Discovery of a transcriptomic core of genes shared in 8 primary retinoblastoma with a novel detection score analysis.

PURPOSE: Expression microarrays are powerful technology that allows large-scale analysis of RNA profiles in a tissue; these platforms include underexploited detection scores outputs. We developed an algorithm using the detection score, to generate a detection profile of shared elements in retinoblastoma as well as to determine its transcriptomic size and structure. METHODS: We analyzed eight briefly cultured primary retinoblastomas with the Human transcriptome array 2.0 (HTA2.0). Transcripts and genes detection scores were determined using the Detection Above Background algorithm (DABG). We used unsupervised and supervised computational tools to analyze detected and undetected elements; WebGestalt was used to explore functions encoded by genes in relevant clusters and performed experimental validation. RESULTS: We found a core cluster with 7,513 genes detected and shared by all samples, 4,321 genes in a cluster that was commonly absent, and 7,681 genes variably detected across the samples accounting for tumor heterogeneity. Relevant pathways identified in the core cluster relate to cell cycle, RNA transport, and DNA replication. We performed a kinome analysis of the core cluster and found 4 potential therapeutic kinase targets. Through analysis of the variably detected genes, we discovered 123 differentially expressed transcripts between bilateral and unilateral cases. CONCLUSIONS: This novel analytical approach allowed determining the retinoblastoma transcriptomic size, a shared active transcriptomic core among the samples, potential therapeutic target kinases shared by all samples, transcripts related to inter tumor heterogeneity, and to determine transcriptomic profiles without the need of control tissues. This approach is useful to analyze other cancer or tissue types.

Circulating miRNome detection analysis reveals 537 miRNAS in plasma, 625 in extracellular vesicles and a discriminant plasma signature of 19 miRNAs in children with retinoblastoma from which 14 are also detected in corresponding primary tumors.

miRNAs regulate post-transcriptional gene expression in metazoans, and thus are involved in many fundamental cellular biological processes. Extracellular miRNAs are also found in most human biofluids including plasma. These circulating miRNAs constitute a long distance inter cellular communication system and are potentially useful biomarkers. High throughput technologies like microarrays are able to scan a complete miRNome providing useful detection scores that are underexplored. We proposed to answer how many and which miRNAs are detectable in plasma or extracellular vesicles as these questions have not yet been answered. We set out to address this knowledge gap by analyzing the mirRNome in plasma and corresponding extracellular vesicles (EVs) from 12 children affected by retinoblastoma (Rb) a childhood intraocular malignant tumor, as well as from 12 healthy similarly aged controls. We calculated an average of 537 detectable miRNAs in plasma and 625 in EVs. The most miRNA enriched compartment were EVs from Rb cases with an average of 656 detectable elements. Using hierarchical clustering with the detection scores, we generated broad detection mirnome maps and identified a plasma signature of 19 miRNAs present in all Rb cases that is able to discriminate cases from controls. An additional 9 miRNAs were detected in all the samples; within this group, miRNA-5787 and miRNA-6732-5p were highly abundant and displayed very low variance across all the samples, suggesting both are good candidates to serve as plasma references or normalizers. Further exploration considering participant's sex, allowed discovering 5 miRNAs which corresponded only to females and 4 miRNAs corresponding only to males. Target and pathway analysis of these miRNAs revealed hormonal function including estrogen, thyroid signaling pathways and testosterone biosynthesis. This approach allows a comprehensive unbiased survey of a circulating miRNome landscape, creating the possibility to define normality in mirnomic profiles, and to locate where in these miRNome profiles promising and potentially useful circulating miRNA signatures can be found.

miRNome landscape analysis reveals a 30 miRNA core in retinoblastoma.

BACKGROUND: miRNAs 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. METHODS: Twelve 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. RESULTS: We 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. CONCLUSION: These 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.

Detection of common chromosomal translocations in small round blue cell pediatric tumors.

BACKGROUND AND AIMS: Recurrent and specific chromosomal translocations have been described in four pediatric sarcomas belonging to the small round blue cell (SRBC) group of tumors. Identification of mRNA chimeras using RT-PCR discriminates among alveolar rhabdomyosarcoma (ARMS), Ewing's sarcoma (ES/pPNET), synovial sarcoma (SS) and desmoplastic small round cell tumor (DSRCT); however, frequencies of these translocations are variable. We present a retrospective study comparing histological examination and occurrence of major chromosomal translocations to validate the diagnosis and to assess the frequency of these molecular markers in a group of 92 small round blue cell (SRBC) tumor samples from Hospital Infantil de Mexico. METHODS: We tested a panel of RT-PCR assays to each RNA tumor sample from formalin-fixed, paraffin-embedded tumors to detect specific mRNA chimeras in 47 ES/pPNET, 19 ARMS, four SS, three DSRCT, and 19 other SRBC tumors. RESULTS: After excluding poor RNA quality samples, we found translocations in 17/31 ES/pPNET (54.8%), 10/19 ARMS (52.6%), 4/4 SS (100%) and 4/4 DSRCT (100%). We found disagreement in only three samples: one ES/pPNET and one embryonal rhabdomyosarcoma harbor a PAX3-FOXO1 translocation (for ARMS), and one neuroepithelioma harboring a EWS-WT1 (for DSRCT). Unsuitable RNA was found in 20/92 samples (21.7%) and was related to necrosis, small amount of tumor tissue, and use of nitric acid in bone biopsies, but was not related to age of the block. CONCLUSIONS: We found a significantly lower occurrence of chromosomal translocations in ES/pPNET compared to reports from other groups. Differences may exist in the frequencies of these molecular markers among different populations.