Recurrent chimeric fusion RNAs in non-cancer tissues and cells

RNA Dysregulation: An Expanding Source of Cancer Immunotherapy Targets

Cancer transcriptomes frequently exhibit RNA dysregulation. As the resulting aberrant transcripts may be translated into cancer-specific proteins, there is growing interest in exploiting RNA dysregulation as a source of tumor antigens (TAs) and thus novel immunotherapy targets. Recent advances in high-throughput technologies and rapid accumulation of multiomic cancer profiling data in public repositories have provided opportunities to systematically characterize RNA dysregulation in cancer and identify antigen targets for immunotherapy. However, given the complexity of cancer transcriptomes and proteomes, important conceptual and technological challenges exist. Here, we highlight the expanding repertoire of TAs arising from RNA dysregulation and introduce multiomic and big data strategies for identifying optimal immunotherapy targets. We discuss extant barriers for translating these targets into effective therapies as well as the implications for future research.

Chimeric RNA ASTN2-PAPPAas aggravates tumor progression and metastasis in human esophageal cancer

Transcription-induced chimeric RNAs are an emerging area of research into molecular signatures for disease biomarker and therapeutic target development. Despite their importance, little is known for chimeric RNAs-relevant roles and the underlying mechanisms for cancer pathogenesis and progression. Here we describe a unique ASTN2-PAPPA_antisense chimeric RNA (A-P_aschiRNA) that could be the first reported chimeric RNA derived from the splicing of exons and intron antisense of two neighboring genes, respectively. Aberrant A-P_aschiRNA level in ESCC tissues was associated with tumor progression and patients' outcome. In vitro and in vivo studies demonstrated that A-P_aschiRNA aggravated ESCC metastasis and enhanced stemness through modulating OCT4. Mechanistic studies demonstrated that ERK5-mediated non-canonical PAF1 activity was required for A-P_aschiRNA-induced cancer malignancy. The study defined an undocumented function of chimeric RNAs in aggravating cancer stemness and metastasis.

Landscape of Chimeric RNAs in Non-Cancerous Cells

Gene fusions and their products (RNA and protein) have been traditionally recognized as unique features of cancer cells and are used as ideal biomarkers and drug targets for multiple cancer types. However, recent studies have demonstrated that chimeric RNAs generated by intergenic alternative splicing can also be found in normal cells and tissues. In this study, we aim to identify chimeric RNAs in different non-neoplastic cell lines and investigate the landscape and expression of these novel candidate chimeric RNAs. To do so, we used HEK-293T, HUVEC, and LO2 cell lines as models, performed paired-end RNA sequencing, and conducted analyses for chimeric RNA profiles. Several filtering criteria were applied, and the landscape of chimeric RNAs was characterized at multiple levels and from various angles. Further, we experimentally validated 17 chimeric RNAs from different classifications. Finally, we examined a number of validated chimeric RNAs in different cancer and non-cancer cells, including blood from healthy donors, and demonstrated their ubiquitous expression pattern.

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.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Factorial study of the RNA-seq computational workflow identifies biases as technical gene signatures

RNA-seq is a modular experimental and computational approach aiming in identifying and quantifying RNA molecules. The modularity of the RNA-seq technology enables adaptation of the protocol to develop new ways to explore RNA biology, but this modularity also brings forth the importance of methodological thoroughness. Liberty of approach comes with the responsibility of choices, and such choices must be informed. Here, we present an approach that identifies gene group-specific quantification biases in current RNA-seq software and references by processing datasets using diverse RNA-seq computational pipelines, and by decomposing these expression datasets with an independent component analysis matrix factorization method. By exploring the RNA-seq pipeline using this systemic approach, we identify genome annotations as a design choice that affects to the same extent quantification results as does the choice of aligners and quantifiers. We also show that the different choices in RNA-seq methodology are not independent, identifying interactions between genome annotations and quantification software. Genes were mainly affected by differences in their sequence, by overlapping genes and genes with similar sequence. Our approach offers an explanation for the observed biases by identifying the common features used differently by the software and references, therefore providing leads for the betterment of RNA-seq methodology.

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.

Performances of Targeted RNA Sequencing for the Analysis of Fusion Transcripts, Gene Mutation, and Expression in Hematological Malignancies

RNA sequencing holds great promise to improve the diagnostic of hematological malignancies, because this technique enables to detect fusion transcripts, to look for somatic mutations in oncogenes, and to capture transcriptomic signatures of nosological entities. However, the analytical performances of targeted RNA sequencing have not been extensively described in diagnostic samples. Using a targeted panel of 1385 cancer-related genes in a series of 100 diagnosis samples and 8 controls, we detected all the already known fusion transcripts and also discovered unknown and/or unsuspected fusion transcripts in 12 samples. Regarding the analysis of transcriptomic profiles, we show that targeted RNA sequencing is performant to discriminate acute lymphoblastic leukemia entities driven by different oncogenic translocations. Additionally, we show that 86% of the mutations identified at the DNA level are also detectable at the messenger RNA (mRNA) level, except for nonsense mutations that are subjected to mRNA decay. We conclude that targeted RNA sequencing might improve the diagnosis of hematological malignancies. Standardization of the preanalytical steps and further refinements of the panel design and of the bioinformatical pipelines will be an important step towards its use in standard diagnostic procedures.

A Roadmap Toward the Definition of Actionable Tumor-Specific Antigens

The search for tumor-specific antigens (TSAs) has considerably accelerated during the past decade due to the improvement of proteogenomic detection methods. This provides new opportunities for the development of novel antitumoral immunotherapies to mount an efficient T cell response against one or multiple types of tumors. While the identification of mutated antigens originating from coding exons has provided relatively few TSA candidates, the possibility of enlarging the repertoire of targetable TSAs by looking at antigens arising from non-canonical open reading frames opens up interesting avenues for cancer immunotherapy. In this review, we outline the potential sources of TSAs and the mechanisms responsible for their expression strictly in cancer cells. In line with the heterogeneity of cancer, we propose that discrete families of TSAs may be enriched in specific cancer types.

Fusion genes as biomarkers in pediatric cancers: A review of the current state and applicability in diagnostics and personalized therapy

The incidence of pediatric cancers is rising steadily across the world, along with the challenges in understanding the molecular mechanisms and devising effective therapeutic strategies. Pediatric cancers are presented with diverse molecular characteristics and more distinct subtypes when compared to adult cancers. Recent studies on the genomic landscape of pediatric cancers using next-generation sequencing (NGS) approaches have redefined this field by providing better subtype characterization and novel actionable targets. Since early identification and personalized treatment strategies influence therapeutic outcomes, survival, and quality of life in pediatric cancer patients, the quest for actionable biomarkers is of great value in this field. Fusion genes that are prevalent and recurrent in several pediatric cancers are ideally suited in this context due to their disease-specific occurrence. In this review, we explore the current status of fusion genes in pediatric cancer subtypes and their use as biomarkers for diagnosis and personalized therapy. We discuss the technological advancements made in recent years in NGS sequencing and their impact on fusion detection algorithms that have revolutionized this field. Finally, we also discuss the advantages of pairing liquid biopsy protocols for fusion detection and their eventual use in diagnosis and treatment monitoring.

DEEPrior: a deep learning tool for the prioritization of gene fusions

SUMMARY

In the last decade, increasing attention has been paid to the study of gene fusions. However, the problem of determining whether a gene fusion is a cancer driver or just a passenger mutation is still an open issue. Here we present DEEPrior, an inherently flexible deep learning tool with two modes (Inference and Retraining). Inference mode predicts the probability of a gene fusion being involved in an oncogenic process, by directly exploiting the amino acid sequence of the fused protein. Retraining mode allows to obtain a custom prediction model including new data provided by the user.

AVAILABILITY AND IMPLEMENTATION

Both DEEPrior and the protein fusions dataset are freely available from GitHub at (https://github.com/bioinformatics-polito/DEEPrior). The tool was designed to operate in Python 3.7, with minimal additional libraries.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Evolution and structure of clinically relevant gene fusions in multiple myeloma

Multiple myeloma is a plasma cell blood cancer with frequent chromosomal translocations leading to gene fusions. To determine the clinical relevance of fusion events, we detect gene fusions from a cohort of 742 patients from the Multiple Myeloma Research Foundation CoMMpass Study. Patients with multiple clinic visits enable us to track tumor and fusion evolution, and cases with matching peripheral blood and bone marrow samples allow us to evaluate the concordance of fusion calls in patients with high tumor burden. We examine the joint upregulation of WHSC1 and FGFR3 in samples with t(4;14)-related fusions, and we illustrate a method for detecting fusions from single cell RNA-seq. We report fusions at MYC and a neighboring gene, PVT1, which are related to MYC translocations and associated with divergent progression-free survival patterns. Finally, we find that 4% of patients may be eligible for targeted fusion therapies, including three with an NTRK1 fusion.

Multiple myeloma is characterised by frequent gene fusions. Here, the authors use data from the Multiple Myeloma Research Foundation CoMMpass Study to further investigate fusion genes in this disease and their clinical relevance.

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.

Novel Gene Fusions in Glioblastoma Tumor Tissue and Matched Patient Plasma

Sequencing studies have provided novel insights into the heterogeneous molecular landscape of glioblastoma (GBM), unveiling a subset of patients with gene fusions. Tissue biopsy is highly invasive, limited by sampling frequency and incompletely representative of intra-tumor heterogeneity. Extracellular vesicle-based liquid biopsy provides a minimally invasive alternative to diagnose and monitor tumor-specific molecular aberrations in patient biofluids. Here, we used targeted RNA sequencing to screen GBM tissue and the matched plasma of patients (n = 9) for RNA fusion transcripts. We identified two novel fusion transcripts in GBM tissue and five novel fusions in the matched plasma of GBM patients. The fusion transcripts FGFR3-TACC3 and VTI1A-TCF7L2 were detected in both tissue and matched plasma. A longitudinal follow-up of a GBM patient with a FGFR3-TACC3 positive glioma revealed the potential of monitoring RNA fusions in plasma. In summary, we report a sensitive RNA-seq-based liquid biopsy strategy to detect RNA level fusion status in the plasma of GBM patients.

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.

GOLT1A-KISS1 fusion is associated with metastasis in adenoid cystic carcinomas

Genetic alterations can drive carcinogenesis. Numerous studies have shown that gene fusion is associated with cancer progression and could provide valuable biomarkers for clinical diagnosis or targets for cancer therapy. Adenoid cystic carcinoma (ACC) is a rare form of adenocarcinoma, characterized by frequent local recurrence and high rates of distant metastasis, ultimately resulting in low survival rates. Owing to the lack of effective therapeutic targets and limited biomarkers for diagnosis, a deeper understanding of the molecular basis of ACC is urgently needed. Here, we show that gene fusion is associated with ACC metastasis. We identified a metastasis suppressor KISS1 fused with a close-by gene, GOLT1A, in highly metastatic ACC cell lines and human specimens. Such fusion blocks KISS1 translation, but not transcription, by introducing 5' upstream open reading frames (uORFs) in the GOLT1A-KISS1 fusion transcript. Deletion of these uORFs rescued KISS1 expression and reduced invasion and migration of metastatic ACC cells. We also detected GOLT1A-KISS1 fusion transcripts in other types of highly metastatic cancer cell lines. Taken together, our results highlight the significance of this novel GOLT1A-KISS1 gene fusion in tumor metastasis and provide a valuable biomarker for clinical diagnosis and future therapeutic targeting of ACC.

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.

Analysis of fusion transcripts indicates widespread deregulation of snoRNAs and their host genes in breast cancer

Genomic rearrangements in cancer can join the sequences of two separate genes. Studies of such gene fusion events have mainly focused on identification of fusion proteins from the chimeric transcripts. We have previously investigated how fusions instead can affect the expression of intronic microRNA (miRNA) genes that are encoded within fusion gene partners. Here, we extend our analysis to small nucleolar RNAs (snoRNAs) that also are embedded within protein-coding or noncoding host genes. We found that snoRNA hosts are selectively enriched in fusion transcripts, like miRNA host genes, and that this enrichment is associated with all snoRNA classes. These structural changes may have functional consequences for the cell; proteins involved in the protein translation machinery are overrepresented among snoRNA host genes, a gene architecture assumed to be needed for closely coordinated expression of snoRNAs and host proteins. Our data indicate that this structure is frequently disrupted in cancer. We furthermore observed that snoRNA genes involved in fusions tend to associate with stronger promoters than the natural host, suggesting a mechanism that selects for snoRNA overexpression. In summary, we highlight a previously unexplored frequent structural change in cancer that affects important components of cellular physiology.

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.

Molecular variations in uterine carcinosarcomas identify therapeutic opportunities

OBJECTIVE

To perform comprehensive genomic profiling on a large cohort of patients with uterine carcinosarcomas to identify potential therapeutic targets.

METHODS

Molecular profiling was conducted on 168 retrospectively de-identified patients with uterine carcinosarcomas using the Caris Life Sciences platform. Specimens were evaluated for aberrations in protein expression by immunohistochemistry, DNA sequence mutation using a 592-gene next generation sequencing panel, copy number amplification using next generation sequencing or in situ hybridization, and fusion events using NextGen RNA sequencing. Tumor mutational load and microsatellite instability were also evaluated.

RESULTS

We identified 168 patients with uterine carcinosarcoma; median age of the cohort was 67 years. The most common mutations were observed in the following genes: TP53 (86%), PIK3CA (34%), FBXW7 (23%), PTEN (18%), KRAS (16%), PPP2R1A (10%). Tumor mutational load was low to moderate in most cases (50% and 45%, respectively). HER2/neu (ERBB2) was amplified in 9% of tumors. Immunohistochemistry protein expression was elevated in TOP2A (95%), TS (80%), PTEN (76%), and TUBB3 (66%). Mismatch repair deficiency was rare (4%).

CONCLUSIONS

Multiple somatic mutations and copy number alterations in genes that are therapeutic targets were identified in half of cases. Uterine carcinosarcomas represent an aggressive histology with limited treatment options and poor outcomes, and clinical trials are needed to validate new therapeutic targets.

Proteogenomic Characterization of Endometrial Carcinoma

We undertook a comprehensive proteogenomic characterization of 95 prospectively collected endometrial carcinomas, comprising 83 endometrioid and 12 serous tumors. This analysis revealed possible new consequences of perturbations to the p53 and Wnt/β-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways. An extensive genome-wide acetylation survey yielded insights into regulatory mechanisms linking Wnt signaling and histone acetylation. We also characterized aspects of the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, identify new molecular associations of potential mechanistic significance in the development of endometrial cancers, and suggest novel approaches for identifying potential therapeutic targets.

Fusion transcripts in normal human cortex increase with age and show distinct genomic features for single cells and tissues

Fusion transcripts can contribute to diversity of molecular networks in the human cortex. In this study, we explored the occurrence of fusion transcripts in normal human cortex along with single neurons and astrocytes. We identified 1305 non-redundant fusion events from 388 transcriptomes representing 59 human cortices and 329 single cells. Our results indicate while the majority of fusion transcripts in human cortex are intra-chromosomal (85%), events found in single neurons and astrocytes were primarily inter-chromosomal (80%). The number of fusions in single neurons was significantly higher than that in single astrocytes (p < 0.05), indicating fusion as a possible contributor towards transcriptome diversity in neuronal cells. The identified fusions were largely private and 4 specific recurring events were found both in cortex and in single neurons but not in astrocytes. We found a significant increase in the number of fusion transcripts in human brain with increasing age both in single cells and whole cortex (p < 0.0005 and < 0.005, respectively). This is likely one of the many possible contributors for the inherent plasticity of the adult brain. The fusion transcripts in fetal brain were enriched for genes for long-term depression; while those in adult brain involved genes enriched for long-term potentiation pathways. Our findings demonstrate fusion transcripts are naturally occurring phenomenon spanning across the health-disease continuum, and likely contribute to the diverse molecular network of human brain.

Detection of Fusion Genes Using a Targeted RNA Sequencing Panel in Gastrointestinal and Rare Cancers

Successful identification and targeting of oncogenic gene fusion is a major breakthrough in cancer treatment. Here, we investigate the therapeutic implications and feasibility of using a targeted RNA sequencing panel to identify fusion genes in gastrointestinal and rare cancers. From February through December 2017, patients with gastrointestinal, hepatobiliary, gynecologic, sarcoma, or rare cancers were recruited for a clinical sequencing project at Samsung Medical Center (NCT #02593578). The median age of the patients was 58 years (range, 31-81 years), and the male-to-female ratio was 1.3 : 1. A total of 118 patients passed the quality control process for a next-generation sequencing- (NGS-) based targeted sequencing assay. The NGS-based targeted sequencing assay was performed to detect gene fusions in 36-53 cancer-implicated genes. The following cancer types were included in this study: 28 colorectal cancers, 27 biliary tract cancers, 25 gastric cancers, 18 soft tissue sarcomas, 9 pancreatic cancers, 6 ovarian cancers, and 9 other rare cancers. Strong fusion was detected in 25 samples (21.2%). We found that 5.9% (7/118) of patients had known targetable fusion genes involving NTRK1 (n=3), FGFR (n=3), and RET (n=1), and 10.2% (12/118) of patients had potentially targetable fusion genes involving RAF1 (n=4), BRAF (n=2), ALK (n=2), ROS1 (n=1), EGFR (n=1), and CLDN18 (n=2). Thus, we successfully identified a substantial proportion of patients harboring fusion genes by RNA panel sequencing of gastrointestinal/rare cancers. Targetable and potentially targetable involved fusion genes were NTRK1, RET, FGFR3, FGFR2, BRAF, RAF1, ALK, ROS1, and CLDN18. Detection of fusion genes by RNA panel sequencing may be beneficial in refractory patients with gastrointestinal/rare cancers.

ChiTaRS 5.0: the comprehensive database of chimeric transcripts matched with druggable fusions and 3D chromatin maps

Chimeric RNA transcripts are formed when exons from two genes fuse together, often due to chromosomal translocations, transcriptional errors or trans-splicing effect. While these chimeric RNAs produce functional proteins only in certain cases, they play a significant role in disease phenotyping and progression. ChiTaRS 5.0 (http://chitars.md.biu.ac.il/) is the latest and most comprehensive chimeric transcript repository, with 111 582 annotated entries from eight species, including 23 167 known human cancer breakpoints. The database includes unique information correlating chimeric breakpoints with 3D chromatin contact maps, generated from public datasets of chromosome conformation capture techniques (Hi-C). In this update, we have added curated information on druggable fusion targets matched with chimeric breakpoints, which are applicable to precision medicine in cancers. The introduction of a new section that lists chimeric RNAs in various cell-lines is another salient feature. Finally, using text-mining techniques, novel chimeras in Alzheimer's disease, schizophrenia, dyslexia and other diseases were collected in ChiTaRS. Thus, this improved version is an extensive catalogue of chimeras from multiple species. It extends our understanding of the evolution of chimeric transcripts in eukaryotes and contributes to the analysis of 3D genome conformational changes and the functional role of chimeras in the etiopathogenesis of cancers and other complex diseases.

Knockdown of Chimeric RNA by RNAi

Knockdown assays are widely used to study the functions of a gene of interest. RNA interference (RNAi) describes a set of well-known methods used to reduce the expression of a target gene by degrading its mRNA with short hairpin RNAs (shRNAs) or short interfering RNAs (siRNAs). Knockdown of chimeric RNAs present different challenges than standard RNAi targeting for regular genes. Most specifically, sequence homology restricts the targeting region to the chimeric junction and can result in off-target effects on the parental genes. In this chapter, we provide guidelines and procedures for RNAi design of chimeric RNAs, knockdown of chimeric RNAs, downstream experiments for chimeric RNA functional studies and necessary controls to accompany each set of experiments.

Validation of Chimeric Fusion Peptides Using Proteomics Data

Chimeric RNAs as well as their fused protein products have therapeutic applications ranging from diagnostics to being used as therapeutic target. Many algorithms have been developed to identify chimeric RNAs, however, identification and validation of fused protein product of the chimeric RNA is still an emerging field. These chimeric proteins can be validated by searching and identifying them in publicly available proteomics datasets. Here we describe the detailed steps for (1) downloading and processing publicly available proteomics datasets, (2) developing fusion peptide database by performing in silico tryptic digestion of chimeric proteins, and (3) software used to identify chimeric peptides in the proteomics data.

Case Study: The Recurrent Fusion RNA DUS4L-BCAP29 in Noncancer Human Tissues and Cells

Traditional gene fusions are involved in the development of various neoplasias. DUS4L-BCAP29, a chimeric fusion RNA, has been reported to be a cancer-related fusion in prostate and gastric cancers. This chimeric RNA is believed to play a tumorigenic role. Here, we showed that the DUS4L-BCAP29 fusion transcript exists in a variety of normal tissues. It is also present in noncancerous epithelial and fibroblast cell lines. Quantitatively, the fusion transcript has a similar expression level in noncancerous gastric and prostate cell lines and tissues to its expression in cancerous cell lines and tissues. Previously, a loss-of-function approach was used to report a probable functionality for this fusion. However, this approach is not sufficient to prove such functionality. Alternatively, a gain-of-function approach showed that overexpression of DUS4L-BCAP29 promotes cell growth and motility, even in noncancerous cell lines. Finally, we provide further evidence that the fusion transcript is a product of cis-splicing between adjacent genes. In summary, we believe that in contrast to traditional gene fusions, DUS4L-BCAP29 cannot be used as a cancer biomarker. Instead, it is a fusion transcript that exists in normal physiology and its progrowth effect is not unique to cancer situations.

Confirmation of Transcriptional Read-Through Events by RT-PCR

Chimeric RNAs can be formed by trans-splicing from different transcripts or cis-splicing of adjacent genes (cis-SAGe). Cis-SAGe results from read-through transcription of two neighbor genes. To investigate the mechanisms underlying intergenic splicing of adjacent genes, it is important to develop an assay to detect transcriptional read-through. Here, we describe a general RT-PCR based method to confirm the process for cis-SAGe candidates. In this method, we use PCR to amplify cDNA that is reverse transcribed from the read-through precursor mRNA. The result provides a foundation for further downstream mechanistic studies.

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.

Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods

BACKGROUND

Accurate fusion transcript detection is essential for comprehensive characterization of cancer transcriptomes. Over the last decade, multiple bioinformatic tools have been developed to predict fusions from RNA-seq, based on either read mapping or de novo fusion transcript assembly.

RESULTS

We benchmark 23 different methods including applications we develop, STAR-Fusion and TrinityFusion, leveraging both simulated and real RNA-seq. Overall, STAR-Fusion, Arriba, and STAR-SEQR are the most accurate and fastest for fusion detection on cancer transcriptomes.

CONCLUSION

The lower accuracy of de novo assembly-based methods notwithstanding, they are useful for reconstructing fusion isoforms and tumor viruses, both of which are important in cancer research.

A tailored approach to fusion transcript identification increases diagnosis of rare inherited disease

BACKGROUND

RNA sequencing has been proposed as a means of increasing diagnostic rates in studies of undiagnosed rare inherited disease. Recent studies have reported diagnostic improvements in the range of 7.5-35% by profiling splicing, gene expression quantification and allele specific expression. To-date however, no study has systematically assessed the presence of gene-fusion transcripts in cases of germline disease. Fusion transcripts are routinely identified in cancer studies and are increasingly recognized as having diagnostic, prognostic or therapeutic relevance. Isolated reports exist of fusion transcripts being detected in cases of developmental and neurological phenotypes, and thus, systematic application of fusion detection to germline conditions may further increase diagnostic rates. However, current fusion detection methods are unsuited to the investigation of germline disease due to performance biases arising from their development using tumor, cell-line or in-silico data.

METHODS

We describe a tailored approach to fusion candidate identification and prioritization in a cohort of 47 undiagnosed, suspected inherited disease patients. We modify an existing fusion transcript detection algorithm by eliminating its cell line-derived filtering steps, and instead, prioritize candidates using a custom workflow that integrates genomic and transcriptomic sequence alignment, biological and technical annotations, customized categorization logic, and phenotypic prioritization.

RESULTS

We demonstrate that our approach to fusion transcript identification and prioritization detects genuine fusion events excluded by standard analyses and efficiently removes phenotypically unimportant candidates and false positive events, resulting in a reduced candidate list enriched for events with potential phenotypic relevance. We describe the successful genetic resolution of two previously undiagnosed disease cases through the detection of pathogenic fusion transcripts. Furthermore, we report the experimental validation of five additional cases of fusion transcripts with potential phenotypic relevance.

CONCLUSIONS

The approach we describe can be implemented to enable the detection of phenotypically relevant fusion transcripts in studies of rare inherited disease. Fusion transcript detection has the potential to increase diagnostic rates in rare inherited disease and should be included in RNA-based analytical pipelines aimed at genetic diagnosis.

Functional heritage: the evolution of chimeric RNA into a gene

Once believed to be unique features of neoplasia, chimeric RNAs are now being discovered in normal physiology. We speculated that some chimeric RNAs may be functional precursors of genes, and that forming chimeric RNA at the transcriptional level may be a 'trial' mechanism before the functional element is fixed into the genome. Supporting this idea, we identified a chimeric RNA, HNRNPA1L2-SUGT1 (H-S), whose sequence is highly similar to that of a 'pseudogene' MRPS31P5. Sequence analysis revealed that MRPS31P5 transcript is more similar to H-S chimeric RNA than its 'parent' gene, MRPS31. Evolutionarily, H-S precedes MRPS31P5, as it can be detected bioinformatically and experimentally in marmosets, which do not yet possess MRPS31P5 in their genome. Conversely, H-S is minimally expressed in humans, while instead, MRPS31P5 is abundantly expressed. Silencing H-S in marmoset cells resulted in similar phenotype as silencing MRPS31P5 in human cells. In addition, whole transcriptome analysis and candidate downstream target validation revealed common signalling pathways shared by the two transcripts. Interestingly, H-S failed to rescue the phenotype caused by silencing MPRS31P5 in human and rhesus cells, whereas MRPS31P5 can at least partially rescue the phenotype caused by silencing H-S in marmoset cells, suggesting that MRPS31P5 may have further evolved into a distinct entity. Thus, multiple lines of evidence support that MRPS31P5 is not truly a pseudogene of MRPS31, but a likely functional descendent of H-S chimera. Instead being a gene fusion product, H-S is a product of cis-splicing between adjacent genes, while MRPS31P5 is likely produced by genome rearrangement.

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy.

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.

A cell-based splicing reporter system to identify regulators of cis-splicing between adjacent genes

Chimeric RNAs generated by cis-splicing between adjacent genes (cis-SAGe) are increasingly recognized as a widespread phenomenon. These chimeric messenger RNAs are present in normal human cells, and are also detected in various cancers. The mechanisms for how this group of chimeras is formed are not yet clear, in part due to the lack of a tractable system for their experimental investigation. Here we developed a fast, easy and versatile cell-based reporter system to identify regulators of cis-SAGe. The reporter, consisting of four main cassettes, simultaneously measures the effects of a candidate regulator on cis-SAGe and canonical splicing. Using this cell-based assay, we screened 102 candidate factors involved in RNA pol II cleavage and termination, elongation, splicing, alternative splicing and R-loop formation. We discovered that two factors, SRRM1 and SF3B1, affect not only cis-SAGe chimeras, but also other types of chimeric RNAs in a genome-wide fashion. This system can be used for studying trans-acting factors and cis-acting sequence elements and factors, as well as for screening small molecule inhibitors.

Molecular profiling of biliary cancers reveals distinct molecular alterations and potential therapeutic targets

Background

Biliary tract cancers (BTCs) are a heterogeneous group of aggressive, rare malignancies with limited standard chemotherapeutic options for advanced disease. Recent studies have demonstrated potential novel biliary cancer targets and a possible role for immunotherapy in the treatment of patients with this disease. Intrahepatic cholangiocarcinoma (IHCC), extrahepatic cholangiocarcinoma (EHCC), and gallbladder carcinoma (GBC) are frequently grouped together in clinical trials despite differences in tumor biology.

Methods

To further investigate tumor biology differences, we profiled 1,502 BTCs using next-generation sequencing (NGS), immunohistochemistry, in situ hybridization, and RNA sequencing.

Results

IHCCs had higher rates of IDH1, BAP1, and PBRM1 mutations and FGFR2 fusions; EHCCs had higher rates of KRAS, CDKN2A, and BRCA1 mutations; and GBCs had higher rates of homologous recombination repair deficiency and Her2/neu overexpression and amplification. IHCCs and GBCs had higher rates of potential positive predictive biomarkers for immune checkpoint inhibition (PD-L1 expression, high microsatellite instability, and high tumor mutational burden) than EHCCs.

Conclusions

These findings support clinical molecular profiling of BTCs to inform potential therapeutic selection and clinical trial design based on the primary tumor's site of origin within the biliary tree.

Not Only Mutations Matter: Molecular Picture of Acute Myeloid Leukemia Emerging from Transcriptome Studies

The last two decades of genome-scale research revealed a complex molecular picture of acute myeloid leukemia (AML). On the one hand, a number of mutations were discovered and associated with AML diagnosis and prognosis; some of them were introduced into diagnostic tests. On the other hand, transcriptome studies, which preceded AML exome and genome sequencing, remained poorly translated into clinics. Nevertheless, gene expression studies significantly contributed to the elucidation of AML pathogenesis and indicated potential therapeutic directions. The power of transcriptomic approach lies in its comprehensiveness; we can observe how genome manifests its function in a particular type of cells and follow many genes in one test. Moreover, gene expression measurement can be combined with mutation detection, as high-impact mutations are often present in transcripts. This review sums up 20 years of transcriptome research devoted to AML. Gene expression profiling (GEP) revealed signatures distinctive for selected AML subtypes and uncovered the additional within-subtype heterogeneity. The results were particularly valuable in the case of AML with normal karyotype which concerns up to 50% of AML cases. With the use of GEP, new classes of the disease were identified and prognostic predictors were proposed. A plenty of genes were detected as overexpressed in AML when compared to healthy control, including KIT, BAALC, ERG, MN1, CDX2, WT1, PRAME, and HOX genes. High expression of these genes constitutes usually an unfavorable prognostic factor. Upregulation of FLT3 and NPM1 genes, independent on their mutation status, was also reported in AML and correlated with poor outcome. However, transcriptome is not limited to the protein-coding genes; other types of RNA molecules exist in a cell and regulate genome function. It was shown that microRNA (miRNA) profiles differentiated AML groups and predicted outcome not worse than protein-coding gene profiles. For example, upregulation of miR-10a, miR-10b, and miR-196b and downregulation of miR-192 were found as typical of AML with NPM1 mutation whereas overexpression of miR-155 was associated with FLT3-internal tandem duplication (FLT3-ITD). Development of high-throughput technologies and microarray replacement by next generation sequencing (RNA-seq) enabled uncovering a real variety of leukemic cell transcriptomes, reflected by gene fusions, chimeric RNAs, alternatively spliced transcripts, miRNAs, piRNAs, long noncoding RNAs (lncRNAs), and their special type, circular RNAs. Many of them can be considered as AML biomarkers and potential therapeutic targets. The relations between particular RNA puzzles and other components of leukemic cells and their microenvironment, such as exosomes, are now under investigation. Hopefully, the results of this research will shed the light on these aspects of AML pathogenesis which are still not completely understood.

Alternative polyadenylation produces multiple 3' untranslated regions of odorant receptor mRNAs in mouse olfactory sensory neurons

BACKGROUND

Odorant receptor genes constitute the largest gene family in mammalian genomes and this family has been extensively studied in several species, but to date far less attention has been paid to the characterization of their mRNA 3' untranslated regions (3'UTRs). Given the increasing importance of UTRs in the understanding of RNA metabolism, and the growing interest in alternative polyadenylation especially in the nervous system, we aimed at identifying the alternative isoforms of odorant receptor mRNAs generated through 3'UTR variation.

RESULTS

We implemented a dedicated pipeline using IsoSCM instead of Cufflinks to analyze RNA-Seq data from whole olfactory mucosa of adult mice and obtained an extensive description of the 3'UTR isoforms of odorant receptor mRNAs. To validate our bioinformatics approach, we exhaustively analyzed the 3'UTR isoforms produced from 2 pilot genes, using molecular approaches including northern blot and RNA ligation mediated polyadenylation test. Comparison between datasets further validated the pipeline and confirmed the alternative polyadenylation patterns of odorant receptors. Qualitative and quantitative analyses of the annotated 3' regions demonstrate that 1) Odorant receptor 3'UTRs are longer than previously described in the literature; 2) More than 77% of odorant receptor mRNAs are subject to alternative polyadenylation, hence generating at least 2 detectable 3'UTR isoforms; 3) Splicing events in 3'UTRs are restricted to a limited subset of odorant receptor genes; and 4) Comparison between male and female data shows no sex-specific differences in odorant receptor 3'UTR isoforms.

CONCLUSIONS

We demonstrated for the first time that odorant receptor genes are extensively subject to alternative polyadenylation. This ground-breaking change to the landscape of 3'UTR isoforms of Olfr mRNAs opens new avenues for investigating their respective functions, especially during the differentiation of olfactory sensory neurons.

Targetable Gene Fusions Associate With the IDH Wild-Type Astrocytic Lineage in Adult Gliomas

Gene fusions involving oncogenes have been reported in gliomas and may serve as novel therapeutic targets. Using RNA-sequencing, we interrogated a large cohort of gliomas to assess for the incidence of targetable genetic fusions. Gliomas (n = 390) were profiled using the ArcherDx FusionPlex Assay. Fifty-two gene targets were analyzed and fusions with preserved kinase domains were investigated. Overall, 36 gliomas (9%) harbored a total of 37 potentially targetable fusions, the majority of which were found in astrocytomas (n = 34). Within this lineage 11% (25/235) of glioblastomas, 12% (5/42) of anaplastic astrocytomas, 8% (2/25) of grade II astrocytomas, and 33% (2/6) of pilocytic astrocytoma harbored targetable fusions. Fusions were significantly more frequent in IDH wild-type tumors (12%, n = 31/261) relative to IDH mutants (4%; n = 4/109) (p = 0.011). No fusions were seen in oligodendrogliomas. The most frequently observed therapeutically targetable fusions were in FGFR (n = 12), MET (n = 11), and NTRK (n = 8). Several additional novel fusions that have not been previously described in gliomas were identified including EGFR:VWC2 and FGFR3:NBR1. In summary, targetable gene fusions are enriched in IDH wild-type high-grade astrocytic tumors, which will influence enrollment in and interpretation of clinical trials of glioma patients.

A Simple RNA Target Capture NGS Strategy for Fusion Genes Assessment in the Diagnostics of Pediatric B-cell Acute Lymphoblastic Leukemia

Supplemental Digital Content is available in the text

Acute lymphoblastic leukemia (ALL) is the most frequent pediatric cancer. Fusion genes are hallmarks of ALL, and they are used as biomarkers for risk stratification as well as targets for precision medicine. Hence, clinical diagnostics pursues broad and comprehensive strategies for accurate discovery of fusion genes. Currently, the gold standard methodologies for fusion gene detection are fluorescence in situ hybridization and polymerase chain reaction; these, however, lack sensitivity for the identification of new fusion genes and breakpoints. In this study, we implemented a simple operating procedure (OP) for detecting fusion genes. The OP employs RNA CaptureSeq, a versatile and effortless next-generation sequencing assay, and an in-house as well as a purpose-built bioinformatics pipeline for the subsequent data analysis. The OP was evaluated on a cohort of 89 B-cell precursor ALL (BCP-ALL) pediatric samples annotated as negative for fusion genes by the standard techniques. The OP confirmed 51 samples as negative for fusion genes, and, more importantly, it identified known (KMT2A rearrangements) as well as new fusion events (JAK2 rearrangements) in the remaining 38 investigated samples, of which 16 fusion genes had prognostic significance. Herein, we describe the OP and its deployment into routine ALL diagnostics, which will allow substantial improvements in both patient risk stratification and precision medicine.

A Deep Learning Approach to the Screening of Oncogenic Gene Fusions in Humans

Gene fusions have a very important role in the study of cancer development. In this regard, predicting the probability of protein fusion transcripts of developing into a cancer is a very challenging and yet not fully explored research problem. To this date, all the available approaches in literature try to explain the oncogenic potential of gene fusions based on protein domain analysis, that is cancer-specific and not easy to adapt to newly developed information. In our work, we choose the raw protein sequences as the input baseline, and propose the use of deep learning, and more specifically Convolutional Neural Networks, to infer the oncogenity probability score of gene fusion transcripts and to group them into a number of categories (e.g., oncogenic/not oncogenic). This is an inherently flexible methodology that, unlike previous approaches, can be re-trained with very less efforts on newly available data (for example, from a different cancer). Based on experimental results on a large dataset of pre-annotated gene fusions, our method is able to predict the oncogenity potential of gene fusion transcripts with accuracy of about 72%, which increases to 86% if we consider the only instances that are classified with a high confidence level.

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.

Diagnosis of fusion genes using targeted RNA sequencing

Fusion genes are a major cause of cancer. Their rapid and accurate diagnosis can inform clinical action, but current molecular diagnostic assays are restricted in resolution and throughput. Here, we show that targeted RNA sequencing (RNAseq) can overcome these limitations. First, we establish that fusion gene detection with targeted RNAseq is both sensitive and quantitative by optimising laboratory and bioinformatic variables using spike-in standards and cell lines. Next, we analyse a clinical patient cohort and improve the overall fusion gene diagnostic rate from 63% with conventional approaches to 76% with targeted RNAseq while demonstrating high concordance for patient samples with previous diagnoses. Finally, we show that targeted RNAseq offers additional advantages by simultaneously measuring gene expression levels and profiling the immune-receptor repertoire. We anticipate that targeted RNAseq will improve clinical fusion gene detection, and its increasing use will provide a deeper understanding of fusion gene biology.

Rapid and accurate detection of fusion genes is important in cancer diagnostics. Here, the authors demonstrate that targeted RNA sequencing provides fast, sensitive and quantitative gene fusion detection and overcomes the limitations of approaches currently in clinical use.

Detection of novel fusion-transcripts by RNA-Seq in T-cell lymphoblastic lymphoma

Fusions transcripts have been proven to be strong drivers for neoplasia-associated mutations, although their incidence in T-cell lymphoblastic lymphoma needs to be determined yet. Using RNA-Seq we have selected 55 fusion transcripts identified by at least two of three detection methods in the same tumour. We confirmed the existence of 24 predicted novel fusions that had not been described in cancer or normal tissues yet, indicating the accuracy of the prediction. Of note, one of them involves the proto oncogene TAL1. Other confirmed fusions could explain the overexpression of driver genes such as COMMD3-BMI1, LMO1 or JAK3. Five fusions found exclusively in tumour samples could be considered pathogenic (NFYG-TAL1, RIC3-TCRBC2, SLC35A3-HIAT1, PICALM MLLT10 and MLLT10-PICALM). However, other fusions detected simultaneously in normal and tumour samples (JAK3-INSL3, KANSL1-ARL17A/B and TFG-ADGRG7) could be germ-line fusions genes involved in tumour-maintaining tasks. Notably, some fusions were confirmed in more tumour samples than predicted, indicating that the detection methods underestimated the real number of existing fusions. Our results highlight the potential of RNA-Seq to identify new cryptic fusions, which could be drivers or tumour-maintaining passenger genes. Such novel findings shed light on the searching for new T-LBL biomarkers in these haematological disorders.

Most gene fusions in cancer are stochastic events

Cancer-associated gene fusions resulting in chimeric proteins or aberrant expression of one or both partner genes are pathogenetically and clinically important in several hematologic malignancies and solid tumors. Since the advent of different types of massively parallel sequencing (MPS), the number of identified gene fusions has increased dramatically, prompting the question whether they all have a biologic impact. By ascertaining the chromosomal locations of 8934 genes involved in 10 861 gene fusions reported in the literature, we here show that there is a highly significant association between gene content of chromosomes and chromosome bands and number of genes involved in fusions. This strongly suggests that a clear majority of gene fusions detected by MPS are stochastic events associated with the number of genes available to participate in fusions and that most reported gene fusions are passengers without any pathogenetic importance.

Novel TG-FGFR1 and TRIM33-NTRK1 transcript fusions in papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is most common among all thyroid cancers. Multiple genomic alterations occur in PTC, and gene rearrangements are one of them. Here we screened 14 tumors for novel fusion transcripts by RNA‐Seq. Two samples harboring RET/PTC1 and RET/PTC3 rearrangements were positive controls whereas the remaining ones were negative regarding the common PTC alterations. We used Sanger sequencing to validate potential fusions. We detected 2 novel potentially oncogenic transcript fusions: TG‐FGFR1 and TRIM33‐NTRK1. We detected 4 novel fusion transcripts of unknown significance accompanying the TRIM33‐NTRK1 fusion: ZSWIM5‐TP53BP2, TAF4B‐WDR1, ABI2‐MTA3, and ARID1B‐PSMA1. Apart from confirming the presence of RET/PTC1 and RET/PTC3 in positive control samples, we also detected known oncogenic fusion transcripts in remaining samples: TFG‐NTRK1, ETV6‐NTRK3, MKRN1‐BRAF, EML4‐ALK, and novel isoform of CCDC6‐RET.

PAX3-FOXO1 escapes miR-495 regulation during muscle differentiation

Pax3 plays an essential role in myogenesis. Previously, we found a tumor-signature chimeric fusion RNA, PAX3-FOXO1 also present during muscle differentiation, raising the possibility of its physiological role. Here we demonstrated that the fusion is needed transiently for muscle lineage commitment. Interestingly, the fusion ortholog was not found in seven mouse muscle differentiation/regeneration systems, nor in other stem cell differentiation systems of another three mammal species. We noticed that Pax3 is expressed at a much lower level in human stem cells, and during muscle differentiation than in other mammals. Given the fact that the fusion and the parental Pax3 share common downstream targets, we reasoned that forming the fusion may be a mechanism for human cells to escape certain microRNA regulation on Pax3. By sequence comparison, we identified 16 candidate microRNAs that may specifically target the human PAX3 3'UTR. We used a luciferase reporter assay, examined the microRNAs expression, and conducted mutagenesis on the reporters, as well as a CRISPR/Cas9 mediated editing on the endogenous allele. Finally, we identified miR-495 as a microRNA that specifically targets human PAX3. Examining several other fusion RNAs revealed that the human-specificity is not limited to PAX3-FOXO1. Based on these observations, we conclude that PAX3-FOXO1 fusion RNA is absent in mouse, or other mammals we tested, the fusion RNA is a mechanism to escape microRNA, miR-495 regulation in humans, and that it is not the only human-specific fusion RNA.