Dataset Information

A peptide CORO1C-47aa encoded by circ-0000437 functions as a negative regulator in endometrium tumor angiogenesis

ABSTRACT: Circular RNAs (circRNA) are a novel class of widespread non-coding RNAs (ncRNAs) that regulate gene expression in mammals. Recent studies demonstrate that functional peptides can be encoded by short open reading frames (sORFs) in ncRNAs, including circRNAs. In this study, through deep RNA sequencing on human endometrial cancer (EC) samples and their paired adjacent normal tissues, we uncovered that the circRNA hsa-circ-0000437 is significantly reduced in EC compared to matched paracancerous tissue. The hsa-circ-0000437 contains a sORF encoding a functional peptide termed as CORO1C-47aa. Overexpression of CORO1C-47aa is capable of inhibiting angiogenesis at the initiation stage by suppressing endothelial cell proliferation, migration, and differentiation through competing with TACC3 to bind to ARNT and suppress VEGF. The anti-tumor effects of CORO1C-47aa on EC progression suggest that CORO1C-47aa has a potential value in anti-carcinoma therapies and deserves further investigation.

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: fang li

LAB HEAD: fang li

PROVIDER: PXD026046 | Pride | 2022-02-17

REPOSITORIES: Pride

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A peptide CORO1C-47aa encoded by the circular noncoding RNA circ-0000437 functions as a negative regulator in endometrium tumor angiogenesis.

Li Fang F Cai Yuhan Y Deng Sihan S Yang Lin L Liu Na N Chang Xiaohan X Jing Lankai L Zhou Yifeng Y Li Hua H

The Journal of biological chemistry 20210914 5

Circular RNAs (circRNAs) are a novel class of widespread noncoding RNAs that regulate gene expression in mammals. Recent studies demonstrate that functional peptides can be encoded by short open reading frames in noncoding RNAs, including circRNAs. However, the role of circRNAs in various physiological and pathological states, such as cancer, is not well understood. In this study, through deep RNA sequencing on human endometrial cancer (EC) samples and their paired adjacent normal tissues, we un ...[more]

PMID: 34534547

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Project description:In platelets, splicing and translation occur in the absence of a nucleus. However, the integrity and stability of mRNAs derived from megakaryocyte progenitor cells remain poorly quantified on a transcriptome-wide level. As circular RNAs (circRNAs) are resistant to degradation by exonucleases, their abundance relative to linear RNAs can be used as a surrogate marker for mRNA stability in the absence of transcription. Here we show that circRNAs are enriched in human platelets 17-188 fold relative to nucleated tissues, and 14-26 fold relative to samples digested with RNAseR to selectively remove linear RNA. We compare RNAseq read depths inside and outside circRNAs to provide in silico evidence of transcript circularity, show that exons within circRNAs are enriched ~13X in platelets relative to nucleated tissues, and identify 3162 genes significantly enriched for circRNAs including some where all RNAs appear to be derived from circular molecules. We also confirm that this is a feature of other anucleate cells through transcriptome sequencing of mature erythrocytes, demonstrate that circRNAs are not enriched in megakaryocytes, and that linear RNAs decay more rapidly than circRNAs in platelet preparations. Collectively, these results suggest that circulating platelets have lost on aveage over 90% of their progenitor mRNAs, and that translation in platelets occurrs against the backdrop of a highly degraded transcriptome. Finally, we find that transcripts classified as products of reverse transcriptase template switching are both enriched in platelets and resistant to decay, countering the recent suggestion that up to 50% of rearranged RNAs are artefacts. A single rRNA depleted total RNA sample was sequenced. This together with 25 publicly available rRNA depleted total RNA samples (including 3 from platelets) were analysed using PTESFinder v 1 (http://sourceforge.net/projects/ptesfinder-v1/) to identify back-splice junctions, characteristic of circRNA transcripts. The contribution of circRNA producing exons was analysed on a gene by gene basis as follows: All circRNA transcripts identified in any sample were first pooled to define exons which can contribute to circRNA generation using custom scripts (available on request). For each sample, expression estimates (RPKMI) across all circRNA producing exons were computed for each locus using the total size of exons (in bp) and the read counts mapping to them. Similarly, total size and exonic read counts for exons for which no circRNA were detected in any sample were used to compute expression estimates (RPKME) for non-circRNA producing exons for each locus. Abundance ratios (RPKMI/RPKME and RPKMI/RPKMI+RPKME) were calculated and compared between Platelets and human tissues using Wilcoxon signed-rank test. Please note that the '25sample_info_accn_no.txt' contains the accession numbers and tissue/cell type information for 25 samples analyzed together.

			Action	DRS
	HA-HEC-1-B.msf	Msf
	HA-HEC-1-B.raw	Raw
	HA-Ishikawa.msf	Msf
	HA-Ishikawa.raw	Raw
	IGG-Ishikawa.raw	Raw