On the surface, circular RNA (circRNA) looks like a great candidate for a cancer biomarker. These non-coding RNAs have a closed continuous loop structure and, though less abundant than messenger RNAs (mRNAs) in biofluids, they are highly stable. And that means they can be detected in situations where mRNAs often degrade.
Unfortunately, the two techniques commonly used to profile circRNAs – RNAse R enrichment and ribo-depletion – both have drawbacks. RNase-R enriches circRNAs by degrading linear RNAs, rendering it unsuitable for clinical sequencing. Ribo-depletion preserves both circular and linear RNAs by depleting ribosomal RNA, but requires a large amount (5 μg) of sample to yield reliable results. In search of a more practical solution, a group at Michigan Medicine devised a novel approach using exome capture RNA sequencing.
Arul Chinnaiyan, Director of the Michigan Center for Translational Pathology and S.P. Hicks Professor of Pathology at Michigan Medicine, explains: “By using exome capture sequencing, we achieve overall circRNA enrichment comparable to that of the RNase R method, but still keeps all mRNA information intact.” The new sequencing method needs only a small amount of RNA to pinpoint circRNAs and has already shown its value in identifying prostate cancer-specific circRNAs in urine samples (1). The team analyzed samples from hundreds of tumors and detected large numbers of previously unknown circRNAs, which they added to a new database – MiOncoCirc – to serve as a resource for future study. “Our resource is the first and largest cancer-focused database of circRNAs curated from clinical sequencing. We hope that it will enable researchers to mine for meaningful cancer biomarker candidates.”
Chinnaiyan also hopes that circRNAs, which may be tissue-specific, could be useful as surrogate markers for various types of cancer in future noninvasive tests. “We think this is achievable if we can further refine the list of circRNA candidates and optimize our capture protocol,” he says.
The current design of the team’s capture panel focuses mainly on coding genes, but they are also systematically investigating the ability of non-coding RNAs to form circRNAS. Another promising avenue is to search for circRNAs derived from genomic structural rearrangements, such as gene fusions. With plenty of scope for further research and optimization, will we, one day, see circRNAs running rings around other cancer biomarkers?
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References
- JN Vo et al., “The landscape of circular RNA in cancer”, Cell, 176, 869–881 (2019). PMID: 30735636.
