Paul T. Spellman

Minimum information about a microarray experiment (MIAME)-toward standards for microarray data.

Microarray analysis has become a widely used tool for the generation of gene expression data on a genomic scale. Although many significant results have been derived from microarray studies, one limitation has been the lack of standards for presenting and exchanging such data. Here we present a proposal, the Minimum Information About a Microarray Experiment (MIAME), that describes the minimum information required to ensure that microarray data can be easily interpreted and that results derived from its analysis can be independently verified. The ultimate goal of this work is to establish a standard for recording and reporting microarray-based gene expression data, which will in turn facilitate the establishment of databases and public repositories and enable the development of data analysis tools. With respect to MIAME, we concentrate on defining the content and structure of the necessary information rather than the technical format for capturing it.

Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1

The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.

Systematic variation in gene expression patterns in human cancer cell lines

We used cDNA microarrays to explore the variation in expression of approximately 8,000 unique genes among the 60 cell lines used in the National Cancer Institutes screen for anti-cancer drugs. Classification of the cell lines based solely on the observed patterns of gene expression revealed a correspondence to the ostensible origins of the tumours from which the cell lines were derived. The consistent relationship between the gene expression patterns and the tissue of origin allowed us to recognize outliers whose previous classification appeared incorrect. Specific features of the gene expression patterns appeared to be related to physiological properties of the cell lines, such as their doubling time in culture, drug metabolism or the interferon response. Comparison of gene expression patterns in the cell lines to those observed in normal breast tissue or in breast tumour specimens revealed features of the expression patterns in the tumours that had recognizable counterparts in specific cell lines, reflecting the tumour, stromal and inflammatory components of the tumour tissue. These results provided a novel molecular characterization of this important group of human cell lines and their relationships to tumours in vivo.

The somatic genomic landscape of glioblastoma.

We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

Genome-wide analysis of the Drosophila immune response by using oligonucleotide microarrays

To identify new Drosophila genes involved in the immune response, we monitored the gene expression profile of adult flies in response to microbial infection by using high-density oligonucleotide microarrays encompassing nearly the full Drosophila genome. Of 13,197 genes tested, we have characterized 230 induced and 170 repressed by microbial infection, most of which had not previously been associated with the immune response. Many of these genes can be assigned to specific aspects of the immune response, including recognition, phagocytosis, coagulation, melanization, activation of NF-κB transcription factors, synthesis of antimicrobial peptides, production of reactive oxygen species, and regulation of iron metabolism. Additionally, we found a large number of genes with unknown function that may be involved in control and execution of the immune response. Determining the function of these genes represents an important challenge for improving our knowledge of innate immunity. Complete results may be found at http://www.fruitfly.org/expression/immunity/.

The morphologies of breast cancer cell lines in three-dimensional assays correlate with their profiles of gene expression

3D cell cultures are rapidly becoming the method of choice for the physiologically relevant modeling of many aspects of non‐malignant and malignant cell behavior ex vivo. Nevertheless, only a limited number of distinct cell types have been evaluated in this assay to date. Here we report the first large scale comparison of the transcriptional profiles and 3D cell culture phenotypes of a substantial panel of human breast cancer cell lines. Each cell line adopts a colony morphology of one of four main classes in 3D culture. These morphologies reflect, at least in part, the underlying gene expression profile and protein expression patterns of the cell lines, and distinct morphologies were also associated with tumor cell invasiveness and with cell lines originating from metastases. We further demonstrate that consistent differences in genes encoding signal transduction proteins emerge when even tumor cells are cultured in 3D microenvironments.

The Toll and Imd pathways are the major regulators of the immune response in Drosophila

Microarray studies have shown recently that microbial infection leads to extensive changes in the Drosophila gene expression programme. However, little is known about the control of most of the fly immune‐responsive genes, except for the antimicrobial peptide (AMP)‐encoding genes, which are regulated by the Toll and Imd pathways. Here, we used oligonucleotide microarrays to monitor the effect of mutations affecting the Toll and Imd pathways on the expression programme induced by septic injury in Drosophila adults. We found that the Toll and Imd cascades control the majority of the genes regulated by microbial infection in addition to AMP genes and are involved in nearly all known Drosophila innate immune reactions. However, we identified some genes controlled by septic injury that are not affected in double mutant flies where both Toll and Imd pathways are defective, suggesting that other unidentified signalling cascades are activated by infection. Interestingly, we observed that some Drosophila immune‐responsive genes are located in gene clusters, which often are transcriptionally co‐regulated.

The Stanford Microarray Database

The Stanford Microarray Database (SMD) stores raw and normalized data from microarray experiments, and provides web interfaces for researchers to retrieve, analyze and visualize their data. The two immediate goals for SMD are to serve as a storage site for microarray data from ongoing research at Stanford University, and to facilitate the public dissemination of that data once published, or released by the researcher. Of paramount importance is the connection of microarray data with the biological data that pertains to the DNA deposited on the microarray (genes, clones etc.). SMD makes use of many public resources to connect expression information to the relevant biology, including SGD [Ball,C.A., Dolinski,K., Dwight,S.S., Harris,M.A., Issel-Tarver,L., Kasarskis,A., Scafe,C.R., Sherlock,G., Binkley,G., Jin,H. et al. (2000) Nucleic Acids Res., 28, 77-80], YPD and WormPD [Costanzo,M.C., Hogan,J.D., Cusick,M.E., Davis,B.P., Fancher,A.M., Hodges,P.E., Kondu,P., Lengieza,C., Lew-Smith,J.E., Lingner,C. et al. (2000) Nucleic Acids Res., 28, 73-76], Unigene [Wheeler,D.L., Chappey,C., Lash,A.E., Leipe,D.D., Madden,T.L., Schuler,G.D., Tatusova,T.A. and Rapp,B.A. (2000) Nucleic Acids Res., 28, 10-14], dbEST [Boguski,M.S., Lowe,T.M. and Tolstoshev,C.M. (1993) Nature Genet., 4, 332-333] and SWISS-PROT [Bairoch,A. and Apweiler,R. (2000) Nucleic Acids Res., 28, 45-48] and can be accessed at http://genome-www.stanford.edu/microarray.

Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy

Pancreatic ductal adenocarcinoma (PDA) is a lethal disease. Overall survival is typically 6 months from diagnosis. Numerous phase 3 trials of agents effective in other malignancies have failed to benefit unselected PDA populations, although patients do occasionally respond. Studies in other solid tumors have shown that heterogeneity in response is determined, in part, by molecular differences between tumors. Furthermore, treatment outcomes are improved by targeting drugs to tumor subtypes in which they are selectively effective, with breast and lung cancers providing recent examples. Identification of PDA molecular subtypes has been frustrated by a paucity of tumor specimens available for study. We have overcome this problem by combined analysis of transcriptional profiles of primary PDA samples from several studies, along with human and mouse PDA cell lines. We define three PDA subtypes: classical, quasimesenchymal and exocrine-like, and we present evidence for clinical outcome and therapeutic response differences between them. We further define gene signatures for these subtypes that may have utility in stratifying patients for treatment and present preclinical model systems that may be used to identify new subtype specific therapies.

Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt

Genomic experiments produce multiple views of biological systems, among them are DNA sequence and copy number variation, and mRNA and protein abundance. Understanding these systems needs integrated bioinformatic analysis. Public databases such as Ensembl provide relationships and mappings between the relevant sets of probe and target molecules. However, the relationships can be biologically complex and the content of the databases is dynamic. We demonstrate how to use the computational environment R to integrate and jointly analyze experimental datasets, employing BioMart web services to provide the molecule mappings. We also discuss typical problems that are encountered in making gene-to-transcript–to-protein mappings. The approach provides a flexible, programmable and reproducible basis for state-of-the-art bioinformatic data integration.