The failure of protein cancer biomarkers to reach the clinic: why, and what can be done to address the problem?

Diagnosis: From classification to prediction

Over the last two decades diagnostic labels have increasingly been sub-divided based on molecular and genetic 'signatures'. But this emphasis on disease sub-types defined in molecular terms, elides the central role of population-based predictive technologies in determining these new diagnoses. While molecular diagnostic sub-types might flow from the laboratory, the clinical validity of every putative diagnostic category must ultimately be tested against its predictive powers. In effect, the former logic of prognosis following diagnosis is reversed. This paper explores the emergence of this new method of diagnostic practice over the last half century.

Improved Sensitivity for Protein Turnover Quantification by Monitoring Immonium Ion Isotopologue Abundance

We describe an analytical strategy allowing for the direct quantification of stable isotope label incorporation in newly synthesized proteins following administration of the stable isotope tracer deuterium oxide. We present a demonstration of coupling high-resolution mass spectrometry, metabolic stable isotope labeling, and MS/MS-based isotopologue quantification for the measurement of protein turnover. Stable isotope labeling with deuterium oxide, followed by immonium ion isotopologue quantification, is a more sensitive strategy for determining protein fractional synthesis rates compared to peptide centric mass isotopomer distribution analysis approaches when labeling time and/or stable isotope tracer exposure is limited and, as such, offers a great advantage for human studies.

Ultra-Sensitive TP53 Sequencing for Cancer Detection Reveals Progressive Clonal Selection in Normal Tissue over a Century of Human Lifespan

High-accuracy next-generation DNA sequencing promises a paradigm shift in early cancer detection by enabling the identification of mutant cancer molecules in minimally invasive body fluid samples. We demonstrate 80% sensitivity for ovarian cancer detection using ultra-accurate Duplex Sequencing to identify TP53 mutations in uterine lavage. However, in addition to tumor DNA, we also detect low-frequency TP53 mutations in nearly all lavages from women with and without cancer. These mutations increase with age and share the selection traits of clonal TP53 mutations commonly found in human tumors. We show that low-frequency TP53 mutations exist in multiple healthy tissues, from newborn to centenarian, and progressively increase in abundance and pathogenicity with older age across tissue types. Our results illustrate that subclonal cancer evolutionary processes are a ubiquitous part of normal human aging, and great care must be taken to distinguish tumor-derived from age-associated mutations in high-sensitivity clinical cancer diagnostics.

Epigenetic IVD Tests for Personalized Precision Medicine in Cancer

Epigenetic alterations play a key role in the initiation and progression of cancer. Therefore, it is possible to use epigenetic marks as biomarkers for predictive and precision medicine in cancer. Precision medicine is poised to impact clinical practice, patients, and healthcare systems. The objective of this review is to provide an overview of the epigenetic testing landscape in cancer by examining commercially available epigenetic-based in vitro diagnostic tests for colon, breast, cervical, glioblastoma, lung cancers, and for cancers of unknown origin. We compile current commercial epigenetic tests based on epigenetic biomarkers (i.e., DNA methylation, miRNAs, and histones) that can actually be implemented into clinical practice.

Shortcomings in the evaluation of biomarkers in ovarian cancer: a systematic review

Background

Shortcomings in study design have been hinted at as one of the possible causes of failures in the translation of discovered biomarkers into the care of ovarian cancer patients, but systematic assessments of biomarker studies are scarce. We aimed to document study design features of recently reported evaluations of biomarkers in ovarian cancer.

Methods

We performed a systematic search in PubMed (MEDLINE) for reports of studies evaluating the clinical performance of putative biomarkers in ovarian cancer. We extracted data on study designs and characteristics.

Results

Our search resulted in 1026 studies; 329 (32%) were found eligible after screening, of which we evaluated the first 200. Of these, 93 (47%) were single center studies. Few studies reported eligibility criteria (17%), sampling methods (10%) or a sample size justification or power calculation (3%). Studies often used disjoint groups of patients, sometimes with extreme phenotypic contrasts; 46 studies included healthy controls (23%), but only five (3%) had exclusively included advanced stage cases.

Conclusions

Our findings confirm the presence of suboptimal features in clinical evaluations of ovarian cancer biomarkers. This may lead to premature claims about the clinical value of these markers or, alternatively, the risk of discarding potential biomarkers that are urgently needed.

Prognostic and Predictive Immunohistochemistry-Based Biomarkers in Cancer and Immunotherapy

Immunotherapy has drastically improved the prognosis of many patients with cancer, but it can also lead to severe immune-related adverse events. Biomarkers, which are molecular markers that indicate a patient's disease outcome or a patient's response to treatment, are therefore crucial to helping clinicians weigh the potential benefits of immunotherapy against its potential toxicities. Immunohistochemistry (IHC) has thus far been a powerful technique for discovery and use of biomarkers such as CD8+ tumor-infiltrating lymphocytes. However, IHC has limited reproducibility. Thus, if more IHC-based biomarkers are to reach the clinic, refinement of the technique using multiplexing or automation is key.

Benefits and harms of wellness initiatives

Wellness projects are large scale studies of healthy individuals through extensive laboratory and other testing. The “Hundred Person Wellness Study”, was one of the first to report results and lessons from its approach and these lessons can be applied to other wellness projects which are being undertaken by major companies and other organizations. In the “Hundred Person Wellness Study”, investigators from the Institute for Systems Biology (ISB) sequenced the genome, and analyzed the blood, saliva, urine and microbiome of 108 healthy participants every 3 months, for 9 months, to look for subtle changes signifying the transition to disease. We discuss some of the possible shortcomings of this approach; questioning the need to “improve” biomarker levels, excessive testing leading to over-diagnosis and over-treatment, expected results and improvements, selection of tests, problems with whole genome sequencing and speculations on therapeutic measures. We hope this discussion will lead to a continued evaluation of wellness interventions, leading to strategies that truly benefit patients within the constraint of limited health care resources.

Tissue-infiltrating immune cells as prognostic markers in oral squamous cell carcinoma: a systematic review and meta-analysis

Background

Various immune cells have been suggested as prognostic markers for cancer patients. In this article, we present a systematic review and meta-analysis of studies assessing the prognostic value of tissue-infiltrating immune cells in oral cancer and discuss the reporting quality of these studies.

Methods

We performed a systematic literature search and included studies using immunohistochemistry and survival analysis to assess the prognostic value of tumour-infiltrating T cells, B cells, macrophages, dendritic cells, mast cells and natural killer cells in oral cancer. We performed meta-analysis of studies providing necessary statistical data and investigated the studies’ adherence to the REporting recommendations for tumour MARKer prognostic studies (REMARK) guidelines.

Results

Of the 1960 articles identified, 33 were eligible for this systematic review and 8 were included in the meta-analysis. CD163+ M2 macrophages and CD57+ natural killer cells were the most promising predictors of survival in oral cancer patients. Many studies lacked important information on their design and conduct.

Conclusion

Deficiencies in the reporting of study design and conduct make it difficult to draw reliable conclusions about the suggested markers. The prognostic value of CD163+ M2 macrophages and CD57+ natural killer cells should be validated in large, standardised studies.

An Integrative Data Mining and Omics-Based Translational Model for the Identification and Validation of Oncogenic Biomarkers of Pancreatic Cancer

Substantial alterations at the multi-omics level of pancreatic cancer (PC) impede the possibility to diagnose and treat patients in early stages. Herein, we conducted an integrative omics-based translational analysis, utilizing next-generation sequencing, transcriptome meta-analysis, and immunohistochemistry, combined with statistical learning, to validate multiplex biomarker candidates for the diagnosis, prognosis, and management of PC. Experiment-based validation was conducted and supportive evidence for the essentiality of the candidates in PC were found at gene expression or protein level by practical biochemical methods. Remarkably, the random forests (RF) model exhibited an excellent diagnostic performance and LAMC2, ANXA2, ADAM9, and APLP2 greatly influenced its decisions. An explanation approach for the RF model was successfully constructed. Moreover, protein expression of LAMC2, ANXA2, ADAM9, and APLP2 was found correlated and significantly higher in PC patients in independent cohorts. Survival analysis revealed that patients with high expression of ADAM9 (Hazard ratio (HR)_OS = 2.2, p-value < 0.001), ANXA2 (HR_OS = 2.1, p-value < 0.001), and LAMC2 (HR_DFS = 1.8, p-value = 0.012) exhibited poorer survival rates. In conclusion, we successfully explore hidden biological insights from large-scale omics data and suggest that LAMC2, ANXA2, ADAM9, and APLP2 are robust biomarkers for early diagnosis, prognosis, and management for PC.

Healthy human serum N-glycan profiling reveals the influence of ethnic variation on the identified cancer-relevant glycan biomarkers

Background

Most glycomics studies have focused on understanding disease mechanisms and proposing serum markers for various diseases, yet the influence of ethnic variation on the identified glyco-biomarker remains poorly addressed. This study aimed to investigate the inter-ethnic serum N-glycan variation among US origin control, Japanese, Indian, and Ethiopian healthy volunteers.

Methods

Human serum from 54 healthy subjects of various ethnicity and 11 Japanese hepatocellular carcinoma (HCC) patients were included in the study. We employed a comprehensive glycoblotting-assisted MALDI-TOF/MS-based quantitative analysis of serum N-glycome and fluorescence HPLC-based quantification of sialic acid species. Data representing serum N-glycan or sialic acid levels were compared among the ethnic groups using SPSS software.

Results

Total of 51 N-glycans released from whole serum glycoproteins could be reproducibly quantified within which 33 glycoforms were detected in all ethnicities. The remaining N-glycans were detected weakly but exclusively either in the Ethiopians (13 glycans) or in all the other ethnic groups (5 glycans). Highest abundance (p < 0.001) of high mannose, core-fucosylated, hyperbranched/hypersialylated N-glycans was demonstrated in Ethiopians. In contrast, only one glycan (m/z 2118) significantly differed among all ethnicities being highest in Indians and lowest in Ethiopians. Glycan abundance trend in Ethiopians was generally close to that of Japanese HCC patients. Glycotyping analysis further revealed ethnic-based disparities mainly in the branched and sialylated structures. Surprisingly, some of the glycoforms greatly elevated in the Ethiopian subjects have been identified as serum biomarkers of various cancers. Sialic acid level was significantly increased primarily in Ethiopians, compared to the other ethnicities.

Conclusion

The study revealed ethnic-specific differences in healthy human serum N-glycome with highest abundance of most glycoforms in the Ethiopian ethnicity. The results strongly emphasized the need to consider ethnicity matching for accurate glyco-biomarker identification. Further large-scale study employing various ethnic compositions is needed to verify the current result.

Clinical Proteomics in Colorectal Cancer, a Promising Tool for Improving Personalised Medicine

Colorectal cancer is the third most common and the fourth most lethal cancer worldwide. In most of cases, patients are diagnosed at an advanced or even metastatic stage, thus explaining the high mortality. The lack of proper clinical tests and the complicated procedures currently used for detecting this cancer, as well as for predicting the response to treatment and the outcome of a patient's resistance in guiding clinical practice, are key elements driving the search for biomarkers. In the present overview, the different biomarkers (diagnostic, prognostic, treatment resistance) discovered through proteomics studies in various colorectal cancer study models (blood, stool, biopsies), including the different proteomic techniques used for the discovery of these biomarkers, are reviewed, as well as the various tests used in clinical practice and those currently in clinical phase. These studies define the limits and perspectives related to proteomic biomarker research for personalised medicine in colorectal cancer.

Hemostatic biomarkers in cancer progression

Malignant disease is characterized by a hemostatic imbalance, usually shifted towards a procoagulant direction, and a high incidence of thrombotic complications. The mechanisms of hemostasis that are critically involved in thrombosis are also implicated in tumor progression, angiogenesis, and metastatic spread. As there is a close relationship between cancer and the clotting system, circulating biomarkers of activation of various hemostasis compartments (i.e. coagulation, fibrinolysis, platelets, endothelium, and other blood cells) have been extensively studied to predict cancer outcomes along with predicting the thrombotic risk. In this review, we will summarize the results of published studies and will focus on ongoing research and future directions of clotting activation bioproducts as biomarkers of cancer disease and progression.

Predictive Markers of Response to Everolimus and Sunitinib in Neuroendocrine Tumors

Neuroendocrine tumors (NETs) represent a large and heterogeneous group of malignancies with various biological and clinical characteristics, depending on the site of origin and the grade of tumor proliferation. In NETs, as in other cancer types, molecularly targeted therapies have radically changed the therapeutic landscape. Recently two targeted agents, the mammalian target of rapamycin inhibitor everolimus and the tyrosine kinase inhibitor sunitinib, have both demonstrated significantly prolonged progression free survival in patients with advanced pancreatic NETs. Despite these important therapeutic developments, there are still significant limitations to the use of these agents due to the lack of accurate biomarkers for predicting tumor response and efficacy of therapy. In this review, we provide an overview of the current clinical data for the evaluation of predictive factors of response to/efficacy of everolimus and sunitinib in advanced pancreatic NETs. Surrogate indicators discussed include circulating and tissue markers, as well as non-invasive imaging techniques.

Practical guide for identifying unmet clinical needs for biomarkers

The development and evaluation of novel biomarkers and testing strategies requires a close examination of existing clinical pathways, including mapping of current pathways and identifying areas of unmet need. This approach enables early recognition of analytical and clinical performance criteria to guide evaluation studies, in a cyclical and iterative manner, all the time keeping the clinical pathway and patient health outcomes as the key drivers in the process. The Test Evaluation Working Group of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM TE-WG) https://www.eflm.eu/site/page/a/1158 has published a conceptual framework of the test evaluation cycle which is driven by the clinical pathway, inherent to which is the test purpose and role within the pathway that are defined by clinical need. To supplement this framework, the EFLM TE-WG has also published an interactive checklist for identifying unmet clinical needs for new biomarkers; a practical tool that laboratories, clinicians, researchers and industry can equally use in a consistent manner when new tests are developed and before they are released to the market. It is hoped that these practical tools will provide consistent and appropriate terminology in this diverse field and offer a platform that facilitates greater consultation and collaboration between all stakeholders. The checklist should assist the work of all colleagues involved in the discovery of novel biomarkers and implementation of new medical tests. The tool is aligned with the IOM recommendations and the FDA and CE regulating body's requirements.

Probing the colorectal cancer proteome for biomarkers: Current status and perspectives

Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide. Biomarkers that can facilitate better clinical management of CRC are in high demand to improve patient outcome and to reduce mortality. In this regard, proteomic analysis holds a promising prospect in the hunt of novel biomarkers for CRC and in understanding the mechanisms underlying tumorigenesis. This review aims to provide an overview of the current progress of proteomic research, focusing on discovery and validation of diagnostic biomarkers for CRC. We will summarize the contributions of proteomic strategies to recent discoveries of protein biomarkers for CRC and also briefly discuss the potential and challenges of different proteomic approaches in biomarker discovery and translational applications.

A large-scale and robust dynamic MRM study of colorectal cancer biomarkers

Over the past 20 years, mass spectrometry (MS) has emerged as a dynamic tool for proteomics biomarker discovery. However, published MS biomarker candidates often do not translate to the clinic, failing during attempts at independent replication. The cause can be shortcomings in study design, sample quality, assay quantitation, and/or quality/process control. To address these shortcomings, we developed an MS workflow in accordance with Tier 2 measurement requirements for targeted peptides, defined by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) "fit-for-purpose" approach, using dynamic multiple reaction monitoring (dMRM), which measures specific peptide transitions during predefined retention time (RT) windows. We describe the development of a robust multipex dMRM assay measuring 641 proteotypic peptides from 392 colorectal cancer (CRC) related proteins, and the procedures to track and handle sample processing and instrument variation over a four-month study, during which the assay measured blood samples from 1045 patients with CRC symptoms. After data collection, transitions were filtered by signal quality metrics before entering receiver operating characteristic (ROC) analysis. The results demonstrated CRC signal carried by 127 proteins in the symptomatic population. The workflow might be further developed to build Tier 1 assays for clinical tests identifying symptomatic individuals at elevated risk of CRC.

SIGNIFICANCE

We developed a dMRM MS method with the rigor of a Tier 2 assay as defined by the CPTAC 'fit for purpose approach' [1]. Using quality and process control procedures, the assay was used to quantify 641 proteotypic peptides representing 392 CRC-related proteins in plasma from 1045 CRC-symptomatic patients. To our knowledge, this is the largest MRM method applied to the largest study to date. The results showed that 127 of the proteins carried univariate CRC signal in the symptomatic population. This large number of single biomarkers bodes well for future development of multivariate classifiers to distinguish CRC in the symptomatic population.

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMS^E applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The "core" sputum proteome (proteins detected in ≥40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMS^E is influenced by several factors, with some proteins being measured in all participants' samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.

Emerging proteomics biomarkers and prostate cancer burden in Africa

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers.

Translating secondary electrospray ionization-high-resolution mass spectrometry to the clinical environment

While there has been progress in making use of breath tests to guide clinical decision making, the full potential of exhaled breath analysis still remains to be exploited. Here we summarize some of the reasons why this is the case, what we have done so far to overcome some of the existing obstacles, and our vision of how we think breath analysis will play a more prominent role in the coming years. In particular, we envision that real-time high-resolution mass spectrometry will provide valuable information in biomarker discovery studies. However, this can only be achieved by a coordinated effort, using standardized equipment and methods in multi-center studies to eventually deliver tangible advances in the field of breath analysis in a clinical setting. Concrete aspects such as sample integrity, compound identification, quantification and standardization are discussed. Novel secondary electrospray ionization developments with the aim of facilitating inter-groups comparisons and biomarker validation studies are also presented.

Circulating tumor DNA: a promising biomarker in the liquid biopsy of cancer

Tissue biopsy is the standard diagnostic procedure for cancers and also provides a material for genotyping, which can assist in the targeted therapies of cancers. However, tissue biopsy-based cancer diagnostic procedures have limitations in their assessment of cancer development, prognosis and genotyping, due to tumor heterogeneity and evolution. Circulating tumor DNA (ctDNA) is single- or double-stranded DNA released by the tumor cells into the blood and it thus harbors the mutations of the original tumor. In recent years, liquid biopsy based on ctDNA analysis has shed a new light on the molecular diagnosis and monitoring of cancer. Studies found that the screening of genetic mutations using ctDNA is highly sensitive and specific, suggesting that ctDNA analysis may significantly improve current systems of tumor diagnosis, even facilitating early-stage detection. Moreover, ctDNA analysis is capable of accurately determining the tumor progression, prognosis and assisting in targeted therapy. Therefore, using ctDNA as a liquid biopsy may herald a revolution for tumor management. Herein, we review the biology of ctDNA, its detection methods and potential applications in tumor diagnosis, treatment and prognosis.

Circulating biomarkers in osteosarcoma: new translational tools for diagnosis and treatment

Osteosarcoma (OS) is a rare primary malignant bone tumour arising from primitive bone-forming mesenchymal cells, with high incidence in children and young adults, accounting for approximately 60% of all malignant bone tumours. Currently, long-term disease-free survival can be achieved by surgical treatment plus chemotherapy in approximately 60% of patients with localized extremity disease, and in 20-30% of patients with metastatic lung or bone disease. Diagnosis of primary lesions and recurrences is achieved by using radiological investigations and standard tissue biopsy, the latter being costly, painful and hardly repeatable for patients. Therefore, despite some recent advances, novel biomarkers for OS diagnosis, prediction of response to therapy, disease progression and chemoresistance, are urgently needed. Biological fluids such as blood represent a rich source of non-invasive cancer biomarkers, which allow to understand what is really happening inside the tumour, either at diagnosis or during disease progression. In this regard, liquid biopsy potentially represents an alternative and non-invasive method to detect tumour onset, progression and response to therapy. In this review, we will summarize the state of the art in this novel area, illustrating recent studies on OS. Although the data reported in literature seem preliminary, liquid biopsy represents a promising tool with the potential to be rapidly translated in the clinical practice.

LINCRNA00273 promotes cancer metastasis and its G-Quadruplex promoter can serve as a novel target to inhibit cancer invasiveness

Discovery of anti-metastatic drugs is of immense clinical significance as metastasis is responsible for 90% of all cancer deaths. Here we report the inhibitory effect of a bis schiff base (M2) on cancer cell migration and invasion in vitro and in vivo. M2 has shown good solubility and permeability across the intestinal cell wall and hence can be classified as BCS (Biopharmaceutical classification system) class I. Microarray studies identified a long non coding intergenic RNA, LINC00273 as a novel molecular target of M2. We report that LINC00273 harbors a unique (4n-1) parallel G-Quadruplex structure in its promoter as validated by DMS footprint. M2 is proposed to stabilize this G-quadruplex structure resulting in the down-regulation of LINC00273 expression. Dual Luciferase reporter assay also suggests inhibition of LINC00273 promoter activity by M2. Involvement of this linc in metastasis is proven by siRNA and shRNA mediated knock down of LINC00273 in vitro and in vivo in nude mice which significantly decelerates cancer cell migration and invasion and also makes the cells unresponsive to TGF-β's pro-metastatic effects. Furthermore, the real time expression of LINC00273 in thirty seven human clinical samples is found to be positively correlated with the histopathological staging of metastasis.

CANcer-specific Evaluation System (CANES): a high-accuracy platform, for preclinical single/multi-biomarker discovery

The recent creation of enormous, cancer-related “Big Data” public depositories represents a powerful means for understanding tumorigenesis. However, a consistently accurate system for clinically evaluating single/multi-biomarkers remains lacking, and it has been asserted that oft-failed clinical advancement of biomarkers occurs within the very early stages of biomarker assessment. To address these challenges, we developed a clinically testable, web-based tool, CANcer-specific single/multi-biomarker Evaluation System (CANES), to evaluate biomarker effectiveness, across 2,134 whole transcriptome datasets, from 94,147 biological samples (from 18 tumor types). For user-provided single/multi-biomarkers, CANES evaluates the performance of single/multi-biomarker candidates, based on four classification methods, support vector machine, random forest, neural networks, and classification and regression trees. In addition, CANES offers several advantages over earlier analysis tools, including: 1) survival analysis; 2) evaluation of mature miRNAs as markers for user-defined diagnostic or prognostic purposes; and 3) provision of a “pan-cancer” summary view, based on each single marker. We believe that such “landscape” evaluation of single/multi-biomarkers, for diagnostic therapeutic/prognostic decision-making, will be highly valuable for the discovery and “repurposing” of existing biomarkers (and their specific targeted therapies), leading to improved patient therapeutic stratification, a key component of targeted therapy success for the avoidance of therapy resistance.

Lectins: an effective tool for screening of potential cancer biomarkers

In recent years, the use of lectins for screening of potential biomarkers has gained increased importance in cancer research, given the development in glycobiology that highlights altered structural changes of glycans in cancer associated processes. Lectins, having the properties of recognizing specific carbohydrate moieties of glycoconjugates, have become an effective tool for detection of new cancer biomarkers in complex bodily fluids and tissues. The specificity of lectins provides an added advantage of selecting peptides that are differently glycosylated and aberrantly expressed in cancer patients, many of which are not possibly detected using conventional methods because of their low abundance in bodily fluids. When coupled with mass spectrometry, research utilizing lectins, which are mainly from plants and fungi, has led to identification of numerous potential cancer biomarkers that may be used in the future. This article reviews lectin-based methods that are commonly adopted in cancer biomarker discovery research.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

Proteases and cytokines as mediators of interactions between cancer and stromal cells in tumours

Proteolytic enzymes are highly relevant in different processes of cancer progression. Their interplay with other signalling molecules such as cytokines represents important regulation of multicellular cross-talk. In this review, we discuss protease regulation mechanisms of cytokine signalling in various types of cancer. Additionally, we highlight the reverse whereby cytokines have an impact on protease expression in an autocrine and paracrine manner, representing complex feedback mechanisms among multiple members of these two protein families. The relevance of the protease-cytokine axis is illustrated in glioblastoma, where interactions between normal mesenchymal stem cells and cancer cells play an important role in this very malignant form of brain cancer.

Temporal Signal Pattern Recognition in Mass Spectrometry: A Method for Rapid Identification and Accurate Quantification of Biomarkers for Inborn Errors of Metabolism with Quality Assurance

Mass spectrometry (MS)-based metabolomic initiatives that use conventional separation techniques are limited by low sample throughput and complicated data processing that contribute to false discoveries. Herein, we introduce a new strategy for unambiguous identification and accurate quantification of biomarkers for inborn errors of metabolism (IEM) from dried blood spots (DBS) with quality assurance. A multiplexed separation platform based on multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS) was developed to provide comparable sample throughput to flow injection analysis-tandem MS (FIA-MS/MS) but with greater selectivity as required for confirmatory testing and discovery-based metabolite profiling of volume-restricted biospecimens. Mass spectral information is encoded temporally within a separation by serial injection of three or more sample pairs, each having a unique dilution pattern, alongside a quality control (QC) that serves as a reference in every run to facilitate between-sample comparisons and/or batch correction due to system drift. Optimization of whole blood extraction conditions on DBS filter paper cut-outs was first achieved to maximize recovery of a wide range of polar metabolites from DBS extracts. An interlaboratory comparison study was also conducted using a proficiency test and retrospective neonatal DBS that demonstrated good agreement between MSI-CE-MS and validated FIA-MS/MS methods within an accredited facility. Our work demonstrated accurate identification of various IEM based on reliable measurement of a panel of primary or secondary biomarkers above an upper cutoff concentration limit for presumptive screen-positive cases without stable isotope-labeled reagents. Additionally, nontargeted metabolite profiling by MSI-CE-MS with temporal signal pattern recognition revealed new biomarkers for early detection of galactosemia, such as N-galactated amino acids, that are a novel class of pathognomonic marker due to galactose stress in affected neonates.

Live-single-cell phenotypic cancer biomarkers-future role in precision oncology?

The promise of precision and personalized medicine is rooted in accurate, highly sensitive, and specific disease biomarkers. This is particularly true for cancer-a disease characterized by marked tumor heterogeneity and diverse molecular signatures. Although thousands of biomarkers have been described, only a very small number have been successfully translated into clinical use. Undoubtedly, there is need for rapid, quantitative, and more cost effective biomarkers for tumor diagnosis and prognosis, to allow for better risk stratification and aid clinicians in making personalized treatment decisions. This is particularly true for cancers where specific biomarkers are either not available (e.g., renal cell carcinoma) or where current biomarkers tend to classify individuals into broad risk categories unable to accurately assess individual tumor aggressiveness and adverse pathology potential (e.g., prostate cancer), thereby leading to problems of over-diagnosis and over-treatment of indolent cancer and under-treatment of aggressive cancer. This perspective highlights an emerging class of cancer biomarkers-live-single-cell phenotypic biomarkers, as compared to genomic biomarkers, and their potential application for cancer diagnosis, risk-stratification, and prognosis.

Did the reporting of prognostic studies of tumour markers improve since the introduction of REMARK guideline? A comparison of reporting in published articles

Although biomarkers are perceived as highly relevant for future clinical practice, few biomarkers reach clinical utility for several reasons. Among them, poor reporting of studies is one of the major problems. To aid improvement, reporting guidelines like REMARK for tumour marker prognostic (TMP) studies were introduced several years ago. The aims of this project were to assess whether reporting quality of TMP-studies improved in comparison to a previously conducted study assessing reporting quality of TMP-studies (PRE-study) and to assess whether articles citing REMARK (citing group) are better reported, in comparison to articles not citing REMARK (not-citing group). For the POST-study, recent articles citing and not citing REMARK (53 each) were identified in selected journals through systematic literature search and evaluated in same way as in the PRE-study. Ten of the 20 items of the REMARK checklist were evaluated and used to define an overall score of reporting quality. The observed overall scores were 53.4% (range: 10%-90%) for the PRE-study, 57.7% (range: 20%-100%) for the not-citing group and 58.1% (range: 30%-100%) for the citing group of the POST-study. While there is no difference between the two groups of the POST-study, the POST-study shows a slight but not relevant improvement in reporting relative to the PRE-study. Not all the articles of the citing group, cited REMARK appropriately. Irrespective of whether REMARK was cited, the overall score was slightly higher for articles published in journals requesting adherence to REMARK than for those published in journals not requesting it: 59.9% versus 51.9%, respectively. Several years after the introduction of REMARK, many key items of TMP-studies are still very poorly reported. A combined effort is needed from authors, editors, reviewers and methodologists to improve the current situation. Good reporting is not just nice to have but is essential for any research to be useful.

Towards personalized tumor markers

The cancer biomarker discovery pipeline is progressing slowly. The difficulties of finding novel and effective biomarkers for diagnosis and management of cancer patients are well-known. We speculate that it is unlikely to discover new serological biomarkers characterized by high sensitivity and specificity. This projection is supported by recent findings that cancers are genetically highly heterogeneous. Here, we propose a new way of improving the landscape of cancer biomarker research. There are currently hundreds, if not thousands, of described biomarkers which perform at high specificity (> 90%), but at relatively low sensitivity (< 30%). We call these “rare tumor markers.” Borrowing from the principles of precision medicine, we advocate that among these low sensitivity markers, some may be useful to specific patients. We suggest screening new patients for hundreds to thousands of cancer biomarkers to identify a few that are informative, and then use them clinically. This is similar to what we currently do with genomics to identify personalized therapies. We further suggest that this approach may explain as to why some biomarkers are elevated in only a small group of patients. It is likely that these differences in expression are linked to specific genomic alterations, which could then be found with genomic sequencing.

Waste, Leaks, and Failures in the Biomarker Pipeline

BACKGROUND

The large, expanding literature on biomarkers is characterized by almost ubiquitous significant results, with claims about the potential importance, but few of these discovered biomarkers are used in routine clinical care.

CONTENT

The pipeline of biomarker development includes several specific stages: discovery, validation, clinical translation, evaluation, implementation (and, in the case of nonutility, deimplementation). Each of these stages can be plagued by problems that cause failures of the overall pipeline. Some problems are nonspecific challenges for all biomedical investigation, while others are specific to the peculiarities of biomarker research. Discovery suffers from poor methods and incomplete and selective reporting. External independent validation is limited. Selection for clinical translation is often shaped by nonrational choices. Evaluation is sparse and the clinical utility of many biomarkers remains unknown. The regulatory environment for biomarkers remains weak and guidelines can reach biased or divergent recommendations. Removing inefficient or even harmful biomarkers that have been entrenched in clinical care can meet with major resistance.

SUMMARY

The current biomarker pipeline is too prone to failures. Consideration of clinical needs should become a starting point for the development of biomarkers. Improvements can include the use of more stringent methodology, better reporting, larger collaborative studies, careful external independent validation, preregistration, rigorous systematic reviews and umbrella reviews, pivotal randomized trials, and implementation and deimplementation studies. Incentives should be aligned toward delivering useful biomarkers.

Identification and Validation of Novel Subtype-Specific Protein Biomarkers in Pancreatic Ductal Adenocarcinoma

OBJECTIVES

Pancreatic ductal adenocarcinoma (PDAC) has been subclassified into 3 molecular subtypes: classical, quasi-mesenchymal, and exocrine-like. These subtypes exhibit differences in patient survival and drug resistance to conventional therapies. The aim of the current study is to identify novel subtype-specific protein biomarkers facilitating subtype stratification of patients with PDAC and novel therapy development.

METHODS

A set of 12 human patient-derived primary cell lines was used as a starting material for an advanced label-free proteomics approach leading to the identification of novel cell surface and secreted biomarkers. Cell surface protein identification was achieved by in vitro biotinylation, followed by mass spectrometric analysis of purified biotin-tagged proteins. Proteins secreted into a chemically defined serum-free cell culture medium were analyzed by shotgun proteomics.

RESULTS

Of 3288 identified proteins, 2 pan-PDAC (protocadherin-1 and lipocalin-2) and 2 exocrine-like-specific (cadherin-17 and galectin-4) biomarker candidates have been validated. Proximity ligation assay analysis of the 2 exocrine-like biomarkers revealed their co-localization on the surface of exocrine-like cells.

CONCLUSIONS

The study reports the identification and validation of novel PDAC biomarkers relevant for the development of patient stratification tools. In addition, cadherin-17 and galectin-4 may serve as targets for bispecific antibodies as novel therapeutics in PDAC.

Circulating microRNAs as Potential Biomarkers of Infectious Disease

microRNAs (miRNAs) are a class of small non-coding endogenous RNA molecules that regulate a wide range of biological processes by post-transcriptionally regulating gene expression. Thousands of these molecules have been discovered to date, and multiple miRNAs have been shown to coordinately fine-tune cellular processes key to organismal development, homeostasis, neurobiology, immunobiology, and control of infection. The fundamental regulatory role of miRNAs in a variety of biological processes suggests that differential expression of these transcripts may be exploited as a novel source of molecular biomarkers for many different disease pathologies or abnormalities. This has been emphasized by the recent discovery of remarkably stable miRNAs in mammalian biofluids, which may originate from intracellular processes elsewhere in the body. The potential of circulating miRNAs as biomarkers of disease has mainly been demonstrated for various types of cancer. More recently, however, attention has focused on the use of circulating miRNAs as diagnostic/prognostic biomarkers of infectious disease; for example, human tuberculosis caused by infection with Mycobacterium tuberculosis, sepsis caused by multiple infectious agents, and viral hepatitis. Here, we review these developments and discuss prospects and challenges for translating circulating miRNA into novel diagnostics for infectious disease.

Towards comprehensive and quantitative proteomics for diagnosis and therapy of human disease

Given superior analytical features, MS proteomics is well suited for the basic investigation and clinical diagnosis of human disease. Modern MS enables detailed functional characterization of the pathogenic biochemical processes, as achieved by accurate and comprehensive quantification of proteins and their regulatory chemical modifications. Here, we describe how high-accuracy MS in combination with high-resolution chromatographic separations can be leveraged to meet these analytical requirements in a mechanism-focused manner. We review the quantification methods capable of producing accurate measurements of protein abundance and posttranslational modification stoichiometries. We then discuss how experimental design and chromatographic resolution can be leveraged to achieve comprehensive functional characterization of biochemical processes in complex biological proteomes. Finally, we describe current approaches for quantitative analysis of a common functional protein modification: reversible phosphorylation. In all, current instrumentation and methods of high-resolution chromatography and MS proteomics are poised for immediate translation into improved diagnostic strategies for pediatric and adult diseases.

Assessment of the extent of unpublished studies in prognostic factor research: a systematic review of p53 immunohistochemistry in bladder cancer as an example

OBJECTIVES

When study groups fail to publish their results, a subsequent systematic review may come to incorrect conclusions when combining information only from published studies. p53 expression measured by immunohistochemistry is a potential prognostic factor in bladder cancer. Although numerous studies have been conducted, its role is still under debate. The assumption that unpublished studies too harbour evidence on this research topic leads to the question about the attributable effect when adding this information and comparing it with published data. Thus, the aim was to identify published and unpublished studies and to explore their differences potentially affecting the conclusion on its function as a prognostic biomarker.

DESIGN

Systematic review of published and unpublished studies assessing p53 in bladder cancer in Germany between 1993 and 2007.

RESULTS

The systematic search revealed 16 studies of which 11 (69%) have been published and 5 (31%) have not. Key reason for not publishing the results was a loss of interest of the investigators. There were no obviously larger differences between published and unpublished studies. However, a meaningful meta-analysis was not possible mainly due to the poor (ie, incomplete) reporting of study results.

CONCLUSIONS

Within this well-defined population of studies, we could provide empirical evidence for the failure of study groups to publish their results that was mainly caused by loss of interest. This fact may be coresponsible for the role of p53 as a prognostic factor still being unclear. We consider p53 and the restriction to studies in Germany as a specific example, but the critical issues are probably similar for other prognostic factors and other countries.

Avoiding false discovery in biomarker research

Background

Human tyrosine-protein phosphatase non-receptor type substrate 1α (SIRPA) is a surface marker identified in cardiomyocytes differentiated from human embryonic stem cells. Our objective was to determine if circulating SIRPA levels can serve as a biomarker of cardiac injury in children undergoing open heart surgery.

Results

Paired pre- and post-operative serum samples from 48 pediatric patients undergoing open heart surgery and from 6 pediatric patients undergoing non-cardiac surgery (controls) were tested for SIRPA protein levels using commercially available SIRPA ELISA kits from two manufacturers. Post-operative SIRPA concentrations were significantly higher in patients after cardiac surgery compared to non-cardiac surgery when tested using SIRPA ELISA kits from both manufacturers. To verify the identity of the protein detected, recombinant human SIRPA protein (rhSIRPA) was tested on both ELISA kits. The calibrator from both ELISA kits was analyzed by Western blot as well as by Mass Spectrometry (MS). Western blot analysis of calibrators from both kits did not identity SIRPA. MS analysis of calibrators from both ELISA kits identified several inflammatory markers and albumin but no SIRPA was detected.

Conclusions

We conclude that commercially available ELISA kits for SIRPA give false-positive results. Verifying protein identity using robust protein characterization is critical to avoid false biomarker discovery when using commercial ELISA kits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12858-016-0073-x) contains supplementary material, which is available to authorized users.

Biomarker development targeting unmet clinical needs

BACKGROUND

The introduction of new biomarkers can lead to inappropriate utilization of tests if they do not fill in existing gaps in clinical care. We aimed to define a strategy and checklist for identifying unmet needs for biomarkers.

METHODS

A multidisciplinary working group used a 4-step process: 1/ scoping literature review; 2/ face-to-face meetings to discuss scope, strategy and checklist items; 3/ iterative process of feedback and consensus to develop the checklist; 4/ testing and refinement of checklist items using case scenarios.

RESULTS

We used clinical pathway mapping to identify clinical management decisions linking biomarker testing to health outcomes and developed a 14-item checklist organized into 4 domains: 1/ identifying and 2/ verifying the unmet need; 3/ validating the intended use; and 4/ assessing the feasibility of the new biomarker to influence clinical practice and health outcome. We present an outcome-focused approach that can be used by multiple stakeholders for any medical test, irrespective of the purpose and role of testing.

CONCLUSIONS

The checklist intends to achieve more efficient biomarker development and translation into practice. We propose the checklist is field tested by stakeholders, and advocate the role of the clinical laboratory professional to foster trans-sector collaboration in this regard.

Systems for multiplexing homogeneous immunoassays

High-throughput multiplex protein biomarker assays continue to gain significance in the fields of biomarker discovery and drug development, due to their economical use of not only the precious clinical biological samples but also expensive reagents. Among these platforms, homogeneous multiplex systems have potential for short assay run times and cost-effective reagent consumptions. However, these systems must overcome challenges of signal cross talk and biochemical cross-reactivity. Despite these obstacles, several homogeneous multiplex immunoassays have been demonstrated. These include fluorescent polarization, fluorescent resonance energy transfer with quantum dots or graphene, luminescent oxygen-channeling immunoassay coupled with aqueous two-phase systems and DNA proximity assays. The balance between speed/simplicity and high multiplexing and robustness of these homogeneous multiplex immunoassays are discussed in this review.

Emerging applications of metabolomics in drug discovery and precision medicine

Metabolomics is an emerging 'omics' science involving the comprehensive characterization of metabolites and metabolism in biological systems. Recent advances in metabolomics technologies are leading to a growing number of mainstream biomedical applications. In particular, metabolomics is increasingly being used to diagnose disease, understand disease mechanisms, identify novel drug targets, customize drug treatments and monitor therapeutic outcomes. This Review discusses some of the latest technological advances in metabolomics, focusing on the application of metabolomics towards uncovering the underlying causes of complex diseases (such as atherosclerosis, cancer and diabetes), the growing role of metabolomics in drug discovery and its potential effect on precision medicine.

A multiplex immunoassay for the non-invasive detection of bladder cancer

BACKGROUND

Urine based assays that can non-invasively detect bladder cancer (BCa) have the potential to reduce unnecessary and invasive procedures. The purpose of this study was to develop a multiplex immunoassay that can accurately and simultaneously monitor ten diagnostic urinary protein biomarkers for application as a non-invasive test for BCa detection.

METHODS

A custom electrochemiluminescent multiplex assay was constructed (Meso Scale Diagnostics, LLC, Rockville, MD, USA) to detect the following urinary proteins; IL8, MMP9, MMP10, ANG, APOE, SDC1, A1AT, PAI1, CA9 and VEGFA. Voided urine samples from two cohorts were collected prior to cystoscopy and samples were analyzed blinded to the clinical status of the participants. Means (±SD) and receiver operating characteristic (ROC) curve analysis were used to compare assay performance and to assess the diagnostic accuracy of the diagnostic signature.

RESULTS

Comparative diagnostic performance analyses revealed an AUROC value of 0.9258 for the multiplex assay and 0.9467 for the combination of the single-target ELISA assays (p = 0.625), so there was no loss of diagnostic utility for the MSD multiplex assay. Analysis of the independent 200-sample cohort using the multiplex assay achieved an overall diagnostic sensitivity of 0.85, specificity of 0.81, positive predictive value 0.82 and negative predictive value 0.84.

CONCLUSIONS

It is technically feasible to simultaneously monitor complex urinary diagnostic signatures in a single assay without loss of performance. The described protein-based assay has the potential to be developed for the non-invasive detection of BCa.

Differentially Expressed Genes and Signature Pathways of Human Prostate Cancer

Genomic technologies including microarrays and next-generation sequencing have enabled the generation of molecular signatures of prostate cancer. Lists of differentially expressed genes between malignant and non-malignant states are thought to be fertile sources of putative prostate cancer biomarkers. However such lists of differentially expressed genes can be highly variable for multiple reasons. As such, looking at differential expression in the context of gene sets and pathways has been more robust. Using next-generation genome sequencing data from The Cancer Genome Atlas, differential gene expression between age- and stage- matched human prostate tumors and non-malignant samples was assessed and used to craft a pathway signature of prostate cancer. Up- and down-regulated genes were assigned to pathways composed of curated groups of related genes from multiple databases. The significance of these pathways was then evaluated according to the number of differentially expressed genes found in the pathway and their position within the pathway using Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis. The “transforming growth factor-beta signaling” and “Ran regulation of mitotic spindle formation” pathways were strongly associated with prostate cancer. Several other significant pathways confirm reported findings from microarray data that suggest actin cytoskeleton regulation, cell cycle, mitogen-activated protein kinase signaling, and calcium signaling are also altered in prostate cancer. Thus we have demonstrated feasibility of pathway analysis and identified an underexplored area (Ran) for investigation in prostate cancer pathogenesis.

Biomarkers for Bone Tumors: Discovery from Genomics and Proteomics Studies and Their Challenges

Diagnosis of bone tumor currently relies on imaging and biopsy, and hence, the need to find less invasive ways for its accurate detection. More recently, numerous promising deoxyribonucleic acid (DNA) and protein biomarkers with significant prognostic, diagnostic and/or predictive abilities for various types of bone tumors have been identified from genomics and proteomics studies. This article reviewed the putative biomarkers for the more common types of bone tumors (that is, osteosarcoma, Ewing sarcoma, chondrosarcoma [malignant] and giant cell tumor [benign]) that were unveiled from the studies. The benefits and drawbacks of these biomarkers, as well as the technology platforms involved in the research, were also discussed. Challenges faced in the biomarker discovery studies and the problems in their translation from the bench to the clinical settings were also addressed.