Circular RNAs and their associations with breast cancer subtypes.
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.
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Asha A
AA
Nair
Division of Genomic and Molecular Pathology, University of Chicago, Chicago, IL, USA.
Nifang
N
Niu
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Xiaojia
X
Tang
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Kevin J
KJ
Thompson
Department of Pharmacology, Mayo Clinic, Rochester, MN, USA.
Liewei
L
Wang
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Jean-Pierre
JP
Kocher
Division of Basic and Translational Research, University of Minnesota, Minneapolis, MN, USA.
Subbaya
S
Subramanian
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
Krishna R
KR
Kalari
D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D001943:Breast Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D049109:Cell Proliferation; D019295:Computational Biology; D030541:Databases, Genetic; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D020022:Genetic Predisposition to Disease; D006801:Humans; D061986:MCF-7 Cells; D010641:Phenotype; D012313:RNA / Q000235:genetics* / Q000378:metabolism; D000079962:RNA, Circular; D011960:Receptors, Estrogen / Q000378:metabolism; D017423:Sequence Analysis, RNA / Q000379:methods*; D057188:Workflow
D014408:Biomarkers, Tumor; D000079962:RNA, Circular; D011960:Receptors, Estrogen; D012313:RNA
breast cancer; circ-seq; circular RNA; molecular subtypes; proliferation