Colorectal cancer (CRC) is one of the most common cancer types, ranking third after lung and breast cancers. As such, it demands special attention for better characterization, which may eventually result in the development of early detection strategies and preventive measures. Currently, components of bodily fluids, which may reflect various disease states, are being increasingly researched for their biomarker potential. One of these components is the circulating extracellular vesicles, namely, exosomes, which are demonstrated to carry various cargo. Of importance, the non-coding RNA cargo of circulating exosomes, especially long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and micro RNAs (miRNAs), may potentially serve as significant diagnostic and prognostic/predictive biomarkers. In this review, we present existing evidence on the diagnostic and prognostic/predictive biomarker value of exosomal non-coding RNAs in CRC. In addition, taking advantage of the miRNA sponging functionality of lncRNAs and circRNAs, we demonstrate an experimentally validated CRC exosomal non-coding RNA-regulated target gene axis benefiting from published miRNA sponging studies in CRC. Hence, we present a set of target genes and pathways downstream of the lncRNA/circRNA–miRNA–target axis along with associated significant Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, which may collectively serve to better characterize CRC and shed light on the significance of exosomal non-coding RNAs in CRC diagnosis and prognosis/prediction.

Pediatric pineoblastomas (PBs) are rare and aggressive tumors of grade IV histology. Although some oncogenic drivers are characterized, including germline mutations inRB1andDICER1, the role of epigenetic deregulation andcis-regulatory regions in PB pathogenesis and progression is largely unknown. Here, we generated genome-wide gene expression, chromatin accessibility, and H3K27ac profiles covering key time-points of PB initiation and progression from pineal tissues of a mouse model ofCcnd1-driven pineoblastoma. We identified PB-specific enhancers and super-enhancers and found that, in some cases, the accessible genome dynamic precedes the transcriptome, a characteristic that is underexplored in tumor progression. During progression of PB, newly acquired open chromatin regions lacking H3K27ac signal become enriched for repressive state elements and harbor motifs of repressor transcription factors like HINFP, GLI2, and YY1. Copy number variant analysis identified deletion events specific to the tumorigenic stage, affecting among others the histone genes cluster andGas1, the growth arrest specific gene. Gene set enrichment analysis and gene expression signatures positioned the model used here close to human PB samples demonstrating the potential of our findings for exploring new avenues in PB management and therapy. Overall, this study reports the first temporal and in vivocis-regulatory, expression, and accessibility maps in PB.

Background Finding combinations of homotypic or heterotypic genomic sites obeying a specific grammar in DNA sequences is a frequent task in bioinformatics. A typical case corresponds to the identification of cis-regulatory modules characterized by a combination of transcription factor binding sites in a defined window size. Although previous studies identified clusters of genomic sites in species with varying genome sizes, the availability of a dedicated and versatile tool to search for such clusters is lacking. Results We present fcScan, an R/Bioconductor package to search for clusters of genomic sites based on user defined criteria including cluster size, inter-cluster distances and sites order and orientation allowing users to adapt their search criteria to specific biological questions. It supports GRanges, data frame and VCF/BED files as input and returns data in GRanges format. By performing clustering on vectorized data, fcScan is adapted to search for genomic clusters in millions of sites as input in short time and is thus ideal to scan data generated by high throughput methods including next generation sequencing. Conclusions fcScan is ideal for detecting cis-regulatory modules of transcription factor binding sites with a specific grammar as well as genomic loci enriched for mutations. The flexibility in input parameters allows users to perform searches targeting specific research questions. It is released under Artistic-2.0 License. The source code is freely available through Bioconductor (https://bioconductor.org/packages/fcScan) and GitHub (https://github.com/pkhoueiry/fcScan).

Introduction Glioblastoma (GBM) is an aggressive brain tumor associated with high degree of resistance to treatment. Given its heterogeneity, it is important to understand the molecular landscape of this tumor for the development of more effective therapies. Because of the different genetic profiles of patients with GBM, we sought to identify genetic variants in Lebanese patients with GBM (LEB-GBM) and compare our findings to those in the Cancer Genome Atlas (TCGA). Methods We performed whole exome sequencing (WES) to identify somatic variants in a cohort of 60 patient-derived GBM samples. We focused our analysis on 50 commonly mutated GBM candidate genes and compared mutation signatures between our population and publicly available GBM data from TCGA. We also cross-tabulated biological covariates to assess for associations with overall survival, time to recurrence and follow-up duration. Results We included 60 patient-derived GBM samples from 37 males and 23 females, with age ranging from 3 to 80 years (mean and median age at diagnosis were 51 and 56, respectively). Recurrent tumor formation was present in 94.8% of patients (n = 55/58). After filtering, we identified 360 somatic variants from 60 GBM patient samples. After filtering, we identified 360 somatic variants from 60 GBM patient samples. Most frequently mutated genes in our samples included ATRX, PCDHX11, PTEN, TP53, NF1, EGFR, PIK3CA, and SCN9A. Mutations in NLRP5 were associated with decreased overall survival among the Lebanese GBM cohort (p = 0.002). Mutations in NLRP5 were associated with decreased overall survival among the Lebanese GBM cohort (p = 0.002). EGFR and NF1 mutations were associated with the frontal lobe and temporal lobe in our LEB-GBM cohort, respectively. Conclusions Our WES analysis confirmed the similarity in mutation signature of the LEB-GBM population with TCGA cohorts. It showed that 1 out of the 50 commonly GBM candidate gene mutations is associated with decreased overall survival among the Lebanese cohort. This study also highlights the need for studies with larger sample sizes to inform clinicians for better prognostication and management of Lebanese patients with GBM.

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