Combining functional genomics strategies identifies modular heterogeneity of breast cancer intrinsic subtypes

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.

Identifying the crosstalk of dysfunctional pathways mediated by lncRNAs in breast cancer subtypes

Crosstalk among abnormal pathways widely occurs in human cancer and generally leads to insensitivity to cancer treatment. How long non-coding RNAs (lncRNAs) participate in the regulation of an abnormal pathway crosstalk in human cancer is largely unknown. Here, we proposed a strategy that integrates mRNA and lncRNA expression profiles for systematic identification of lncRNA-mediated crosstalk among risk pathways in different breast cancer subtypes. We identified 12 to 44 crosstalking pathway pairs mediated by 28 to 49 lncRNAs in four breast cancer subtypes. An LncRNA-mediated crosstalking pathway network in each breast cancer subtype was then constructed. We observed a number of breast cancer subtype-specific crosstalks of risk pathways. These subtype-specific lncRNA-mediated pathway crosstalks largely determined subtype-selective functions. Notably, we observed that lncRNAs mediated the crosstalk of pathways by cooperating with known important protein-coding genes, which play core roles in the deterioration of breast cancer. And we also identified key lncRNAs contributing to the crosstalk network in each subtype. As an example, the low expression of LIFR-AS1 was associated with poor survival in LumB subtype, and its cooperated genes IL1R and TGFBR located at the most upstream of the MAPK signaling pathway shared a common cascade path (p38 MAPKs-MEF2C) that can result in proliferation, differentiation and apoptosis. In summary, we offer an effective way to characterize complex crosstalks mediated by lncRNAs in breast cancer subtypes, which can be applied to other diseases and provide useful information for understanding the pathogenesis of human cancer.