Abstract
Circular RNAs (circRNAs) are covalently closed endogenous molecules with tissue- and disease-specific expression patterns, which have potential as diagnostic and prognostic biomarkers in cancer. The molecules are formed by a backsplicing event linking the 3′-end of an exon to the 5′-end of the same or an upstream exon, and they exert diverse regulatory functions important in carcinogenesis. The landscape of circRNA expression has not been characterized in B-cell malignancies, and current methods for circRNA quantification have several limitations that prevent development of clinically applicable assays. Here, we demonstrate that circRNAs can be accurately quantified without enzymatic reactions or bias using color-coded probes (NanoString technology). First, we performed high-throughput RNA sequencing (RNA-seq) of several mantle cell lymphoma and multiple myeloma cell lines to profile the genome-wide landscape of circRNA expression. We detected several circRNAs known to be deregulated in other cancers and identified a novel circRNA from the IKZF3 gene. Based on these data, we selected 52 unique circRNAs for which we designed color-coded probes spanning their specific backsplicing junctions. These circRNAs were quantified in cell lines and patient samples from several different B-cell malignancies (mantle cell lymphoma, multiple myeloma, follicular lymphoma, diffuse large B-cell lymphoma, Burkitt lymphoma and chronic lymphocytic leukemia) simultaneously using the NanoString technology. The circRNA expression profiles obtained could distinguish different B-cell malignancies, and confirmed the presence of the novel circRNA derived from IKZF3. The NanoString assays were specific for circRNA detection and data were more reproducible and quantitatively more accurate than RNA-seq data. In addition, we obtained high-quality data on severely degraded RNA samples from formalin-fixed, paraffin-embedded (FFPE) tissues. Together, we provide a map of circRNA expression in B-cell malignancies and present an enzyme-free digital counting methodology, which has the potential to become a new gold standard for circRNA quantification.Endogenous circular RNA (circRNA) expression has not been characterized in B-cell malignancies, and current methods for circRNA quantification have several limitations. Here, the authors provide a map of circRNA expression in B-cell malignancies based on high-throughput RNA sequencing and present an enzyme-free digital counting methodology, which has the potential to become the gold standard for circRNA quantification.
Highlights
Paired fresh frozen and FFPE tissue samples from archived lymph nodes were obtained from five patients with mantle cell lymphomas (MCLs), three patients with chronic lymphocytic leukemia (CLL), three patients with follicular lymphoma (FL) grade 1–2 and two patients with diffuse large B-cell lymphoma (DLBCL)
RNA sequencing (RNA-seq) was performed on the HiSeq 4000 system (Illumina, San Diego, CA, USA) at the Beijing Genomics Institute (BGI) using the 100 paired-end sequencing protocol with nine samples pooled on one lane
These assays were used to elucidate the expression of circRNA in B-cell malignancies by analyzing RNA from 15 different cell lines, including four DLBCL, two Burkitt lymphoma (BL), four MCL and five MM
Summary
Circular RNA (circRNA) is a recently discovered component of the non-coding genome adding yet another layer of complexity to the gene regulation involved in cell differentiation and homeostasis, as well as in the development of various diseases such as cancer [1, 2]. Variability between individual RNase R treatments has been observed [4], and some circRNAs seem to be sensitive to RNase R [25] Because of these problems, northern blotting, which does not rely on RT and PCR amplification, is currently regarded as the gold standard for circRNA detection. Northern blotting, which does not rely on RT and PCR amplification, is currently regarded as the gold standard for circRNA detection This method requires large quantities of RNA, is labor intensive and not quantitatively accurate. We profiled the genome-wide landscape of circRNA expression in MCL and MM cell lines using RNA-seq. Based on these data, we designed a panel of NanoString assays for 52 unique circRNAs to analyze on the nCounter SPRINTTM Profiler from NanoString Technologies. We compared the NanoString data with RNA-seqand RT-qPCR data
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