Revolutionizing Precision Oncology through Collaborative Proteogenomics and Data Sharing.

The integration of proteomics into precision oncology presents opportunities that may transform the molecular analysis of cancer and accelerate basic and clinical cancer research. This Commentary discusses the importance of international collaboration and data sharing inspired by the Cancer Moonshot to accelerate the progress of multi-omic precision medicine-an approach that addresses the global diversity of people and of cancers.

Differentiating patients with psoriasis from psoriatic arthritis using collagen biomarkers.

OBJECTIVES: Around 30% of patients diagnosed with cutaneous psoriasis (PsC) will go on to develop psoriatic arthritis (PsA) which includes inflammation of the joints. Collagens are core proteins in all tissues, which are involved in the inflammatory process in both PsC and PsA. The aim of this study is to investigate collagen biomarkers and their potential use in separating the three patient groupings: PsC, PsA and healthy donors. METHODS: Healthy donors (n=41), patients with PsC (n=30) and patients with PsA (n=30) were recruited. Clinical disease parameters were recorded. Collagen remodelling was measured using ELISA immunoassays which detect the serological anabolic biomarkers quantifying formation of type I, III and IV collagen (PRO-C1, PRO-C3 and PRO-C4 respectively), and the catabolic biomarkers measuring degradation of type I, II, III, IV and X collagen (C1M, C2M, C3M, C4M and C10C respectively). RESULTS: Patients with PsC and PsA presented lower levels of PRO-C1 and C3M compared to healthy controls (p<0.05-p<0.0001), C1M was higher in PsA compared to healthy controls (p<0.0001) and C2M was all elevated in PsC and PsA compared to healthy controls (p=0.0002 and p=0.0004 respectively), reflecting alterations in the tissues. In addition, C1M was able to separate between PsC and PsA patients with an AUROC=0.664, indicating that this biomarker may be a biomarker of joint involvement. CONCLUSIONS: This work provides evidence that serum collagen biomarkers are dysregulated in PsC and PsA, as compared to healthy controls. C1M was able to differentiate patients with PsC from PsA and could be a potential biomarker of inflammatory systemic musculoskeletal involvement.

Standardized Workflow for Precise Mid- and High-Throughput Proteomics of Blood Biofluids.

BACKGROUND: Accurate discovery assay workflows are critical for identifying authentic circulating protein biomarkers in diverse blood matrices. Maximizing the commonalities in the proteomic workflows between different biofluids simplifies the approach and increases the likelihood for reproducibility. We developed a workflow that can accommodate 3 blood-based proteomes: naive plasma, depleted plasma and dried blood. METHODS: Optimal conditions for sample preparation and data independent acquisition-mass spectrometry analysis were established in plasma then automated for depleted plasma and dried blood. The mass spectrometry workflow was modified to facilitate sensitive high-throughput analysis or deeper profiling with mid-throughput analysis. Analytical performance was evaluated by the linear response of peptides and proteins to a 6- or 7-point dilution curve and the reproducibility of the relative peptide and protein intensity for 5 digestion replicates per day on 3 different days for each biofluid. RESULTS: Using the high-throughput workflow, 74% (plasma), 93% (depleted), and 87% (dried blood) displayed an inter-day CV <30%. The mid-throughput workflow had 67% (plasma), 90% (depleted), and 78% (dried blood) of peptides display an inter-day CV <30%. Lower limits of detection and quantification were determined for peptides and proteins observed in each biofluid and workflow. Based on each protein and peptide's analytical performance, we could describe the observable, reliable, reproducible, and quantifiable proteomes for each biofluid and workflow. CONCLUSION: The standardized workflows established here allows for reproducible and quantifiable detection of proteins covering a broad dynamic range. We envisage that implementation of this standard workflow should simplify discovery approaches and facilitate the translation of candidate markers into clinical use.

Proceedings of the 2020 GRAPPA Collaborative Research Network (CRN) Meeting.

At the 2020 Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)-Collaborative Research Network (CRN) annual meeting, the GRAPPA-CRN group presented a pilot investigator-initiated study protocol to test electronic case report forms (eCRFs) and proposed Standardized Operating Procedures (SOPs) to evaluate biomarkers of psoriatic arthritis (PsA) associated with axial disease. The progress on 3 studies was also presented: BioDAM PsA (Biomarkers as Predictors of structural DAMage in PsA; to validate soluble biomarkers as predictors of structural damage in PsA), PreventPsA (examining the development of PsA and risk factors among patients with psoriasis and no arthritis), and PredictORPsA (Predicting Treatment respOnse in patients with eaRly PsA; in collaboration with Pfizer using samples from the Oral Psoriatic Arthritis TriaL [OPAL], to identify biomarkers of treatment response). GRAPPA-CRN funding partnerships and applications are also underway with both the Innovative Medicines Initiative (IMI) in Europe and Accelerating Medicines Partnerships (AMP) 2.0 in the USA, and the progress of these applications and associated objectives were presented.

Research on the Human Proteome Reaches a Major Milestone: >90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project.

According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19 773 predicted proteins coded in the human genome. The HPP annually reports on progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2020-01 classified 17 874 proteins as PE1, having strong protein-level evidence, up 180 from 17 694 one year earlier. These represent 90.4% of the 19 773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), was reduced by 230 from 2129 to 1899 since the neXtProt 2019-01 release. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry data for neXtProt, supplemented this year with extensive data from MassIVE. PeptideAtlas 2020-01 added 362 canonical proteins between 2019 and 2020 and MassIVE contributed 84 more, many of which converted PE1 entries based on non-MS evidence to the MS-based subgroup. The 19 Biology and Disease-driven B/D-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions, and the progression of transitions from correlation to coexpression to causal networks after system perturbations. And the Human Protein Atlas published Blood, Brain, and Metabolic Atlases.

Clinical proteomics for prostate cancer: understanding prostate cancer pathology and protein biomarkers for improved disease management.

Following the introduction of routine Prostate Specific Antigen (PSA) screening in the early 1990's, Prostate Cancer (PCa) is often detected at an early stage. There are also a growing number of treatment options available and so the associated mortality rate is generally low. However, PCa is an extremely complex and heterogenous disease and many patients suffer disease recurrence following initial therapy. Disease recurrence commonly results in metastasis and metastatic PCa has an average survival rate of just 3-5 years. A significant problem in the clinical management of PCa is being able to differentiate between patients who will respond to standard therapies and those who may benefit from more aggressive intervention at an earlier stage. It is also acknowledged that for many men the disease is not life threatenting. Hence, there is a growing desire to identify patients who can be spared the significant side effects associated with PCa treatment until such time (if ever) their disease progresses to the point where treatment is required. To these important clinical needs, current biomarkers and clinical methods for patient stratification and personlised treatment are insufficient. This review provides a comprehensive overview of the complexities of PCa pathology and disease management. In this context it is possible to review current biomarkers and proteomic technologies that will support development of biomarker-driven decision tools to meet current important clinical needs. With such an in-depth understanding of disease pathology, the development of novel clinical biomarkers can proceed in an efficient and effective manner, such that they have a better chance of improving patient outcomes.

A robust multiplex immunoaffinity mass spectrometry assay (PromarkerD) for clinical prediction of diabetic kidney disease.

BACKGROUND: PromarkerD is a novel proteomics derived blood test for predicting diabetic kidney disease (DKD). The test is based on an algorithm that combines the measurement of three plasma protein biomarkers (CD5L, APOA4, and IBP3) with three clinical variables (age, HDL-cholesterol, and eGFR). The initial format of the assay used immunodepletion of plasma samples followed by targeted mass spectrometry (MRM-LCMS). The aim of this study was to convert the existing assay into an immunoaffinity approach compatible with higher throughput and robust clinical application. METHODS: A newly optimised immunoaffinity-based assay was developed in a 96 well format with MRM measurements made using a low-flow LCMS method. The stability, reproducibility and precision of the assay was evaluated. A direct comparison between the immunoaffinity method and the original immunodepletion method was conducted on a 100-person cohort. Subsequently, an inter-lab study was performed of the optimised immunoaffinity method in two independent laboratories. RESULTS: Processing of plasma samples was greatly simplified by switching to an immunoaffinity bead capture method, coupled to a faster and more robust microflow LCMS system. Processing time was reduced from seven to two days and the chromatography reduced from 90 to 8 min. Biomarker stability by temperature and time difference treatments passed acceptance criteria. Intra/Inter-day test reproducibility and precision were within 11% CV for all biomarkers. PromarkerD test results from the new immunoaffinity method demonstrated excellent correlation (R = 0.96) to the original immunodepletion method. The immunoaffinity assay was successfully transferred to a second laboratory (R = 0.98) demonstrating the robustness of the methodology and ease of method transfer. CONCLUSIONS: An immunoaffinity capture targeted mass spectrometry assay was developed and optimised. It showed statistically comparable results to those obtained from the original immunodepletion method and was also able to provide comparable results when deployed to an independent laboratory. Taking a research grade assay and optimising to a clinical grade workflow provides insights into the future of multiplex biomarker measurement with an immunoaffinity mass spectrometry foundation. In the current format the PromarkerD immunoaffinity assay has the potential to make a significant impact on prediction of diabetic kidney disease with consequent benefit to patients.

Aiming for Cure and Preventive Initiatives in Psoriatic Disease: Building Synergy at NPF, GRAPPA, and PPACMAN.

PURPOSE OF REVIEW: To provide a general overview of the organizations dedicated to advance clinical and translational research in the field of psoriatic disease and to describe the current and future opportunities for team science approaches to overcome unmet needs in the field. Descriptions of initiatives from the NPF, PPACMAN, and GRAPPA are summarized. RECENT FINDINGS: Program projects have recently identified areas of knowledge gaps in diagnosis, treatment, and prevention of psoriasis and psoriatic arthritis (PsA). NPF's Psoriasis Prevention Initiative aims to identify interventions that can prevent the onset and relapse of psoriatic disease or related comorbidities. The Psorcast Study is a joint venture between PPACMAN and Sage Bionetworks based on patient-generated smartphone measurements of psoriatic disease. Similarly, GRAPPA is involved in a number of projects related to axial PsA, enthesitis prevalence, and biomarker discoveries. As important initiatives bring new targets for diagnosis and therapeutics in psoriatic disease, supra-endeavors such as the NIH-Accelerating Medicines Partnership (AMP) and the European Innovative Medicines Initiative (IMI) are promising public-private partnerships that can significantly catapult the field forward.

SCREENED: A Multistage Model of Thyroid Gland Function for Screening Endocrine-Disrupting Chemicals in a Biologically Sex-Specific Manner.

Endocrine disruptors (EDs) are chemicals that contribute to health problems by interfering with the physiological production and target effects of hormones, with proven impacts on a number of endocrine systems including the thyroid gland. Exposure to EDs has also been associated with impairment of the reproductive system and incidence in occurrence of obesity, type 2 diabetes, and cardiovascular diseases during ageing. SCREENED aims at developing in vitro assays based on rodent and human thyroid cells organized in three different three-dimensional (3D) constructs. Due to different levels of anatomical complexity, each of these constructs has the potential to increasingly mimic the structure and function of the native thyroid gland, ultimately achieving relevant features of its 3D organization including: 1) a 3D organoid based on stem cell-derived thyrocytes, 2) a 3D organoid based on a decellularized thyroid lobe stromal matrix repopulated with stem cell-derived thyrocytes, and 3) a bioprinted organoid based on stem cell-derived thyrocytes able to mimic the spatial and geometrical features of a native thyroid gland. These 3D constructs will be hosted in a modular microbioreactor equipped with innovative sensing technology and enabling precise control of cell culture conditions. New superparamagnetic biocompatible and biomimetic particles will be used to produce "magnetic cells" to support precise spatiotemporal homing of the cells in the 3D decellularized and bioprinted constructs. Finally, these 3D constructs will be used to screen the effect of EDs on the thyroid function in a unique biological sex-specific manner. Their performance will be assessed individually, in comparison with each other, and against in vivo studies. The resulting 3D assays are expected to yield responses to low doses of different EDs, with sensitivity and specificity higher than that of classical 2D in vitro assays and animal models. Supporting the "Adverse Outcome Pathway" concept, proteogenomic analysis and biological computational modelling of the underlying mode of action of the tested EDs will be pursued to gain a mechanistic understanding of the chain of events from exposure to adverse toxic effects on thyroid function. For future uptake, SCREENED will engage discussion with relevant stakeholder groups, including regulatory bodies and industry, to ensure that the assays will fit with purposes of ED safety assessment. In this project review, we will briefly discuss the current state of the art in cellular assays of EDs and how our project aims at further advancing the field of cellular assays for EDs interfering with the thyroid gland.

Moving Toward Precision Medicine in Psoriasis and Psoriatic Arthritis.

Current management approaches for the treatment of psoriasis and psoriatic arthritis (PsA) are imprecise and depend largely on clinical assessment. A more precise approach, which takes into account an individual patient's variations in genes, proteins, environment, and lifestyle, is beginning to receive attention with the most advanced progress seen in the treatment of cancer. Herein, the methodological approaches required for this precision medicine approach to be adopted in psoriatic disease, as well as their advantages, are reviewed. In addition, advances that are being made to address areas of unmet need in PsA, notably the use of proteomic approaches, are presented with suggestions that combine genetic and protein data (proteogenomics). Finally, progress that is being made in 2 large-scale, multipartner studies focused on the development of a precision medicine approach to the treatment of skin psoriasis is presented and discussed.

Proceedings of the 2019 GRAPPA Collaborative Research Network Meeting.

At the 2019 Group for Research and Assessment of Psoriasis and Psoriatic Arthritis-Collaborative Research Network annual meeting, the group presented its progress in selecting a database platform; items to include in an electronic case report form (eCRF); and standardized operating procedures (SOP) for the collection, processing, storage, and transport of biomaterial. A pilot investigator-initiated study was also proposed that, in addition to addressing an area of unmet need, would allow for the testing of both the eCRF and SOP.

Progress on Identifying and Characterizing the Human Proteome: 2019 Metrics from the HUPO Human Proteome Project.

The Human Proteome Project (HPP) annually reports on progress made throughout the field in credibly identifying and characterizing the complete human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2019-01-11 contains 17 694 proteins with strong protein-level evidence (PE1), compliant with HPP Guidelines for Interpretation of MS Data v2.1; these represent 89% of all 19 823 neXtProt predicted coding genes (all PE1,2,3,4 proteins), up from 17 470 one year earlier. Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), has been reduced from 2949 to 2129 since 2016 through efforts throughout the community, including the chromosome-centric HPP. PeptideAtlas is the source of uniformly reanalyzed raw mass spectrometry data for neXtProt; PeptideAtlas added 495 canonical proteins between 2018 and 2019, especially from studies designed to detect hard-to-identify proteins. Meanwhile, the Human Protein Atlas has released version 18.1 with immunohistochemical evidence of expression of 17 000 proteins and survival plots as part of the Pathology Atlas. Many investigators apply multiplexed SRM-targeted proteomics for quantitation of organ-specific popular proteins in studies of various human diseases. The 19 teams of the Biology and Disease-driven B/D-HPP published a total of 160 publications in 2018, bringing proteomics to a broad array of biomedical research.

Molecular signature characterisation of different inflammatory phenotypes of systemic juvenile idiopathic arthritis.

OBJECTIVES: The International League of Associations for Rheumatology classification criteria define systemic juvenile idiopathic arthritis (SJIA) by the presence of fever, rash and chronic arthritis. Recent initiatives to revise current criteria recognise that a lack of arthritis complicates making the diagnosis early, while later a subgroup of patients develops aggressive joint disease. The proposed biphasic model of SJIA also implies a 'window of opportunity' to abrogate the development of chronic arthritis. We aimed to identify novel SJIA biomarkers during different disease phases. METHODS: Children with active SJIA were subgrouped clinically as systemic autoinflammatory disease with fever (SJIA syst ) or polyarticular disease (SJIA poly ). A discovery cohort of n=10 patients per SJIA group, plus n=10 with infection, was subjected to unbiased label-free liquid chromatography mass spectrometry (LC-MS/MS) and immunoassay screens. In a separate verification cohort (SJIA syst , n=45; SJIA poly , n=29; infection, n=32), candidate biomarkers were measured by multiple reaction monitoring MS (MRM-MS) and targeted immunoassays. RESULTS: Signatures differentiating the two phenotypes of SJIA could be identified. LC-MS/MS in the discovery cohort differentiated SJIA syst from SJIA poly well, but less effectively from infection. Targeted MRM verified the discovery data and, combined with targeted immunoassays, correctly identified 91% (SJIA syst vs SJIA poly ) and 77% (SJIA syst vs infection) of all cases. CONCLUSIONS: Molecular signatures differentiating two phenotypes of SJIA were identified suggesting shifts in underlying immunological processes in this biphasic disease. Biomarker signatures separating SJIA in its initial autoinflammatory phase from the main differential diagnosis (ie, infection) could aid early-stage diagnostic decisions, while markers of a phenotype switch could inform treat-to-target strategies.

Proceedings of the 2018 GRAPPA Collaborative Research Network Meeting.

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)-Collaborative Research Network (CRN) intends to launch and secure funding for 3 pilot projects related to psoriatic disease, psoriatic arthritis (PsA), and cutaneous psoriasis (PsC). The first pilot project, a PsA Biomarkers for Joint Damage (BioDAM) pilot, will seek to determine the independent predictive ability of serum biomarkers for joint damage in PsA. The second pilot project will aim to identify predictors of the development of PsA among patients with PsC. The third pilot project will aim to identify biomarkers that predict treatment response in PsA and PsC. These pilot projects will prompt the development of clinical protocols to operate across participating centers, lead to the development of standard operating procedures for the collection and transport of biosamples across international borders, and begin to establish administrative and managerial structures for the CRN. The CRN hopes that the successful completion and research outputs of these 3 pilot projects will demonstrate the CRN's value to prospective collaborators and sponsors and thereby secure sustainable longterm funding.

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.

Discovery and confirmation of a protein biomarker panel with potential to predict response to biological therapy in psoriatic arthritis.

OBJECTIVE: Biological therapies, which include antitumour necrosis factor-α and T-cell inhibitors, are potentially effective treatments for psoriatic arthritis (PsA) but are costly and may induce a number of side effects. Response to treatment in PsA is variable and difficult to predict. Here, we sought to identify a panel of protein biomarkers that could be used to predict which patients diagnosed with PsA will respond to biologic treatment. METHODS: An integrated discovery to targeted proteomics approach was used to investigate the protein profiles of good and non-responders to biological treatments in patients with PsA. Reverse-phase liquid chromatography coupled to tandem mass spectrometry was used to generate protein profiles of synovial tissue obtained at baseline from 10 patients with PsA. Targeted proteomics using multiple reaction monitoring (MRM) was used to confirm and prevalidate a potential protein biomarker panel in 18 and 7 PsA patient samples, respectively. RESULTS: A panel of 107 proteins was selected, and targeted mass spectrometry MRM assays were successfully developed for 57 of the proteins. The 57 proteins include S100-A8, S100-A10, Ig kappa chain C fibrinogen-α and γ, haptoglobin, annexin A1 and A2, collagen alpha-2, vitronectin, and alpha-1 acid glycoprotein. The proteins were measured simultaneously and confirmed to be predictive of response to treatment with an area under the curve of 0.76. In a blinded study using a separate cohort of patients, the panel was able to predict response to treatment. CONCLUSIONS: The approach reported here and the initial data provide evidence that a multiplexed protein assay of a panel of biomarkers that predict response to treatment could be developed. TRIAL REGISTRATION NUMBER: ISRCTN23328456.

Clinical translation of MS-based, quantitative plasma proteomics: status, challenges, requirements, and potential.

INTRODUCTION: Aided by the advent of advanced mass spectrometry (MS)-based technologies and methodologies, quantitative proteomics has emerged as a viable technique to capture meaningful data for candidate biomarker evaluation. To aid clinical translation, these methods generally utilize a bottom-up strategy with isotopically labeled standards and a targeted form of MS measurement. AREAS COVERED: This article reviews the status, challenges, requirements, and potential of translating current, MS-based methods to the clinical laboratory. The described methods are discussed and contrasted within a fit-for-purpose approach, while different resources for quality control, quantitative analysis, and data interpretation are additionally provided. Expert commentary: Although great strides have been made over the past five years in developing reliable quantitative assays for plasma protein biomarkers, it is crucial for investigators to have an understanding of the clinical validation process, a major roadblock in translational research. Continued progress in method design and validation of protein assays is necessary to ultimately achieve widespread adoption and regulatory approval.

Protein-Protein Interaction Detection Via Mass Spectrometry-Based Proteomics.

Analysis of protein-protein interactions is one of the mainstays of mass spectrometry-based proteomics and recent developments, which have simplified the methodology, have permitted non-specialised laboratories to adopt the approach. We introduce and review three complimentary methods which allow for the targeted, global and site-specific analysis of protein complexes. Co-precipitation of endogenous or ectopically expressed proteins and their complexes followed by proteomic analysis allows for the discovery and accurate quantification of specific protein interactions. Whereas complimentary methods, such as co-purification of entire complexes based on physico-chemical attributes, can give a snap-shot of the composition and dynamics of protein complexes on a global scale. Cross-linking on the other hand can pinpoint the amino acids involved in protein-protein interactions to such a resolution that the likely complex can be reconstructed computationally.

Proteomes, Their Compositions and Their Sources.

Biological samples of human and animal origin are utilized in research for many purposes and in a variety of scientific fields, including mass spectrometry-based proteomics. Various types of samples, including organs, tissues, cells, body fluids such as blood, plasma, cerebrospinal fluid, saliva and semen, can be collected from humans or animals and processed for proteomics analysis. Depending on the physiological state and sample origin, collected samples are used in research and diagnostics for different purposes. In mass spectrometry-based proteomics, body fluids and tissues are commonly used in discovery experiments to search for specific protein markers that can distinguish physiological from pathophysiological states, which in turn offer new diagnosis strategies and help developing new drugs to prevent disease more efficiently. Cell lines in combination with technologies such as Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) have broader application and are used frequently to investigate the mechanism of a disease or to investigate for the mechanism of a drug function. All of these are important components for defining the mechanisms of disease, discovering new pharmaceutical treatments and finally testing side effects of newly discovered drugs.

Discovery and Longitudinal Evaluation of Candidate Protein Biomarkers for Disease Recurrence in Prostate Cancer.

When compared with hormonal therapy alone, treatment with combined hormone and radiation therapy (CHRT) gives improved disease-specific survival outcomes for patients with prostate cancer; however, a significant number of CHRT patients still succumb to recurrent disease. The purpose of this study was to use longitudinal patient samples obtained as part of an ongoing noninterventional clinical trial (ICORG06-15) to identify and evaluate a potential serum protein signature of disease recurrence. Label-free LC-MS/MS based protein discovery was undertaken on depleted serum samples from CHRT patients who showed evidence of disease recurrence (n = 3) and time-matched patient controls (n = 3). A total of 104 proteins showed a significant change between these two groups. Multiple reaction monitoring (MRM) assays were designed for a subset of these proteins as part of a panel of putative prostate cancer biomarkers (41 proteins) for evaluation in longitudinal serum samples. These data revealed significant interpatient variability in individual protein expression between time of diagnosis, disease recurrence, and beyond and serve to highlight the importance of longitudinal patient samples for evaluating the use of candidate protein biomarkers in disease monitoring.