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PubMed2001

Early acquisition of bowel segment-specific Bcl-2 homolog expression profiles during development of the human ileum and colon.

The adult small and large intestines display distinct expression profiles of Bcl-2 homologs, known regulators of apoptosis. This is thought to indicate that control mechanisms of intestinal apoptosis are gut segment-specific. Little is known on the expression of Bcl-2 homologs during gut development. In man, intestinal features and functions are acquired largely by mid-gestation (18-20 wks); the question whether segment-specific controls of intestinal apoptosis are also acquired early during development remains open. In the present study, we approached this by investigating the expression of six Bcl-2 homologs (Bcl-2, Bcl-XL, Mcl-1, Bax, Bak, Bad), and one nonhomologous associated molecule (Bag-1), during development of the human ileum and colon (12-20 wks of gestation). Beginning at 18 wks, we found that the epithelial localization of Bcl-2 homologs displayed differential patterns (or gradients) in both the ileum and colon; however, the patterns of some of the homologs differed between the two segments. For instance, Bag-1 and Bcl-2 exhibited crypt-villus decreasing gradients of expression in the ileum but not in the colon, whereas Mcl-1 displayed differing compartimentalizations between the two segments. Further analyses indicated that the steady-state expression levels of Bcl-2 homologs underwent modulations between 12 and 20 wks; however, the observed developmental profiles contrasted significantly between the two segments. For example, Bcl-2, Bag-1 and Bak levels increased in the colon, but the levels of these same homologs decreased in the ileum. Furthermore, by 18-20 wks, we found that the expression levels of each Bcl-2 homolog analyzed differed greatly between the ileum and colon. Altogether, these data indicate that the expression of Bcl-2 homologs is modulated differentially during human gut development in order to establish, by mid-gestation, distinct expression profiles for the small and large intestines. This in turn suggests that gut segment-specific control mechanisms of human intestinal apoptosis are acquired early during fetal life.

Apoptosis↗
PubMed2006

Gene-expression profiling and array-based CGH classify CD4+CD56+ hematodermic neoplasm and cutaneous myelomonocytic leukemia as distinct disease entities.

CD4+CD56+ hematodermic neoplasm (CD4+CD56+HN) is an aggressive hematopoietic malignancy with distinct clinicopathologic and immunophenotypic features that commonly involve the skin, bone marrow, and blood. Differentiation from cutaneous myelomonocytic leukemia (c-AML) may be exceedingly difficult and requires extensive phenotyping. The molecular mechanisms involved in the development of CD4+CD56+HN are largely unresolved. Moreover, recurrent chromosomal alterations have not yet been precisely defined in CD4+CD56+HN and c-AML. In the present study an integrated genomic analysis using expression profiling and array-based comparative genomic hybridization (CGH) was performed on lesional skin biopsy samples of patients with CD4+CD56+HN and c-AML. Our results demonstrate that CD4+CD56+HN and c-AML show distinct gene-expression profiles and distinct patterns of chromosomal aberrations. CD4+CD56+HN is characterized by recurrent deletion of regions on chromosome 4 (4q34), chromosome 9 (9p13-p11 and 9q12-q34), and chromosome 13 (13q12-q31) that contain several tumor suppressor genes with diminished expression (Rb1, LATS2). Elevated expression of the oncogenes HES6, RUNX2, and FLT3 was found but was not associated with genomic amplification. We noted high expression of various plasmacytoid dendritic-cell (pDC)-related genes, pointing to the cell of origin of this malignancy.

Aged↗
PubMed2004

Prediction of outcome of advanced cervical cancer to thermoradiotherapy according to expression profiles of 35 genes selected by cDNA microarray analysis.

PURPOSE: To identify a set of genes related to thermoradiosensitivity of cervical carcinoma and to establish a predictive method. METHODS AND MATERIALS: A total of 19 patients with cervical cancer (1 with Stage IIIA, 11 with Stage IIIB, 5 with Stage IVA, and 2 with Stage IVB) who underwent definitive thermoradiotherapy between May 1995 and August 2001 were included in this study. We compared the expression profiles of 8 thermoradiosensitive and 11 thermoradioresistant tumors obtained by punch biopsy before treatment using a cDNA microarray consisting of 23,040 human genes. RESULTS: We selected 35 genes on the basis of a clustering analysis and confirmed the validity of these genes with a cross-validation test. Some of these genes were already known to be associated with apoptosis (BIK, TEGT, SSI-3), hypoxia-inducible genes (HIF1A, CA12), and tumor cell invasion and metastasis (CTSL, CTSB, PLAU, CD44). We developed a "predictive score" system that could clearly separate the thermoradiosensitive group from the thermoradioresistant group. CONCLUSION: These results from the treatment program between May 1995 and August 2001 showed that by using gene-expression profiles we can predict the outcome of thermoradiotherapy for advanced cervical carcinoma. A "predictive score" system was developed that could clearly separate the thermoradiosensitive group from the thermoradioresistant group. These results may eventually lead to the achievement of "personalized therapy" for this disease.

Adult↗
PubMed2006

Expression profiling by whole-genome interspecies microarray hybridization reveals differential gene expression in procyclic promastigotes, lesion-derived amastigotes, and axenic amastigotes in Leishmania mexicana.

We examined the Leishmania mexicana transcriptome to identify differentially regulated mRNAs using high-density whole-genome oligonucleotide microarrays designed from the genome data of a closely related species, Leishmania major. Statistical analysis on array hybridization data representing 8156 predicted coding regions revealed 288 genes (3.5% of all genes) whose steady-state mRNA levels meet criteria for differential regulation between promastigotes and lesion-derived amastigotes. Interestingly, sample comparison of promastigotes to axenic amastigotes resulted in only 17 genes (0.2%) that meet the same statistical criteria for differential regulation. The reduced number of regulated genes is a consequence of an increase in the magnitude of the transcript levels in cells under axenic conditions. The expression data for a subset of genes was validated by quantitative PCR. Our studies show that interspecies hybridization on microarrays can be used to analyze closely related protozoan parasites, that axenic culture conditions may alter amastigote transcript abundance, and that there is only a relatively modest change in abundance of a few mRNAs between morphologically distinct promastigote and amastigote cultured cells. Leishmania may represent an alternative paradigm for eukaryotic differentiation with minimal contributions from changes in mRNA abundance.

Animals↗
PubMed2004

Comparison of different isolation techniques prior gene expression profiling of blood derived cells: impact on physiological responses, on overall expression and the role of different cell types.

Owing to its clinical accessibility, peripheral blood is probably the best source for the assessment of differences or changes in gene expression associated with disease or drug response and therapy. Gene expression patterns in peripheral blood cells greatly depend on temporal and interindividual variations. However, technical aspects of blood sampling, isolation of cellular components, RNA isolation techniques and clinical aspects such as time to analysis and temperature during processing have been suggested to affect gene expression patterns. We therefore assessed gene expression patterns in peripheral blood from 29 healthy individuals by using Affymetrix microarrays. When RNA isolation was delayed for 20-24 h-a typical situation in clinical studies-gene signatures related to hypoxia were observed, and downregulation of genes associated with metabolism, cell cycle or apoptosis became dominant preventing the assessment of gene signatures of interindividual variation. Similarly, gene expression patterns were strongly dependent on choice of cell and RNA isolation and preparation techniques. We conclude that for large clinical studies, it is crucial to reduce maximally the time to RNA isolation. Furthermore, prior to study initiation, the cell type of interest should already be defined. Our data therefore will help to optimize clinical studies applying gene expression analysis of peripheral blood to exploit drug responses and to better understand changes associated with disease.

Adult↗
PubMed2004

Expression profiling and comparative genomics identify a conserved regulatory region controlling midline expression in the zebrafish embryo.

Differential gene transcription is a fundamental regulatory mechanism of biological systems during development, body homeostasis, and disease. Comparative genomics is believed to be a rapid means for the identification of regulatory sequences in genomes. We tested this approach to identify regulatory sequences that control expression in the midline of the zebrafish embryo. We first isolated a set of genes that are coexpressed in the midline of the zebrafish embryo during somitogenesis stages by gene array analysis and subsequent rescreens by in situ hybridization. We subjected 45 of these genes to Compare and DotPlot analysis to detect conserved sequences in noncoding regions of orthologous loci in the zebrafish and Takifugu genomes. The regions of homology that were scored in nonconserved regions were inserted into expression vectors and tested for their regulatory activity by transient transgenesis in the zebrafish embryo. We identified one conserved region from the connective tissue growth factor gene (ctgf), which was able to drive expression in the midline of the embryo. This region shares sequence similarity with other floor plate/notochord-specific regulatory regions. Our results demonstrate that an unbiased comparative approach is a relevant method for the identification of tissue-specific cis-regulatory sequences in the zebrafish embryo.

Animals↗
PubMed2005

Gene expression profiling of HIV-1 infection using cDNA microarrays.

To illustrate the methods employed in gene expression profiling using cDNA microarrays, infection of CD4+ T cell lines with HIV-1LAI is used to identify expression changes relevant to in vitro HIV-1 infection. Cell lines are infected at a high multiplicity of infection to ensure a population of near-synchronously infected cells to be compared to uninfected cells. Infection status is verified using flow cytometry to determine the intracellular expression of the viral gag p24 protein before samples are harvested for total RNA extraction. Total RNA is extracted and amplified using commercially available kits, and RNA quality is verified using Bioanalyzer technology. To obtain fluorescently labeled cDNA probes, the amplified RNA is reverse-transcribed to yield cDNA, using random nonamers in the presence of dye-labeled dCTP. After first-strand cDNA synthesis, RNA is degraded and the probes are purified. For each infection condition (LAI and mock), two slides are hybridized with identical probes generated from the same RNAs, but with fluorescent labels reversed on one of the slides to control for dye-specific effects. Troubleshooting strategies and issues to consider prior to starting the experiment are discussed in detail in the notes section.

CD4-Positive T-Lymphocytes↗
PubMed2002

Prediction of in vivo synergistic activity of antiangiogenic compounds by gene expression profiling.

Angiogenesis, an essential phenotype for tumor formation, requires the interaction of many cells within the tumor microenvironment. Therefore, successful antiangiogenic therapies must be able to block all of the different mechanisms tumors use to induce neovascularization. A major challenge for developing such protocols is determining which agents are likely to have the highest degree of synergistic activity in vivo. We treated human microvascular endothelial cells with six inhibitors of angiogenesis and used microarrays to seek divergent patterns of gene expression suggestive of potential synergies. The expression profiles of a thrombospondin-mimetic peptide (DI-TSPa) and TNP-470 (TNP) were very similar, whereas endostatin had a dramatically different profile. In vitro, endostatin was synergistically antiangiogenic with either TNP-470 or DI-TSPa. In vivo, mice bearing Lewis lung carcinoma cells treated with a combination of endostatin and either DI-TSPa or TNP-470, at doses that were ineffective when used alone, resulted in a marked inhibition of tumor growth and decreased tumor angiogenesis. Conversely, animals treated with both DI-TSPa and TNP-470 demonstrated a modest effect on both tumor growth and angiogenesis. These results suggest that even in the absence of a complete mechanistic understanding of how these inhibitors work, gene expression profiling may be used to predict synergistic antiangiogenic activity and thus maximize their antitumor efficacy.

Angiogenesis Inhibitors↗
PubMed2001

Analysis of cellular adhesion by microarray expression profiling.

Microarrays of oligonucleotides or cDNAs can be used to establish the expression profiles of numerous genes in a single experiment. We have established a microarray platform to identify genes in a number of different pathological conditions, particularly those with an inflammation component. This platform utilised the output of an eosinophil sequencing project in which 1069 sequences were identified that were not represented in the public domain. An eosinophil model cell line, AML14.3D10, was used to investigate cell adhesion. The transcription profile of adhered and non-adhered AML 14.3D10 cells was shown to be both technically and biologically reproducible. A number of genes were found differentially expressed in the adhered vs. non-adhered populations. In the adhered population, the expression of these genes was restricted compared to brain, lung, kidney and especially bone marrow. However, the differentially regulated genes were not among those genes most restricted to eosinophils. We discuss the implications of transcription profiling on gene annotation and its potential utility for the identification of targets for drug intervention.

Base Sequence↗
PubMed2005

Random walk models for bayesian clustering of gene expression profiles.

The analysis of gene expression temporal profiles is a topic of increasing interest in functional genomics. Model-based clustering methods are particularly interesting because they are able to capture the dynamic nature of these data and to identify the optimal number of clusters. We have defined a new Bayesian method that allows us to cope with some important issues that remain unsolved in the currently available approaches: the presence of time dislocations in gene expression, the non-stationarity of the processes generating the data, and the presence of data collected on an irregular temporal grid. Our method, which is based on random walk models, requires only mild a priori assumptions about the nature of the processes generating the data and explicitly models inter-gene variability within each cluster. It has first been validated on simulated datasets and then employed for the analysis of a dataset relative to serum-stimulated fibroblasts. In all cases, the results have been promising, showing that the method can be helpful in functional genomics research.

Journal Article↗
PubMed2007

Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles.

Machine learning approaches offer the potential to systematically identify transcriptional regulatory interactions from a compendium of microarray expression profiles. However, experimental validation of the performance of these methods at the genome scale has remained elusive. Here we assess the global performance of four existing classes of inference algorithms using 445 Escherichia coli Affymetrix arrays and 3,216 known E. coli regulatory interactions from RegulonDB. We also developed and applied the context likelihood of relatedness (CLR) algorithm, a novel extension of the relevance networks class of algorithms. CLR demonstrates an average precision gain of 36% relative to the next-best performing algorithm. At a 60% true positive rate, CLR identifies 1,079 regulatory interactions, of which 338 were in the previously known network and 741 were novel predictions. We tested the predicted interactions for three transcription factors with chromatin immunoprecipitation, confirming 21 novel interactions and verifying our RegulonDB-based performance estimates. CLR also identified a regulatory link providing central metabolic control of iron transport, which we confirmed with real-time quantitative PCR. The compendium of expression data compiled in this study, coupled with RegulonDB, provides a valuable model system for further improvement of network inference algorithms using experimental data.

Algorithms↗
PubMed2005

Prediction of recurrence in advanced gastric cancer patients after curative resection by gene expression profiling.

The prognosis of patients with advanced gastric cancer remains unfavorable. Even after curative resection, 40% of patients with advanced gastric cancer die of recurrence. Conventional clinicopathlogic findings are sometimes inadequate for predicting recurrence in individuals. Hence, we tried to construct a new diagnostic system, which predicts recurrence in patients with advanced gastric cancer after curative resection based on molecular analysis. Gastric cancer progression is a function of multiple genetic events that may affect the expression of large number of genes. We performed gene expression profiling with 2,304 genes in 60 advanced gastric cancer patients who underwent curative resection using a PCR array technique, a high-throughput quantitative RT-PCR technique. The diagnostic system, which was constructed from the learning set comprised of 40 patients with the most informative 29 genes, classified each case into a good-signature or poor-signature group. Then, we confirmed the predictive performance in an additional test set comprised of 20 patients, and the prediction accuracy for recurrence was 75%. Kaplan-Meier analysis revealed significant difference between the good-signature and the poor-signature group (p = 0.0125). Especially in patients with smaller tumor (< or = 5 cm), less developed LN metastasis (N(0,1)), or earlier stage (stages I and II), the prediction accuracy was high (88.9%, 84.6%, or 81.8%, respectively). Our diagnostic system based on systematic analysis of gene expression profiling can predict the recurrence at clinically meaningful level. By combining our system with conventional clinicopathologic factors, we can improve the prediction of recurrence in patients with advanced gastric cancer who underwent curative surgery.

Aged↗
PubMed2001

BodyMap incorporated PCR-based expression profiling data and a gene ranking system.

BodyMap is a human and mouse gene expression database that is based on site-directed 3'-expressed sequence tags generated at Osaka University. To date, it contains more than 300 000 tag sequences from 64 human and 39 mouse tissues. For the recent release, the precise anatomical expression patterns for more than half of the human gene entries were generated by introduced amplified fragment length polymorphism (iAFLP), which is a PCR-based high-throughput expression profiling method. The iAFLP data incorporated into BodyMap describe the relative contents of more than 12 000 transcripts across 30 tissue RNAs. In addition, a newly developed gene ranking system helps users obtain lists of genes that have desired expression patterns according to their significance. BodyMap supports complete transfer of unique data sets and provides analysis that is accessible through the WWW at http://bodymap.ims.u-tokyo.ac. jp.

Animals↗
PubMed2003

Computational analysis of flow-cytometry antigen expression profiles in childhood acute lymphoblastic leukemia: an MLL/AF4 identification.

Precursor B-acute lymphoblastic leukemia (pB-ALL) is a heterogeneous disease and multiparameter flow cytometry, molecular genetics, and cytogenetic studies have all contributed to classification of subgroups with prognostic significance. Recently, gene expression microarray technology has been used to investigate lymphoblastic leukemias, demonstrating that known and novel pB-ALL subclasses can be separated on the basis of gene expression profiles. The strength of microarray technique lays in part in the multivariate nature of the expression data. We propose a parallel multiparametric approach based on immunophenotypic flow-cytometry expression data for the analysis of leukemia patients. Specifically, we tested the potential of this approach on a data set of 145 samples of pediatric pB-ALL that included 46 samples positive for mixed lineage leukemia (MLL) translocations (MLL+) and 99 control pB-ALLs, negative for this translocation (MLL-). The expression levels of 16 marker proteins have been monitored by four-color flow cytometry using a standardized diagnostic panel of antibodies. The protein expression database has been then analyzed using those univariate and multivariate computational techniques normally applied to mine and model large microarray data sets. Marker protein expression profiling not only allowed separating pB-ALL cases with an MLL rearrangement from other ALLs, but also demonstrates that MLL+ leukemias constitute a heterogeneous group in which MLL/AF4 leukemias represent a homogenous subclass described by a specific expression fingerprint.

Adolescent↗
PubMed2002

Multi-class cancer classification via partial least squares with gene expression profiles.

MOTIVATION: Discrimination between two classes such as normal and cancer samples and between two types of cancers based on gene expression profiles is an important problem which has practical implications as well as the potential to further our understanding of gene expression of various cancer cells. Classification or discrimination of more than two groups or classes (multi-class) is also needed. The need for multi-class discrimination methodologies is apparent in many microarray experiments where various cancer types are considered simultaneously. RESULTS: Thus, in this paper we present the extension to the classification methodology proposed earlier Nguyen and Rocke (2002b; Bioinformatics, 18, 39-50) to classify cancer samples from multiple classes. The methodologies proposed in this paper are applied to four gene expression data sets with multiple classes: (a) a hereditary breast cancer data set with (1) BRCA1-mutation, (2) BRCA2-mutation and (3) sporadic breast cancer samples, (b) an acute leukemia data set with (1) acute myeloid leukemia (AML), (2) T-cell acute lymphoblastic leukemia (T-ALL) and (3) B-cell acute lymphoblastic leukemia (B-ALL) samples, (c) a lymphoma data set with (1) diffuse large B-cell lymphoma (DLBCL), (2) B-cell chronic lymphocytic leukemia (BCLL) and (3) follicular lymphoma (FL) samples, and (d) the NCI60 data set with cell lines derived from cancers of various sites of origin. In addition, we evaluated the classification algorithms and examined the variability of the error rates using simulations based on randomization of the real data sets. We note that there are other methods for addressing multi-class prediction recently and our approach is along the line of Nguyen and Rocke (2002b; Bioinformatics, 18, 39-50). CONTACT: dnguyen@stat.tamu.edu; dmrocke@ucdavis.edu

Algorithms↗
PubMed2006

Gene expression profiling of CD34+ cells identifies a molecular signature of chronic myeloid leukemia blast crisis.

Despite recent success in the treatment of early-stage disease, blastic phase (BP) of chronic myeloid leukemia (CML) that is characterized by rapid expansion of therapy-refractory and differentiation-arrested blasts, remains a therapeutic challenge. The development of resistance upon continuous administration of imatinib mesylate is associated with poor prognosis pointing to the need for alternative therapeutic strategies and a better understanding of the molecular mechanisms underlying disease progression. To identify transcriptional signatures that may explain pathological characteristics and aggressive behavior of BP blasts, we performed comparative gene expression profiling on CD34+ Ph+ cells purified from patients with untreated newly diagnosed chronic phase CML (CP, n=11) and from patients in BP (n=9) using Affymetrix oligonucleotide arrays. Supervised microarray data analysis revealed 114 differentially expressed genes (P<10(-4)), 34 genes displaying more than two-fold transcriptional changes when comparing CP and BP groups. While 24 of these genes were downregulated, 10 genes, especially suppressor of cytokine signalling 2 (SOCS2), CAMPATH-1 antigen (CD52), and four human leukocyte antigen-related genes were strongly overexpressed in BP. Expression of selected genes was validated by real-time-polymerase chain reaction and flow cytometry. Our data suggest the existence of a common gene expression profile of CML-BP and provide new insight into the molecular phenotype of blasts associated with disease progression and high malignancy.

Adult↗
PubMed2006

Prognosis and gene expression profiling of 20q13-amplified breast cancers.

PURPOSE: Amplification of chromosomal region 20q13 occurs in breast cancer but remains poorly characterized. EXPERIMENTAL DESIGN: To establish the frequency of 20q13 amplification and select the amplified cases to be studied, we used fluorescence in situ hybridization of bacterial artificial chromosome probes for three 20q13 loci (MYBL2, STK6, ZNF217) on sections of tissue microarrays containing 466 primary carcinoma samples. We used Affymetryx whole-genome DNA microarrays to establish the gene expression profiles of 20q13-amplified tumors and quantitative reverse transcription-PCR to validate the results. RESULTS: We found 36 (8%) 20q13-amplified samples. They were distributed in two types: type 1 tumors showed ZNF217 amplification only, whereas type 2 tumors showed amplification at two or three loci. Examination of the histoclinical features of the amplified tumors showed two strikingly opposite data. First, type 1 tumors were more frequently lymph node-negative tumors but were paradoxically associated with a poor prognosis. Second, type 2 tumors were more frequently lymph node-positive tumors but were paradoxically associated with a good prognosis. Type 1 and type 2 showed different gene expression profiles. No 20q13 gene could be associated with type 1 amplification, whereas several 20q13 genes were overexpressed in type 2 tumors. CONCLUSIONS: Our results suggest that amplified tumors of types 1 and 2 are two distinct entities resulting from two different mechanisms and associated to different prognosis.

Breast Neoplasms↗