The regulatory landscape of retinoblastoma: a pathway analysis perspective.

Retinoblastoma (Rb) is a rare intraocular tumour in early childhood, with an approximate incidence of 1 in 18 000 live births. Experimental studies for Rb are complex due to the challenges associated with obtaining a normal retina to contrast with diseased tissue. In this work, we reanalyse a dataset that contains normal retina samples. We identified the individual genes whose expression is different in Rb in contrast with normal tissue, determined the pathways whose global expression pattern is more distant from the global expression observed in normal tissue, and finally, we identified which transcription factors regulate the highest number of differentially expressed genes (DEGs) and proposed as transcriptional master regulators (TMRs). The enrichment of DEGs in the phototransduction and retrograde endocannabinoid signalling pathways could be associated with abnormal behaviour of the processes leading to cellular differentiation and cellular proliferation. On the other hand, the TMRs nuclear receptor subfamily 5 group A member 2 and hepatocyte nuclear factor 4 gamma are involved in hepatocyte differentiation. Therefore, the enrichment of aberrant expression in these transcription factors could suggest an abnormal retina development that could be involved in Rb origin and progression.

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.