Circular RNAs and their associations with breast cancer subtypes

Asha A Nair; Nifang Niu; Xiaojia Tang; Kevin J Thompson; Liewei Wang; Jean-Pierre Kocher; Subbaya Subramanian; Krishna R Kalari

doi:10.18632/oncotarget.13134

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Circular RNAs and their associations with breast cancer subtypes

Journal article

Open access

Peer reviewed

Circular RNAs and their associations with breast cancer subtypes

Asha A Nair, Nifang Niu, Xiaojia Tang, Kevin J Thompson, Liewei Wang, Jean-Pierre Kocher, Subbaya Subramanian and Krishna R Kalari

Oncotarget, Vol.7(49), pp.80967-80979

12/06/2016

DOI: 10.18632/oncotarget.13134

PMCID: PMC5348369

PMID: 27829232

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https://doi.org/10.18632/oncotarget.13134View

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Abstract

Circular RNAs (circRNAs) are highly stable forms of non-coding RNAs with diverse biological functions. They are implicated in modulation of gene expression thus affecting various cellular and disease processes. Based on existing bioinformatics approaches, we developed a comprehensive workflow called Circ-Seq to identify and report expressed circRNAs. Circ-Seq also provides informative genomic annotation along circRNA fused junctions thus allowing prioritization of circRNA candidates. We applied Circ-Seq first to RNA-sequence data from breast cancer cell lines and validated one of the large circRNAs identified. Circ-Seq was then applied to a larger cohort of breast cancer samples (n = 885) provided by The Cancer Genome Atlas (TCGA), including tumors and normal-adjacent tissue samples. Notably, circRNA results reveal that normal-adjacent tissues in estrogen receptor positive (ER+) subtype have relatively higher numbers of circRNAs than tumor samples in TCGA. Similar phenomenon of high circRNA numbers were observed in normal breast-mammary tissues from the Genotype-Tissue Expression (GTEx) project. Finally, we observed that number of circRNAs in normal-adjacent samples of ER+ subtype is inversely correlated to the risk-of-relapse proliferation (ROR-P) score for proliferating genes, suggesting that circRNA frequency may be a marker for cell proliferation in breast cancer. The Circ-Seq workflow will function for both single and multi-threaded compute environments. We believe that Circ-Seq will be a valuable tool to identify circRNAs useful in the diagnosis and treatment of other cancers and complex diseases.

Biomarkers, Tumor - genetics

Biomarkers, Tumor - metabolism

Breast Neoplasms - genetics

Breast Neoplasms - metabolism

Breast Neoplasms - pathology

Cell Proliferation

Computational Biology

Databases, Genetic

Female

Gene Expression Regulation, Neoplastic

Genetic Predisposition to Disease

Humans

MCF-7 Cells

Phenotype

Receptors, Estrogen - metabolism

RNA - genetics

RNA - metabolism

Sequence Analysis, RNA - methods

Workflow

Details

Title: Subtitle: Circular RNAs and their associations with breast cancer subtypes
Creators: Asha A Nair - Mayo Clinic in Florida
Nifang Niu - University of Chicago
Xiaojia Tang - Mayo Clinic in Florida
Kevin J Thompson - Mayo Clinic in Florida
Liewei Wang - Mayo Clinic in Arizona
Jean-Pierre Kocher - Mayo Clinic
Subbaya Subramanian - University of Minnesota
Krishna R Kalari - Mayo Clinic in Florida
Resource Type: Journal article
Publication Details: Oncotarget, Vol.7(49), pp.80967-80979
DOI: 10.18632/oncotarget.13134
PMID: 27829232
PMCID: PMC5348369
NLM abbreviation: Oncotarget
ISSN: 1949-2553
eISSN: 1949-2553
Publisher: Impact Journals LLC
Grant note: P30 CA015083 / NCI NIH HHS
Language: English
Date published: 12/06/2016
Academic Unit: Stead Family Department of Pediatrics; Medical Genetics and Genomics
Record Identifier: 9984701554602771

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