Christopher J. Roberts

Gene expression profiling predicts clinical outcome of breast cancer.

Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70–80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases (‘poor prognosis’ signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.

Functional Discovery via a Compendium of Expression Profiles

Ascertaining the impact of uncharacterized perturbations on the cell is a fundamental problem in biology. Here, we describe how a single assay can be used to monitor hundreds of different cellular functions simultaneously. We constructed a reference database or compendium of expression profiles corresponding to 300 diverse mutations and chemical treatments in S. cerevisiae, and we show that the cellular pathways affected can be determined by pattern matching, even among very subtle profiles. The utility of this approach is validated by examining profiles caused by deletions of uncharacterized genes: we identify and experimentally confirm that eight uncharacterized open reading frames encode proteins required for sterol metabolism, cell wall function, mitochondrial respiration, or protein synthesis. We also show that the compendium can be used to characterize pharmacological perturbations by identifying a novel target of the commonly used drug dyclonine.

Drug target validation and identification of secondary drug target effects using DNA microarrays

We describe here a method for drug target validation and identification of secondary drug target effects based on genome-wide gene expression patterns. The method is demonstrated by several experiments, including treatment of yeast mutant strains defective in calcineurin, immunophilins or other genes with the immunosuppressants cyclosporin A or FK506. Presence or absence of the characteristic drug signature pattern of altered gene expression in drug-treated cells with a mutation in the gene encoding a putative target established whether that target was required to generate the drug signature. Drug dependent effects were seen in targetless cells, showing that FK506 affects additional pathways independent of calcineurin and the immunophilins. The described method permits the direct confirmation of drug targets and recognition of drug-dependent changes in gene expression that are modulated through pathways distinct from the drugs intended target. Such a method may prove useful in improving the efficiency of drug development programs.

Transcriptional Profiling Shows that Gcn4p Is a Master Regulator of Gene Expression during Amino Acid Starvation in Yeast

ABSTRACT Starvation for amino acids induces Gcn4p, a transcriptional activator of amino acid biosynthetic genes in Saccharomyces cerevisiae. In an effort to identify all genes regulated by Gcn4p during amino acid starvation, we performed cDNA microarray analysis. Data from 21 pairs of hybridization experiments using two different strains derived from S288c revealed that more than 1,000 genes were induced, and a similar number were repressed, by a factor of 2 or more in response to histidine starvation imposed by 3-aminotriazole (3AT). Profiling of a gcn4Δ strain and a constitutively induced mutant showed that Gcn4p is required for the full induction by 3AT of at least 539 genes, termed Gcn4p targets. Genes in every amino acid biosynthetic pathway except cysteine and genes encoding amino acid precursors, vitamin biosynthetic enzymes, peroxisomal components, mitochondrial carrier proteins, and autophagy proteins were all identified as Gcn4p targets. Unexpectedly, genes involved in amino acid biosynthesis represent only a quarter of the Gcn4p target genes. Gcn4p also activates genes involved in glycogen homeostasis, and mutant analysis showed that Gcn4p suppresses glycogen levels in amino acid-starved cells. Numerous genes encoding protein kinases and transcription factors were identified as targets, suggesting that Gcn4p is a master regulator of gene expression. Interestingly, expression profiles for 3AT and the alkylating agent methyl methanesulfonate (MMS) overlapped extensively, and MMS inducedGCN4 translation. Thus, the broad transcriptional response evoked by Gcn4p is produced by diverse stress conditions. Finally, profiling of a gcn4Δ mutant uncovered an alternative induction pathway operating at many Gcn4p target genes in histidine-starved cells.

Exploration of Essential Gene Functions via Titratable Promoter Alleles

Nearly 20% of yeast genes are required for viability, hindering genetic analysis with knockouts. We created promoter-shutoff strains for over two-thirds of all essential yeast genes and subjected them to morphological analysis, size profiling, drug sensitivity screening, and microarray expression profiling. We then used this compendium of data to ask which phenotypic features characterized different functional classes and used these to infer potential functions for uncharacterized genes. We identified genes involved in ribosome biogenesis (HAS1, URB1, and URB2), protein secretion (SEC39), mitochondrial import (MIM1), and tRNA charging (GSN1). In addition, apparent negative feedback transcriptional regulation of both ribosome biogenesis and the proteasome was observed. We furthermore show that these strains are compatible with automated genetic analysis. This study underscores the importance of analyzing mutant phenotypes and provides a resource to complement the yeast knockout collection.

Overexpression of a kinase-inactive ATR protein causes sensitivity to DNA-damaging agents and defects in cell cycle checkpoints.

ATR, a phosphatidylinositol kinase‐related protein homologous to ataxia telangiectasia mutated (ATM), is important for the survival of human cells following many forms of DNA damage. Expression of a kinase‐inactive allele of ATR (ATRkd) in human fibroblasts causes increased sensitivity to ionizing radiation (IR), cis‐platinum and methyl methanesulfonate, but only slight UV radiation sensitivity. ATRkd overexpression abrogates the G2/M arrest after exposure to IR, and overexpression of wild‐type ATR complements the radioresistant DNA synthesis phenotype of cells lacking ATM, suggesting a potential functional overlap between these proteins. ATRkd overexpression also causes increased sensitivity to hydroxyurea that is associated with microtubule‐mediated nuclear abnormalities. These observations are consistent with uncoupling of certain mitotic events from the completion of S‐phase. Thus, ATR is an important component of multiple DNA damage response pathways and may be involved in the DNA replication (S/M) checkpoint.

Widespread aneuploidy revealed by DNA microarray expression profiling

Expression profiling using DNA microarrays holds great promise for a variety of research applications, including the systematic characterization of genes discovered by sequencing projects. To demonstrate the general usefulness of this approach, we recently obtained expression profiles for nearly 300 Saccharomyces cerevisiae deletion mutants. Approximately 8% of the mutants profiled exhibited chromosome-wide expression biases, leading to spurious correlations among profiles. Competitive hybridization of genomic DNA from the mutant strains and their isogenic parental wild-type strains showed they were aneuploid for whole chromosomes or chromosomal segments. Expression profile data published by several other laboratories also suggest the use of aneuploid strains. In five separate cases, the extra chromosome harboured a close homologue of the deleted gene; in two cases, a clear growth advantage for cells acquiring the extra chromosome was demonstrated. Our results have implications for interpreting whole-genome expression data, particularly from cells known to suffer genomic instability, such as malignant or immortalized cells.

Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes.

Modern medicine faces the challenge of developing safer and more effective therapies to treat human diseases. Many drugs currently in use were discovered without knowledge of their underlying molecular mechanisms. Understanding their biological targets and modes of action will be essential to design improved second-generation compounds. Here, we describe the use of a genome-wide pool of tagged heterozygotes to assess the cellular effects of 78 compounds in Saccharomyces cerevisiae. Specifically, lanosterol synthase in the sterol biosynthetic pathway was identified as a target of the antianginal drug molsidomine, which may explain its cholesterol-lowering effects. Further, the rRNA processing exosome was identified as a potential target of the cell growth inhibitor 5-fluorouracil. This genome-wide screen validated previously characterized targets or helped identify potentially new modes of action for over half of the compounds tested, providing proof of this principle for analyzing the modes of action of clinically relevant compounds.

Role of scaffolds in MAP kinase pathway specificity revealed by custom design of pathway-dedicated signaling proteins

BACKGROUNDnSignal transduction pathways with shared components must be insulated from each other to avoid the inappropriate activation of multiple pathways by a single stimulus. Scaffold proteins are thought to contribute to this specificity by binding select substrates.nnnRESULTSnWe have studied the ability of scaffold proteins to influence signaling by the yeast kinase Ste11, a MAPKKK molecule that participates in three distinct MAP kinase pathways: mating, filamentation, and HOG. We used protein fusions to force Ste11 to associate preferentially with a subset of its possible binding partners in vivo, including Ste5, Ste7, and Pbs2. Signaling became confined to a particular pathway when Ste11 was covalently attached to these scaffolds or substrates. This pathway bias was conferred upon both stimulus-activated and constitutively active forms of Ste11. We also used membrane-targeted derivatives of the mating pathway scaffold, Ste5, to show that stimulus-independent signaling initiated by this scaffold remained pathway specific. Finally, we demonstrate that loss of pathway insulation has a negative physiological consequence, as nonspecific activation of both the HOG and mating pathways interfered with proper execution of the mating pathway.nnnCONCLUSIONSnThe signaling properties of these kinase fusions support a model in which scaffold proteins dictate substrate choice and promote pathway specificity by presenting preferred substrates in high local concentration. Furthermore, insulation is inherent to scaffold-mediated signaling and does not require that signaling be initiated by pathway-specific stimuli or activator proteins. Our results give insight into the mechanisms and physiological importance of pathway insulation and provide a foundation for the design of customized signaling proteins.

Systems analysis of eleven rodent disease models reveals an inflammatome signature and key drivers.

Common inflammatome gene signatures as well as disease‐specific signatures were identified by analyzing 12 expression profiling data sets derived from 9 different tissues isolated from 11 rodent inflammatory disease models. The inflammatome signature significantly overlaps with known drug targets and co‐expressed gene modules linked to metabolic disorders and cancer. A large proportion of genes in this signature are tightly connected in tissue‐specific Bayesian networks (BNs) built from multiple independent mouse and human cohorts. Both the inflammatome signature and the corresponding consensus BNs are highly enriched for immune response‐related genes supported as causal for adiposity, adipokine, diabetes, aortic lesion, bone, muscle, and cholesterol traits, suggesting the causal nature of the inflammatome for a variety of diseases. Integration of this inflammatome signature with the BNs uncovered 151 key drivers that appeared to be more biologically important than the non‐drivers in terms of their impact on disease phenotypes. The identification of this inflammatome signature, its network architecture, and key drivers not only highlights the shared etiology but also pinpoints potential targets for intervention of various common diseases.