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David Botstein

Publications and source records attributed to David Botstein.

At least 55 records · Page 3Linked to original sources

The role of heat shock transcription factor 1 in the genome-wide regulation of the mammalian heat shock response.

Previous work has implicated heat shock transcription factor 1 (HSF1) as the primary transcription factor responsible for the transcriptional response to heat stress in mammalian cells. We characterized the heat shock response of mammalian cells by measuring changes in transcript levels and assaying binding of HSF1 to promoter regions for candidate heat shock genes chosen by a combination of genome-wide computational and experimental methods. We found that many heat-inducible genes have HSF1 binding sites (heat shock elements, HSEs) in their promoters that are bound by HSF1. Surprisingly, for 24 heat-inducible genes, we detected no HSEs and no HSF1 binding. Furthermore, of 182 promoters with likely HSE sequences, we detected HSF1 binding at only 94 of these promoters. Also unexpectedly, we found 48 genes with HSEs in their promoters that are bound by HSF1 but that nevertheless did not show induction after heat shock in the cell types we examined. We also studied the transcriptional response to heat shock in fibroblasts from mice lacking the HSF1 gene. We found 36 genes in these cells that are induced by heat as well as they are in wild-type cells. These results provide evidence that HSF1 does not regulate the induction of every transcript that accumulates after heat shock, and our results suggest that an independent posttranscriptional mechanism regulates the accumulation of a significant number of transcripts.

Animals↗

T cell receptor-independent basal signaling via Erk and Abl kinases suppresses RAG gene expression.

Signal transduction pathways guided by cellular receptors commonly exhibit low-level constitutive signaling in a continuous, ligand-independent manner. The dynamic equilibrium of positive and negative regulators establishes such a tonic signal. Ligand-independent signaling by the precursors of mature antigen receptors regulates development of B and T lymphocytes. Here we describe a basal signal that controls gene expression profiles in the Jurkat T cell line and mouse thymocytes. Using DNA microarrays and Northern blots to analyze unstimulated cells, we demonstrate that expression of a cluster of genes, including RAG-1 and RAG-2, is repressed by constitutive signals requiring the adapter molecules LAT and SLP-76. This TCR-like pathway results in constitutive low-level activity of Erk and Abl kinases. Inhibition of Abl by the drug STI-571 or inhibition of signaling events upstream of Erk increases RAG-1 expression. Our data suggest that physiologic gene expression programs depend upon tonic activity of signaling pathways independent of receptor ligation.

Adaptor Proteins, Signal Transducing↗

Diverse effects of methylseleninic acid on the transcriptional program of human prostate cancer cells.

Methylseleninic acid (MSA) has been shown to have potent anticancer activity and is an excellent compound for studying the anticancer effects of selenium in vitro. To gain insights into the effects of MSA in prostate cancer, we characterized the global transcriptional response of LNCaP, an androgen-sensitive human prostate cancer cell line, to MSA by using high-density cDNA microarrays. We identified 951 genes whose expression shows striking dose- and time-dependent changes in response to 3-30 microM MSA over the time course of 48 h. Transcript levels of many cell cycle-regulated genes change in response to MSA, suggesting that MSA inhibits proliferation. Consistent with these gene expression changes, cell proliferation, monitored by carboxyfluoroscein succinimidyl ester staining, was decreased after MSA treatment, and an accumulation of cells at G0/G1 phase was detected by flow cytometry. Surprisingly, MSA also modulated expression of many androgen-regulated genes, suppressed androgen receptor (AR) expression at both mRNA and protein level, and decreased levels of prostate specific antigen secreted into the medium. Low concentrations of MSA also induced significant increases in transcript levels of phase 2 detoxification enzymes and induced NADPH dehydrogenase, quinone 1 enzymatic activity, a surrogate marker of global phase 2 enzyme activity. Our results suggest that MSA may protect against prostate cancer by inhibiting cell proliferation, by modulating the expression of AR and AR-regulated genes and by inducing carcinogen defenses.

Adenocarcinoma↗

Systemic and cell type-specific gene expression patterns in scleroderma skin.

We used DNA microarrays representing >12,000 human genes to characterize gene expression patterns in skin biopsies from individuals with a diagnosis of systemic sclerosis with diffuse scleroderma. We found consistent differences in the patterns of gene expression between skin biopsies from individuals with scleroderma and those from normal, unaffected individuals. The biopsies from affected individuals showed nearly indistinguishable patterns of gene expression in clinically affected and clinically unaffected tissue, even though these were clearly distinguishable from the patterns found in similar tissue from unaffected individuals. Genes characteristically expressed in endothelial cells, B lymphocytes, and fibroblasts showed differential expression between scleroderma and normal biopsies. Analysis of lymphocyte populations in scleroderma skin biopsies by immunohistochemistry suggest the B lymphocyte signature observed on our arrays is from CD20+ B cells. These results provide evidence that scleroderma has systemic manifestations that affect multiple cell types and suggests genes that could be used as potential markers for the disease.

Adult↗

Endothelial cell diversity revealed by global expression profiling.

The vascular system is locally specialized to accommodate widely varying blood flow and pressure and the distinct needs of individual tissues. The endothelial cells (ECs) that line the lumens of blood and lymphatic vessels play an integral role in the regional specialization of vascular structure and physiology. However, our understanding of EC diversity is limited. To explore EC specialization on a global scale, we used DNA microarrays to determine the expression profile of 53 cultured ECs. We found that ECs from different blood vessels and microvascular ECs from different tissues have distinct and characteristic gene expression profiles. Pervasive differences in gene expression patterns distinguish the ECs of large vessels from microvascular ECs. We identified groups of genes characteristic of arterial and venous endothelium. Hey2, the human homologue of the zebrafish gene gridlock, was selectively expressed in arterial ECs and induced the expression of several arterial-specific genes. Several genes critical in the establishment of left/right asymmetry were expressed preferentially in venous ECs, suggesting coordination between vascular differentiation and body plan development. Tissue-specific expression patterns in different tissue microvascular ECs suggest they are distinct differentiated cell types that play roles in the local physiology of their respective organs and tissues.

Cells, Cultured↗

Gene expression patterns in ovarian carcinomas.

We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A comparison of the gene expression patterns in the ovarian cancers to published data of gene expression in breast cancers revealed a large number of differentially expressed genes. We identified a group of 62 genes that correctly classified all 125 breast and ovarian cancer specimens. Among the best discriminators more highly expressed in the ovarian carcinomas were PAX8 (paired box gene 8), mesothelin, and ephrin-B1 (EFNB1). Although estrogen receptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estrogen receptor in breast cancers, including GATA-3, LIV-1, and X-box binding protein 1, did not show a similar pattern of coexpression in the ovarian cancers.

Adenocarcinoma↗

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.

Breast Neoplasms↗

A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae).

Genomic sequencing is no longer a novelty, but gene function annotation remains a key challenge in modern biology. A variety of functional genomics experimental techniques are available, from classic methods such as affinity precipitation to advanced high-throughput techniques such as gene expression microarrays. In the future, more disparate methods will be developed, further increasing the need for integrated computational analysis of data generated by these studies. We address this problem with MAGIC (Multisource Association of Genes by Integration of Clusters), a general framework that uses formal Bayesian reasoning to integrate heterogeneous types of high-throughput biological data (such as large-scale two-hybrid screens and multiple microarray analyses) for accurate gene function prediction. The system formally incorporates expert knowledge about relative accuracies of data sources to combine them within a normative framework. MAGIC provides a belief level with its output that allows the user to vary the stringency of predictions. We applied MAGIC to Saccharomyces cerevisiae genetic and physical interactions, microarray, and transcription factor binding sites data and assessed the biological relevance of gene groupings using Gene Ontology annotations produced by the Saccharomyces Genome Database. We found that by creating functional groupings based on heterogeneous data types, MAGIC improved accuracy of the groupings compared with microarray analysis alone. We describe several of the biological gene groupings identified.

Algorithms↗

Variation in gene expression patterns in human gastric cancers.

Gastric cancer is the world's second most common cause of cancer death. We analyzed gene expression patterns in 90 primary gastric cancers, 14 metastatic gastric cancers, and 22 nonneoplastic gastric tissues, using cDNA microarrays representing approximately 30,300 genes. Gastric cancers were distinguished from nonneoplastic gastric tissues by characteristic differences in their gene expression patterns. We found a diversity of gene expression patterns in gastric cancer, reflecting variation in intrinsic properties of tumor and normal cells and variation in the cellular composition of these complex tissues. We identified several genes whose expression levels were significantly correlated with patient survival. The variations in gene expression patterns among cancers in different patients suggest differences in pathogenetic pathways and potential therapeutic strategies.

Adenocarcinoma↗

Generalized singular value decomposition for comparative analysis of genome-scale expression data sets of two different organisms.

We describe a comparative mathematical framework for two genome-scale expression data sets. This framework formulates expression as superposition of the effects of regulatory programs, biological processes, and experimental artifacts common to both data sets, as well as those that are exclusive to one data set or the other, by using generalized singular value decomposition. This framework enables comparative reconstruction and classification of the genes and arrays of both data sets. We illustrate this framework with a comparison of yeast and human cell-cycle expression data sets.

Cell Cycle↗

Variation in gene expression patterns in follicular lymphoma and the response to rituximab.

Analysis of the patterns of gene expression in follicular lymphomas from 24 patients suggested that two groups of tumors might be distinguished. All patients, whose biopsies were obtained before any treatment, were treated with rituximab, a monoclonal antibody directed against the B cell antigen, CD20. Gene expression patterns in the tumors that subsequently failed to respond to rituximab appeared more similar to those of normal lymphoid tissues than to gene expression patterns of tumors from rituximab responders. These findings suggest the possibility that the response of follicular lymphoma to rituximab treatment may be predicted from the gene expression pattern of tumors.

Adult↗

SOURCE: a unified genomic resource of functional annotations, ontologies, and gene expression data.

The explosion in the number of functional genomic datasets generated with tools such as DNA microarrays has created a critical need for resources that facilitate the interpretation of large-scale biological data. SOURCE is a web-based database that brings together information from a broad range of resources, and provides it in manner particularly useful for genome-scale analyses. SOURCE's GeneReports include aliases, chromosomal location, functional descriptions, GeneOntology annotations, gene expression data, and links to external databases. We curate published microarray gene expression datasets and allow users to rapidly identify sets of co-regulated genes across a variety of tissues and a large number of conditions using a simple and intuitive interface. SOURCE provides content both in gene and cDNA clone-centric pages, and thus simplifies analysis of datasets generated using cDNA microarrays. SOURCE is continuously updated and contains the most recent and accurate information available for human, mouse, and rat genes. By allowing dynamic linking to individual gene or clone reports, SOURCE facilitates browsing of large genomic datasets. Finally, SOURCEs batch interface allows rapid extraction of data for thousands of genes or clones at once and thus facilitates statistical analyses such as assessing the enrichment of functional attributes within clusters of genes. SOURCE is available at http://source.stanford.edu.

Animals↗

Saccharomyces Genome Database (SGD) provides biochemical and structural information for budding yeast proteins.

The Saccharomyces Genome Database (SGD: http://genome-www.stanford.edu/Saccharomyces/) has recently developed new resources to provide more complete information about proteins from the budding yeast Saccharomyces cerevisiae. The PDB Homologs page provides structural information from the Protein Data Bank (PDB) about yeast proteins and/or their homologs. SGD has also created a resource that utilizes the eMOTIF database for motif information about a given protein. A third new resource is the Protein Information page, which contains protein physical and chemical properties, such as molecular weight and hydropathicity scores, predicted from the translated ORF sequence.

Amino Acid Motifs↗

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 SMD's newer tools for accessing public data, assessing data quality and for data analysis.

Animals↗

Tissue microarray validation of epidermal growth factor receptor and SALL2 in synovial sarcoma with comparison to tumors of similar histology.

Histological diagnosis of synovial sarcoma can be difficult. Genome-wide expression profiling has identified a number of genes expressed at higher levels in synovial sarcoma than in other soft tissue tumors, representing excellent candidates for diagnostic immunohistochemical markers. A tissue microarray comprising 77 sarcomas, including 46 synovial sarcomas, was constructed to validate identified markers and investigate their expression in tumors in the differential diagnosis of synovial sarcoma. Immunostaining was performed for two such markers, epidermal growth factor receptor and SAL (drosophila)-like 2 (SALL2), and for fifteen established markers used in the differential diagnosis of sarcomas. As predicted by expression profiling, epidermal growth factor receptor (a potential therapeutic target) and SALL2 stained most cases of synovial sarcoma; staining was significantly less common among other tested sarcomas. Hierarchical clustering analysis applied to immunostaining results for all 18 antibodies showed that synovial sarcomas, leiomyosarcomas, hemangiopericytomas, and solitary fibrous tumors cluster distinctly, and assigned one case with indeterminate histology as a Ewing sarcoma. Digital images from over 2500 immunostained cores analyzed in this study were captured and are made accessible through the accompanying website: http://microarray-pubs.stanford.edu/tma_portal/synsarc.

Biomarkers↗

Gene expression patterns and gene copy number changes in dermatofibrosarcoma protuberans.

Dermatofibrosarcoma protuberans (DFSP) is an aggressive spindle cell neoplasm. It is associated with the chromosomal translocation, t(17:22), which fuses the COL1A1 and PDGFbeta genes. We determined the characteristic gene expression profile of DFSP and characterized DNA copy number changes in DFSP by array-based comparative genomic hybridization (array CGH). Fresh frozen and formalin-fixed, paraffin-embedded samples of DFSP were analyzed by array CGH (four cases) and DNA microarray analysis of global gene expression (nine cases). The nine DFSPs were readily distinguished from 27 other diverse soft tissue tumors based on their gene expression patterns. Genes characteristically expressed in the DFSPs included PDGF beta and its receptor, PDGFRB, APOD, MEOX1, PLA2R, and PRKCA. Array CGH of DNA extracted either from frozen tumor samples or from paraffin blocks yielded equivalent results. Large areas of chromosomes 17q and 22q, bounded by COL1A1 and PDGF beta, respectively, were amplified in DFSP. Expression of genes in the amplified regions was significantly elevated. Our data shows that: 1) DFSP has a distinctive gene expression profile; 2) array CGH can be applied successfully to frozen or formalin-fixed, paraffin-embedded tumor samples; 3) a characteristic amplification of sequences from chromosomes 17q and 22q, demarcated by the COL1A1 and PDGF beta genes, respectively, was associated with elevated expression of the amplified genes.

Adult↗

A genome scan for hypertension susceptibility loci in populations of Chinese and Japanese origins.

BACKGROUND: Our understanding of genes that predispose to essential hypertension is poor. METHODS: A genome-wide scan for linkage at approximately 10 cM resolution was done on 1425 sibpairs of Chinese and Japanese origins that were concordant for hypertension (N = 661), low-normal blood pressure (BP) (N = 184), or discordant for BP (N = 580). RESULTS: There was no significant evidence of linkage to a single locus in the genome. There was suggestive evidence of linkage to chromosome 10p, with a LOD score of 2.5. CONCLUSIONS: We can exclude the possibility that a single gene accounts for at least 15% of the variance in hypertension in this population.

Adult↗