Disruption of regulatory domains and novel transcripts as disease-causing mechanisms.

Deletions, duplications, insertions, inversions, and translocations, collectively called structural variations (SVs), affect more base pairs of the genome than any other sequence variant. The recent technological advancements in genome sequencing have enabled the discovery of tens of thousands of SVs per human genome. These SVs primarily affect non-coding DNA sequences, but the difficulties in interpreting their impact limit our understanding of human disease etiology. The functional annotation of non-coding DNA sequences and methodologies to characterize their three-dimensional (3D) organization in the nucleus have greatly expanded our understanding of the basic mechanisms underlying gene regulation, thereby improving the interpretation of SVs for their pathogenic impact. Here, we discuss the various mechanisms by which SVs can result in altered gene regulation and how these mechanisms can result in rare genetic disorders. Beyond changing gene expression, SVs can produce novel gene-intergenic fusion transcripts at the SV breakpoints.

circPVT1 and PVT1/AKT3 show a role in cell proliferation, apoptosis, and tumor subtype-definition in small cell lung cancer.

Small cell lung cancer (SCLC) is treated as a homogeneous disease, although the expression of NEUROD1, ASCL1, POU2F3, and YAP1 identifies distinct molecular subtypes. The MYC oncogene, amplified in SCLC, was recently shown to act as a lineage-specific factor to associate subtypes with histological classes. Indeed, MYC-driven SCLCs show a distinct metabolic profile and drug sensitivity. To disentangle their molecular features, we focused on the co-amplified PVT1, frequently overexpressed and originating circular (circRNA) and chimeric RNAs. We analyzed hsa_circ_0001821 (circPVT1) and PVT1/AKT3 (chimPVT1) as examples of such transcripts, respectively, to unveil their tumorigenic contribution to SCLC. In detail, circPVT1 activated a pro-proliferative and anti-apoptotic program when over-expressed in lung cells, and knockdown of chimPVT1 induced a decrease in cell growth and an increase of apoptosis in SCLC in vitro. Moreover, the investigated PVT1 transcripts underlined a functional connection between MYC and YAP1/POU2F3, suggesting that they contribute to the transcriptional landscape associated with MYC amplification. In conclusion, we have uncovered a functional role of circular and chimeric PVT1 transcripts in SCLC; these entities may prove useful as novel biomarkers in MYC-amplified tumors.

Fast and sensitive validation of fusion transcripts in whole-genome sequencing data.

BACKGROUND: In cancer, genomic rearrangements can create fusion genes that either combine protein-coding sequences from two different partner genes or place one gene under the control of the promoter of another gene. These fusion genes can act as oncogenic drivers in tumor development and several fusions involving kinases have been successfully exploited as drug targets. Expressed fusions can be identified in RNA sequencing (RNA-Seq) data, but fusion prediction software often has a high fraction of false positive fusion transcript predictions. This is problematic for both research and clinical applications. RESULTS: We describe a method for validation of fusion transcripts detected by RNA-Seq in matched whole-genome sequencing (WGS) data. Our pipeline uses discordant read pairs to identify supported fusion events and analyzes soft-clipped read alignments to determine genomic breakpoints. We have tested it on matched RNA-Seq and WGS data for both tumors and cancer cell lines and show that it can be used to validate both new predicted gene fusions and experimentally validated fusion events. It was considerably faster and more sensitive than using BreakDancer and Manta, software that is instead designed to detect many different types of structural variants on a genome-wide scale. CONCLUSIONS: We have developed a fast and very sensitive pipeline for validation of gene fusions detected by RNA-Seq in matched WGS data. It can be used to identify high-quality gene fusions for further bioinformatic and experimental studies, including validation of genomic breakpoints and studies of the mechanisms that generate fusions. In a clinical setting, it could help find expressed gene fusions for personalized therapy.

Improved detection of clinically relevant fusion transcripts in cancer by machine learning classification.

BACKGROUND: Genomic rearrangements in cancer cells can create fusion genes that encode chimeric proteins or alter the expression of coding and non-coding RNAs. In some cancer types, fusions involving specific kinases are used as targets for therapy. Fusion genes can be detected by whole genome sequencing (WGS) and targeted fusion panels, but RNA sequencing (RNA-Seq) has the advantageous capability of broadly detecting expressed fusion transcripts. RESULTS: We developed a pipeline for validation of fusion transcripts identified in RNA-Seq data using matched WGS data from The Cancer Genome Atlas (TCGA) and applied it to 910 tumors from 11 different cancer types. This resulted in 4237 validated gene fusions, 3049 of them with at least one identified genomic breakpoint. Utilizing validated fusions as true positive events, we trained a machine learning classifier to predict true and false positive fusion transcripts from RNA-Seq data. The final precision and recall metrics of the classifier were 0.74 and 0.71, respectively, in an independent dataset of 249 breast tumors. Application of this classifier to all samples with RNA-Seq data from these cancer types vastly extended the number of likely true positive fusion transcripts and identified many potentially targetable kinase fusions. Further analysis of the validated gene fusions suggested that many are created by intrachromosomal amplification events with microhomology-mediated non-homologous end-joining. CONCLUSIONS: A classifier trained on validated fusion events increased the accuracy of fusion transcript identification in samples without WGS data. This allowed the analysis to be extended to all samples with RNA-Seq data, facilitating studies of tumor biology and increasing the number of detected kinase fusions. Machine learning could thus be used in identification of clinically relevant fusion events for targeted therapy. The large dataset of validated gene fusions generated here presents a useful resource for development and evaluation of fusion transcript detection algorithms.

Fusion transcriptome profiling defines the monoclonal origin of multifocal epithelioid haemangioma of bone.

AIMS: Epithelioid haemangioma (EH) of bone remains a highly controversial entity. Indeed, the WHO classifies EHs of soft tissues as benign tumours, whereas bone EHs are considered intermediate-locally aggressive tumours due to common multifocal presentation and local destructive growth. To gain insights into the clinical behaviour and biology of EH of bone we retrospectively analysed 42 patients treated in a single institution from 1978 to 2021. METHODS AND RESULTS: Multifocal presentation was detected in 17 of 42 patients (40%) primarily as synchronous lesions. Patients were treated with curettage (57%), resection (29%) or biopsy, followed by radiotherapy or embolisation (14%). Follow-up (minimum 24 months) was available for 38 patients, with only five local recurrences (13%) and no death of disease. To clarify whether the synchronous bone lesions in multifocal EH represent multicentric disease or clonal dissemination, four cases were profiled by RNA-sequencing. Separate lesions from the same patient, which showed a similar transcriptional profile, expressed the same fusion transcript (involving FOS or FOSB) with identical gene breakpoints. CONCLUSIONS: These results indicate that, in EH of bone, multifocal lesions are clonally related and therefore represent the spread of a same neoplastic clone rather than simultaneous independent tumours. This finding is in apparent contradiction with the benign clinical course of the disease, and suggests that tumour dissemination in bone EH probably reflects a phenomenon of passive spreading, with tumour cells colonising distal sites while maintaining their benign biological nature.

Recurrent FOXK1::GRHL and GPS2::GRHL fusions in trichogerminoma.

We report 21 cases of trichogerminoma harbouring previously undescribed FOXK1::GRHL1/2 or GPS2::GRHL1/2/3 in-frame fusion transcripts. Microscopic examination of a preliminary set of five cases revealed well-delimitated tumours located in the dermis with frequent extension to the subcutaneous tissue. Tumours presented a massive and nodular architecture and consisted of a proliferation of basaloid cells. A biphasic pattern sometime resulting in tumour cell nests ('cell balls') was present. Immunohistochemistry demonstrated the expression of cytokeratins (CKs) 15, 17, and PHLDA1. In addition, numerous CK20-positive Merkel cells were detected. RNA sequencing (RNA-seq) revealed a FOXK1::GRHL1 chimeric transcript in three cases and a FOXK1::GRHL2 fusion in two cases. In a second series for validation (n = 88), FOXK1::GRHL1/2 fusion transcripts were detected by RT-qPCR or FISH in an additional 12 trichogerminomas and not in any other follicular tumour entities or basal cell carcinoma cases (n = 66). Additional RNA-seq analysis in trichogerminoma cases without detected FOXK1::GRHL1/2 rearrangements revealed GPS2::GRHL1 fusion transcripts in two cases, GPS2::GRHL2 in one case, and GPS2::GRHL3 fusion transcript in one case. Therefore, our study strongly suggests that GRHL1/2/3 gene rearrangements might represent the oncogenic driver in trichogerminoma, a subset of follicular tumours characterized by immature features and numerous Merkel cells. © 2022 The Pathological Society of Great Britain and Ireland.

Wholistic approach: Transcriptomic analysis and beyond using archival material for molecular diagnosis.

Many neoplasms remain unclassified after histopathological examination, which requires further molecular analysis. To this regard, mesenchymal neoplasms are particularly challenging due to the combination of their rarity and the large number of subtypes, and many entities still lack robust diagnostic hallmarks. RNA transcriptomic profiles have proven to be a reliable basis for the classification of previously unclassified tumors and notably for mesenchymal neoplasms. Using exome-based RNA capture sequencing on more than 5000 samples of archival material (formalin-fixed, paraffin-embedded), the combination of expression profiles analyzes (including several clustering methods), fusion genes, and small nucleotide variations has been developed at the Centre Léon Bérard (CLB) in Lyon for the molecular diagnosis of challenging neoplasms and the discovery of new entities. The molecular basis of the technique, the protocol, and the bioinformatics algorithms used are described herein, as well as its advantages and limitations.

Novel read-through fusion transcript Bcl2l2-Pabpn1 in glioblastoma cells.

Read-through fusion transcripts have recently been identified as chimeric RNAs and have since been linked to tumour growth in some cases. Many fusion genes generated by chromosomal rearrangements have been described in glioblastoma. However, read-through fusion transcripts between neighbouring genes in glioblastoma remain unexplored. We performed paired-end RNA-seq of rat C6 glioma cells and normal cells and discovered a read-through fusion transcript Bcl2l2-Pabpn1 in which exon 3 of Bcl-2-like protein 2 (Bcl2l2) fused to exon 2 of Polyadenylate-binding protein 1 (Pabpn1). This fusion transcript was found in both human glioblastoma and normal cells. Unlike other fusions reported in glioblastoma, Bcl2l2-Pabpn1 appeared to result from RNA processing rather than genomic rearrangement. Bcl2l2-Pabpn1 fusion transcript encoded a fusion protein with BH4, BCL and RRM domains. Functionally, Bcl2l2-Pabpn1 knockdown by targeting its fusion junction decreased its expression, and suppressed cell proliferation, migration and invasion in vitro. Mechanistically, Bcl2l2-Pabpn1 blocked Bax activity and activated PI3K/AKT pathway to promote glioblastoma progression. Together, our work characterized a glioblastoma-associated Bcl2l2-Pabpn1 fusion transcript shared by humans and rats.

Regulatory networks and 5' partner usage of miRNA host gene fusions in breast cancer.

Genomic rearrangements in cancer cells can create gene fusions where the juxtaposition of two different genes leads to the production of chimeric proteins or altered gene expression through promoter-swapping. We have previously shown that fusion transcripts involving microRNA (miRNA) host genes contribute to deregulation of miRNA expression regardless of the protein-coding potential of these transcripts. Many different genes can also be used as 5' partners by a miRNA host gene in what we named recurrent miRNA-convergent fusions. Here, we have explored the properties of 5' partners in fusion transcripts that involve miRNA hosts in breast tumours from The Cancer Genome Atlas (TCGA). We hypothesised that firstly, 5' partner genes should belong to pathways and transcriptional programmes that reflect the tumour phenotype and secondly, there should be a selection for fusion events that shape miRNA expression to benefit the tumour cell through the known hallmarks of cancer. We found that the set of 5' partners in miRNA host fusions is non-random, with overrepresentation of highly expressed genes in pathways active in cancer including epithelial-to-mesenchymal transition, translational regulation and oestrogen signalling. Furthermore, many miRNAs were upregulated in samples with host gene fusions, including established oncogenic miRNAs such as mir-21 and the mir-106b~mir-93~mir-25 cluster. To the list of mechanisms for deregulation of miRNA expression, we have added fusion transcripts that change the promoter region. We propose that this adds material for genetic selection and tumour evolution in cancer cells and that miRNA host fusions can act as tumour 'drivers'.

Transcriptome analysis of colorectal cancer liver metastasis: The importance of long non-coding RNAs and fusion transcripts in the disease pathogenesis.

BACKGROUND: Despite several attempts to define the many genomic aspects of colorectal cancer liver metastasis (CRC-LM), there is still a lack of a complete and accurate picture of the cancer transcriptome and its function in the generation of metastasis. METHODS: Cancer Genome Atlas Sequence Read Archive (SRA) was used to get RNA sequencing data for CRC-LM and primary CRC. The CDseqR deconvolution method followed by the edgeR statistical approach was employed to accurately find differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) was used to determine the long non-coding RNA (lncRNA) and mRNA pairs in CRC-LM etiology. Three alternative methods were used to explore fusion transcripts to anticipate the potential driver chimeras. RESULTS: Multiple cancer-related pathways were enriched in the up-regulated genes, including cell cycle, DNA replication, and RNA transport. SPP1 was the most up-regulated gene important in the cellular proliferation and migration and CCDC152 was the most down-regulated gene known in the metastatic spread of CRC. There were seven distinct lncRNAs discovered, two of which were novel (LOC107984834 and LOC107985040) and associated with metastatic related pathways such as the extracellular matrix-receptor interaction. Overall survival analysis demonstrated that SPP1 and LOC107985040 were significantly associated with poor prognosis outcomes. Seven new fusion transcripts were found in seven CRC-LM patients (22.5%) anticipated to have potential driver functions in cancer. CONCLUSION: The newly discovered dysregulated genes and other transcriptome abnormalities could contribute to a better understanding of the CRC-LM underlying mechanism, leading to the development of new diagnostic, prognostic, and therapeutic molecular options for personalized medicine.

Identification of a Novel Oncogenic Fusion Gene SPON1-TRIM29 in Clinical Ovarian Cancer That Promotes Cell and Tumor Growth and Enhances Chemoresistance in A2780 Cells.

Gene structure alterations, such as chromosomal rearrangements that develop fusion genes, often contribute to tumorigenesis. It has been shown that the fusion genes identified in public RNA-sequencing datasets are mainly derived from intrachromosomal rearrangements. In this study, we explored fusion transcripts in clinical ovarian cancer specimens based on our RNA-sequencing data. We successfully identified an in-frame fusion transcript SPON1-TRIM29 in chromosome 11 from a recurrent tumor specimen of high-grade serous carcinoma (HGSC), which was not detected in the corresponding primary carcinoma, and validated the expression of the identical fusion transcript in another tumor from a distinct HGSC patient. Ovarian cancer A2780 cells stably expressing SPON1-TRIM29 exhibited an increase in cell growth, whereas a decrease in apoptosis was observed, even in the presence of anticancer drugs. The siRNA-mediated silencing of SPON1-TRIM29 fusion transcript substantially impaired the enhanced growth of A2780 cells expressing the chimeric gene treated with anticancer drugs. Moreover, a subcutaneous xenograft model using athymic mice indicated that SPON1-TRIM29-expressing A2780 cells rapidly generated tumors in vivo compared to control cells, whose growth was significantly repressed by the fusion-specific siRNA administration. Overall, the SPON1-TRIM29 fusion gene could be involved in carcinogenesis and chemotherapy resistance in ovarian cancer, and offers potential use as a diagnostic and therapeutic target for the disease with the fusion transcript.

The Efficacy of Molecular Analysis in the Diagnosis of Bone and Soft Tissue Sarcoma: A 15-Year Mono-Institutional Study.

The histological diagnosis of sarcoma can be difficult as it sometimes requires the combination of morphological and immunophenotypic analyses with molecular tests. A total of 2705 tissue samples of sarcoma consecutively collected from 2006 until 2020 that had undergone molecular analysis were assessed to evaluate their diagnostic utility compared with histological assessments. A total of 3051 molecular analyses were performed, including 1484 gene fusions tested by c/qRT-PCR, 992 gene rearrangements analysed by FISH, 433 analyses of the gene status of MDM2, 126 mutational analyses and 16 NGS analysis. Of the samples analysed, 68% were from formalin-fixed, paraffin-embedded tissue and 32% were from frozen tissue. C/qRT-PCR and FISH analyses were conclusive on formalin-fixed, paraffin-embedded tissue in 74% and 76% of samples, respectively, but the combination of the two methods gave us conclusive results in 96% and 89% of frozen and formalin-fixed, paraffin-embedded tissues, respectively. We demonstrate the utility of c/qRT-PCR and FISH for sarcoma diagnosis and that each has advantages in specific contexts. We conclude that it is possible to accurately predict the sarcoma subtype using a panel of different subtype-specific FISH probes and c/qRT-PCR assays, thereby greatly facilitating the differential diagnosis of these tumours.

mRNA Capture Sequencing and RT-qPCR for the Detection of Pathognomonic, Novel, and Secondary Fusion Transcripts in FFPE Tissue: A Sarcoma Showcase.

We assess the performance of mRNA capture sequencing to identify fusion transcripts in FFPE tissue of different sarcoma types, followed by RT-qPCR confirmation. To validate our workflow, six positive control tumors with a specific chromosomal rearrangement were analyzed using the TruSight RNA Pan-Cancer Panel. Fusion transcript calling by FusionCatcher confirmed these aberrations and enabled the identification of both fusion gene partners and breakpoints. Next, whole-transcriptome TruSeq RNA Exome sequencing was applied to 17 fusion gene-negative alveolar rhabdomyosarcoma (ARMS) or undifferentiated round cell sarcoma (URCS) tumors, for whom fluorescence in situ hybridization (FISH) did not identify the classical pathognomonic rearrangements. For six patients, a pathognomonic fusion transcript was readily detected, i.e., PAX3-FOXO1 in two ARMS patients, and EWSR1-FLI1, EWSR1-ERG, or EWSR1-NFATC2 in four URCS patients. For the 11 remaining patients, 11 newly identified fusion transcripts were confirmed by RT-qPCR, including COPS3-TOM1L2, NCOA1-DTNB, WWTR1-LINC01986, PLAA-MOB3B, AP1B1-CHEK2, and BRD4-LEUTX fusion transcripts in ARMS patients. Additionally, recurrently detected secondary fusion transcripts in patients diagnosed with EWSR1-NFATC2-positive sarcoma were confirmed (COPS4-TBC1D9, PICALM-SYTL2, SMG6-VPS53, and UBE2F-ALS2). In conclusion, this study shows that mRNA capture sequencing enhances the detection rate of pathognomonic fusions and enables the identification of novel and secondary fusion transcripts in sarcomas.

Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia.

BACKGROUND: Considering the clinical and genetic characteristics, acute lymphoblastic leukemia (ALL) is a rather heterogeneous hematological neoplasm for which current standard diagnostics require various analyses encompassing morphology, immunophenotyping, cytogenetics, and molecular analysis of gene fusions and mutations. Hence, it would be desirable to rely on a technique and an analytical workflow that allows the simultaneous analysis and identification of all the genetic alterations in a single approach. Moreover, based on the results with standard methods, a significant amount of patients have no established abnormalities and hence, cannot further be stratified. METHODS: We performed WTS and WGS in 279 acute lymphoblastic leukemia (ALL) patients (B-cell: n = 211; T-cell: n = 68) to assess the accuracy of WTS, to detect relevant genetic markers, and to classify ALL patients. RESULTS: DNA and RNA-based genotyping was used to ensure correct WTS-WGS pairing. Gene expression analysis reliably assigned samples to the B Cell Precursor (BCP)-ALL or the T-ALL group. Subclassification of BCP-ALL samples was done progressively, assessing first the presence of chromosomal rearrangements by the means of fusion detection. Compared to the standard methods, 97% of the recurrent risk-stratifying fusions could be identified by WTS, assigning 76 samples to their respective entities. Additionally, read-through fusions (indicative of CDKN2A and RB1 gene deletions) were recurrently detected in the cohort along with 57 putative novel fusions, with yet untouched diagnostic potentials. Next, copy number variations were inferred from WTS data to identify relevant ploidy groups, classifying an additional of 31 samples. Lastly, gene expression profiling detected a BCR-ABL1-like signature in 27% of the remaining samples. CONCLUSION: As a single assay, WTS allowed a precise genetic classification for the majority of BCP-ALL patients, and is superior to conventional methods in the cases which lack entity defining genetic abnormalities.

Comparative study of bioinformatic tools for the identification of chimeric RNAs from RNA Sequencing.

Chimeric RNAs are gaining more and more attention as they have broad implications in both cancer and normal physiology. To date, over 40 chimeric RNA prediction methods have been developed to facilitate their identification from RNA sequencing data. However, a limited number of studies have been conducted to compare the performance of these tools; additionally, previous studies have become outdated as more software tools have been developed within the last three years. In this study, we benchmarked 16 chimeric RNA prediction software, including seven top performers in previous benchmarking studies, and nine that were recently developed. We used two simulated and two real RNA-Seq datasets, compared the 16 tools for their sensitivity, positive prediction value (PPV), F-measure, and also documented the computational requirements (time and memory). We noticed that none of the tools are inclusive, and their performance varies depending on the dataset and objects. To increase the detection of true positive events, we also evaluated the pair-wise combination of these methods to suggest the best combination for sensitivity and F-measure. In addition, we compared the performance of the tools for the identification of three classes (read-through, inter-chromosomal and intra-others) of chimeric RNAs. Finally, we performed TOPSIS analyses and ranked the weighted performance of the 16 tools.

FusionPro, a Versatile Proteogenomic Tool for Identification of Novel Fusion Transcripts and Their Potential Translation Products in Cancer Cells.

Fusion proteoforms are translation products derived from gene fusion. Although very rare, the fusion proteoforms play important roles in biomedical science. For example, fusion proteoforms influence the development of tumors by serving as cancer markers or cell cycle regulators. Although numerous studies have reported bioinformatics tools that can predict fusion transcripts, few proteogenomic tools are available that can predict and identify proteoforms. In this study, we develop a versatile proteogenomic tool "FusionPro," which facilitates the identification of fusion transcripts and their potential translatable peptides. FusionPro provides an independent gene fusion prediction module and can build sequence databases for annotated fusion proteoforms. FusionPro shows greater sensitivity than the available fusion finders when analyzing simulated or real RNA sequencing data sets. We use FusionPro to identify 18 fusion junction peptides and three potential fusion-derived peptides by MS/MS-based analysis of leukemia cell lines (Jurkat and K562) and ovarian cancer tissues from the Clinical Proteomic Tumor Analysis Consortium. Among the identified fusion proteins, we molecularly validate two fusion junction isoforms and a translation product of FAM133B:CDK6. Moreover, sequence analysis suggests that the fusion protein participates in the cell cycle progression. In addition, our prediction results indicate that fusion transcripts often have multiple fusion junctions and that these fusion junctions tend to be distributed in a nonrandom pattern at both the chromosome and gene levels. Thus, FusionPro allows users to detect various types of fusion translation products using a transcriptome-informed approach and to gain a comprehensive understanding of the formation and biological roles of fusion proteoforms.

Fusion Genes in Breast Cancer.

Fusion gene is a hybrid form of two distinct genes resulting in broad spectrum of downstream pathway alterations. Gene fusion events are mostly from genomic rearrangements though diverse mechanisms have now been identified from in-depth analyses of next generation sequencing data. While profound level of genomic, transcriptomic driver alterations have been identified, till now, not many gene fusions are found to be the 'driver' of cancer development nor progression.ESR1 gene is a protein coding gene, encoding estrogen receptor, a transcription factor which is a key pathway in hormone sensitive breast cancers. Several hotspot mutations of this ESR1 gene have recently been associated with resistance to endocrine therapy. ESR1 gene fusion with diverse partner genes have also been identified recently, and are suggested to be acquired during previous endocrine therapy. Recurrent ESR1 gene fusions are indicative of ligand-independent hyperactivity according to 3' partner gene found among 1%~ of metastatic hormone sensitive metastatic breast cancers.

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.

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.

Implementation of RNA sequencing and array CGH in the diagnostic workflow of the AIEOP-BFM ALL 2017 trial on acute lymphoblastic leukemia.

Risk-adapted therapy has significantly contributed to improved survival rates in pediatric acute lymphoblastic leukemia (ALL) and reliable detection of chromosomal aberrations is mandatory for risk group stratification. This study evaluated the applicability of panel-based RNA sequencing and array CGH within the diagnostic workflow of the German study group of the international AIEOP-BFM ALL 2017 trial. In a consecutive cohort of 117 children with B cell precursor (BCP) ALL, array analysis identified twelve cases with an IKZF1plus profile of gene deletions and one case of masked hypodiploidy. Genetic markers BCR-ABL1 (n = 1), ETV6-RUNX1 (n = 25), and rearrangements involving KMT2A (n = 3) or TCF3 (n = 3) were assessed by established conventional techniques such as karyotyping, FISH, and RT-PCR. Comparison of these results with RNA sequencing analysis revealed overall consistency in n=115/117 cases, albeit with one undetected AFF1-KMT2A fusion in RNA sequencing and one undetected ETV6-RUNX1 fusion in conventional analyses. The combined application of RNA sequencing, FISH, and CGH+SNP array reliably detected all genetic markers necessary for risk stratification and will be used as the diagnostic standard workflow for BCP-ALL patients enrolled in the AIEOP-BFM ALL 2017 study. Prospectively, consistent collection of genome-wide CGH+SNP array as well as RNA sequencing data will be a valuable source to elucidate new prognostic lesions beyond established markers of pediatric ALL. In this respect, RNA sequencing identified various gene fusions in up to half of the IKZF1plus (n = 6/12) and B-other (n = 19/36) cases but not in cases with hyperdiploid karyotypes (n = 35). Among these fusions, this study reports several previously undescribed in frame PAX5 fusions, including PAX5-MYO1G and PAX5-NCOA6.