Circular RNAs and their associations with breast cancer subtypes.
Circular RNAs and their associations with breast cancer subtypes.
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DOI：
10.18632/oncotarget.13134
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发表时间：
2016-12-06
期刊：
影响因子：
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通讯作者：
Kalari KR
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作者：
Nair AA;Niu N;Tang X;Thompson KJ;Wang L;Kocher JP;Subramanian S;Kalari KR
环状RNA（CircRNA）是一类高度稳定的非编码RNA，具有多种生物学功能。它们涉及基因表达的调节，从而影响各种细胞和疾病过程。基于现有的生物信息学方法，我们开发了一个名为Circ-Seq的综合工作流程来识别和报告表达的circRNA。Circ-Seq还提供沿沿着circRNA融合连接的信息性基因组注释，从而允许对circRNA候选物进行优先化。我们首先将Circ-Seq应用于来自乳腺癌细胞系的RNA序列数据，并验证了所鉴定的大circRNA之一。然后将Circ-Seq应用于由癌症基因组图谱（TCGA）提供的更大的乳腺癌样本队列（n = 885），包括肿瘤和正常相邻组织样本。值得注意的是，circRNA结果揭示，雌激素受体阳性（ER+）亚型的正常邻近组织具有比TCGA中的肿瘤样品相对更高数量的circRNA。在来自基因型-组织表达（GTEx）项目的正常乳房-乳腺组织中观察到高circRNA数目的类似现象。最后，我们观察到ER+亚型正常相邻样本中的circRNA数量与增殖基因的复发增殖风险（ROR-P）评分呈负相关，表明circRNA频率可能是乳腺癌细胞增殖的标志物。Circ-Seq工作流程将在单线程和多线程计算环境中发挥作用。我们相信，Circ-Seq将成为一种有价值的工具，用于识别可用于诊断和治疗其他癌症和复杂疾病的circRNA。
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.