SLC45A3-ELK4 is a novel and frequent erythroblast transformation-specific fusion transcript in prostate cancer

Oncogenic SLC2A11-MIF fusion protein interacts with polypyrimidine tract binding protein 1 to facilitate bladder cancer proliferation and metastasis by regulating mRNA stability

Chimeric RNAs, distinct from DNA gene fusions, have emerged as promising therapeutic targets with diverse functions in cancer treatment. However, the functional significance and therapeutic potential of most chimeric RNAs remain unclear. Here we identify a novel fusion transcript of solute carrier family 2-member 11 (SLC2A11) and macrophage migration inhibitory factor (MIF). In this study, we investigated the upregulation of SLC2A11-MIF in The Cancer Genome Atlas cohort and a cohort of patients from Sun Yat-Sen Memorial Hospital. Subsequently, functional investigations demonstrated that SLC2A11-MIF enhanced the proliferation, antiapoptotic effects, and metastasis of bladder cancer cells in vitro and in vivo. Mechanistically, the fusion protein encoded by SLC2A11-MIF interacted with polypyrimidine tract binding protein 1 (PTBP1) and regulated the mRNA half-lives of Polo Like Kinase 1, Roundabout guidance receptor 1, and phosphoinositide-3-kinase regulatory subunit 3 in BCa cells. Moreover, PTBP1 knockdown abolished the enhanced impact of SLC2A11-MIF on biological function and mRNA stability. Furthermore, the expression of SLC2A11-MIF mRNA is regulated by CCCTC-binding factor and stabilized through RNA N4-acetylcytidine modification facilitated by N-acetyltransferase 10. Overall, our findings revealed a significant fusion protein orchestrated by the SLC2A11-MIF-PTBP1 axis that governs mRNA stability during the multistep progression of bladder cancer.

Comprehensive characterization of somatic mutations associated with chimeric RNAs in human cancers

Chimeric RNAs, which can arise from gene recombination at the DNA level or non-canonical splicing events at the RNA level, have been identified as important roles in human tumors. Dysregulated gene expression caused by somatic mutations and altered splicing patterns of oncogenes or tumor suppressor genes can contribute to the development of tumors. Therefore, investigating the formation mechanism of chimeric RNAs via somatic mutations is critical for understanding tumor pathogenesis. This project is the first to propose studying the association between somatic single nucleotide variants and chimeric RNAs, identifying around 2900 somatic SNVs affecting chimeric RNAs in pan-cancer level. The somatic SNVs on chimeric RNAs were commonly observed in various types of tumor tissues, providing a valuable resource for future study. Additionally, these SNVs show distinct tumor specificity, and those with high frequency had a significant impact on the survival time of patients with tumors. Further research revealed that somatic SNVs associated with chimeric RNA (chiR-SNVs) were typically found within 10 nt of the junction site of chimeric RNAs and had a particularly significant effect on chimeric RNAs from different chromosomes. The enrichment analysis revealed that chiR-SNVs were significantly overrepresented in oncogenes and genes related to RNA binding proteins involved in RNA splicing, which could imply that chiR-SNVs may disrupt the process of RNA splicing and induce the occurrence of chimeric RNAs. This study sheds light on the potential molecular interaction mechanism between somatic SNVs and chimeric RNAs, which opens up a new avenue for researching disease pathway and tumorigenesis development.

Conserved features and diversity attributes of chimeric RNAs across accessions in four plants

As a non-collinear expression form of genetic information, chimeric RNAs increase the complexity of transcriptome in diverse organisms. Although chimeric RNAs have been identified in plants, few common features have been revealed. Here, we systemically explored the landscape of chimeric RNAs across multi-accession and multi-tissue using pan-genome and transcriptome data of four plants: rice, maize, soybean, and Arabidopsis. Among the four species, conserved characteristics of breakpoints and parental genes were discovered. In each species, chimeric RNAs displayed a high level of diversity among accessions, and the clustering of accessions using chimeric events was generally concordant with clustering based on genomic variants, implying a general relationship between genetic variations and chimeric RNAs. Through mass spectrometry, we confirmed a fusion protein OsNDC1-OsGID1L2 and observed its subcellular localization, which differed from the original proteins. Phenotypic cues in transgenic rice suggest the potential functions of OsNDC1-OsGID1L2. Moreover, an intriguing chimeric event Os01g0216500-Os01g0216900, generated by a large deletion in basmati rice, also exists in another accession without the deletion, demonstrating its convergence in evolution. Our results illuminate the characteristics and hint at the evolutionary implications of plant chimeric RNAs, which serve as a supplement to genetic variations, thus expanding our understanding of genetic diversity.

Cancer fusion transcripts with human non-coding RNAs

Cancer chimeric, or fusion, transcripts are thought to most frequently appear due to chromosomal aberrations that combine moieties of unrelated normal genes. When being expressed, this results in chimeric RNAs having upstream and downstream parts relatively to the breakpoint position for the 5'- and 3'-fusion components, respectively. As many other types of cancer mutations, fusion genes can be of either driver or passenger type. The driver fusions may have pivotal roles in malignisation by regulating survival, growth, and proliferation of tumor cells, whereas the passenger fusions most likely have no specific function in cancer. The majority of research on fusion gene formation events is concentrated on identifying fusion proteins through chimeric transcripts. However, contemporary studies evidence that fusion events involving non-coding RNA (ncRNA) genes may also have strong oncogenic potential. In this review we highlight most frequent classes of ncRNAs fusions and summarize current understanding of their functional roles. In many cases, cancer ncRNA fusion can result in altered concentration of the non-coding RNA itself, or it can promote protein expression from the protein-coding fusion moiety. Differential splicing, in turn, can enrich the repertoire of cancer chimeric transcripts, e.g. as observed for the fusions of circular RNAs and long non-coding RNAs. These and other ncRNA fusions are being increasingly recognized as cancer biomarkers and even potential therapeutic targets. Finally, we discuss the use of ncRNA fusion genes in the context of cancer detection and therapy.

Readon: a novel algorithm to identify read-through transcripts with long-read sequencing data

MOTIVATION

There are many clustered transcriptionally active regions in the human genome, in which the transcription complex cannot immediately terminate transcription at the upstream gene termination site, but instead continues to transcribe intergenic regions and downstream genes, resulting in read-through transcripts. Several studies have demonstrated the regulatory roles of read-through transcripts in tumorigenesis and development. However, limited by the read length of next-generation sequencing, discovery of read-through transcripts has been slow. For long but also erroneous third-generation sequencing data, this study developed a novel minimizer sketch algorithm to accurately and quickly identify read-through transcripts.

RESULTS

Readon initially splits the reference sequence into distinct active regions. It employs a sliding window approach within each region, calculates minimizers, and constructs the specialized structured arrays for query indexing. Following initial alignment anchor screening of candidate read-through transcripts, further confirmation steps are executed. Comparative assessments against existing software reveal Readon's superior performance on both simulated and validated real data. Additionally, two downstream tools are provided: one for predicting whether a read-through transcript is likely to undergo nonsense-mediated decay or encodes a protein, and another for visualizing splicing patterns.

AVAILABILITY AND IMPLEMENTATION

Readon is freely available on GitHub (https://github.com/Bulabula45/Readon).

SLC45A3 Serves as a Potential Therapeutic Biomarker to Attenuate White Matter Injury After Intracerebral Hemorrhage

Intracerebral hemorrhage (ICH) is a severe cerebrovascular disease, which impairs patients' white matter even after timely clinical interventions. Indicated by studies in the past decade, ICH-induced white matter injury (WMI) is closely related to neurological deficits; however, its underlying mechanism and pertinent treatment are yet insufficient. We gathered two datasets (GSE24265 and GSE125512), and by taking an intersection among interesting genes identified by weighted gene co-expression networks analysis, we determined target genes after differentially expressing genes in two datasets. Additional single-cell RNA-seq analysis (GSE167593) helped locate the gene in cell types. Furthermore, we established ICH mice models induced by autologous blood or collagenase. Basic medical experiments and diffusion tensor imaging were applied to verify the function of target genes in WMI after ICH. Through intersection and enrichment analysis, gene SLC45A3 was identified as the target one, which plays a key role in the regulation of oligodendrocyte differentiation involving in fatty acid metabolic process, etc. after ICH, and single-cell RNA-seq analysis also shows that it mainly locates in oligodendrocytes. Further experiments verified overexpression of SLC45A3 ameliorated brain injury after ICH. Therefore, SLC45A3 might serve as a candidate therapeutic biomarker for ICH-induced WMI, and overexpression of it may be a potential approach for injury attenuation.

RTCpredictor: identification of read-through chimeric RNAs from RNA sequencing data

Read-through chimeric RNAs are being recognized as a means to expand the functional transcriptome and contribute to cancer tumorigenesis when mis-regulated. However, current software tools often fail to predict them. We have developed RTCpredictor, utilizing a fast ripgrep tool to search for all possible exon-exon combinations of parental gene pairs. We also added exonic variants allowing searches containing common SNPs. To our knowledge, it is the first read-through chimeric RNA specific prediction method that also provides breakpoint coordinates. Compared with 10 other popular tools, RTCpredictor achieved high sensitivity on a simulated and three real datasets. In addition, RTCpredictor has less memory requirements and faster execution time, making it ideal for applying on large datasets.

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data

Bulk DNA sequencing of multiple samples from the same tumor is becoming common, yet most methods to infer copy-number aberrations (CNAs) from this data analyze individual samples independently. We introduce HATCHet2, an algorithm to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 extends the earlier HATCHet method by improving identification of focal CNAs and introducing a novel statistic, the minor haplotype B-allele frequency (mhBAF), that enables identification of mirrored-subclonal CNAs. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 10 prostate cancer patients reveals previously unreported mirrored-subclonal CNAs affecting cancer genes.

Integrative Molecular Analyses of the MD Anderson Prostate Cancer Patient-derived Xenograft (MDA PCa PDX) Series

PURPOSE

Develop and deploy a robust discovery platform that encompasses heterogeneity, clinical annotation, and molecular characterization and overcomes the limited availability of prostate cancer models. This initiative builds on the rich MD Anderson (MDA) prostate cancer (PCa) patient-derived xenograft (PDX) resource to complement existing publicly available databases by addressing gaps in clinically annotated models reflecting the heterogeneity of potentially lethal and lethal prostate cancer.

EXPERIMENTAL DESIGN

We performed whole-genome, targeted, and RNA sequencing in representative samples of the same tumor from 44 PDXs derived from 38 patients linked to donor tumor metadata and corresponding organoids. The cohort includes models derived from different morphologic groups, disease states, and involved organ sites (including circulating tumor cells), as well as paired samples representing heterogeneity or stages before and after therapy.

RESULTS

The cohort recapitulates clinically reported alterations in prostate cancer genes, providing a data resource for clinical and molecular interrogation of suitable experimental models. Paired samples displayed conserved molecular alteration profiles, suggesting the relevance of other regulatory mechanisms (e.g., epigenomic) influenced by the microenvironment and/or treatment. Transcriptomically, models were grouped on the basis of morphologic classification. DNA damage response-associated mechanisms emerged as differentially regulated between adenocarcinoma and neuroendocrine prostate cancer in a cross-interrogation of PDX/patient datasets.

CONCLUSIONS

We addressed the gap in clinically relevant prostate cancer models through comprehensive molecular characterization of MDA PCa PDXs, providing a discovery platform that integrates with patient data and benchmarked to therapeutically relevant consensus clinical groupings. This unique resource supports robust hypothesis generation and testing from basic, translational, and clinical perspectives.

Tumor microenvironment deconvolution identifies cell-type-independent aberrant DNA methylation and gene expression in prostate cancer

BACKGROUND

Among men, prostate cancer (PCa) is the second most common cancer and the second leading cause of cancer death. Etiologic factors associated with both prostate carcinogenesis and somatic alterations in tumors are incompletely understood. While genetic variants associated with PCa have been identified, epigenetic alterations in PCa are relatively understudied. To date, DNA methylation (DNAm) and gene expression (GE) in PCa have been investigated; however, these studies did not correct for cell-type proportions of the tumor microenvironment (TME), which could confound results.

METHODS

The data (GSE183040) consisted of DNAm and GE data from both tumor and adjacent non-tumor prostate tissue of 56 patients who underwent radical prostatectomies prior to any treatment. This study builds upon previous studies that examined methylation patterns and GE in PCa patients by using a novel tumor deconvolution approach to identify and correct for cell-type proportions of the TME in its epigenome-wide association study (EWAS) and differential expression analysis (DEA).

RESULTS

The inclusion of cell-type proportions in EWASs and DEAs reduced the scope of significant alterations associated with PCa. We identified 2,093 significantly differentially methylated CpGs (DMC), and 51 genes associated with PCa, including PCA3, SPINK1, and AMACR.

CONCLUSIONS

This work illustrates the importance of correcting for cell types of the TME when performing EWASs and DEAs on PCa samples, and establishes a more confounding-adverse methodology. We identified a more tumor-cell-specific set of altered genes and epigenetic marks that can be further investigated as potential biomarkers of disease or potential therapeutic targets.

HATCHet2: clone- and haplotype-specific copy number inference from bulk tumor sequencing data

Multi-region DNA sequencing of primary tumors and metastases from individual patients helps identify somatic aberrations driving cancer development. However, most methods to infer copy-number aberrations (CNAs) analyze individual samples. We introduce HATCHet2 to identify haplotype- and clone-specific CNAs simultaneously from multiple bulk samples. HATCHet2 introduces a novel statistic, the mirrored haplotype B-allele frequency (mhBAF), to identify mirrored-subclonal CNAs having different numbers of copies of parental haplotypes in different tumor clones. HATCHet2 also has high accuracy in identifying focal CNAs and extends the earlier HATCHet method in several directions. We demonstrate HATCHet2's improved accuracy using simulations and a single-cell sequencing dataset. HATCHet2 analysis of 50 prostate cancer samples from 10 patients reveals previously-unreported mirrored-subclonal CNAs affecting cancer genes.

How chromosomal translocations arise to cause cancer: Gene proximity, trans-splicing, and DNA end joining

Chromosomal translocations (CTs) are a genetic hallmark of cancer. They could be identified as recurrent genetic aberrations in hemato-malignancies and solid tumors. More than 40% of all "cancer genes" were identified in recurrent CTs. Most of these CTs result in the production of oncofusion proteins of which many have been studied over the past decades. They influence signaling pathways and/or alter gene expression. However, a precise mechanism for how these CTs arise and occur in a nearly identical fashion in individuals remains to be elucidated. Here, we performed experiments that explain the onset of CTs: (1) proximity of genes able to produce prematurely terminated transcripts, which lead to the production of (2) trans-spliced fusion RNAs, and finally, the induction of (3) DNA double-strand breaks which are subsequently repaired via EJ repair pathways. Under these conditions, balanced chromosomal translocations could be specifically induced. The implications of these findings will be discussed.

Fusion sequencing via terminator-assisted synthesis (FTAS-seq) identifies TMPRSS2 fusion partners in prostate cancer

Genetic rearrangements that fuse an androgen-regulated promoter area with a protein-coding portion of an originally androgen-unaffected gene are frequent in prostate cancer, with the fusion between transmembrane serine protease 2 (TMPRSS2) and ETS transcription factor ERG (ERG) (TMPRSS2-ERG fusion) being the most prevalent. Conventional hybridization- or amplification-based methods can test for the presence of expected gene fusions, but the exploratory analysis of currently unknown fusion partners is often cost-prohibitive. Here, we developed an innovative next-generation sequencing (NGS)-based approach for gene fusion analysis termed fusion sequencing via terminator-assisted synthesis (FTAS-seq). FTAS-seq can be used to enrich the gene of interest while simultaneously profiling the whole spectrum of its 3'-terminal fusion partners. Using this novel semi-targeted RNA-sequencing technique, we were able to identify 11 previously uncharacterized TMPRSS2 fusion partners and capture a range of TMPRSS2-ERG isoforms. We tested the performance of FTAS-seq with well-characterized prostate cancer cell lines and utilized the technique for the analysis of patient RNA samples. FTAS-seq chemistry combined with appropriate primer panels holds great potential as a tool for biomarker discovery that can support the development of personalized cancer therapies.

Model System to Analyze RNA-Mediated DNA Repair in Mammalian Cells

"RNA-templated/directed DNA repair" is a biological mechanism that has been experimentally demonstrated in bacteria, yeast, and mammalian cells. Recent study has shown that small noncoding RNAs (DDRNAs) and/or newly RNAPII transcribed RNAs (dilncRNAs) are orchestrating the initial steps of double-strand break (DSB) repair. In this study, we demonstrate that also pre-mRNA could be used as direct or indirect substrate for DSB repair. Our test system is based on (1) a stably integrated mutant reporter gene that produces constitutively a nonspliceable pre-mRNA, (2) a transiently expressed sgRNA-guided dCas13b::ADAR fusion protein to specifically RNA edit the nonspliceable pre-mRNA, and (3) transiently expressed I-SceI to create a DSB situation to study the effect of spliceable pre-mRNA on DNA repair. Based on our data, the RNA-edited pre-mRNA was used in cis for the DSB repair process, thereby converting the genomically encoded mutant reporter gene into an active reporter gene. Overexpression and knockdown of several cellular proteins were performed to delineate their role in this novel "RNA-mediated end joining" pathway.

RTCpredictor: Identification of Read-Through Chimeric RNAs from RNA Sequencing Data

Read-through chimeric RNAs are gaining attention in cancer and other research fields, yet current tools often fail in predicting them. We have thus developed the first read-through chimeric RNA specific prediction method, RTCpredictor, utilizing a fast ripgrep algorithm to search for all possible exon-exon combinations of parental gene pairs. Compared with other ten popular tools, RTCpredictor achieved top performance on both simulated and real datasets. We randomly selected up to 30 candidate read-through chimeras predicted from each software method and experimentally validated a total of 109 read-throughs and on this set, RTCpredictor outperformed all the other methods. In addition, RTCpredictor ( https://github.com/sandybioteck/RTCpredictor ) has less memory requirements and faster execution time.

Recent advances in cancer fusion transcript detection

Extensive investigation of gene fusions in cancer has led to the discovery of novel biomarkers and therapeutic targets. To date, most studies have neglected chromosomal rearrangement-independent fusion transcripts and complex fusion structures such as double or triple-hop fusions, and fusion-circRNAs. In this review, we untangle fusion-related terminology and propose a classification system involving both gene and transcript fusions. We highlight the importance of RNA-level fusions and how long-read sequencing approaches can improve detection and characterization. Moreover, we discuss novel bioinformatic tools to identify fusions in long-read sequencing data and strategies to experimentally validate and functionally characterize fusion transcripts.

Neoplasia-associated Chromosome Translocations Resulting in Gene Truncation

Chromosomal translocations in cancer as well as benign neoplasias typically lead to the formation of fusion genes. Such genes may encode chimeric proteins when two protein-coding regions fuse in-frame, or they may result in deregulation of genes via promoter swapping or translocation of the gene into the vicinity of a highly active regulatory element. A less studied consequence of chromosomal translocations is the fusion of two breakpoint genes resulting in an out-of-frame chimera. The breaks then occur in one or both protein-coding regions forming a stop codon in the chimeric transcript shortly after the fusion point. Though the latter genetic events and mechanisms at first awoke little research interest, careful investigations have established them as neither rare nor inconsequential. In the present work, we review and discuss the truncation of genes in neoplastic cells resulting from chromosomal rearrangements, especially from seemingly balanced translocations.

Patterns of structural variation define prostate cancer across disease states

The complex genomic landscape of prostate cancer evolves across disease states under therapeutic pressure directed toward inhibiting androgen receptor (AR) signaling. While significantly altered genes in prostate cancer have been extensively defined, there have been fewer systematic analyses of how structural variation shapes the genomic landscape of this disease across disease states. We uniformly characterized structural alterations across 531 localized and 143 metastatic prostate cancers profiled by whole genome sequencing, 125 metastatic samples of which were also profiled via whole transcriptome sequencing. We observed distinct significantly recurrent breakpoints in localized and metastatic castration-resistant prostate cancers (mCRPC), with pervasive alterations in noncoding regions flanking the AR, MYC, FOXA1, and LSAMP genes enriched in mCRPC and TMPRSS2-ERG rearrangements enriched in localized prostate cancer. We defined 9 subclasses of mCRPC based on signatures of structural variation, each associated with distinct genetic features and clinical outcomes. Our results comprehensively define patterns of structural variation in prostate cancer and identify clinically actionable subgroups based on whole genome profiling.

The Prostate Cancer Androgen Receptor Cistrome in African American Men Associates with Upregulation of Lipid Metabolism and Immune Response

African-American (AA) men are more likely to be diagnosed with and die from prostate cancer than European American (EA) men. Despite the central role of the androgen receptor (AR) transcription factor in prostate cancer, little is known about the contribution of epigenetics to observed racial disparities. We performed AR chromatin immunoprecipitation sequencing on primary prostate tumors from AA and EA men, finding that sites with greater AR binding intensity in AA relative to EA prostate cancer are enriched for lipid metabolism and immune response genes. Integration with transcriptomic and metabolomic data demonstrated coinciding upregulation of lipid metabolism gene expression and increased lipid levels in AA prostate cancer. In a metastatic prostate cancer cohort, upregulated lipid metabolism associated with poor prognosis. These findings offer the first insights into ancestry-specific differences in the prostate cancer AR cistrome. The data suggest a model whereby increased androgen signaling may contribute to higher levels of lipid metabolism, immune response, and cytokine signaling in AA prostate tumors. Given the association of upregulated lipogenesis with prostate cancer progression, our study provides a plausible biological explanation for the higher incidence and aggressiveness of prostate cancer observed in AA men.

SIGNIFICANCE

With immunotherapies and inhibitors of metabolic enzymes in clinical development, the altered lipid metabolism and immune response in African-American men provides potential therapeutic opportunities to attenuate racial disparities in prostate cancer.

The evolving landscape of prostate cancer somatic mutations

BACKGROUND

The landscape of somatic mutations in prostate cancer (PCa) has quickly evolved over the past years.

RESULTS

This evolution was in part due to the improved quality and lower cost of genomic sequencing platforms available to an ever-larger group of clinicians and researchers. The result of these efforts is a better understanding of early and late mutations that are enriched or nearly exclusive to treated PCa. There are, however, some important limitations to the current knowledge. The expanding variety of next-generation sequencing (NGS) assays either capture a wide spectrum of mutations but at low coverage or are focused panels that cover a select number of genes, most often cancer-related, at a deep coverage. Both of these approaches have their advantages, but ultimately miss low-frequency mutations or fail to cover the spectrum of potential mutations. Additionally, some alterations, such as the common ETS gene fusions, require a mixture of DNA and RNA analysis to capture the true frequency. Finally, almost all studies rely on bulk PCa tumor samples, which fail to consider tumor heterogeneity. Given all these caveats, the true picture of the somatic landscape of PCa continues to develop.

SUMMARY

In this review, the focus will be on how the landscape of mutations evolves during disease progression considering therapy. It will focus on a select group of early and late mutations and utilize SPOP mutations to illustrate recurrent alterations that may have clinical implications.

Current insights into the role of Fli-1 in hematopoiesis and malignant transformation

Fli-1, a member of the ETS family of transcription factors, was discovered in 1991 through retroviral insertional mutagenesis as a driver of mouse erythroleukemias. In the past 30 years, nearly 2000 papers have defined its biology and impact on normal development and cancer. In the hematopoietic system, Fli-1 controls self-renewal of stem cells and their differentiation into diverse mature blood cells. Fli-1 also controls endothelial survival and vasculogenesis, and high and low levels of Fli-1 are implicated in the auto-immune diseases systemic lupus erythematosus and systemic sclerosis, respectively. In addition, aberrant Fli-1 expression is observed in, and is essential for, the growth of multiple hematological malignancies and solid cancers. Here, we review the historical context and latest research on Fli-1, focusing on its role in hematopoiesis, immune response, and malignant transformation. The importance of identifying Fli-1 modulators (both agonists and antagonists) and their potential clinical applications is discussed.

Genion, an accurate tool to detect gene fusion from long transcriptomics reads

BACKGROUND

The advent of next-generation sequencing technologies empowered a wide variety of transcriptomics studies. A widely studied topic is gene fusion which is observed in many cancer types and suspected of having oncogenic properties. Gene fusions are the result of structural genomic events that bring two genes closely located and result in a fused transcript. This is different from fusion transcripts created during or after the transcription process. These chimeric transcripts are also known as read-through and trans-splicing transcripts. Gene fusion discovery with short reads is a well-studied problem, and many methods have been developed. But the sensitivity of these methods is limited by the technology, especially the short read length. Advances in long-read sequencing technologies allow the generation of long transcriptomics reads at a low cost. Transcriptomic long-read sequencing presents unique opportunities to overcome the shortcomings of short-read technologies for gene fusion detection while introducing new challenges.

RESULTS

We present Genion, a sensitive and fast gene fusion detection method that can also detect read-through events. We compare Genion against a recently introduced long-read gene fusion discovery method, LongGF, both on simulated and real datasets. On simulated data, Genion accurately identifies the gene fusions and its clustering accuracy for detecting fusion reads is better than LongGF. Furthermore, our results on the breast cancer cell line MCF-7 show that Genion correctly identifies all the experimentally validated gene fusions.

CONCLUSIONS

Genion is an accurate gene fusion caller. Genion is implemented in C++ and is available at https://github.com/vpc-ccg/genion .

Identification of Chimeric RNAs in Pig Skeletal Muscle and Transcriptomic Analysis of Chimeric RNA TNNI2-ACTA1 V1

Chimeric RNA was considered a special marker of cancer. However, recent studies have demonstrated that chimeric RNAs also exist in non-cancerous cells and tissues. Here, we analyzed and predicted jointly 49 chimeric RNAs by Star-Fusion and FusionMap. One chimeric RNA, we named TNNI2-ACTA1, and its eight transcript variants were identified by reverse transcriptase–polymerase chain reaction. The overexpression of TNNI2-ACTA1 V1 inhibited the proliferation of porcine skeletal muscle satellite cells through down-regulating the mRNA expression levels of cell cycle–related genes cyclinD1. However, as parental genes, there is no such effect in the TNNI2 and ACTA1. To explore the underlying mechanism for this phenomenon, we used RNA-seq to profile the transcriptomes of PSCs with overexpression. Compared with the negative control group, 1,592 differentially expressed genes (DEGs) were upregulated and 1,077 DEGs downregulated in TNNI2 group; 1,226 DEGs were upregulated and 902 DEGs downregulated in ACTA1 group; and 13 DEGs were upregulated and 16 DEGs downregulated in TNNI2-ACTA1 V1 group, respectively. Compared with the parental gene groups, three specific genes were enriched in the TNNI2-ACTA1 V1 group (NCOA3, Radixin, and DDR2). These three genes may be the key to TNNI2-ACTA1 V1 regulating cell proliferation. Taken together, our study explores the role of chimeric RNAs in normal tissues. In addition, our study as the first research provides the foundation for the mechanism of chimeric RNAs regulating porcine skeletal muscle growth.

The Fusion of CLEC12A and MIR223HG Arises from a trans-Splicing Event in Normal and Transformed Human Cells

Chimeric RNAs are often associated with chromosomal rearrangements in cancer. In addition, they are also widely detected in normal tissues, contributing to transcriptomic complexity. Despite their prevalence, little is known about the characteristics and functions of chimeric RNAs. Here, we examine the genetic structure and biological roles of CLEC12A-MIR223HG, a novel chimeric transcript produced by the fusion of the cell surface receptor CLEC12A and the miRNA-223 host gene (MIR223HG), first identified in chronic myeloid leukemia (CML) patients. Surprisingly, we observed that CLEC12A-MIR223HG is not just expressed in CML, but also in a variety of normal tissues and cell lines. CLEC12A-MIR223HG expression is elevated in pro-monocytic cells resistant to chemotherapy and during monocyte-to-macrophage differentiation. We observed that CLEC12A-MIR223HG is a product of trans-splicing rather than a chromosomal rearrangement and that transcriptional activation of CLEC12A with the CRISPR/Cas9 Synergistic Activation Mediator (SAM) system increases CLEC12A-MIR223HG expression. CLEC12A-MIR223HG translates into a chimeric protein, which largely resembles CLEC12A but harbours an altered C-type lectin domain altering key disulphide bonds. These alterations result in differences in post-translational modifications, cellular localization, and protein-protein interactions. Taken together, our observations support a possible involvement of CLEC12A-MIR223HG in the regulation of CLEC12A function. Our workflow also serves as a template to study other uncharacterized chimeric RNAs.

Gene fusions in tumourigenesis with particular reference to ovarian cancer

Gene fusion, a genomic event that generates a novel gene from two independent genes, has long been known to be implicated in tumourigenesis and cancer progression. It has thus served as a diagnostic and prognostic biomarker in cancer, as well as an ideal therapeutic target in cancer therapy. Gene fusion can arise from chromosomal rearrangement and alternative splicing of transcripts, resulting in deregulation of proto-oncogenes or creation of an oncogenic novel gene. Largely facilitated by next generation sequencing technologies, a plethora of novel gene fusions have been identified in a variety of cancers, which leaves us the challenge of functionally characterising these candidate gene fusions. In this review, we summarise the molecular mechanisms, the oncogenic consequences and the therapeutic implications of verified gene fusions. We also discuss recent studies on gene fusions in both common and rare subtypes of ovarian tumours and how these findings can be translated to cancer therapies to benefit patients carrying these gene fusions.

Emerging Role of Chimeric RNAs in Cell Plasticity and Adaptive Evolution of Cancer Cells

Gene fusions can give rise to somatic alterations in cancers. Fusion genes have the potential to create chimeric RNAs, which can generate the phenotypic diversity of cancer cells, and could be associated with novel molecular functions related to cancer cell survival and proliferation. The expression of chimeric RNAs in cancer cells might impact diverse cancer-related functions, including loss of apoptosis and cancer cell plasticity, and promote oncogenesis. Due to their recurrence in cancers and functional association with oncogenic processes, chimeric RNAs are considered biomarkers for cancer diagnosis. Several recent studies demonstrated that chimeric RNAs could lead to the generation of new functionality for the resistance of cancer cells against drug therapy. Therefore, targeting chimeric RNAs in drug resistance cancer could be useful for developing precision medicine. So, understanding the functional impact of chimeric RNAs in cancer cells from an evolutionary perspective will be helpful to elucidate cancer evolution, which could provide a new insight to design more effective therapies for cancer patients in a personalized manner.

Identification of the cross-strand chimeric RNAs generated by fusions of bi-directional transcripts

A major part of the transcriptome complexity is attributed to multiple types of DNA or RNA fusion events, which take place within a gene such as alternative splicing or between different genes such as DNA rearrangement and trans-splicing. In the present study, using the RNA deep sequencing data, we systematically survey a type of non-canonical fusions between the RNA transcripts from the two opposite DNA strands. We name the products of such fusion events cross-strand chimeric RNA (cscRNA). Hundreds to thousands of cscRNAs can be found in human normal tissues, primary cells, and cancerous cells, and in other species as well. Although cscRNAs exhibit strong tissue-specificity, our analysis identifies thousands of recurrent cscRNAs found in multiple different samples. cscRNAs are mostly originated from convergent transcriptions of the annotated genes and their anti-sense DNA. The machinery of cscRNA biogenesis is unclear, but the cross-strand junction events show some features related to RNA splicing. The present study is a comprehensive survey of the non-canonical cross-strand RNA junction events, a resource for further characterization of the originations and functions of the cscRNAs.

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

MOTIVATION

Current fusion detection tools use diverse calling approaches and provide varying results, making selection of the appropriate tool challenging. Ensemble fusion calling techniques appear promising; however, current options have limited accessibility and function.

RESULTS

MetaFusion is a flexible meta-calling tool that amalgamates outputs from any number of fusion callers. Individual caller results are standardized by conversion into the new file type Common Fusion Format (CFF). Calls are annotated, merged using graph clustering, filtered, and ranked to provide a final output of high confidence candidates. MetaFusion consistently achieves higher precision and recall than individual callers on real and simulated datasets, and reaches up to 100% precision, indicating that ensemble calling is imperative for high confidence results. MetaFusion uses FusionAnnotator to annotate calls with information from cancer fusion databases, and is provided with a benchmarking toolkit to calibrate new callers.

AVAILABILITY

MetaFusion is freely available at https://github.com/ccmbioinfo/MetaFusion.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Interstitial Deletions Generating Fusion Genes

A fusion gene is the physical juxtaposition of two different genes resulting in a structure consisting of the head of one gene and the tail of the other. Gene fusion is often a primary neoplasia-inducing event in leukemias, lymphomas, solid malignancies as well as benign tumors. Knowledge about fusion genes is crucial not only for our understanding of tumorigenesis, but also for the diagnosis, prognostication, and treatment of cancer. Balanced chromosomal rearrangements, in particular translocations and inversions, are the most frequent genetic events leading to the generation of fusion genes. In the present review, we summarize the existing knowledge on chromosome deletions as a mechanism for fusion gene formation. Such deletions are mostly submicroscopic and, hence, not detected by cytogenetic analyses but by array comparative genome hybridization (aCGH) and/or high throughput sequencing (HTS). They are found across the genome in a variety of neoplasias. As tumors are increasingly analyzed using aCGH and HTS, it is likely that more interstitial deletions giving rise to fusion genes will be found, significantly impacting our understanding and treatment of cancer.

Aberrant splicing in neuroblastoma generates RNA-fusion transcripts and provides vulnerability to spliceosome inhibitors

The paucity of recurrent mutations has hampered efforts to understand and treat neuroblastoma. Alternative splicing and splicing-dependent RNA-fusions represent mechanisms able to increase the gene product repertoire but their role in neuroblastoma remains largely unexplored. Here we investigate the presence and possible roles of aberrant splicing and splicing-dependent RNA-fusion transcripts in neuroblastoma. In addition, we attend to establish whether the spliceosome can be targeted to treat neuroblastoma. Through analysis of RNA-sequenced neuroblastoma we show that elevated expression of splicing factors is a strong predictor of poor clinical outcome. Furthermore, we identified >900 primarily intrachromosomal fusions containing canonical splicing sites. Fusions included transcripts from well-known oncogenes, were enriched for proximal genes and in chromosomal regions commonly gained or lost in neuroblastoma. As a proof-of-principle that these fusions can generate altered gene products, we characterized a ZNF451-BAG2 fusion, producing a truncated BAG2-protein which inhibited retinoic acid induced differentiation. Spliceosome inhibition impeded neuroblastoma fusion expression, induced apoptosis and inhibited xenograft tumor growth. Our findings elucidate a splicing-dependent mechanism generating altered gene products in neuroblastoma and show that the spliceosome is a potential target for clinical intervention.

Androgen-Driven Fusion Genes and Chimeric Transcripts in Prostate Cancer

Androgens are steroid hormones governing the male reproductive development and function. As such, androgens and the key mediator of their effects, androgen receptor (AR), have a leading role in many diseases. Prostate cancer is a major disease where AR and its transcription factor function affect a significant number of patients worldwide. While disease-related AR-driven transcriptional programs are connected to the presence and activity of the receptor itself, also novel modes of transcriptional regulation by androgens are exploited by cancer cells. One of the most intriguing and ingenious mechanisms is to bring previously unconnected genes under the control of AR. Most often this occurs through genetic rearrangements resulting in fusion genes where an androgen-regulated promoter area is combined to a protein-coding area of a previously androgen-unaffected gene. These gene fusions are distinctly frequent in prostate cancer compared to other common solid tumors, a phenomenon still requiring an explanation. Interestingly, also another mode of connecting androgen regulation to a previously unaffected gene product exists via transcriptional read-through mechanisms. Furthermore, androgen regulation of fusion genes and transcripts is not linked to only protein-coding genes. Pseudogenes and non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs) can also be affected by androgens and de novo functions produced. In this review, we discuss the prevalence, molecular mechanisms, and functional evidence for androgen-regulated prostate cancer fusion genes and transcripts. We also discuss the clinical relevance of especially the most common prostate cancer fusion gene TMPRSS2-ERG, as well as present open questions of prostate cancer fusions requiring further investigation.

Fusion Genes and RNAs in Cancer Development

Fusion RNAs are a hallmark of some cancers. They result either from chromosomal rearrangements or from splicing mechanisms that are non-chromosomal rearrangements. Chromosomal rearrangements that result in gene fusions are particularly prevalent in sarcomas and hematopoietic malignancies; they are also common in solid tumors. The splicing process can also give rise to more complex RNA patterns in cells. Gene fusions frequently affect tyrosine kinases, chromatin regulators, or transcription factors, and can cause constitutive activation, enhancement of downstream signaling, and tumor development, as major drivers of oncogenesis. In addition, some fusion RNAs have been shown to function as noncoding RNAs and to affect cancer progression. Fusion genes and RNAs will therefore become increasingly important as diagnostic and therapeutic targets for cancer development. Here, we discuss the function, biogenesis, detection, clinical relevance, and therapeutic implications of oncogenic fusion genes and RNAs in cancer development. Further understanding the molecular mechanisms that regulate how fusion RNAs form in cancers is critical to the development of therapeutic strategies against tumorigenesis.

Affinity Captured Urinary Extracellular Vesicles Provide mRNA and miRNA Biomarkers for Improved Accuracy of Prostate Cancer Detection: A Pilot Study

Serum prostate-specific antigen (sPSA) testing has helped to increase early detection of and decrease mortality from prostate cancer. However, since sPSA lacks specificity, an invasive prostate tissue biopsy is required to confirm cancer diagnosis. Using urinary extracellular vesicles (EVs) as a minimally invasive biomarker source, our goal was to develop a biomarker panel able to distinguish prostate cancer from benign conditions with high accuracy. We enrolled 56 patients in our study, 28 negative and 28 positive for cancer based on tissue biopsy results. Using our Vn96 peptide affinity method, we isolated EVs from post-digital rectal exam urines and used quantitative polymerase chain reaction to measure several mRNA and miRNA targets. We identified a panel of seven mRNA biomarkers whose expression ratio discriminated non-cancer from cancer with an area under the curve (AUC) of 0.825, sensitivity of 75% and specificity of 84%. We also identified two miRNAs whose combined score yielded an AUC of 0.744. A model pairing the seven mRNA and two miRNA panels yielded an AUC of 0.843, sensitivity of 79% and specificity of 89%. Addition of EV-derived PCA3 levels and clinical characteristics to the biomarker model further improved test accuracy. An AUC of 0.955, sensitivity of 86% and specificity of 93% were obtained. Hence, Vn96-isolated urinary EVs are a clinically applicable and minimally invasive source of mRNA and miRNA biomarkers with potential to improve on the accuracy of prostate cancer screening and diagnosis.

Fusion transcript detection using spatial transcriptomics

BACKGROUND

Fusion transcripts are involved in tumourigenesis and play a crucial role in tumour heterogeneity, tumour evolution and cancer treatment resistance. However, fusion transcripts have not been studied at high spatial resolution in tissue sections due to the lack of full-length transcripts with spatial information. New high-throughput technologies like spatial transcriptomics measure the transcriptome of tissue sections on almost single-cell level. While this technique does not allow for direct detection of fusion transcripts, we show that they can be inferred using the relative poly(A) tail abundance of the involved parental genes.

METHOD

We present a new method STfusion, which uses spatial transcriptomics to infer the presence and absence of poly(A) tails. A fusion transcript lacks a poly(A) tail for the 5' gene and has an elevated number of poly(A) tails for the 3' gene. Its expression level is defined by the upstream promoter of the 5' gene. STfusion measures the difference between the observed and expected number of poly(A) tails with a novel C-score.

RESULTS

We verified the STfusion ability to predict fusion transcripts on HeLa cells with known fusions. STfusion and C-score applied to clinical prostate cancer data revealed the spatial distribution of the cis-SAGe SLC45A3-ELK4 in 12 tissue sections with almost single-cell resolution. The cis-SAGe occurred in disease areas, e.g. inflamed, prostatic intraepithelial neoplastic, or cancerous areas, and occasionally in normal glands.

CONCLUSIONS

STfusion detects fusion transcripts in cancer cell line and clinical tissue data, and distinguishes chimeric transcripts from chimeras caused by trans-splicing events. With STfusion and the use of C-scores, fusion transcripts can be spatially localised in clinical tissue sections on almost single cell level.

Chimeric RNAs in cancer

Chimeric RNAs are hybrid transcripts containing exons from two separate genes. Chimeric RNAs are traditionally considered to be transcribed from fusion genes caused by chromosomal rearrangement. These canonical chimeric RNAs are well characterized to be expressed in a cancer-unique pattern and/or act as oncogene products. However, benefited by the development of advanced deep sequencing technologies, novel types of non-canonical chimeric RNAs have been discovered to be generated from intergenic splicing without genomic aberrations. They can be formed through trans-splicing or cis-splicing between adjacent genes (cis-SAGe) mechanisms. Non-canonical chimeric RNAs are widely detected in normal physiology, although several have been shown to have a cancer-specific expression pattern. Further studies have indicated that some of them play fundamental roles in controlling cell growth and motility, and may have functions independent of the parental genes. These discoveries are unveiling a new layer of the functional transcriptome and are also raising the possibility of utilizing non-canonical chimeric RNAs as cancer diagnostic markers and therapeutic targets. In this chapter, we will overview different categories of chimeric RNAs and their expression in various types of cancerous and normal samples. Acknowledging that chimeric RNAs are not unique to cancer, we will discuss both bioinformatic and biological methods to identify credible cancer-specific chimeric RNAs. Furthermore, we will describe downstream methods to explore their molecular processing mechanisms and potential functions. A better understanding of the biogenesis mechanisms and functional products of cancer-specific chimeric RNAs will pave ways for the development of novel cancer biomarkers and therapeutic targets.

Evidence of constraint in the 3D genome for trans-splicing in human cells

Fusion transcripts are commonly found in eukaryotes, and many aberrant fusions are associated with severe diseases, including cancer. One class of fusion transcripts is generated by joining separate transcripts through trans-splicing. However, the mechanism of trans-splicing in mammals remains largely elusive. Here we showed evidence to support an intuitive hypothesis that attributes trans-sphcing to the spatial proximity between premature transcripts. A novel trans-splicing detection tool (TSD) was developed to reliably identify intra-chromosomal trans-splicing events (iTSEs) from RNA-seq data. TSD can maintain a remarkable balance between sensitivity and accuracy, thus distinguishing it from most state-of-the-art tools. The accuracy of TSD was experimentally demonstrated by excluding potential false discovery from mosaic genome or template switching during PCR. We showed that iTSEs identified by TSD were frequently found between genomic regulatory elements, which are known to be more prone to interact with each other. Moreover, iTSE sites may be more physically adjacent to each other than random control in the tested human lymphoblastoid cell line according to Hi-C data. Our results suggest that trans-splicing and 3D genome architecture may be coupled in mammals and that our pipeline, TSD, may facilitate investigations of trans-splicing on a systematic and accurate level previously thought impossible.

The landscape of chimeric RNAs in non-diseased tissues and cells

Chimeric RNAs and their encoded proteins have been traditionally viewed as unique features of neoplasia, and have been used as biomarkers and therapeutic targets for multiple cancers. Recent studies have demonstrated that chimeric RNAs also exist in non-cancerous cells and tissues, although large-scale, genome-wide studies of chimeric RNAs in non-diseased tissues have been scarce. Here, we explored the landscape of chimeric RNAs in 9495 non-diseased human tissue samples of 53 different tissues from the GTEx project. Further, we established means for classifying chimeric RNAs, and observed enrichment for particular classifications as more stringent filters are applied. We experimentally validated a subset of chimeric RNAs from each classification and demonstrated functional relevance of two chimeric RNAs in non-cancerous cells. Importantly, our list of chimeric RNAs in non-diseased tissues overlaps with some entries in several cancer fusion databases, raising concerns for some annotations. The data from this study provides a large repository of chimeric RNAs present in non-diseased tissues, which can be used as a control dataset to facilitate the identification of true cancer-specific chimeras.

Pan-Cancer Analysis Reveals the Diverse Landscape of Novel Sense and Antisense Fusion Transcripts

Gene fusions that contribute to oncogenicity can be explored for identifying cancer biomarkers and potential drug targets. To investigate the nature and distribution of fusion transcripts in cancer, we examined the transcriptome data of about 9,000 primary tumors from 33 different cancers in TCGA (The Cancer Genome Atlas) along with cell line data from CCLE (Cancer Cell Line Encyclopedia) using ChimeRScope, a novel fusion detection algorithm. We identified several fusions with sense (canonical, 39%) or antisense (non-canonical, 61%) transcripts recurrent across cancers. The majority of the recurrent non-canonical fusions found in our study are novel, unexplored, and exhibited highly variable profiles across cancers, with breast cancer and glioblastoma having the highest and lowest rates, respectively. Overall, 4,344 recurrent fusions were identified from TCGA in this study, of which 70% were novel. Additional analysis of 802 tumor-derived cell line transcriptome data across 20 cancers revealed significant variability in recurrent fusion profiles between primary tumors and corresponding cell lines. A subset of canonical and non-canonical fusions was validated by examining the structural variation evidence in whole-genome sequencing (WGS) data or by Sanger sequencing of fusion junctions. Several recurrent fusion genes identified in our study show promise for drug repurposing in basket trials and present opportunities for mechanistic studies.

Computational Detection of Known Pathogenic Gene Fusions in a Normal Tissue Database and Implications for Genetic Disease Research

Several recent studies have demonstrated the utility of RNA-Seq in the diagnosis of rare inherited disease. Diagnostic rates 35% higher than those previously achievable with DNA-Seq alone have been attained. These studies have primarily profiled gene expression and splicing defects, however, some have also shown that fusion transcripts are diagnostic or phenotypically relevant in patients with constitutional disorders. Fusion transcripts have traditionally been studied as oncogenic phenomena, with relevance only to cancer testing. Consequently, fusion detection algorithms were biased toward the detection of well-known oncogenic fusions, hindering their application to rare Mendelian genetic disease studies. A recent methodology published by the authors successfully tailored a traditional algorithm to the detection of pathogenic fusion events in inherited disease. A key mechanism of decreasing false positive or biologically benign events was comparison to a database of events detected in normal tissues. This approach is akin to population frequency-based filtering of genetic variants. It is predicated on the idea that pathogenic fusion transcripts are absent from normal tissue. We report on an analysis of RNA-Seq data from the genotype-tissue expression (GTEx) project in which known pathogenic fusions are computationally detected at low levels in normal tissues unassociated with the disease phenotype. Examples include archetypal cancer fusion transcripts, as well as fusions responsible for rare inherited disease. We consider potential explanations for the detectability of such transcripts and discuss the bearing such results have on the future profiling of genetic disease patients for pathogenic gene fusions.

Biochemical characterization of mono ADP ribosyl transferase activity of human sirtuin SIRT7 and its regulation

SIRT7, an epigenetic modulator is related to several important cellular processes like aging, genome stability, and metabolism. The mechanistic and regulatory aspect of this enzyme needs to be explored. SIRT7 contains a conserved catalytic core with long flanking N- and C-terminal extensions. We find that the N terminus is involved in substrate binding, thus also in its dual enzyme activity i.e. deacetylation and ADP ribosylation. The C-terminus is not essential for its catalysis. Mutation of certain residues at the active site suggests that mono ADP-ribosylation and deacetylation are two distinct activities of SIRT7. In this study, we also find that the SIRT7 enzyme can specifically transfer a single moiety of ADP ribose on other nuclear proteins, with a preference for NAD⁺. For this, the ADPr transfer follows the enzymatic reaction mechanism. Nicotinamide and certain metal ions have a significant negative effect on this mono ADP ribosylation process. A comparison of these dual activities suggests SIRT7's preference for the mono ADPr transfer over its deacetylation of H3K18Ac. Mono ADP ribosylation in cells is often linked to different metabolic disease conditions. This kind of modification of transcription factors, p53 and ELK4 by SIRT7 may play a key role in maintaining the tumor phenotype. Thus, SIRT7 becomes an important therapeutic hotspot for drug designing against several diseases. Finally, we can also relate SIRT7 to the DNA repair process through ADP ribosylation of one of its key players, PARP1. Here, SIRT7 positively regulates the PARP1 activity.

Fusion Transcripts of Adjacent Genes: New Insights into the World of Human Complex Transcripts in Cancer

The awareness of genome complexity brought a radical approach to the study of transcriptome, opening eyes to single RNAs generated from two or more adjacent genes according to the present consensus. This kind of transcript was thought to originate only from chromosomal rearrangements, but the discovery of readthrough transcription opens the doors to a new world of fusion RNAs. In the last years many possible intergenic cis-splicing mechanisms have been proposed, unveiling the origins of transcripts that contain some exons of both the upstream and downstream genes. In some cases, alternative mechanisms, such as trans-splicing and transcriptional slippage, have been proposed. Five databases, containing validated and predicted Fusion Transcripts of Adjacent Genes (FuTAGs), are available for the scientific community. A comparative analysis revealed that two of them contain the majority of the results. A complete analysis of the more widely characterized FuTAGs is provided in this review, including their expression pattern in normal tissues and in cancer. Gene structure, intergenic splicing patterns and exon junction sequences have been determined and here reported for well-characterized FuTAGs. The available functional data and the possible roles in cancer progression are discussed.

Gene fusions and chimeric RNAs, and their implications in cancer

Gene fusions are appreciated as ideal cancer biomarkers and therapeutic targets. Chimeric RNAs are traditionally thought to be products of gene fusions, and thus, also cancer-specific. Recent research has demonstrated that chimeric RNAs can be generated by intergenic splicing in the absence of gene fusion, and such chimeric RNAs are also found in normal physiology. These new findings challenge the traditional theory of chimeric RNAs exclusivity to cancer, and complicates use of chimeric RNAs in cancer detection. Here, we provide an overview of gene fusions and chimeric RNAs, and emphasize their differences. We note that gene fusions are able to generate chimeric RNAs in accordance with the central dogma of biology, and that chimeric RNAs may also be able to influence the generation of the gene fusions per the “horse before the cart” hypothesis. We further expand upon the “horse before the cart” hypothesis, summarizing current evidence in support of the theory and exploring its potential impact on the field.

Molecular profiling stratifies diverse phenotypes of treatment-refractory metastatic castration-resistant prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease with diverse drivers of disease progression and mechanisms of therapeutic resistance. We conducted deep phenotypic characterization of CRPC metastases and patient-derived xenograft (PDX) lines using whole genome RNA sequencing, gene set enrichment analysis and immunohistochemistry. Our analyses revealed five mCRPC phenotypes based on the expression of well-characterized androgen receptor (AR) or neuroendocrine (NE) genes: (i) AR-high tumors (ARPC), (ii) AR-low tumors (ARLPC), (iii) amphicrine tumors composed of cells co-expressing AR and NE genes (AMPC), (iv) double-negative tumors (i.e. AR-/NE-; DNPC) and (v) tumors with small cell or NE gene expression without AR activity (SCNPC). RE1-silencing transcription factor (REST) activity, which suppresses NE gene expression, was lost in AMPC and SCNPC PDX models. However, knockdown of REST in cell lines revealed that attenuated REST activity drives the AMPC phenotype but is not sufficient for SCNPC conversion. We also identified a subtype of DNPC tumors with squamous differentiation and generated an encompassing 26-gene transcriptional signature that distinguished the five mCRPC phenotypes. Together, our data highlight the central role of AR and REST in classifying treatment-resistant mCRPC phenotypes. These molecular classifications could potentially guide future therapeutic studies and clinical trial design.

Integrative transcriptome sequencing reveals extensive alternative trans-splicing and cis-backsplicing in human cells

Transcriptionally non-co-linear (NCL) transcripts can originate from trans-splicing (trans-spliced RNA; 'tsRNA') or cis-backsplicing (circular RNA; 'circRNA'). While numerous circRNAs have been detected in various species, tsRNAs remain largely uninvestigated. Here, we utilize integrative transcriptome sequencing of poly(A)- and non-poly(A)-selected RNA-seq data from diverse human cell lines to distinguish between tsRNAs and circRNAs. We identified 24,498 NCL events and found that a considerable proportion (20-35%) of them arise from both tsRNAs and circRNAs, representing extensive alternative trans-splicing and cis-backsplicing in human cells. We show that sequence generalities of exon circularization are also observed in tsRNAs. Recapitulation of NCL RNAs further shows that inverted Alu repeats can simultaneously promote the formation of tsRNAs and circRNAs. However, tsRNAs and circRNAs exhibit quite different, or even opposite, expression patterns, in terms of correlation with the expression of their co-linear counterparts, expression breadth/abundance, transcript stability, and subcellular localization preference. These results indicate that tsRNAs and circRNAs may play different regulatory roles and analysis of NCL events should take the joint effects of different NCL-splicing types and joint effects of multiple NCL events into consideration. This study describes the first transcriptome-wide analysis of trans-splicing and cis-backsplicing, expanding our understanding of the complexity of the human transcriptome.

Understanding the 3D genome: Emerging impacts on human disease

Recent burst of new technologies that allow for quantitatively delineating chromatin structure has greatly expanded our understanding of how the genome is organized in the three-dimensional (3D) space of the nucleus. It is now clear that the hierarchical organization of the eukaryotic genome critically impacts nuclear activities such as transcription, replication, as well as cellular and developmental events such as cell cycle, cell fate decision and embryonic development. In this review, we discuss new insights into how the structural features of the 3D genome hierarchy are established and maintained, how this hierarchy undergoes dynamic rearrangement during normal development and how its perturbation will lead to human disease, highlighting the accumulating evidence that links the diverse 3D genome architecture components to a multitude of human diseases and the emerging mechanisms by which 3D genome derangement causes disease phenotypes.

ceRNA network analysis reveals prognostic markers for glioblastoma

Glioblastoma (GBM) is a common aggressive cancer that originates in the brain, which has a poor prognosis. It is therefore crucial to understand its underlying genetic mechanisms in order to develop novel therapies. The present study aimed to identify some prognostic markers and candidate therapeutic targets for GBM. To do so, RNA expression levels in tumor and normal tissues were compared by microarray analysis. The differential expression of RNAs in normal and cancer tissues was analyzed, and a competing endogenous RNA (ceRNA) network was constructed for pathway analysis. The results revealed that RNA expression patterns were considerably different between normal and tumor samples. A ceRNA network was therefore constructed with the differentially expressed RNAs. ETS variant 5 (ETV5), myocyte enhancer factor 2C and ETS transcription factor (ELK4) were considerably enriched in the significant pathway of ‘transcriptional misregulation in cancer’. In addition, prognostic analysis demonstrated that ETV5 and ELK4 expression levels were associated with the survival time of patients with GBM. These results suggested that ELK4 and ETV5 may be prognostic markers for GBM, and that their microRNAs may be candidate therapeutic targets.

Interfering Expression of Chimeric Transcript SEPT7P2-PSPH Promotes Cell Proliferation in Patients with Nasopharyngeal Carcinoma

Introduction

Nasopharyngeal carcinoma (NPC) is a distinct type of head and neck cancer which is mostly prevalent in southern China. The development of NPC involves accumulation of multiple genetic changes. Chromosomal translocation is always thought to be accompanied with the fusion chimeric products. To data, the role of the fusion chimeric transcript remains obscure.

Materials and Methods

We performed RNA sequencing to detect the fusion genes in ten NPC tissues. Sanger sequencing and quantitative RT-PCR were used to measure the level of the fusion chimeric transcript in NPC tissues and cell lines. The functional experiments such as CCK8 assay, colony formation, and migration/invasion were conducted to analyze the role of this transcript in NPC in vitro.

Results

We demonstrated that the chimeric transcript SEPT7P2-PSPH was formed by trans-splicing of adjacent genes in the absence of chromosomal rearrangement and observed in both NPC patients and cell lines in parallel. Low-expression of the SEPT7P2-PSPH chimeric transcript induced the protein expression of PSPH and promoted cell proliferation, metastasis/invasion, and transforming ability in vitro.

Conclusions

Our findings indicate that the chimeric transcript SEPT7P2-PSPH is a product of trans-splicing of two adjacent genes and might be a tumor suppressor gene, potentially having the role of anticancer activity.