Abstract 2374: Discovering Cis-SAGe chimeric RNAs in prostate cancer

Abstract

Background: Chimeric RNAs, comprising two or more different transcripts from distinct chromosomal regions, are common features in many cancers and play important roles in carcinogenesis. Prostate cancer is the most important non-skin cancer and a leading cause of cancer-related deaths in American men. During the progression of prostate cancer, various fusion transcripts generated as a result of chromosomal rearrangement have been identified. However, we recently reported that a chimeric RNA SLC45A3-ELK4 was generated in the absence of DNA rearrangement by cis-splicing of adjacent genes(Cis-SAGe)/read-through. CCCTC-binding factor (CTCF) acts as chromatin barrier, with CTCF binding at boundaries between the two parental genes, SLA45A3 and ELK4 to prevent the Cis-SAGe events in normal prostate cells. On the other hand, silencing CTCF resulted in an induction of the fusion RNA expression. These findings promoted us to manipulate CTCF level in combination with deep RNA sequencing (RNA-seq) to discover more Cis-SAGe fusions. Methods: To identify more Cis-SAGe chimeric RNAs in prostate cancer, we sequenced LNCaP cells transfected with negative control siRNA and siRNA against CTCF. The samples were processed in two different companies using Illumina Hi-seq platform to generate two output sequences: paired-end 50-nucleotide and 101-nucleotide reads. SOAPfuse (BGI, China) software was used to identify chimeric RNAs. To filter out non Cis-SAGe events, we required all the candidates to have the features: induced by siCTCF; neighboring parental genes; same transcribing direction; CTCF binding sites at gene boundaries. Majority of the fusions were validated with real-time PCR and Sanger sequencing. Results: Using SOAPfuse, we identified 95 chimeric RNAs from the combined 50- and 100-bp paired RNA sequencing data. For all 95 candidates, 56 are intra-chromosomal same strand neighboring gene fusions, 13 inter-chromosomal, and 26 other intra-chromosomal fusions. We considered the 56 (from 48 pairs of unique parental genes) to be candidates for Cis-SAGe. qPCR results showed 25 candidates were up-regulated more than 2 folds by knocking down CTCF and 4 candidates were down-regulated. Sanger sequencing confirmed 22 out of the 25 candidates. Intergenic transcripts for all these 22 candidates were detected, supporting that these chimeric transcripts could be products of Cis-SAGe. To evaluate their differential expression in cancers vs. benign tissues, we compared the RNA expression of these candidates in LNCaP, PC-3, another prostate cancer cell line and RWPE-1, a benign prostate cell line. Most of the verified chimeric RNAs appeared to be highly expressed in all three cell lines. Four chimeric RNAs are expressed only in the cancer cells, one fusion transcript detected only in RWPE-1 and four other fusions only present in LNCaP cells. Together, our results suggest that many more Cis-SAGe chimeric RNAs are expressed in prostate cancer and they may represent a unique class of bio-markers. Citation Format: Fujun Qin, Yansu Song, Henry F. Frierson, Hui Li. Discovering Cis-SAGe chimeric RNAs in prostate cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2374. doi:10.1158/1538-7445.AM2014-2374

MetaFusion: A high-confidence metacaller for filtering and prioritizing RNA-seq gene fusion candidates

“…Cis-SAGe fusions such as ReadThroughs are often considered a part of normal biology or transcriptional noise (Babiceanu et al 2016; Tang et al 2017) and many tools remove them, prioritizing CodingFusions. Yet some cis-SAGe fusions are translated into fusion proteins, and may occur uniquely in certain types of cancer and serve as disease biomarkers (Varley et al 2014; Qin et al 2014, 2016; Rickman et al 2009). Instead of discarding these fusion calls, MetaFusion stores them in a separate cis-SAGe .…”

MetaFusion: a high-confidence metacaller for filtering and prioritizing RNA-seq gene fusion candidates

“…Cis-SAGe fusions such as ReadThroughs are often considered a part of normal biology or transcriptional noise (Babiceanu et al 2016;Tang et al 2017) and many tools remove them, prioritizing CodingFusions. Yet some cis-SAGe fusions are translated into fusion proteins, and may occur uniquely in certain types of cancer and serve as disease biomarkers (Varley et al 2014;Qin et al 2014Qin et al , 2016Rickman et al 2009). Instead of discarding these fusion calls, MetaFusion stores them in a separate cis-SAGe.cluster file that can be used for downstream analysis (see Methods, Figure 1).…”