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PubMed2025

Transcriptomics-based exploration of ubiquitination-related biomarkers and potential molecular mechanisms in laryngeal squamous cell carcinoma.

BACKGROUND: One of the most common and prevalent cancers is laryngeal squamous cell carcinoma (LSCC), which poses a great threat to the life and health of the patient. Nonetheless, it has been demonstrated that ubiquitination is crucial for the development and course of LSCC. Therefore, it is particularly important to identify biomarkers for ubiquitination-related genes (UbRGs) in LSCC. METHODS: Differentially expressed genes (DEGs) in the LSCC versus controls were obtained by differential expression analysis. Also, key modular genes associated with LSCC were obtained using weighted gene co-expression network analysis (WGCNA). Next, DEGs, key module genes, and UbRGs were taken to intersect to obtain candidate genes. And then machine algorithms were to screen potential biomarkers, further their diagnostic value were analyzed and validated. Then, therapeutic agents for biomarkers were predict. In addition, the regulatory networks of the biomarkers were mapped. The expression levels of biomarkers were detected in clinical samples using reverse transcription-quantitative PCR (RT-qPCR). RESULTS: A total of eight candidate genes were acquired by the overlap 1,911 DEGs, the key modular genes of WGCNA, and 1,393 UbRGs. A sum of four biomarkers (WDR54, KAT2B, NBEAL2 and LNX1) were identified by two machine learning, then these four biomarkers were validated in GSE127165 and the expression trend was consistent with TCGA-LSCC, they were recorded as biomarkers. Moreover, the accuracy of the biomarkers in predicting clinical aspects of LSCC was confirmed by the receiver operating characteristic (ROC) curves. Subsequently, cancers such as malignant neoplasms, colorectal cancers, tumors, and primary malignant neoplasms were significantly associated with the biomarkers, which further suggests that these four biomarkers were strongly associated with cancer. Meanwhile, the drugs garcinol, cocaine, and triazolam, among others, used for LSCC treatment were predicted. Finally, transcription factors (TFs) (BRD4, MYC, AR, and CTCF) were predicted to regulate the biomarkers. RT-qPCR assays illustrated that the expression trends of KAT2B, LNX1 and NBEAL2 remained consistent with the dataset. CONCLUSION: The identification of four biomarkers (WDR54, KAT2B, NBEAL2 and LNX1) associated with UbRGs could ultimately serve as a predictive clinical diagnosis of LSCC and provide insight into the molecular mechanisms of LSCC.

Humans↗

PubMedDate not supplied

Development and use of biomarkers in oncology drug development.

Successful development and use of biomarkers will improve the productivity of oncology drug development. Recognition of the importance of biomarkers for speeding drug development is reflected in the precise definitions and concepts proposed by an NIH Working Group to standardize terminology and promote a more coherent and systematic approach to the development and use of biomarkers. Potential clinical biomarkers of drug efficacy are often identified through pre-clinical studies or basic research. Identification of potential biomarkers for use in oncology is moving rapidly forward through continuing advances in clinical imaging technologies, especially molecular and functional imaging. Other rapid advances are a product of the growing availability of new scientific reagents for established technologies and of high-throughput genomic and proteomic technologies that can generate hundreds of potential biomarkers for further evaluation. In certain cases, conventional clinical diagnostic techniques or assays can be adapted for use in pre-clinical models to evaluate their ability to serve as biomarkers for predicting clinical responses to new drug candidates. Evaluation (pre-clinical and clinical) of a potential biomarker is often the longest stage of biomarker development, and standards for evaluation or validation depend on the intended use and stage of clinical development. Biomarkers verified for use in preclinical studies can be used to help select appropriate animal models and lead compounds. Biomarkers verified for use in clinical trials can confirm a drug's pharmacological or biological mechanism of action, guide protocol design, aid patient and dose selection, and help to minimize safety risks. Oncology drug development can be optimized by using a tiered set of clinical biomarkers that predict compound efficacy and safety with increasing confidence at each rise in tier thereby aiding corporate decision-making about advancing compounds. In oncology, a special class of extensively evaluated biomarkers of efficacy (surrogate endpoints) that generally correlate with desired clinical outcomes can be used as a basis for corporate decisions as well as for gaining accelerated provisional regulatory approval of a drug.

Animals↗

PubMed1992

Intermediate endpoint biomarkers for chemoprevention.

The understanding of intermediate endpoint biomarker expression in relation to the sequential events in bladder tumorigenesis establishes a useful approach for evaluating chemopreventive agents. Biomarkers may be genotypic or phenotypic and function as biomarkers of susceptibility, exposure, effect, or disease. This paper reviews several years of research on biomarkers and their use in monitoring chemoprevention therapy. In initial animal experiments, mice were dosed with N-butyl-N-(4-hydroxybutyl)nitrosamine (OH-BBN) while co-administering N-(4-hydroxyphenyl)retinamide (4-HPR). 4-HPR did not statistically reduce tumor incidence, but did affect tumor differentiation and, consequently, nuclear size and DNA ploidy. These results suggest that nuclear size and ploidy may function as intermediate endpoint biomarkers of effect for oncogenesis and that epigenetic as well as genetic mechanisms may be primary in the oncogenic process. Early biomarkers of effect which occur prior to genetic effects or chromosome aberration may portend a higher probability of being modulated by differentiating agents such as retinoids. In vitro studies demonstrated that RPMI-7666 cells cultured with a phorbol ester tumor promoter (12-O-tetradecanoyl-phorbol-13-acetate) could be redifferentiated with 13-cis-retinoic acid and dimethyl sulfoxide (DMSO). F-actin, a cytoskeletal biomarker with a presumed function in the epigenetic mechanisms of carcinogenesis, could also be normalized in HL-60 cells treated with 4-HPR or DMSO. A clinical evaluation of F-actin in patients with varying degrees of risk confirmed the value of F-actin as a differentiating biomarker useful for bladder cancer risk assessment. The clarification of when the phenotypic changes of F-actin occur in the oncogenic process was achieved when a variety of biochemical changes were mapped in the patients with bladder cancer. These studies confirmed that G-actin, a reciprocal form of F-actin, is increased relatively early in bladder cancer oncogenesis when multiple biomarkers are quantitated in the field, adjacent area, and the tumor. Comparison of each individual biomarker's expression from field, adjacent to tumor, and tumor, and subsequent cluster analysis of these biomarkers, indicated that the possible sequence of phenotypic expression of biomarkers in bladder cancer oncogenesis is from G-actin, to p300 antigen, to epidermal growth factor receptor (EGFR), to p185 (neu oncogene product), to DNA aneuploidy and, finally, to visual morphology.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

PubMed2003

Biomarkers of human cutaneous squamous cell carcinoma from tissues and cell lines identified by DNA microarrays and qRT-PCR.

Squamous cell carcinoma (SCC) is the second most common form of skin cancer in Caucasians. Here we report on the identification of biomarkers of human cutaneous SCC cell lines in vitro and tissue samples in vivo using DermArray and PharmArray DNA microarrays, consisting of ca. 7400 unique human cDNAs. Differentially expressed genes were identified in two facial skin SCC cell lines (SCC 12 and SCC 13) compared to normal keratinocytes, and three cutaneous SCC tissue samples compared to normal skin. Quantitative validations of up- and down-regulated biomarkers were performed by qRT-PCR on 23 biomarker genes for the cell lines and 20 biomarker genes for the tumor tissues. In addition, three oral SCC cell lines were also included in the qRT-PCR validations for comparison, and the biomarker profiles were highly similar between the cutaneous and the oral SCC cell lines for all 23 biomarkers examined. The expression profiles for a variety of non-cutaneous SCC types, such as head-and-neck, oral, and lung, have been previously published. This report is the first to describe biomarkers for cutaneous SCC in two contexts, in vitro and in vivo. Although there was minimal overlap between the two different contexts using DNA microarrays, five genes were found common to both the cell lines and tissues, namely fibronectin 1, annexin A5, glyceraldehyde 3-phosphate dehydrogenase, zinc-finger protein 254, and huntingtin-associated protein interacting protein. Some of our previously published biomarkers of normal keratinocytes were down-regulated in SCC, suggestive of the dedifferentiated status of the transformed cells. While recent reports have identified some of the same genes as SCC biomarkers, for instance in head-and-neck cancer, thereby validating our approach, we have identified some novel biomarkers for cutaneous disease. These biomarker lists may be useful in molecular diagnostics of non-melanoma skin cancer, and a subset of the biomarkers might serve as suitable targets for drug discovery efforts of therapies for SCC.

Biomarkers, Tumor↗

PubMed2006

Screening and testing for endocrine disruption in fish-biomarkers as "signposts," not "traffic lights," in risk assessment.

Biomarkers are currently best used as mechanistic "signposts" rather than as "traffic lights" in the environmental risk assessment of endocrine-disrupting chemicals (EDCs). In field studies, biomarkers of exposure [e.g., vitellogenin (VTG) induction in male fish] are powerful tools for tracking single substances and mixtures of concern. Biomarkers also provide linkage between field and laboratory data, thereby playing an important role in directing the need for and design of fish chronic tests for EDCs. It is the adverse effect end points (e.g., altered development, growth, and/or reproduction) from such tests that are most valuable for calculating adverseNOEC (no observed effect concentration) or adverseEC10 (effective concentration for a 10% response) and subsequently deriving predicted no effect concentrations (PNECs). With current uncertainties, biomarkerNOEC or biomarkerEC10 data should not be used in isolation to derive PNECs. In the future, however, there may be scope to increasingly use biomarker data in environmental decision making, if plausible linkages can be made across levels of organization such that adverse outcomes might be envisaged relative to biomarker responses. For biomarkers to fulfil their potential, they should be mechanistically relevant and reproducible (as measured by interlaboratory comparisons of the same protocol). VTG is a good example of such a biomarker in that it provides an insight to the mode of action (estrogenicity) that is vital to fish reproductive health. Interlaboratory reproducibility data for VTG are also encouraging; recent comparisons (using the same immunoassay protocol) have provided coefficients of variation (CVs) of 38-55% (comparable to published CVs of 19-58% for fish survival and growth end points used in regulatory test guidelines). While concern over environmental xenoestrogens has led to the evaluation of reproductive biomarkers in fish, it must be remembered that many substances act via diverse mechanisms of action such that the environmental risk assessment for EDCs is a broad and complex issue. Also, biomarkers such as secondary sexual characteristics, gonadosomatic indices, plasma steroids, and gonadal histology have significant potential for guiding interspecies assessments of EDCs and designing fish chronic tests. To strengthen the utility of EDC biomarkers in fish, we need to establish a historical control database (also considering natural variability) to help differentiate between statistically detectable versus biologically significant responses. In conclusion, as research continues to develop a range of useful EDC biomarkers, environmental decision-making needs to move forward, and it is proposed that the "biomarkers as signposts" approach is a pragmatic way forward in the current risk assessment of EDCs.

Algorithms↗

PubMed2005

Utilisation of human pharmacology studies with biomarkers for new drug applications in Japan.

OBJECTIVE: This study evaluated the utilisation of human pharmacology studies with biomarkers for either efficacy or safety estimation conducted for new drug applications (NDAs) submitted to the Japanese regulatory authority, the Ministry of Health, Labour and Welfare (MHLW). METHODS: A total of 50 new chemical entities (NCEs) posted on the Websites, which were approved from June 2000 to November 2001, were evaluated by investigating their approval information. The utilisation of human pharmacology studies with biomarkers was evaluated by focusing on the classification referred to biomarkers for either efficacy or safety estimation and timing of studies. RESULTS: The human pharmacology studies with biomarkers for either efficacy or safety estimation were conducted in 20 compounds classified by utilising measures of either efficacy (17 compounds) or safety (seven compounds). In 4 of 17 NCEs, some of the biomarkers in human pharmacology studies were similar to the clinical endpoints for efficacy assessment in therapeutic exploratory and/or therapeutic confirmatory studies. For safety assessment in therapeutic exploratory and/or therapeutic confirmatory studies, clinical endpoints rather than biomarkers in human pharmacology studies were used in all seven NCEs. The timing of each type of clinical study could only be obtained for 15 NCEs. Of these 15 NCEs, human pharmacology studies with biomarkers for either efficacy or safety estimation were conducted on six compounds. There were only two compounds for which human pharmacology studies with biomarkers for efficacy estimation were conducted before pivotal studies such as a therapeutic exploratory study or a bridging study. CONCLUSION: Our survey suggests that with Japanese NDAs, human pharmacology studies with biomarkers for either efficacy or safety estimation do not play a key role in accelerating drug development and maximising the knowledge gained from confirmatory trials. The relationship between a biomarker and a clinical endpoint should be investigated appropriately for accelerating drug development. We think that the utilisation of human pharmacology studies with biomarkers for either efficacy or safety estimation in the regulatory review process for NDAs should be encouraged with the advancements of drug evaluation research using an appropriate biomarker based on clinical pharmacology.

Biomarkers↗

PubMed2004

Genotypic and phenotypic biomarker profiles for individual risk assessment and cancer detection (lessons from bladder cancer risk assessment in symptomatic patients and workers exposed to benzidine).

There is a need for improved methods for detecting individuals at risk for cancer to target subsets of patients for more intensive individual screening and targeted cancer therapy and chemoprevention. One approach for accomplishing this objective is to detect premalignant molecular fingerprints in an organ at risk for cancer or to define biomarkers reflective of treatment selection and response. Bladder cancer is an excellent model for testing this approach; however, comprehending the strategy for biomarker selection and analysis is more complicated than is generally appreciated. The objective of this article is to provide a succinct overview of our experience with the selection of biomarkers for bladder cancer detection, first in symptomatic patients and then in high-risk cohorts of workers at risk for bladder cancer. Biomarker selection depends on multiple parameters, each of which must be optimized to enhance the utility of a biomarker for clinical application. Many markers that initially show promise fail in the clinical arena for a variety of reasons. Important parameters include when a biomarker is expressed in carcinogenesis (i.e., early vs. late), the sample type, and the method of analysis. These all contribute to the sensitivity, specificity, and ultimate clinical utility of a biomarker. New technologies/ support the notion that all diseases start in the cell, and Seymore West indicated the cell, under appropriate conditions, can function as a microcuvette for biophysical cytochemical analysis. Spectroscopy provides an accurate and sensitive method for quantitative single-cell proteomics. Improved and more stable fluorescence probes will enhance the utility of cellular chemistry, as will a rationale approach for biomarker selection based on the concepts of field cancerization, complemented by improved quantitative analysis of protein markers at the single-cell level. Our laboratory has developed a platform for single-cell proteomic analysis that can be applied to multiple basic science and clinical problems. Single-cell proteomics also facilitates the study of genetic instability and epigenetic signaling (stromal-epithelial interactions) in relation to cancer therapy and diagnosis. Because most cancers arise through multiple signaling pathways and are heterogeneous, the identification of appropriate biomarker profiles provides a number of strategic advantages over a single biomarker. Complex networks of signaling pathways lead to increased cell proliferation, decreased cell adhesion, cellular differentiation, genetic instability, and other functions associated with the malignant phenotype. The purpose of this presentation is to illustrate the fundamental concepts for selection and profile analysis of high-level phenotypic biomarkers developed for bladder cancer risk assessment, screening, and early bladder cancer detection.

Benzidines↗

PubMed2005

Method validation and measurement of biomarkers in nonclinical and clinical samples in drug development: a conference report.

Biomarkers are increasingly used in drug development to aid scientific and clinical decisions regarding the progress of candidate and marketed therapeutics. Biomarkers can improve the understanding of diseases as well as therapeutic and off-target effects of drugs. Early implementation of biomarker strategies thus promises to reduce costs and time-to-market as drugs proceed through increasingly costly and complex clinical development programs. The 2003 American Association of Pharmaceutical Sciences/Clinical Ligand Assay Society Biomarkers Workshop (Salt Lake City, UT, USA, October 24-25, 2003) addressed key issues in biomarker research, with an emphasis on the validation and implementation of biochemical biomarker assays, covering from preclinical discovery of efficacy and toxicity biomarkers through clinical and postmarketing implementation. This summary report of the workshop focuses on the major issues discussed during presentations and open forums and noted consensus achieved among the participants on topics from nomenclature to best practices. For example, it was agreed that because reliable and accurate data provide the basis for sound decision making, biomarker assays must be validated in a manner that enables the creation of such data. The nature of biomarker measurements often precludes direct application of regulatory guidelines established for clinical diagnostics or drug bioanalysis, and future guidance on biomarker assay validation should therefore be adaptable enough that validation criteria do not stifle creative biomarker solutions.

Biological Assay↗

PubMed2001

Strategy for identifying biomarkers of aging in long-lived species.

If effective anti-aging interventions are to be identified for human application, then the development of reliable and valid biomarkers of aging are essential for this progress. Despite the apparent demand for such gerotechnology, biomarker research has become a controversial pursuit. Much of the controversy has emerged from a lack of consensus on terminology and standards for evaluating the reliability and validity of candidate biomarkers. The initiation of longitudinal studies of aging in long-lived non-human primates has provided an opportunity for establishing the reliability and validity of biomarkers of aging potentially suitable for human studies. From the primate study initiated in 1987 at the National Institute on Aging (NIA), the following criteria for defining a biomarker of aging have been offered: (1) significant cross-sectional correlation with age; (2) significant longitudinal change in the same direction as the cross-sectional correlation; (3) significant stability of individual differences over time. These criteria relate to both reliability and validity. However, the process of validating a candidate biomarker requires a greater standard of proof. Ideally, the rate of change in a biomarker of aging should be predictive of lifespan. In short-lived species, such as rodents, populations differing in lifespan can be identified, such as different strains of rodents or groups on different diets, such as those subjected to calorie restriction (CR), which live markedly longer. However, in the NIA primate study, the objective is to demonstrate that CR retards the rate of aging and increases lifespan. In the absence of lifespan data associated with CR in primates, validation of biomarkers of aging must rely on other strategies of proof. With this challenge, we have offered the following strategy: If a candidate biomarker is a valid measure of the rate of aging, then the rate of age-related change in the biomarker should be proportional to differences in lifespan among related species. Thus, for example, the rate of change in a candidate biomarker of aging in chimpanzees should be twice that of humans (60 vs 120 years maximum lifespan); in rhesus monkeys three times that of humans (40 vs 120 years maximum lifespan). The realization of this strategy will be aided by developing a primate aging database, a project that was recently launched in cooperation with the NIA, the National Center for Research Resources, and the University of Wisconsin Regional Primate Research Center.

Aging↗

PubMed2003

Biomarkers in Barrett's esophagus.

This article provides a framework for clinicians who are attempting the difficult task of interpreting the Barrett's biomarker literature with the goal of improving care for their patients. Although many articles. including more that 60 proposed biomarkers, have been published on this subject, only a few describe phase 3 and 4 studies that are of interest to the clinical gastroenterologist (Table 1). For year, dysplasia grade has been the sole means of risk stratification for patients with BE, and it likely will continue to be used in the foreseeable future. The current authors believe that dysplasia classification can be valuable using the team management approach and quality controls described previously. Significant problems, however, have emerged in phase 2 through 4 studies of dysplasia that make it imperative for the Barrett's field to incorporate additional biomarkers as they are validated. These problems include poor reproducibility of dysplasia interpretations, poor predictive value for negative, indefinite, and low-grade dysplasia, and inconsistent results for HGD in different centers, all of which makes it virtually impossible to develop national guidelines for surveillance. Some studies have even suggested that endoscopic biopsy surveillance using dysplasia may not be worthwhile. Currently, flow cytometric tetraploidy and aneuploidy have progressed furthest in biomarker validation (see Table 1). With proper handling, endoscopic biopsy specimens can be shipped to reference laboratories that have the instruments, computer analytic methods, and expertise to reproducibly detect tetraploidy and aneuploidy. The results of phase 4 studies indicate that flow cytometry appears to be useful in detecting a subset of patients who do not have HGD and yet have an increased risk of progression to cancer that cannot be identified by dysplasia grade. For many reasons, the authors anticipate that the number of validated biomarkers will increase substantially in the future. Biopsy repositories are now readily available for phase 3 studies that can evaluate and compare biomarkers. There are initiatives for multi-institutional Barrett's Centers of Excellence that could provide rapid progress in biomarker evaluation. In addition to new candidate biomarkers, the human genome project has provided high-throughput methodologies and methods for computer analysis of data, which can provide the volume and quality control required for clinically useful biomarkers. Currently, 17p (p53) LOH has progressed the furthest among molecular biomarkers. The authors do not recommend its routine clinical use at the present time, however. Finally, it is likely that clinicians will want to follow the results of clinical treatment-response studies and epidemiologic studies that evaluate relationship between clinical interventions or environmental risk and protective factors and surrogate endpoints, especially if the endpoints are progessing well along the phases of biomarker validation. These studies are likely to be of clinical interest because they may becoming the basis for randomized clinical trials to prevent cancer in BE.

Adenocarcinoma↗

PubMed2002

Biomarkers in cancer screening: a public health perspective.

The last three decades have witnessed a rapid advancement and diffusion of technology in health services. Technological innovations have given health service providers the means to diagnose and treat an increasing number of illnesses, including cancer. In this effort, research on biomarkers for cancer detection and risk assessment has taken a center stage in our effort to reduce cancer deaths. For the first time, scientists have the technologies to decipher and understand these biomarkers and to apply them to earlier cancer detection. By identifying people at high risk of developing cancer, it would be possible to develop intervention efforts on prevention rather than treatment. Once fully developed and validated, then the regular clinical use of biomarkers in early detection and risk assessment will meet nationally recognized health care needs: detection of cancer at its earliest stage. The dramatic rise in health care costs in the past three decades is partly related to the proliferation of new technologies. More recent analysis indicates that technological change, such as new procedures, products and capabilities, is the primary explanation of the historical increase in expenditure. Biomarkers are the new entrants in this competing environment. Biomarkers are considered as a competing, halfway or add-on technology. Technology such as laboratory tests of biomarkers will cost less compared with computed tomography (CT) scans and other radiographs. However, biomarkers for earlier detection and risk assessment have not achieved the level of confidence required for clinical applications. This paper discusses some issues related to biomarker development, validation and quality assurance. Some data on the trends of diagnostic technologies, proteomics and genomics are presented and discussed in terms of the market share. Eventually, the use of biomarkers in health care could reduce cost by providing noninvasive, sensitive and reliable assays at a fraction of the cost of definitive technology, such as CT scan. The National Cancer Institute's Early Detection Research Network (EDRN) has begun an innovative, investigator-initiated project to improve methods for detecting the biomarkers of cancer cells. The EDRN is a consortium of more than 32 institutions to link discovery of biomarkers to the next steps in the process of developing early detection tests. These discoveries will lead to early clinical validation of tests with improved accuracy and reliability.

Biomarkers↗

PubMedDate not supplied

Cerebrospinal fluid biomarkers in primary headache disorders.

OBJECTIVE: The object of this review is to examine the published literature for cerebrospinal fluid laboratory measures of primary headache disorders to identify biomarkers and provide recommendations for future biomarker discovery. BACKGROUND: Biomarkers may distinguish deviation from a normal state, provide insight into mechanisms of pathophysiology, quantify the degree of change, discriminate what may be clinically overlapping disorders, and allow monitoring and/or selection of specific treatment. High-throughput, discovery technologies fuel the ability to reveal more biomarkers than past hypothesis-driven studies. DESIGN OR METHODS: Publications were identified in PubMed, ISI web of knowledge (both Web of Science and BIOSYS), and SciFinder, using the key words for cerebrospinal fluid (CSF) and migraine, headache, or biomarkers. Additional references were sought from the papers identified in these searches. Data were assessed relating to all primary headache types for clinical and scientific methods and results. RESULTS: Fifty-five out of 82 biomarkers were found from 55 publications, though none have been validated for clinical utility. Data for site (ventricular, cervical, lumbar) and timing of CSF collection, headache state, and diagnostic description were patchy, and controls were often poorly defined. Most routinely performed CSF measurements were within normal limits. Most levels of pain-related molecules were reduced, and concentrations of most neurotransmitters, neuropeptides, proteins, and small molecules were increased. Though few studies assessed the specificity of biomarkers for primary headaches, it is clear that there are differences in CSF biomarkers between migraine, cluster headache, tension-type headache, and trigeminal neuralgia. CONCLUSIONS: The high proportion (67%) of biomarkers identified from laboratory measures tested thus far predicts that many more biomarkers will be identified for primary headaches when more candidates are evaluated. In order to discover and evaluate more biomarkers, especially those that may have clinical application for headache management, 3 recommendations are encouraged: prospective design of care-independent studies; evaluation of more clinical variables; and evaluation of substantially more candidates by using discovery-based research methods. Outlines of approaches to pursue these aims are proposed.

Biomarkers↗

PubMed2002

Overview of biomarkers and surrogate endpoints in drug development.

There are numerous factors that recommend the use of biomarkers in drug development including the ability to provide a rational basis for selection of lead compounds, as an aid in determining or refining mechanism of action or pathophysiology, and the ability to work towards qualification and use of a biomarker as a surrogate endpoint. Examples of biomarkers come from many different means of clinical and laboratory measurement. Total cholesterol is an example of a clinically useful biomarker that was successfully qualified for use as a surrogate endpoint. Biomarkers require validation in most circumstances. Validation of biomarker assays is a necessary component to delivery of high-quality research data necessary for effective use of biomarkers. Qualification is necessary for use of a biomarker as a surrogate endpoint. Putative biomarkers are typically identified because of a relationship to known or hypothetical steps in a pathophysiologic cascade. Biomarker discovery can also be effected by expression profiling experiment using a variety of array technologies and related methods. For example, expression profiling experiments enabled the discovery of adipocyte related complement protein of 30 kD (Acrp30 or adiponectin) as a biomarker for in vivo activation of peroxisome proliferator-activated receptors (PPAR) gamma activity.

Adiponectin↗

PubMed2007

ProteinChip array profiling for identification of disease- and chemotherapy-associated biomarkers of nasopharyngeal carcinoma.

BACKGROUND: We previously used ProteinChip array profiling analysis to discover a serum biomarker associated with nasopharyngeal carcinoma (NPC). In this study, we used the same method to examine other biomarkers associated with NPC and response to chemotherapy (CT) in NPC patients. METHODS: We performed ProteinChip array analysis in 209 serum samples from 66 relapsed patients before and after salvage CT with gemcitabine and cisplatin or etoposide and cisplatin combinations, 11 patients in remission, and 35 healthy individuals. Intensities of the biomarker peaks were correlated with CT response of the patients and other clinical parameters. RESULTS: We discovered 13 candidate biomarkers associated with different clinical parameters. Two biomarkers (2803 and 3953 Da) were significantly increased in patients compared with controls at all stages of disease. Analysis of pre- and post-CT paired serum samples revealed 7 biomarkers correlated with impact of CT. Of these 7 biomarkers, 2 (2509 and 2756 Da) were significantly increased and 5 (7588, 7659, 7765, 7843, and 8372 Da) were significantly decreased post-CT in either 1 or both CT cohorts. Four biomarkers from pre-CT sera were correlated with CT response, with 3 (2950, 13 510, and 14 855 Da) being significantly decreased and 1 (6701 Da) significantly increased in patients who did not respond to CT. Tandem mass spectrometric sequencing and/or immunoaffinity capture assay identified the 3953 Da biomarker as a fragment of interalpha-trypsin inhibitor precursor and 7765 Da biomarker as platelet factor-4. CONCLUSIONS: Treatment-associated serum biomarkers found might serve to triage NPC patients for appropriate CT treatment.

Adult↗

PubMed2005

Upper reference limits for biomarkers of exposure to aromatic diisocyanates.

OBJECTIVES: The objectives of this study were to determine the levels of 2,4-toluenediamine, 2,6-toluenediamine, 1,5-naphthtalenediamine and 4,4'-methylenediphenyldianiline in hydrolyzed urine and plasma for occupationally unexposed workers and to calculate upper reference limits (URLs). These analytes are biomarkers of exposure to 2,4-toluene diisocyanate and 2,6-toluene diisocyanate (2,4-TDI and 2,6-TDI), 1,5-naphtalene diisocyanate (NDI) and 4,4'-methylenediphenyl diisocyanate (MDI), respectively. METHODS: The biomarker levels were determined in urinary and plasma samples obtained from 121 occupationally unexposed workers. Based on these biomarkers levels and the biomarker levels in an occupationally exposed group of workers, URLs were calculated. The method used for these calculations was based on the receiver operator characteristic (ROC) curve method technique, and the URLs were set at the optimum of sum of sensitivity and specificity. RESULTS: The URLs for the different diisocyanates were calculated to be in the range of 0.1-0.5 microg/L. Occupationally unexposed workers had detectable biomarker levels of the diisocyanates investigated. Especially abundant was the biomarkers of MDI which were found in 97% of both urinary and plasma samples. For the other biomarkers, 0-15% of the unexposed workers had detectable levels. The detected levels were mostly close to the limit of detection (LOD), but urinary levels of biomarkers of MDI up to 60 times the LOD were found. The sensitivities and specificities for classification of the workers as occupationally exposed or not, were in the range of 88-100% and 97-100%, respectively. CONCLUSIONS: The URLs were calculated that may be applicable when screening for occupational exposure. A worker with a biomarker level above the URL will be classified as occupationally exposed. Biomarkers of aromatic diisocyanates, especially biomarkers of MDI, were present among occupationally unexposed workers, but the source and nature of the exposure is unknown.

Adult↗

PubMed1995

Role of biomarkers of exposure in the assessment of health risks.

Biomarkers of exposure can be used as part of an exposure assessment to assess potential health risks when exposure measurements and health effects occur during the same period of time. Exposure assessment is the determination of the concentration of a chemical in an environmental medium coupled with the presence of the human in that environment. A biomarker of exposure gives an assessment of absorbed dose in the worker. A biomarker of effect, often referred to as a biomarker, is used in the assessment of health risk. A biomarker of effect gives an assessment of the effect of a chemical on a physiological process and is an indicator of a possible adverse health effect. For example, biomarkers of exposure give an assessment of a worker's current exposure to solvents and some metals. Biomarkers of exposure for chronic health effects with long latent periods, such as carcinogens, are more problematical. These exposure indicators, however, can be used to help reconstruct past exposures. Selected biomarkers of exposure can also be predictors of adverse health effects. Examples include the use of 2,5-hexanedione and 2-ethoxyacetic acid in urine as indicators of exposure to n-hexane and 2-ethoxyethanol, respectively. These two urinary metabolites are 'active' metabolites responsible for observed neurotoxic and reproductive effects. Biomarkers of exposure are particularly useful for the objective assessment of current systemic exposure to chemicals that are readily absorbed through the skin. Exposure assessments, including the use of biomarkers of exposure, are necessary to postulate a cause of observed adverse health effects seen in epidemiological investigations and to determine the bioavailability of the chemicals present in the workplace.

Biomarkers↗

PubMed2005

The use of biomarkers in surveillance, medical screening, and intervention.

Building on mechanistic information, much of molecular epidemiologic research has focused on validating biomarkers, that is, assessing their ability to accurately indicate exposure, effect, disease, or susceptibility. To be of use in surveillance, medical screening, or interventions, biomarkers must already be validated so that they can be used as outcomes or indicators that can serve a particular function. In surveillance, biomarkers can be used as indicators of hazard, exposure, disease, and population risk. However, to obtain rates for these measures, the population at risk will need to be assessed. In medical screening, biomarkers can serve as early indicators of disease in asymptomatic people. This allows for the identification of those who should receive diagnostic confirmation and early treatment. In intervention (which includes risk assessment and communication, risk management, and various prevention efforts), biomarkers can be used to assess the effectiveness of a prevention or control strategy as well as help determine whether the appropriate individuals are assigned to the correct intervention category. Biomarkers can be used to provide group and individual risk assessments that can be the basis for marshalling resources. Critical for using biomarkers in surveillance, medical screening, and intervention is the justification that the biomarkers can provide information not otherwise accessible by a less expensive and easier-to-obtain source of information, such as medical records, surveys, or vital statistics. The ability to use validated biomarkers in surveillance, medical screening, and intervention will depend on the extent to which a strategy for evidence-based procedures for biomarker knowledge transfer can be developed and implemented. This will require the interaction of researchers and decision-makers to collaborate on public health and medical issues.

Biomarkers↗

PubMed2026

Predictive Biomarkers for Immune Checkpoint Inhibitor Efficacy: Challenges, Innovations, and a Pathway to Precision Medicine in the Era of Cancer Immunotherapy.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed oncology practice. However, treatment response remains heterogeneous, rendering predictive biomarkers critical for optimal patient care. The 3 established biomarkers, programmed death-ligand 1, tumor mutational burden (TMB), and microsatellite instability-high/deficient mismatch repair, are approved and clinically validated but are modest predictors of benefit. As a result, multiple novel predictive biomarkers remain under investigation. CONTENT: This review highlights established and investigational predictive ICI efficacy biomarkers. For established biomarkers, we describe biology, assay modalities, approved companion diagnostics, landmark studies, and notable limitations. Due to the multisystem nature of antitumor immune effects, investigational biomarkers span multiple domains, including tumor genomic biomarkers (e.g., mutational signatures, TMB, neoantigen clonality), tumor microenvironment (e.g., tumor-infiltrating lymphocytes [TILs], tertiary lymphoid structures), systemic immune biomarkers (e.g., cytokines, autoantibodies, glycoproteins, peripheral blood mononuclear cells), and the microbiome (e.g., gastrointestinal microbial diversity, responder-enriched taxa). SUMMARY: The established biomarkers PD-L1, TMB, and microsatellite instability-high/deficient mismatch repair inform ICI use in clinical practice but have important limitations. Multiple investigational biomarkers show promise in refining patient selection and optimizing therapy. Moving forward, increased assay harmonization, prospective validation, and standardized parameters may improve performance. Composite models integrating complementary signals across domains may further individualize treatment and lead to an era of personalized cancer immunotherapy.

Humans↗