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PubMed2026

Development of a Computational Histology Artificial Intelligence-Powered Prognostic Biomarker in Colorectal Cancer in The Cancer Genome Atlas.

BACKGROUND: Risk stratification in colorectal cancer (CRC) plays an important role in treatment decision-making. As such, prognostic biomarkers that can augment risk stratification have clinical value. Quantitative histologic features from routine hematoxylin and eosin (H&E)-stained whole slide images (WSIs) provide a novel avenue for biomarker discovery. In this study, we explored the potential for a computational histology artificial intelligence (CHAI) platform to develop and validate a prognostic biomarker in CRC. METHODS: The Cancer Genome Atlas Colorectal Adenocarcinoma project was utilized for this study, with inclusion of all subjects (stage I-IV) with available digitized H&E specimens. The cohort was split into development and validation cohorts by a stratified random split. The previously developed CHAI platform was applied in the development cohort to construct a continuous risk score from histologic features associated with progression-free interval (PFI) that was dichotomized based on an optimized cutpoint for distinguishing PFI into a high risk CHAI (+) and lower risk CHAI (-). PFI was compared between CHAI (+) and CHAI (-) patients in the validation cohort in multivariable Cox proportional hazards models. Time-dependent area under the curve (tdAUC) and C-indices were also calculated for PFI. RESULTS: A total of 583 participants were included in the study, with 409 assigned to the validation cohort. The CHAI biomarker classified 229 participants (56%) as CHAI (+) and 180 (44%) as CHAI (-) in the validation set. CHAI (+) participants had worse PFI in a multivariable analysis adjusting for available clinicopathologic variables (hazard ratio (HR) = 2.65; 95% confidence interval (CI), 1.63-4.30). TdAUC for the CHAI biomarker was 0.60 (95% CI, 0.53-0.67) at 12 months, 0.62 (0.55-0.69) at 36 months, and 0.67 (0.55-0.79) at 60 months; the C-index was 0.62 (95% CI, 0.58-0.67). CONCLUSIONS: The CHAI platform was used to develop a prognostic digital pathology biomarker in CRC. This demonstrates the feasibility and potential to apply this artificial intelligence-based digital pathology biomarker platform for risk stratification in CRC and supports its further study.

Artificial intelligence↗
PubMed2000

Biomarkers for monitoring efficacy of bioremediation by microbial inoculants.

Bioaugmentation of contaminated sites with microbes that are adapted or genetically engineered for degradation of specific toxic compounds is an area that is currently being explored as a clean-up option. Biomarkers have been developed to track the survival and efficacy of specific bacteria that are used as inocula for bioremediation of contaminated soil. Examples of biomarkers include the luc gene, encoding firefly luciferase and the gfp gene, encoding the green fluorescent protein (GFP). The luc gene was used to tag different bacteria used for bioremediation of gasoline or chlorophenols. The bacteria were monitored on the basis of luciferase activity in cell extracts from soil. The gfp gene was also used to monitor bacteria during degradation of chlorophenol in soil, based on fluorescence of the GFP protein. Other biomarkers can also be used for monitoring of microbial inocula used for bioaugmentation of contaminated sites. The choice of biomarker and monitoring system depends on the particular site, bacterial strain and sensitivity and specificity of detection required.

Journal Article↗
PubMed2005

Biomarker-based risk assessment model in acute pulmonary embolism.

AIMS: Despite growing interest in biomarkers application for risk evaluation in acute pulmonary embolism (APE), no decision-making levels have been defined. METHODS AND RESULTS: We developed a biomarker-based risk stratification in 100 consecutive, normotensive on admission, APE patients (35 males, 65 females, 62+/-18 years). On admission serum NT-proBNP and cardiac troponin T (cTnT) levels were assessed and echocardiography was performed. All-cause 40-day mortality was 15% and APE mortality was 8%. In univariable analysis, cTnT>0.07 microg/L predicted all-cause mortality, hazard ratio (HR) 9.2 (95% CI: 3.3-26.1, P<0.0001), and APE mortality, HR 18.1 (95% CI: 3.6-90.2, P=0.0004); similarly, NT-proBNP>7600 ng/L predicted all-cause and APE mortalities [HR 6.7 (95% CI: 2.4-19.0, P=0.0003) and 7.3 (95% CI: 1.7-30.6, P=0.007)]. NT-proBNP<600 ng/L indicated uncomplicated outcome. Multivariable analysis revealed that cTnT>0.07 microg/L was the most significant independent predictor, whereas NT-proBNP and systemic systolic blood pressure measured on admission and echocardiographic parameters were non-significant. APE mortality in patients with NT-proBNP> or =600 ng/L and cTnT> or =0.07 microg/L reached 33%. NT-proBNP<600 ng/L indicated group without deaths. APE mortality for patients with NT-proBNP> or =600 ng/L and cTnT<0.07 microg/L was 3.7%. Incorporation of echocardiographic data did not improve group selection. CONCLUSION: Simultaneous measurement of serum cTnT and NT-proBNP allows for precise APE prognosis. Normotensive patients on admission with cTnT> or =0.07 microg/L and NT-proBNP> or =600 ng/L are at high risk of APE mortality, whereas NTproBNP<600 ng/L indicates excellent prognosis.

Acute Disease↗
PubMed2004

Gene expression profiling identifies platelet-derived growth factor as a diagnostic molecular marker for papillary thyroid carcinoma.

PURPOSE: Cancer diagnostics and therapeutics are often based on clinically relevant markers that are expressed specifically in a malignant tissue at levels higher than in normal tissue. We examined potential markers for papillary thyroid carcinoma (PTC) by monitoring PTC-specific gene expression using cDNA microarray. EXPERIMENTAL DESIGN: Gene expression profiles for PTC tissue, normal thyroid tissue, and healthy peripheral blood cells were compared by use of a human 4000-gene cDNA microarray. Protein expressions of the up-regulated genes in PTC were examined in thyroid tissues by immunohistochemistry. RESULTS: Sixty-four genes were overexpressed in PTC tissue relative to normal thyroid tissue and healthy peripheral blood cells. The genes that were up-regulated in PTC were involved in cell cycle regulation, DNA damage response, angiogenesis, and oncogenesis. Among these genes, basic fibroblast growth factor and platelet-derived growth factor were identified by immunochemical methods as proteins that are specifically expressed at high levels in thyroid neoplasms. Basic fibroblast growth factor, which has been identified as a biomarker for PTC, was overexpressed in 54% of PTC cases, 67% of follicular thyroid carcinomas, and 36% of benign thyroid neoplasms. Platelet-derived growth factor was overexpressed in 81% of PTC cases and 100% of follicular carcinomas, but was immunonegative in normal thyroid tissues and benign thyroid neoplasms. CONCLUSIONS: Platelet-derived growth factor may be a potential biomarker for PTC and follicular carcinoma. Expression profile analysis using a microarray followed by immunohistochemical study can be used to facilitate the development of molecular biomarkers for cancer.

Carcinoma, Papillary↗
PubMed2005

Bioinformatics in microbial biotechnology--a mini review.

The revolutionary growth in the computation speed and memory storage capability has fueled a new era in the analysis of biological data. Hundreds of microbial genomes and many eukaryotic genomes including a cleaner draft of human genome have been sequenced raising the expectation of better control of microorganisms. The goals are as lofty as the development of rational drugs and antimicrobial agents, development of new enhanced bacterial strains for bioremediation and pollution control, development of better and easy to administer vaccines, the development of protein biomarkers for various bacterial diseases, and better understanding of host-bacteria interaction to prevent bacterial infections. In the last decade the development of many new bioinformatics techniques and integrated databases has facilitated the realization of these goals. Current research in bioinformatics can be classified into: (i) genomics--sequencing and comparative study of genomes to identify gene and genome functionality, (ii) proteomics--identification and characterization of protein related properties and reconstruction of metabolic and regulatory pathways, (iii) cell visualization and simulation to study and model cell behavior, and (iv) application to the development of drugs and anti-microbial agents. In this article, we will focus on the techniques and their limitations in genomics and proteomics. Bioinformatics research can be classified under three major approaches: (1) analysis based upon the available experimental wet-lab data, (2) the use of mathematical modeling to derive new information, and (3) an integrated approach that integrates search techniques with mathematical modeling. The major impact of bioinformatics research has been to automate the genome sequencing, automated development of integrated genomics and proteomics databases, automated genome comparisons to identify the genome function, automated derivation of metabolic pathways, gene expression analysis to derive regulatory pathways, the development of statistical techniques, clustering techniques and data mining techniques to derive protein-protein and protein-DNA interactions, and modeling of 3D structure of proteins and 3D docking between proteins and biochemicals for rational drug design, difference analysis between pathogenic and non-pathogenic strains to identify candidate genes for vaccines and anti-microbial agents, and the whole genome comparison to understand the microbial evolution. The development of bioinformatics techniques has enhanced the pace of biological discovery by automated analysis of large number of microbial genomes. We are on the verge of using all this knowledge to understand cellular mechanisms at the systemic level. The developed bioinformatics techniques have potential to facilitate (i) the discovery of causes of diseases, (ii) vaccine and rational drug design, and (iii) improved cost effective agents for bioremediation by pruning out the dead ends. Despite the fast paced global effort, the current analysis is limited by the lack of available gene-functionality from the wet-lab data, the lack of computer algorithms to explore vast amount of data with unknown functionality, limited availability of protein-protein and protein-DNA interactions, and the lack of knowledge of temporal and transient behavior of genes and pathways.

Journal Article↗
PubMed2006

Genomic-based biomarkers of drug-induced nephrotoxicity.

Typical drug development timelines are 10 - 15 years, with high attrition rates that make it difficult for companies to sustain productive pipelines. Investigational and discovery toxicology are novel and revolutionary extensions of the field of general toxicology, which has been created to fulfil the growing need for generating higher throughput, and integrative and predictive toxicological information, in an effort to reduce attrition. Included in this new paradigm is transcript profiling, and recent innovations have led some to speculate that genomics would help revolutionise drug development, as more better predictive biomarkers of organ damage would be identified. The kidney has been a focus of toxicogenomics investigations, and candidate genomic-based biomarkers of renal damage have been identified for rodent as well as nonhuman primate models of nephrotoxicity. This review highlights published results that have led to the preliminary identification of candidate genomic-based markers of nephrotoxicity and provides insight into the future of toxicogenomics.

Animals↗
PubMed1996

The quantitation of metabolites of quercetin flavonols in human urine.

The flavonoid quercetin, or its metabolites, inhibit chemical carcinogenesis in rodents and may have a role in the prevention of human cancers. Quercetin exposure in human populations results from the dietary intake of various plant foods; high concentrations of quercetin are found in apples, onions, tea, and red wine. Determination of the relationship between dietary intake and cancer risk depends on the characterization of quercetin intake. The development and use of biomarkers for quercetin intake may provide a basis for the objective classification of this exposure. One possible biomarker is metabolic products of quercetin. We report the development of a high-performance liquid chromatography (HPLC)-based assay for quantitation of quercetin metabolites in human urine. The metabolites include 3,4-dihydroxyphenylacetic acid (homoprotocatechuic acid), metahydroxyphenylacetic acid, and 4-hydroxy-3-methoxyphenylacetic acid (homovanillic acid). The assay has only two major steps, ether extraction and HPLC analysis, and is suitable for analysis of large sample numbers. Analytical characteristics of the assay include a sensitivity of less than 1 microgram, precision with coefficients of variation < 10%, and metabolite recoveries > 90%. The mean concentrations of 3,4-dihydroxyphenylacetic acid, metahydroxyphenylacetic acid, and homovanillic acid in two human urine samples are approximately 0.7, 4.8, and 2.8 micrograms/ml, respectively. The identification of each metabolite is confirmed by HPLC, UV absorbance scans, and gas chromatography-mass spectrometry analysis. These results verify the occurrence of quercetin metabolites in human urine and the feasibility of quercetin metabolite quantitation, by the assay described herein, for epidemiological studies. Development of the analytical procedure is an essential first step for validation of the metabolites as biomarkers of quercetin intake.

3,4-Dihydroxyphenylacetic Acid↗
PubMed1995

The role of biomarkers in derivation of WHO-guidance values for air pollutants.

The Air Quality Guidelines for Europe (AQG) have provided a basis for the control of air pollution, and have contributed to the maintenance and improvement of public health in several countries. The process of updating and revision of the AQG will be completed by 1996. The applicability of biomarkers for derivation of health-based guidelines will depend on the validation of biomarkers also at low (environmental) levels of exposure, the availability of adequate population studies using biomarker information, and the development of better quantitative relationships between ambient levels, biomarker concentrations and, ideally, effects.

Air Pollutants↗
PubMed2006

Toward biomarkers for chronic graft-versus-host disease: National Institutes of Health consensus development project on criteria for clinical trials in chronic graft-versus-host disease: III. Biomarker Working Group Report.

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.

Biomarkers↗
PubMed2000

Quantitative method for biomarkers of collagen degradation using liquid chromatography tandem mass spectrometry.

Preclinical efficacy testing commonly involves studies that require considerable resources and time. One valuable tool in this endeavor is the characterization of relevant biomarkers. A method has been developed for the simultaneous determination of collagen biomarker candidates as an instrument in screening compounds for efficacy. Two potential candidates, the 3-hydroxypyridinium crosslinks pyridinoline and deoxypyridinoline, were selected for analysis in collagen degradation models. Tissue or urine samples were collected, prepared, and quantitated for the biomarkers using spiked calibration curves and liquid chromatography tandem mass spectrometry. The development of a quick and simple assay method would allow us to increase the chances for success in efficacy screening by eliminating compounds with poor biomarker profiles. The method proposed here appears to be more selective, convenient, precise (generally <10% RSD), accurate (generally <10% RE), and sensitive relative to previously established methodology.

Amino Acids↗
PubMed2026

Predictive biomarkers in cancer immunotherapy for genitourinary malignancies.

Immunotherapy has transformed the management of genitourinary cancers, offering durable responses in selected patient groups. However, the clinical benefit of immune checkpoint inhibitors varies significantly across renal cell carcinoma, urothelial carcinoma, and prostate cancer, underscoring the need for reliable predictive biomarkers. This review summarizes current knowledge on established and emerging biomarkers, including PD L1 expression, tumor mutational burden, molecular subtypes, genomic alterations, tumor microenvironment characteristics, circulating biomarkers, microbiome influences, and multi omic integrative approaches. We discuss their potential clinical relevance, limitations, and applicability across different tumor types. Future directions emphasize the development of composite biomarkers, standardization of testing platforms, real time monitoring strategies, and the integration of advanced technologies such as artificial intelligence and spatial profiling. Understanding and validating these biomarkers will be essential for optimizing personalized immunotherapy in genitourinary cancers.

Circulating tumor DNA↗
PubMed1999

Single-photon emission computed tomography of the dopamine transporter in parkinsonism.

The known dopaminergic abnormalities in Parkinson's disease have facilitated the development of radiolabeled biomarkers for diagnostic and research applications in humans. Presynaptic, intrasynaptic, and postsynaptic imaging now is possible using single-photon emission computed tomography. In particular, the development of new radiotracers that target the dopamine transporter located on degenerating dopamine neurons in Parkinson's disease and related disorders is directly relevant to improved clinical diagnosis, disease monitoring, and assessment of putative neuroprotective strategies in patients. In addition, the ability to characterize in vivo neuronal degeneration in these disorders provides a powerful research tool to better understand the natural course of these disorders and could provide clues to etiology.

Brain↗
PubMed1998

Biomarkers for assessing human female reproductive health, an interdisciplinary approach.

Identification of environmental hazards to reproductive health and characterization of the adverse outcomes necessitate a multidisciplinary approach. Epidemiologic studies are required for the identification of adverse health effects in human populations and then to confirm that specific exposures are responsible. Clinical studies are required to develop assays for reproductive biomarkers and to validate these assays prior to their application in the field. Assays for field use must be formatted and streamlined for large-scale applications and, whenever possible, computer algorithms should be developed to interpret biomarker data. Appropriate animal models must be identified, biomarker assays validated for that model, and animal experiments conducted to identify the mode of action and target organ of a putative reproductive toxicant. Finally, in vitro studies at the level of the cell and cell organelle are essential for mechanisms for toxicity to be clearly identified and understood. In this article we describe the interdisciplinary approach that we have developed for study of the effects of environmental agents on female reproductive functions. This effort requires specific skills of toxicologists, epidemiologists, physicians, biochemists, and physiologists.

Adult↗
PubMed2003

The use of biomarkers in environmental monitoring programmes.

The monitoring of biological effects has recently become an integral component of environmental monitoring programmes as a supplement to the commonly used contaminant monitoring. Over the years, many biomarkers have been developed that are claimed to be efficient at providing an early warning of deleterious effects on biological systems and for estimating biological effects due to contaminants. Although biomarkers are potentially useful, they have a number of important limitations. In this paper, we examine some of the key assumptions behind the theory and practice of use of biomarkers, and propose a scheme, which may facilitate decisions by environmental managers as to how and when to use biomarkers in their monitoring programmes.

Animals↗
PubMed2025

Recent Advances in nccRCC Classification and Therapeutic Approaches.

Non-clear cell renal cell carcinoma (nccRCC) constitutes a biologically diverse category of renal malignancies. The 2022 WHO classification framework has significantly evolved to incorporate molecularly defined entities alongside traditional histologic subtypes, reflecting the growing recognition of distinct pathogenic drivers. Current therapeutic paradigms for advanced disease remain suboptimal, with treatment strategies often extrapolated from clear cell renal cell carcinoma (ccRCC). In this review, we highlight transformative multi-omics approaches to address nccRCC's profound heterogeneity, which enables molecular stratification beyond conventional pathology, identifying novel subtypes characterized by unique immune microenvironment features, metabolic profiles, and genomic instability patterns. This molecular reclassification provides a foundational framework for precision oncology, facilitating patient selection for targeted therapies and immunomodulatory strategies. Advancements in multi-omics subtyping represent a pivotal shift toward biologically guided clinical management and underscore the imperative for biomarker-driven therapeutic development in nccRCC.

Humans↗
PubMed2003

Identification and validation of a potential lung cancer serum biomarker detected by matrix-assisted laser desorption/ionization-time of flight spectra analysis.

Many abnormalities detected in the thorax by routine conventional imaging studies are benign, yet all require further evaluation because of the concern for cancer. To address this deficiency and develop a serum biomarker for lung cancer, we designed a matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) based platform to display the proteins present in the serum of patients with or without lung cancer, and then challenged the scientific community to analyze these data with the aim of determining specific ion signal differences among the resulting spectra. The most statistically significant ion peak identified by the various analysis algorithms that differentiated the serum of patients with lung cancer from the serum of individuals without lung cancer was found at m/z 11,702. We identified the protein responsible for this ion peak as serum amyloid A (SAA; M(r) = 11,682.7) by partial purification followed by in-gel digestion and peptide mapping. By enzyme-linked immunosorbent assay, we showed SAA to be present at 286 ng/mL in the serum of cancer patients vs. 34.1 ng/mL in the serum of individuals without cancer. These data suggest that the combination of MALDI-TOF MS and computer analysis can be a powerful tool in the search for serum biomarkers of lung cancer and other diseases.

Adenocarcinoma↗
PubMed1994

Fish as biomarkers in immunotoxicology.

This paper presents an overview on the state of the art in the development and application of biomarkers for immunotoxicology in fish. There are several reasons for developing this field: many fish diseases are related to environmental quality, various environmental pollutants have immunotoxic potential and many fish diseases have an immunological component. As in immunotoxicology in general, this aspect, in fish, has received ample attention in the recent past. Much benefit has been obtained from progress in related fields of science, such as fish immunology and rodent immunotoxicology. Meanwhile there is a broad spectrum of potential biomarkers for immunotoxicology in fish, from which macrophage parameters seem to be most widely used. The application of others, such as lymphoid cell parameters is still limited, probably due to practical problems such as lack of experience with conduct, validation and interpretation. Specific problems include the paucity of background data in the case of epidemiological field studies and the important role of other (non-chemical) stress factors in the immune response, and hence the lack of specificity of potential biomarkers.

Animals↗
PubMed2005

Oxidative stress and cyclooxygenase activity in prostate carcinogenesis: targets for chemopreventive strategies.

Over the last decade, epidemiological, experimental and clinical studies have implicated oxidative stress in the development and progression of prostate cancer. Oxidative stress may be linked to the effects of androgens, anti-oxidant systems and the pre-malignant condition, high-grade prostatic intraepithelial neoplasia. Cyclooxygenase-2 activity has been linked with prostate carcinogenesis. Evidence suggests that oxidative stress and cyclo-oxygenase-2 activity may be mechanistically linked. Agents such as anti-oxidants and cyclo-oxgenase-2 inhibitors may be of value in the chemoprevention of prostate cancer. The feasibility of intervention with such agents will depend on the development and validation of biomarkers for clinical trials, particularly markers of oxidative damage caused by reactive oxygen species (ROS). A greater understanding of the molecular events associated with oxidative stress will enhance the development of such biomarkers and should result in better strategies for the chemoprevention of prostate cancer.

Aged↗