Janos Demeter

Repeated observation of breast tumor subtypes in independent gene expression data sets

Characteristic patterns of gene expression measured by DNA microarrays have been used to classify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors were analyzed by hierarchical clustering based on patterns of expression of 534 “intrinsic” genes and shown to subdivide into one basal-like, one ERBB2-overexpressing, two luminal-like, and one normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. Similar cluster analyses of two published, independent data sets representing different patient cohorts from different laboratories, uncovered some of the same breast cancer subtypes. In the one data set that included information on time to development of distant metastasis, subtypes were associated with significant differences in this clinical feature. By including a group of tumors from BRCA1 carriers in the analysis, we found that this genotype predisposes to the basal tumor subtype. Our results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities.

The Stanford Microarray Database: data access and quality assessment tools

The Stanford Microarray Database (SMD; http://genome-www.stanford.edu/microarray/) serves as a microarray research database for Stanford investigators and their collaborators. In addition, SMD functions as a resource for the entire scientific community, by making freely available all of its source code and providing full public access to data published by SMD users, along with many tools to explore and analyze those data. SMD currently provides public access to data from 3500 microarrays, including data from 85 publications, and this total is increasing rapidly. In this article, we describe some of SMDs newer tools for accessing public data, assessing data quality and for data analysis.

The Stanford Microarray Database accommodates additional microarray platforms and data formats

The Stanford Microarray Database (SMD) (http://smd.stanford.edu) is a research tool for hundreds of Stanford researchers and their collaborators. In addition, SMD functions as a resource for the entire biological research community by providing unrestricted access to microarray data published by SMD users and by disseminating its source code. In addition to storing GenePix (Axon Instruments) and ScanAlyze output from spotted microarrays, SMD has recently added the ability to store, retrieve, display and analyze the complete raw data produced by several additional microarray platforms and image analysis software packages, so that we can also now accept data from Affymetrix GeneChips (MAS5/GCOS or dChip), Agilent Catalog or Custom arrays (using Agilents Feature Extraction software) or data created by SpotReader (Niles Scientific). We have implemented software that allows us to accept MAGE-ML documents from array manufacturers and to submit MIAME-compliant data in MAGE-ML format directly to ArrayExpress and GEO, greatly increasing the ease with which data from SMD can be published adhering to accepted standards and also increasing the accessibility of published microarray data to the general public. We have introduced a new tool to facilitate data sharing among our users, so that datasets can be shared during, before or after the completion of data analysis. The latest version of the source code for the complete database package was released in November 2004 (http://smd.stanford.edu/download/), allowing researchers around the world to deploy their own installations of SMD.

The Stanford Microarray Database: implementation of new analysis tools and open source release of software

The Stanford Microarray Database (SMD; ) is a research tool and archive that allows hundreds of researchers worldwide to store, annotate, analyze and share data generated by microarray technology. SMD supports most major microarray platforms, and is MIAME-supportive and can export or import MAGE-ML. The primary mission of SMD is to be a research tool that supports researchers from the point of data generation to data publication and dissemination, but it also provides unrestricted access to analysis tools and public data from 300 publications. In addition to supporting ongoing research, SMD makes its source code fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD. In this article, we describe several data analysis tools implemented in SMD and we discuss features of our software release.

Implementation of GenePattern within the Stanford Microarray Database

Hundreds of researchers across the world use the Stanford Microarray Database (SMD; http://smd.stanford.edu/) to store, annotate, view, analyze and share microarray data. In addition to providing registered users at Stanford access to their own data, SMD also provides access to public data, and tools with which to analyze those data, to any public user anywhere in the world. Previously, the addition of new microarray data analysis tools to SMD has been limited by available engineering resources, and in addition, the existing suite of tools did not provide a simple way to design, execute and share analysis pipelines, or to document such pipelines for the purposes of publication. To address this, we have incorporated the GenePattern software package directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. In this article, we describe our implementation of the GenePattern microarray analysis software package into the SMD code base. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability.

Comparative Genomic Hybridizations of Entamoeba Strains Reveal Unique Genetic Fingerprints That Correlate with Virulence

ABSTRACT Variable phenotypes have been identified for Entamoeba species. Entamoeba histolytica is invasive and causes colitis and liver abscesses but only in ∼10% of infected individuals; 90% remain asymptomatically colonized. Entamoeba dispar, a closely related species, is avirulent. To determine the extent of genetic diversity among Entamoeba isolates and potential genotype-phenotype correlations, we have developed an E. histolytica genomic DNA microarray and used it to genotype strains of E. histolytica and E. dispar. On the basis of the identification of divergent genetic loci, all strains had unique genetic fingerprints. Comparison of divergent genetic regions allowed us to distinguish between E. histolytica and E. dispar, identify novel genetic regions usable for strain and species typing, and identify a number of genes restricted to virulent strains. Among the four E. histolytica strains, a strain with attenuated virulence was the most divergent and phylogenetically distinct strain, raising the intriguing possibility that genetic subtypes of E. histolytica may be partially responsible for the observed variability in clinical outcomes. This microarray-based genotyping assay can readily be applied to the study of E. histolytica clinical isolates to determine genetic diversity and potential genotypic-phenotypic associations.

Cell-line and tissue-specific signatures of androgen receptor-coregulator transcription

Normal genital skin fibroblasts (GSF) and the human prostate carcinoma cell line LNCaP have been used widely as cell culture models of genital origin to study androgen receptor (AR) signaling. We demonstrate that LNCaP shows a reproducible response to androgens as assessed using cDNA-microarrays representing approximately 32,000 unique human genes, whereas several independent GSF strains are virtually unresponsive. We show that LNCaP cells express markedly higher AR protein levels likely contributing to the observed differences of androgen responsiveness. However, previous data suggested that AR-expression levels alone do not determine androgen responsiveness of human GSF compared to LNCaP. We hypothesized that cell-specific differences in expression levels of AR coregulators might contribute to differences in androgen responsiveness and might be found by comparing LNCaP and GSFs. Using the Canadian McGill-database of AR coregulators (http://www.mcgill.ca/androgendb), we identified 61 AR-coregulator genes represented by 282 transcripts on our microarray platform that was used to measure transcript profiles of LNCaP and GSF cells. Baseline expression levels of 48 AR-coregulator transcripts representing 33 distinct genes showed significant differences between GSF and LNCaP, four of which we confirmed by reverse transcriptase polymerase chain reaction. Compared to LNCaP, GSFs displayed significant upregulation of AR coregulators that can function as repressors of AR-transactivation, such as caveolin 1. Analysis of a recently published comprehensive dataset of 115 microarrays representing 35 different human tissues revealed tissue-specific signatures of AR coregulators that segregated with ontogenetically related groups of tissues (e.g., lymphatic system and genital tissues, brain). Our data demonstrate the existence of cell-line and tissue-specific expression patterns of molecules with documented AR coregulatory functions. Therefore, differential expression patterns of AR coregulators could modify tissue-specificity and diversity of androgen actions in development, physiology, and disease.

Differential gene-expression patterns in genital fibroblasts of normal males and 46,XY females with androgen insensitivity syndrome: evidence for early programming involving the androgen receptor

BackgroundAndrogen insensitivity syndrome (AIS) comprises a range of phenotypes from male infertility to complete feminization. Most individuals with AIS carry germline mutations of the androgen receptor (AR) that interfere with or ablate its function. As genital fibroblasts retain expression of the AR in vitro, we used genital skin fibroblasts from normal males and 46,XY females with complete AIS due to known AR mutations to gain insights into the role of the AR in human genital differentiation.ResultsUsing DNA microarrays representing 32,968 different genes, we identified 404 transcripts with significant differences in transcription levels between genital skin fibroblasts cultured from normal and AIS-affected individuals. Gene-cluster analyses uncovered coordinated expression of genes involved in key processes of morphogenesis. On the basis of animal studies and human genetic syndromes, several of these genes are known to have specific roles in genital differentiation. Remarkably, genital fibroblasts from both normal and AIS-affected individuals showed no transcriptional response to dihydrotestosterone treatment despite expression of the AR.ConclusionsThe results suggest that in addition to differences in the anatomic origin of the cells, androgen signaling during prenatal development contributes to setting long-lasting, androgen-independent transcriptional programs in genital fibroblasts. Our findings have broad implications in understanding the establishment and the stability of sexual dimorphism in human genital development.

The Ran GTPase System in Fission Yeast Affects Microtubules and Cytokinesis in Cells That Are Competent for Nucleocytoplasmic Protein Transport

ABSTRACT Misregulation of the evolutionarily conserved GTPase Ran in fission yeast results in defects in several cellular processes in cells that are competent for nucleocytoplasmic protein transport. These results suggest that transport is neither the only nor the primary Ran-dependent process in living cells. The ability of Ran to independently regulate multiple cellular processes in vivo is demonstrated by showing that (i) eight different transport-competent RanGEF (guanine nucleotide exchange factor) mutants have defects in mitotic spindle formation; (ii) the RanGEF temperature-sensitive mutant pim1-d1 has abnormal actin ring structures at the septum. Overexpression of Imp2p, which specifically destabilizes these structures, restores viability. (iii) Ran-dependent processes differ in their requirements for active Ran in vivo. Microtubule function, cytokinesis, and nuclear envelope structure are the Ran-dependent processes most sensitive to the amount of Ran protein in the cell, whereas nucleocytoplasmic protein transport is the most robust. Therefore, the ability of Ran from Schizosaccharomyces pombe to independently regulate multiple cellular processes may reflect differences in its interactions with the binding proteins that mediate these functions and explain the complex phenotypic consequences of its misregulation in vivo.

Intrinsic androgen-dependent gene expression patterns revealed by comparison of genital fibroblasts from normal males and individuals with complete and partial androgen insensitivity syndrome

BackgroundTo better understand the molecular programs of normal and abnormal genital development, clear-cut definition of androgen-dependent gene expression patterns, without the influence of genotype (46, XX vs. 46, XY), is warranted. Previously, we have identified global gene expression profiles in genital-derived fibroblasts that differ between 46, XY males and 46, XY females with complete androgen insensitivity syndrome (CAIS) due to inactivating mutations of the androgen receptor (AR). While these differences could be due to cell autonomous changes in gene expression induced by androgen programming, recent work suggests they could also be influenced by the location from which the fibroblasts were harvested (topology). To minimize the influence of topology, we compared gene expression patterns of fibroblasts derived from identical urogenital anlagen: the scrotum in normally virilized 46, XY males and the labia majora from completely feminized 46, XY individuals with CAIS.Results612 transcripts representing 440 unique genes differed significantly in expression levels between scrotum and CAIS labia majora, suggesting the effects of androgen programming. While some genes coincided with those we had identified previously (TBX3, IGFBP5, EGFR, CSPG2), a significant number did not, implying that topology had influenced gene expression in our previous experiments. Supervised clustering of gene expression data derived from a large set of fibroblast cultures from individuals with partial AIS revealed that the new, topology controlled data set better classified the specimens.ConclusionInactivating mutations of the AR, in themselves, appear to induce lasting changes in gene expression in cultured fibroblasts, independent of topology and genotype. Genes identified are likely to be relevant candidates to decipher androgen-dependent normal and abnormal genital development.