Format

Send to

Choose Destination
Cell. 2019 Feb 7;176(4):869-881.e13. doi: 10.1016/j.cell.2018.12.021.

The Landscape of Circular RNA in Cancer.

Author information

1
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
2
Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Biosciences and Bioengineering, Indian Institute of Technology Dharwad, Dharwad, 580011, India.
3
Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA.
4
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: nesvi@med.umich.edu.
5
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA; Howard Hughes Medical Institute, University of Michigan, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA; Department of Urology, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: arul@umich.edu.

Abstract

Circular RNAs (circRNAs) are an intriguing class of RNA due to their covalently closed structure, high stability, and implicated roles in gene regulation. Here, we used an exome capture RNA sequencing protocol to detect and characterize circRNAs across >2,000 cancer samples. When compared against Ribo-Zero and RNase R, capture sequencing significantly enhanced the enrichment of circRNAs and preserved accurate circular-to-linear ratios. Using capture sequencing, we built the most comprehensive catalog of circRNA species to date: MiOncoCirc, the first database to be composed primarily of circRNAs directly detected in tumor tissues. Using MiOncoCirc, we identified candidate circRNAs to serve as biomarkers for prostate cancer and were able to detect circRNAs in urine. We further detected a novel class of circular transcripts, termed read-through circRNAs, that involved exons originating from different genes. MiOncoCirc will serve as a valuable resource for the development of circRNAs as diagnostic or therapeutic targets across cancer types.

KEYWORDS:

biomarkers; cancer; circRNA; circRNA database; exome capture sequencing; non-coding RNA; read-through transcripts

PMID:
30735636
DOI:
10.1016/j.cell.2018.12.021

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center