journal contribution
posted on 2023-10-13, 07:20 authored by Juan L. García-Rodríguez, Ulrik Korsgaard, Ulvi Ahmadov, Morten T. Jarlstad Olesen, Kim-Gwendolyn Dietrich, Emma B. Hansen, Stine M. Vissing, Benedichte P. Ulhøi, Lars Dyrskjøt, Karina D. Sørensen, Jørgen Kjems, Henrik Hager, Lasse S. Kristensen Evaluation of the most abudant circRNAs from human datasets. Boxplot showing the normalized
nCounter counts from the top 50 circRNAs extracted from publicly available human RNAseq datasets (2 normal colon, 1 tumor and paired normal adjacent tissue) (GSE77661) (A) and from the top 20 high-abundance circRNAs according to the data extracted from the three different microarray datasets comparing human tumor vs paired normal tisues (GSE126094,
GSE142837 and GSE138589) (B). C, NanoString nCounter analysis of 48 circRNA and 7 mRNA in mock and RNase R treated RNA samples from the Caco-2 cell line. Among the 48 circRNAs only 37 were expressed above cutoff levels in this cell line. D, Sanger sequencing across the backsplicing junction of the 3 circRNAs that haven't been described before. The scattered horizontal lines represent the background threshold. The box represents the interquartile range (Q1 and Q3), the median is marked with horizontral line, and whiskers represent m and maximum values.
Funding
Lundbeck Foundation (Lundbeckfonden)
Riisfort Fonden (Riisfort Foundation)
Magda Sofie and Aase Lutz's Mindelegat (Fond)
Novo Nordisk Fonden (NNF)
The Danish Cancer Society
Dansk Kraeftforskningsfond
Koebmand i Odense Johann og Hanne Weimann Foedt Seedorffs
History
ARTICLE ABSTRACT
Circular RNAs (circRNA) are covalently closed molecules that can play important roles in cancer development and progression. Hundreds of differentially expressed circRNAs between tumors and adjacent normal tissues have been identified in studies using RNA sequencing or microarrays, emphasizing a strong translational potential. Most previous studies have been performed using RNA from bulk tissues and lack information on the spatial expression patterns of circRNAs. Here, we showed that the majority of differentially expressed circRNAs from bulk tissue analyses of colon tumors relative to adjacent normal tissues were surprisingly not differentially expressed when comparing cancer cells directly with normal epithelial cells. Manipulating the proliferation rates of cells grown in culture revealed that these discrepancies were explained by circRNAs accumulating to high levels in quiescent muscle cells due to their high stability; on the contrary, circRNAs were diluted to low levels in the fast-proliferating cancer cells due to their slow biogenesis rates. Thus, different subcompartments of colon tumors and adjacent normal tissues exhibited striking differences in circRNA expression patterns. Likewise, the high circRNA content in muscle cells was also a strong confounding factor in bulk analyses of circRNAs in bladder and prostate cancers. Together, these findings emphasize the limitations of using bulk tissues for studying differential circRNA expression in cancer and highlight a particular need for spatial analysis in this field of research.
The abundance of circRNAs varies systematically between subcompartments of solid tumors and adjacent tissues, implying that differentially expressed circRNAs discovered in bulk tissue analyses may reflect differences in cell type composition between samples.
