Subtype and cell type specific expression of lncRNAs provide insight into breast cancer.

Long non-coding RNAs (lncRNAs) are involved in breast cancer pathogenesis through chromatin remodeling, transcriptional and post-transcriptional gene regulation. We report robust associations between lncRNA expression and breast cancer clinicopathological features in two population-based cohorts: SCAN-B and TCGA. Using co-expression analysis of lncRNAs with protein coding genes, we discovered three distinct clusters of lncRNAs. In silico cell type deconvolution coupled with single-cell RNA-seq analyses revealed that these three clusters were driven by cell type specific expression of lncRNAs. In one cluster lncRNAs were expressed by cancer cells and were mostly associated with the estrogen signaling pathways. In the two other clusters, lncRNAs were expressed either by immune cells or fibroblasts of the tumor microenvironment. To further investigate the cis-regulatory regions driving lncRNA expression in breast cancer, we identified subtype-specific transcription factor (TF) occupancy at lncRNA promoters. We also integrated lncRNA expression with DNA methylation data to identify long-range regulatory regions for lncRNA which were validated using ChiA-Pet-Pol2 loops. lncRNAs play an important role in shaping the gene regulatory landscape in breast cancer. We provide a detailed subtype and cell type-specific expression of lncRNA, which improves the understanding of underlying transcriptional regulation in breast cancer.

The expression of the long NEAT1_2 isoform is associated with human epidermal growth factor receptor 2-positive breast cancers.

The long non-coding RNA NEAT1 locus is transcribed into two overlapping isoforms, NEAT1_1 and NEAT1_2, of which the latter is essential for the assembly of nuclear paraspeckles. NEAT1 is abnormally expressed in a wide variety of human cancers. Emerging evidence suggests that the two isoforms have distinct functions in gene expression regulation, and recently it was shown that NEAT1_2, but not NEAT1_1, expression predicts poor clinical outcome in cancer. Here, we report that NEAT1_2 expression correlates with HER2-positive breast cancers and high-grade disease. We provide evidence that NEAT1_1 and NEAT1_2 have distinct expression pattern among different intrinsic breast cancer subtypes. Finally, we show that NEAT1_2 expression and paraspeckle formation increase upon lactation in humans, confirming what has previously been demonstrated in mice.

Widespread alternative exon usage in clinically distinct subtypes of Invasive Ductal Carcinoma.

Cancer cells can have different patterns of exon usage of individual genes when compared to normal tissue, suggesting that alternative splicing may play a role in shaping the tumor phenotype. The discovery and identification of gene variants has increased dramatically with the introduction of RNA-sequencing technology, which enables whole transcriptome analysis of known, as well as novel isoforms. Here we report alternative splicing and transcriptional events among subtypes of invasive ductal carcinoma in The Cancer Genome Atlas (TCGA) Breast Invasive Carcinoma (BRCA) cohort. Alternative exon usage was widespread, and although common events were shared among three subtypes, ER+ HER2-, ER- HER2-, and HER2+, many events on the exon level were subtype specific. Additional RNA-seq analysis was carried out in an independent cohort of 43 ER+ HER2- and ER- HER2- primary breast tumors, confirming many of the exon events identified in the TCGA cohort. Alternative splicing and transcriptional events detected in five genes, MYO6, EPB41L1, TPD52, IQCG, and ACOX2 were validated by qRT-PCR in a third cohort of 40 ER+ HER2- and ER- HER2- patients, showing that these events were truly subtype specific.

Expression of an estrogen-regulated variant transcript of the peroxisomal branched chain fatty acid oxidase ACOX2 in breast carcinomas.

BACKGROUND: Alternate transcripts from a single gene locus greatly enhance the combinatorial flexibility of the human transcriptome. Different patterns of exon usage have been observed when comparing normal tissue to cancers, suggesting that variant transcripts may play a role in the tumor phenotype. METHODS: Ribonucleic acid-sequencing (RNA-seq) data from breast cancer samples was used to identify an intronic start variant transcript of Acyl-CoA oxidase 2, ACOX2 (ACOX2-i9). Difference in expression between Estrogen Receptor (ER) positive and ER negative patients was assessed by the Wilcoxon rank sum test, and the findings validated in The Cancer Genome Atlas (TCGA) breast cancer dataset (BRCA). ACOX2-i9 expression was also assessed in cell lines using both quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) and Western blot analysis. Knock down by short hairpin RNA (shRNA) and colony formation assays were used to determine whether ACOX2-i9 expression would influence cellular fitness. The effect of ACOX2-i9 expression on patient survival was assessed by the Kaplan-Meier survival function, and association to clinical parameters was analyzed using a Fisher exact test. RESULTS: The expression and translation of ACOX2-i9 into a 25 kDa protein was demonstrated in HepG2 cells as well as in several breast cancer cell lines. shRNA knock down of the ACOX2-i9 variant resulted in decreased cell viability of T47D and MDA-MB 436 cells. Moreover, expression of ACOX2-i9 was shown to be estrogen regulated, being induced by propyl pyrazoletriol and inhibited by tamoxifen and fulvestrant in ER+ T47D and Mcf-7 cells, but not in the ER- MDA-MB 436 cell line. This variant transcript showed expression predominantly in ER-positive breast tumors as assessed in our initial set of 53 breast cancers and further validated in 87 tumor/normal pairs from the TCGA breast cancer dataset, and expression was associated with better outcome in ER positive patients. CONCLUSIONS: ACOX2-i9 is specifically enriched in ER+ breast cancers where expression of the variant is associated with improved outcome. These data identify variant ACOX2 as a potential novel therapeutic biomarker in ER+ breast tumors.