Absolute Quantification of Apolipoproteins Following Treatment with Omega-3 Carboxylic Acids and Fenofibrate Using a High Precision Stable Isotope-labeled Recombinant Protein Fragments Based SRM Assay

The Circulating Proteome─Technological Developments, Current Challenges, and Future Trends

Recent improvements in proteomics technologies have fundamentally altered our capacities to characterize human biology. There is an ever-growing interest in using these novel methods for studying the circulating proteome, as blood offers an accessible window into human health. However, every methodological innovation and analytical progress calls for reassessing our existing approaches and routines to ensure that the new data will add value to the greater biomedical research community and avoid previous errors. As representatives of HUPO's Human Plasma Proteome Project (HPPP), we present our 2024 survey of the current progress in our community, including the latest build of the Human Plasma Proteome PeptideAtlas that now comprises 4608 proteins detected in 113 data sets. We then discuss the updates of established proteomics methods, emerging technologies, and investigations of proteoforms, protein networks, extracellualr vesicles, circulating antibodies and microsamples. Finally, we provide a prospective view of using the current and emerging proteomics tools in studies of circulating proteins.

Orthogonal proteomics methods warrant the development of Duchenne muscular dystrophy biomarkers

BACKGROUND

Molecular components in blood, such as proteins, are used as biomarkers to detect or predict disease states, guide clinical interventions and aid in the development of therapies. While multiplexing proteomics methods promote discovery of such biomarkers, their translation to clinical use is difficult due to the lack of substantial evidence regarding their reliability as quantifiable indicators of disease state or outcome. To overcome this challenge, a novel orthogonal strategy was developed and used to assess the reliability of biomarkers and analytically corroborate already identified serum biomarkers for Duchenne muscular dystrophy (DMD). DMD is a monogenic incurable disease characterized by progressive muscle damage that currently lacks reliable and specific disease monitoring tools.

METHODS

Two technological platforms are used to detect and quantify the biomarkers in 72 longitudinally collected serum samples from DMD patients at 3 to 5 timepoints. Quantification of the biomarkers is achieved by detection of the same biomarker fragment either through interaction with validated antibodies in immuno-assays or through quantification of peptides by Parallel Reaction Monitoring Mass Spectrometry assay (PRM-MS).

RESULTS

Five, out of ten biomarkers previously identified by affinity-based proteomics methods, were confirmed to be associated with DMD using the mass spectrometry-based method. Two biomarkers, carbonic anhydrase III and lactate dehydrogenase B, were quantified with two independent methods, sandwich immunoassays and PRM-MS, with Pearson correlations of 0.92 and 0.946 respectively. The median concentrations of CA3 and LDHB in DMD patients was elevated in comparison to those in healthy individuals by 35- and 3-fold, respectively. Levels of CA3 vary between 10.26 and 0.36 ng/ml in DMD patients whereas those of LDHB vary between 15.1 and 0.8 ng/ml.

CONCLUSIONS

These results demonstrate that orthogonal assays can be used to assess the analytical reliability of biomarker quantification assays, providing a means to facilitate the translation of biomarkers to clinical practice. This strategy also warrants the development of the most relevant biomarkers, markers that can be reliably quantified with different proteomics methods.

Targeted proteomics using stable isotope labeled protein fragments enables precise and robust determination of total apolipoprotein(a) in human plasma

Lipoprotein(a), also known as Lp(a), is an LDL-like particle composed of apolipoprotein(a) (apo(a)) bound covalently to apolipoprotein B100. Plasma concentrations of Lp(a) are highly heritable and vary widely between individuals. Elevated plasma concentration of Lp(a) is considered as an independent, causal risk factor of cardiovascular disease (CVD). Targeted mass spectrometry (LC-SRM/MS) combined with stable isotope-labeled recombinant proteins provides robust and precise quantification of proteins in the blood, making LC-SRM/MS assays appealing for monitoring plasma proteins for clinical implications. This study presents a novel quantitative approach, based on proteotypic peptides, to determine the absolute concentration of apo(a) from two microliters of plasma and qualified according to guideline requirements for targeted proteomics assays. After optimization, assay parameters such as linearity, lower limits of quantification (LLOQ), intra-assay variability (CV: 4.7%) and inter-assay repeatability (CV: 7.8%) were determined and the LC-SRM/MS results were benchmarked against a commercially available immunoassay. In summary, the measurements of an apo(a) single copy specific peptide and a kringle 4 specific peptide allow for the determination of molar concentration and relative size of apo(a) in individuals.

Addressing the Protease Bias in Quantitative Proteomics

Protein quantification strategies using multiple proteases have been shown to deliver poor interprotease accuracy in label-free mass spectrometry experiments. By utilizing six different proteases with different cleavage sites, this study explores the protease bias and its effect on accuracy and precision by using recombinant protein standards. We established 557 SRM assays, using a recombinant protein standard resource, toward 10 proteins in human plasma and determined their concentration with multiple proteases. The quantified peptides of these plasma proteins spanned 3 orders of magnitude (0.02–70 μM). In total, 60 peptides were used for absolute quantification and the majority of the peptides showed high robustness. The retained reproducibility was achieved by quantifying plasma proteins using spiked stable isotope standard recombinant proteins in a targeted proteomics workflow.

Proteomics in thrombosis research

A State of the Art lecture titled “Proteomics in Thrombosis Research” was presented at the ISTH Congress in 2021. In clinical practice, there is a need for improved plasma biomarker‐based tools for diagnosis and risk prediction of venous thromboembolism (VTE). Analysis of blood, to identify plasma proteins with potential utility for such tools, could enable an individualized approach to treatment and prevention. Technological advances to study the plasma proteome on a large scale allows broad screening for the identification of novel plasma biomarkers, both by targeted and nontargeted proteomics methods. However, assay limitations need to be considered when interpreting results, with orthogonal validation required before conclusions are drawn. Here, we review and provide perspectives on the application of affinity‐ and mass spectrometry‐based methods for the identification and analysis of plasma protein biomarkers, with potential application in the field of VTE. We also provide a future perspective on discovery strategies and emerging technologies for targeted proteomics in thrombosis research. Finally, we summarize relevant new data on this topic, presented during the 2021 ISTH Congress.

Targeted proteomics analysis of plasma proteins using recombinant protein standards for addition only workflows

Targeted proteomics is an attractive approach for the analysis of blood proteins. Here, we describe a novel analytical platform based on isotope-labeled recombinant protein standards stored in a chaotropic agent and subsequently dried down to allow storage at ambient temperature. This enables a straightforward protocol suitable for robotic workstations. Plasma samples to be analyzed are simply added to the dried pellet followed by enzymatic treatment and mass spectrometry analysis. Here, we show that this approach can be used to precisely (coefficient of variation <10%) determine the absolute concentrations in human plasma of hundred clinically relevant protein targets, spanning four orders of magnitude, using simultaneous analysis of 292 peptides. The use of this next-generation analytical platform for high-throughput clinical proteome profiling is discussed.

Development of an antibody-free ID-LC MS method for the quantification of procalcitonin in human serum at sub-microgram per liter level using a peptide-based calibration

The quantification of low abundant proteins in complex matrices by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) remains challenging. A measurement procedure based on optimized antibody-free sample preparation and isotope dilution coupled to LC-MS/MS was developed to quantify procalcitonin (PCT) in human serum at sub-microgram per liter level. A combination of sodium deoxycholate-assisted protein precipitation with acetonitrile, solid-phase extraction, and trypsin digestion assisted with Tween-20 enhanced the method sensitivity. Linearity was established through peptide-based calibration curves in the serum matrix (0.092-5.222 μg/L of PCT) with a good linear fit (R2 ≥ 0.999). Quality control materials spiked with known amounts of protein-based standards were used to evaluate the method's accuracy. The bias ranged from -2.6 to +4.3%, and the intra-day and inter-day coefficients of variations (CVs) were below 2.2% for peptide-based quality controls. A well-characterized correction factor was determined and applied to compensate for digestion incompleteness and material loss before the internal standards spike. Results with metrological traceability to the SI units were established using standard peptide of well-characterized purity determined by peptide impurity corrected amino acid analysis. The validated method enables accurate quantification of PCT in human serum at a limit of quantification down to 0.245 μg/L (bias -1.9%, precision 9.1%). The method was successfully applied to serum samples obtained from patients with sepsis. Interestingly, the PCT concentration reported implementing the isotope dilution LC-MS/MS method was twofold lower than the concentration provided by an immunoassay.

Detailed Method for Performing the ExSTA Approach in Quantitative Bottom-Up Plasma Proteomics

The use of stable isotope-labeled standards (SIS) is an analytically valid means of quantifying proteins in biological samples. The nature of the labeled standards and their point of insertion in a bottom-up proteomic workflow can vary, with quantification methods utilizing curves in analytically sound practices. A promising quantification strategy for low sample amounts is external standard addition (ExSTA). In ExSTA, multipoint calibration curves are generated in buffer using serially diluted natural (NAT) peptides and a fixed concentration of SIS peptides. Equal concentrations of SIS peptides are spiked into experimental sample digests, with all digests (control and experimental) subjected to solid-phase extraction prior to liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. Endogenous peptide concentrations are then determined using the regression equation of the standard curves. Given the benefits of ExSTA in large-scale analysis, a detailed protocol is provided herein for quantifying a multiplexed panel of 125 high-to-moderate abundance proteins in undepleted and non-enriched human plasma samples. The procedural details and recommendations for successfully executing all phases of this quantification approach are described. As the proteins have been putatively correlated with various noncommunicable diseases, quantifying these by ExSTA in large-scale studies should help rapidly and precisely assess their true biomarker efficacy.

Inflammation and Apolipoproteins Are Potential Biomarkers for Stratification of Cutaneous Melanoma Patients for Immunotherapy and Targeted Therapy

Malignant cutaneous melanoma is one of the most common cancers in young adults. During the last decade, targeted and immunotherapies have significantly increased the overall survival of patients with malignant cutaneous melanoma. Nevertheless, disease progression is common, and a lack of predictive biomarkers of patient response to therapy hinders individualized treatment strategies. To address this issue, we performed a longitudinal study using an unbiased proteomics approach to identify and quantify proteins in plasma both before and during treatment from 109 patients treated with either targeted or immunotherapy. Linear modeling and machine learning approaches identified 43 potential prognostic and predictive biomarkers. A reverse correlation between apolipoproteins and proteins related to inflammation was observed. In the immunotherapy group, patients with low pretreatment expression of apolipoproteins and high expression of inflammation markers had shorter progression-free survival. Similarly, increased expression of LDHB during treatment elicited a significant impact on response to immunotherapy. Overall, we identified potential common and treatment-specific biomarkers in malignant cutaneous melanoma, paving the way for clinical use of these biomarkers following validation on a larger cohort. SIGNIFICANCE: This study identifies a potential biomarker panel that could improve the selection of therapy for patients with cutaneous melanoma.

Mass Spectrometry-Based Assay for Targeting Fifty-Two Proteins of Brain Origin in Cerebrospinal Fluid

Cerebrospinal fluid (CSF) is a circulatory fluid of the central nervous system and it can reflect the biochemical changes occurring in the brain. Although CSF retrieval through lumbar puncture is invasive, it remains the most commonly used fluid in exploring brain pathology as it is less complex and contains a higher concentration of brain-derived proteins than plasma (Reiber, H. Clin. Chim. Acta 2001, 310, 173-186; Macron et al. J. Proteome Res. 2018, 17, 4315-4319). We hypothesize that proteins produced by the brain will have diagnostic significance for brain pathologies. Hence, we expanded the previously in-house-developed 31-protein panel with more proteins classified as brain-specific by the Human Protein Atlas (HPA). Using the HPA, we selected 76 protein coding genes and screened CSF using liquid chromatography-mass spectrometry (LC-MS) and narrowed the protein list to candidates identified endogenously in CSF. Next, we developed a parallel reaction monitoring (PRM) assay for the 21 new proteins and merged it with the 31-protein assay developed earlier. In the process, we evaluated different screening strategies and optimized MS collision energies and ion isolation windows to achieve the highest possible analyte signal resulting in the PRM assay with an average linear dynamic range of 4.3 × 10³. We also assessed the extent of Asn (N)-Gln (Q) deamidation, N-terminal pyro-Glu (E) conversion, and Met (M) oxidation and found that deamidation can be misassigned without high mass accuracy and high-resolution settings. We also assessed how many of these proteins could be reliably measured in 10 individual patient CSF samples. Our approach allows us to measure the relative levels of 52 brain-derived proteins in CSF by a single LC-MS method. This new assay may have important applications in discovering CSF biomarkers for various neurological diseases.