Discovery of CTCF-sensitive Cis-spliced fusion RNAs between adjacent genes in human prostate cells

Fusion RNA profiling provides hints on cell of origin of mysterious tumor

Biological samples can be grouped into separate clusters based on their gene expression profiles. This approach has yielded meaningful biological insights and facilitated biomarker discoveries. Recently, we developed another approach to study connections between biological samples based on their fusion RNA expression. We have used this approach to provide insights into the cell of origin for a mysterious tumor, alveolar rhabdomyosarcoma.

MiR-101 Targets the EZH2/Wnt/β-Catenin the Pathway to Promote the Osteogenic Differentiation of Human Bone Marrow-Derived Mesenchymal Stem Cells

Mounting evidence indicates that microRNAs (miRNAs) are involved in multiple processes of osteogenic differentiation. MicroRNA-101 (miR-101), identified as a tumor suppressor, has been implicated in the pathogenesis of several types of cancer. However, the expression of miR-101 and its roles in the osteogenic differentiation of human bone marrow-derived mesenchymal stem cells (hBMSCs) remain unclear. We found that the miR-101 expression level was significantly increased during the osteogenic differentiation of hBMSCs. MiR-101 depletion suppressed osteogenic differentiation, whereas the overexpression of miR-101 was sufficient to promote this process. We further demonstrated that enhancer of zeste homolog 2 (EZH2) was a target gene of miR-101. EZH2 overexpression and depletion reversed the promoting or suppressing effect of osteogenic differentiation of hBMSCs, respectively, caused by miR-101. In addition, we showed that miR-101 overexpression promoted the expression of Wnt genes, resulting in the activation of the Wnt/β-catenin signaling pathway by targeting EZH2, while the activity of β-catenin and the Wnt/β-catenin signaling pathway was inhibited by ICG-001, a β-Catenin inhibitor, which reversed the promoting effect of miR-101. Finally, miR-101 also promotes in vivo bone formation by hBMSCs. Collectively, these data suggest that miR-101 is induced by osteogenic stimuli and promotes osteogenic differentiation at least partly by targeting the EZH2/Wnt/β-Catenin signaling pathway.

Identifying fusion transcripts using next generation sequencing

Fusion transcripts (i.e., chimeric RNAs) resulting from gene fusions have been used successfully for cancer diagnosis, prognosis, and therapeutic applications. In addition, many fusion transcripts are found in normal human cell lines and tissues, with some data supporting their role in normal physiology. Besides chromosomal rearrangement, intergenic splicing can generate them. Global identification of fusion transcripts becomes possible with the help of next generation sequencing technology like RNA-Seq. In the past decade, major advancements have been made for chimeric RNA discovery due to the development of advanced sequencing platform and software packages. However, current software tools behave differently in terms of specificity, sensitivity, time, and computational memory usage. Recent benchmarking studies showed that none of the tools are inclusive. The development of high performance (accurate and fast), and user-friendly fusion detection tool/pipeline is still an open quest. In this article, we review the existing software packages for fusion detection. We explain the methods of the tools, and discuss various factors that affect fusion detection. We summarize conclusions drawn from several comparative studies, and then discuss some of the pitfalls of these studies. We also describe the limitations of current tools, and suggest directions for future development. WIREs RNA 2016, 7:811-823. doi: 10.1002/wrna.1382 For further resources related to this article, please visit the WIREs website.

Fusion transcriptome profiling provides insights into alveolar rhabdomyosarcoma

Gene fusions and fusion products were thought to be unique features of neoplasia. However, more and more studies have identified fusion RNAs in normal physiology. Through RNA sequencing of 27 human noncancer tissues, a large number of fusion RNAs were found. By analyzing fusion transcriptome, we observed close clusterings between samples of same or similar tissues, supporting the feasibility of using fusion RNA profiling to reveal connections between biological samples. To put the concept into use, we selected alveolar rhabdomyosarcoma (ARMS), a myogenic pediatric cancer whose exact cell of origin is not clear. PAX3-FOXO1 (paired box gene 3 fused with forkhead box O1) fusion RNA, which is considered a hallmark of ARMS, was recently found during normal muscle cell differentiation. We performed and analyzed RNA sequencing from various time points during myogenesis and uncovered many chimeric fusion RNAs. Interestingly, we found that the fusion RNA profile of RH30, an ARMS cell line, is most similar to the myogenesis time point when PAX3-FOXO1 is expressed. In contrast, full transcriptome clustering analysis failed to uncover this connection. Strikingly, all of the 18 chimeric RNAs in RH30 cells could be detected at the same myogenic time point(s). In addition, the seven chimeric RNAs that follow the exact transient expression pattern as PAX3-FOXO1 are specific to rhabdomyosarcoma cells. Further testing with clinical samples also confirmed their specificity to rhabdomyosarcoma. These results provide further support for the link between at least some ARMSs and the PAX3-FOXO1-expressing myogenic cells and demonstrate that fusion RNA profiling can be used to investigate the etiology of fusion-gene-associated cancers.

Intergenically Spliced Chimeric RNAs in Cancer

Gene fusions and their encoded products (fusion RNAs and proteins) are viewed as one of the hallmarks of cancer. Traditionally, they were thought to be generated solely by chromosomal rearrangements. However, recent discoveries of trans-splicing and cis-splicing events between neighboring genes, suggest that there are other mechanisms to generate chimeric fusion RNAs without corresponding changes in DNA. In addition, chimeric RNAs have been detected in normal physiology, complicating the use of fusions in cancer detection and therapy. On the other hand, "intergenically spliced" fusion RNAs represent a new repertoire of biomarkers and therapeutic targets. Here, we review current knowledge on chimeric RNAs and implications for cancer detection and treatment, and discuss outstanding questions for the advancement of the field.

Recurrent cis-SAGe chimeric RNA, D2HGDH-GAL3ST2, in prostate cancer

Neighboring genes transcribing in the same direction can form chimeric RNAs via cis-splicing (cis-SAGe). Previously, we reported 16 novel cis-SAGe chimeras in prostate cancer cell lines, and performed in silico validation on 14 pairs of normal and tumor samples from Chinese patients. However, whether these fusions exist in different populations, as well as their clinical implications, remains unclear. To investigate, we developed a bioinformatics pipeline using modified Spliced Transcripts Alignment to a Reference (STAR) to quantify these fusion RNAs simultaneously in silico. From RNA-Seq data of 100 paired normal and prostate cancer samples from TCGA, we find that most fusions are not specific to cancer. However, D2HGDH-GAL3ST2 is more frequently seen in cancer samples, and seems to be enriched in the African American group. Further validation with our own collection as well as from commercial sources did not detect this fusion RNA in 29 normal prostate samples, but in 19 of 93 prostate cancer samples. It is more frequently detected in late stage cancer, suggesting a role in cancer progression. Consistently, silencing this fusion resulted in dramatic reduction of cell proliferation rate and cell motility.

Lessons from non-canonical splicing

Recent improvements in experimental and computational techniques that are used to study the transcriptome have enabled an unprecedented view of RNA processing, revealing many previously unknown non-canonical splicing events. This includes cryptic events located far from the currently annotated exons and unconventional splicing mechanisms that have important roles in regulating gene expression. These non-canonical splicing events are a major source of newly emerging transcripts during evolution, especially when they involve sequences derived from transposable elements. They are therefore under precise regulation and quality control, which minimizes their potential to disrupt gene expression. We explain how non-canonical splicing can lead to aberrant transcripts that cause many diseases, and also how it can be exploited for new therapeutic strategies.

Discovering and understanding oncogenic gene fusions through data intensive computational approaches

Although gene fusions have been recognized as important drivers of cancer for decades, our understanding of the prevalence and function of gene fusions has been revolutionized by the rise of next-generation sequencing, advances in bioinformatics theory and an increasing capacity for large-scale computational biology. The computational work on gene fusions has been vastly diverse, and the present state of the literature is fragmented. It will be fruitful to merge three camps of gene fusion bioinformatics that appear to rarely cross over: (i) data-intensive computational work characterizing the molecular biology of gene fusions; (ii) development research on fusion detection tools, candidate fusion prioritization algorithms and dedicated fusion databases and (iii) clinical research that seeks to either therapeutically target fusion transcripts and proteins or leverages advances in detection tools to perform large-scale surveys of gene fusion landscapes in specific cancer types. In this review, we unify these different-yet highly complementary and symbiotic-approaches with the view that increased synergy will catalyze advancements in gene fusion identification, characterization and significance evaluation.

Role of CTCF in Regulating SLC45A3-ELK4 Chimeric RNA

The chimeric RNA, SLC45A3-ELK4, was found to be a product of cis-splicing between the two adjacent genes (cis-SAGe). Despite the biological and clinical significance of SLC45A3-ELK4, its generating mechanism has not been elucidated. It was shown in one cell line that the binding of transcription factor CTCF to the insulators located at or near the gene boundaries, inversely correlates with the level of the chimera. To investigate the mechanism of such cis-SAGe events, we sequenced potential regions that may play a role in such transcriptional read-through. We could not detect mutations at the transcription termination site, insulator sites, splicing sites, or within CTCF itself in LNCaP cells, thus suggesting a “soft-wired” mechanism in regulating the cis-SAGe event. To investigate the role CTCF plays in regulating the chimeric RNA expression, we compared the levels of CTCF binding to the insulators in different cell lines, as well as clinical samples. Surprisingly, we did not find an inverse correlation between CTCF level, or its bindings to the insulators and SLC45A3-ELK4 expression among different samples. However, in three prostate cancer cell lines, different environmental factors can cause the expression levels of the chimeric RNA to change, and these changes do inversely correlate with CTCF level, and/or its bindings to the insulators. We thus conclude that CTCF and its bindings to the insulators are not the primary reasons for differential SLC45A3-ELK4 expression in different cell lines, or clinical cases. However, they are the likely mechanism for the same cells to respond to different environmental cues, in order to regulate the expression of SLC45A3-ELK4 chimeric RNA. This response to different environmental cues is not general to other cis-SAGe events, as we only found one out of 16 newly identified chimeric RNAs showing a pattern similar to SLC45A3-ELK4.

Comparative assessment of methods for the fusion transcripts detection from RNA-Seq data

RNA-Seq made possible the global identification of fusion transcripts, i.e. "chimeric RNAs". Even though various software packages have been developed to serve this purpose, they behave differently in different datasets provided by different developers. It is important for both users, and developers to have an unbiased assessment of the performance of existing fusion detection tools. Toward this goal, we compared the performance of 12 well-known fusion detection software packages. We evaluated the sensitivity, false discovery rate, computing time, and memory usage of these tools in four different datasets (positive, negative, mixed, and test). We conclude that some tools are better than others in terms of sensitivity, positive prediction value, time consumption and memory usage. We also observed small overlaps of the fusions detected by different tools in the real dataset (test dataset). This could be due to false discoveries by various tools, but could also be due to the reason that none of the tools are inclusive. We have found that the performance of the tools depends on the quality, read length, and number of reads of the RNA-Seq data. We recommend that users choose the proper tools for their purpose based on the properties of their RNA-Seq data.

Recurrent chimeric fusion RNAs in non-cancer tissues and cells

Gene fusions and their products (RNA and protein) were once thought to be unique features to cancer. However, chimeric RNAs can also be found in normal cells. Here, we performed, curated and analyzed nearly 300 RNA-Seq libraries covering 30 different non-neoplastic human tissues and cells as well as 15 mouse tissues. A large number of fusion transcripts were found. Most fusions were detected only once, while 291 were seen in more than one sample. We focused on the recurrent fusions and performed RNA and protein level validations on a subset. We characterized these fusions based on various features of the fusions, and their parental genes. They tend to be expressed at higher levels relative to their parental genes than the non-recurrent ones. Over half of the recurrent fusions involve neighboring genes transcribing in the same direction. A few sequence motifs were found enriched close to the fusion junction sites. We performed functional analyses on a few widely expressed fusions, and found that silencing them resulted in dramatic reduction in normal cell growth and/or motility. Most chimeras use canonical splicing sites, thus are likely products of 'intergenic splicing'. We also explored the implications of these non-pathological fusions in cancer and in evolution.