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PubMed2005

Experimental trial for diagnosis of pancreatic ductal carcinoma based on gene expression profiles of pancreatic ductal cells.

Pancreatic ductal carcinoma (PDC) remains one of the most intractable human malignancies, mainly because of the lack of sensitive detection methods. Although gene expression profiling by DNA microarray analysis is a promising tool for the development of such detection systems, a simple comparison of pancreatic tissues may yield misleading data that reflect only differences in cellular composition. To directly compare PDC cells with normal pancreatic ductal cells, we purified MUC1-positive epithelial cells from the pancreatic juices of 25 individuals with a normal pancreas and 24 patients with PDC. The gene expression profiles of these 49 specimens were determined with DNA microarrays containing >44 000 probe sets. Application of both Welch's analysis of variance and effect size-based selection to the expression data resulted in the identification of 21 probe sets corresponding to 20 genes whose expression was highly associated with clinical diagnosis. Furthermore, correspondence analysis and 3-D projection with these probe sets resulted in separation of the transcriptomes of pancreatic ductal cells into distinct but overlapping spaces corresponding to the two clinical classes. To establish an accurate transcriptome-based diagnosis system for PDC, we applied supervised class prediction algorithms to our large data set. With the expression profiles of only five predictor genes, the weighted vote method diagnosed the class of samples with an accuracy of 81.6%. Microarray analysis with purified pancreatic ductal cells has thus provided a basis for the development of a sensitive method for the detection of PDC.

Carcinoma, Pancreatic Ductal↗

PubMed2005

Comparative application of antibody and gene array for expression profiling in human squamous cell lung carcinoma.

Expression profiling by gene microarray techniques have been developed to predict malignant tissue but there are no experiences with the application of antibody arrays to identify malignancy-related proteins. Because altered protein patterns might also better interpret biological processes, we applied tumour samples from 12 patients with squamous cell lung carcinoma and individual lung tissue controls to antibody arrays spotted with 378 distinct monoclonal antibodies. Array analysis defined 20 proteins with higher and nine with lower abundance in lung tumours. Comparison with gene microarray data revealed that 31% of the differentially regulated proteins correlate with altered mRNA expression in squamous cell lung carcinomas, including PEX1, MKK7 and HDAC3 for up-regulated proteins. The histone deacetylase (HDAC) 3 was investigated in detail by immunoblot analysis showing that HDAC3 is indeed elevated in 92% of tumours (n=22/24; P<0.001). Thus, antibody microarrays can be useful for detection of some target proteins related to lung cancer.

Antibodies, Monoclonal↗

PubMed2005

Gene expression profiling of responses to dimethylarsinic acid in female F344 rat urothelium.

Gene expression profiling has been shown to be useful for identifying underlying mechanisms of toxicity, determining patterns of biological response, and elucidating candidate markers of exposure and response. Inorganic arsenic (iAs) is a human carcinogen and epidemiologic evidence implicates it in the development of urinary bladder cancer. Dimethylarsinic acid (DMA), the major excreted metabolite of iAs in humans, is a known rat bladder carcinogen. To examine the changes associated with DMA exposure, microarray analysis of the urothelium was performed in female F344 rats exposed to non-toxic and toxic doses of DMA in their drinking water for 28 days. A novel method for isolating predominantly urothelial cells was developed. Gene expression profiling of the urothelium using a custom 2-dye spotted array revealed that DMA treatment modulated the expression of transcripts of genes that regulate apoptosis, cell cycle regulation and the oxidative stress response. Expression of genes mapping to pathways involved in cancer control processes were also altered after DMA exposure. Morphological data suggested a dose dependent increase in cellular toxicity. Significant changes in differential gene expression were present after all treatments event at doses where standard toxicological responses were not detectable. The greatest perturbation in gene expression was present in rats after treatment with 40 ppm DMA. Doses which produced no histologic or ultrastructural evidence of toxicity (non-toxic) could be differentiated from toxic doses based on the expression of a subset of genes, which control cell signaling and the stress response. These reported changes in gene expression show similarities between the mechanisms of action of DMA in vivo and those previously described for iAs in vitro. These data illustrate the utility of transcriptional profiling and its potential in predicting key mechanistic pathways involved in toxicity and as a time efficient tool to inform the mode of action analysis in risk assessment.

Animals↗

PubMed2004

Skeletal muscle gene expression profiles in 20-29 year old and 65-71 year old women.

Gene expression profiling may provide leads for investigations of the molecular basis of functional declines associated with aging. In this study, high-density oligonucleotide arrays were used to probe the patterns of gene expression in skeletal muscle of seven young women (20-29 years old) and eight healthy older women (65-71 years old). The older subjects had reduced muscle mass, strength, and peak oxygen consumption relative to young women. There were approximately 1000 probe sets that suggested differential gene expression in younger and older muscle according to statistical criteria. The most highly overexpressed genes (>3-fold) in older muscle were p21 (cyclin-dependent kinase inhibitor 1A), which might reflect increased DNA damage, perinatal myosin heavy chain, which might reflect increased muscle fiber regeneration, and tomoregulin, which does not have a defined function in muscle. More than 40 genes encoding proteins that bind to pre-mRNAs or mRNAs were expressed at higher levels in older muscle. More than 100 genes involved in energy metabolism were expressed at lower levels in older muscle. In general, these results support previous observations on the differences in gene expression profiles between younger and older men.

Adult↗

PubMed2006

Comparison of gene expression profiles in core biopsies and corresponding surgical breast cancer samples.

INTRODUCTION: Gene expression profiling has been successfully used to classify breast cancer into clinically distinct subtypes, and to predict the risk of recurrence and treatment response. The aim of this study was to investigate whether the gene expression profile (GEP) detected in a core biopsy (CB) is representative for the entire tumor, since CB is an important tool in breast cancer diagnosis. Moreover, we investigated whether performing CBs prior to the surgical excision could influence the GEP of the respective tumor. METHODS: We quantified the RNA expression of 60 relevant genes by quantitative real-time PCR in paired CBs and surgical specimens from 22 untreated primary breast cancer patients. Subsequently, expression data were compared with independent GEPs obtained from tumors of 317 patients without preceding CB. RESULTS: In 82% of the cases the GEP detected in the CB correlated very well with the corresponding profile in the surgical sample (rs > or = 0.95, p < 0.001). Gene-by-gene analysis revealed four genes significantly elevated in the surgical sample compared to the CB; these comprised genes mainly involved in inflammation and the wound repair process as well as in tumor invasion and metastasis. CONCLUSION: A GEP detected in a CB are representative for the entire tumor and is, therefore, of clinical relevance. The observed alterations of individual genes after performance of CB deserve attention since they might impact the clinical interpretation with respect to prognosis and therapy prediction of the GEP as detected in the surgical specimen following CB performance.

Aged↗

PubMed2006

Establishment of a discriminant mathematical model for diagnosis of deficiency-cold syndrome using gene expression profiling.

OBJECTIVE: To screen diagnostic markers of Deficiency-Cold syndrome by gene expression profile and to establish a discriminant mathematical milliliters model for the clinical diagnosis of this syndrome based on a support vector machine (SVM). METHODS: A family suffering from Deficiency-Cold syndrome is chosen for this study. This family has 5 patients with Deficiency-Cold syndrome and 10 normal members. The peripheral blood samples for these 5 patients and 5 normal members are tested by using cDNA microarray with 18,816 clones to get their differential expression genes. These genes are further explored to understand their biological functions and pathways through existing databases. A SVM model for clinical diagnosis is then developed based on these differential expression genes. RESULTS: A total of 83 differential expression genes were identified between patients and normal members, in which 21 genes were recorded in the FATIGO database and 16 genes were related to metabolism. Eight (8) pathways were sorted out in the KEGG database, and half pathways were associated with human metabolism. A discriminant mathematical model based on a support vector machine successfully predicted a normal person and a patient with heavy Deficiency-Cold syndrome based on their gene differential expression profiles. Thus, this model may classify the Deficiency-Cold syndrome. CONCLUSION: This work demonstrates that the differential expression genes can be used to identify normal persons and patients with Deficiency-Cold syndrome. Deficiency-Cold syndrome is mainly associated with the metabolism-related gene regulations. In addition, the discriminant mathematical model based on a support vector machine is applicable to the clinical diagnosis for Deficiency-Cold syndrome.

Adolescent↗

PubMed2002

Clinical translation of gene expression profiling in lymphomas and leukemias.

Current lymphoma classification schemes that incorporate information on immunophenotype and genetic aberrations of the neoplastic cells represent a first attempt at a molecular diagnosis of these malignancies. Gene expression profiling using DNA microarrays promises to dramatically enhance molecular diagnosis by quantitating gene expression in tumor cells on a genomic scale. In this review, we focus on recent studies of diffuse large B-cell lymphoma (DLBCL) and chronic lymphocytic leukemia (CLL) that illustrate the effectiveness of gene expression profiling in defining molecularly distinct diseases. In DLBCL, germinal center B-like (GCB) and activated B-cell-like (ABC) subgroups differ in the expression of more than 1,000 genes and have a markedly different clinical outcome, suggesting that this diagnostic category includes at least two distinct molecular diseases. In CLL, by contrast, all cases express a characteristic set of genes, suggesting that CLL should be considered a single disease. Nonetheless, two subtypes of CLL exist that are distinguished by the presence or absence of immunoglobulin gene mutations, by the expression of approximately 175 genes, and by clinical course. Clinical translation of these results should be implemented initially in clinical trials where gene expression profiles could identify subsets of patients that are particularly responsive to the therapies being evaluated. As the armamentarium of molecularly targeted therapies expands, molecular diagnosis will be seen as an integral component of clinical management.

Gene Expression Profiling↗

PubMed2001

Expression profiling of renal epithelial neoplasms: a method for tumor classification and discovery of diagnostic molecular markers.

The expression patterns of 7075 genes were analyzed in four conventional (clear cell) renal cell carcinomas (RCC), one chromophobe RCC, and two oncocytomas using cDNA microarrays. Expression profiles were compared among tumors using various clustering algorithms, thereby separating the tumors into two categories consistent with corresponding histopathological diagnoses. Specifically, conventional RCCs were distinguished from chromophobe RCC/oncocytomas based on large-scale gene expression patterns. Chromophobe RCC/oncocytomas displayed similar expression profiles, including genes involved with oxidative phosphorylation and genes expressed normally by distal nephron, consistent with the mitochondrion-rich morphology of these tumors and the theory that both lesions are related histogenetically to distal nephron epithelium. Conventional RCCs underexpressed mitochondrial and distal nephron genes, and were further distinguished from chromophobe RCC/oncocytomas by overexpression of vimentin and class II major histocompatibility complex-related molecules. Novel, tumor-specific expression of four genes-vimentin, class II major histocompatibility complex-associated invariant chain (CD74), parvalbumin, and galectin-3-was confirmed in an independent tumor series by immunohistochemistry. Vimentin was a sensitive, specific marker for conventional RCCs, and parvalbumin was detected primarily in chromophobe RCC/oncocytomas. In conclusion, histopathological subtypes of renal epithelial neoplasia were characterized by distinct patterns of gene expression. Expression patterns were useful for identifying novel molecular markers with potential diagnostic utility.

Adult↗

PubMed2001

Transcriptome of channel catfish (Ictalurus punctatus): initial analysis of genes and expression profiles of the head kidney.

Analysis of expressed sequence tags (ESTs) is an efficient approach for gene discovery, expression profiling, and development of resources useful for functional genomics studies. As part of the transcriptome analysis in channel catfish (Ictalurus punctatus), we have conducted EST analysis using a cDNA library made from the head kidney. We analysed 2228 EST clones. Orthologues were established for 1495 (67.1%) clones representing 748 genes, of which 545 (36.5%) clones were singletons. The remaining 733 (32.9%) clones represent unknown gene clones, for which the number of genes has not yet been determined.

Animals↗

PubMed2003

GeneChip analysis of hippocampal gene expression profiles of short- and long-attack-latency mice: technical and biological implications.

To gain insight into the molecular mechanisms underlying the behavioral differences between two mouse lines genetically selected for long and short attack latency (LAL and SAL mice, respectively), we have recently applied the large-scale gene expression profiling method known as serial analysis of gene expression (SAGE) to generate hippocampal gene expression profiles of these mice. The aim of the present study is to extend and validate the SAGE expression profile of hippocampi of LAL and SAL mice using GeneChips (Affymetrix, Santa Clara, CA; one array per mouse, n = 5 per mouse line). As was the case with SAGE, GeneChips detect only medium- to high-abundance genes in the hippocampus. Extensive analysis of GeneChip data using very stringent parameters shows differential expression of 122 genes, all except one of which were expressed at higher levels in LAL mice (P < 0.01). As predicted by SAGE, our data indicate higher expression of several cytoskeleton genes in LAL mice, suggesting longer axonal and dendritic projections in the hippocampus of these mice. This is consistent with our tentative model, in which the behavioral differences between LAL and SAL mice may be related to structural differences in the hippocampus. In addition, a group of 76 genes with diverse biological function and 46 expressed sequence tags (ESTs) were all expressed at higher levels in LAL mice. A novel finding in this study was the significantly lower expression of only a single gene, growth arrest-specific gene (gas5), in LAL mice. As gas5 does not encode a protein but several small nuclear RNAs, our data suggest that small RNAs may contribute to the molecular mechanisms underlying the extreme behavioral differences between LAL and SAL mice.

Aggression↗

PubMed2002

mRNA expression profiling of laser microbeam microdissected cells from slender embryonic structures.

Microarray hybridization has rapidly evolved as an important tool for genomic studies and studies of gene regulation at the transcriptome level. Expression profiles from homogenous samples such as yeast and mammalian cell cultures are currently extending our understanding of biology, whereas analyses of multicellular organisms are more difficult because of tissue complexity. The combination of laser microdissection, RNA amplification, and microarray hybridization has the potential to provide expression profiles from selected populations of cells in vivo. In this article, we present and evaluate an experimental procedure for global gene expression analysis of slender embryonic structures using laser microbeam microdissection and laser pressure catapulting. As a proof of principle, expression profiles from 1000 cells in the mouse embryonic (E9.5) dorsal aorta were generated and compared with profiles for captured mesenchymal cells located one cell diameter further away from the aortic lumen. A number of genes were overexpressed in the aorta, including 11 previously known markers for blood vessels. Among the blood vessel markers were endoglin, tie-2, PDGFB, and integrin-beta1, that are important regulators of blood vessel formation. This demonstrates that microarray analysis of laser microbeam micro-dissected cells is sufficiently sensitive for identifying genes with regulative functions.

Animals↗

PubMed2005

Expression profiling of serous low malignant potential, low-grade, and high-grade tumors of the ovary.

Papillary serous low malignant potential (LMP) tumors are characterized by malignant features and metastatic potential yet display a benign clinical course. The role of LMP tumors in the development of invasive epithelial cancer of the ovary is not clearly defined. The aim of this study is to determine the relationships among LMP tumors and invasive ovarian cancers and identify genes contributing to their phenotypes. Affymetrix U133 Plus 2.0 microarrays (Santa Clara, CA) were used to interrogate 80 microdissected serous LMP tumors and invasive ovarian malignancies along with 10 ovarian surface epithelium (OSE) brushings. Gene expression profiles for each tumor class were used to complete unsupervised hierarchical clustering analyses and identify differentially expressed genes contributing to these associations. Unsupervised hierarchical clustering analysis revealed a distinct separation between clusters containing borderline and high-grade lesions. The majority of low-grade tumors clustered with LMP tumors. Comparing OSE with high-grade and LMP expression profiles revealed enhanced expression of genes linked to cell proliferation, chromosomal instability, and epigenetic silencing in high-grade cancers, whereas LMP tumors displayed activated p53 signaling. The expression profiles of LMP, low-grade, and high-grade papillary serous ovarian carcinomas suggest that LMP tumors are distinct from high-grade cancers; however, they are remarkably similar to low-grade cancers. Prominent expression of p53 pathway members may play an important role in the LMP tumor phenotype.

Carcinoma, Papillary↗

PubMed2003

Gene expression profiles obtained from fine-needle aspirations of breast cancer reliably identify routine prognostic markers and reveal large-scale molecular differences between estrogen-negative and estrogen-positive tumors.

PURPOSE: The purpose of this study was to determine whether comprehensive transcriptional profiles (TPs) can be obtained from single-passage fine-needle aspirations (FNAs) of breast cancer and to explore whether profiles capture routine clinicopathological parameters. EXPERIMENTAL DESIGN: Expression profiles were available on 38 patients with stage I-III breast cancer who underwent FNA at the time of diagnosis. [(33)P]dCTP-labeled cDNA probes were generated and hybridized to cDNA membrane microarrays that contained 30,000 human sequence clones, including 10,890 expressed sequence tags. RESULTS: The median total RNA yield from the biopsies was 2 micro g (range, 1-25 micro g). The cellular composition of each biopsy was examined and, on average, 79% of the cells were cancer cells. TP was successfully performed on all 38 of the biopsies. Unsupervised complete-linkage hierarchical clustering with all of the biopsies revealed an association between estrogen receptor (ER) status and gene expression profiles. There was a strong correlation between ER status determined by TP and measured by routine immunohistochemistry (P = 0.001). A similar strong correlation was seen with HER-2 status determined by fluorescent in situ hybridization (P = 0.0002). Using the first 18 cases as the discovery set, we established a cutoff of 2.0 and 18.0 for ER and HER-2 mRNA levels, respectively, to distinguish clinically-negative from -positive cases. We also identified 105 genes (excluding the ER gene) the expression of which correlated highly with clinical ER status. Twenty tumors were used for prospective validation. HER-2 status was correctly identified in all 20 of the cases, based on HER-2 mRNA content detected by TP. ER status was correctly identified in 19 of 20 cases. When the marker set of 105 genes was used to prospectively predict ER status, TP-based classification correctly identified 9 of 10 of the ER-positive and 7 of 10 of the ER-negative tumors. We also explored supervised cluster analysis using various functional categories of genes, and we observed a clear separation between ER-negative and ER-positive tumors when genes involved in signal transduction were used for clustering. CONCLUSIONS: These results demonstrate that comprehensive TP can be performed on FNA biopsies. TPs reliably measure conventional single-gene prognostic markers such as ER and HER-2. A complex pattern of genes (not including ER) can also be used to predict clinical ER status. These results demonstrate that needle biopsy-based diagnostic microarray tests may be developed that could capture conventional prognostic information but may also contain additional clinical information that cannot currently be measured with other methods.

Adult↗

PubMed2004

Gene expression profiles derived from single cells in human postmortem brain.

The study of postmortem human brain tissue remains the basis for the understanding of many CNS disorders and to verify data obtained in experimental studies. So far, however, gene expression profiling in cellular sub-populations derived from human postmortem brain was hampered by several technical drawbacks. Here, we describe a method that allows the generation of mRNA expression profiles from single neurons. Dopaminergic neurons from different midbrain areas including substantia nigra, central gray substance and ventral tegmental area were identified and isolated by immuno-laser capture microscopy (LCM). Expression profiles were generated from microdissected cells using a modified RNA fingerprinting protocol. Using this approach, we were able to generate specific RNA fingerprints at a high resolution from phenotype-specific single neurons. Polymorphic fragments were isolated from gels and differential gene expression was confirmed by real-time PCR using gene-specific primer pairs and hybridization probes. The method described here is easy to use and reliable for profiling gene expression at the single cell level in human postmortem brain. It could therefore be valuable to open new insights into the molecular pathogenesis of CNS disorders.

Aged↗

PubMed2006

cDNA microarray analysis reveals fundamental differences in the expression profiles of primary human monocytes, monocyte-derived macrophages, and alveolar macrophages.

We report the systematic use of large-scale cDNA microarrays to study the gene expression profiles of primary human peripheral blood monocytes (MONO) in comparison with in vitro-differentiated, M-CSF-induced MONO-derived macrophages (MAC) and primary human alveolar MAC (AM), obtained by bronchoalveolar lavage from the lungs of normal volunteers. These studies revealed large-scale differences in the gene expression profile between both MAC types (MAC and AM) and MONO. In addition, large differences were observed in the gene expression profiles of the two MAC types. Specifically, 21% of genes on the array (2904 out of 13,582) were differentially expressed between AM and MONO, and 2229 out of 13,583 probes were differentially expressed between MAC and AM. Our expression data show remarkable differences in gene expression between different MAC subpopulations and emphasize the heterogeneity of different MAC populations. This study underscores the need to scrutinize models of MAC biology for relevance to specific disease processes.

Adult↗

PubMedDate not supplied

The detection of hamster connexins: a comparison of expression profiles with wild-type mouse and the cancer-prone Min mouse.

The open reading frames of 17 connexins from Syrian hamster (using tissues) and 16 connexins from the Chinese hamster cell line V79, were fully (Cx30, Cx31, Cx37, Cx43 and Cx45) or partially sequenced. We have also detected, and partially sequenced, seven rat connexins that previously were unavailable. The expression of connexin genes was examined in some hamster organs and cultured hamster cells, and compared with wild-type mouse and the cancer-prone Min mouse. Although the expression patterns were similar for most organs and connexins in hamster and mouse, there were also some prominent differences (Cx29 and 30.3 in testis; Cx31.1 and 32 in eye; Cx46 in brain, kidney and testis; Cx47 in kidney). This suggests that some connexins have species-specific expression profiles. In contrast, there were minimal differences in expression profiles between wild type and Min mice. Species-specific expression profiles should be considered in attempts to make animal models of human connexin-associated diseases.

Animals↗

PubMed2006

Expression profiling of proteins in L-threonine biosynthetic pathway of Escherichia coli by using antibody microarray.

We demonstrate the use of an antibody (Ab) microarray for a comparative expression profiling of proteins in an L-threonine biosynthetic pathway of Escherichia coli between a parental strain (W3110) and L-threonine overproducing mutant (TF5015). On the basis of a global comparative transcriptome analysis between the two strains, 28 analytical target proteins were selected and subjected to a production of polyclonal Abs against them. An Ab microarray was constructed by spotting a set of produced antibodies on a glass slide, and was employed for a comparative expression profiling of the proteins between the two strains by a two-color fluorescence assay method. The performance of the Ab microarray was evaluated with respect to cross-reactivity of the antibodies, dye-labeling efficiency, and the nature of antigenic proteins. Of these, the cross-reactivity of the used antibodies was found to mainly cause the deviation of the observed expression ratios from the expected ones. To offset the deviations, correction factors were derived from a statistical analysis and introduced. As a result, ten proteins were categorized to be up-regulated, while one was down-regulated in TF5015. Expression profiling of proteins using the Ab microarray was further verified by comparison with Western blotting and 2-DE.

Antibodies, Bacterial↗

PubMed2004

Angiogenesis gene expression profiling in xenograft models to study cellular interactions.

The present study describes a method to simultaneously obtain the angiogenic expression profile in tumor cells and vascular cells of a single tumor. Human- and mouse-specific primers were used for quantitative real-time RT-PCR to determine the expression of vascular endothelial growth factors A, B, C, and D, vascular endothelial growth factor receptors 1, 2, and 3, neuropilin 1 and 2, angiopoietin 1, 2, 3/4, tyrosine kinase receptors 1 and 2, basic fibroblast growth factor (bFGF) in xenograft tumors obtained by injection of human ovarian carcinoma cells in nude mice. In addition, the effect of treatment with anginex and taxol on the expression profile was analyzed. Most factors were expressed higher in vascular cells as compared to tumor cells. In response to treatment, tumor cells significantly upregulated bFGF expression and downregulated VEGF receptor expression. This was accompanied by downregulation of VEGF-B and -D, and upregulation of angiopoietin-3 as well as angiopoetin receptors in nontumor cells. In conclusion, real-time qRT-PCR combined with xenograft tumor models presents a sensitive method to monitor angiogenesis and to analyze interactions between tumor cells and nontumor cells in vivo. The approach can be applied to different research fields in which xenograft models are used.

Angiogenesis Inhibitors↗