Biology subjects

Flemington, E. K.

Publications and source records attributed to Flemington, E. K..

3 recordsLinked to original sources

bioRxiv2026

SON-mediated circular RNA suppression promotes PKR signaling and radiation resistance in glioblastoma

Glioblastoma (GBM) exhibits extensive loss of circular RNAs (circRNAs), yet the mechanisms driving this depletion and its functional consequences remain unclear. Here, we identify the splicing co-factor SON as a previously unrecognized suppressor of circRNA biogenesis in GBM. CircRNA sequencing revealed widespread increases in circRNA abundance following SON knockdown. Conversely, elevated SON expression in GBM, with further increases in radiation-resistant models, was associated with widespread circRNA loss, including reduced expression of circUSP1 and circSUCO. SON knockdown increased circRNA abundance and attenuated activation of the dsRNA-responsive kinase PKR and downstream NF{kappa}B signaling, whereas radiation-resistant GBM cells exhibited enhanced PKR/NF{kappa}B activation that was attenuated by SON depletion. Importantly, overexpression of the SON-suppressed circRNAs circUSP1 and circSUCO reduced PKR activation and selectively decreased clonogenic survival following irradiation in radiation-resistant GBM cells, with little effect on parental cells. Together, these findings identify a previously unrecognized SON/circRNA/PKR regulatory pathway linking RNA processing to acquired radiation resistance in GBM and highlight specific PKR-inhibitory circRNAs as potential therapeutic tools for resensitizing radiation-resistant GBM to radiotherapy.

cancer biology↗

bioRxiv2020

EBV miRNAs are potent effectors of tumor cell transcriptome remodeling in promoting immune escape.

Epstein Barr virus (EBV) contributes to the tumor phenotype through a limited set of primarily non-coding viral RNAs, including 31 mature miRNAs. Here we investigated the impact of EBV miRNAs on remodeling the tumor cell transcriptome. Strikingly, EBV miRNAs displayed exceptionally abundant expression in primary EBV-associated Burkitts Lymphomas (BLs) and Gastric Carcinomas (GCs). To investigate viral miRNA targeting, we used the high-resolution approach, CLASH in GC and a BL cell models. Affinity constant calculations of targeting efficacies for CLASH hits showed that viral miRNAs bind their targets more effectively than their host counterparts, as did Kaposis sarcoma-associated herpesvirus (KSHV) and murine gammaherpesvirus 68 (MHV68) miRNAs. Using public BL and GC RNA-seq datasets, we found that high EBV miRNA targeting efficacies translates to enhanced reduction of target expression. Pathway analysis of high efficacy EBV miRNA targets showed enrichment for innate and adaptive immune responses. Inhibition of the immune response by EBV miRNAs was functionally validated in vivo through the finding of inverse correlations between EBV miRNAs and immune cell infiltration and T-cell diversity in TCGA GC dataset. Together, this study demonstrates that EBV miRNAs are potent effectors of the tumor transcriptome that play a role in suppressing the host immune response. AUTHOR SUMMARYBurkitts Lymphoma and gastric cancer are both associated with EBV, a prolific DNA tumor virus that latently resides in nearly all human beings. Despite mostly restricting viral gene expression to noncoding RNAs, EBV has important influences on the fitness of infected tumor cells. Here, we show that the miRNA class of viral noncoding RNAs are a major viral contributor to remodeling the tumor cell regulatory machinery in patient tumor samples. First, an assessment of miRNA expression in clinical tumor samples showed that EBV miRNAs are expressed at unexpectedly high levels relative to cell miRNAs. Using a highly specific miRNA target identification approach, CLASH, we comprehensively identified both viral and cellular microRNA targets and the relative abundance of each microRNA-mRNA interaction. We also show that viral microRNAs bind to and alter the expression of their mRNA targets more effectively than their cellular microRNA counterparts. Pathway analysis of the most effectively targeted mRNAs revealed enrichment of immune signaling pathways and we show a corresponding inverse correlation between EBV miRNA expression and infiltrating immune cells in EBV positive primary tumors. Altogether, this study shows that EBV miRNAs are key regulators of the tumor cell phenotype and the immune cell microenvironment.

cancer biology↗

bioRxiv2019

SpliceV: Analysis and publication quality printing of linear and circular RNA splicing, expression and regulation.

In eukaryotes, most genes code for multiple transcript isoforms that are generated through the complex and tightly regulated process of RNA splicing. Despite arising from identical precursor transcripts, alternatively spliced RNAs can have dramatically different functions. Transcriptome complexity is elevated further by the production of circular RNAs (circRNAs), another class of mature RNA that results from the splicing of a downstream splice donor to an upstream splice acceptor. While there has been a rapid expansion of circRNA catalogs in the last few years through the utilization of next generation sequencing approaches, our understanding of the mechanisms and regulation of circular RNA biogenesis, the impact that circRNA generation has on parental transcript processing, and the functions carried out by circular RNAs remains limited. Here, we present a visualization and analysis tool, SpliceV, that rapidly plots all relevant forward-and back-splice data, with exon and single nucleotide level coverage information from RNA-seq experiments in a publication quality format. SpliceV also integrates analysis features that assist investigations into splicing regulation and transcript functions through the display of predicted RNA binding protein sites and the configuration of repetitive elements along the primary transcript. SpliceV is compatible with both Python 2.7 and 3+, and is distributed under the GNU Public License. The source code is freely available for download at https://github.com/flemingtonlab/SpliceV and can be installed from PyPI using pip.

bioinformatics↗