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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Luminal breast cancer-specific circular RNAs uncovered by a novel tool for data analysis
Lucia Coscujuela Tarrero1,2, Giulio Ferrero1,2,3, Valentina Miano1,2
1Center for Molecular Systems Biology, University of Turin, Turin, Italy.
Abstract:
Circular RNAs are highly stable molecules present in all eukaryotes generated by distinct transcript processing. We have exploited poly(A-) RNA-Seq data generated in our lab in MCF-7 breast cancer cells to define a compilation of exonic circRNAs more comprehensive than previously existing lists. Development of a novel computational tool, named CircHunter, allowed us to more accurately characterize circRNAs and to quantitatively evaluate their expression in publicly available RNA-Seq data from breast cancer cell lines and tumor tissues. We observed and confirmed, by ChIP analysis, that exons involved in circularization events display significantly higher levels of the histone post-transcriptional modification H3K36me3 than non-circularizing exons. This result has potential impact on circRNA biogenesis since H3K36me3 has been involved in alternative splicing mechanisms. By analyzing an Ago-HITS-CLIP dataset we also found that circularizing exons overlapped with an unexpectedly higher number of Ago binding sites than non-circularizing exons. Finally, we observed that a subset of MCF-7 circRNAs are specific to tumor versus normal tissue, while others can distinguish Luminal from other tumor subtypes, thus suggesting that circRNAs can be exploited as novel biomarkers and drug targets for breast cancer.
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