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A combined computational pipeline to detect circular RNAs in human cancer cells under hypoxic stress

Di Liddo, Antonella ; de Oliveira Freitas Machado, Camila ; Fischer, Sandra ; Ebersberger, Stefanie ; Heumüller, Andreas W. ; Weigand, Julia E. ; Müller-McNicoll, Michaela ; Zarnack, Kathi (2019)
A combined computational pipeline to detect circular RNAs in human cancer cells under hypoxic stress.
In: Journal of molecular cell biology, 11 (10)
doi: 10.1093/jmcb/mjz094
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

Hypoxia is associated with several diseases, including cancer. Cells that are deprived of adequate oxygen supply trigger transcriptional and post-transcriptional responses, which control cellular pathways such as angiogenesis, proliferation, and metabolic adaptation. Circular RNAs (circRNAs) are a novel class of mainly non-coding RNAs, which have been implicated in multiple cancers and attract increasing attention as potential biomarkers. Here, we characterize the circRNA signatures of three different cancer cell lines from cervical (HeLa), breast (MCF-7), and lung (A549) cancer under hypoxia. In order to reliably detect circRNAs, we integrate available tools with custom approaches for quantification and statistical analysis. Using this consolidated computational pipeline, we identify ~12000 circRNAs in the three cancer cell lines. Their molecular characteristics point to an involvement of complementary RNA sequences as well as trans-acting factors in circRNA biogenesis, such as the RNA-binding protein HNRNPC. Notably, we detect a number of circRNAs that are more abundant than their linear counterparts. In addition, 64 circRNAs significantly change in abundance upon hypoxia, in most cases in a cell type-specific manner. In summary, we present a comparative circRNA profiling in human cancer cell lines, which promises novel insights into the biogenesis and function of circRNAs under hypoxic stress.

Typ des Eintrags: Artikel
Erschienen: 2019
Autor(en): Di Liddo, Antonella ; de Oliveira Freitas Machado, Camila ; Fischer, Sandra ; Ebersberger, Stefanie ; Heumüller, Andreas W. ; Weigand, Julia E. ; Müller-McNicoll, Michaela ; Zarnack, Kathi
Art des Eintrags: Bibliographie
Titel: A combined computational pipeline to detect circular RNAs in human cancer cells under hypoxic stress
Sprache: Englisch
Publikationsjahr: 27 September 2019
Verlag: Oxford Academic
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Journal of molecular cell biology
Jahrgang/Volume einer Zeitschrift: 11
(Heft-)Nummer: 10
DOI: 10.1093/jmcb/mjz094
URL / URN: https://academic.oup.com/jmcb/article/11/10/829/5575096
Kurzbeschreibung (Abstract):

Hypoxia is associated with several diseases, including cancer. Cells that are deprived of adequate oxygen supply trigger transcriptional and post-transcriptional responses, which control cellular pathways such as angiogenesis, proliferation, and metabolic adaptation. Circular RNAs (circRNAs) are a novel class of mainly non-coding RNAs, which have been implicated in multiple cancers and attract increasing attention as potential biomarkers. Here, we characterize the circRNA signatures of three different cancer cell lines from cervical (HeLa), breast (MCF-7), and lung (A549) cancer under hypoxia. In order to reliably detect circRNAs, we integrate available tools with custom approaches for quantification and statistical analysis. Using this consolidated computational pipeline, we identify ~12000 circRNAs in the three cancer cell lines. Their molecular characteristics point to an involvement of complementary RNA sequences as well as trans-acting factors in circRNA biogenesis, such as the RNA-binding protein HNRNPC. Notably, we detect a number of circRNAs that are more abundant than their linear counterparts. In addition, 64 circRNAs significantly change in abundance upon hypoxia, in most cases in a cell type-specific manner. In summary, we present a comparative circRNA profiling in human cancer cell lines, which promises novel insights into the biogenesis and function of circRNAs under hypoxic stress.

ID-Nummer: pmid:31560396
Fachbereich(e)/-gebiet(e): 10 Fachbereich Biologie
10 Fachbereich Biologie > RNA Biochemie
Hinterlegungsdatum: 05 Mär 2021 08:08
Letzte Änderung: 05 Mär 2021 08:08
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