hsp70s) and cytoskeletal proteins. While short-term bursts of heat had a minor impact on leaves, male gametophyte development was profoundly damaged. Cotton acclimates to maxima of 36°C at both the vegetative and reproductive stages but 5-days exposure to 40°C significantly impairs reproductive development.

Workflow for Rapidly Extracting Biological Insights from Complex, Multicondition Proteomics Experiments with WGCNA and PloGO2.

We describe a useful workflow for characterizing proteomics experiments incorporating many conditions and abundance data using the popular weighted gene correlation network analysis (WGCNA) approach and functional annotation with the PloGO2 R package, the latter of which we have extended and made available to Bioconductor. The approach can use quantitative data from labeled or label-free experiments and was developed to handle multiple files stemming from data partition or multiple pairwise comparisons. The WGCNA approach can similarly produce a potentially large number of clusters of interest, which can also be functionally characterized using PloGO2. Enrichment analysis will identify clusters or subsets of proteins of interest, and the WGCNA network topology scores will produce a ranking of proteins within these clusters or subsets. This can naturally lead to prioritized proteins to be considered for further analysis or as candidates of interest for validation in the context of complex experiments. We demonstrate the use of the package on two published data sets using two different biological systems (plant and human plasma) and proteomics platforms (sequential window acquisition of all theoretical fragment-ion spectra (SWATH) and tandem mass tag (TMT)): an analysis of the effect of drought on rice over time generated using TMT and a pediatric plasma sample data set generated using SWATH. In both, the automated workflow recapitulates key insights or observations of the published papers and provides additional suggestions for further investigation. These findings indicate that the data set analysis using WGCNA combined with the updated PloGO2 package is a powerful method to gain biological insights from complex multifaceted proteomics experiments.

iSwathX: an interactive web-based application for extension of DIA peptide reference libraries.

Summary: Large-scale peptide mass spectrometry (MS)/MS reference libraries are essential for the comprehensive analysis of data-independent acquisition (DIA) MS datasets, providing a comprehensive set of spectra for identification and quantification of proteins. We have developed a novel web-based R-package (iSwathX) for combining reference libraries that is compatible with different DIA analysis software. This open-source web GUI automates the process of normalization and combination of spectral libraries and provides a user-friendly method for performing library format conversions, analysis and visualizations, with no need for programing familiarity. Availability and implementation: iSwathX is freely accessible at https://biolinfo.shinyapps.io/iSwathX with the R-package and Shiny source code available from GitHub (https://github.com/znoor/iSwathX). Supplementary information: Supplementary data are available at Bioinformatics online.

Proteomic Responses to Drought Vary Widely Among Eight Diverse Genotypes of Rice (Oryza sativa).

Rice is a critically important food source but yields worldwide are vulnerable to periods of drought. We exposed eight genotypes of upland and lowland rice (Oryza sativa L. ssp. japonica and indica) to drought stress at the late vegetative stage, and harvested leaves for label-free shotgun proteomics. Gene ontology analysis was used to identify common drought-responsive proteins in vegetative tissues, and leaf proteins that are unique to individual genotypes, suggesting diversity in the metabolic responses to drought. Eight proteins were found to be induced in response to drought stress in all eight genotypes. A total of 213 proteins were identified in a single genotype, 83 of which were increased in abundance in response to drought stress. In total, 10 of these 83 proteins were of a largely uncharacterized function, making them candidates for functional analysis and potential biomarkers for drought tolerance.

Proteomes of Leaf-Growing Zones in Rice Genotypes with Contrasting Drought Tolerance.

Plants require a distinctive cohort of enzymes to coordinate cell division and expansion. Proteomic analysis now enables interrogation of immature leaf bases where these processes occur. Hence, proteins in tissues sampled from leaves of a drought-tolerant rice (IAC1131) are investigated to provide insights into the effect of soil drying on gene expression relative to the drought-sensitive genotype Nipponbare. Shoot growth zones are dissected to estimate the proportion of dividing cells and extract protein for subsequent tandem mass tags quantitative proteomic analysis. Gene ontology annotations of differentially expressed proteins provide insights into responses of Nipponbare and IAC1131 to drought. Soil drying does not affect the percentage of mitotic cells in IAC1131. More than 800 proteins across most functional categories increase in drought (and decrease on rewatering) in IAC1131, including proteins involved in "organizing the meristem" and "new cell formation". On the other hand, the percentage of dividing cells in Nipponbare is severely impaired during drought and fewer than 200 proteins respond in abundance when growing zones undergo a drying cycle. Remarkably, the proteomes of the growing zones of each genotype respond in a highly distinctive manner, reflecting their contrasting drought tolerance even at the earliest stages of leaf development.

Proteomics Reveals Cell-Surface Urokinase Plasminogen Activator Receptor Expression Impacts Most Hallmarks of Cancer.

While metastasis is the primary cause of colorectal cancer (CRC) mortality, the molecular mechanisms underpinning it remains elusive. Metastasis is propagated through driver oncogene/suppressor gene mutations, accompanied by passenger mutations and underlying genomic instability. To understand cancer biology, a unifying framework called the "hallmarks of cancer" (HoCs) has been developed, which organizes cell biological alterations under ten key hallmarks. Underlying these HoCs, genome instability generates mutational diversity that is amplified by inflammation. Recognizing how critical cancer cell-surface proteins influence, these HoCs have been proposed to accelerate precision medicine therapeutic development. A moderate decrease (43%↓) in HCT116 cell surface urokinase plasminogen activator receptor (uPAR) expression mitigates against many HoCs driven by these cell's KRAS and PIK3CA mutational signature. Comprehensive proteomics (whole cell lysis with two membrane protein enrichments) coupled with ingenuity pathway analysis (IPA) demonstrates that uPAR negates essential pathways across the HoC spectrum, particularly those associated with metastasis, resisting cell death, and sustaining proliferation, and parallels Cancer Hallmarks Analytics Tool analysis. Decreasing uPAR predominantly alters metastasis-related and uPAR-interactome protein expression (e.g., EGFR, caveolin, vitronectin, integrin ß4). Collectively, it is demonstrated that uPAR is a lynchpin protein capable of regulating several HoC pathways in a classical CRC mutational background.

Salt-Treated Roots of Oryza australiensis Seedlings are Enriched with Proteins Involved in Energetics and Transport.

Salinity is a major constraint on rice productivity worldwide. However, mechanisms of salt tolerance in wild rice relatives are unknown. Root microsomal proteins are extracted from two Oryza australiensis accessions contrasting in salt tolerance. Whole roots of 2-week-old seedlings are treated with 80 mM NaCl for 30 days to induce salt stress. Proteins are quantified by tandem mass tags (TMT) and triple-stage Mass Spectrometry. More than 200 differentially expressed proteins between the salt-treated and control samples in the two accessions (p-value <0.05) are found. Gene Ontology (GO) analysis shows that proteins categorized as "metabolic process," "transport," and "transmembrane transporter" are highly responsive to salt treatment. In particular, mitochondrial ATPases and SNARE proteins are more abundant in roots of the salt-tolerant accession and responded strongly when roots are exposed to salinity. mRNA quantification validated the elevated protein abundances of a monosaccharide transporter and an antiporter observed in the salt-tolerant genotype. The importance of the upregulated monosaccharide transporter and a VAMP-like protein by measuring salinity responses of two yeast knockout mutants for genes homologous to those encoding these proteins in rice are confirmed. Potential new mechanisms of salt tolerance in rice, with implications for breeding of elite cultivars are also discussed.

Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel.

BACKGROUND: One of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high-as the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood test (FOBT) have low compliance (~ 40%) and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (≥ 97%), if they can at least match the sensitivity and specificity of FOBTs. However, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin). METHODS: A combination of high abundance protein ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasma samples (i.e., pools of 20 healthy and 20 stages I-IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p < 0.05; fold-change > 1.5), and further examined with a neural network classification method using in silico augmented 5000 patient datasets. RESULTS: Ultradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, 7 candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC. CONCLUSION: MS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature.

Quantitative Age-specific Variability of Plasma Proteins in Healthy Neonates, Children and Adults.

Human blood plasma is a complex biological fluid containing soluble proteins, sugars, hormones, electrolytes, and dissolved gasses. As plasma interacts with a wide array of bodily systems, changes in protein expression, or the presence or absence of specific proteins are regularly used in the clinic as a molecular biomarker tool. A large body of literature exists detailing proteomic changes in pathologic contexts, however little research has been conducted on the quantitation of the plasma proteome in age-specific, healthy subjects, especially in pediatrics. In this study, we utilized SWATH-MS to identify and quantify proteins in the blood plasma of healthy neonates, infants under 1 year of age, children between 1-5 years, and adults. We identified more than 100 proteins that showed significant differential expression levels across these age groups, and we analyzed variation in protein expression across the age spectrum. The plasma proteomic profiles of neonates were strikingly dissimilar to the older children and adults. By extracting the SWATH data against a large human spectral library we increased protein identification more than 6-fold (940 proteins) and confirmed the concentrations of several of these using ELISA. The results of this study map the variation in expression of proteins and pathways often implicated in disease, and so have significant clinical implication.

The Art of Validating Quantitative Proteomics Data.

Western blotting as an orthogonal validation tool for quantitative proteomics data has rapidly become a de facto requirement for publication. In this viewpoint article, the pros and cons of western blotting as a validation approach are discussed, using examples from our own published work, and how to best apply it to improve the quality of data published is outlined. Further, suggestions and guidelines for some other experimental approaches are provided, which can be used for validation of quantitative proteomics data in addition to, or in place of, western blotting.

Proteomic phenotyping of metastatic melanoma reveals putative signatures of MEK inhibitor response and prognosis.

BACKGROUND: Genotyping of melanomas is used to identify patients for treatment with BRAF and MEK inhibitors, but clinical responses are highly variable. This study investigated the utility of protein expression phenotyping to provide an integrated assessment of gene expression programs in BRAF/NRAS melanoma which would be useful for prognosis and may predict response to MEK inhibition. METHODS: Mass spectrometry profiling of early passage cell lines established from Stage III cutaneous melanomas was conducted. Basal protein expression was correlated with in vitro response to the MEK inhibitor, selumetinib. Protein expression in a cohort of 32 drug naïve BRAF/NRAS metastatic melanoma specimens was examined. The prognostic utility of a subset of these proteins and mRNA transcripts from a separate cohort was determined. RESULTS: Unsupervised analysis of basal cell line protein abundances delineated response to selumetinib, but BRAF/NRAS genotype did not. Resistance was associated with functions including cell motility, cell adhesion and cytoskeletal organization. Several of these response biomarkers were observed in lymph node biospecimens and correlated with melanoma-specific survival. Loss of ICAM-1 protein and mRNA expression was a strong prognosticator of diminished survival in BRAF/NRAS mutant melanoma. CONCLUSIONS: These results demonstrate the utility of proteomic phenotyping to identify both putative biomarkers of response to MEK inhibition and prognostication associated with metastatic melanoma.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries.

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools.

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

Improving Protein Detection Confidence Using SWATH-Mass Spectrometry with Large Peptide Reference Libraries.

Protein quantification using data-independent acquisition methods such as SWATH-MS most commonly relies on spectral matching to a reference MS/MS assay library. To enable deep proteome coverage and efficient use of existing data, in silico approaches have been described to use archived or publicly available large reference spectral libraries for spectral matching. Since implicit in the use of larger libraries is the increasing likelihood of false-discoveries, new workflows are needed to ensure high confidence in protein matching under these conditions. We present a workflow which introduces a range of filters and thresholds aimed at increasing confidence that the resulting proteins are reliably detected and their quantitation is consistent and reproducible. We demonstrated the workflow using extended libraries with SWATH data from human plasma samples and yeast-spiked human K562 cell lysate digest.

Pseudomonas aeruginosa Proteome under Hypoxic Stress Conditions Mimicking the Cystic Fibrosis Lung.

Pseudomonas aeruginosa is a ubiquitous Gram-negative pathogen known to inhabit hypoxic mucus plugs of cystic fibrosis (CF) patient lungs. Despite the high prevalence and related patient mortality, the protein machinery enabling the bacterium to adapt to low oxygen environment remains to be fully elucidated. We investigated this by performing both SWATH mass spectrometry and data-dependent SPS-MS3 of TMT-labeled peptides to profile the proteomes of two P. aeruginosa CF isolates, PASS2 and PASS3, and a laboratory reference strain, PAO1, grown under hypoxic stress (O2 < 1%) in media that mimic the nutrient components of the CF lung. Quantitated across all three strains were 3967 P. aeruginosa proteins, reflecting approximately 71% of predicted ORFs in PAO1 and representing the most comprehensive proteome of clinically relevant P. aeruginosa to date. Comparative analysis revealed 735, 640, and 364 proteins were altered by 2-fold or more when comparing low oxygen to aerobic growth in PAO1, PASS2, and PASS3, respectively. Strikingly, under hypoxic stress, all strains showed concurrent increased abundance of proteins required for both aerobic (cbb3-1 and cbb3-2 terminal oxidases) and anaerobic denitrification and arginine fermentation, with the two clinical isolates showing higher relative expression of proteins in these pathways. Additionally, functional annotation revealed that clinical strains portray a unique expression profile of replication, membrane biogenesis, and virulence proteins during hypoxia which may endow these bacteria with a survival advantage. These protein profiles illuminate the diversity of P. aeruginosa mechanisms to adapt to low oxygen and shows that CF isolates initiate a robust molecular response to persist under these conditions.

Blood group antigen expression is involved in C. albicans interaction with buccal epithelial cells.

Human blood group polymorphisms are known to be determined by the expression of A, B or H antigens and the Lewis antigens. Protection against microbial infections has been associated with inheritance of polymorphisms in genes encoding and regulating the expression of ABH and Lewis antigens in bodily secretions and epithelial tissue surfaces, subsequently resulting in the presentation of different glycosylated terminal antigens on the cell surface. We investigated the role of blood group antigens in diversifying the glycosylation of buccal epithelial cells (BEC) that line the oral cavity. Specifically, we characterized and statistically evaluated the expression of histo-blood group (A, B, O) antigens on N-and O-linked glycans from BEC membrane proteins of various individuals that represented different blood group type and secretor status using a porous graphitic carbon liquid chromatography electrospray ionization mass spectrometry (PGC-LC-ESI-MS) based glycomics approach. From these BEC membrane proteins a total of 77 N-glycan and 96 O-glycan structures were structurally characterized from 19 individuals and relatively quantitated. The N-glycans from the secretor individuals did not express any A/B blood group determinants, but contained several terminal H-antigens. Apart from the non-secretors, the N-glycan profiles of BEC from all blood groups displayed similar glycan types, while varying in their relative intensities between individuals. However, multivariate analysis of the O-glycans from individuals displayed segregation patterns clearly associated with their blood group type and secretor status. In adhesion assays the oral pathogen Candida albicans showed a significantly higher interaction to blood group O type BECs relative to other blood groups.

Multiple testing corrections in quantitative proteomics: A useful but blunt tool.

Multiple testing corrections are a useful tool for restricting the FDR, but can be blunt in the context of low power, as we demonstrate by a series of simple simulations. Unfortunately, in proteomics experiments low power can be common, driven by proteomics-specific issues like small effects due to ratio compression, and few replicates due to reagent high cost, instrument time availability and other issues; in such situations, most multiple testing corrections methods, if used with conventional thresholds, will fail to detect any true positives even when many exist. In this low power, medium scale situation, other methods such as effect size considerations or peptide-level calculations may be a more effective option, even if they do not offer the same theoretical guarantee of a low FDR. Thus, we aim to highlight in this article that proteomics presents some specific challenges to the standard multiple testing corrections methods, which should be employed as a useful tool but not be regarded as a required rubber stamp.

Analytical performance of nano-LC-SRM using nondepleted human plasma over an 18-month period.

A standardized procedure for label-free nano-LC-SRM analysis of 32 high-medium abundance proteins from nondepleted human plasma was established and SRM data were acquired on 45 separate days for a control sample that was independently prepared on 39 distinct dates over an 18-month period (542 days). This case study enabled us to assess quantitative variance associated with nano-LC-SRM plasma analysis, mimicking experimental conditions that would be experienced with clinical trial biomarker studies. We assessed sample preparation variability attributed to different technicians and sample storage stability. Instrument performance varied over the 18-month period requiring ion path cleaning, so we assessed the impact of declining performance on specific peptide ion sensitivity and evaluated how various data normalization strategies could compensate for these changes. Our analysis demonstrated that while sample preparation was the main contributor for data variances when MS data were acquired within days, variability in SRM sensitivity was a far greater source of variance when data were acquired over a long period. The overall median multiplexed assay CV was 13% over the 18-month period. This case study is illustrative of large-scale plasma biomarker studies using nano-LC-SRM over extended periods and highlights aspects of bioanalysis that require careful attention to ensure reliable quantitation.