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Identification of CD36 as a new surface marker of marginal zone B cells by transcriptomic analysis.

Follicular (FO) B cells and marginal zone (MZ) B cells belong to the mature B cell population in spleen of mice. To identify new surface markers of these mature B cell subsets, we compared gene expression profiles of FO and MZ B cells by DNA microarray using FACS-sorted mouse FO and MZ B cells. From 14,000 mouse genes, 27 membrane proteins were expressed mainly in MZ B cells while another 22 membrane proteins expressed largely in FO B cells. Using FACS analysis, we identified that CD36, CD68, and CD49e were expressed on MZ B cells but not on FO B cells. In addition, using semi-quantitative PCR, we found that the mRNA of CD131 were much more abundant in MZ B cells. These results revealed new phenotypic properties of MZ and FO B cells, and would facilitate further studies in the differentiation and functions of these mature B cells.

Animals↗

Organ messenger ribonucleic acid and plasma proteome changes in the adjuvant-induced arthritis model: responses to disease induction and therapy with the estrogen receptor-beta selective agonist ERB-041.

Two receptors [estrogen receptor (ER)alpha and ERbeta] mediate the manifold effects of estrogens throughout the body. Although a clear role has been established for ERalpha in the classical effects of estrogen activity, the physiological role of ERbeta is less well understood. A small-molecule ERbeta selective agonist, ERB-041, has potent antiinflammatory activity in the Lewis rat model of adjuvant-induced arthritis. To characterize the response of target organs and pathways responsible for this antiinflammatory effect, mRNA expression profiling of the spleen, lymph node, and liver was performed, in conjunction with a global analysis of the plasma proteome. We find that the expression of a large number of genes and proteins are altered in the disease model and the majority of these are partially or fully reversed by ERB-041 treatment. Regulated pathways include the acute-phase response, eicosanoid synthesis, fatty acid metabolism, and iron metabolism. In addition, many of the regulated genes and proteins are known to be dysregulated in human rheumatoid arthritis, providing further evidence that the manifestations of the Lewis rat adjuvant-induced arthritis model bear similarity to the human disease.

Animals↗

Application of PathoChip to urine-derived nucleic acids for broad microbial profiling in men with suspected prostate cancer: setup of a methodological workflow and pilot feasibility study.

BACKGROUND: Urine-based liquid biopsy is an attractive non-invasive source of prostate cancer (PCa) biomarkers, but urinary microbiome studies have mainly relied on 16S rRNA sequencing or shotgun metagenomics. This pilot study optimized and evaluated a practical workflow using PathoChip - a broad-spectrum microarray designed to detect bacterial, viral, fungal, and parasitic signatures - for microbial profiling of urine sediments from men with suspected PCa, an application not previously established. METHODS: First-morning urine was collected without prostatic massage from 35 men scheduled for biopsy; 19 were diagnosed with PCa and 16 were biopsy-negative. Different urine volumes and extraction strategies were evaluated to optimize DNA/RNA recovery. A setup phase compared 25 ng versus 50 ng of urine DNA and RNA input. DNA/RNA isolated from human B cells was used as reference control. An analysis pipeline was developed to detect outlier probes and create a presence/absence matrix. Reproducibility was assessed via library yield, Pearson correlation, blank-control subtraction, outlier probe detection. Prevalence comparisons were performed between clinical groups. RESULTS: An 8 mL starting volume was chosen as consistently available from self-collected urine. Sequential DNA/RNA extraction using the AllPrep DNA/RNA Micro Kit from sediment provided the best balance between nucleic-acid recovery, purity, and clinical compatibility. Reducing the input from 50 ng to 25 ng preserved highly concordant hybridization profiles, with matched samples clustering together with strong correlations. Exploratory analysis revealed PCa- and grade-associated patterns involving Actinomycetaceae, Aerococcaceae, and Streptococcaceae, with Streptococcaceae enriched in PCa of higher grades (ISUP GG ≥ 2). Other signatures, including Mobiluncus, Prevotella, Rhodotorula, Hymenolepis, and JC polyomavirus, were broadly detected but not PCa-discriminating. CONCLUSIONS: PathoChip can be adapted to urine sediments, generating reproducible microbial profiles from limited DNA/RNA input without prostatic massage. This platform provides a quick and accessible approach to broad screening, extending beyond 16S rRNA sequencing by enabling simultaneous multi-kingdom detection. The observed PCa- and grade-associated patterns are hypothesis-generating and require validation in larger independent cohorts.

Pathochip↗

Lessons learned from gene expression profile studies of aging and caloric restriction.

To examine molecular events associated with aging and its retardation by caloric restriction (CR), we have employed high-density oligonucleotide microarrays to define transcriptional patterns in mouse tissues, including skeletal muscle, brain, heart, and adipose. Aging results in a differential gene expression pattern specific to each tissue, and most alterations can be completely or partially prevented by CR. Transcriptional patterns of tissues from calorie-restricted animals suggest that CR retards the aging process by reducing endogenous damage and by inducing metabolic shifts associated with specific transcriptional profiles. These studies demonstrate that DNA microarrays can be used in aging research to generate panels of hundreds of transcriptional biomarkers, providing a new tool to measure biological age on a tissue-specific basis and to evaluate interventions designed to mimic the effects of CR.

Aging↗

Combining gene expression profiles and clinical parameters for risk stratification in medulloblastomas.

PURPOSE: Stratification of risk in patients with medulloblastoma remains a challenge. As clinical parameters have been proven insufficient for accurately defining disease risk, molecular markers have become the focus of interest. Outcome predictions on the basis of microarray gene expression profiles have been the most accurate to date. We ask in a multivariate model whether clinical parameters enhance survival predictions of gene expression profiles. PATIENTS AND METHODS: In a cohort of 55 young patients (whose medulloblastoma samples have been analyzed previously for gene expression profile), associations between clinical and gene expression variables and survival were assessed using Cox proportional hazards models. Available clinical variables included age, stage (ie, the presence of disseminated disease at diagnosis), sex, histologic subtype, treatment, and status. RESULTS: Univariate analysis demonstrated expression profiles to be the only significant clinical prognostic factor (P=.03). In multivariate analysis, gene expression profiles predicted outcome independent of other criteria. Clinical criteria did not significantly contribute additional information for outcome predictions, although an exploratory analysis noted a trend for decreased survival of patients with metastases at diagnosis but favorable gene expression profile. CONCLUSION: Gene expression profiling predicts medulloblastoma outcome independent of clinical variables. These results need to be validated in a larger prospective study.

Adolescent↗

Tumor gene expression and prognosis in breast cancer patients with 10 or more positive lymph nodes.

PURPOSE: This study, along with two others, was done to develop the 21-gene Recurrence Score assay (Oncotype DX) that was validated in a subsequent independent study and is used to aid decision making about chemotherapy in estrogen receptor (ER)-positive, node-negative breast cancer patients. EXPERIMENTAL DESIGN: Patients with >or=10 nodes diagnosed from 1979 to 1999 were identified. RNA was extracted from paraffin blocks, and expression of 203 candidate genes was quantified using reverse transcription-PCR (RT-PCR). RESULTS: Seventy-eight patients were studied. As of August 2002, 77% of patients had distant recurrence or breast cancer death. Univariate Cox analysis of clinical and immunohistochemistry variables indicated that HER2/immunohistochemistry, number of involved nodes, progesterone receptor (PR)/immunohistochemistry (% cells), and ER/immunohistochemistry (% cells) were significantly associated with distant recurrence-free survival (DRFS). Univariate Cox analysis identified 22 genes associated with DRFS. Higher expression correlated with shorter DRFS for the HER2 adaptor GRB7 and the macrophage marker CD68. Higher expression correlated with longer DRFS for tumor protein p53-binding protein 2 (TP53BP2) and the ER axis genes PR and Bcl2. Multivariate methods, including stepwise variable selection and bootstrap resampling of the Cox proportional hazards regression model, identified several genes, including TP53BP2 and Bcl2, as significant predictors of DRFS. CONCLUSION: Tumor gene expression profiles of archival tissues, some more than 20 years old, provide significant information about risk of distant recurrence even among patients with 10 or more nodes.

Adult↗

DNA microarrays for assessing ovarian cancer gene expression.

Although DNA microarray analysis is presented as a revolution in gene expression studies, it is in fact based on the classic technique of Southern DNA hybridisation where a labelled DNA probe is hybridised to single stranded DNA that is bound to a solid support matrix. The truly revolutionary aspect of microarray analysis lies in the fact that, within a given cell population, the expression of tens of thousands of genes, and ultimately the entire genome, can be assayed simultaneously. This capability, when coupled with powerful data analysis software, allows researchers to rapidly compare gene expression between two cell populations. In the cancer field, this enables researchers to compare gene expression between normal and malignant cells and to identify genes that are differentially regulated during cancer development. Microarray data can also be used to categorize tumours on the basis of their molecular profile, which may provide important biological, diagnostic and prognostic information. As little as 5 years ago identifying even a few differentially expressed genes may have taken several years and cost tens of thousands of dollars. Today microarrays can identify ten times the number of candidate genes in just a few months and at a tenth of the cost. Even so, microarray analysis is still in its infancy and the technology is advancing rapidly. There is little doubt that microarrays will revolutionize our ability to quantify the complex changes that occur in gene expression during cancer development. The greatest challenge that lies ahead is how to translate this knowledge into clinically useful diagnostic and therapeutic tools. In this review, we describe the technical aspects of DNA microarray analysis and some of the current and future applications of this technology for analysing gene expression in ovarian cancer.

Biomarkers, Tumor↗

Biomarker discovery by imaging mass spectrometry: transthyretin is a biomarker for gentamicin-induced nephrotoxicity in rat.

Adverse drug effects are often associated with pathological changes in tissue. An accurate depiction of the undesired affected area, possibly supported by mechanistic data, is important to classify the effects with regard to relevance for human patients. MALDI imaging MS represents a new analytical tool to directly provide the spatial distribution and the relative abundance of proteins in tissue. Here we evaluate this technique to investigate potential toxicity biomarkers in kidneys of rats that were administered gentamicin, a well known nephrotoxicant. Differential analysis of the mass spectrum profiles revealed a spectral feature at 12,959 Da that strongly correlates with histopathology alterations of the kidney. We unambiguously identified this spectral feature as transthyretin (Ser(28)-Gln(146)) using an innovative combination of tissue microextraction and fractionation by reverse-phase liquid chromatography followed by a top-down tandem mass spectrometric approach. Our findings clearly demonstrate the emerging role of imaging MS in the discovery of toxicity biomarkers and in obtaining mechanistic insights concerning toxicity mechanisms.

Amino Acid Sequence↗

Butter naturally enriched in conjugated linoleic acid and vaccenic acid alters tissue fatty acids and improves the plasma lipoprotein profile in cholesterol-fed hamsters.

Butter, which is naturally enriched in cis-9, trans-11 conjugated linoleic acid (rumenic acid; RA) and vaccenic acid (VA), has been shown to be an effective anticarcinogen in studies with animal models; however, there has been no examination of the effects of a naturally derived source of VA and RA on atherosclerosis-related biomarkers. The current study was designed to determine the effect of a diet containing VA/RA-enriched butter on plasma lipoproteins and tissue fatty acid profiles in cholesterol-fed hamsters. Male Golden Syrian hamsters were fed diets containing 0.2% cholesterol and 20% added fat as: 1) Control, 20% standard butter (CT); 2) 5% standard butter + 15% VA/RA-enriched butter (EB); 3) 15% standard butter + 5% partially-hydrogenated vegetable oil (VO). After 4 wk, plasma lipoproteins were isolated, cholesterol quantified, and tissue fatty acid profiles determined. Tissue concentrations of VA and RA were increased by consumption of the EB diet compared with both the CT and VO diets, whereas the VO diet increased their concentration compared with the CT diet only. Total and LDL cholesterol concentrations were significantly reduced in hamsters fed EB and VO compared with CT, whereas VLDL cholesterol concentrations were reduced in hamsters fed EB compared with those fed CT and VO. HDL cholesterol concentrations did not differ among treatments. The ratio of potentially atherogenic lipoproteins [VLDL + intermediate density lipoproteins (IDL) + LDL] to antiatherogenic HDL was significantly lower in hamsters fed VA/RA-enriched butter (0.60) than in those fed either control diet (1.70) or the diet containing partially hydrogenated vegetable oil (1.04). Thus, increasing the VA/RA concentration of butter results in a plasma lipoprotein cholesterol profile that is associated with a reduced risk of atherosclerosis.

Animals↗

Neurogenic potential of human mesenchymal stem cells revisited: analysis by immunostaining, time-lapse video and microarray.

The possibility of generating neural cells from human bone-marrow-derived mesenchymal stem cells (hMSCs) by simple in vitro treatments is appealing both conceptually and practically. However, whether phenotypic modulations observed after chemical manipulation of such stem cells truly represent a genuine trans-lineage differentiation remains to be established. We have re-evaluated the effects of a frequently reported biochemical approach, based on treatment with butylated hydroxyanisole and dimethylsulphoxide, to bring about such phenotypic conversion by monitoring the morphological changes induced by the treatment in real time, by analysing the expression of phenotype-specific protein markers and by assessing the modulation of transcriptome. Video time-lapse microscopy showed that conversion of mesenchymal stem cells to a neuron-like morphology could be reproduced in normal primary fibroblasts as well as mimicked by addition of drugs eliciting cytoskeletal collapse and disruption of focal adhesion contacts. Analysis of markers revealed that mesenchymal stem cells constitutively expressed multi-lineage traits, including several pertaining to the neural one. However, the applied ;neural induction' protocol neither significantly modulated the expression of such markers, nor induced de novo translation of other neural-specific proteins. Similarly, global expression profiling of over 21,000 genes demonstrated that gene transcription was poorly affected. Most strikingly, we found that the set of genes whose expression was altered by the inductive treatment did not match those sets of genes differentially expressed when comparing untreated mesenchymal stem cells and immature neural tissues. Conversely, by comparing these gene expression profiles with that obtained from comparisons between the same cells and an unrelated non-neural organ, such as liver, we found that the adopted neural induction protocol was no more effective in redirecting human mesenchymal stem cells toward a neural phenotype than toward an endodermal hepatic pathway.

Adult↗

Identification of key immune-related genes and potential therapeutic drugs in diabetic nephropathy based on machine learning algorithms.

BACKGROUND: Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study aims to identify immune biomarkers and potential therapeutic drugs in DN. METHODS: We analyzed two DN microarray datasets (GSE96804 and GSE30528) for differentially expressed genes (DEGs) using the Limma package, overlapping them with immune-related genes from ImmPort and InnateDB. LASSO regression, SVM-RFE, and random forest analysis identified four hub genes (EGF, PLTP, RGS2, PTGDS) as proficient predictors of DN. The model achieved an AUC of 0.995 and was validated on GSE142025. Single-cell RNA data (GSE183276) revealed increased hub gene expression in epithelial cells. CIBERSORT analysis showed differences in immune cell proportions between DN patients and controls, with the hub genes correlating positively with neutrophil infiltration. Molecular docking identified potential drugs: cysteamine, eltrombopag, and DMSO. And qPCR and western blot assays were used to confirm the expressions of the four hub genes. RESULTS: Analysis found 95 and 88 distinctively expressed immune genes in the two DN datasets, with 14 consistently differentially expressed immune-related genes. After machine learning algorithms, EGF, PLTP, RGS2, PTGDS were identified as the immune-related hub genes associated with DN. In addition, the mRNA and protein levels of them were obviously elevated in HK-2 cells treated with glucose for 24 h, as well as their mRNA expressions in kidney tissues of mice with DN. CONCLUSION: This study identified 4 hub immune-related genes (EGF, PLTP, RGS2, PTGDS), as well as their expression profiles and the correlation with immune cell infiltration in DN.

Diabetic Nephropathies↗

Osteoblasts respond to hydroxyapatite surfaces with immediate changes in gene expression.

Bone mineral contains hydroxyapatite (HA). This is the surface that mature osteoblasts and osteocytes interact with. Synthetic HA is widely used in orthopedic surgeries as an implant or implant coating. The bone-like HA surfaces increase implant union and bone formation; however, the mechanisms accounting for this effect on osteoblasts are not known. In this study, we compared gene expression profiles of osteoblasts responding to HA or plastic surfaces for 24 h. Expression profiles were also compared between HA discs processed with gravity-sieved compared with combined gravity and air-jet-sieved HA powders. The latter, composed of smaller HA particles, exhibits an increase in grain boundary surface area. Discs made with either HA powder similarly up-regulated osteoblast expression of 10 genes (including proliferin 3, Glvr-1, DMP-1, and tenascin C) and down-regulated 15 genes (such as osteoglycin) by more than 2-fold compared with plastic surfaces. The overall changes are indicative of an immediate (24-h) response to the HA surface and a trend toward osteoblast differentiation. In addition, subsets of modulated genes exist that are unique to each HA subtype. Taken together, we identified HA responsive genes evident within 24 h of surface contact, indicating a critical role for extracellular mineral surfaces in the regulation of osteoblast gene expression and phenotype.

3T3 Cells↗

Recent developments in protein microarray technology.

The sequencing of the human genome and the advent of DNA chips and sophisticated bioinformatics platforms have enabled molecular biologists to take a more global view of biological systems and to analyze naturally occurring genetic variation. Microarrays of antibodies can measure the concentrations of many proteins quickly and simultaneously. Microarrays of genomically encoded proteins allow scientists to screen entire genomes for proteins that interact with particular factors, catalyze particular reactions, or act as substrates for protein-modifying enzymes or as targets of autoimmune responses. The new protein microarray platforms will prove invaluable to basic biological research, and will dramatically accelerate the pace of discovery of drug targets and diagnostic biomarkers.

Drug Design↗

Chronic fatigue syndrome: the need for subtypes.

Chronic fatigue syndrome (CFS) is an important condition confronting patients, clinicians, and researchers. This article provides information concerning the need for appropriate diagnosis of CFS subtypes. We first review findings suggesting that CFS is best conceptualized as a separate diagnostic entity rather than as part of a unitary model of functional somatic distress. Next, research involving the case definitions of CFS is reviewed. Findings suggest that whether a broad or more conservative case definition is employed, and whether clinic or community samples are recruited, these decisions will have a major influence in the types of patients selected. Review of further findings suggests that subtyping individuals with CFS on sociodemographic, functional disability, viral, immune, neuroendocrine, neurology, autonomic, and genetic biomarkers can provide clarification for researchers and clinicians who encounter CFS' characteristically confusing heterogeneous symptom profiles. Treatment studies that incorporate subtypes might be particularly helpful in better understanding the pathophysiology of CFS. This review suggests that there is a need for greater diagnostic clarity, and this might be accomplished by subgroups that integrate multiple variables including those in cognitive, emotional, and biological domains.

Diagnosis, Differential↗

Toxicogenomic approach for assessing toxicant-related disease.

The problems of identifying environmental factors involved in the etiology of human disease and performing safety and risk assessments of drugs and chemicals have long been formidable issues. Three principal components for predicting potential human health risks are: (1) the diverse structure and properties of thousands of chemicals and other stressors in the environment; (2) the time and dose parameters that define the relationship between exposure and disease; and (3) the genetic diversity of organisms used as surrogates to determine adverse chemical effects. The global techniques evolving from successful genomics efforts are providing new exciting tools with which to address these intractable problems of environmental health and toxicology. In order to exploit the scientific opportunities, the National Institute of Environmental Health Sciences has created the National Center for Toxicogenomics (NCT). The primary mission of the NCT is to use gene expression technology, proteomics and metabolite profiling to create a reference knowledge base that will allow scientists to understand mechanisms of toxicity and to be able to predict the potential toxicity of new chemical entities and drugs. A principal scientific objective underpinning the use of microarray analysis of chemical exposures is to demonstrate the utility of signature profiling of the action of drugs or chemicals and to utilize microarray methodologies to determine biomarkers of exposure and potential adverse effects. The initial approach of the NCT is to utilize proof-of-principle experiments in an effort to "phenotypically anchor" the altered patterns of gene expression to conventional parameters of toxicity and to define dose and time relationships in which the expression of such signature genes may precede the development of overt toxicity. The microarray approach is used in conjunction with proteomic techniques to identify specific proteins that may serve as signature biomarkers. The longer-range goal of these efforts is to develop a reference relational database of chemical effects in biological systems (CEBS) that can be used to define common mechanisms of toxicity, chemical and drug actions, to define cellular pathways of response, injury and, ultimately, disease. In order to implement this strategy, the NCT has created a consortium of research organizations and private sector companies to actively collaborative in populating the database with high quality primary data. The evolution of discrete databases to a knowledge base of toxicogenomics will be accomplished through establishing relational interfaces with other sources of information on the structure and activity of chemicals such as that of the National Toxicology Program (NTP) and with databases annotating gene identity, sequence, and function.

Animals↗

Label-free detection of proteins in crude cell lysate with antibody arrays by a surface plasmon resonance imaging technique.

We established a label-free method of measuring proteins in crude cell lysate using antibody arrays and surface plasmon resonance (SPR) imaging. The refractivity of the running buffer was adjusted with that of the lysate to overcome the bulk effect. The chemistries of the fabricated arrays were investigated to reduce nonspecific adsorption on the array surface. We found that the hydrophilicity of the poly(ethylene glycol) moiety and lower electrostatic charge on the surface provided a specific measurement of antigen-antibody interaction. We validated the system by measuring the expression of eight proteins in the mouse brain and comparing the results to those by conventional Western blotting. The detection limit of the antibody array was approximately 30 ng/mL in crude cell lysate, on the same order as that of previous SPR research. The system enabled quick, label-free, and high-throughput analysis of abundant proteins with minimal sample volume ( approximately 200 muL). It is expected that our SPR antibody array will be applicable for direct protein expression profiling of cell lysate, as well as for cell phenotyping, food analysis, discovery of new biomarkers, and immunological disease diagnostics.

Animals↗

Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP Study.

Large-scale population phenotyping for molecular epidemiological studies is subject to all the usual criteria of analytical chemistry. As part of a major phenotyping investigation we have used high-resolution 1H NMR spectroscopy to characterize 24-h urine specimens obtained from population samples in Aito Town, Japan (n = 259), Chicago, IL (n = 315), and Guangxi, China (n = 278). We have investigated analytical reproducibility, urine specimen storage procedures, interinstrument variability, and split specimen detection. Our data show that the multivariate analytical reproducibility of the NMR screening platform was >98% and that most classification errors were due to urine specimen handling inhomogeneity. Differences in metabolite profiles were then assessed for Aito Town, Chicago, and Guangxi population samples; novel combinations of biomarkers were detected that separated the population samples. These cross-population differences in urinary metabolites could be related to genetic, dietary, and gut microbial factors.

Biomarkers↗

Hyperlactate-Associated Lysine Lactylome Remodeling in Laryngeal Squamous Cell Carcinoma.

Laryngeal squamous cell carcinoma (LSCC) lacks reliable biomarkers, and the roles of lactate metabolism and lysine lactylation (Kla) remain largely unknown. We profiled the lysine lactylome of LSCC, paired it with adjacent normal tissues, and integrated the data with quantitative proteomic and transcriptomic analyses. LSCC exhibited a hyperlactate-associated phenotype characterized by dysregulated lactate-related genes (LRGs), altered protein abundance, increased tissue lactate, and globally increased Kla levels. Data-independent acquisition mass spectrometry (DIA-MS) identified 1616 Kla sites on 1468 peptides from 688 proteins, with most differential sites being upregulated in tumors. Differentially lactylated proteins were enriched in cell-matrix adhesion, cell migration, chromatin remodeling, and gene-regulatory processes and were clustered into cytoskeletal and nuclear regulatory modules. Multiple Kla sites were also detected on the core histones. Immunoblotting and tissue microarray analyses confirmed increased pan-Kla expression in the LSCC. Pan-Kla levels were independent of sex and age but positively correlated with the tumor stage and lymph-node metastasis. These findings provide a systematic resource for hyperlactate-associated lactylome remodeling in LSCCs and identify candidate Kla-related molecular features associated with clinicopathological progression for future functional and clinical evaluation.

Humans↗