Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation

Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac rejection may offer a relevant post-transplant monitoring tool to effectively guide clinical care. The proposed computational pipeline is highly applicable to a wide range of biomarker proteomic studies.     

Protein biomarker discovery and validation: the long and uncertain path to clinical utility

Better biomarkers are urgently needed to improve diagnosis, guide molecularly targeted therapy and monitor activity and therapeutic response across a wide spectrum of disease. Proteomics methods based on mass spectrometry hold special promise for the discovery of novel biomarkers that might form the foundation for new clinical blood tests, but to date their contribution to the diagnostic armamentarium has been disappointing. This is due in part to the lack of a coherent pipeline connecting marker discovery with well-established methods for validation. Advances in methods and technology now enable construction of a comprehensive biomarker pipeline from six essential process components: candidate discovery, qualification, verification, research assay optimization, biomarker validation and commercialization. Better understanding of the overall process of biomarker discovery and validation and of the challenges and strategies inherent in each phase should improve experimental study design, in turn increasing the efficiency of biomarker development and facilitating the delivery and deployment of novel clinical tests.     

Targeted proteomics: a bridge between discovery and validation

New technologies in mass spectrometry are beginning to mature and show unique advantages for the identification and quantitation of proteins. In recent years, one of the significant goals of clinical proteomics has been to identify biomarkers that can be used for clinical diagnosis. As technology has progressed, the list of potential biomarkers has grown. However, the verification and validation of these potential biomarkers is increasingly challenging and require high-throughput quantitative assays, targeting specific candidates. Targeted proteomics bridges the gap between biomarker discovery and the development of clinically applicable biomarker assays.     

Bioinformatic-driven search for metabolic biomarkers in disease

The search and validation of novel disease biomarkers requires the complementary power of professional study planning and execution, modern profiling technologies and related bioinformatics tools for data analysis and interpretation. Biomarkers have considerable impact on the care of patients and are urgently needed for advancing diagnostics, prognostics and treatment of disease. This survey article highlights emerging bioinformatics methods for biomarker discovery in clinical metabolomics, focusing on the problem of data preprocessing and consolidation, the data-driven search, verification, prioritization and biological interpretation of putative metabolic candidate biomarkers in disease. In particular, data mining tools suitable for the application to omic data gathered from most frequently-used type of experimental designs, such as case-control or longitudinal biomarker cohort studies, are reviewed and case examples of selected discovery steps are delineated in more detail. This review demonstrates that clinical bioinformatics has evolved into an essential element of biomarker discovery, translating new innovations and successes in profiling technologies and bioinformatics to clinical application.     

Expression profiling of more than 3500 proteins of MSS-type colorectal cancer by stable isotope labeling and mass spectrometry

An efficient means of identifying protein biomarkers is essential to proper cancer management. A well-characterized proteome resource holds special promise for the discovery of novel biomarkers. However, quantification of the differences between physiological conditions together with deep down profiling has become increasingly challenging in proteomics. Here, we perform expression profiling of the colorectal cancer (CRC) proteome by stable isotope labeling and mass spectrometry. Quantitative analysis included performing mTRAQ and cICAT labeling in a pooled sample of three microsatellite stable (MSS) type CRC tissues and a pooled sample of their matched normal tissues. We identified and quantified a total of 3688 proteins. Among them, 1487 proteins were expressed differentially between normal and cancer tissues by higher than 2-fold; 1009 proteins showed increased expression in cancer tissue, whereas 478 proteins showed decreased expression. Bioinformatic analysis revealed that our data were largely consistent with known CRC relevant signaling pathways, such as the Wnt/β-catenin, caveolar-mediated endocytosis, and RAN signaling pathways. Mitochondrial dysfunction, known as the Waburg hypothesis, was also confirmed. Therefore, our data showing alterations in the proteomic profile of CRC constitutes a useful resource that may provide insights into tumor progression with later goal of identifying biologically and clinically relevant marker proteins. This article is part of a Special Issue entitled: Proteomics: The clinical link.     

Clinical application of urinary proteomics/peptidomics

The technology platforms for proteome analysis have advanced considerably over the last few years. Driven by these advancements in technology, the number of studies on the analysis of the proteome/peptidome, with the aim of defining clinically relevant biomarkers, has substantially risen. Urine has become an increasingly relevant target for clinically oriented proteome analysis; the first clinical trials based on urinary proteomics have been initiated, and studies including several hundred patients have been published. In this article, we summarize the relevant technical aspects in biomarkers discovery and the course from biomarker discovery or ‘potential’ biomarkers to those that have been validated and are clinically important. We discuss experimental design based on the statistics calculated to produce a clinically important end point. We present several examples of proteomic studies that have defined urinary biomarkers for clinical applications, focusing on capillary electrophoresis coupled to mass spectrometry as a technology. Finally, current challenges and considerations for future studies will be discussed.     

Quantification of Cardiovascular Biomarkers in Patient Plasma by Targeted Mass Spectrometry and Stable Isotope Dilution

Verification of candidate biomarkers requires specific assays to selectively detect and quantify target proteins in accessible biofluids. The primary objective of verification is to screen potential biomarkers to ensure that only the highest quality candidates from the discovery phase are taken forward into preclinical validation. Because antibody reagents for a clinical grade immunoassay often exist for a small number of candidates, alternative methodologies are required to credential new and unproven candidates in a statistically viable number of serum or plasma samples. Using multiple reaction monitoring coupled with stable isotope dilution MS, we developed quantitative, multiplexed assays in plasma for six proteins of clinical relevance to cardiac injury. The process described does not require antibodies for immunoaffinity enrichment of either proteins or peptides. Limits of detection and quantitation for each signature peptide used as surrogates for the target proteins were determined by the method of standard addition using synthetic peptides and plasma from a healthy donor. Limits of quantitation ranged from 2 to 15 ng/ml for most of the target proteins. Quantitative measurements were obtained for one to two signature peptides derived from each target protein, including low abundance protein markers of cardiac injury in the nanogram/milliliter range such as the cardiac troponins. Intra- and interassay coefficients of variation were predominantly <10 and 25%, respectively. The configured multiplex assay was then used to measure levels of these proteins across three time points in six patients undergoing alcohol septal ablation for hypertrophic obstructive cardiomyopathy. These results are the first demonstration of a multiplexed, MS-based assay for detection and quantification of changes in concentration of proteins associated with cardiac injury in the low nanogram/milliliter range. Our results also demonstrate that these assays retain the necessary precision, reproducibility, and sensitivity to be applied to novel and uncharacterized candidate biomarkers for verification of proteins in blood.Discovery of disease-specific biomarkers with diagnostic and prognostic utility has become an important challenge in clinical proteomics. In general, unbiased discovery experiments often result in the confident identification of thousands of proteins, hundreds of which may vary significantly between case and control samples in small discovery studies. However, because of the stochastic sampling of proteomes in discovery “omics” experiments, a large fraction of the protein biomarkers “discovered” in these experiments are false positives arising from biological or technical variability. Clearly discovery omics experiments do not lead to biomarkers of immediate clinical utility but rather produce candidates that must be qualified and verified in larger sample sets than were used for discovery (1).Traditional, clinical validation of biomarkers has relied primarily on immunoassays because of their specificity and sensitivity for the target analyte and high throughput capability. However, antibody reagents for a clinical grade immunoassay often only exist for a short list of candidates. The development of a reliable sandwich immunoassay for one target protein is expensive, has a long development time, and is dependent upon the generation of high quality protein antibodies. For the large majority of new, unproven candidate biomarkers, an intermediate verification technology is required that has shorter assay development time lines, lower assay cost, and effective multiplexing of dozens of candidates in low sample volumes. Ideally the approach should be capable of analyzing hundreds of samples of serum or plasma with good precision. The desired outcome of verification is a small number of highly credentialed candidates suitable for traditional preclinical and clinical validation studies.Multiple reaction monitoring (MRM)¹ coupled with stable isotope dilution (SID) MS has recently been shown to be well suited for direct quantification of proteins in plasma (2–4) and has emerged as the core technology for candidate biomarker verification. MRM assays can be highly multiplexed such that a moderate number of candidate proteins (in the range of 10–50) can be simultaneously targeted and measured in the statistically viable number of patient samples required for verification (hundreds of serum samples). However, sensitivity for unambiguous detection and quantification of proteins by MS-based assays is often constrained by sample complexity, particularly when the measurements are being made in complex fluids such as plasma.Many biomarkers of current clinical importance, such as prostate-specific antigen and the cardiac troponins, reside in the low nanogram/milliliter range in plasma and, until recently, have been inaccessible by non-antibody approaches. Our laboratory has recently shown for the first time that a combination of abundant protein depletion with limited fractionation at the peptide level prior to SID-MRM-MS provides robust limits of quantitation (LOQs) in the 1–20 ng/ml range with coefficient of variation (CV) of 10–20% at the LOQ for proteins in plasma (3).Here we demonstrate that this work flow can be extended to configure assays for a number of known markers of cardiovascular disease and, more importantly, can be deployed to measure their concentrations in clinical samples. We modeled a verification study comprising six patients undergoing alcohol septal ablation treatment for hypertrophic obstructive cardiomyopathy, a human model of “planned” myocardial infarction (PMI), and obtained targeted, quantitative measurements for moderate to low concentrations of cardiac biomarkers in plasma. This work provides additional evidence that MS-based assays can be configured and applied to verification of new protein targets for which high quality antibody reagents are not available.     

Clinical application of urinary proteomics/peptidomics

The technology platforms for proteome analysis have advanced considerably over the last few years. Driven by these advancements in technology, the number of studies on the analysis of the proteome/peptidome, with the aim of defining clinically relevant biomarkers, has substantially risen. Urine has become an increasingly relevant target for clinically oriented proteome analysis; the first clinical trials based on urinary proteomics have been initiated, and studies including several hundred patients have been published. In this article, we summarize the relevant technical aspects in biomarkers discovery and the course from biomarker discovery or 'potential' biomarkers to those that have been validated and are clinically important. We discuss experimental design based on the statistics calculated to produce a clinically important end point. We present several examples of proteomic studies that have defined urinary biomarkers for clinical applications, focusing on capillary electrophoresis coupled to mass spectrometry as a technology. Finally, current challenges and considerations for future studies will be discussed.     

Current progress in protein profiling of complex samples

Accurate cancer biomarkers are needed for early detection, disease classification, prediction of therapeutic response and monitoring treatment. While there appears to be no shortage of candidate biomarker proteins, a major bottleneck in the biomarker pipeline continues to be their verification by enzyme linked immunosorbent assays. Multiple reaction monitoring (MRM), also known as selected reaction monitoring, is a targeted mass spectrometry approach to protein quantitation and is emerging to bridge the gap between biomarker discovery and clinical validation. Highly multiplexed MRM assays are readily configured and enable simultaneous verification of large numbers of candidates facilitating the development of biomarker panels which can increase specificity. This review focuses on recent applications of MRM to the analysis of plasma and serum from cancer patients for biomarker verification. The current status of this approach is discussed along with future directions for targeted mass spectrometry in clinical biomarker validation.     

Novel molecular imaging platform for monitoring oncological kinases

Recent advances in oncology have lead to identification of a plethora of alterations in signaling pathways that are critical to oncogenesis and propagation of malignancy. Among the biomarkers identified, dysregulated kinases and associated changes in signaling cascade received the lion's share of scientific attention and have been under extensive investigations with goal of targeting them for anti-cancer therapy. Discovery of new drugs is immensely facilitated by molecular imaging technology which enables non-invasive, real time, dynamic imaging and quantification of kinase activity. Here, we review recent development of novel kinase reporters based on conformation dependent complementation of firefly luciferase to monitor kinase activity. Such reporter system provides unique insights into the pharmacokinetics and pharmacodynamics of drugs that modulate kinase signaling and have a huge potential in drug discovery, validation, and drug-target interactions.     

Biomarkers of cell death applicable to early clinical trials

The development of biomarkers of cell death to reflect tumor biology and drug-induced response has garnered interest with the development of several classes of drugs aimed at decreasing the cellular threshold for apoptosis and exploiting pre-existing oncogenic stresses. These novel anticancer drugs, directly targeted to the apoptosis regulatory machinery and aimed at abrogating survival signaling pathways, are entering early clinical trials provoking the question of how to monitor their impact on cancer patients. The parallel development of drugs with predictive biomarkers and their incorporation into early clinical trials are anticipated to support the pharmacological audit trail, to speed the development and reduce the attrition rate of novel drugs whose objective is to provoke tumor cell death. Tumor biopsies are an ideal matrix to measure apoptosis, but surrogate less invasive biomarkers such as blood samples and functional imaging are less challenging to acquire clinically. Archetypal and exploratory examples illustrating the importance of biomarkers to drug development are given. This review explores the substantive challenges associated with the validation, deployment, interpretation and utility of biomarkers of cell death and reviews recent advances in their incorporation in preclinical and early clinical trial contexts.     

Negative regulators of cell death pathways in cancer: perspective on biomarkers and targeted therapies

Cancer is a primary cause of human fatality and conventional cancer therapies, e.g., chemotherapy, are often associated with adverse side-effects, tumor drug-resistance, and recurrence. Molecularly targeted therapy, composed of small-molecule inhibitors and immunotherapy (e.g., monoclonal antibody and cancer vaccines), is a less harmful alternative being more effective against cancer cells whilst preserving healthy tissues. Drug-resistance, however, caused by negative regulation of cell death signaling pathways, is still a challenge. Circumvention of negative regulators of cell death pathways or development of predictive and response biomarkers is, therefore, quintessential. This review critically discusses the current state of knowledge on targeting negative regulators of cell death signaling pathways including apoptosis, ferroptosis, necroptosis, autophagy, and anoikis and evaluates the recent advances in clinical and preclinical research on biomarkers of negative regulators. It aims to provide a comprehensive platform for designing efficacious polytherapies including novel agents for restoring cell death signaling pathways or targeting alternative resistance pathways to improve the chances for antitumor responses. Overall, it is concluded that nonapoptotic cell death pathways are a potential research arena for drug discovery, development of novel biomarkers and targeted therapies.     

Inhibiting hypoxia-inducible factor 1 for cancer therapy

Hypoxia has long been recognized as a common feature of solid tumors and a negative prognostic factor for response to treatment and survival of cancer patients. The discovery of hypoxia-inducible factor 1 (HIF-1), a molecular determinant of the response of mammalian cells to hypoxia, has led to the identification of a "molecular target" of hypoxia suitable for the development of cancer therapeutics. Early controversy about whether or not HIF-1 is a good target for therapy has not discouraged academic groups and pharmaceutical companies from actively engaging in the discovery of small-molecule inhibitors of HIF. However, what is the best strategy to inhibit HIF and how HIF inhibitors should be developed for treatment of human cancers is still poorly defined. In this review, aspects related to the identification and early development of novel HIF inhibitors are discussed. Identification and validation of pharmacodynamic end points relevant to the HIF-1 pathway is essential for a rational development of HIF inhibitors. Integration of these biomarkers in early clinical trials may provide valuable information to determine the contribution of HIF inhibitors to response to therapy. Finally, HIF inhibitors should be incorporated in combination strategies to effectively target multiple cellular components of the tumor microenvironment and redundant signaling pathways frequently deregulated in human cancer.     

Challenges in translating plasma proteomics from bench to bedside: update from the NHLBI Clinical Proteomics Programs

The emerging scientific field of proteomics encompasses the identification, characterization, and quantification of the protein content or proteome of whole cells, tissues, or body fluids. The potential for proteomic technologies to identify and quantify novel proteins in the plasma that can function as biomarkers of the presence or severity of clinical disease states holds great promise for clinical use. However, there are many challenges in translating plasma proteomics from bench to bedside, and relatively few plasma biomarkers have successfully transitioned from proteomic discovery to routine clinical use. Key barriers to this translation include the need for "orthogonal" biomarkers (i.e., uncorrelated with existing markers), the complexity of the proteome in biological samples, the presence of high abundance proteins such as albumin in biological samples that hinder detection of low abundance proteins, false positive associations that occur with analysis of high dimensional datasets, and the limited understanding of the effects of growth, development, and age on the normal plasma proteome. Strategies to overcome these challenges are discussed.     

Evaluating the effects of preanalytical variables on the stability of the human plasma proteome

High quality clinical biospecimens are vital for biomarker discovery, verification, and validation. Variations in blood processing and handling can affect protein abundances and assay reliability. Using an untargeted LC-MS approach, we systematically measured the impact of preanalytical variables on the plasma proteome. Time prior to processing was the only variable that affected the plasma protein levels. LC-MS quantification showed that preprocessing times <6 h had minimal effects on the immunodepleted plasma proteome, but by 4 days significant changes were apparent. Elevated levels of many proteins were observed, suggesting that in addition to proteolytic degradation during the preanalytical phase, changes in protein structure are also important considerations for protocols using antibody depletion. As to processing variables, a comparison of single- vs double-spun plasma showed minimal differences. After processing, the impact ?3 freeze–thaw cycles was negligible regardless of whether freshly collected samples were processed in short succession or the cycles occurred during 14–17 years of frozen storage (−80 °C). Thus, clinical workflows that necessitate modest delays in blood processing times or employ different centrifugation steps can yield valuable samples for biomarker discovery and verification studies.     

Urine as a source for clinical proteome analysis: From discovery to clinical application

The success of clinical proteome analysis should be assessed based on the clinical impact following implementation of findings. Although there have been several technological advancements in mass spectrometry in the last years, these have not resulted in similar advancements in clinical proteomics. In addition, application of proteomic biomarkers in clinical diagnostics and practical improvement in the disease management is extremely rare. In this review, we discuss the relevant issues associated with identification of robust biomarkers of clinical value. Urine appears to be an ideal source of biomarkers, for theoretical, methodological, and practical reasons. Therefore, this review is focused on the search for biomarkers in urine within the last decade. Urine can be used for non-invasive assessment of a variety of diseases including those affecting the urogenital tract and also other pathologies such as cardiovascular disease or appendicitis. We also discuss the importance of data validation, an essential step in translating biomarkers into the clinical practice. Furthermore, we examine several examples of apparently successful proteomic biomarker discovery studies and their implications for disease diagnosis, prognosis, and therapy evaluation. We also discuss some current challenges in this field and reflect on future research prospects. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Proteomic contributions to personalized cancer care

Cancer impacts each patient and family differently. Our current understanding of the disease is primarily limited to clinical hallmarks of cancer, but many specific molecular mechanisms remain elusive. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies that improve patient prognosis are not widely available for most cancers. Individualized care plans, also described as personalized medicine, still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics holds great promise in contributing to the prevention and cure of cancer because it provides unique tools for discovery of biomarkers and therapeutic targets. As such, proteomics can help translate basic science discoveries into the clinical practice of personalized medicine. Here we describe how biological mass spectrometry and proteome analysis interact with other major patient care and research initiatives and present vignettes illustrating efforts in discovery of diagnostic biomarkers for ovarian cancer, development of treatment strategies in lung cancer, and monitoring prognosis and relapse in multiple myeloma patients.     

Predictive markers in early research and companion diagnostic developments in oncology

Predictive biomarkers are discovered and used in oncology research to formulate hypotheses aimed at the identification of patients benefiting from specific therapeutic intervention(s). They pave the way to the development of companion diagnostic tests which are tools readily implemented in the clinic and serve to qualify a patient for treatment with a particular targeted drug or the continued use of a particular drug, thus maximizing the benefit to risk ratio of the medical intervention to the patient. Predictive biomarkers are defined by biological characteristics of the patient's or tumor status that can be measured objectively and correlated with clinical outcome: these can be molecular, cellular or biochemical features. Predictive markers need extensive analytical validation - specific for the tool utilized for their assessment - as well as rigorous clinical qualification in the context of the drug treatment for which they define clinical utility. The process of companion diagnostic development is a highly interdisciplinary and complex one, driven by key crucial milestones and accompanying the same and typical process of a whole drug discovery and development continuum, from marker discovery and validation, assay development, clinical qualification until test approval and commercialization.     

Biomarker discovery in biological fluids

Discovery of novel protein biomarkers is essential for successful drug discovery and development. These novel protein biomarkers may aid accelerated drug efficacy, response, or toxicity decision making based on their enhanced sensitivity and/or specificity. These biomarkers, if necessary, could eventually be converted into novel diagnostic marker assays. Proteomic platforms developed over the past few years have given us the ability to rapidly identify novel protein biomarkers in various biological matrices from cell cultures (lysates, supernatants) to human clinical samples (serum, plasma, and urine). In this article, we delineate an approach to biomarker discovery. This approach is divided into three steps, (i) identification of markers, (ii) prioritization of identified markers, and (iii) preliminary validation (qualification) of prioritized markers. Using drug-induced idiosyncratic hepatotoxicity as a case study, the article elaborates methods and techniques utilized during the three steps of biomarker discovery process. The first step involves identification of markers using multi-dimensional protein identification technology. The second step involves prioritization of a subset of marker candidates based on several criteria such as availability of reagent set for assay development and literature association to disease biology. The last step of biomarker discovery involves development of preliminary assays to confirm the bio-analytical measurements from the first step, as well as qualify the marker(s) in pre-clinical models, to initiate future marker validation and development.