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PubMedDate not supplied

Prediction of treatment response using gene expression profiles.

This paper concerns prediction of clinical outcome from gene expression profiles using work in a different area, nonlinear system identification. In particular, the approach can predict long-term treatment response from data of a landmark article by Golub et al. (Golub, T. R.; Slonim, D. K.; Tamayo, P.; Huard, C.; Gaasenbeek, M.; Mesirov, J. P. et al. Science 1999, 286, 531-537) that has not previously been achieved with these data. The present paper shows that, for these data, gene expression profiles taken at time of diagnosis of acute myeloid leukemia contain information predictive of eventual response to chemotherapy. This was not evident in previous work; indeed, the Golub et al. article did not find a set of genes strongly correlated with clinical outcome. However, the present approach can accurately predict outcome class of gene expression profiles even when the genes do not have large differences in expression levels between the classes.

Antibiotics, Antineoplastic↗

PubMed2005

Gene expression profiling of primary breast cancer.

Gene expression profiling is a method to measure the expression of a large number of genes in tissue specimens simultaneously. This analytical technique is actively explored as an emerging diagnostic tool for breast cancer. An important assumption behind this research is that the constellation of multiple genes will be more predictive of clinical outcome than any single gene alone. Gene expression signatures were shown to predict prognosis of breast cancer as well as response to particular chemotherapy regimens. The first multigene predictor of prognosis after tamoxifen therapy is already commercially available in the United States. This article reviews recent advances in the clinical application of this technique to breast cancer.

Breast Neoplasms↗

PubMed1999

Reactivation of insulin-like growth factor binding protein 2 expression in glioblastoma multiforme: a revelation by parallel gene expression profiling.

We carried out a gene expression profiling study using cDNA array technology with 24 primary glioma tissues of low-grade (oligodendroglioma), intermediate-grade (anaplastic oligodendroglioma and anaplastic astrocytoma), and high-grade (glioblastomas multiforme) tumors and found that insulin-like growth factor binding protein 2 (IGFBP2) was consistently overexpressed only in glioblastoma multiforme. The cDNA array results were confirmed by Northern and Western blotting. The fact that the IGFBP2 gene, which is normally expressed in fetal cells and turned off in adult cells, becomes reactivated in the most advanced stage of glioma suggests that glioma progression is a result of dedifferentiation or results from a block of differentiation. Identification of IGFBP2 as a gene associated with glioma progression demonstrates the power and utility of high-throughput gene expression profiling in cancer gene discovery.

Gene Expression Regulation, Enzymologic↗

PubMed2001

Expression profile of nine novel genes differentially expressed in hepatitis B virus-associated hepatocellular carcinomas.

Chronic hepatitis B virus (HBV) infection is known to be one of the major causes in the development of hepatocellular carcinoma (HCC), although the biomolecular mechanism(s) involved remain unclear. To identify the cellular gene(s) involved in HBV-associated hepatocarcinogenesis, we used the mRNA differential display method and examined three paired tumor and nontumor tissues, all of which had chromosomally integrated HBV-DNA through chronic infection. Using 240 different combinations of three one-base anchored oligo-dT primers and 80 arbitrary 13-mers, genes decreased or increased in expression more than twofold between each tumor tissue and its paired nontumor tissue were identified. Twenty-nine known genes and four novel genes were differentially over-expressed in the HCC tumor tissues. In contrast, 27 known genes and five novel genes were under-expressed in those tumor tissues. The nucleotide sequences of the nine novel gene fragments were determined and their expression patterns were examined in 40 HCC samples. HA61T2, PT18, HG63T1, and HG57T1 were preferentially over-expressed in 32 cases (80%, P<0.001), 24 cases (60%), 23 cases (57.5%) and 22 cases (55%) of the 40 tumor tissues, respectively. There was an increased frequency of HG57T1 over-expression in HCC patients with HBV-positive serology and low serum alpha-feto protein (AFP) levels (P<0.05). DNT10, PT8, PT19, ENT25 and HA6T4 were under-expressed in 26 cases (65%), 23 cases (57.5%), 21 cases (53%), 20 cases (50%) and 18 cases (45%) of the 40 tumor samples, respectively. There was a strong correlation of DNT10 under-expression with high serum AFP level in HCC patients, irrespective of HBV serology (P<0.01). HA6T4 was preferentially under-expressed in HCC tumors in patients with HBV-positive serology and high serum AFP levels (P<0.05). Thus, the functional analyses of the known and novel genes identified in this study should prove valuable to further understand the mechanism(s) of hepatocarcinogenesis.

Base Sequence↗

PubMed2005

Characterization and gene expression profiling of a stable cell line expressing a cell cycle GFP sensor.

The use of stable cell lines expressing fusions with green fluorescent protein (GFP) has increased significantly in recent years. In this study we have used a range of complimentary analytical techniques to examine the characteristics of a cell line stably expressing a EGFP cell cycle sensor relative to parental U2OS cells. Analysis of cell cycle duration and cell cycle phase distribution by cell growth assays and flow cytometry revealed that the two cell lines had identical doubling times and cell cycle distributions. Measurement of EGFP fusion protein mRNA by quantitative RT-PCR indicated a EGFP sensor expression level equivalent to endogenous Cyclin B1 (7000 copies/cell in G2). Microarray analysis showed a 0.9% (>2 fold at p<0.001 across 20,000 genes) difference in global gene expression levels between parental and EGFP expressing U2OS cells, with no significant differences in expression of A, B, C, D, E, F, G, H, I, K, L, M or T type Cyclins between the two cell types. These results confirm that engineering a stable cell line for low expression of a EGFP cell cycle sensor is minimally perturbing to the cell cycle and cellular gene expression.

Cell Cycle↗

PubMed2003

Gene expression profiling of diffuse large B-cell lymphoma.

Initial gene expression profiling studies of diffuse large B-cell lymphoma (DLBCL) revealed that this single diagnosis actually encompasses two distinct diseases that differ in the expression of hundreds of genes. One subtype, germinal center B-cell-like (GCB) DLBCL, strongly resembles normal germinal center B-cells and has a good prognosis following chemotherapy, whereas activated B-cell-like (ABC) DLBCL resembles mitogenically activated blood B cells and has a poor outcome. An expanded analysis of 274 DLBCL cases confirmed the existence of the GCB and ABC subgroups, but demonstrated that additional subgroups exist. Furthermore, two recurrent oncogenic events in DLBCL, t(14;18) and amplification of the c-rel locus on chromosome 2p, were only observed in GCB DLBCL, whereas constitutive activation of NF-kappaB was seen in ABC DLBCL, showing that the gene expression subgroups represent pathogenetically distinct diseases. Gene expression profiling has also been used to identify individual genes that predict overall survival in DLBCL, the majority coming from gene expression signatures that reflect the cell of origin, proliferation rate, and host immune response to the tumor. A multivariate model including 17 genes representing these biological features divided patients with DLBCL into quartiles with strikingly distinct 5-year survival rates, ranging from 73% to 15%. The use of gene expression profiling should eventually lead to an integration of molecular diagnosis and consequent selection of the most appropriate treatment.

Diagnosis, Differential↗

PubMed2005

Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues.

A critical and difficult part of studying cancer with DNA microarrays is data interpretation. Besides the need for data analysis algorithms, integration of additional information about genes might be useful. We performed genome-wide expression profiling of 36 types of normal human tissues and identified 2503 tissue-specific genes. We then systematically studied the expression of these genes in cancers by reanalyzing a large collection of published DNA microarray datasets. We observed that the expression level of liver-specific genes in hepatocellular carcinoma (HCC) correlates with the clinically defined degree of tumor differentiation. Through unsupervised clustering of tissue-specific genes differentially expressed in tumors, we extracted expression patterns that are characteristic of individual cell types, uncovering differences in cell lineage among tumor subtypes. We were able to detect the expression signature of hepatocytes in HCC, neuron cells in medulloblastoma, glia cells in glioma, basal and luminal epithelial cells in breast tumors, and various cell types in lung cancer samples. We also demonstrated that tissue-specific expression signatures are useful in locating the origin of metastatic tumors. Our study shows that integration of each gene's breadth of expression (BOE) in normal tissues is important for biological interpretation of the expression profiles of cancers in terms of tumor differentiation, cell lineage, and metastasis.

Algorithms↗

PubMed1997

An expression profile of genes in human retina and isolation of a complementary DNA for a novel rod photoreceptor protein.

PURPOSE: To characterize expression patterns of active genes in human retina, and to isolate novel genes that are uniquely expressed in this tissue. METHODS: A 3'-directed complementary DNA (cDNA) library that faithfully represents the composition of messenger RNA (mRNA) was constructed with an mRNA preparation from a cadaveric human retina. A total of 925 3' terminal sequences were collected by sequencing randomly selected clones, of which 789 were regarded as representing chromosomally coded genes (gene signatures [GS]). GS were compared with each other and searched against GenBank. The resulting expression profile, listing gene species and their frequency, represents the composition of mRNA in the retina. By comparing this expression profile with those obtained from 10 other source cells or tissues, genes uniquely active in the retina were discovered, including some not previously described. A full-sized cDNA corresponding to one of these was isolated and sequenced. Its expression was analyzed by multitissue Northern hybridization and in situ hybridization to the retina specimen. It was then mapped on human chromosomes. RESULTS: In the expression profile, 108 genes were detected recurrently, suggesting that they are very active. Fifty-five of them were identified in GenBank, including the most abundant opsin gene and several other genes for phototransduction. Among the remaining novel and active genes, 19 were considered unique to retina on the basis of their representation status in other expression profiles and in dbEST. One of these was identified as a gene that encodes a novel secretory protein expressed in a rod photoreceptor that maps to chromosome 18p11.3. CONCLUSIONS: The expression profile of active genes in the retina represents the composition of mRNA, which reflects the relative activities of genes in this tissue. A comparison of this expression profile with those obtained with other tissues resulted in isolation of a novel cDNA specifically expressed in the rod photoreceptor. It is anticipated that additional novel genes that are uniquely active in the neural retina may be obtained with the same strategy, leading to further clarification of the biologic or physiological characteristics of this tissue.

Amino Acid Sequence↗

PubMed2004

Analysis of transcription factors in thymic and CD34+ progenitor-derived plasmacytoid and myeloid dendritic cells: evidence for distinct expression profiles.

OBJECTIVE: The expression of mRNA for pre-Talpha is specific for human plasmacytoid dendritic cells (PDC), a population ontogenically close to T cells. The latter need Gata-3 transcription factor to develop. PU1 and RelB are two transcription factors involved in the development of murine myeloid DC (MDC). To determine the lineage origin of human thymic DC, the expression of these genes was investigated. MATERIALS AND METHODS: Fresh thymic DC, CD34(+)CD1a(-) progenitors, and progenitor-derived DC populations were sorted, analyzed, and compared to blood DC. RESULTS: Three DC populations were found in the thymus. 1) CD123(-/lo)HLA-DR(hi) DC expressing PU1 and RelB; 2) CD123(hi)HLA-DR(+) DC expressing only pre-Talpha, the expression of which was similar to that of MDC and PDC from peripheral blood; and 3) a new mature CD123(hi)HLA-DR(hi) PDC population with pre-Talpha, PU1 and RelB mRNAs. In culture, most CD34(+)CD1a(-) progenitors remained CD1a(-)CD123(-); had a T and natural killer cell differentiation potential; and expressed Gata-3 mRNA contrary to DC precursors. A few cells (10%) became CD1a(+)CD123(+) expressing pre-Talpha, PU1, and RelB mRNAs and were able to differentiate into typical Langerhans cells with transforming growth factor-beta. Coculture of thymic progenitors on a murine cell line generated CD123(hi)CD1a(-) cells with typical PDC morphology, expressing pre-Talpha but not PU1 and RelB transcripts. Activated PDC acquired myeloid antigens, and up-regulated PU1 and RelB mRNAs while down-regulating pre-Talpha mRNA expression. CONCLUSION: Both DC maturation pathways may arise from distinct precursors but are interconnected. DC differentiation seems to occur from Gata-3(-) precursors upstream of T and natural killer precursors.

Antigens, CD1↗

PubMed2004

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

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

Adolescent↗

PubMed2005

Gene expression profiles associated with treatment response in oligodendrogliomas.

Oligodendrogliomas are a specific subtype of brain tumor of which the majority responds favorably to chemotherapy. In this study, we made use of expression profiling to identify chemosensitive oligodendroglial tumors. Correlation of expression profiles to loss of heterozygosity on 1p and 19q, common chromosomal aberrations associated with response to treatment, identified 376, 64, and 60 differentially expressed probe sets associated with loss of 1p, 19q or 1p, and 19q, respectively. Correlation of expression profiles to the tumors' response to treatment identified 16 differentially expressed probe sets. Because transcripts associated with chemotherapeutic response were identified independent of common chromosomal aberrations, expression profiling may be used as an alternative approach to the tumors' 1p status to identify chemosensitive oligodendroglial tumors. Finally, we correlated expression profiles to survival of the patient after diagnosis and identified 103 differentially expressed probe sets. The observation that many genes are differentially expressed between long and short survivors indicates that the genetic background of the tumor is an important factor in determining the prognosis of the patient. Furthermore, these transcripts can help identify patient subgroups that are associated with favorable prognosis. Our study is the first to correlate gene expression with chromosomal aberrations and clinical performance (response to treatment and survival) in oligodendrogliomas. The differentially expressed transcripts can help identify patient subgroups with good prognosis and those that will benefit from chemotherapeutic treatments.

Adult↗

PubMed2005

Correlation of murine embryonic stem cell gene expression profiles with functional measures of pluripotency.

Global gene expression profiling was performed on murine embryonic stem cells (ESCs) induced to differentiate by removal of leukemia inhibitory factor (LIF) to identify genes whose change in expression correlates with loss of pluripotency. To identify appropriate time points for the gene expression analysis, the dynamics of loss of pluripotency were investigated using three functional assays: chimeric mouse formation, embryoid body generation, and colony-forming ability. A rapid loss of pluripotency was detected within 24 hours, with very low residual activity in all assays by 72 hours. Gene expression profiles of undifferentiated ESCs and ESCs cultured for 18 and 72 hours in the absence of LIF were determined using the Affymetrix GeneChip U74v2. In total, 473 genes were identified as significantly differentially expressed, with approximately one third having unknown biological function. Among the 275 genes whose expression decreased with ESC differentiation were several factors previously identified as important for, or markers of, ESC pluripotency, including Stat3, Rex1, Sox2, Gbx2, and Bmp4. A significant number of the decreased genes also overlap with previously published mouse and human ESC data. Furthermore, several membrane proteins were among the 48 decreased genes correlating most closely with the functional assays, including the stem cell factor receptor c-Kit. Through identification of genes whose expression closely follows functional properties of ESCs during early differentiation, this study lays the foundation for further elucidating the molecular mechanisms regulating the maintenance of ESC pluripotency and facilitates the identification of more reliable molecular markers of the undifferentiated state.

Animals↗

PubMed2006

Immunohistochemical classification of de novo, transformed, and relapsed diffuse large B-cell lymphoma into germinal center B-cell and nongerminal center B-cell subtypes correlates with gene expression profile and patient survival.

CONTEXT: Diffuse large B-cell lymphoma (DLBCL) can be assigned to prognostic subgroups, including germinal center B-cell (GCB) and activated B-cell subgroups, by using gene expression profiling and, reportedly, immunohistochemistry for CD10, Bcl-6, and multiple myeloma-1/interferon regulatory factor-4 (MUM1/IRF4). OBJECTIVE: To compare 2 commercial MUM1/IRF4 antibody formulations for accuracy in subtyping DLBCL against gene expression profiling, compare subtyping to patient survival, and evaluate the usefulness of GCB and non-GCB subtyping in relapsed and transformed DLBCL. DESIGN: Evaluation of 2 commercial MUM1/IRF4 antibodies, ICSTAT/M17 and Mum-1p, by using 40 cases of de novo, relapsed, and transformed DLBCL; and comparison of the results obtained with gene expression profiling and survival. RESULTS: Immunohistochemistry predicted the gene expression profiling subtype 71.8% and 69.2% of the time overall with use of the Mum-1p and ICSTAT/M17 antibodies, respectively, and 100% and 91.7% of the time when MUM1/IRF4 expression determined subtype. Gene expression profiling and immunohistochemistry revealed nearly identical 5-year overall survival rates for the GCB vs non-GCB subtypes (68.0% for GCB vs 24.7% for non-GCB with use of gene expression profiling [P = .03] and 70.2% vs 18.4%, respectively, with use of immunohistochemistry [P < .001]). When de novo, transformed, and relapsed cases were analyzed separately, 5-year overall survival rates were also significantly different. CONCLUSIONS: Immunohistochemistry can be used to subclassify DLBCL, including a very small series of transformed and relapsed cases, into GCB and non-GCB subtypes and predict survival rates similar to those predicted by use of gene expression profiling. The 2 MUM1/IRF4 antibodies performed similarly.

B-Lymphocytes↗

PubMed2004

Recent translational research: microarray expression profiling of breast cancer--beyond classification and prognostic markers?

Genomic expression profiling has greatly improved our ability to subclassify human breast cancers according to shared molecular characteristics and clinical behavior. The logical next question is whether this technology will be similarly useful for identifying the dominant signaling pathways that drive tumor initiation and progression within each breast cancer subtype. A major challenge will be to integrate data generated from the experimental manipulation of model systems with expression profiles obtained from primary tumors. We highlight some recent progress and discuss several obstacles in the use of expression profiling to identify pathway signatures in human breast cancer.

Animals↗

PubMed2005

Highly conserved gene expression profiles in humans with allergic rhinitis altered by immunotherapy.

BACKGROUND: Atopic diseases, resulting from hypersensitivity to a wide variety of allergens, affect 10-20% of the population. Immunotherapy is an effective treatment for atopic diseases, but its mechanisms are not fully understood. OBJECTIVE: We studied gene expression profiles in the peripheral blood mononuclear cells (PBMC) and examined whether the individuals with allergic rhinitis (AR) have a unique gene expression profile and how the immunotherapy affect the gene expression profiles. METHODS: We used cDNA microarray and 'expression analysis systemic explorer' to examine the gene expression profiles in the PBMC of atopic subjects and other groups. RESULTS: We identified a highly conserved gene expression profile in atopic subjects that permitted their accurate segregation from control or autoimmune subjects. A major feature of this profile was the under-expression of a variety of genes that encode proteins required for apoptosis and over-expression of genes that encode proteins critical for stress responses and signal transduction. We also identified 563 genes that can segregate individuals with AR based upon receipt of immunotherapy. CONCLUSION: There is a highly conserved gene expression profile in the PBMC of individuals with AR. This profile can be used to identify individuals with AR and to evaluate responses to immunotherapy. Quantitative endpoints, such as gene expression, may assist clinicians faced with clinical decisions in the diagnosis of patients and the evaluation of response to therapy. The knowledge of the possible genetic basis for immunotherapy efficacy may also lead to novel therapeutic approaches for atopic diseases.

Adult↗

PubMed2004

A versatile assay for high-throughput gene expression profiling on universal array matrices.

We report a flexible, sensitive, and quantitative gene-expression profiling system for assaying more than 400 genes, with three probes per gene, for 96 samples in parallel. The cDNA-mediated annealing, selection, extension and ligation (DASL) assay targets specific transcripts, using oligonucleotides containing unique address sequences that can hybridize to universal arrays. Cell-specific gene expression profiles were obtained using this assay for hormone-treated cell lines and laser-capture microdissected cancer tissues. Gene expression profiles derived from this assay were consistent with those determined by qRT-PCR. The DASL assay has been automated for use with a bead-based 96-array matrix system. The combined high-throughput assay and readout system is accurate and efficient, and can cost-effectively profile the expression of hundreds of genes in thousands of samples.

Androgens↗

PubMed2004

Gene expression profiling of hairy cell leukemia reveals a phenotype related to memory B cells with altered expression of chemokine and adhesion receptors.

Hairy cell leukemia (HCL) is a chronic B cell malignancy characterized by the diffuse infiltration of bone marrow and spleen by cells displaying a typical "hairy" morphology. However, the nature of the HCL phenotype and its relationship to normal B cells and to other lymphoma subtypes remains unclear. Using gene expression profiling, we show here that HCL displays a homogeneous pattern of gene expression, which is clearly distinct from that of other B cell non-Hodgkin lymphomas. Comparison with the gene expression profiles of purified normal B cell subpopulations, including germinal center (GC), pre-GC (naive), and post-GC (memory) B cells, shows that HCL cells are more related to memory cells, suggesting a derivation from this B cell population. Notably, when compared with memory cells, HCL cells displayed a remarkable conservation in proliferation, apoptosis, and DNA metabolism programs, whereas they appeared significantly altered in the expression of genes controlling cell adhesion and response to chemokines. Finally, these analyses have identified several genes that are specifically expressed in HCL and whose expression was confirmed at the protein level by immunocytochemical analysis of primary HCL cases. These results have biological implications relevant to the pathogenesis of this malignancy as well as clinical implications for its diagnosis and therapy.

B-Lymphocytes↗

PubMed2004

Expression Profiler: next generation--an online platform for analysis of microarray data.

Expression Profiler (EP, http://www.ebi.ac.uk/expressionprofiler) is a web-based platform for microarray gene expression and other functional genomics-related data analysis. The new architecture, Expression Profiler: next generation (EP:NG), modularizes the original design and allows individual analysis-task-related components to be developed by different groups and yet still seamlessly to work together and share the same user interface look and feel. Data analysis components for gene expression data preprocessing, missing value imputation, filtering, clustering methods, visualization, significant gene finding, between group analysis and other statistical components are available from the EBI (European Bioinformatics Institute) web site. The web-based design of Expression Profiler supports data sharing and collaborative analysis in a secure environment. Developed tools are integrated with the microarray gene expression database ArrayExpress and form the exploratory analytical front-end to those data. EP:NG is an open-source project, encouraging broad distribution and further extensions from the scientific community.

Gene Expression Profiling↗