Combined genome-wide expression profiling and targeted RNA interference in primary mouse macrophages reveals perturbation of transcriptional networks associated with interferon signalling.

BACKGROUND: Interferons (IFNs) are potent antiviral cytokines capable of reprogramming the macrophage phenotype through the induction of interferon-stimulated genes (ISGs). Here we have used targeted RNA interference to suppress the expression of a number of key genes associated with IFN signalling in murine macrophages prior to stimulation with interferon-gamma. Genome-wide changes in transcript abundance caused by siRNA activity were measured using exon-level microarrays in the presence or absence of IFNgamma. RESULTS: Transfection of murine bone-marrow derived macrophages (BMDMs) with a non-targeting (control) siRNA and 11 sequence-specific siRNAs was performed using a cationic lipid transfection reagent (Lipofectamine2000) prior to stimulation with IFNgamma. Total RNA was harvested from cells and gene expression measured on Affymetrix GeneChip Mouse Exon 1.0 ST Arrays. Network-based analysis of these data revealed six siRNAs to cause a marked shift in the macrophage transcriptome in the presence or absence IFNgamma. These six siRNAs targeted the Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2 transcripts. The perturbation of the transcriptome by the six siRNAs was highly similar in each case and affected the expression of over 600 downstream transcripts. Regulated transcripts were clustered based on co-expression into five major groups corresponding to transcriptional networks associated with the type I and II IFN response, cell cycle regulation, and NF-KB signalling. In addition we have observed a significant non-specific immune stimulation of cells transfected with siRNA using Lipofectamine2000, suggesting use of this reagent in BMDMs, even at low concentrations, is enough to induce a type I IFN response. CONCLUSION: Our results provide evidence that the type I IFN response in murine BMDMs is dependent on Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2, and that siRNAs targeted to these genes results in perturbation of key transcriptional networks associated with type I and type II IFN signalling and a suppression of macrophage M1 polarization.

Highly parallel identification of essential genes in cancer cells.

More complete knowledge of the molecular mechanisms underlying cancer will improve prevention, diagnosis and treatment. Efforts such as The Cancer Genome Atlas are systematically characterizing the structural basis of cancer, by identifying the genomic mutations associated with each cancer type. A powerful complementary approach is to systematically characterize the functional basis of cancer, by identifying the genes essential for growth and related phenotypes in different cancer cells. Such information would be particularly valuable for identifying potential drug targets. Here, we report the development of an efficient, robust approach to perform genome-scale pooled shRNA screens for both positive and negative selection and its application to systematically identify cell essential genes in 12 cancer cell lines. By integrating these functional data with comprehensive genetic analyses of primary human tumors, we identified known and putative oncogenes such as EGFR, KRAS, MYC, BCR-ABL, MYB, CRKL, and CDK4 that are essential for cancer cell proliferation and also altered in human cancers. We further used this approach to identify genes involved in the response of cancer cells to tumoricidal agents and found 4 genes required for the response of CML cells to imatinib treatment: PTPN1, NF1, SMARCB1, and SMARCE1, and 5 regulators of the response to FAS activation, FAS, FADD, CASP8, ARID1A and CBX1. Broad application of this highly parallel genetic screening strategy will not only facilitate the rapid identification of genes that drive the malignant state and its response to therapeutics but will also enable the discovery of genes that participate in any biological process.

CYP4F2 genetic variant alters required warfarin dose.

Warfarin is an effective, commonly prescribed anticoagulant used to treat and prevent thrombotic events. Because of historically high rates of drug-associated adverse events, warfarin remains underprescribed. Further, interindividual variability in therapeutic dose mandates frequent monitoring until target anticoagulation is achieved. Genetic polymorphisms involved in warfarin metabolism and sensitivity have been implicated in variability of dose. Here, we describe a novel variant that influences warfarin requirements. To identify additional genetic variants that contribute to warfarin requirements, screening of DNA variants in additional genes that code for drug-metabolizing enzymes and drug transport proteins was undertaken using the Affymetrix drug-metabolizing enzymes and transporters panel. A DNA variant (rs2108622; V433M) in cytochrome P450 4F2 (CYP4F2) was associated with warfarin dose in 3 independent white cohorts of patients stabilized on warfarin representing diverse geographic regions in the United States and accounted for a difference in warfarin dose of approximately 1 mg/day between CC and TT subjects. Genetic variation of CYP4F2 was associated with a clinically relevant effect on warfarin requirement.

Orphan G protein-coupled receptor GPR56 plays a role in cell transformation and tumorigenesis involving the cell adhesion pathway.

GPR56 is an orphan G protein - coupled receptor, mutations of which have recently been associated with bilateral frontoparietal polymicrogyria, a rare neurologic disease that has implications in brain development. However, no phenotype beyond central nervous system has yet been described for the GPR56-null mutations despite abundant GPR56 expression in many non - central nervous system adult tissues. In the present study, we show that higher GPR56 expression is correlated with the cellular transformation phenotypes of several cancer tissues compared with their normal counterparts, implying a potential oncogenic function. RNA interference-mediated GPR56 silencing results in apoptosis induction and reduced anchorage-independent growth of cancer cells via increased anoikis, whereas cDNA overexpression resulted in increased foci formation in mouse fibroblast NIH3T3 cell line. When GPR56 silencing was induced in vivo in several xenograft tumor models, significant tumor responses (including regression) were observed, suggesting the potential of targeting GPR56 in the development of tumor therapies. The expression profiling of GPR56-silenced A2058 melanoma cell line revealed several genes whose expression was affected by GPR56 silencing, particularly those in the integrin-mediated signaling and cell adhesion pathways. The potential role of GPR56 in cancer cell adhesion was further confirmed by the observation that GPR56 silencing also reduced cell adhesion to the extracellular matrix, which is consistent with the observed increase in anoikis and reduction in anchorage-independent growth phenotypes. The oncogenic potential and apparent absence of physiologic defects in adult human tissues lacking GPR56, as well as the targetable nature of G protein - coupled receptor by small molecule or antibody, make GPR56 an attractive drug target for the development of cancer therapies.

Chemical genetic transcriptional fingerprinting for selectivity profiling of kinase inhibitors.

The importance of protein kinases as a major class of drug targets across multiple diseases has generated a critical need for technologies that enable the identification of potent and selective kinase inhibitors. Bruton's tyrosine kinase (Btk) is a compelling drug target in multiple therapeutic areas, including systemic lupus erythematosus, asthma, rheumatoid arthritis, and B cell malignancies. We have combined potent, selective kinase inhibition through chemical genetics with gene expression profiling to identify a "fingerprint" of transcriptional changes associated with selective Btk kinase inhibition. The Btk transcriptional fingerprint shows remarkable relevance for Btk's biological roles and was used for functional selectivity profiling of two kinase inhibitor compounds. The fingerprint was able to rank the compounds by relative selectivity for Btk, and revealed broader off-target effects than observed in a broad panel of biochemical kinase cross screens. In addition to being useful for functional selectivity profiling, the fingerprint genes are themselves potential preclinical and clinical biomarkers for developing Btk-directed therapies.

Alternative splicing and differential gene expression in colon cancer detected by a whole genome exon array.

BACKGROUND: Alternative splicing is a mechanism for increasing protein diversity by excluding or including exons during post-transcriptional processing. Alternatively spliced proteins are particularly relevant in oncology since they may contribute to the etiology of cancer, provide selective drug targets, or serve as a marker set for cancer diagnosis. While conventional identification of splice variants generally targets individual genes, we present here a new exon-centric array (GeneChip Human Exon 1.0 ST) that allows genome-wide identification of differential splice variation, and concurrently provides a flexible and inclusive analysis of gene expression. RESULTS: We analyzed 20 paired tumor-normal colon cancer samples using a microarray designed to detect over one million putative exons that can be virtually assembled into potential gene-level transcripts according to various levels of prior supporting evidence. Analysis of high confidence (empirically supported) transcripts identified 160 differentially expressed genes, with 42 genes occupying a network impacting cell proliferation and another twenty nine genes with unknown functions. A more speculative analysis, including transcripts based solely on computational prediction, produced another 160 differentially expressed genes, three-fourths of which have no previous annotation. We also present a comparison of gene signal estimations from the Exon 1.0 ST and the U133 Plus 2.0 arrays. Novel splicing events were predicted by experimental algorithms that compare the relative contribution of each exon to the cognate transcript intensity in each tissue. The resulting candidate splice variants were validated with RT-PCR. We found nine genes that were differentially spliced between colon tumors and normal colon tissues, several of which have not been previously implicated in cancer. Top scoring candidates from our analysis were also found to substantially overlap with EST-based bioinformatic predictions of alternative splicing in cancer. CONCLUSION: Differential expression of high confidence transcripts correlated extremely well with known cancer genes and pathways, suggesting that the more speculative transcripts, largely based solely on computational prediction and mostly with no previous annotation, might be novel targets in colon cancer. Five of the identified splicing events affect mediators of cytoskeletal organization (ACTN1, VCL, CALD1, CTTN, TPM1), two affect extracellular matrix proteins (FN1, COL6A3) and another participates in integrin signaling (SLC3A2). Altogether they form a pattern of colon-cancer specific alterations that may particularly impact cell motility.

A whole genome long-range haplotype (WGLRH) test for detecting imprints of positive selection in human populations.

MOTIVATION: The identification of signatures of positive selection can provide important insights into recent evolutionary history in human populations. Current methods mostly rely on allele frequency determination or focus on one or a small number of candidate chromosomal regions per study. With the availability of large-scale genotype data, efficient approaches for an unbiased whole genome scan are becoming necessary. METHODS: We have developed a new method, the whole genome long-range haplotype test (WGLRH), which uses genome-wide distributions to test for recent positive selection. Adapted from the long-range haplotype (LRH) test, the WGLRH test uses patterns of linkage disequilibrium (LD) to identify regions with extremely low historic recombination. Common haplotypes with significantly longer than expected ranges of LD given their frequencies are identified as putative signatures of recent positive selection. In addition, we have also determined the ancestral alleles of SNPs by genotyping chimpanzee and gorilla DNA, and have identified SNPs where the non-ancestral alleles have risen to extremely high frequencies in human populations, termed 'flipped SNPs'. Combining the haplotype test and the flipped SNPs determination, the WGLRH test serves as an unbiased genome-wide screen for regions under putative selection, and is potentially applicable to the study of other human populations. RESULTS: Using WGLRH and high-density oligonucleotide arrays interrogating 116 204 SNPs, we rapidly identified putative regions of positive selection in three populations (Asian, Caucasian, African-American), and extended these observations to a fourth population, Yoruba, with data obtained from the International HapMap consortium. We mapped significant regions to annotated genes. While some regions overlap with genes previously suggested to be under positive selection, many of the genes have not been previously implicated in natural selection and offer intriguing possibilities for further study. AVAILABILITY: the programs for the WGLRH algorithm are freely available and can be downloaded at http://www.affymetrix.com/support/supplement/WGLRH_program.zip.

Gene array profiling of large hypothalamic CNS regions in lactating and randomly cycling virgin mice.

A dramatic example of neuronal and physiological plasticity in adult mammals occurs during the transition from a non-maternal to a maternal, lactating state. In this study, we compared gene expression within a large continuous region of the CNS involved in maternal behaviors (hypothalamus, preoptic regions, and nucleus accumbens) between lactating (L) (postpartum Day 7) and randomly cycling virgin (V) outbred mice. Using high-density oligonucleotide arrays representing 11,904 genes, two statistical algorithms were used to identify significant differences in gene expression: robust multiarray (P < 0.001) (n = 92 genes) and significance analysis of microarrays using a 10% false discover rate (n = 114 genes). 27 common genes were identified as significant using both techniques. A subset of genes (n = 5) were selected and examined by real-time PCR. Our findings were consistent with previous published work. For example, neuropeptide Y (NPY) and proenkephalin were elevated in L mice, whereas POMC was decreased. Increased levels of NPY Y2 receptor and polo-like kinase and decreased levels of endothelin receptor type b in L mice are examples of novel gene expression changes not previously identified. Expression differences occurred in broad classes. Together, our findings provide possible new material on gene expression changes that may support maternal behaviors. The advantages and drawbacks of sampling large CNS regions using arrays are discussed.

A knowledge-based clustering algorithm driven by Gene Ontology.

We have developed an algorithm for inferring the degree of similarity between genes by using the graph-based structure of Gene Ontology (GO). We applied this knowledge-based similarity metric to a clique-finding algorithm for detecting sets of related genes with biological classifications. We also combined it with an expression-based distance metric to produce a co-cluster analysis, which accentuates genes with both similar expression profiles and similar biological characteristics and identifies gene clusters that are more stable and biologically meaningful. These algorithms are demonstrated in the analysis of MPRO cell differentiation time series experiments.

Influence of the period-dependent circadian clock on diurnal, circadian, and aperiodic gene expression in Drosophila melanogaster.

We measured daily gene expression in heads of control and period mutant Drosophila by using oligonucleotide microarrays. In control flies, 72 genes showed diurnal rhythms in light-dark cycles; 22 of these also oscillated in free-running conditions. The period gene significantly influenced the expression levels of over 600 nonoscillating transcripts. Expression levels of several hundred genes also differed significantly between control flies kept in light-dark versus constant darkness but differed minimally between per(01) flies kept in the same two conditions. Thus, the period-dependent circadian clock regulates only a limited set of rhythmically expressed transcripts. Unexpectedly, period regulates basal and light-regulated gene expression to a very broad extent.