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PubMed2005

Expression analysis of psychological stress-associated genes in peripheral blood leukocytes.

In this study, we have developed a microarray including 1467 cDNAs that were selected to specifically measure stress response in peripheral blood leukocytes. Venous blood was collected from 10 graduate students 2 h before and 2 or 24 h after an open presentation for their Ph.D. The mRNA levels in leukocytes were compared with those prepared 4 weeks before the presentation. Hierarchical cluster showed that distinct groups of genes uniformly changed their expression values in response to the stress. Bayesian t test identified significantly up-regulated 49 genes and down-regulated 21 genes. Most of them are categorized into cytokines, cytokine receptors, growth- or apoptosis-related molecules, and heat shock proteins, suggesting that stressful life events trigger acute responses in leukocytes. Our results suggest that gene expression profile in peripheral blood leukocytes may be a potentially useful method for the assessment of complex stress responses.

Adult↗
PubMed2002

HPLC measurement of harderoporphyrin in the harderian glands of rodents as a biomarker for sub-lethal or chronic arsenic exposure.

An improved HPLC method has been established for the measurement of harderoporphyrin (HP) in the harderian gland of rats and mice. Groups of female Wistar rats were given a single oral dose of sodium arsenite at 0, 0.5 or 5.0 mg As(III)/kg body weight, or a slurry of arsenic-contaminated soil at equivalent dose rates and the animals were sacrificed 96 h after dosing. A group of C57BL/6J female mice were chronically exposed to drinking water containing 500 microg As(V)/l of sodium arsenate ad libitum for over 2 years. Porphyrins were measured in the harderian glands of rats and mice. Our results suggest that HP and the alteration of the porphyrin profile in the harderian glands of rodents is a highly sensitive biomarker for both single sub-lethal and chronic arsenic exposure.

Animals↗
PubMed2006

Integration of HapMap-based SNP pattern analysis and gene expression profiling reveals common SNP profiles for cancer therapy outcome predictor genes.

Recent completion of the initial phase of a haplotype map of human genome (www.hapmap.org) provides opportunity for integrative analysis on a genome-wide scale of microarray-based gene expression profiling and SNP variation patterns for discovery of cancer-causing genes and genetic markers of therapy outcome. Here we applied this approach for analysis of SNPs of cancer-associated genes, expression profiles of which predicts the likelihood of treatment failure and death after therapy in patients diagnosed with multiple types of cancer. Unexpectedly, this analysis reveals a common SNP pattern for a majority (60 of 74; 81%) of analyzed cancer treatment outcome predictor (CTOP) genes. Our analysis suggests that heritable germ-line genetic variations driven by geographically localized form of natural selection determining population differentiations may have a significant impact on cancer treatment outcome by influencing the individual's gene expression profile. We demonstrate a translational utility of this approach by building a highly informative CTOP algorithm combining prognostic power of multiple gene expression-based CTOP models derived from signatures of oncogenic pathways associated with activation of BMI1; Myc; Her2/neu; Ras; beta-catenin; Suz12; E2F; and CCND1 oncogenes. Application of a CTOP algorithm to large databases of early-stage breast and prostate tumors identifies cancer patients with 100% probability of a cure with existing cancer therapies as well as patients with nearly 100% likelihood of treatment failure, thus providing a clinically feasible framework essential for introduction of rational evidence-based individualized therapy selection and prescription protocols. Our analysis indicates that genetic determinants of human disease susceptibility and severity are encoded by population differentiation SNP variants. Evolution of these SNPs is driven by geographically-localized form of natural selection causing population differentiation. Recent analysis identifies a class of SNPs regulating gene expression in normal individuals and likely determining unique genome-wide expression profiles of each individual. We propose that critical disease-causing combinations of SNP variants arise from SNPs regulating mRNA levels and determining genome-wide haplotype patterns of individual's disease susceptibility.

Biomarkers, Tumor↗
PubMed2005

Histology-based expression profiling yields novel prognostic markers in human glioblastoma.

Although the prognosis for patients with glioblastoma is poor, survival is variable, with some patients surviving longer than others. For this reason, there has been longstanding interest in the identification of prognostic markers for glioblastoma. We hypothesized that specific histologic features known to correlate with malignancy most likely express molecules that are directly related to the aggressive behavior of these tumors. We further hypothesized that such molecules could be used as biomarkers to predict behavior in a manner that might add prognostic power to sole histologic observation of the feature. We reasoned that perinecrotic tumor cell palisading, which denotes the most aggressive forms of malignant gliomas, would be a striking histologic feature on which to test this hypothesis. We therefore used laser capture microdissection and oligonucleotide arrays to detect molecules differentially expressed in perinecrotic palisades. A set of RNAs (including POFUT2, PTDSR, PLOD2, ATF5, and HK2) that were differentially expressed in 3 initially studied, microdissected glioblastomas also provided prognostic information in an independent set of 28 glioblastomas that did not all have perinecrotic palisades. On validation in a second, larger independent series, this approach could be applied to other human glioma types to derive tissue biomarkers that could offer ancillary prognostic and predictive information alongside standard histopathologic examination.

Biomarkers, Tumor↗
PubMed1996

Development and validation of new screening tests for nephrotoxic effects.

Within the framework of an European Commission-funded project, groups of industrial workers exposed to heavy metals (cadmium, mercury and lead) or solvents were studied together with corresponding control groups. Eighty-one measurements were carried out on urine and serum samples and the scientific results together with individual questionnaire information were entered into a central database. Data obtained was assessed centrally and individually in subsidiary studies. The measurable contributions were assessed either singly or in combination, of smoking, gender, metal exposure and site, to nephrotoxicity. The potential value of each test as an indicator of nephrotoxicity was then assessed on the basis of sensitivity and specificity. A number of new tests including prostaglandins and for extracellular matrix components were investigated as well as established tests for renal damage and dysfunction. The data obtained from this comprehensive study emphasises the value of noninvasive biomarkers for the early detection of nephrotoxicity due to environmental toxins. The urinary profile varied with the type of environmental/occupational toxin. By careful selection of a small panel of markers they can be used to indicate the presence of renal damage, the principal region affected, and to monitor the progress of disease and damage. Biomarkers were also used to confirm and tentatively establish safe exposure levels to nephrotoxins.

Biomarkers↗
PubMed2004

Development of biomarkers based on diet-dependent metabolic serotypes: characteristics of component-based models of metabolic serotypes.

Our research seeks to identify a serum profile, or serotype, that reflects the systemic physiologic modifications resultant from dietary restriction (DR), in part such that this knowledge can be applied for biomarker studies. Direct comparison suggests that component-based classification algorithms consistently out-perform distance-based metrics for studies of nutritional modulation of metabolic serotype, but are subject to over-fitting concerns. Intercohort differences in the sera metabolome could partially obscure the effects of DR. Further analysis now shows that implementation of component-based approaches (also called projection methods) optimized for class separation and controlled for over-fitting have >97% accuracy for distinguishing sera from control or DR rats. DR's effect on the metabolome is shown to be robust across cohorts, but differs in males and females (although some metabolites are affected in both). We demonstrate the utility of projection-based methods for both sample and variable diagnostics, including identification of critical metabolites and samples that are atypical with respect to both class and variable models. Inclusion of non-statistically different variables enhances classification models. Variables that contribute to these models are sharply dependent on mathematical processing techniques; some variables that do not contribute under one paradigm are powerful under alternative mathematical paradigms. In practical terms, this information may find purpose in other endeavors, such as mechanistic studies of DR. Application of these approaches confirms the utility of megavariate data analysis techniques for optimal generation of biomarkers based on nutritional modulation of physiological processes.

Animals↗
PubMed2005

Differential endocrine responses to rosiglitazone therapy in new mouse models of type 2 diabetes.

Polygenic mouse models for obesity-induced type 2 diabetes (T2D) more accurately reflect the most common manifestations of the human disease. Two inbred mouse strains (NON/Lt and NZO/HlLt) separately contributed T2D susceptibility- conferring quantitative trait loci to F1 males. Although chronic administration of rosiglitazone (Rosi) in diet (50 mg/kg) effectively suppressed F1 diabetes, hepatosteatosis was an undesired side effect. Three recombinant congenic strains (designated RCS1, -2, and -10) developed on the NON/Lt background carry variable numbers of these quantitative trait loci that elicit differential weight gain and male glucose intolerance syndromes of variable severity. We previously showed that RCS1 and -2 mice responded to chronic Rosi therapy without severe steatosis, whereas RCS10 males were moderately sensitive. In contrast, another recombinant congenic strain, RCS8, responded to Rosi therapy with the extreme hepatosteatosis observed in the F1. Longitudinal changes in multiple plasma analytes, including insulin, the adipokines leptin, resistin, and adiponectin, and plasminogen activator inhibitor-1 (PAI-1) allowed profiling of the differential Rosi responses in steatosis-exacerbated F1 and RCS8 males vs. the resistant RCS1 and RCS2 or moderately sensitive RCS10. Of these biomarkers, PAI-1 most effectively predicted adverse drug responses. Unexpectedly, mean resistin concentrations were higher in Rosi-treated RCS8 and RCS10. In summary, longitudinal profiling of multiple plasma analytes identified PAI-1 as a useful biomarker to monitor for differential pharmacogenetic responses to Rosi in these new mouse models of T2D.

Adiponectin↗
PubMed2026

Metabolomics in breast cancer: insights into treatment responses, disease progression, and prognostic assessment.

BACKGROUND: Alterations in metabolic pathways are a hallmark of cancer and play a pivotal role in breast cancer development and progression. The inherent metabolic heterogeneity of breast cancer contributes to differences in therapeutic response and patients' prognosis. Clinical metabolomics has emerged as a promising approach for identifying metabolic biomarkers that reflect tumor biology, treatment-related changes after diagnosis, and patients' outcomes. AIMS OF REVIEW: This review summarizes the metabolomic profiles of breast cancer patients, using various biological materials and analytical methods, to assess their potential role as biomarkers for monitoring therapeutic response, adverse treatment effects, tracking disease progression, and predicting prognosis. KEY SCIENTIFIC CONCEPT OF REVIEW: Metabolomic shifts generate unique signatures with promising potential as biomarkers for evaluating treatment response, monitoring therapeutic adverse effects, disease progression, and predicting clinical outcomes in breast cancer patients. Biological matrices, such as serum, plasma, and tumor tissue, were commonly used in both untargeted and targeted metabolomics approaches. Liquid chromatography-mass spectrometry is the most commonly used analytical method in clinical metabolomics studies. Altered metabolites were identified and linked to metabolic pathways, particularly amino acids, glucose, and fatty acids metabolism. When integrated with genomic and transcriptomic data, these metabolic fingerprints offer a multidimensional perspective on disease trajectory, thereby enhancing patient stratification and informing personalized therapeutic strategies.

Humans↗
PubMed2026

Comparative Multiomics Analysis of Cerebral Organoid-Derived Exosomes during Organoid Maturation.

Cerebral organoids derived from human pluripotent stem cells recapitulate key features of early brain development and provide a physiologically relevant model for neurogenesis. Exosomes secreted by these organoids carry bioactive cargo and offer a noninvasive means to monitor maturation and intercellular communication. We performed comprehensive multiomics profiling of exosomes collected from cerebral organoids at defined developmental stages to evaluate their utility as biomarkers of neuronal differentiation. Metabolomic analysis revealed a progressive decline in amino acids, including glutamic acid, consistent with increased metabolic demand during neurogenesis. Lipidomic and neurosteroid profiling showed dynamic increases in phosphatidylethanolamine and pregnenolone, reflecting synaptic membrane formation and signaling. Transcriptomic and proteomic analyses identified stage-specific neurodevelopmental signatures, with key markers mirroring those of parent organoids. Collectively, cerebral organoid-derived exosomes faithfully reflect organoid maturation and provide a robust platform for tracking in vitro brain development.

Humans↗
PubMed2002

Identification of differentially expressed genes in normal and malignant prostate by electronic profiling of expressed sequence tags.

Differentially expressed genes between corresponding normal and cancertissue can advance our understanding of the molecular basis of malignancy and potentially serve as biomarkers or prognostic markers of malignancy. To identify differentially expressed genes in prostate cancer, we used a procedure combining electronic expression profiling of the prostate expressed sequence tag (EST) database and molecular biology techniques. A novel electronic expression-profiling algorithm was developed to search publicly available EST sequences for genes that show significant differential expression in prostate cancer compared with normal prostate tissue. Approximately 600 genes expressed in prostate were identified through adequate EST counts of ESTs for electronic profiling. Of these 600 genes, 9 showed statistically significant differences in their EST counts between cancer and normal prostate and were further analyzed. The predictions associated with electronic profiling were experimentally verified for two genes, cysteine-rich secretory protein 3 (CRISP-3) and deadenylating nuclease (DAN), using real-time reverse transcription-PCR with total RNA extracted from cells isolated by laser capture microdissection. In five of five Gleason score 6 cancer cases, CRISP-3 expression was increased >50 fold, whereas the expression of DAN was reduced by >80%.

Algorithms↗
PubMed2003

Targeted therapy and pharmacogenomic programs.

The goal in administering chemotherapeutics is to develop the ability to predict the outcome of therapy in terms of response and toxicity. Technology has been developed to allow tumor profiling with measurement of protein expression, gene expression levels of markers, and even genetic polymorphisms, which may predict response to particular chemotherapeutics. The chemotherapeutics for which particular markers have been shown to predict outcome include the fluoropyrimidines and platinums. The next step is to develop clinical trials that will assess prospectively the benefits of profiling a patient's particular tumor, which should translate into an improvement in response and toxicity.

Antineoplastic Agents↗
PubMed2004

Signature of a silent killer: expression profiling in epithelial ovarian cancer.

With the sequencing of the human genome and the simultaneous development of high-throughput strategies, cancer biologists have entered an exciting new area for gene expression analysis, with the ability to glimpse higher order patterns of genetic and epigenetic alterations in complex diseases. Ovarian cancer biologists are rising to the challenge of applying these new technologies to this silent killer, with the eventual goal of improving the quality of life and long-term survival of patients. This review provides a summary of the disease, a description of available technologies and their application to the ovarian cancer problem, as well as a discussion on the challenges and opportunities related to DNA microarray expression profiling-based research, including downstream clinical applications.

Biomarkers, Tumor↗
PubMed2025

Extracellular vesicle proteomic expression is influenced by mining tenure in former uranium miners.

BACKGROUND: Chronic exposure to uranium (U) rich environments poses significant health risks, yet the molecular mechanisms underlying these effects remain poorly understood. Extracellular vesicles (EVs) are membrane-bound vesicles that transfer multiple biomolecules between cells and can regulate cellular function. OBJECTIVE: To determine whether U-mining tenure is associated with specific alterations in serum-derived EV proteomic and plasma cytokine profiles among former U-miners, and to assess the potential of EV-derived proteins as robust biomarkers of chronic U-exposure relative to canonical cytokines. METHODS: Serum and plasma samples were obtained from 39 former U-miners. Small and large EVs were isolated via differential ultracentrifugation and characterized by nanoparticle tracking and western blotting. EV proteomic profiles were analyzed using liquid chromatography-tandem mass spectrometry. Plasma cytokines were quantified using multiplex immunoassays. Age-adjusted linear regression was used to assess associations with mining tenure, and pathway enrichment analysis was performed on significant EV proteins. RESULTS: Eight small-EV and four large-EV proteins significantly correlated with mining tenure after age adjustment. Notably, Complement C1r subcomponent and Vitamin K-dependent protein S, and Fibrinogen alpha chain exhibited strong inverse correlations. Enrichment analyses highlighted immune-related and extracellular matrix pathways. Six cytokines were initially associated with mining tenure but lost significance after age adjustment. In contrast, EV protein associations appeared more robust for this confounding, underscoring their potential as exposure biomarkers. CONCLUSIONS: Serum EV-derived protein signatures were nominally associated with U-mining tenure independent of age, whereas cytokine profiles were confounded by age. These findings suggest that EV-derived proteins may provide sensitive biomarkers for monitoring long-term health effects of U-exposure, which warrants further investigation in larger cohorts.

Humans↗
PubMed2026

Diversified cell origin of Helicobacter pylori eradication-responsive gastric diffuse large B-cell lymphomas.

A significant proportion of gastric diffuse large B-cell lymphoma with mucosa-associated lymphoid tissue [DLBCL(MALT)] and without MALT ('pure' DLBCL) can be resolved by Helicobacter pylori eradication (HPE). Gastric MALT lymphoma is an indolent lymphoma derived from memory B cells in the marginal zone. In the present study, we aimed to explore the origin of large cells in HPE-responsive gastric DLBCLs (complete remission after HPE). We investigated gastric lymphoma biopsies from 31 patients with HPE-responsive DLBCLs [15 'pure' DLBCLs, 16 DLBCL(MALT)s]. We used the Hans algorithm (CD10, BCL-6, and MUM1) to define the origins of germinal center B cell (GCB) and non-GCB. To further ascertain the cellular origin, 11 'pure' DLBCLs were examined using an Agilent whole-human genome microarray. Eleven DLBCLs [eight with 'pure' DLBCL and three with DLBCL(MALT)] were also assessed using Lymph2Cx. Specific GCB markers, including BACH2, AID, and BCL2 rearrangement and enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) codon 641 mutations, were evaluated in 31 patients with HPE-responsive gastric DLBCLs. According to the Hans algorithm, 53% (8/15) of gastric 'pure' DLBCLs and 50% (8/16) of DLBCL(MALT)s were of the GCB phenotype. Gene expression assays revealed that five of six patients with 'Hans' GCB had GCB genetic signatures, whereas four of five patients with 'Hans' non-GCB had activated B-cell genetic signatures. The Lymph2Cx assay revealed the GCB subtype in seven of eight patients with 'Hans' GCB. The expression patterns of BACH2 (p = 0.005) and AID (p = 0.038) closely correlated with the 'Hans' GCB phenotype. BCL2 rearrangements and EZH2 codon 641 mutations were detected in 44% (7/16) and 13% (2/16) of patients with 'Hans' GCB, respectively. In another cohort of 29 HPE-unresponsive gastric DLBCLs [19 'pure' DLBCLs and 10 DLBCL(MALT)s], we found a close association between the 'Hans' GCB subtype and the GCB subtype as determined by the Agilent whole-human genome microarray and Lymph2Cx in lymphoma cells of these patients. In conclusion, more than half of HPE-responsive large cell lymphoma cases in the stomach were of GCB origin. © 2026 The Pathological Society of Great Britain and Ireland.

Humans↗
PubMed2005

[Genetics of retinal dystrophies--an overview].

Vision requires complex retinal functions, involving multiple genes with different functions. Retinal degeneration results from disturbance of retina-specific processes such as the visual transduction cascade, but also from defects in basic functions such as pre-mRNA splicing and nucleotide synthesis. As a consequence, the retinal dystrophies are genetically extremely heterogeneous (as shown in the table). Thanks to the Human Genome Project, the identification of retinal disease genes and additional loci has skyrocketed. Today, a typical search for the causative gene in a disease-linked genomic interval starts at the computer. Genes from a particular region can be displayed, and multiple gene-specific data such as expression patterns are immediately accessible. Candidate genes can then be investigated in DNA from affected individuals.

Biomarkers↗
PubMed2005

Clinical significance of interleukin-6 (IL-6) in the spread of gastric cancer: role of IL-6 as a prognostic factor.

BACKGROUND: It is becoming clear that various cytokines are associated with the spread of cancer cells. The purpose of this study was to compare interleukin (IL)-6 levels in patients with gastric cancer to elucidate the role of IL-6 in predicting the spread of tumors. METHODS: In 60 patients, we assessed the correlation of serum IL-6 (pg/ml) with stage, histological findings, hepatic metastasis, and related factors (hepatocyte growth factor [HGF], IL-1beta, tumor necrosis factor [TNF]-alpha, and transforming growth factor [TGF]-beta1). We also investigated the diagnostic significance of the IL-6 level for advanced gastric cancer and lymph node metastasis, as well as the association between IL-6 elevation and outcome. Finally, we examined the expression of IL-6 in tumor tissue. RESULTS: Significant relationships were seen between serum IL-6 and stage, depth of tumor invasion (pT), lymphatic invasion (ly), venons invasion (v)*, lymph node metastasis (pN), hepatic metastasis (cH), and HGF (P < 0.01; *P < 0.05). With regard to the diagnostic significance of the IL-6 level for advanced gastric cancer and lymph node metastasis, when the cutoff value of IL-6 was set at 1.97 pg/ml, the sensitivity was 81.8% and 87.5%; specificity was 66.7% and 58.3%; and accuracy was 77.1% and 72.9%, respectively. The 1- and 3-year cumulative survival rates for patients with an IL-6 value of more than 1.97 pg/ml (69.0% and 43.4%, respectively) were significantly lower than those for patients with an IL-6 value of 1.97 pg/ml or less (94.4% and 87.2%, respectively; P < 0.05). Immunohistochemical staining was positive for IL-6 in the cytoplasm of cancer cells. CONCLUSION: We suspect that IL-6 is involved in cancer invasion and lymph node and/or hepatic metastasis. Our results indicate that IL-6 could be used as a prognostic factor for survival.

Adult↗
PubMed2005

From proteomics to biomarker discovery in Alzheimer's disease.

Alzheimer's disease (AD) is the most common form of dementia in the elderly. AD is an invariably fatal neurodegenerative disorder with no effective treatment or definitive antemortem diagnostic test. Little is known about the changes in the brain preceding or accompanying initiation of the disease. Understanding the biological processes, which occur during AD onset and/or progression, will improve the diagnosis and treatment of the disease. As we will discuss in this review article, using high-throughput cDNA microarray we identified candidate genes whose expression is altered in the brain of cases at risk for AD dementia. However, it is possible that the use of the cDNA microarray technology alone may underestimate post-transcriptional modifications and therefore provides only a partial view of the biological problem of interest. As such, the combination of cDNA and protein arrays may provide a more global picture of the biological processes being studied. Based on this hypothesis, we initiated a series of high-throughput proteomic studies and found that the expressions of proteins involved in synaptic plasticity are selectively altered in the brain of cases at high risk to develop AD dementia (mild cognitive impairment; MCI). This is consistent with our cDNA microarray evidence showing that the expression of a-type synapsins is selectively altered in the brain of MCI cases. Collectively, these studies support the feasibility and usefulness of high-throughput cDNA microarray and proteomics techniques to study the sequential changes of distinctive gene expression patterns in the brain as a function of the progression of AD dementia.

Alzheimer Disease↗