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Many candidate biomarkers emerging from genomics and proteomics research have the potential to serve as predictive indexes for guiding the development of safer and more efficacious drugs. Research and development of biomarker discovery, selection, and clinical qualification, however, is still a relatively new field for the pharmaceutical industry. Advances in technology provide a plethora of analytical tools to discover and analyze mechanism-and-disease-specific biomarkers for drug development. In the discovery phase, differential proteomic analysis using mass spectrometry enables the identification of candidate biomarkers that are associated with a specific mechanism relevant to disease progression and affected by drug treatment. Reliable bioanalytical methods are then developed and implemented to select promising biomarkers for further studies in animals and humans. Quantitative analytical methods capable of generating reliable data constitute a solid basis for statistical assessment of the predictive utility of biomarkers. Biomarker method validation is diverse and for purposes that are very different from those of drug bioanalysis or diagnostic use. Besides being flexible, it should sufficiently demonstrate the method's ability to meet the study intent and the attendant regulatory requirements. Several papers have been published outlining specific requirements for successful biomarker method development and validation using a "Fit-for-Purpose" approach. Many of the challenges faced during biomarker discovery as well as during technology and process translation are discussed in this chapter, including preanalytical planning, assay development, and preclinical and clinical validation. Specific references to protein biomarkers for cancer drug development are also discussed.
Cross-sectional biomarker studies can provide a snapshot of the frequency and characteristics of exposure/disease in a population at a particular point in time and, as a result, valuable insights for delineating the multi-step association between exposure and disease occurrence. Three major issues should be considered when designing biomarker studies: selection of appropriate biomarkers, the assay (laboratory validity), and the population validity of the selected biomarkers. Factors related to biomarker selection include biological relevance, specificity, sensitivity, biological half-life, stability, and so on. The assay attributes include limit of detection, reproducibility/reliability, inter-laboratory variation, specificity, time, and cost. Factors related to the population validity include the frequency or prevalence of markers, greater inter-individual variation than intra-individual variation, intra-class correlation coefficients (ICC), association with potential confounders, invasiveness of specimen collection, and subject selection. Three studies are selected to demonstrate different features of cross-sectional biomarker studies: (1) characterizing the determinants of the biomarkers (study I: urinary PAH metabolites and environmental particulate exposure), (2) relationship of multiple biomarkers of exposure and effect (study II: relationship between urinary PAH metabolites and oxidative stress), and (3) evaluating gene-environmental interaction (study III: effect of genetic polymorphisms of GSTM1 on the association of green tea consumption and urinary 1-OHPG levels in shipbuilding workers).
The results of the present study suggest that the signaling molecule cAMP could constitute a reliable biomarker of pollution monitoring. Increased levels of cAMP were observed in tissues of mussels Mytilus galloprovincialis exposed to PAHs, 2,4-dichlorophenoxyacetic acid and lindane for 15 days. cAMP levels were higher in mantle/gonad complex, in relation to other tissues studied (digestive gland and gills). In support of our suggestion, cAMP was significantly correlated with established biomarkers, such as lysosomal membrane stability, AChE activity and metallothionein content. In addition, our results support the establishment of morphometrical alterations of neutral lipids as biomarker of organic pollution, since high accumulation of neutral lipids in the digestive gland of mussels exposed to organic pollutants in relation to non-exposed mussels was noted. In addition, correlation analysis between cellular and biochemical biomarkers showed that the volume density of neutral lipids negatively correlated with both lysosomal membrane stability and AChE activity. Regarding micronucleus test, our results do not support its use as a biomarker of organic pollution, since no statistical differences were found between control and exposed mussels. On the other hand, significant correlations were observed among the battery of biomarkers, such as lysosomal membrane stability, AChE activity and metallothionein content after the mussels' exposure to the specific organic compounds, thus supporting the important role of these biomarkers as reliable indicators of organic pollution. In conclusion, our results support cAMP and morphometrical alterations of neutral lipids as biomarkers of environmental pollution.
BACKGROUND: Limited access to echocardiography can delay the diagnosis of suspected heart failure (HF), which in turn postpones the initiation of optimal guideline-directed medical therapy. Although natriuretic peptides like B-type natriuretic peptide (BNP) are valuable biomarkers for diagnosing and managing HF, the utility of combining BNP with other blood-based biomarkers to predict subtypes of new-onset HF remains underexplored. OBJECTIVES: This study sought to investigate and evaluate the diagnostic significance of adding blood-based biomarkers to BNP for identifying heart failure with preserved ejection fraction (HFpEF) or reduced ejection fraction (HFrEF), with the goal of enhancing diagnostic assays beyond BNP measurements. METHODS: We identified candidate blood protein biomarkers using untargeted proteomics workflows from a cohort of individuals recruited to the STOP-HF trial who were at risk of HF and subsequently developed either HFpEF or HFrEF over time ("HF progressors"; n = 40). Candidate biomarkers were verified in an independent cohort (n = 52) from a community-based rapid access HF diagnostic clinic. The biological processes associated with these proteins were assessed, and the diagnostic values of biomarker panels were evaluated using a machine learning approach. RESULTS: Within HF progressors, we identified 3 proteins associated with HFpEF development: vascular cell adhesion protein 1 (VCAM1), insulin-like growth factor 2 (IGF2), and inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3). Additionally, 4 proteins were linked to HFrEF development: C-reactive protein (CRP), interleukin-6 receptor subunit beta (IL6RB), phosphatidylinositol-glycan-specific phospholipase D (PHLD), and noelin (NOE1). These findings were verified in an independent cohort to distinguish HF subtypes from controls. Moreover, a random forest algorithm demonstrated that combining these candidate biomarkers with BNP measurement significantly improved the prediction of HF subtypes. CONCLUSIONS: We identified candidate proteins linked to HFpEF and HFrEF in a longitudinal HF progressor cohort and validated them in a community-based cohort. Adding these proteins to BNP led to a significant improvement in HF subtype prediction. Study results have clinical implications for blood-based screening of HF subtypes using panels of biomarkers, particularly in resource-limited settings.
Biology-based markers that can be used to confirm the diagnosis of chronic graft-versus-host disease (GVHD) or monitor progression of the disease could help in the evaluation of new therapies. Biomarkers have been defined as any characteristic that is objectively measured and evaluated as an indicator of a normal biologic or pathogenic process, a pharmacologic response to a therapeutic intervention, or a surrogate end point intended to substitute for a clinical end point. The following applications of biomarkers could be useful in chronic GVHD clinical trials or management: (1) predicting response to therapy; (2) measuring disease activity and distinguishing irreversible damage from continued disease activity; (3) predicting the risk of developing chronic GVHD; (4) diagnosing chronic GVHD: (5) predicting the prognosis of chronic GVHD; (6) evaluating the balance between GVHD and graft-versus-leukemia effects (graft-versus-leukemia or GVT); and (7) serving as a surrogate end point for therapeutic response. Such biomarkers can be identified by either hypothesis-driven testing or by high-throughput discovery-based methods. To date, no validated biomarkers have been established for chronic GVHD, although several candidate biomarkers have been identified from limited hypothesis-driven studies. Both approaches have merit and should be pursued. The consistent treatment and standardized documentation needed to support biomarker studies are most likely to be satisfied in prospective clinical trials.
The burgeoning field of proteomics plays a powerful and relevant role in the discovery of biomarkers, which are biometric measurements that convey information about the biological condition of the subject being tested. Biomarkers have changed the manner in which we diagnose disease, monitor the effect of therapy, classify disease, detect toxicity, and develop new drugs. The central part that proteins command in both disease etiology and treatment make them prime biomarker candidates. Indeed, the majority of clinical tests in use today measure proteins. This perspective introduces the Journal of Proteome Research Special Issue on Proteomics and Biomarkers. It outlines the major applications of biomarkers, discusses the basics of statistically assessing them and considers the crucial choice of sample type. Central considerations of biomarker discovery and validation, particularly with respect to their intended clinical and research applications, are highlighted.
Guiding principles are provided and discussed on how to inform the physician scientist and cancer researcher about quality control systems to enable a consistent assessment of the clinical value of tumor-associated biomarkers. Next to cancer research itself, the Receptor and Biomarker Group of the European Organization for Research and Treatment of Cancer (RBG-EORTC) advises on methodologies, test kits and test reagents utilized for tumor biomarker determination. Tumor-associated biomarkers are important and clinically useful tools which can aid the early diagnosis of cancer, determine prognosis, predict therapy response, and monitor disease. With regard to clinical use of tumor-associated bio-markers, quality assessment and quality assurance programs of the RBG-EORTC are crucially important issues. Test reagents, assays, and procedures for tumor sample collection and handling should be standardized. Furthermore, standard operating procedures (SOPs) should be developed for each type of tumor specimen. Assay formats and the quality of the tumor biomarker assay results have to be monitored by continuous within- and inter-laboratory proficiency testing. With this approach, a major step forward in the knowledge and understanding of the biological role and the clinical utility of tumor-associated biomarkers would be anticipated.
During the last decade, there has been increasing interest in the use of biomarkers in cancer epidemiology to enhance exposure assessment, to gain insight into disease mechanism, and to understand acquired or inherited susceptibility. To facilitate the use of biomarkers in health research, biomarkers have been divided into categories that depict the spectrum of cancer pathogenesis from exposure to disease. In this paper, we consider the epidemiological designs most suitable for the study of each type of marker. In particular, we present a two-dimensional matrix relating the biomarker categories on one axis to four different types of activities (laboratory, transitional, and etiological studies and public health applications) that develop markers and apply them in human populations. We then use the matrix to review the potential application of biomarkers in observational studies of cancer etiology, discussing the advantages, disadvantages, and logistical considerations in using biomarkers to answer research questions.
Biomarker analysis and evaluation in oncology is the product of a number of processes (including managerial, technical and interpretation steps) which need to be monitored and controlled to prevent and correct errors and guarantee a satisfactory level of quality. Several biomarkers have recently moved to clinical validation studies and successively to clinical practice without any definition of standard procedures and/or quality control (QC) schemes necessary to guarantee the reproducibility of the laboratory information. In Italy several national scientific societies and single researchers have activated -- often on a pilot level -- specific external quality assessment protocols, thereby potentially jeopardizing the clinical reality even further. In view of the seriousness of the problem, in 1998 the Italian Ministry of Health sponsored a National Survey Project to coordinate and standardize the procedures and to develop QC programs for the analysis of cancer biomarkers of potential clinical relevance. Twelve QC programs focused on biomarkers and concerning morphological, immunohistochemical, biochemical, molecular, and immunoenzymatic assays were coordinated and implemented. Specifically, external QC programs for the analytical phase of immunohistochemical p53, Bcl-2, c-erb-2/neu/HER2, and microvessel density determination, of morphological evaluation of tumor differentiation grade, and of molecular p53 analysis were activated for the first time within the project. Several hundreds of Italian laboratories took part in these QC programs, the results of which are available on the web site of the Network (www.cqlaboncologico.it). Financial support from the Italian Government and the National Research Council (CNR) will guarantee the pursuit of activities that will be extended to new biomarkers, to preanalytical phases of the assays, and to revision of the criteria of clinical usefulness for evaluating the cost/benefit ratio.
Death or myocardial infarction, the most serious clinical consequences of atherosclerosis, often result from plaque rupture at non-flow limiting lesions. Current diagnostic imaging with coronary angiography only detects large plaques that already impinge on the lumen and cannot accurately identify those that have a propensity to cause unheralded events. Accurate evaluation of the composition or of the biomechanical characteristics of plaques with invasive or non-invasive methods, alone or in conjunction with assessment of circulating biomarkers, could help identify high-risk patients, thus providing the rationale for aggressive treatments in order to reduce future clinical events. The IBIS (Integrated Biomarker and Imaging Study) study is a prospective, single-center, non-randomized, observational study conducted in Rotterdam. The aim of the IBIS study is to evaluate both invasive (quantitative coronary angiography, intravascular ultrasound (IVUS) and palpography) and non-invasive (multislice spiral computed tomography) imaging techniques to characterize non-flow limiting coronary lesions. In addition, multiple classical and novel biomarkers will be measured and their levels correlated with the results of the different imaging techniques. A minimum of 85 patients up to a maximum of 120 patients will be included. This paper describes the study protocol and methodological solutions that have been devised for the purpose of comparisons among several imaging modalities. It outlines the analyses that will be performed to compare invasive and non-invasive imaging techniques in conjunction with multiple biomarkers to characterize non-flow limiting subclinical coronary lesions.
BACKGROUND AND HYPOTHESIS: Schizophrenia spectrum disorders (SSDs) produce severe symptoms, disability, and premature mortality, but only partially effective symptomatic treatments exist. Treatment development is impeded by lack of insight into disease mechanisms or objective biomarkers for clinical trials. Advances in genetics and neurobiology have converged on strong pathogenic hypotheses for SSDs centered on synapse dysfunction and excessive pruning, pathogenic processes that may produce measurable proteomic evidence in cerebrospinal fluid (CSF). Leveraging design precedents from successful fluid biomarkers discovery for Alzheimer's disease, we undertook a pilot study to test the feasibility of repeated CSF and blood samples collection from individuals with SSDs. Here we report on successful implementation of longitudinal bio-behavioral phenotyping in SSDs and establishment of a repository to permit broad sample and data sharing. STUDY DESIGN: The Schizophrenia Spectrum Biomarkers Consortium (SSBC) study principles included longitudinal study design, paired CSF and plasma collection associated with robust phenotypic characterization, at 3 academic sites and the establishment of a biorepository. Participants underwent clinical and cognitive assessments, neuroimaging, blood draws, and CSF collection via lumbar puncture (LP) every 6 months. STUDY RESULTS: SSBC successfully enrolled 48 SSD and 41 Healthy Controls with a 73% longitudinal retention. Clinical, cognitive, and neuroimaging results were consistent across sites and with existing studies. Study procedures were well tolerated, and almost all LPs (99%) resulted in either no or minor headache/backache that resolved without medical interventions. CONCLUSIONS: The pilot SSBC study demonstrates that a multi-site, longitudinal study with repeat CSF collection is feasible, with excellent participant acceptability and retention.
The MN protein is a newly described biomarker found to be overexpressed in most cervical carcinomas. This study was an effort to evaluate the prognostic importance of tumor MN expression, HPV status, and the presence of other biomarkers in cervical cancers. Tumor DNA and protein for study were extracted from archived frozen tissue. Tumor tissues and controls were evaluated by Western blot analysis for MN, intestinal alkaline phosphatase (IAP), c-myc, and p53 protein overexpression. Immunohistochemistry was performed for MN quantification and the study of expression patterns in histologic subtypes of cervical cancer. HPV data were obtained by PCR amplification of extracted DNA using consensus and type-specific primers. Clinical data were obtained from the patients' records and from the cancer registry. Clinical and molecular data were correlated by chi2, Fisher's exact test, and logistic regression. The results demonstrate that IAP is not overexpressed in clinical specimens of cervical carcinoma, although in somatic cell hybrid experiments, overexpression of IAP correlates with the malignant state. None of 47 tumors, including those which were HPV negative, overexpressed p53. c-myc protein overexpression occurred in 11 of 52 tumors, most of which contained HPV 16, but this was not significantly different from the tumors as a whole. There was no apparent association between MN protein expression and the overexpression of c-myc protein. MN was overexpressed in all cancers and quantitatively varied with the histologic subtype. Specifically, lower expression of MN correlated with adenosquamous and less-differentiated histology (P < 0.01 for grade 3 tumors). Low expression of MN protein also correlated with HPV negativity (P < 0.05). In stage IB and IIA cancers, low expression of MN was associated with deeper cervical stromal invasion (P < 0.03). Further, low expression of MN correlated with lymph node metastases in small (<3.5 cm) IB and IIA cervical cancers (P < 0.04). These data suggest that MN is emerging as a potentially important new biomarker for cervical carcinoma. The overexpression commonly seen in cervical cancer is possibly associated with loss of a critical tumor suppressor gene located on chromosome 11. Low expression of MN antigen appears to correlate with several adverse prognostic features and further prospective study is warranted.
Management of host responses to allografts by immunosuppressive therapy is the cornerstone of transplantation medicine, but it is still deficient in one important element: biomarkers that are readily accessible and predict the fate of the transplant early, specifically, and reliably. Using a Brown Norway (BN)-to-Lewis rat renal allograft model of kidney transplantation, this study aims at evaluating two proteomic approaches to discover biomarkers for acute rejection: SELDI-MS technology and 2D gel electrophoresis combined with mass spectrometry. Several novel potential serum biomarkers have been identified for follow up. Overall, the conclusion is that apparently at the serum protein level, dramatic changes only occur at a stage where kidney function is already severely affected. Multivariate analysis of serum profiles suggests that there is an ensemble of subtle changes, comprising a proteomic signature of acute rejection at an early stage, a more detailed evaluation of which might provide novel opportunities for the diagnosis of acute rejection. Profiling of the excreted proteins indicates that urine might even present the earliest signs of the rejection process.
Fine-needle aspiration (FNA) is a sensitive and cost-effective method for evaluating breast lesions. However, the diagnosis of early premalignant lesions is less reliable by FNA because of a lack of distinctive cytological features. Accurately defining the risk of such lesions at the individual level may have significant impact in breast cancer prevention and management. The main objective of this preliminary study was to develop a method to study multiple biomarkers on archival FNA slides using quantitative fluorescence image analysis (QFIA). Biomarkers p53, G-actin, and DNA content were labeled with an immunofluorescence technique and measured by QFIA simultaneously on a single cell basis. QFIA allows the labeling and measurement procedures to be carried out in situ, without the need to remove cells from the slide while preserving the morphology of the cells. FNA slides from 72 incident patients were obtained for this study. Fifty-six cases had an adequate number of cells for the actual analysis (25 benign breast lesions, 14 proliferative breast diseases with nuclear atypia, and 17 malignant lesions). The DNA content (> or = 5c) and G-actin (average gray mean, > 90) were positive in 81% and 88% of malignant lesions, respectively. These were significantly higher than the corresponding positive rates in benign lesions (7% and 15%, respectively; P <0.01 for both). None of the benign cases were positive for G-actin and DNA simultaneously, and none of the malignant cases were negative for G-actin and DNA together. p53 was positive in 33% of malignant lesions and 8% of benign lesions (P >0.05). Our study demonstrates the feasibility of evaluating multiple biomarkers by QFIA on archival FNA-fixed specimens. The G-actin and DNA content assayed by QFIA may be potential intermediate end point markers for breast cancer individual risk assessment.
The human placenta as a body component is exposed to several harmful substances, depending upon the environmental conditions encountered. In the case of toxic metals, placental tissue can be regarded as a dual biomarker to assess maternal and fetal health. The average range of concentrations for toxic trace elements in placenta based on wet weight are found to be: cadmium 1-6 ng/g; total mercury 2-13 ng/g; methyl mercury 1-14 microg/g; and lead 5-60 ng/g. The placenta appears to be at least a partial barrier for Cadmium. Cadmium transport includes a broad variety of mechanisms. Once in circulation, it mainly interferes with Ca and Zn transportation. On the other hand, placenta appears to be a weaker harrier for Pb than for Cd. In the case of Hg, predominantly the organic form is absorbed and readily crosses the placenta. In fetal blood, the organic mercury content is equal or even greater than in maternal blood, raising questions on normal fetal development. Placenta as a biomarker could be taken as an alternative to repeated maternal blood sampling for assessing lead exposure in utero. Placenta samples are usually obtained at the time of parturition, a one-time event. Hence, each pregnancy has to be looked upon as an RTM (real time monitoring) process since the affected species is exposed to the placental source of pollutants only during the course of that particular pregnancy.
Adverse drug effects are often associated with pathological changes in tissue. An accurate depiction of the undesired affected area, possibly supported by mechanistic data, is important to classify the effects with regard to relevance for human patients. MALDI imaging MS represents a new analytical tool to directly provide the spatial distribution and the relative abundance of proteins in tissue. Here we evaluate this technique to investigate potential toxicity biomarkers in kidneys of rats that were administered gentamicin, a well known nephrotoxicant. Differential analysis of the mass spectrum profiles revealed a spectral feature at 12,959 Da that strongly correlates with histopathology alterations of the kidney. We unambiguously identified this spectral feature as transthyretin (Ser(28)-Gln(146)) using an innovative combination of tissue microextraction and fractionation by reverse-phase liquid chromatography followed by a top-down tandem mass spectrometric approach. Our findings clearly demonstrate the emerging role of imaging MS in the discovery of toxicity biomarkers and in obtaining mechanistic insights concerning toxicity mechanisms.
Estrogen receptor (ER) assays have clinical relevance in selecting women who would benefit from endocrine intervention. As the degree of benefit from endocrine therapy is directly related to the quantity of receptor present in the tumour, the quality of the steroid receptor assays is important. Moreover, since patients entered in multi-centre trials often include stratification based on the receptor status, receptor assays should be comparable between different institutes. ER- and progesterone receptor (PgR)-assays have been evaluated in quality assessment studies for almost 20 years by the EORTC Receptor and Biomarker Study Group. This study analyses our findings over these years and concludes with a recommended minimum structure on which QA schemes for any biomarker could be based.