Novel gene fusion discovery in Spitz tumours and its relevance in diagnostics.

In addition to morphologic analysis, molecular diagnostic work up of Spitz tumours is often of great value for their accurate diagnosis/classification. Nowadays, next-generation sequencing (NGS) is the predominant screening method in molecular diagnostics. Up to 80% of these melanocytic neoplasms comprise gene fusions as genetic anomalies for which the driver codes for a protein harbouring a kinase domain. However, because of the variety of fusion partners the use of PCR-based targeted enrichment NGS methods is not recommended. We describe a series of four Spitz tumour samples in which distinct gene fusions were detected by hybridisation-based capture NGS (TPM3::ALK, LIMA1::ROS1, LRRFIP2::ROS1 and MYO5A::RET). Two of these fusions are not previously described. All 4 fusions were confirmed by reverse transcription-PCR. These findings demonstrate the need for molecular analysis that can detect unknown fusions in Spitz neoplasms for optimal diagnosis.

Orthogonal proteomics methods to unravel the HOTAIR interactome.

Accumulating evidence highlights the role of long non-coding RNAs (lncRNAs) in cellular homeostasis, and their dysregulation in disease settings. Most lncRNAs function by interacting with proteins or protein complexes. While several orthogonal methods have been developed to identify these proteins, each method has its inherent strengths and limitations. Here, we combine two RNA-centric methods ChIRP-MS and RNA-BioID to obtain a comprehensive list of proteins that interact with the well-known lncRNA HOTAIR. Overexpression of HOTAIR has been associated with a metastasis-promoting phenotype in various cancers. Although HOTAIR is known to bind with PRC2 and LSD1 protein complexes, only very limited unbiased comprehensive approaches to map its interactome have been performed. Both ChIRP-MS and RNA-BioID data sets show an association of HOTAIR with mitoribosomes, suggesting that HOTAIR has functions independent of its (post-)transcriptional mode-of-action.

MEIS2 Is an Adrenergic Core Regulatory Transcription Factor Involved in Early Initiation of TH-MYCN-Driven Neuroblastoma Formation.

Roughly half of all high-risk neuroblastoma patients present with MYCN amplification. The molecular consequences of MYCN overexpression in this aggressive pediatric tumor have been studied for decades, but thus far, our understanding of the early initiating steps of MYCN-driven tumor formation is still enigmatic. We performed a detailed transcriptome landscaping during murine TH-MYCN-driven neuroblastoma tumor formation at different time points. The neuroblastoma dependency factor MEIS2, together with ASCL1, was identified as a candidate tumor-initiating factor and shown to be a novel core regulatory circuit member in adrenergic neuroblastomas. Of further interest, we found a KEOPS complex member (gm6890), implicated in homologous double-strand break repair and telomere maintenance, to be strongly upregulated during tumor formation, as well as the checkpoint adaptor Claspin (CLSPN) and three chromosome 17q loci CBX2, GJC1 and LIMD2. Finally, cross-species master regulator analysis identified FOXM1, together with additional hubs controlling transcriptome profiles of MYCN-driven neuroblastoma. In conclusion, time-resolved transcriptome analysis of early hyperplastic lesions and full-blown MYCN-driven neuroblastomas yielded novel components implicated in both tumor initiation and maintenance, providing putative novel drug targets for MYCN-driven neuroblastoma.

Validation of Circular RNAs Using RT-qPCR After Effective Removal of Linear RNAs by Ribonuclease R.

Circular RNAs (circRNAs) are a class of endogenous noncoding RNAs that have been shown to play a role in normal development, homeostasis, and disease, including cancer. CircRNAs are formed through a process called back-splicing, which results in a covalently closed loop with a nonlinear back-spliced junction (BSJ). In general, circRNA BSJs are predicted in RNA sequencing data using one of numerous circRNA detection algorithms. Selected circRNAs are then typically validated using an orthogonal method such as reverse transcription quantitative PCR (RT-qPCR) with circRNA-specific primers. However, linear transcripts originating from endogenous trans-splicing can lead to false-positive signals both in RNA sequencing and in RT-qPCR experiments. Therefore, it is essential to perform the RT-qPCR validation step only after linear RNAs have been degraded using an exonuclease such as ribonuclease R (RNase R). Several RNase R protocols are available for circRNA detection using RNA sequencing or RT-qPCR. These protocols-which vary in enzyme concentration, RNA input amount, incubation times, and cleanup steps-typically lack a detailed validated standard protocol and fail to provide a range of conditions that deliver accurate results. As such, some protocols use RNase R concentrations that are too high, resulting in partial degradation of the target circRNAs. Here, we describe an optimized workflow for circRNA validation, combining RNase R treatment and RT-qPCR. First, we outline the steps for circRNA primer design and qPCR assay validation. Then, we describe RNase R treatment of total RNA and, importantly, a subsequent essential buffer cleanup step. Lastly, we outline the steps to perform the RT-qPCR and discuss the downstream data analyses. © 2021 Wiley Periodicals LLC. Basic Protocol 1: CircRNA primer design and qPCR assay validation Basic Protocol 2: RNase R treatment, cleanup, and RT-qPCR.

The RNA landscape of the human placenta in health and disease.

The placenta is the interface between mother and fetus and inadequate function contributes to short and long-term ill-health. The placenta is absent from most large-scale RNA-Seq datasets. We therefore analyze long and small RNAs (~101 and 20 million reads per sample respectively) from 302 human placentas, including 94 cases of preeclampsia (PE) and 56 cases of fetal growth restriction (FGR). The placental transcriptome has the seventh lowest complexity of 50 human tissues: 271 genes account for 50% of all reads. We identify multiple circular RNAs and validate 6 of these by Sanger sequencing across the back-splice junction. Using large-scale mass spectrometry datasets, we find strong evidence of peptides produced by translation of two circular RNAs. We also identify novel piRNAs which are clustered on Chr1 and Chr14. PE and FGR are associated with multiple and overlapping differences in mRNA, lincRNA and circRNA but fewer consistent differences in small RNAs. Of the three protein coding genes differentially expressed in both PE and FGR, one encodes a secreted protein FSTL3 (follistatin-like 3). Elevated serum levels of FSTL3 in pregnant women are predictive of subsequent PE and FGR. To aid visualization of our placenta transcriptome data, we develop a web application ( https://www.obgyn.cam.ac.uk/placentome/ ).

Closing the circle: current state and perspectives of circular RNA databases.

Circular RNAs (circRNAs) are covalently closed RNA molecules that have been linked to various diseases, including cancer. However, a precise function and working mechanism are lacking for the larger majority. Following many different experimental and computational approaches to identify circRNAs, multiple circRNA databases were developed as well. Unfortunately, there are several major issues with the current circRNA databases, which substantially hamper progression in the field. First, as the overlap in content is limited, a true reference set of circRNAs is lacking. This results from the low abundance and highly specific expression of circRNAs, and varying sequencing methods, data-analysis pipelines, and circRNA detection tools. A second major issue is the use of ambiguous nomenclature. Thus, redundant or even conflicting names for circRNAs across different databases contribute to the reproducibility crisis. Third, circRNA databases, in essence, rely on the position of the circRNA back-splice junction, whereas alternative splicing could result in circRNAs with different length and sequence. To uniquely identify a circRNA molecule, the full circular sequence is required. Fourth, circRNA databases annotate circRNAs' microRNA binding and protein-coding potential, but these annotations are generally based on presumed circRNA sequences. Finally, several databases are not regularly updated, contain incomplete data or suffer from connectivity issues. In this review, we present a comprehensive overview of the current circRNA databases and their content, features, and usability. In addition to discussing the current issues regarding circRNA databases, we come with important suggestions to streamline further research in this growing field.

COSS: A Fast and User-Friendly Tool for Spectral Library Searching.

Spectral similarity searching to identify peptide-derived MS/MS spectra is a promising technique, and different spectrum similarity search tools have therefore been developed. Each of these tools, however, comes with some limitations, mainly because of low processing speed and issues with handling large databases. Furthermore, the number of spectral data formats supported is typically limited, which also creates a threshold to adoption. We have therefore developed COSS (CompOmics Spectral Searching), a new and user-friendly spectral library search tool supporting two scoring functions. COSS also includes decoy spectra generation for result validation. We have benchmarked COSS on three different spectral libraries and compared the results with established spectral searching tools and a sequence database search tool. Our comparison showed that COSS more reliably identifies spectra, is capable of handling large data sets and libraries, and is an easy to use tool that can run on low computer specifications. COSS binaries and source code can be freely downloaded from https://github.com/compomics/COSS.

Distinct Notch1 and BCL11B requirements mediate human γδ/αß T cell development.

γδ and αß T cells have unique roles in immunity and both originate in the thymus from T-lineage committed precursors through distinct but unclear mechanisms. Here, we show that Notch1 activation is more stringently required for human γδ development compared to αß-lineage differentiation and performed paired mRNA and miRNA profiling across 11 discrete developmental stages of human T cell development in an effort to identify the potential Notch1 downstream mechanism. Our data suggest that the miR-17-92 cluster is a Notch1 target in immature thymocytes and that miR-17 can restrict BCL11B expression in these Notch-dependent T cell precursors. We show that enforced miR-17 expression promotes human γδ T cell development and, consistently, that BCL11B is absolutely required for αß but less for γδ T cell development. This study suggests that human γδ T cell development is mediated by a stage-specific Notch-driven negative feedback loop through which miR-17 temporally restricts BCL11B expression and provides functional insights into the developmental role of the disease-associated genes BCL11B and the miR-17-92 cluster in a human context.

Long noncoding RNA expression profiling in cancer: Challenges and opportunities.

In recent years, technological advances in transcriptome profiling revealed that the repertoire of human RNA molecules is more diverse and extended than originally thought. This diversity and complexity mainly derive from a large ensemble of noncoding RNAs. Because of their key roles in cellular processes important for normal development and physiology, disruption of noncoding RNA expression is intrinsically linked to human disease, including cancer. Therefore, studying the noncoding portion of the transcriptome offers the prospect of identifying novel therapeutic and diagnostic targets. Although evidence of the relevance of noncoding RNAs in cancer is accumulating, we still face many challenges when it comes to accurately profiling their expression levels. Some of these challenges are inherent to the technologies employed, whereas others are associated with characteristics of the noncoding RNAs themselves. In this review, we discuss the challenges related to long noncoding RNA expression profiling, highlight how cancer long noncoding RNAs provide new opportunities for cancer diagnosis and treatment, and reflect on future developments.

Targeted Genomic Screen Reveals Focal Long Non-Coding RNA Copy Number Alterations in Cancer Cell Lines.

The landscape of somatic copy-number alterations (SCNAs) affecting long non-coding RNAs (lncRNAs) in human cancers remains largely unexplored. While the majority of lncRNAs remain to be functionally characterized, several have been implicated in cancer development and metastasis. Considering the plethora of lncRNAs genes that have been currently reported, it is conceivable that many more lncRNAs might function as oncogenes or tumor suppressor genes. We devised a strategy to detect focal lncRNA SCNAs using a custom DNA microarray platform probing 10,519 lncRNA genes. By screening a panel of 80 cancer cell lines, we detected numerous focal aberrations targeting one or multiple lncRNAs without affecting neighboring protein-coding genes. These focal aberrations are highly suggestive for a tumor suppressive or oncogenic role of the targeted lncRNA gene. Although functional validation remains an essential step in the further characterization of the involved candidate cancer lncRNAs, our results provide a direct way of prioritizing candidate lncRNAs that are involved in cancer pathogenesis.

decodeRNA- predicting non-coding RNA functions using guilt-by-association.

Database URL: http://www.decoderna.org.

Long non-coding RNAs in cutaneous melanoma: clinical perspectives.

Metastatic melanoma of the skin has a high mortality despite the recent introduction of targeted therapy and immunotherapy. Long non-coding RNAs (lncRNAs) are defined as transcripts of more than 200 nucleotides in length that lack protein-coding potential. There is growing evidence that lncRNAs play an important role in gene regulation, including oncogenesis. We present 13 lncRNA genes involved in the pathogenesis of cutaneous melanoma through a variety of pathways and molecular interactions. Some of these lncRNAs are possible biomarkers or therapeutic targets for malignant melanoma.

Long non-coding RNA expression profiling in the NCI60 cancer cell line panel using high-throughput RT-qPCR.

Long non-coding RNAs (lncRNAs) form a new class of RNA molecules implicated in various aspects of protein coding gene expression regulation. To study lncRNAs in cancer, we generated expression profiles for 1707 human lncRNAs in the NCI60 cancer cell line panel using a high-throughput nanowell RT-qPCR platform. We describe how qPCR assays were designed and validated and provide processed and normalized expression data for further analysis. Data quality is demonstrated by matching the lncRNA expression profiles with phenotypic and genomic characteristics of the cancer cell lines. This data set can be integrated with publicly available omics and pharmacological data sets to uncover novel associations between lncRNA expression and mRNA expression, miRNA expression, DNA copy number, protein coding gene mutation status or drug response.

Genome wide expression profiling of p53 regulated miRNAs in neuroblastoma.

Restoration of the antitumor activity of p53 could offer a promising approach for the treatment of neuroblastoma. MicroRNAs (miRNAs) are important mediators of p53 activity, but their role in the p53 response has not yet been comprehensively addressed in neuroblastoma. Therefore, we set out to characterize alterations in miRNA expression that are induced by p53 activation in neuroblastoma cells. Genome-wide miRNA expression analysis showed that miR-34a-5p, miR-182-5p, miR-203a, miR-222-3p, and miR-432-5p are upregulated following nutlin-3 treatment in a p53 dependent manner. The function of miR-182-5p, miR-203a, miR-222-3p, and miR-432-5p was analyzed by ectopic overexpression of miRNA mimics. We observed that these p53-regulated miRNAs inhibit the proliferation of neuroblastoma cells to varying degrees, with the most profound growth inhibition recorded for miR-182-5p. Overexpression of miR-182-5p promoted apoptosis in some neuroblastoma cell lines and induced neuronal differentiation of NGP cells. Using Chromatin Immunoprecipitation-qPCR (ChIP-qPCR), we did not observe direct binding of p53 to MIR182, MIR203, MIR222, and MIR432 in neuroblastoma cells. Taken together, our findings yield new insights in the network of p53-regulated miRNAs in neuroblastoma.

The Notch driven long non-coding RNA repertoire in T-cell acute lymphoblastic leukemia.

Genetic studies in T-cell acute lymphoblastic leukemia have uncovered a remarkable complexity of oncogenic and loss-of-function mutations. Amongst this plethora of genetic changes, NOTCH1 activating mutations stand out as the most frequently occurring genetic defect, identified in more than 50% of T-cell acute lymphoblastic leukemias, supporting a role as an essential driver for this gene in T-cell acute lymphoblastic leukemia oncogenesis. In this study, we aimed to establish a comprehensive compendium of the long non-coding RNA transcriptome under control of Notch signaling. For this purpose, we measured the transcriptional response of all protein coding genes and long non-coding RNAs upon pharmacological Notch inhibition in the human T-cell acute lymphoblastic leukemia cell line CUTLL1 using RNA-sequencing. Similar Notch dependent profiles were established for normal human CD34(+) thymic T-cell progenitors exposed to Notch signaling activity in vivo. In addition, we generated long non-coding RNA expression profiles (array data) from ex vivo isolated Notch active CD34(+) and Notch inactive CD4(+)CD8(+) thymocytes and from a primary cohort of 15 T-cell acute lymphoblastic leukemia patients with known NOTCH1 mutation status. Integration of these expression datasets with publicly available Notch1 ChIP-sequencing data resulted in the identification of long non-coding RNAs directly regulated by Notch activity in normal and malignant T cells. Given the central role of Notch in T-cell acute lymphoblastic leukemia oncogenesis, these data pave the way for the development of novel therapeutic strategies that target hyperactive Notch signaling in human T-cell acute lymphoblastic leukemia.