BackgroundmiRNAs exert their effect through a negative regulatory mechanism silencing expression upon hybridizing to their target mRNA, and have a prominent position in the control of many cellular processes including carcinogenesis. Previous miRNA studies on retinoblastoma (Rb) have been limited to specific miRNAs reported in other tumors or to medium density arrays. Here we report expression analysis of the whole miRNome on 12 retinoblastoma tumor samples using a high throughput microarray platform including 2578 mature miRNAs.MethodsTwelve retinoblastoma tumor samples were analyzed using an Affymetrix platform including 2578 mature miRNAs. We applied RMA analysis to normalize raw data, obtained categorical data from detection call values, and also used signal intensity derived expression data. We used Diana-Tools-microT-CDS to find miRNA targets and ChromDraw to map miRNAs in chromosomes.ResultsWe discovered a core-cluster of 30 miRNAs that were highly expressed in all the cases and a cluster of 993 miRNAs that were uniformly absent in all cases. Another 1022 miRNA were variably present in the samples reflecting heterogeneity between tumors. We explored mRNA targets, pathways and biological processes affected by some of these miRNAs. We propose that the core-cluster of 30 miRs represent miRNA machinery common to all Rb, and affecting most pathways considered hallmarks of cancer. In this core, we identified miR-3613 as a potential and critical down regulatory hub, because it is highly expressed in all the samples and its potential mRNA targets include at least 36 tumor suppressor genes, including RB1. In the variably expressed miRNA, 36 were differentially expressed between males and females. Some of the potential pathways targeted by these 36 miRNAs were associated with hormonal production.ConclusionThese findings indicate that Rb tumor samples share a common miRNA expression profile regardless of tumor heterogeneity, and shed light on potential novel therapeutic targets such as mir-3613 This is the first work to delineate the miRNA landscape in retinoblastoma tumor samples using an unbiased approach.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-017-3421-3) contains supplementary material, which is available to authorized users.
The genus Psychrobacter contains environmental, psychrophilic and halotolerant gram-negative bacteria considered rare opportunistic pathogens in humans. Metagenomics was performed on the cerebrospinal fluid (CSF) of a pediatric patient with meningitis. Nucleic acids were extracted, randomly amplified, and sequenced with the 454 GS FLX Titanium next-generation sequencing (NGS) system. Sequencing reads were assembled, and potential virulence genes were predicted. Phylogenomic and phylogenetic studies were performed. Psychrobacter sp. 310 was identified, and several virulence genes characteristic of pathogenic bacteria were found. The phylogenomic study and 16S rRNA gene phylogenetic analysis showed that the closest relative of Psychrobacter sp. 310 was Psychrobacter sanguinis. To our knowledge, this is the first report of a meningitis case associated with Psychrobacter sp. identified by NGS metagenomics in CSF from a pediatric patient. The metagenomic strategy based on NGS was a powerful tool to identify a rare unknown pathogen in a clinical case.
Genes are frequently lost or gained in malignant tumors and the analysis of these changes can be informative about the underlying tumor biology. Retinoblastoma is a pediatric intraocular malignancy, and since deletions in chromosome 13 have been described in this tumor, we performed genome wide sequencing with the Illumina platform to test whether recurrent losses could be detected in low coverage data from DNA pools of Rb cases. An in silico reference profile for each pool was created from the human genome sequence GRCh37p5; a chromosome integrity score and a graphics 40 Kb window analysis approach, allowed us to identify with high resolution previously reported non random recurrent losses in all chromosomes of these tumors. We also found a pattern of gains and losses associated to clear and dark cytogenetic bands respectively. We further analyze a pool of medulloblastoma and found a more stable genomic profile and previously reported losses in this tumor. This approach facilitates identification of recurrent deletions from many patients that may be biological relevant for tumor development.
Retinoblastoma (Rb) is a pediatric intraocular malignancy and probably the most robust clinical model on which genetic predisposition to develop cancer has been demonstrated. Since deletions in chromosome 13 have been described in this tumor, we performed next generation sequencing to test whether recurrent losses could be detected in low coverage data. We used Illumina platform for 13 tumor tissue samples: two pools of 4 retinoblastoma cases each and one pool of 5 medulloblastoma cases (raw data can be found at http://www.ebi.ac.uk/ena/data/view/PRJEB6630).We first created an in silico reference profile generated from a human sequenced genome (GRCh37p5). From this data we calculated an integrity score to get an overview of gains and losses in all chromosomes; we next analyzed each chromosome in windows of 40 kb length, calculating for each window the log2 ratio between reads from tumor pool and in silico reference. Finally we generated panoramic maps with all the windows whether lost or gained along each chromosome associated to its cytogenetic bands to facilitate interpretation. Expression microarrays was done for the same samples and a list of over and under expressed genes is presented here. For this detection a significance analysis was done and a log2 fold change was chosen as significant (raw data can be found at http://www.ncbi.nlm.nih.gov/geo/accession number GSE11488). The complete research article can be found at Cancer Genetics journal (Garcia-Chequer et al., in press) [1]. In summary here we provide an overview with visual graphics of gains and losses chromosome by chromosome in retinoblastoma and medulloblastoma, also the integrity score analysis and a list of genes with relevant expression associated. This material can be useful to researchers that may want to explore gains and losses in other malignant tumors with this approach or compare their data with retinoblastoma.
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