TY - JOUR
T1 - Comprehensive characterization of circular RNAs in ~ 1000 human cancer cell lines
AU - Ruan, Hang
AU - Xiang, Yu
AU - Ko, Junsuk
AU - Li, Shengli
AU - Jing, Ying
AU - Zhu, Xiaoyu
AU - Ye, Youqiong
AU - Zhang, Zhao
AU - Mills, Tingting
AU - Feng, Jing
AU - Liu, Chun Jie
AU - Jing, Ji
AU - Cao, Jin
AU - Zhou, Bingying
AU - Wang, Li
AU - Zhou, Yubin
AU - Lin, Chunru
AU - Guo, An Yuan
AU - Chen, Xi
AU - Diao, Lixia
AU - Li, Wenbo
AU - Chen, Zhiao
AU - He, Xianghuo
AU - Mills, Gordon B.
AU - Blackburn, Michael R.
AU - Han, Leng
N1 - Funding Information:
This work was supported by the Cancer Prevention and Research Institute of Texas (grant no. RR150085) to CPRIT Scholar in Cancer Research (L.H.). This work was also supported by the Cancer Prevention and Research Institute of Texas (grant no. RP160083) to CPRIT Scholar in Cancer Research (W.L.). This work was also supported by American Heart Association Predoctoral Fellowship (grant no. 18PRE33960076 to J.K.), the Cancer Prevention and Research Institute of Texas (grant no. RP170660 to Y.Z.), the Welch Foundation (grant no. BE-1913 to Y.Z.), the American Cancer Society (grant no. RSG-16-215-01-TBE to Y.Z.), and the National Institutes of Health (grant no. 1R01AR073284-01A1 to T.M., grant no. K22CA204468 to W.L.).
Funding Information:
This work was supported by the Cancer Prevention and Research Institute of Texas (grant no. RR150085) to CPRIT Scholar in Cancer Research (L.H.). This work was also supported by the Cancer Prevention and Research Institute of Texas (grant no. RP160083) to CPRIT Scholar in Cancer Research (W.L.). This work was also supported by American Heart Association Predoctoral Fellowship (grant no. 18PRE33960076 to J.K.), the Cancer Prevention and Research Institute of Texas (grant no. RP170660 to Y.Z.), the Welch Foundation (grant no. BE-1913 to Y.Z.), the American Cancer Society (grant no. RSG-16-215-01-TBE to Y.Z.), and the National Institutes of Health (grant no. 1R01AR073284-01A1 to T.M., grant no. K22CA204468 to W.L.). We thank LeeAnn Chastain for editorial assistance.
Publisher Copyright:
© 2019 The Author(s).
PY - 2019/8/26
Y1 - 2019/8/26
N2 - Background: Human cancer cell lines are fundamental models for cancer research and therapeutic strategy development. However, there is no characterization of circular RNAs (circRNAs) in a large number of cancer cell lines. Methods: Here, we apply four circRNA identification algorithms to heuristically characterize the expression landscape of circRNAs across ~ 1000 human cancer cell lines from CCLE polyA-enriched RNA-seq data. By using integrative analysis and experimental approaches, we explore the expression landscape, biogenesis, functional consequences, and drug response of circRNAs across different cancer lineages. Results: We revealed highly lineage-specific expression patterns of circRNAs, suggesting that circRNAs may be powerful diagnostic and/or prognostic markers in cancer treatment. We also identified key genes involved in circRNA biogenesis and confirmed that TGF-β signaling may promote biogenesis of circRNAs. Strikingly, we showed that clinically actionable genes are more likely to generate circRNAs, potentially due to the enrichment of RNA-binding protein (RBP) binding sites. Among these, circMYC can promote cell proliferation. We observed strong association between the expression of circRNAs and the response to drugs, especially those targeting chromatin histone acetylation. Finally, we developed a user-friendly data portal, CircRNAs in cancer cell lines (CircRiC, https://hanlab.uth.edu/cRic), to benefit the biomedical research community. Conclusions: Our study provides the characterization of circRNAs in cancer cell lines and explored the potential mechanism of circRNA biogenesis as well as its therapeutic implications. We also provide a data portal to facilitate the related biomedical researches.
AB - Background: Human cancer cell lines are fundamental models for cancer research and therapeutic strategy development. However, there is no characterization of circular RNAs (circRNAs) in a large number of cancer cell lines. Methods: Here, we apply four circRNA identification algorithms to heuristically characterize the expression landscape of circRNAs across ~ 1000 human cancer cell lines from CCLE polyA-enriched RNA-seq data. By using integrative analysis and experimental approaches, we explore the expression landscape, biogenesis, functional consequences, and drug response of circRNAs across different cancer lineages. Results: We revealed highly lineage-specific expression patterns of circRNAs, suggesting that circRNAs may be powerful diagnostic and/or prognostic markers in cancer treatment. We also identified key genes involved in circRNA biogenesis and confirmed that TGF-β signaling may promote biogenesis of circRNAs. Strikingly, we showed that clinically actionable genes are more likely to generate circRNAs, potentially due to the enrichment of RNA-binding protein (RBP) binding sites. Among these, circMYC can promote cell proliferation. We observed strong association between the expression of circRNAs and the response to drugs, especially those targeting chromatin histone acetylation. Finally, we developed a user-friendly data portal, CircRNAs in cancer cell lines (CircRiC, https://hanlab.uth.edu/cRic), to benefit the biomedical research community. Conclusions: Our study provides the characterization of circRNAs in cancer cell lines and explored the potential mechanism of circRNA biogenesis as well as its therapeutic implications. We also provide a data portal to facilitate the related biomedical researches.
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U2 - 10.1186/s13073-019-0663-5
DO - 10.1186/s13073-019-0663-5
M3 - Article
C2 - 31446897
AN - SCOPUS:85071640549
SN - 1756-994X
VL - 11
JO - Genome Medicine
JF - Genome Medicine
IS - 1
M1 - 55
ER -