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Samir Hanash

Publications and source records attributed to Samir Hanash.

At least 37 records · Page 2Linked to original sources
PubMed2004

Hepatitis C virus NS5A-regulated gene expression and signaling revealed via microarray and comparative promoter analyses.

Most individuals exposed to hepatitis C virus (HCV) become chronically infected and are predisposed to liver disease. The mechanisms underlying viral persistence and disease progression are unknown. A role for the HCV NS5A protein in viral replication and interferon resistance has been demonstrated. To identify mechanisms affected by NS5A, we analyzed the gene expression of Huh7 cells expressing NS5A and control cells using oligonucleotide microarrays. A set of 103 genes (43 up-regulated, 60 down-regulated) whose expression was modified by at least twofold was selected. These included genes involved in cell adhesion and motility, calcium homeostasis, lipid transport and metabolism, and genes regulating immune responses. The finding of modulated expression of genes related to the TGF-beta superfamily and liver fibrosis was observed. Interestingly, both the tumor necrosis factor and lymphotoxin beta receptors were down-regulated by NS5A. Similar data were obtained following expression of four NS5A mutants obtained from patients who were not responsive or were sensitive to interferon therapy. Through computational analysis, we determined that 39 of the 43 genes up-regulated by NS5A contained one or more nuclear factor kappaB (NF-kappaB) binding sites within their promoter region. Using the Gibbs sampling method, we also detected enrichment of NF-kappaB consensus binding sites in the upstream regions of the 43 coexpressed genes. Activation of NF-kappaB by NS5A was subsequently demonstrated in luciferase reporter assays. Adenovirus-mediated expression of IkappaBalpha reverted NS5A mediated up-regulation of gene expression. In conclusion, this study suggests a role of NS5A and NF-kappaB in HCV pathogenesis and related liver disease. Supplementary material for this article can be found on the HEPATOLOGY website (http://interscience.wiley.com/jpages/0270-9139/suppmat/index.html).

Amino Acid Sequence↗
PubMed2004

The molecular basis of pancreatic fibrosis: common stromal gene expression in chronic pancreatitis and pancreatic adenocarcinoma.

OBJECTIVES: Tissue desmoplasia occurs in a number of disease states, but its molecular basis is poorly understood. To determine which genes are overexpressed in cells contained within the desmoplastic stroma of pancreatic adenocarcinoma and chronic pancreatitis, we undertook genetic profiling of microdissected tissue samples of pancreatic adenocarcinoma, chronic pancreatitis, normal pancreas, and pancreatic cancer cell lines. We observed that samples of both pancreatic adenocarcinoma and chronic pancreatitis showed elevated expression of many shared genes compared with the normal pancreas. We hypothesized that these common genes likely important in stromal production and/or function could be identified using a strategy that involved comparisons between pancreatic adenocarcinoma, chronic pancreatitis, normal pancreas, and pancreatic cancer cell lines. METHODS: We performed oligonucleotide microarray analysis of 6800 different genes expressed in 10 samples of pancreatic adenocarcinoma, 5 samples of normal pancreas, 5 samples of chronic pancreatitis, and 7 pancreatic cancer cell lines. Microarray findings were validated with RT-PCR, and immunohistochemistry was used to verify protein localization to the stromal compartment of both pancreatic cancer and chronic pancreatitis. RESULTS: We employed a deductive comparison whereby genes expressed in the normal pancreas and pancreatic cancer cell lines were selectively eliminated from those expressed in common by pancreatic adenocarcinoma and chronic pancreatitis. This strategy identified 107 genes predicted to be expressed within cells of the stromal compartment of both pancreatic adenocarcinoma and chronic pancreatitis. CONCLUSIONS: These genes are likely important factors in epithelial-stromal signaling in pancreatic desmoplasia and may serve as diagnostic or therapeutic targets.

Adenocarcinoma↗
PubMed2004

Proteomics approaches to identify tumor antigen directed autoantibodies as cancer biomarkers.

The identification of autoantibodies to tumor cell proteins by proteomics approaches has great potential impact on cancer biomarker discovery. The humoral immune response represents a form of biological amplification of signals that are otherwise weak due to very low concentrations of antigen, especially in the early stages of cancers. In addition, proteomics can detect immunoreactivity directed against protein post-translational modifications. Two-dimensional gel based Western blots, protein antigen microarrays, and multiplex ELISA reactions have been applied by our group to antigen based biomarker detection and validation. The latter two are based on liquid-phase separations that are suitable for automation. This work has resulted in the identification of numerous cancer biomarker candidates. Large clinical studies are currently planned to establish their value in early cancer diagnosis.

Antibodies, Neoplasm↗
PubMed2004

A genome scanning approach to assess the genetic effects of radiation in mice and humans.

We used Restriction Landmark Genome Scanning (RLGS) to assess, on a genome-wide basis, the mutation induction rate in mouse germ cells after radiation exposure. Analyses of 1,115 autosomal NotI DNA fragments per mouse for reduced spot intensity, indicative of loss of one copy, in 506 progeny derived from X-irradiated spermatogonia (190, 237 and 79 mice in 0-, 3-, and 5-Gy groups, respectively), permitted us to identify 16 mutations affecting 23 fragments in 20 mice. The 16 mutations were composed of eight small changes (1-9 bp) at microsatellite sequences, five large deletions (more than 25 kb), and three insertions of SINE B2 or LINE1 transposable elements. The maximum induction rate of deletion mutations was estimated as (0.17 +/- 0.09) x 10(-5)/locus Gy(-1). The estimate is considerably lower than 1 x 10(-5)/locus Gy(-1), the mean induction rate of deletion mutations at Russell's 7 loci, which assumed that deletion mutations comprise 50% of all mutations. We interpret the results as indicating that the mean induction rate of mutations in the whole genome may be substantially lower than that at the 7 loci. We also demonstrate the applicability of RLGS for detection of human mutations, which allows direct comparisons between the two species.

Animals↗
PubMed2003

Inducible expression of macrophage receptor Marco by dendritic cells following phagocytic uptake of dead cells uncovered by oligonucleotide arrays.

The efficient Ag presenting and immunostimulatory capacity of dendritic cells (DCs) has led to the use of tumor Ag-pulsed DCs in treatment regimens for cancer. Although vaccine studies involving tumor lysate-pulsed DCs have been performed, little, if any, information is available on the effects of phagocytic uptake of tumor lysate on DC biology and function. We have investigated gene expression pattern differences between unpulsed DCs and tumor lysate-pulsed-DCs, using Affymetrix MG-U74Av2 oligonucleotide arrays, which contain approximately 12,000 genes and expressed sequence tags. Upon 24 h tumor lysate pulsing, the levels of 87 transcripts increased at least 3-fold while the levels of 121 transcripts were reduced by one-third or more, with accompanying p values <0.01. Most of these genes encoded proteins important for DC effector functions including cytokines, chemokines, and receptors, such as IL-12p40, macrophage inflammatory protein-2, and IL-6; Ag presentation, such as carboxypeptidase D and H2-DM; cell adhesion (e.g., EGF-like module containing, mucin-like, hormone receptor-like sequence 1, rhoB); and T cell activation. Interestingly, we observed a high level of expression of a novel member of the class A scavenger receptor family, macrophage receptor with collagenous structure (Marco). Marco is thought to play an important role in the immune response by mediating binding and phagocytosis, but also in the formation of lamellipodia-like structures and of dendritic processes. Therefore, we have identified a repertoire of genes that likely play a role in DC function.

Animals↗
PubMed2003

Pancreatic gene expression during the initiation of acute pancreatitis: identification of EGR-1 as a key regulator.

We hypothesized that genes expressed in pancreatic acinar cells during the initiation of acute pancreatitis determine the severity of the disease. Therefore, we utilized microarrays to identify those genes commonly induced in rat pancreatic acinar cells within 1-4 h in two in vivo models, caerulein and taurocholate administration. This strategy yielded 51 known genes representing a complex array of molecules, including those that are likely to either reduce or increase the severity of the disease. Novel genes identified in the current study included ATF3, BRF1, C/EBPbeta, CGRP, EGR-1, ephrinA1, villin2, ferredoxin, latexin, lipocalin, MKP-1, NGFI-B, RhoA, tissue factor (TF), and syndecan. To validate these microarray results, the role of EGR-1 was further investigated using quantitative RT-PCR, Western blotting, and immunocytochemistry. EGR-1 expression occurred within acinar cells and correlated with the development of caerulein-induced acute pancreatitis in rats. Furthermore, the levels of the inflammation-related genes MCP-1, PAI, TF, IL-6, and ICAM-1 and the extent of lung inflammation were reduced during the initiation of caerulein-induced acute pancreatitis in EGR-1-deficient mice. Thus this study identified EGR-1 and several other novel genes likely to be important in the development and severity of acute pancreatitis.

Acute Disease↗
PubMed2003

Profiling of pathway-specific changes in gene expression following growth of human cancer cell lines transplanted into mice.

BACKGROUND: Tumor cells cultured in vitro are widely used to investigate the molecular biology of cancers and to evaluate responses to drugs and other agents. The full extent to which gene expression in cancer cells is modulated by extrinsic factors and by the microenvironment in which the cancer cells reside remains to be determined. Two cancer cell lines (A549 lung adenocarcinoma and U118 glioblastoma) were transplanted subcutaneously into immunodeficient mice to form tumors. Global gene-expression profiles of the tumors were determined, based on analysis of expression of human genes, and compared with expression profiles of the cell lines grown in culture. RESULTS: A bioinformatics approach associated genes that showed changes in their expression levels with functional classes as defined by either the GO gene annotations or MeSH terms in the literature. The classes of genes expressed at higher levels in cells grown in vitro indicated increased cell division and metabolism, reflecting the more favorable environment for cell proliferation. In contrast, in vivo tumor growth resulted in upregulation of a significant number of genes involved in the extracellular matrix (ECM), cell adhesion, cytokine and metalloendopeptidase activity, and neovascularization. When placed in comparable tissue environments, the U118 cells and the A549 cells expressed different sets of ECM and cell adhesion-related genes, suggesting different mechanisms of extracellular interaction at work in the different cancers. CONCLUSIONS: Studies of this type allow us to examine the specific contribution of cancer cells to gene expression patterns within an in vivo tumor mixed with non-cancerous tissue.

Animals↗
PubMed2003

DNA methylation and chromatin structure regulate T cell perforin gene expression.

Perforin is a cytotoxic effector molecule expressed in NK cells and a subset of T cells. The mechanisms regulating its expression are incompletely understood. We observed that DNA methylation inhibition could increase perforin expression in T cells, so we examined the methylation pattern and chromatin structure of the human perforin promoter and upstream enhancer in primary CD4(+) and CD8(+) T cells as well as in an NK cell line that expresses perforin, compared with fibroblasts, which do not express perforin. The entire region was nearly completely unmethylated in the NK cell line and largely methylated in fibroblasts. In contrast, only the core promoter was constitutively unmethylated in primary CD4(+) and CD8(+) cells, and expression was associated with hypomethylation of an area residing between the upstream enhancer at -1 kb and the distal promoter at -0.3 kb. Treating T cells with the DNA methyltransferase inhibitor 5-azacytidine selectively demethylated this area and increased perforin expression. Selective methylation of this region suppressed promoter function in transfection assays. Finally, perforin expression and hypomethylation were associated with localized sensitivity of the 5' flank to DNase I digestion, indicating an accessible configuration. These results indicate that DNA methylation and chromatin structure participate in the regulation of perforin expression in T cells.

5' Untranslated Regions↗
PubMed2003

Molecular profiling of pancreatic adenocarcinoma and chronic pancreatitis identifies multiple genes differentially regulated in pancreatic cancer.

The molecular basis of pancreatic cancer is not understood. Previous attempts to determine the specific genes expressed in pancreatic cancer have been hampered by similarities between adenocarcinoma and chronic pancreatitis. In the current study, microarrays (Affymetrix) were used to profile gene expression in pancreatic adenocarcinoma (10), pancreatic cancer cell lines (7), chronic pancreatitis (5), and normal pancreas (5). Molecular profiling indicated a large number of genes differentially expressed between pancreatic cancer and normal pancreas but many fewer differences between pancreatic cancer and chronic pancreatitis, likely because of the shared stromal influences in the two diseases. To specifically identify genes expressed in neoplastic epithelium, we selected genes more highly expressed (>2-fold, p < 0.01) in adenocarcinoma compared with both normal pancreas and chronic pancreatitis and which were also highly expressed in pancreatic cancer cell lines. This strategy yielded 158 genes, of which 124 were not previously associated with pancreatic cancer. Quantitative-reverse transcription-PCR for two molecules, S100P and 14-3-3sigma, validated the microarray data. Support for the success of the neoplastic cell gene expression identification strategy was obtained by immunocytochemical localization of four representative genes, 14-3-3sigma, S100P, S100A6, and beta4 integrin, to neoplastic cells in pancreatic tumors. Thus, comparisons between pancreatic adenocarcinoma, pancreatic cancer cell lines, normal pancreas, and chronic pancreatitis have identified genes that are selectively expressed in the neoplastic epithelium of pancreatic adenocarcinoma. These data provide new insights into the molecular pathology of pancreatic cancer that may be useful for detection, diagnosis, and treatment.

Adenocarcinoma↗
PubMed2003

Gene expression patterns define pathways correlated with loss of differentiation in lung adenocarcinomas.

An analysis of microarray data from 86 lung adenocarcinomas reveals hundreds of genes significantly correlated with tumor cell differentiation. A bioinformatics approach of linking these genes to public information from the Locuslink and KEGG databases yields evidence for a loss of tumor cell differentiation being associated with biological processes of cell division, protein degradation, pyrimidine and purine metabolism, oxidative phosphorylation, glyoxylate and dicarboxylate metabolism, folate biosynthesis, and glutamate metabolism. The increased expression of genes involved in these processes is consistent with increased proliferation and metabolism characteristics of poorly differentiated tumors. The complete results of this analysis are available at http://dot.ped.med.umich.edu:2000/pub/diff/index.htm.

Adenocarcinoma↗
PubMed2003

T cell chemokine receptor expression in aging.

Changes in chemokine receptor expression are important in determining T cell migration and the subsequent immune response. To better understand the contribution of the chemokine system in immune senescence we determined the effect of aging on CD4(+) T cell chemokine receptor function using microarray, RNase protection assays, Western blot, and in vitro chemokine transmigration assays. Freshly isolated CD4(+) cells from aged (20-22 mo) mice were found to express a higher level of CCR1, 2, 4, 5, 6, and 8 and CXCR2-5, and a lower level of CCR7 and 9 than those from young (3-4 mo) animals. Caloric restriction partially or completely restored the aging effects on CCR1, 7, and 8 and CXCR2, 4, and 5. The aging-associated differences in chemokine receptor expression cannot be adequately explained by the age-associated shift in the naive/memory or Th1/Th2 profile. CD4(+) cells from aged animals have increased chemotactic response to stromal cell-derived factor-1 and macrophage-inflammatory protein-1alpha, suggesting that the observed chemokine receptor changes have important functional consequences. We propose that the aging-associated changes in T cell chemokine receptor expression may contribute to the different clinical outcome in T cell chemokine receptor-dependent diseases in the elderly.

Aging↗
PubMed2003

Profiling of the cell surface proteome.

The in depth-mining of the proteome necessitates the comprehensive analysis of proteins in individual subcellular compartments to uncover interesting patterns of protein expression that include assessment of protein location, trafficking and of post-translational modifications that are location specific. One of the compartments of substantial interest from a diagnostic and therapeutic point of view is the plasma membrane which contains intrinsic membrane proteins and other proteins expressed on the cell surface. Technologies are currently available for the comprehensive profiling of the cell surface proteome that rely on protein tagging of intact cells. Studies are emerging that point to unexpected patterns of expression of specific proteins on the cell surface, with a common occurrence of proteins previously considered to occur predominantly in other compartments, notably the endoplasmic reticulum. The profiling of the cell surface and plasma membrane proteomes will likely provide novel insights and uncover disease related alterations.

ADP-ribosyl Cyclase↗
PubMed2003

Microarrays of tumor cell derived proteins uncover a distinct pattern of prostate cancer serum immunoreactivity.

The broad characterization of the immune responses elicited by tumors has valuable applications in diagnostics and basic research. We present here the use of microarrays of tumor-derived proteins to profile the antibody repertoire in the sera of prostate cancer patients and controls. Two-dimensional liquid chromatography was used to separate proteins from the prostate cancer cell line LNCaP into 1760 fractions. These fractions were spotted in microarrays on coated microscope slides, and the microarrays were incubated individually with serum samples from 25 men with prostate cancer and 25 male controls. The amount of immunoglobulin bound to each fraction by each serum sample was quantified. Statistical analysis revealed that 38 of the fractions had significantly higher levels of immunoglobulin binding in the prostate cancer samples compared to the controls. Two fractions showed higher binding in the control samples. The significantly higher immunoglobulin reactivity from the prostate cancer samples may reflect a strong immune response to the tumors in the prostate cancer patients. We used multivariate analysis to classify the samples as either prostate cancer or control. In a cross-validation study, recursive partitioning classified the samples with 84% accuracy. A decision tree with two levels of partitioning classified the samples with 98% accuracy. Additional studies will allow further characterization of tumor antigens in prostate cancer and their significance for diagnosis. These results suggest that microarrays of fractionated proteins could be a powerful tool for tumor antigen discovery and cancer diagnosis.

Antibodies, Neoplasm↗
PubMed2003

Accurate molecular classification of human cancers based on gene expression using a simple classifier with a pathological tree-based framework.

Recent studies suggest accurate prediction of tissue of origin for human cancers can be achieved by applying sophisticated statistical learning procedures to gene expression data obtained from DNA microarrays. We have pursued the hypothesis that a more straightforward and equally accurate strategy for classifying human tumors is to use a simple algorithm that considers gene expression levels within a tree-based framework that encodes limited information about pathology and tissue ontogeny. By considering gene expression data within this framework, we found only a small number of genes were required to achieve a relatively high accuracy level in tumor classification. Using as few as 45 genes we were able to classify 157 of 190 human malignant tumors correctly, which is comparable to previous results obtained with sophisticated classifiers using thousands of genes. Our simple classifier accurately predicted the origin of metastatic tumors even when the classifier was trained using only primary tumors, and the classifier produced accurate predictions when trained and tested on expression data from different labs, and from different microarray platforms. Our findings suggest that accurate and robust cancer diagnosis from gene expression profiles can be achieved by mimicking the classification strategies routinely used by surgical pathologists.

Algorithms↗
PubMed2003

Amplification and overexpression of the L-MYC proto-oncogene in ovarian carcinomas.

Gene amplification is an important mechanism of oncogene activation in various human cancers, including ovarian carcinomas (OvCas). We used restriction landmark genomic scanning (RLGS) to detect amplified DNA fragments in the genomes of 47 primary OvCas. Visual analysis of the RLGS gel images revealed several OvCa samples with spots of greater intensity than corresponding spots from normal tissues, indicating possible DNA amplification in specific tumors. Two primary tumors (E1 and S12) shared four high-intensity spots. A recently developed informatics tool termed Virtual Genome Scans was used to compare the RLGS patterns in these tumors with patterns predicted from the human genome sequence. Virtual Genome Scans determined that three of the four fragments localized to chromosome 1p34-35, a region containing the proto-oncogene L-MYC. Sixty-eight primary OvCas, including 40 analyzed by RLGS, were screened by quantitative polymerase chain reaction (PCR) for possible amplification of L-MYC. Ten tumors with increased L-MYC copy number were identified, including tumor E1, which showed an approximately 24-fold increase in copy number compared to normal DNA. Southern analysis of several tumors confirmed the quantitative PCR results. Using sequence tagged site (STS) markers flanking L-MYC, increased DNA copy number in tumor E1 was found to span the region flanking L-MYC between D1S432 and D1S463 ( approximately 3.1 Mb). Other tumors showed amplification only at the L-MYC locus. Using oligonucleotide microarrays, L-MYC was found to be more frequently overexpressed in OvCas than either c-MYC or N-MYC relative to ovarian surface epithelium. Quantitative reverse transcriptase-PCR analysis confirmed elevated L-MYC expression in a substantial fraction of OvCas, including nine of nine tumors with increased L-MYC copy number. The data implicate L-MYC gene amplification and/or overexpression in human OvCa pathogenesis.

Base Sequence↗
PubMed2003

Mining gene expression databases for association rules.

MOTIVATION: Global gene expression profiling, both at the transcript level and at the protein level, can be a valuable tool in the understanding of genes, biological networks, and cellular states. As larger and larger gene expression data sets become available, data mining techniques can be applied to identify patterns of interest in the data. Association rules, used widely in the area of market basket analysis, can be applied to the analysis of expression data as well. Association rules can reveal biologically relevant associations between different genes or between environmental effects and gene expression. An association rule has the form LHS --> RHS, where LHS and RHS are disjoint sets of items, the RHS set being likely to occur whenever the LHS set occurs. Items in gene expression data can include genes that are highly expressed or repressed, as well as relevant facts describing the cellular environment of the genes (e.g. the diagnosis of a tumor sample from which a profile was obtained). RESULTS: We demonstrate an algorithm for efficiently mining association rules from gene expression data, using the data set from Hughes et al. (2000, Cell, 102, 109-126) of 300 expression profiles for yeast. Using the algorithm, we find numerous rules in the data. A cursory analysis of some of these rules reveals numerous associations between certain genes, many of which make sense biologically, others suggesting new hypotheses that may warrant further investigation. In a data set derived from the yeast data set, but with the expression values for each transcript randomly shifted with respect to the experiments, no rules were found, indicating that most all of the rules mined from the actual data set are not likely to have occurred by chance. AVAILABILITY: An implementation of the algorithm using Microsoft SQL Server with Access 2000 is available at http://dot.ped.med.umich.edu:2000/pub/assoc_rules/assoc_rules.zip. Our results from mining the yeast data set are available at http://dot.ped.med.umich.edu:2000/pub/assoc_rules/yeast_results.zip.

Algorithms↗