Development of a pharmaceutical hepatotoxicity biomarker panel using a discovery to targeted proteomics approach

MS1 ion current-based quantitative proteomics: A promising solution for reliable analysis of large biological cohorts

The rapidly-advancing field of pharmaceutical and clinical research calls for systematic, molecular-level characterization of complex biological systems. To this end, quantitative proteomics represents a powerful tool but an optimal solution for reliable large-cohort proteomics analysis, as frequently involved in pharmaceutical/clinical investigations, is urgently needed. Large-cohort analysis remains challenging owing to the deteriorating quantitative quality and snowballing missing data and false-positive discovery of altered proteins when sample size increases. MS1 ion current-based methods, which have become an important class of label-free quantification techniques during the past decade, show considerable potential to achieve reproducible protein measurements in large cohorts with high quantitative accuracy/precision. Nonetheless, in order to fully unleash this potential, several critical prerequisites should be met. Here we provide an overview of the rationale of MS1-based strategies and then important considerations for experimental and data processing techniques, with the emphasis on (i) efficient and reproducible sample preparation and LC separation; (ii) sensitive, selective and high-resolution MS detection; iii)accurate chromatographic alignment; (iv) sensitive and selective generation of quantitative features; and (v) optimal post-feature-generation data quality control. Prominent technical developments in these aspects are discussed. Finally, we reviewed applications of MS1-based strategy in disease mechanism studies, biomarker discovery, and pharmaceutical investigations.

Proteomics in Chronic Arthritis-Will We Finally Have Useful Biomarkers?

PURPOSE OF REVIEW

Current technical advances enable the assessment of the complex changes in body fluid proteomes and thus allow for the discovery of biomarker signatures rather than just following differences of a single marker. In this review, we aim to summarize current approaches to discover and evaluate multi-biomarker panels for improved monitoring of chronic arthritis disease activity.

RECENT FINDINGS

Mass spectrometry and affinity proteomic methodologies have been used to identify biomarker panels in synovial fluid, serum, plasma, or urine of pediatric and adult chronic arthritis patients. Notably, despite the numerous efforts to develop new and better biomarker panels, very few have undergone extensive analytical and clinical validation and been adopted into routine use for patient benefit. There remains a significant gap between discovery of chronic arthritis biomarker signatures and their validation for clinical use.

A Multiplatform Approach for the Discovery of Novel Drug-Induced Kidney Injury Biomarkers

Drug-induced kidney injury (DIKI) is a common toxicity observed in pharmaceutical development. We demonstrated the use of label-free liquid chromatography-mass spectrometry (LC-MS) and multiplex liquid chromatography-single reaction monitoring (LC-SRM) as practical extensions of standard immunoassay based safety biomarker assessments for identification of new toxicity marker candidates and for improved mechanistic understanding. Two different anticancer drugs, doxorubicin (DOX) and cisplatin (cis-diamminedichloridoplatinum, CDDP), were chosen as the toxicants due to their different modes of nephrotoxicity. Analyses of urine samples from toxicant treated and untreated rats were compared to identify biochemical analytes that changed in response to toxicant exposure. A discovery (label-free LC-MS) and targeted proteomics (multiplex LC-SRM) approach was used in combination with well established immunoassay experiments for the identification of a panel of urinary protein markers related to drug induced nephrotoxicity in rats. The initial generation of an expanded set of markers was accomplished using the label-free LC-MS discovery screen and ELISA based analysis of six nephrotoxicity biomarker proteins. Diagnostic performance of the expanded analyte set was statistically compared to conventional nephrotoxicity biomarkers. False discovery rate (FDR) analysis revealed 18 and 28 proteins from the CDDP and DOX groups, respectively, exhibiting significant differences between the vehicle and treated groups. Multiplex SRM assays were constructed to more precisely quantify candidate markers selected from the discovery screen and immunoassay experiments. To evaluate the sensitivity and specificity for each of the candidate biomarkers, histopathology severity scores were used as a benchmark for renal injury followed by receiver-operating characteristic (ROC) curve analysis on selected biomarkers. Further examination of the best performing analytes revealed relevant biological significance after consideration of anatomical localization and functional roles. In summary, the inclusion of mass spectrometry together with conventional ELISA based assays resulted in the identification of an expanded set of biomarkers with a realistic potential for providing additional beneficial information in mechanistic investigations of drug induced kidney injury and with similar responsiveness to conventionally applied indicators of renal injury.

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/β-catenin, TGF-β, 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.

Developing clinically relevant biomarkers in inflammatory arthritis: A multiplatform approach for serum candidate protein discovery

PURPOSE

To identify candidate biomarkers that have the potential to distinguish between patients with psoriatic arthritis (PsA) or rheumatoid arthritis (RA) and explore the value of combining different protein discovery platforms for the development of a multiplexed protein biomarker panel.

EXPERIMENTAL DESIGN

Serum samples from 32 patients (PsA; n = 16 and RA; n = 16) defined as active, early onset, and treatment naïve were analyzed using unbiased label-free LC-MS/MS, a microsphere bead-based immunoassay (Luminex xMAP) and an aptamer-based assay (SOMAscan).

RESULTS

LC-MS/MS was used to quantify 324 proteins, while the Luminex xMAP targeted 48 proteins and SOMAscan supported the measurement of 1129 proteins. The combined data from these techniques gave reproducible quantification of 1501 proteins in total. Of these, 42 (LC-MS/MS), 3 (Luminex xMAP), and 127 (SOMAscan) proteins were found to be differentially expressed between PsA and RA (p < 0.05).

CONCLUSION AND CLINICAL RELEVANCE

Using three different and potentially complementary proteomic platforms we identified a total of 172 proteins that are differentially expressed in patients with PsA compared to RA. These proteins collectively represent candidates for inclusion in a protein signature that could be developed as a diagnostic test to discriminate patients with PsA from RA and therefore be of clinical utility.

Subacute nicotine co-exposure has no effect on 2,2',3,5',6- pentachlorobiphenyl disposition but alters hepatic cytochrome P450 expression in the male rat

Polychlorinated biphenyls (PCBs) are metabolized by cytochrome P450 2B enzymes (CYP2B) and nicotine is reported to alter CYP2B activity in the brain and liver. To test the hypothesis that nicotine influences PCB disposition, 2,2',3,5',6-pentachlorobiphenyl (PCB 95) and its metabolites were quantified in tissues of adult male Wistar rats exposed to PCB 95 (6mg/kg/d, p.o.) in the absence or presence of nicotine (1.0mg/kg/d of the tartrate salt, s.c.) for 7 consecutive days. PCB 95 was enantioselectively metabolized to hydroxylated (OH-) PCB metabolites, resulting in a pronounced enrichment of E1-PCB 95 in all tissues investigated. OH-PCBs were detected in blood and liver tissue, but were below the detection limit in adipose, brain and muscle tissues. Co-exposure to nicotine did not change PCB 95 disposition. CYP2B1 mRNA and CYP2B protein were not detected in brain tissues but were detected in liver. Co-exposure to nicotine and PCB 95 increased hepatic CYP2B1 mRNA but did not change CYP2B protein levels relative to vehicle control animals. However, hepatic CYP2B protein in animals co-exposed to PCB 95 and nicotine were reduced compared to animals that received only nicotine. Quantification of CYP2B3, CYP3A2 and CYP1A2 mRNA identified significant effects of nicotine and PCB 95 co-exposure on hepatic CYP3A2 and hippocampal CYP1A2 transcripts. Our findings suggest that nicotine co-exposure does not significantly influence PCB 95 disposition in the rat. However, these studies suggest a novel influence of PCB 95 and nicotine co-exposure on hepatic cytochrome P450 (P450) expression that may warrant further attention due to the increasing use of e-cigarettes and related products.

Early biomarkers of joint damage in rheumatoid and psoriatic arthritis

Joint destruction, as evidenced by radiographic findings, is a significant problem for patients suffering from rheumatoid arthritis and psoriatic arthritis. Inherently irreversible and frequently progressive, the process of joint damage begins at and even before the clinical onset of disease. However, rheumatoid and psoriatic arthropathies are heterogeneous in nature and not all patients progress to joint damage. It is therefore important to identify patients susceptible to joint destruction in order to initiate more aggressive treatment as soon as possible and thereby potentially prevent irreversible joint damage. At the same time, the high cost and potential side effects associated with aggressive treatment mean it is also important not to over treat patients and especially those who, even if left untreated, would not progress to joint destruction. It is therefore clear that a protein biomarker signature that could predict joint damage at an early stage would support more informed clinical decisions on the most appropriate treatment regimens for individual patients. Although many candidate biomarkers for rheumatoid and psoriatic arthritis have been reported in the literature, relatively few have reached clinical use and as a consequence the number of prognostic biomarkers used in rheumatology has remained relatively static for several years. It has become evident that a significant challenge in the transition of biomarker candidates to clinical diagnostic assays lies in the development of suitably robust biomarker assays, especially multiplexed assays, and their clinical validation in appropriate patient sample cohorts. Recent developments in mass spectrometry-based targeted quantitative protein measurements have transformed our ability to rapidly develop multiplexed protein biomarker assays. These advances are likely to have a significant impact on the validation of biomarkers in the future. In this review, we have comprehensively compiled a list of candidate biomarkers in rheumatoid and psoriatic arthritis, evaluated the evidence for their potential as biomarkers of bone (joint) damage, and outlined how mass spectrometry-based targeted and multiplexed measurement of candidate biomarker proteins is likely to accelerate their clinical validation and the development of clinical diagnostic tests.

Application of a discovery to targeted LC-MS proteomics approach to identify deregulated proteins associated with idiosyncratic liver toxicity in a rat model of LPS/diclofenac co-administration

Increasing experimental and clinical evidence suggest a contribution of non-drug related risk factors (e.g., underlying disease, bacterial/viral infection) to idiosyncratic drug reactions (IDR). Our previous work showed that co-treatment with bacterial endotoxin (LPS) and therapeutic doses of diclofenac (Dcl), an analgesic associated with drug idiosyncrasy in patients, induced severe hepatotoxicity in rats. Here, we used an integrated discovery to targeted LC-MS proteomics approach to identify mechanistically relevant liver and plasma proteins modulated by LPS/Dcl treatment, potentially applicable as early markers for IDRs. Based on pre-screening results and their role in liver toxicity, 47 liver and 15 plasma proteins were selected for targeted LC-MS analysis. LPS alone significantly changed the levels of 19 and 3 of these proteins, respectively. T-kininogen-1, previously suggested as a marker of drug-induced liver injury, was markedly elevated in plasma after repeated Dcl treatment in the absence of hepatotoxicity, possibly indicating clinically silent stress. Dcl both alone and in combination with LPS, caused up-regulation of the ATP synthase subunits (ATP5J, ATPA, and ATPB), suggesting that Dcl may sensitize cells against additional stress factors, such as LPS through generation of mitochondrial stress. Additionally, depletion of plasma fibrinogen was observed in the co-treatment group, consistent with an increased hepatic fibrin deposition and suspected contribution of the hemostatic system to IDRs. In contrast, several proteins previously suggested as liver biomarkers, such as clusterin, did not correlate with liver injury in this model. Taken together, these analyses revealed proteomic changes in a rat model of LPS/Dcl co-administration that could offer mechanistic insight and may serve as biomarkers or safety alert for a drug's potential to cause IDRs.

DIGESTIF: a universal quality standard for the control of bottom-up proteomics experiments

In bottom-up mass spectrometry-based proteomics analyses, variability at any step of the process, particularly during sample proteolysis, directly affects the sensitivity, accuracy, and precision of peptide detection and quantification. Currently, no generic internal standards are available to control the quality of sample processing steps. This makes it difficult to assess the comparability of MS proteomic data obtained under different experimental conditions. Here, we describe the design, synthesis, and validation of a universal protein standard, called DIGESTIF, that can be added to any biological sample. The DIGESTIF standard consists of a soluble recombinant protein scaffold to which a set of 11 artificial peptides (iRT peptides) with good ionization properties has been incorporated. In the protein scaffold, the amino acids flanking iRT peptide cleavage sites were selected either to favor or hinder protease cleavage. After sample processing, the retention time and relative intensity pattern of the released iRT peptides can be used to assess the quality of sample workup, the extent of digestion, and the performance of the LC-MS system. Thus, DIGESTIF can be used to standardize a broad spectrum of applications, ranging from simple replicate measurements to large-scale biomarker screening in biomedical applications.

A review on preparative and semi-preparative offgel electrophoresis for multidimensional protein/peptide assessment

Mass spectrometry (MS) techniques are commonly used for protein identification and further analysis of selected protein spots after high resolution 2-D electrophoresis. Complementary gel-free approaches have been developed during the last few years and have shown to be useful tools in modern proteomics. The development and application of various gel-free electrophoresis devices for performing protein fractionation according to the pI differences is therefore a topic of interest. This review describes the current state of isoelectric focusing (IEF) gel-free electrophoresis based on the Agilent offgel 3100 fractionator. The review includes, therefore, (i) an overview on IEF as well as other previous IEF gel-free electrophoresis developments; (ii) offgel fundamentals and future trends; (iii) advantages and disadvantages of current offgel procedures; (iv) requirements of isolated protein pellets for further offgel fractionation; (v) offgel fraction requirements to perform the second dimensional analysis by advance electrophoresis and chromatographic techniques; and (vi) effect of the offgel operating conditions on the stability of metal-protein complexes.

Determination of selected reaction monitoring peptide transitions via multiplexed product-ion scan modes

RATIONALE

Although in silico prediction of selected reaction monitoring (SRM) peptide transitions is the most commonly used approach in quantitative proteomics, systematically detectable peptide transitions selected from actual experimental data are desirable. Here, we demonstrated the use of two triple quadrupole mass spectrometry (QqQ-MS) operation modes to identify reliable SRM peptide transitions of target peptides selected from a shotgun proteomic linear ion-trap mass spectrometry (LIT-MS) profiling dataset.

METHODS

Transition ions (Q1 and Q3 ions) of target peptides were selected from the LIT MS/MS spectra. We performed multiplexed SRM blindly for the selected transition ions of target peptides using QqQ-MS and selected peptide transitions for which the chromatographically aligned and correlated ion intensities to the corresponding fragment ions appeared in the LIT MS/MS spectra. The identities of the peptides were further confirmed by MS/MS spectra acquired via SRM-triggered MS/MS on QqQ-MS.

RESULTS

Despite the different MS platforms, we observed similar MS/MS patterns and relative ion abundance using both LIT-MS and QqQ-MS. Therefore, we were able to determine peptide transitions based on matching the chromatographic peak areas of all the selected Q3 ions of target peptides by the order of the corresponding ion intensities in the LIT MS/MS spectra. This approach demonstrated an efficient method to determine SRM peptide transitions, particularly when the target proteins are in low abundance and are therefore not easily detected by the QqQ full MS/MS scan mode. We employed this approach to determine the SRM peptide transitions of mitochondrial oxidative phosphorylation (OXPHOS) proteins involved in mitochondrial ATP synthesis.

CONCLUSIONS

The multiplexed product-ion scan mode using QqQ-MS generates systematically detectable peptide transitions in a single liquid chromatography/MS run, in which we were able to identify SRM peptides that represent known target proteins in complex biological samples. The method presented here is easy to implement and has high-throughput capabilities as a result of the short analysis time. It is therefore well suited for the design of optimal SRM experiments.

Protein Quantification by MRM for Biomarker Validation

In this chapter we describe how mass spectrometry-based quantitative protein measurements by multiple reaction monitoring (MRM) have opened up the opportunity for the assembly of large panels of candidate protein biomarkers that can be simultaneously validated in large clinical cohorts to identify diagnostic protein biomarker signatures. We outline a workflow in which candidate protein biomarker panels are initially assembled from multiple diverse sources of discovery data, including proteomics and transcriptomics experiments, as well as from candidates found in the literature. Subsequently, the individual candidates in these large panels may be prioritised by application of a range of bioinformatics tools to generate a refined panel for which MRM assays may be developed. We describe a process for MRM assay design and implementation, and illustrate how the data generated from these multiplexed MRM measurements of prioritised candidates may be subjected to a range of statistical tools to create robust biomarker signatures for further clinical validation in large patient sample cohorts. Through this overall approach MRM has the potential to not only support individual biomarker validation but also facilitate the development of clinically useful protein biomarker signatures.