ABSTRACT: Targeted long-read nanopore sequencing.
Abstract: Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment. Fusion gene partner choice and breakpoint-position promiscuity restricts diagnostic detection, even for known and recurrent configurations. To accurately and impartially identify fusions, we developed FUDGE: FUsion Detection from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for fusion gene driver enrichment - without prior knowledge of fusion partner or breakpoint-location – to long-read Nanopore sequencing with the bioinformatics pipeline NanoFG. FUDGE has flexible target-loci choices and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in one sequencing run. We observe on-average 665 fold breakpoint-site enrichment and identify nucleotide resolution fusion breakpoints - within two days. The assay identifies cancer cell line and tumor sample fusions irrespective of partner gene or breakpoint-position. FUDGE is a rapid and versatile fusion detection assay, providing unparalleled opportunity for diagnostic pan-cancer fusion detection.
Project description:Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508-fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.
Project description:Studies of fusion genes have mainly focused on the formation of fusions that result in the production of hybrid proteins or, alternatively, on promoter-switching events that put a gene under the control of aberrant signals. However, gene fusions may also disrupt the transcriptional control of genes that are encoded in introns downstream of the breakpoint. By ignoring structural constraints of the transcribed fusions, we highlight the importance of a largely unexplored function of fusion genes. Using breast cancer as an example, we show that miRNA host genes are specifically enriched in fusion genes and that many different, low-frequency, 5' partners may deregulate the same miRNA irrespective of the coding potential of the fusion transcript. These results indicate that the concept of recurrence, defined by the rate of functionally important aberrations, needs to be revised to encompass convergent fusions that affect a miRNA independently of transcript structure and protein-coding potential. Overall design: Illumina paired-end RNA-sequencing was performed on 1600 sequencing libraries (49 technical replicates, 1552 tumour samples) for fusion gene detection analysis. miRNA sequencing was performed on a subset of the fusion detection samples, 191 sequence libraries (5 technical replicates, 186 tumour samples), for miRNA transcript expression estimation. ------------------------------------ This represents the miRNA sequencing component of 191 libraries only. -------------------------------------- The authors state "due to Swedish law, the patient consent, and the risk that the sequencing data contains personally-identifiable information andhereditary mutations, we cannot deposit the short sequencing read data in a repository". Thus, this submission is incomplete.
Project description:We report the design and implementation of a "breakpoint analysis" pipeline to discover novel gene fusions by tell-tale transcript level or genomic DNA copy number transitions occurring within genes. We use this method to prioritize candidate rearrangements from high density array CGH datasets as well as exon-resolution expression microarrays. We mine both publicly available data as well as datasets generated in our laboratory. Several gene fusion candidates were chosen for further characterization, and corresponding samples were profiled using paired end RNA sequencing to discover the identity of the gene fusion. Using this approach, we report the discovery and characterization of novel gene fusions spanning multiple cancer subtypes including angiosarcoma, pancreatic cancer, anaplastic astrocytoma, melanoma, breast cancer, and T-cell acute lymphoblastic leukemia. Taken together, this study provides a robust approach for gene fusion discovery, and our results highlight a more widespread role of fusion genes in cancer pathogenesis. Breakpoint analysis for the discovery of novel gene fusions across human cancers
Project description:Fusion genes can be oncogenic drivers in a variety of cancer types and represent potential targets for targeted therapy. The BRAF gene is frequently involved in oncogenic fusions, with fusion frequencies of 0.2-3% throughout different cancers. However, BRAF fusions rarely occur in the same gene configuration, potentially challenging personalized therapy design. In particular, the influence that is imposed by the wide variety of fusion partners on the oncogenic role of BRAF during tumor growth and drug response is unknown. Here, we used patient-derived colorectal cancer organoids to functionally characterize and cross-compare previously identified BRAF fusions containing various partner genes (AGAP3, DLG1 and TRIM24) with respect to cellular behaviour, downstream signaling activation and response to targeted therapies. We demonstrate that 5’ partner choice of BRAF fusions affects their subcellular localization and intracellular signaling capacity. In particular the DLG1-BRAF fusion protein showed distinct localization to the plasma membrane and exhibited increased activation of downstream MAPK signaling under unperturbed conditions. Moreover, phosphoproteomics and RNA sequencing identified distinct subsets of affected signaling pathways and altered gene expression of BRAF fusions. The different BRAF fusions exhibited varying sensitivities to simultaneous targeted inhibition of MEK and the EGF receptor family. However, all BRAF fusions conveyed resistance to targeted monotherapy against the EGF receptor family, suggesting that BRAF fusions should be screened alongside other MAPK pathway alterations to identify mCRC patients to exclude from cetuximab treatment
Project description:Purpose: Assessment of the performance characteristics of an RNA-Seq assay designed to detect gene fusions in 573 genes to aid in the management of cancer patients. Methods: Polyadenylated RNA was converted to cDNA which was then used to prepare NGS libraries that were sequenced on a HiSeq 2500 instrument and analyzed with an in-house developed bioinformatic pipeline. Results: The assay identified 38 of 41 (93%) gene fusions previously detected by a different laboratory using FISH, RT-PCR, or RNA-Seq for a sensitivity of 93%. No false positive gene fusions were identified in 15 normal tissue specimens and 10 tumor specimens that were negative for fusions by RNA-Seq in a different laboratory (100% specificity). The assay also identified 22 fusions in 17 tumor specimens that had not been detected by other methods. Nineteen of the 22 fusions had not previously been described. Good intra- and inter-assay reproducibility was observed with complete concordance for the presence or absence of gene fusions in replicates. The analytical sensitivity of the assay was tested by diluting RNA isolated from gene fusion positive cases with fusion negative RNA. Gene fusions were generally detectable down to 12.5% dilutions for most fusions and as little as 3% for some fusions. The assay identified 38 of 41 (93%) gene fusions previously detected by a different laboratory using FISH, RT-PCR, or RNA-Seq for a sensitivity of 93%. No false positive gene fusions were identified in 15 normal tissue specimens and 10 tumor specimens that were negative for fusions by RNA-Seq in a different laboratory (100% specificity). The assay also identified 22 fusions in 17 tumor specimens that had not been detected by other methods. Nineteen of the 22 fusions had not previously been described. Good intra- and inter-assay reproducibility was observed with complete concordance for the presence or absence of gene fusions in replicates. The analytical sensitivity of the assay was tested by diluting RNA isolated from gene fusion positive cases with fusion negative RNA. Gene fusions were generally detectable down to 12.5% dilutions for most fusions and as little as 3% for some fusions. This assay should be useful for identifying cancer patients that may benefit from both FDA-approved and investigational targeted therapies. Overall design: Sequencing data was generated using Hiseq 2500 with a library of 101 paired end reads in the rapid run mode
Project description:Gene fusions and chimeric transcripts occur frequently in cancers and in some cases drive the development of the disease. An accurate detection of these events is crucial for cancer research and in a long-term perspective could be applied for personalized therapy. RNA-seq technology has been established as an efficient approach to investigate transcriptomes and search for gene fusions and chimeric transcripts on a genome-wide scale. A number of computational methods for the detection of gene fusions from RNA-seq data have been developed. However, recent studies demonstrate differences between commonly used approaches in terms of specificity and sensitivity. Moreover their ability to detect gene fusions on the isoform level has not been studied carefully so far. Here we propose a novel computational approach called InFusion for fusion gene detection from deep RNA sequencing data. Validation of InFusion on simulated and on several public RNA-seq datasets demonstrated better detection accuracy compared to other tools. We also performed deep RNA sequencing of two well-established prostate cancer cell lines. Using these data we showed that InFusion is capable of discovering alternatively spliced gene fusion isoforms as well as chimeric transcripts that include non-exonic regions. In addition our method can detect anti-sense transcription in the fusions by incorporating strand specificity of the sequencing library. Overall design: Detection of fusion genes and chimeric transcripts from deep RNA-seq data
Project description:Purpose: The primary goal of this study was to identify gene-expression profiles of anaplastic thyroid cancer and to identify some novel in-frame gene fusions that could result in translated protein products affecting the development of anaplastic thyroid cancer. Methods: RNAseq Data was processed with TCGA UNC V2 RNAseq protocol and different expressed genes were identify by using DESeq2, limma-voom, and edgeR. Potential fusion genes were identified by using SOAPfuse, Chimerascan and TopHat-Fusion. Potential fusion genes were confirmed by cDNA PCR and Sanger sequencing. Results: A total of 21 fusion genes were detected, including six predicted in-frame fusions; none were recurrent. Global gene expression analysis showed 661 genes to be differentially expressed between anaplastic thyroid cancer and papillary thyroid cancer cell lines, with pathway enrichment analyses showing downregulation of TP53-signaling as well as cell adhesion molecules in anaplastic thyroid cancer . Conclusions: Our study represents the first detailed analysis of anaplastic thyroid cancer cell lines and found several novel in-frame gene fusions that could result in translated protein products affecting the development of anaplastic thyroid cancer. These data provide novel insights into the tumorigenesis of anaplastic thyroid cancer and may be used to identify new therapeutic targets. Overall design: Gene expression profiles of anaplastic thyroid cancer cell lines and papillary thyroid cancer cell lines were generated by deep sequencing by using Illumina HiSeq2000 platform.
Project description:Pilocytic astrocytoma (PA) is the most common pediatric brain tumor. A recurrent feature of PA is deregulation of the mitogen activated protein kinase (MAPK) pathway most often through KIAA1549-BRAF fusion, but also by other BRAF- or RAF1-gene fusions and point mutations (e.g. BRAFV600E). These features may serve as diagnostic and prognostic markers, and also facilitate development of targeted therapy. The aim of this study was to characterize the genetic alterations underlying the development of PA tumor in six cases, and evaluate methods for fusion oncogene detection. Using a combined analysis of RNA sequencing and copy number variation data we identified a new BRAF fusion involving the 5’ gene fusion partner GTF2I (7q11.23), not previously described in PA. The novel GTF2I-BRAF 19-10 fusion was found in one case, while the other five cases harbored the frequent KIAA1549-BRAF 16-9 fusion gene. Comparing fusion detection methods, Fluorescence in situ hybridization with BRAF break apart probe was the most sensitive method for detection of the two different BRAF rearrangements (GTF2I-BRAF and KIAA1549-BRAF). Our finding of a novel BRAF fusion in PA further emphasis the important role of B-Raf in tumorigenesis of these tumor types. Also, the growing list of BRAF/RAF gene fusions suggests these to be informative tumor markers in molecular diagnostics, which could guide future treatment strategies.
Project description:Fusion genes may be oncogenic drivers and potential targets for personalized therapies in a variety of cancer types. The BRAF gene is frequently involved in oncogenic fusions, with fusion frequencies of 0.2-3% throughout different cancers. BRAF can be fused to a wide variety of genes, however, BRAF fusions rarely occur in the exact same gene configuration, making assessment of the fusion relevance and decision for drug treatment challenging. Here, we devised a colorectal cancer organoid-based platform to functionally characterize diverse BRAF fusions, containing various partner genes (AGAP3, DLG1 and TRIM24). We compared these BRAF fusions with respect to cellular behaviour, downstream signaling activation and response to targeted therapies. We found that 5’ partner choice of BRAF affects cellular localization and intracellular signaling capacities of the fusion genes. The DLG1-BRAF fusion gene showed distinct localization to the plasma membrane and exhibited increased levels of MAPK pathway activation under unperturbed conditions. Furthermore, the different BRAF fusions showed varying sensitivities to the targeted inhibition of ERK and BRAF, with the DLG1-BRAF fusion being the most sensitive. Additionally, RNA-sequencing identified distinct subsets of genes affected by the DLG1-BRAF fusion gene. Importantly, all fusion genes conveyed resistance to the clinically relevant EGFR/HER2/HER4-inhibitor afatinib, suggesting that BRAF fusions should be screened alongside other MAPK pathway alterations to identify mCRC patients amenable to cetuximab treatment. In summary, we developed a platform to efficiently assess molecular and cellular effects of fusion genes, and revealed that differential drug responses and distinct gene expression profiles can be induced by different BRAF fusions .
Project description:Purpose: Popular methods for library preparation in RNA-seq such as Illumina TruSeq® RNA v2 kit use a poly-A pulldown strategy. Such methods can cause loss of coverage at the 5’ end of genes, impacting the ability to detect fusions when used on degraded samples. The goal of this study was to quantify the effects RNA degradation has on fusion detection when using poly-A selected mRNA and to identify the variables involved in this process Methods: Total RNA was extracted from solid tumor tissue and whole blood using the Qiagen® miRNeasy Micro and Mini kits, respectively. The KU812 cell line was purchased from Sigma-Aldrich (St. Louis, MO) and UHR (Universal Human Reference RNA) was purchased from Agilent (Santa Clara, CA). UHR is a mixture of cell lines derived from breast adenocarcinoma, hepatoblastoma, cervix adenocarcinoma, testis embryonal carcinoma, gliobastoma, melanoma, liposarcoma, histiocytic lymphoma, lymphoblastic leukemia and plasmocytoma. For Degradation experiments, two micrograms of human universal reference RNA (UHR) (Agilent Technologies, Santa Clara, CA) and 1ug of RNA extracted from KU812 cell line (purchased from ATCC) were degraded at 74oC from 1 to 11 minutes in 1 minute intervals, using the NEBNext® Magnesium RNA Fragmentation Module Kit (NEB, Ipswich, MA). RNA was then purified and concentrated with RNeasy MinElute Cleanup Kit (Qiagen, Valencia, CA). Results: In this study, we designed experiments using artificially degraded RNA from cell lines as well as naturally degraded RNA from tissue samples to quantify the effect RNA degradation has on fusion detection when using poly-A selected RNA libraries We found that both the RNA degradation level and the distance from the 3’ end of a gene, negatively impact the read coverage profile in RNA-seq. Furthermore, the median transcript coverage decreases exponentially as a function of the distance from the 3’ end and there is a linear relationship between the coverage decay rate and the RNA integrity number (RIN). Conclusions: we found that when using poly-A pulldown techniques for library preparation in RNA-seq, the fusion sensitivity is negatively impacted by both sample degradation and distance of the fusion breakpoint from the 3’ end and developed graphs that show such effect. Such graphs can be useful in assessing the fusion sensitivity of RNA-seq in both research and clinical settings Overall design: Sequencing data was generated using Hiseq 2500 with a library of 101 paired end reads in the rapid run mode