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PubMed2004

Microarray-based, high-throughput gene expression profiling of microRNAs.

MicroRNAs (miRNAs) are small regulatory RNAs that serve fundamental biological roles across eukaryotic species. We describe a new method for high-throughput miRNA detection. The technique is termed the RNA-primed, array-based Klenow enzyme (RAKE) assay, because it involves on-slide application of the Klenow fragment of DNA polymerase I to extend unmodified miRNAs hybridized to immobilized DNA probes. We used RAKE to study human cell lines and brain tumors. We show that the RAKE assay is sensitive and specific for miRNAs and is ideally suited for rapid expression profiling of all known miRNAs. RAKE offers unique advantages for specificity over northern blots or other microarray-based expression profiling platforms. Furthermore, we demonstrate that miRNAs can be isolated and profiled from formalin-fixed paraffin-embedded tissue, which opens up new opportunities for analyses of small RNAs from archival human tissue. The RAKE assay is theoretically versatile and may be used for other applications, such as viral gene profiling.

Cell Line↗
PubMed2005

Gene expression profiling of colorectal adenomas and early invasive carcinomas by cDNA array analysis.

It is generally accepted that most colorectal carcinomas arise in pre-existing adenomas. Morphologically, colorectal adenomas can be divided into two groups, protruded type and flat type. The aim of this study was to clarify relevant alterations of gene expression associated with the early stage of colorectal carcinogenesis. Using cDNA array, we analysed the expression profiles of 550 cancer-related genes in 36 colorectal adenomas (18 flat-type and 18 protruded-type adenomas) and 14 early invasive carcinomas. Among the 550 genes, we chose 32 genes the average expression levels of which were at least three-fold up- or downregulated in tumour tissues compared with levels in matched normal tissues. A total of 13 and 19 genes were identified as up- and downregulated genes in tumour tissues, respectively. Among the upregulated genes, the average expression levels of E1AF, bone morphogenic protein (BMP)-4, insulin-like growth factor (IGF)-2, inducible nitric oxide synthase (iNOS), tissue inhibitors of metalloproteinase (TIMP)-1, Smad4, and nm23 in tumour tissues were over five times higher than those in matched normal tissues. Colorectal adenomas and early invasive carcinomas were divided into two major clusters by clustering analysis. Moreover, flat- and protruded-type adenomas were divided into two major clusters by clustering analysis. The expression profiles obtained by the cDNA array clearly indicate that colorectal adenomas and early invasive carcinomas have specific expression profiles. Likewise, the gene expression profiles of flat- and protruded-type adenomas are different. These results indicate that molecular classification of early colorectal tumours by a cDNA array is feasible.

Adenoma↗
PubMed2001

Distinctive gene expression profiles associated with Hepatitis B virus x protein.

Hepatitis B virus (HBV) is a major risk factor for the development of hepatocellular carcinoma (HCC). HBV encodes the potentially oncogenic HBx protein, which mainly functions as a transcriptional co-activator involving in multiple gene deregulations. However, mechanisms underlying HBx-mediated oncogenicity remain unclear. To determine the role(s) of HBx in the early genesis of HCC, we utilized the NCI Oncochip microarray that contains 2208 human cDNA clones to examine the gene expression profiles in either freshly isolated normal primary adult human hepatocytes (Hhep) or an HCC cell line (SK-Hep-1) ecotopically expressing HBx via an adenoviral system. The gene expression profiles also were determined in liver samples from HBV-infected chronic active hepatitis patients when compared with normal liver samples. The microarray results were validated through Northern blot analysis of the expression of selected genes. Using reciprocally labeling hybridizations, scatterplot analysis of gene expression ratios in human primary hepatocytes expressing HBx demonstrates that microarrays are highly reproducible. The comparison of gene expression profiles between HBx-expressing primary hepatocytes and HBV-infected liver samples shows a consistent alteration of many cellular genes including a subset of oncogenes (such as c-myc and c-myb) and tumor suppressor genes (such as APC, p53, WAF1 and WT1). Furthermore, clustering algorithm analysis showed distinctive gene expression profiles in Hhep and SK-Hep-1 cells. Our findings are consistent with the hypothesis that the deregulation of cellular genes by oncogenic HBx may be an early event that favors hepatocyte proliferation during liver carcinogenesis.

Adult↗
PubMed2004

Genome-wide cDNA microarray analysis of gene expression profiles in pancreatic cancers using populations of tumor cells and normal ductal epithelial cells selected for purity by laser microdissection.

To characterize molecular mechanism involved in pancreatic carcinogenesis, we analysed gene-expression profiles of 18 pancreatic tumors using a cDNA microarray representing 23,040 genes. As pancreatic ductal adenocarcinomas usually contain a low proportion of cancer cells in the tumor mass, we prepared 95% pure populations of pancreatic cancer cells by means of laser microbeam microdissection, and compared their expression profiles to those of similarly purified, normal pancreatic ductal cells. We identified 260 genes that were commonly upregulated and 346 genes that were downregulated in pancreatic cancer cells. Because of the high degree of purity in the cell populations, a large proportion of genes that we detected as upregulated or downregulated in pancreatic cancers were different from those reported in previous studies. Comparison of clinicopathological parameters with the expression profiles indicated that altered expression of 76 genes was associated with lymph-node metastasis and that of 168 genes with liver metastasis. In addition, expression levels of 30 genes were related to the recurrence of disease. These genome-wide expression profiles should provide useful information for finding candidate genes whose products might serve as specific tumor markers and/or as molecular targets for treatment of patients with pancreatic cancer.

Epithelium↗
PubMed2006

Gene expression profiling identifies molecular subgroups among nodal peripheral T-cell lymphomas.

The classification of peripheral T-cell lymphomas (PTCL) is still a matter of debate. To establish a molecular classification of PTCL, we analysed 59 primary nodal T-cell lymphomas using cDNA microarrays, including 56 PTCL and three T-lymphoblastic lymphoma (T-LBL). The expression profiles could discriminate angioimmunoblastic lymphoma, anaplastic large-cell lymphoma and T-LBL. In contrast, cases belonging to the broad category of 'PTCL, unspecified' (PTCL-U) did not share a single molecular profile. Using a multiclass predictor, we could separate PTCL-U into three molecular subgroups called U1, U2 and U3. The U1 gene expression signature included genes known to be associated with poor outcome in other tumors, such as CCND2. The U2 subgroup was associated with overexpression of genes involved in T-cell activation and apoptosis, including NFKB1 and BCL-2. The U3 subgroup was mainly defined by overexpression of genes involved in the IFN/JAK/STAT pathway. It comprised a majority of histiocyte-rich PTCL samples. Gene Ontology annotations revealed different functional profile for each subgroup. These results suggest the existence of distinct subtypes of PTCL-U with specific molecular profiles, and thus provide a basis to improve their classification and to develop new therapeutic targets.

Gene Expression Profiling↗
PubMed2002

cDNA arrays: gene expression profiles of Hodgkin's disease and anaplastic large cell lymphoma cell lines.

cDNA arrays are a powerful tool for the identification of differentially expressed genes in malignant tumors. We used this technique to study the gene expression profiles of anaplastic large cell lymphoma (ALCL) and Hodgkin's disease (HD). Gene expression of 11 lymphoma cell lines was analyzed covering 1176 cDNA sequences. Comparing these data to the expression profiles of B- and T-lymphocytes, we identified 27 genes that were deregulated in all cell lines or in a particular entity. For the establishment of gene expression profiles the 27 genes were assigned to four groups composed of genes deregulated in (i) all lymphoma cell lines, (ii) ALCL and HD, (iii) only HD, and (iv) ALCL exclusively. Our results indicate that ALCL and HD share the differential expression of at least five genes. In addition, both entities are characterized by the differentially deregulated expression of four genes in HD and seven genes in ALCL. Because the expression profiling was performed on cell lines, further studies are needed to clarify the biological significance of the differentially expressed genes.

B-Lymphocytes↗
PubMed2003

Microarray expression profiling: capturing a genome-wide portrait of the transcriptome.

The bacterial transcriptome is a dynamic entity that reflects the organism's immediate, ongoing and genome-wide response to its environment. Microarray expression profiling provides a comprehensive portrait of the transcriptional world enabling us to view the organism as a 'system' that is more than the sum of its parts. The vigilance of microorganisms to environmental change, the alacrity of the transcriptional response, the short half-life of bacterial mRNA and the genome-scale nature of the investigation collectively explain the power of this method. These same features pose the most significant experimental design and execution issues which, unless surmounted, predictably generate a distorted image of the transcriptome. Conversely, the expression profile of a properly conceived and conducted microarray experiment can be used for hypothesis testing: disclosure of the metabolic and biosynthetic pathways that underlie adaptation of the organism to chang-ing conditions of growth; the identification of co-ordinately regulated genes; the regulatory circuits and signal transduction systems that mediate the adaptive response; and temporal features of developmental programmes. The study of bacterial pathogenesis by microarray expression profiling poses special challenges and opportunities. Although the technical hurdles are many, obtaining expression profiles of an organism growing in tissue will probably reveal strategies for growth and survival in the host's microenvironment. Identifying these colonization strategies and their cognate expression patterns involves a 'deconstruction' process that combines bioinformatics analysis and in vitro DNA array experimentation.

Bacteria↗
PubMed2002

Monitoring the expression profiles of 7000 Arabidopsis genes under drought, cold and high-salinity stresses using a full-length cDNA microarray.

Full-length cDNAs are essential for functional analysis of plant genes in the post-sequencing era of the Arabidopsis genome. Recently, cDNA microarray analysis has been developed for quantitative analysis of global and simultaneous analysis of expression profiles. We have prepared a full-length cDNA microarray containing approximately 7000 independent, full-length cDNA groups to analyse the expression profiles of genes under drought, cold (low temperature) and high-salinity stress conditions over time. The transcripts of 53, 277 and 194 genes increased after cold, drought and high-salinity treatments, respectively, more than fivefold compared with the control genes. We also identified many highly drought-, cold- or high-salinity- stress-inducible genes. However, we observed strong relationships in the expression of these stress-responsive genes based on Venn diagram analysis, and found 22 stress-inducible genes that responded to all three stresses. Several gene groups showing different expression profiles were identified by analysis of their expression patterns during stress-responsive gene induction. The cold-inducible genes were classified into at least two gene groups from their expression profiles. DREB1A was included in a group whose expression peaked at 2 h after cold treatment. Among the drought, cold or high-salinity stress-inducible genes identified, we found 40 transcription factor genes (corresponding to approximately 11% of all stress-inducible genes identified), suggesting that various transcriptional regulatory mechanisms function in the drought, cold or high-salinity stress signal transduction pathways.

Arabidopsis↗
PubMed2004

Profiling of microdissected gastric epithelial cells reveals a cell type-specific response to Helicobacter pylori infection.

BACKGROUND AND AIMS: Helicobacter pylori colonizes the epithelial lining of the human stomach and is associated with disorders ranging from chronic gastritis to peptic ulcers and gastric cancer. We have explored the transcriptional response of the epithelium globally by applying a whole-genome approach to a murine model of infection. METHODS: The 3 major epithelial lineages of the stomach-the parietal, mucus-producing, and chief cells-were harvested from cryosections of infected and uninfected murine stomachs by laser microdissection and subjected to gene expression profiling. The localization and quantity of selected transcripts were verified by in situ hybridization and quantitative real-time reverse-transcription polymerase chain reaction. RESULTS: Each cell type is characterized by a transcriptional signature profile. The parietal cell profile is highly enriched for factors involved in mitochondrial energy generation, whereas the chief cell predominantly expresses digestive enzymes and glycosylation-associated proteins. In contrast, the mucus cell signature is distinguished by an abundance of cell-surface receptors, signaling molecules, and factors involved in antigen presentation. All of these indicate a role in sampling, sensing, and responding to environmental stimuli. In line with this biological function, we measured a strong transcriptional response to Helicobacter pylori infection only in this cell type. The genes that are differentially expressed upon infection are implicated in a proinflammatory and mucosal defense response as well as modulation of angiogenesis, iron availability, and tumor suppression. CONCLUSIONS: Laser microdissection-assisted transcriptional profiling is a useful tool to explore the biology of specific cell populations and is sensitive enough to measure the transcriptional response to bacterial infection in vivo.

Animals↗
PubMed2006

Gene expression profiles of breast cancer obtained from core cut biopsies before neoadjuvant docetaxel, adriamycin, and cyclophoshamide chemotherapy correlate with routine prognostic markers and could be used to identify predictive signatures.

BACKGROUND: Neoadjuvant administration of chemotherapy provides a unique opportunity to monitor response to treatment in breast cancer and assesses response exactly. Global gene expression profiling by microarrays has been used as a valuable tool for the identification of prognostic and predictive marker genes. Even though this technology is now wide spread and relatively standardized, there are only few data available which compare established parameters with expression values to determine reliability of this method. Therefore we analyzed gene expression data of pretreatment biopsies of breast cancer patients and compared them with the results of the immunohistochemical receptor expression for ER/ PR and Her-2, as well as FISH testing for HER-2 amplification. We analyzed the change of expression of these markers before and after neoadjuvant chemotherapy. Furthermore we evaluated the predictive significance of prognostic gene signatures as described by Sorlie, van't Veer and Ahr for response to neoadjuvant chemotherapy. METHODS: Pretherapeutic core biopsies were obtained from 70 patients undergoing neoadjuvant TAC chemotherapy within the GEPARTRIO-trial. Samples were characterized according to standard pathology including ER, PR and HER2 IHC and amount of cancer cells. Only biopsies with more than 80 % tumor cells were considered for further examination. RNA was isolated and expression profiling performed using Affymetrix Hg U133 Arrays (22 500 genes). GeneData's Expressionist software was used for bioinformatic analyses. RESULTS: More than two thirds of the biopsies yielded sufficient amounts (> 5 microg) of RNA for expression profiling and high quality data were obtained for 50 samples. Unsupervised clustering broadly revealed a correlation with hormone receptor status. When ER-alpha, PR and HER2 as analyzed by immunohistochemistry were compared to the corresponding mRNA data from gene chips more than 90 % concordance was observed. We could observe a switch of receptor expression for ER, PR or HER-2 from positive to negative and vice versa in 16/35 cases (45.7 %) and 5/22 cases (22.7 %) respectively. The prognostic marker sets of Sorlie, van't Veer and Ahr could not discriminate responders from non-responders in our patient group. CONCLUSIONS: Our results demonstrate that reliable expression profiles can be achieved by using limited amounts of tissue obtained during neoadjuvant chemotherapy. Microarray data capture conventional prognostic markers but might contain additional informative gene sets correlated with treatment outcome. Prognostic marker sets are not suitable to predict tumor response in the neoadjuvant setting, suggesting the necessity of class prediction methods to identify marker sets predictive for the type of therapy used.

Adult↗
PubMed2002

Integrated classification of lung tumors and cell lines by expression profiling.

The utility of cancer cell lines depends largely on their accurate classification, commonly based on histopathological diagnosis of the cancers from which they were derived. However, because cancer is often heterogeneous, the cell line, which also has the opportunity to alter in vitro, may not be representative. Yet without the overall architecture used in histopathological diagnosis of fresh samples, reclassification of cell lines has been difficult. Gene-expression profiling accurately reproduces histopathological classification and is readily applicable to cell lines. Here, we compare the gene-expression profiles of 41 cell lines with 44 tumors from lung cancer. These profiles were generated after hybridization of samples to four replicate 7,685-element cDNA microarrays. After removal of genes that were uniformly up- or down-regulated in fresh compared with cell-line samples, cluster analysis produced four major branch groups. Within these major branches, fresh tumor samples essentially clustered according to pathological type, and further subclusters were seen for both adenocarcinoma (AC) and small cell lung carcinoma (SCLC). Four of eight squamous cell carcinoma (SCC) cell lines clustered with fresh SCC, and 11 of 13 SCLC cell lines grouped with fresh SCLC. In contrast, although none of the 11 AC cell lines clustered with AC tumors, three clustered with SCC tumors and six with SCLC tumors. Although it is possible that preexisting SCC or SCLC cells are being selected from AC tumors after establishment of cell lines, we propose that, even in situ, AC will ultimately progress toward one of two poorly differentiated phenotypes with expression profiles resembling SCC or SCLC.

Adenocarcinoma↗
PubMed2001

Insight into hepatocellular carcinogenesis at transcriptome level by comparing gene expression profiles of hepatocellular carcinoma with those of corresponding noncancerous liver.

Human hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. In this work, we report on a comprehensive characterization of gene expression profiles of hepatitis B virus-positive HCC through the generation of a large set of 5'-read expressed sequence tag (EST) clusters (11,065 in total) from HCC and noncancerous liver samples, which then were applied to a cDNA microarray system containing 12,393 genes/ESTs and to comparison with a public database. The commercial cDNA microarray, which contains 1,176 known genes related to oncogenesis, was used also for profiling gene expression. Integrated data from the above approaches identified 2,253 genes/ESTs as candidates with differential expression. A number of genes related to oncogenesis and hepatic function/differentiation were selected for further semiquantitative reverse transcriptase-PCR analysis in 29 paired HCC/noncancerous liver samples. Many genes involved in cell cycle regulation such as cyclins, cyclin-dependent kinases, and cell cycle negative regulators were deregulated in most patients with HCC. Aberrant expression of the Wnt-beta-catenin pathway and enzymes for DNA replication also could contribute to the pathogenesis of HCC. The alteration of transcription levels was noted in a large number of genes implicated in metabolism, whereas a profile change of others might represent a status of dedifferentiation of the malignant hepatocytes, both considered as potential markers of diagnostic value. Notably, the altered transcriptome profiles in HCC could be correlated to a number of chromosome regions with amplification or loss of heterozygosity, providing one of the underlying causes of the transcription anomaly of HCC.

Carcinoma, Hepatocellular↗
PubMed2005

Competition on nitrocellulose-immobilized antibody arrays: from bacterial protein binding assay to protein profiling in breast cancer cells.

Large scale comparative evaluation of protein expression requires miniaturized techniques to provide sensitive and accurate measurements of the abundance of molecules present as individual and/or assembled protein complexes in cells. The principle of competition between target molecules for binding to arrayed antibodies has recently been proposed to assess differential expression of numerous proteins with one-color or two-color fluorescence detection methods. To establish the limiting factors and to validate the use of alternative detection for protein profiling, we performed competitive binding assays under different conditions. A model experimental protocol was developed whereby the competitive displacement of multi-subunit bacterial RNA polymerase and/or its subunits was evaluated through binding to subunit-specific immobilized monoclonal antibodies. We show that the difference in physico-chemical properties of unlabeled and labeled molecules significantly affects the performance of one-color detection, whereas epitope inaccessibility in the protein complex can prohibit the assessment of competition by both detection methods. Our data also demonstrate that antibody cross-reactivity, target protein truncation and abundance, as well as the cellular compartment of origin are major factors that affect protein profiling on antibody arrays. The experimental conditions established for prokaryotic proteins were adopted to compare protein profiles in the breast tumor-derived cell lines MDA MB-231 and SKBR3. Competitive displacement was detected and confirmed for a number of proteins using both detection methods; however, we show that overall the two-color method is better suited for accurate expression profile evaluation of a large, complex set of proteins. Antibody array data confirm the functional linkage between the ErbB2 receptor and AP-2 transcription factors in these cell lines and highlight unexpected differences in G1 cyclin expression.

Antibodies, Immobilized↗
PubMed2004

Lessons from genetic profiling in soft tissue sarcomas.

Soft tissue sarcomas represent a heterogeneous group of tumors and include over 50 histotypes. Some of these tumor types are characterized by specific chromosomal translocations, whereas other types show complex genetic aberrations. The recent developments within gene expression technologies have now been applied to studies of soft tissue sarcomas (STS) and the first results indicate that genetic signatures are useful for classification and diagnosis. Distinctive expression profiles have been found in e.g. gastrointestinal stromal tumors (GISTs), synovial sarcomas, malignant peripheral nerve sheath tumors (MPNSTs), and in subsets of liposarcomas. The more pleomorphic tumor types, such as high-grade variants of leiomyosarcomas, malignant fibrous histiocytomas (MFHs), fibrosarcomas, and subtypes of liposarcomas, show a greater variability among the expression profiles, but interestingly subsets with distinctive expression profiles can be identified also among these tumors. The data available place many of the genes hypothesized to be involved in the development of a certain type of STS, such as the KIT gene in GIST development, among the top discriminating genes. Thereby expression profiling provides novel insights into the pathogenesis of STS. Although much work remains to be done to validate the data and to define optimal discriminating gene lists, the current lessons from gene expression studies in STS are encouraging and imply that genetic signatures may serve as diagnostic and prognostic markers and may help identify novel therapeutic strategies.

Chromosome Aberrations↗
PubMed2005

Gene expression profiling in breast cancer: towards individualising patient management.

Breast cancer is a complex and clinically heterogeneous disease. The increase in knowledge of breast cancer biology has led to a number of clinical advances in the treatment of breast cancer, most notably the implementation of widespread mammography screening and advances in adjuvant treatment of early-stage disease. In the last 20 years, arrays of potential prognostic and/or predictive markers of breast cancer have been analysed. However, relatively few have proven to be clinically useful. To date, the only widely accepted markers for routine use in breast cancer are the oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor, HER-2 (c-erbB2/neu). Expression microarray technology and laser capture microdissection have now been employed to further our understanding of the molecular pathogenesis of breast cancer. Recently reported advances in array technology and RNA amplification methods are having a considerable impact in this field, allowing the analysis of pre-malignant and pre-invasive lesions. A number of studies have identified prognostic and predictive gene 'signatures', whose prediction of disease outcome and response to treatment is superior to conventional prognostic indicators. Despite major technological advances, a number of confounding issues remain concerning the potential clinical utility of gene expression profiling, including differences in study design, patient selection, array technology, chemistry, and methods of analysis. It seems likely, however, that following careful 'hypothesis driven' validation studies and clinical trials, expression profiling will be applied in the future to identify patient-specific disease profiles and provide rationale for individualised treatment. This review focuses on the current use and future potential of microarray profiling in breast cancer.

Breast Neoplasms↗
PubMedDate not supplied

Microarray-based compendium of hepatic gene expression profiles for prototypical ADME gene-inducing compounds in rats and mice in vivo.

To examine species-specific aspects of the induction of absorption, distribution, metabolism and excretion (ADME)-related genes, we used 25 000 gene oligonucleotide microarrays to construct a rodent gene-response compendium that compared hepatic gene expression profiles and developed consensus aryl hydrocarbon receptor (AhR), constitutive androstane receptor (CAR) and pregnane X-receptor (PXR) ligand signatures relevant to drug clearance. Twenty-six inducer compounds were chosen from the literature. Rats and mice received one of six dose levels (log2 dose escalation, 32-fold dose range) of each compound daily for 3 days. Animals were necropsied 6-9 h after the last dose, and tissues were collected for RNA analysis. Hepatic gene expression profiles were obtained using Rosetta Resolver expression analysis system, and ADME-related genes were extracted. Cross-talk among nuclear receptors or hepatoxicity at high dose levels resulted in large signatures (usually >1000 genes at p < 0.01) for most compounds. After ADME gene transcript enrichment, agglomerative clustering separated AhR ligands from CAR/PXR ligands, but it was difficult to distinguish CAR from PXR ligands. Consensus signatures were derived from groups of AhR, CAR and PXR ligands; and cross-talk among responding genes was determined. Many compounds had distinct log dose-response profiles, and relative potencies for ligands were established. Robust responses by CYP1A1, CYP2B10 (CAR responsive in mice) and CYP2B15 (CAR responsive in rats) and CYP3A1 (PXR responsive in rats) were used to benchmark the relative potency of different ligands and to determine the relative selectivity for AhR, CAR or PXR. By using a compendium of gene expression profiles, we defined species-specific induction patterns across the ADME transcriptome.

Animals↗
PubMed2001

Gene expression profiling of B cell chronic lymphocytic leukemia reveals a homogeneous phenotype related to memory B cells.

B cell-derived chronic lymphocytic leukemia (B-CLL) represents a common malignancy whose cell derivation and pathogenesis are unknown. Recent studies have shown that >50% of CLLs display hypermutated immunoglobulin variable region (IgV) sequences and a more favorable prognosis, suggesting that they may represent a distinct subset of CLLs which have transited through germinal centers (GCs), the physiologic site of IgV hypermutation. To further investigate the phenotype of CLLs, their cellular derivation and their relationship to normal B cells, we have analyzed their gene expression profiles using oligonucleotide-based DNA chip microarrays representative of approximately 12,000 genes. The results show that CLLs display a common and characteristic gene expression profile that is largely independent of their IgV genotype. Nevertheless, a restricted number of genes (<30) have been identified whose differential expression can distinguish IgV mutated versus unmutated cases and identify them in independent panels of cases. Comparison of CLL profiles with those of purified normal B cell subpopulations indicates that the common CLL profile is more related to memory B cells than to those derived from naive B cells, CD5(+) B cells, and GC centroblasts and centrocytes. Finally, this analysis has identified a subset of genes specifically expressed by CLL cells of potential pathogenetic and clinical relevance.

B-Lymphocytes↗
PubMed2002

Gene expression profiling of osteoclast differentiation by combined suppression subtractive hybridization (SSH) and cDNA microarray analysis.

Bone homeostasis is maintained by the balanced action of bone-forming osteoblasts and bone-resorbing osteoclasts. Multinucleated, mature osteoclasts develop from hematopoietic stem cells via the monocyte-macrophage lineage, which also give rise to macrophages and dendritic cells. Despite their distinct physiologic roles in bone and the immune system, these cell types share many molecular and biochemical features. To provide insights into how osteoclasts differentiate and function to control bone metabolism, we employed a systematic approach to profile patterns of osteoclast-specific gene expression by combining suppression subtractive hybridization (SSH) and cDNA microarray analysis. Here we examined how gene expression profiles of mature osteoclast differ from macrophage or dendritic cells, how gene expression profiles change during osteoclast differentiation, and how Mitf, a transcription factor critical for osteoclast maturation, affects the gene expression profile. This approach revealed a set of genes coordinately regulated for osteoclast function, some of which have previously been implicated in several bone diseases in humans.

Animals↗