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PubMed2000

Growth and migration markers of rat C6 glioma cells identified by serial analysis of gene expression.

Tumors derived from rat C6 cell implants into rat brain exhibit similar morphological characteristics and degree of vascularization to human glioblastomas. To establish a molecular basis for C6 gliosarcoma malignancy, we have constructed a molecular profile of the most abundantly expressed genes, using serial analysis of gene expression (SAGE). Sequence tags (1168) representing 738 individual transcripts were collected and tag-to-gene mapping was carried out using the UniGene data set for rat. Differentially expressed C6 transcripts were identified by comparison of tags collected for C6 cells with a similar number (1002) of tags from a rat primary astrocyte library. Genes found to be expressed at increased levels in C6 cells are associated with cell surface interactions, migration, or metastasis formation and proliferation. These include the receptor for hyaluronan-mediated motility (RHAMM), S-100 related protein 42A, galectin I, preproenkephalin, osteopontin, autocrine motility factor, alpha-tubulin, ad1 antigen, and cofilin. In addition, a tag with no database match probably representing a previously uncharacterized transcript was differentially expressed in C6 cells. Transcripts showing reduced expression in C6 cells relative to astrocytes included the extracellular matrix glycoprotein osteonectin/SPARC (secreted protein, acidic, rich in cysteine), actin-binding proteins thymosins beta-4 and beta-10, the cysteine protease inhibitor cystatin C, the actin-gelling protein SM22/transgelin, and ferritin-H. SAGE results were confirmed by Northern blot for all transcripts tested, reaffirming the value of the SAGE technique for expression profiling in cancer biology.

Animals↗
PubMed2003

[Genetic tests for molecular markers of cancer].

Based on recent advancements in biotechnology and molecular oncology, genetic tests for molecular markers have been widely used for diagnosis and therapeutic monitoring in patients with hematological malignancies. However, incorporation of such tests has been limited in the care of patients with non-hematopoietic malignancies. The reasons for this include difficulty in sampling of the tumor tissue, and a lack of evidence for cost-effectiveness in the test utilization. A practical approach is the use of bodily fluids, such as blood, sputum, urine and feces, as specimens for early detection and monitoring of tumor-derived nucleic acid sequences. The prospect has been raised for development of tests for individualized medicine based on genetic information such as prediction of responsiveness to chemotherapeutic agents for selection of treatment, which will be promoted by gene expression profiling using DNA microarray.

Biomarkers, Tumor↗
PubMed2004

18F-FDG kinetics and gene expression in giant cell tumors.

UNLABELLED: 18F-FDG kinetics were evaluated by use of compartment and noncompartment models of giant cell tumors. The kinetic data were compared with the gene expression data for a subgroup of patients. METHODS: Nineteen patients with giant cell tumors were examined with PET and 18F-FDG, and tracer kinetics were assessed quantitatively. A 2-compartment model, including the transport constants k1-k4 as well as the vascular fraction (VB) for 18F-FDG, was used for evaluation of the data. A noncompartment model was used to calculate the fractal dimension of the 18F-FDG time-activity curve to assess the heterogeneity of the tracer kinetics. Furthermore, tumor specimens obtained from 5 patients were assessed with gene chip technology (U95A), and these data were compared with the quantitative 18F-FDG data. RESULTS: The giant cell tumors showed generally enhanced 18F-FDG uptake 1 h after tracer application, with a mean 18F-FDG standardized uptake value (SUV) of 4.8 (range, 1.8-9.4). Quantitative evaluation of tracer kinetics showed a preferential increase for 18F-FDG transport, with a mean k1 of 0.340. The vascular fraction accounted for 35% of the tumor volume and was high compared with those for other tumors, such as soft-tissue sarcomas. 18F-FDG kinetics were heterogeneous, with a fractal dimension of 1.3. Gene chip analysis showed that the expression of 137 genes (1.1%) exceeded the median expression value of the reference gene, beta2-microglobulin. The highest expression was observed for the gene for the small, leucine-rich proteoglycan I (biglycan), which is important for bone cell differentiation and proliferative activity. Correlation analysis revealed an association of 18F-FDG data with the expression of several genes. Mainly genes related to angiogenesis were associated with the compartment parameters. The SUV at 56-60 min was correlated with the expression of vascular endothelial growth factor A (angiogenesis) and cell division cycle 2 protein (proliferation). CONCLUSION: Despite their classification as benign tumors, giant cell tumors have generally enhanced 18F-FDG uptake, mainly attributable to an enhanced vascular fraction and increased 18F-FDG transport. A comparison of gene chip data and 18F-FDG kinetic data showed a close association of quantitative 18F-FDG results and the expression of genes related to angiogenesis.

Biomarkers, Tumor↗
PubMed2005

Patterns of expression of TSC-22 protein in astrocytic gliomas.

AIM: To evaluate expression patterns of protein product of putative tumor suppressor gene TSC-22 in human astrocytic tumors by immunohistochemical approach. METHODS: Plasmid pET-23d-TSC22 was constructed for the expression of human TSC-22 protein in bacterial system, and polyclonal rabbit antibodies against recombinant TSC-22 were produced. Immunohistochemical analysis of TSC-22 and GFAP expression with the use of anti-human-TSC-22- and anti-human-GFAP-antibodies was performed on histological slides of astrocytic tumors. RESULTS: Immunohistochemical analysis has shown that the number of cells expressing TSC-22 was significantly lower in glioblastoma tissues than that in diffuse astrocytoma. Double immunohistochemical staining of astrocytic tumors using anti-human-TSC-2- and anti-human-GFAP-antibodies showed that both TSC-22 and GFAP expression is co-localized in astrocytes. CONCLUSION: TSC-22 protein is expressed in astrocytes, but not in macrophage/microglial cells. In more aggressive forms of astrocytic tumors decreased expression of TSC-22 mRNA correlates with its lowered expression on protein level.

Amino Acid Sequence↗
PubMed2005

Using prior knowledge and rule induction methods to discover molecular markers of prognosis in lung cancer.

An iterative computational scientific discovery approach is proposed and applied to gene expression data for resectable lung adenocarcinoma patients. We use genes learned from the C5.0 rule induction algorithm, clinical features and prior knowledge derived from a network of interacting genes as represented in a database obtained with PathwayAssist to discover markers for prognosis in the gene expression data. This is done in an iterative fashion with machine learning techniques seeding the prior knowledge. This research illustrates the utility of combining signaling networks and machine learning techniques to produce simple prognostic classifiers.

Adenocarcinoma↗
PubMedDate not supplied

[BRAF initiating mutations in the papillary thyroid carcinoma].

Among genetic alterations most important for the initiation of papillary thyroid carcinoma (PTC) is mutation T1799A in the BRAF gene which is the most frequent event (54.5%) in this type of thyroid cancer. It is seen in all stages, from microcarcinoma through clinically overt disease to anaplastic cancer. It has been shown that BRAF mutation is correlated with PTC histotype. It is identified most frequently in classical PTC and in tall cell variant. Moreover, BRAF mutation is described more often in older patients, whereas in young patients RET/PTC rearrangements dominate. In PTC cases with BRAF mutation V600E the prognosis is poorer, with more cancer invasiveness, metastasis and recurrence. The presence of BRAF mutation is related to the specific gene expression signature, different than in cancer cases showing RET/PTC rearrangement or no known initiating mutation.

Age Factors↗
PubMed2006

Gene-expression patterns in whole blood identify subjects at risk for recurrent tuberculosis.

BACKGROUND: The majority of patients with tuberculosis who comply with appropriate treatment are cured. However, approximately 5% subsequently have a repeat disease episode, usually within 2 years of successful combination therapy. Presently, there is no way of predicting which patients will experience a relapse. METHODS: We identified 10 subjects who had previously experienced recurrent tuberculosis and carefully matched them to cured subjects who had had only 1 episode of tuberculosis, to patients with active tuberculosis, and to latently infected healthy subjects. We compared their ex vivo whole-blood gene-expression profiles by use of DNA array technology and confirmed the results by use of quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR). RESULTS: The 4 clinical tuberculosis groups exhibited distinct patterns of gene expression. The gene-transcript profiles of the patients with recurrent tuberculosis were more similar to those of the patients with active tuberculosis than to those of the cured or latently infected subjects. Discriminant analysis of a training data set showed that 9 genes were sufficient to classify the subjects. We confirmed that measurement of the expression of these genes by qRT-PCR can accurately discriminate between subjects in a test set of samples. CONCLUSIONS: A simple test based on gene-expression patterns may be used as a biomarker of cure while identifying patients who are at risk for relapse. This would facilitate the introduction of new tuberculosis drugs.

Biomarkers↗
PubMed2005

Expression profiling in the aging brain: a perspective.

To evaluate molecular events associated with the aging process in animal models and human tissues, microarray analysis is performed at the regional and cellular levels to define transcriptional patterns or mosaics that may lead to better understanding of the mechanism(s) that drive senescence. In this review, we outline the experimental and analytical issues associated with high-throughput genomic analyses in aging brain and other tissues for a comprehensive evaluation of the current state of microarray analysis in aging paradigms. Ultimately, the goal of these studies is to apply functional genomics and proteomics approaches to aging research to develop new tools to assess age in cell- and tissue-specific manners in order to develop aging biomarkers for pharmacotherapeutic interventions and disease prevention.

Adult↗
PubMed2006

Metabolomics in monitoring kidney transplants.

PURPOSE OF REVIEW: The success of any given kidney transplant is closely tied to the ability to monitor patients and responsively change their medications. Transplant monitoring is still, however, dependent on relatively old technologies: serum creatinine levels, urine output, blood pressure, blood glucose and histopathology of biopsy samples. These older technologies do not offer sufficient specificity, sensitivity, or accuracy to allow appropriate and timely interventions. Using the tools of genomics, proteomics and metabolomics new biomarkers are being found that may greatly improve transplant monitoring and significantly enhance graft survival. This review describes the basic principles of metabolomics and summarizes a number of recent developments in the use of metabolite biomarkers and metabolomics to monitor kidney transplants. RECENT FINDINGS: Changes in the concentration profiles of a number of small molecule metabolites found in either blood or urine can be used to localize organ damage, identify organs at risk of rejection, assess organs suffering from ischemia-repurfusion injury or identify organs that have been damaged by immunosuppressive drugs. SUMMARY: The application of metabolomics to kidney transplant monitoring is still very much in its infancy. Nevertheless, there are a number of easily measured metabolites in both urine and serum that can provide reliable indications of organ function, organ injury, and immunosuppressive drug toxicity. As the field matures, metabolomics may eventually lead to the development of rapid, inexpensive and noninvasive approaches to assist clinicians in monitoring kidney transplants.

Biomarkers↗
PubMed2002

Induction of cytosolic glutathione S-transferases from Atlantic eel (Anguilla Anguilla) after intraperitoneal treatment with polychlorinated biphenyls.

Glutathione S-transferases (GST) are phase II biotransformation enzymes influenced by exposure to foreign compounds and are proposed as biomarkers of environmental pollution. The hepatic and renal cytosolic GST isoenzymes from juvenile Atlantic eels were isolated and partially characterized. In both organs, three different GST isoenzymes were purified using HPLC and the final subcellular purified fraction resulted in enzymatic subunits of approximately 24,500 Da. Total GST activity was significantly higher towards the substrate 1-chloro-2,4-dinitrobenzene (CDNB) than the ethacrynic acid (ETHA). Induction of isoenzymes of GST was studied after intraperitoneal treatment with a single dose (25 mg/kg bw) of a polychlorinated biphenyls mixture. In the hepatic cytosol, an inductory effect on the major enzymatic isoform was observed when comparing treated with control eels. This was directly related to statistically significant (P < 0.05) differences in total GST activity toward the CDNB between treated and control groups, with an increase of 33.6% of GST total activity measured in the last subcellular purified samples. In the kidney cytosol, PCB treatment did not affect GST activity. Significant differences were observed when analyzing the effect of PCB treatment on the main GST subunit height (retention time of 27 min). These results indicate that hepatic GST profiles could be considered as a good tool in environmental studies as specific biomarkers of contamination.

Anguilla↗
PubMed2005

Apocrine cysts of the breast: biomarkers, origin, enlargement, and relation with cancer phenotype.

Up to one-third of women aged 30-50 years have cysts in their breasts and are presumed to be at increased risk of developing breast cancer. Here we present an extensive proteomic and immunohistochemistry (IHC) study of breast apocrine cystic lesions aimed at generating specific biomarkers and elucidating the relationship, if existent, of apocrine cysts with cancer phenotype. To this end we compared the expression profiles of apocrine macrocysts obtained from mastectomies from high risk cancer patients with those of cancerous and non-malignant mammary tissue biopsies collected from the same patients. We identified two biomarkers, 15-hydroxyprostaglandin dehydrogenase and 3-hydroxymethylglutaryl-CoA reductase, that were expressed specifically by apocrine type I cysts as well as by apocrine metaplastic cells in type II microcysts, terminal ducts, and intraductal papillary lesions. No expression of these markers was observed in non-malignant terminal ductal lobular units, type II flat cysts, stroma cells, or fat tissue as judged by IHC analysis of matched non-malignant tissue samples collected from 93 high risk patients enrolled in our cancer program. IHC analysis of the corresponding 93 primary tumors indicated that most apocrine changes have little intrinsic malignant potential, although some may progress to invasive apocrine cancer. None of the apocrine lesions examined, however, seemed to be a precursor of invasive ductal carcinomas, which accounted for 81% of the tumors analyzed. Our studies also provided some insight into the origin, development, and enlargement of apocrine cysts in mammary tissue. The successful identification of differentially expressed proteins that characterize specific steps in the progression from early benign lesions to apocrine cancer opens a window of opportunity for designing and testing new approaches for pharmacological intervention, not only in a therapeutic setting but also for chemoprevention, to inhibit cyst development as both 15-hydroxyprostaglandin dehydrogenase and 3-hydroxymethylglutaryl-CoA reductase are currently being targeted for chemoprevention strategies in various malignancies.

Adult↗
PubMed2026

Plasma proteomics reveal SERPINA1 and CD59 as candidate biomarkers for COVID-19 severity stratification and prognosis prediction.

BACKGROUND: COVID-19 has been closely associated with coagulation abnormalities. However, existing biomarkers, including D-dimer and fibrin degradation products (FDP), exhibit limited accuracy in stratifying disease severity and predicting long-term clinical outcomes. OBJECTIVES: This study aimed to use proteomic analysis to identify plasma biomarkers associated with COVID-19 severity and prognosis, and validate their predictive utility for mortality and thromboembolic complications. METHODS: Plasma proteomic profiles were analyzed across three COVID-19 severity classes. Differential expression analysis and functional analysis were performed. Clustering analysis was used to identify proteins correlated with disease severity. Candidate biomarkers were validated in an independent cohort. Predictive performance of the biomarkers for mortality, sepsis and venous thromboembolism was evaluated using bootstrap-corrected ROC analyses and multivariable regression analyses. RESULTS: Proteomic analysis revealed progressive involvement of the coagulation and complement pathway with increasing disease severity. SERPINA1 and CD59 were identified as candidate biomarkers and exhibited significantly higher plasma levels in severe cases. Bootstrap-corrected ROC analyses demonstrated strong predictive performance: SERPINA1 achieved AUCs of 0.775 and 0.924 for 30-day and 12-month mortality, and CD59 achieved AUCs of 0.720 for sepsis; the combined model further improved prediction of 12-month mortality (AUC 0.946) and sepsis (AUC 0.904), outperforming D-dimer and FDP. Multivariable regression confirmed their independent prognostic value. CONCLUSION: This exploratory study identifies SERPINA1 and CD59 as candidate prognostic biomarkers in COVID-19, highlighting the role of coagulation and complement-related pathways in disease severity and warranting further prospective validation.

Humans↗
PubMed2026

Proteo-metabolomic integration identifies stage-specific candidate biomarkers for Parkinson's disease.

Parkinson's disease (PD) is a progressive neurodegenerative disorder with a prolonged prodromal phase and complex motor symptoms. Despite improved clinical criteria, early diagnosis and longitudinal monitoring remain challenging. While cerebrospinal fluid (CSF) and plasma metabolites and proteins show biomarker potential, their utility in predictive models is insufficiently characterized. We employed a secondary computational approach to integrate proteometabolomic profiles from CSF and plasma samples of >1100 Parkinson's Progression Markers Initiative (PPMI) participants. Using multi-omics machine learning, we identified biofluid-specific signatures and evaluated predictive performance. Twenty-one biomarker candidates were validated across three models (SVM, GLMNET, RF); SVM and GLMNET achieved the highest recall (83-86%) and AUCs of 0.84-0.89. Longitudinal mixed-effects modeling revealed eight candidates associated with progression across diagnostic stages. We identified a three-part molecular framework characterizing neurodegeneration: a diagnostic subpanel reflecting early microbiome dysregulation (secretory granins and metabolites) and synaptic breakdown; a second subpanel monitoring phenoconversion via neurogenesis precursors and extracellular matrix proteins; and a third subpanel tracking progression through chronic neuroinflammation and immune activation. This integrated multi-omics approach provides a robust framework for stage-specific PD monitoring and potential clinical deployment.

Journal Article↗
PubMedDate not supplied

Evidence of a field effect associated with mammary cancer chemoprevention by methylseleninic acid.

In the present study, the molecular effects of methylseleninic acid in cancer chemoprevention was evaluated using two closely related sets of targets. The first approach examined the modulation of biomarkers in pathologically-defined premalignant lesions of the rat mammary gland. The second approach involved the use of cDNA microarray technology to characterize the profile of gene expression changes in the whole mammary tissue. Treatment with methylseleninic acid led to quantifiable changes in the expression of selective cell cycle and apoptosis regulatory proteins in the premalignant lesions. The biomarkers in the panel included cyclin A, cyclin D1, p21, p27, bcl-2 and bax. These were found to be modulated in a manner that was consistent with a reduction in the development of premalignant lesions by methylseleninic acid. Microarray analysis using RNA isolated from the whole mammary gland provided highly suggestive clues that methylseleninic acid was able to produce a widespread effect on gene expression in adipocytes and stromal cells, which are present in abundance in the mammary tissue. Thus, epithelial cells may not be the only targets for the action of selenium, even though the focus of selenium chemoprevention is to inhibit premalignant lesions and cancers arising from the epithelial cells. In view of the fact that adipocytes and stromal cells are known to play an important role in the growth and differentiation of their neighboring epithelial cells, the concept of a field effect in selenium chemoprevention is proposed as a new frontierforfuture research endeavors.

Animals↗