44 research outputs found

    CRX Is a Diagnostic Marker of Retinal and Pineal Lineage Tumors

    Get PDF
    Background: CRX is a homeobox transcription factor whose expression and function is critical to maintain retinal and pineal lineage cells and their progenitors. To determine the biologic and diagnostic potential of CRX in human tumors of the retina and pineal, we examined its expression in multiple settings. Methodology/Principal Findings: Using situ hybridization and immunohistochemistry we show that Crx RNA and protein expression are exquisitely lineage restricted to retinal and pineal cells during normal mouse and human development. Gene expression profiling analysis of a wide range of human cancers and cancer cell lines also supports that CRX RNA is highly lineage restricted in cancer. Immunohistochemical analysis of 22 retinoblastomas and 13 pineal parenchymal tumors demonstrated strong expression of CRX in over 95% of these tumors. Importantly, CRX was not detected in the majority of tumors considered in the differential diagnosis of pineal region tumors (n = 78). The notable exception was medulloblastoma, 40% of which exhibited CRX expression in a heterogeneous pattern readily distinguished from that seen in retino-pineal tumors. Conclusions/Significance: These findings describe new potential roles for CRX in human cancers and highlight the general utility of lineage restricted transcription factors in cancer biology. They also identify CRX as a sensitive and specific clinical marker and a potential lineage dependent therapeutic target in retinoblastoma and pineoblastoma

    Next-generation sequencing and microarray-based interrogation of microRNAs from formalin-fixed, paraffin-embedded tissue: Preliminary assessment of cross-platform concordance

    Get PDF
    AbstractNext-generation sequencing is increasingly employed in biomedical investigations. Strong concordance between microarray and mRNA-seq levels has been reported in high quality specimens but information is lacking on formalin-fixed, paraffin-embedded (FFPE) tissues, and particularly for microRNA (miRNA) analysis. We conducted a preliminary examination of the concordance between miRNA-seq and cDNA-mediated annealing, selection, extension, and ligation (DASL) miRNA assays. Quantitative agreement between platforms is moderate (Spearman correlation 0.514–0.596) and there is discordance of detection calls on a subset of miRNAs. Quantitative PCR (q-RT-PCR) performed for several discordant miRNAs confirmed the presence of most sequences detected by miRNA-seq but not by DASL but also that miRNA-seq did not detect some sequences, which DASL confidently detected. Our results suggest that miRNA-seq is specific, with few false positive calls, but it may not detect certain abundant miRNAs in FFPE tissue. Further work is necessary to fully address these issues that are pertinent for translational research

    GeneSigDB—a curated database of gene expression signatures

    Get PDF
    The primary objective of most gene expression studies is the identification of one or more gene signatures; lists of genes whose transcriptional levels are uniquely associated with a specific biological phenotype. Whilst thousands of experimentally derived gene signatures are published, their potential value to the community is limited by their computational inaccessibility. Gene signatures are embedded in published article figures, tables or in supplementary materials, and are frequently presented using non-standard gene or probeset nomenclature. We present GeneSigDB (http://compbio.dfci.harvard.edu/genesigdb) a manually curated database of gene expression signatures. GeneSigDB release 1.0 focuses on cancer and stem cells gene signatures and was constructed from more than 850 publications from which we manually transcribed 575 gene signatures. Most gene signatures (n = 560) were successfully mapped to the genome to extract standardized lists of EnsEMBL gene identifiers. GeneSigDB provides the original gene signature, the standardized gene list and a fully traceable gene mapping history for each gene from the original transcribed data table through to the standardized list of genes. The GeneSigDB web portal is easy to search, allows users to compare their own gene list to those in the database, and download gene signatures in most common gene identifier formats

    Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks

    Get PDF
    Genomics provided us with an unprecedented quantity of data on the genes that are activated or repressed in a wide range of phenotypes. We have increasingly come to recognize that defining the networks and pathways underlying these phenotypes requires both the integration of multiple data types and the development of advanced computational methods to infer relationships between the genes and to estimate the predictive power of the networks through which they interact. To address these issues we have developed Predictive Networks (PN), a flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these ‘known’ interactions together with gene expression data to infer robust gene networks. The PN web application is accessible from http://predictivenetworks.org. The PN code base is freely available at https://sourceforge.net/projects/predictivenets/
    corecore