Combined Gene Expression and RNAi Screening to Identify Alkylation Damage Survival Pathways from Fly to Human.

Alkylating agents are a key component of cancer chemotherapy. Several cellular mechanisms are known to be important for its survival, particularly DNA repair and xenobiotic detoxification, yet genomic screens indicate that additional cellular components may be involved. Elucidating these components has value in either identifying key processes that can be modulated to improve chemotherapeutic efficacy or may be altered in some cancers to confer chemoresistance. We therefore set out to reevaluate our prior Drosophila RNAi screening data by comparison to gene expression arrays in order to determine if we could identify any novel processes in alkylation damage survival. We noted a consistent conservation of alkylation survival pathways across platforms and species when the analysis was conducted on a pathway/process level rather than at an individual gene level. Better results were obtained when combining gene lists from two datasets (RNAi screen plus microarray) prior to analysis. In addition to previously identified DNA damage responses (p53 signaling and Nucleotide Excision Repair), DNA-mRNA-protein metabolism (transcription/translation) and proteasome machinery, we also noted a highly conserved cross-species requirement for NRF2, glutathione (GSH)-mediated drug detoxification and Endoplasmic Reticulum stress (ER stress)/Unfolded Protein Responses (UPR) in cells exposed to alkylation. The requirement for GSH, NRF2 and UPR in alkylation survival was validated by metabolomics, protein studies and functional cell assays. From this we conclude that RNAi/gene expression fusion is a valid strategy to rapidly identify key processes that may be extendable to other contexts beyond damage survival.

A high-content morphological screen identifies novel microRNAs that regulate neuroblastoma cell differentiation.

Neuroblastoma, the most common extracranial solid tumor of childhood, arises from neural crest cell precursors that fail to differentiate. Inducing cell differentiation is an important therapeutic strategy for neuroblastoma. We developed a direct functional high-content screen to identify differentiation-inducing microRNAs, in order to develop microRNA-based differentiation therapy for neuroblastoma. We discovered novel microRNAs, and more strikingly, three microRNA seed families that induce neuroblastoma cell differentiation. In addition, we showed that microRNA seed families were overrepresented in the identified group of fourteen differentiation-inducing microRNAs, suggesting that microRNA seed families are functionally more important in neuroblastoma differentiation than microRNAs with unique sequences. We further investigated the differentiation-inducing function of the microRNA-506-3p/microRNA-124-3p seed family, which was the most potent inducer of differentiation. We showed that the differentiation-inducing function of microRNA-506-3p/microRNA-124-3p is mediated, at least partially, by down-regulating expression of their targets CDK4 and STAT3. We further showed that expression of miR-506-3p, but not miR-124-3p, is dramatically upregulated in differentiated neuroblastoma cells, suggesting the important role of endogenous miR-506-3p in differentiation and tumorigenesis. Overall, our functional screen on microRNAs provided the first comprehensive analysis on the involvements of microRNA species in neuroblastoma cell differentiation and identified novel differentiation-inducing microRNAs. Further investigations are certainly warranted to fully characterize the function of the identified microRNAs in order to eventually benefit neuroblastoma therapy.

A novel significance score for gene selection and ranking.

MOTIVATION: When identifying differentially expressed (DE) genes from high-throughput gene expression measurements, we would like to take both statistical significance (such as P-value) and biological relevance (such as fold change) into consideration. In gene set enrichment analysis (GSEA), a score that can combine fold change and P-value together is needed for better gene ranking. RESULTS: We defined a gene significance score π-value by combining expression fold change and statistical significance (P-value), and explored its statistical properties. When compared to various existing methods, π-value based approach is more robust in selecting DE genes, with the largest area under curve in its receiver operating characteristic curve. We applied π-value to GSEA and found it comparable to P-value and t-statistic based methods, with added protection against false discovery in certain situations. Finally, in a gene functional study of breast cancer profiles, we showed that using π-value helps elucidating otherwise overlooked important biological functions. AVAILABILITY: http://gccri.uthscsa.edu/Pi_Value_Supplementary.asp CONTACT: xy@ieee.org, cheny8@uthscsa.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pathway Distiller - multisource biological pathway consolidation.

BACKGROUND: One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. METHODS: After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. RESULTS: We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. CONCLUSIONS: By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.

The RNA-binding protein Musashi1 affects medulloblastoma growth via a network of cancer-related genes and is an indicator of poor prognosis.

Musashi1 (Msi1) is a highly conserved RNA-binding protein that is required during the development of the nervous system. Msi1 has been characterized as a stem cell marker, controlling the balance between self-renewal and differentiation, and has also been implicated in tumorigenesis, being highly expressed in multiple tumor types. We analyzed Msi1 expression in a large cohort of medulloblastoma samples and found that Msi1 is highly expressed in tumor tissue compared with normal cerebellum. Notably, high Msi1 expression levels proved to be a sign of poor prognosis. Msi1 expression was determined to be particularly high in molecular subgroups 3 and 4 of medulloblastoma. We determined that Msi1 is required for tumorigenesis because inhibition of Msi1 expression by small-interfering RNAs reduced the growth of Daoy medulloblastoma cells in xenografts. To characterize the participation of Msi1 in medulloblastoma, we conducted different high-throughput analyses. Ribonucleoprotein immunoprecipitation followed by microarray analysis (RIP-chip) was used to identify mRNA species preferentially associated with Msi1 protein in Daoy cells. We also used cluster analysis to identify genes with similar or opposite expression patterns to Msi1 in our medulloblastoma cohort. A network study identified RAC1, CTGF, SDCBP, SRC, PRL, and SHC1 as major nodes of an Msi1-associated network. Our results suggest that Msi1 functions as a regulator of multiple processes in medulloblastoma formation and could become an important therapeutic target.

Before It Gets Started: Regulating Translation at the 5' UTR.

Translation regulation plays important roles in both normal physiological conditions and diseases states. This regulation requires cis-regulatory elements located mostly in 5' and 3' UTRs and trans-regulatory factors (e.g., RNA binding proteins (RBPs)) which recognize specific RNA features and interact with the translation machinery to modulate its activity. In this paper, we discuss important aspects of 5' UTR-mediated regulation by providing an overview of the characteristics and the function of the main elements present in this region, like uORF (upstream open reading frame), secondary structures, and RBPs binding motifs and different mechanisms of translation regulation and the impact they have on gene expression and human health when deregulated.

Mice heterozygous for CREB binding protein are hypersensitive to γ-radiation and invariably develop myelodysplastic/myeloproliferative neoplasm.

Myelodysplastic syndrome is a complex family of preleukemic diseases in which hematopoietic stem cell defects lead to abnormal differentiation in one or more blood lineages. Disease progression is associated with increasing genomic instability and a large proportion of patients go on to develop acute myeloid leukemia. Primarily a disease of the elderly, it can also develop after chemotherapy. We have previously reported that CREB binding protein (Crebbp) heterozygous mice have an increased incidence of hematological malignancies, and others have shown that CREBBP is one of the genes altered by chromosomal translocations found in patients suffering from therapy-related myelodysplastic syndrome. This led us to investigate whether hematopoietic tumor development in Crebbp(+/-) mice is preceded by a myelodysplastic phase and whether we could uncover molecular mechanisms that might contribute to its development. We report here that Crebbp(+/-) mice invariably develop myelodysplastic/myeloproliferative neoplasm within 9 to 12 months of age. They are also hypersensitive to ionizing radiation and show a marked decrease in poly(ADP-ribose) polymerase-1 activity after irradiation. In addition, protein levels of XRCC1 and APEX1, key components of base excision repair machinery, are reduced in unirradiated Crebbp(+/-) cells or upon targeted knockdown of CREBBP levels. Our results provide validation of a novel myelodysplastic/myeloproliferative neoplasm mouse model and, more importantly, point to defective repair of DNA damage as a contributing factor to the pathogenesis of this currently incurable disease.

miR-33a/b contribute to the regulation of fatty acid metabolism and insulin signaling.

Cellular imbalances of cholesterol and fatty acid metabolism result in pathological processes, including atherosclerosis and metabolic syndrome. Recent work from our group and others has shown that the intronic microRNAs hsa-miR-33a and hsa-miR-33b are located within the sterol regulatory element-binding protein-2 and -1 genes, respectively, and regulate cholesterol homeostasis in concert with their host genes. Here, we show that miR-33a and -b also regulate genes involved in fatty acid metabolism and insulin signaling. miR-33a and -b target key enzymes involved in the regulation of fatty acid oxidation, including carnitine O-octaniltransferase, carnitine palmitoyltransferase 1A, hydroxyacyl-CoA-dehydrogenase, Sirtuin 6 (SIRT6), and AMP kinase subunit-α. Moreover, miR-33a and -b also target the insulin receptor substrate 2, an essential component of the insulin-signaling pathway in the liver. Overexpression of miR-33a and -b reduces both fatty acid oxidation and insulin signaling in hepatic cell lines, whereas inhibition of endogenous miR-33a and -b increases these two metabolic pathways. Together, these data establish that miR-33a and -b regulate pathways controlling three of the risk factors of metabolic syndrome, namely levels of HDL, triglycerides, and insulin signaling, and suggest that inhibitors of miR-33a and -b may be useful in the treatment of this growing health concern.

Two-tiered approach identifies a network of cancer and liver disease-related genes regulated by miR-122.

MicroRNAs function as important regulators of gene expression and are commonly linked to development, differentiation, and diseases such as cancer. To better understand their roles in various biological processes, identification of genes targeted by microRNAs is necessary. Although prediction tools have significantly helped with this task, experimental approaches are ultimately required for extensive target search and validation. We employed two independent yet complementary high throughput approaches to map a large set of mRNAs regulated by miR-122, a liver-specific microRNA implicated in regulation of fatty acid and cholesterol metabolism, hepatitis C infection, and hepatocellular carcinoma. The combination of luciferase reporter-based screening and shotgun proteomics resulted in the identification of 260 proteins significantly down-regulated in response to miR-122 in at least one method, 113 of which contain predicted miR-122 target sites. These proteins are enriched for functions associated with the cell cycle, differentiation, proliferation, and apoptosis. Among these miR-122-sensitive proteins, we identified a large group with strong connections to liver metabolism, diseases, and hepatocellular carcinoma. Additional analyses, including examination of consensus binding motifs for both miR-122 and target sequences, provide further insight into miR-122 function.