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.     

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.     

Methodological advances in the discovery of protein and peptide disease markers

The quest for biomarkers has seen a renaissance due to the application of newly developed separation methodologies and advances in biomolecular mass spectrometry. It can be argued that each disease influences the physiology of an organism and that these changes should be measurable. Many diagnostic and therapeutic decisions are supported by measurable biochemical or cellular changes in plasma, serum or urine but it is unquestionable that there is a great lack in better markers for early disease detection and prevention. In this review we cover recent developments in the areas of separation science, sample preparation and mass spectrometry as applied to biomarker discovery. We focus, in particular, on the use of LC-MS and SELDI-TOF-MS as two approaches that have seen an upswing in recent years. While validation of newly discovered biomarkers or biomarker patterns and their introduction into diagnostic practice will be a long process, it is our believe that many future diagnostic tests will be based on markers discovered through novel profiling technologies as those outlined in this article.     

Practical perspectives of personalized healthcare in oncology

There is an increasing prevalence of drug-diagnostic combinations in oncology. This has placed diagnostic stakeholders directly into the complex benefit-risk, cost, value and uncertainty-driven development paradigm traditionally the preserve of the drug development community. In this review we focus on the delivery of the clinical data required to advance such drug-diagnostic combination development programmes and ultimately satisfy regulators and payors of the value of contemporaneous changes in diagnostic and treatment practice. Ideally all stakeholders would like to initially estimate, and ultimately specify, the comparative benefit-risk for a new treatment option with and without changing diagnostic practice. Hence, in an ideal world clinical trial design is focused on acquiring biomarker treatment interaction data. In this review we describe the key scientific and feasibility inputs required to design and deliver such trials and the drivers, advantages and disadvantages associated with departing from this model. We do not discuss the discovery of new biomarkers nor the analytical validation and marketing of diagnostic products. Following on from trial design we describe how subsequent success then depends upon the concepts that guide trial design being driven into the complex world of large, multinational clinical trial delivery. For every aspect of a traditional clinical drug trial such as supply, recruitment and adherence, there is a corresponding concept for the diagnostic element. In practice, this means that each patient's contribution to the decision making data-set is subject to double jeopardy (attrition on clinical outcome and biomarker status). Historically, this has led to significantly reduced power for detecting biomarker-treatment interactions, reduced decision making confidence and a waste of valuable human and financial resources. We describe recent practice changes and experience that have led to the successful delivery of such trials focusing on both pre- and on trial aspects. The former includes the pivotal role of tissue banks in accurate estimation of evaluability and prevalence for biomarker assays and the latter several practices designed to engage and incentivize key stakeholders particularly CRAs and pathologists. The result is that in the new world of developing personalized treatments for cancer patients the real-time acquisition and monitoring of biomarker data receives similar support to that traditionally reserved for clinical outcome data and far more patients contribute to the testing of personalized medicine hypotheses.     

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.     

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.     

The advancement of biomarker-based diagnostic tools for ovarian, breast, and pancreatic cancer through the use of urine as an analytical biofluid

Despite considerable advancements, the development of effective cancer screening tools based on serum biomarker measurements has thus far failed to achieve a meaningful clinical impact. The incremental progress observed over the course of serum biomarker development suggests that further refinements based on novel approaches may yet result in a breakthrough. The use of urine as an analytical biofluid for biomarker development may represent such an approach. The unique characteristics of urine including a high level of stability, ease of sampling, and an inactive and low-complexity testing matrix offer several potential advantages over the use of serum. A number of recent reports have demonstrated the utility of urine in the identification of novel cancer biomarkers and also the improved performance of biomarkers previously evaluated in serum. In this review, advancements related to the use of urine biomarkers within the settings of ovarian, breast, and pancreatic cancer are presented and discussed. Findings regarding the identification of specific urine biomarkers for each disease are highlighted along with comparative analyses of urine and serum biomarkers as diagnostic tools.     

Modern Tumor Marker Discovery in Urology: Surface Enhanced Laser Desorption and Ionization (SELDI)

During the last two decades, biomarker research has benefited from the introduction of new proteomic analytical techniques. In this article, we review the application of surface enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectroscopy in urologic cancer research. After reviewing the literature from MEDLINE on proteomics and urologic oncology, we found that SELDI-TOF is an emerging proteomic technology in biomarker discovery that allows for rapid and sensitive analysis of complex protein mixtures. SELDI-TOF is a novel proteomic technology that has the potential to contribute further to the understanding and clinical exploitation of new, clinically relevant biomarkers.     

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.     

Proteomics approaches to urologic diseases

Biomarkers are greatly needed for several urologic diseases, such as interstitial cystitis, the symptomatic and clinical progression of benign prostate hyperplasia, as well as the specific detection of urologic cancers, including prostate and bladder cancer. This review aims to: briefly describe the need for biomarkers in the field and biomarkers that are currently available for clinicians; address the limitations and roadblocks to effective biomarker discovery; and provide examples and strategies for implementing biomarkers in clinical practice and/or drug discovery.     

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.     

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.     

Lectin capture strategies combined with mass spectrometry for the discovery of serum glycoprotein biomarkers

The application of mass spectrometry to identify disease biomarkers in clinical fluids like serum using high throughput protein expression profiling continues to evolve as technology development, clinical study design, and bioinformatics improve. Previous protein expression profiling studies have offered needed insight into issues of technical reproducibility, instrument calibration, sample preparation, study design, and supervised bioinformatic data analysis. In this overview, new strategies to increase the utility of protein expression profiling for clinical biomarker assay development are discussed with an emphasis on utilizing differential lectin-based glycoprotein capture and targeted immunoassays. The carbohydrate binding specificities of different lectins offer a biological affinity approach that complements existing mass spectrometer capabilities and retains automated throughput options. Specific examples using serum samples from prostate cancer and hepatocellular carcinoma subjects are provided along with suggested experimental strategies for integration of lectin-based methods into clinical fluid expression profiling strategies. Our example workflow incorporates the necessity of early validation in biomarker discovery using an immunoaffinity-based targeted analytical approach that integrates well with upstream discovery technologies.     

Emerging nanoproteomics approaches for disease biomarker detection: a current perspective

Availability of genome sequence of human and different pathogens has advanced proteomics research for various clinical applications. One of the prime goals of proteomics is identification and characterization of biomarkers for cancer and other fatal human diseases to aid an early diagnosis and monitor disease progression. However, rapid detection of low abundance biomarkers from the complex biological samples under clinically relevant conditions is extremely difficult, and it requires the development of ultrasensitive, robust and high-throughput technological platform. In order to overcome several technical limitations associated with sensitivity, dynamic range, detection time and multiplexing, proteomics has started integrating several emerging disciplines such as nanotechnology, which has led to the development of a novel analytical platform known as 'nanoproteomics'. Among the diverse classes of nanomaterials, the quantum dots, gold nanoparticles, carbon nanotubes and silicon nanowires are the most promising candidates for diagnostic applications. Nanoproteomics offers several advantages such as ultralow detection, short assay time, high-throughput capability and low sample consumption. In this article, we have discussed the application of nanoproteomics for biomarker discovery in various diseases with special emphasis on various types of cancer. Furthermore, we have discussed the prospects, merits and limitations of nanoproteomics.     

Immunomarkers in gynecologic cytology: the search for the ideal 'biomolecular Papanicolaou test'

Harnessing the knowledge we have gained on the cell cycle disruption caused by human papillomaviruses (HPV) will likely lead to improved screening modalities for cervical cancer and its precursors. An easily applied biomarker that has high specificity and sensitivity would represent an attractive alternative or complement to cytology and HPV testing. To date, a number of promising markers have been investigated. These include p16(INK4A), MIB-1, BD-ProEx C, and L1. Newer possibilities involve a variety of gene products associated with aberrations of chromosome 3q, such as telomerase, p63, and PIK3CA, as well the combination of biomarkers such as p16(INK4A) and MIB-1 in the same assay. Although none of them has yet been incorporated into screening algorithms or found its way into routine practice, their performance characteristics remain a focus of current investigations. This review summarizes what we know and where we hope to go in translating basic pathobiology into clinical practice.     

Challenges to developing proteomic-based breast cancer diagnostics

Over the past decade, multiple genetic and histological approaches have accelerated development of new breast cancer diagnostics and treatment paradigms. Multiple distinct genetic subtypes of breast cancers have been defined, and this has progressively led toward more personalized medicine in regard to treatment options. There still remains a deficiency in the development of molecular diagnostic assays that can be used for breast cancer detection and pretherapy clinical decisions. In particular, the type of cancer-specific biomarker typified by a serum or tissue-derived protein. Progress in this regard has been minimal, especially in comparison to the rapid advancements in genetic and histological assays for breast cancers. In this review, some potential reasons for this large gap in developing protein biomarkers will be discussed, as well as new strategies for improving these approaches. Improvements in the study design of protein biomarker discovery strategies in relation to the genetic subtypes and histology of breast cancers is also emphasized. The current successes in use of genetic and histological assays for breast cancer diagnostics are summarized, and in that context, the current limitations of the types of breast cancer-related clinical samples available for protein biomarker assay development are discussed. Based on these limitations, research strategies emphasizing identification of glycoprotein biomarkers in blood and MALDI mass spectrometry imaging of tissues are described.     

Recent advances in extracellular vesicle research for urological cancers: From technology to application

Urological malignancies, including prostate cancer, bladder cancer and kidney cancer, are major causes of morbidity and mortality worldwide. Because of the high incidence, diversity in biology, and especially direct interaction with urine, urological cancers are an important resource for both scientists and clinicians for novel diagnostic and therapeutic discovery. Extracellular vesicles (EVs) are lipid bilayer encapsulated particles released by cells into the extracellular space. Since EVs work as a safe way to transport important biological information through the whole body, they are now recognized as an important mechanism of cell–cell communication and have opened a new window for us to gain a better understanding of cancer biology, novel diagnostics, and therapeutic options. In recent years, numerous evolutions in EV technologies and novel biological and clinical findings continue to be reported in the research field of urological cancers. This comprehensive review aims to give an update of recent advances in EV technologies and summarize the state-of-the-art knowledge of EVs related to prostate cancer, bladder cancer and kidney cancer, particularly focusing on the potential of EV as biomarkers and their biological roles in promoting cancer and metastasis.     

Analytical Performance of ELISA Assays in Urine: One More Bottleneck towards Biomarker Validation and Clinical Implementation

ELISA is the main approach for the sensitive quantification of protein biomarkers in body fluids and is currently employed in clinical laboratories for the measurement of clinical markers. As such, it also constitutes the main methodological approach for biomarker validation and further qualification. For the latter, specific assay performance requirements have to be met, as described in respective guidelines of regulatory agencies. Even though many clinical ELISA assays in serum are regularly used, ELISA clinical applications in urine are significantly less. The scope of our study was to evaluate ELISA assay analytical performance in urine for a series of potential biomarkers for bladder cancer, as a first step towards their large scale clinical validation. Seven biomarkers (Secreted protein acidic and rich in cysteine, Survivin, Slit homolog 2 protein, NRC-Interacting Factor 1, Histone 2B, Proteinase-3 and Profilin-1) previously described in the literature as having differential expression in bladder cancer were included in the study. A total of 11 commercially available ELISA tests for these markers were tested by standard curve analysis, assay reproducibility, linearity and spiking experiments. The results show disappointing performance with coefficients of variation>20% for the vast majority of the tests performed. Only 3 assays (for Secreted protein acidic and rich in cysteine, Survivin and Slit homolog 2 protein) passed the accuracy thresholds and were found suitable for further application in marker quantification. These results collectively reflect the difficulties in developing urine-based ELISA assays of sufficient analytical performance for clinical application, presumably attributed to the urine matrix itself and/or presence of markers in various isoforms.     

Mass spectrometry protein tests: ready for prime time (or not)

Introduction: Mass spectrometry has played an important role in protein biomarker discovery. Yet, very few of the candidate biomarkers have been validated, and mass spectrometry-based protein tests have not made a significant inroad into clinical laboratories.

Areas covered: Offered here is a unique perspective on the future of mass spectrometry protein tests, in view of the following determinants: the true demand for such clinical tests, end-users requirements, platforms and systems design, sample preparation bottlenecks, analytical and clinical validation, and regulatory approval.

Expert commentary: Fresh thoughts and attitudes toward MS protein tests are required in order to move them toward clinical utilization and diagnostic use en masse, with critical emphasis on content, simplicity and cost. In its current format and state of the art, they are simply not ready for prime time.