DAC for "Detection of Gene Fusions using Targeted Next-Generation Sequencing – a Comparative Evaluation"
Ontology highlight
ABSTRACT:
PROVIDER: EGAC00001001905 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:BackgroundGene fusions represent promising targets for cancer therapy in lung cancer. Reliable detection of multiple gene fusions is therefore essential.MethodsFive commercially available parallel sequencing assays were evaluated for their ability to detect gene fusions in eight cell lines and 18 FFPE tissue samples carrying a variety of known gene fusions. Four RNA-based assays and one DNA-based assay were compared; two were hybrid capture-based, TruSight Tumor 170 Assay (Illumina) and SureSelect XT HS Custom Panel (Agilent), and three were amplicon-based, Archer FusionPlex Lung Panel (ArcherDX), QIAseq RNAscan Custom Panel (Qiagen) and Oncomine Focus Assay (Thermo Fisher Scientific).ResultsThe Illumina assay detected all tested fusions and showed the smallest number of false positive results. Both, the ArcherDX and Qiagen panels missed only one fusion event. Among the RNA-based assays, the Qiagen panel had the highest number of false positive events. The Oncomine Focus Assay (Thermo Fisher Scientific) was the least adequate assay for our purposes, seven fusions were not covered by the assay and two fusions were classified as uncertain. The DNA-based SureSelect XT HS Custom Panel (Agilent) missed three fusions and nine fusions were only called by one software version. Additionally, many false positive fusions were observed.ConclusionsIn summary, especially RNA-based parallel sequencing approaches are potent tools for reliable detection of targetable gene fusions in clinical diagnostics.
| S-EPMC7912891 | biostudies-literature
Project description:Gene fusions represent promising targets for cancer therapy in lung cancer. Reliable detection of multiple gene fusions is therefore essential. Here, five commercially available parallel sequencing assays were evaluated for their ability to detect gene fusions in eight cell lines and 18 FFPE tissue samples carrying a variety of known gene fusions. Four RNA-based assays and one DNA-based assay were compared; two were hybrid capture-based, TruSight Tumor 170 Assay (Illumina) and SureSelect XT HS Custom Panel (Agilent), and three were amplicon-based, Archer FusionPlex Lung Panel (ArcherDX), QIAseq RNAscan Custom Panel (Qiagen) and Oncomine Focus Assay (Thermo Fisher Scientific).
| EGAS00001004934 | EGA
Project description:Objective: This study aimed to identify ROS1 fusion partners in Chinese patients with solid tumors. Methods: Next-generation sequencing (NGS) analysis was used to detect ROS1 rearrangement in 45,438 Chinese patients with solid tumors between 2015 and 2020, and the clinical characteristics and genetic features of gene fusion were evaluated. H&E staining of the excised tumor tissues was conducted. Samples with a tumor cell content ≥ 20% were included for subsequent DNA extraction and sequencing analysis. Results: A total of 92 patients with ROS1 rearrangements were identified using next-generation sequencing, and the most common histological type lung cancer. From the 92 ROS1 fusion cases, 24 ROS1 fusion partners had been identified, including 14 novel partners and 10 reported partners. Of these, CD74, EZR, SDC4, and TPM3 were the four most frequently occurring partners. Fourteen novel ROS1 fusion partners were detected in 16 patients, including DCBLD1-ROS1, FRK-ROS1, and VGLL2-ROS1. In many patients, the ROS1 breakpoint was located between exons 32 and 34. Conclusion: This study describes 14 novel ROS1 fusion partners based on the largest ROS1 fusion cohort, and the ROS1 breakpoint was mostly located between exons 32 and 34. Additionally, next-generation sequencing is an optional method for identifying novel ROS1 fusions.
| S-EPMC9798300 | biostudies-literature
Project description:138 papillary thyroid carcinoma (PTC) samples were assessed for somatic mutation profile and fusion genes by targeted resequencing using a cancer panel (ThyGenCapTM) targeting 244 cancer-related genes and 20 potential fusion genes. At least one genetic alteration (including mutations and fusion genes) was observed in 118/138 (85.5%) samples. The most frequently mutated gene was BRAF V600E (57.2%). Moreover, we identified 11 fusion genes including eight previously reported ones and three novel fusion genes, UEVLD-RET, OSBPL9-BRAF, and SQSTM1-NTRK3. Alterations affecting the mitogen-activated protein kinase (MAPK) signaling pathway components were seen in 69.6% of the PTC cases and all of these driver mutations were mutually exclusive. Univariate analysis ascertained that the fusion genes were strongly associated with distinct clinicopathological characteristics, such as young age, local invasion, extensive metastasis, and disease stage. In conclusion, our approach facilitated simultaneous high-throughput detection of gene fusions and somatic mutations in PTC samples.
| S-EPMC5542227 | biostudies-literature
Project description:With next-generation DNA sequencing technologies, one can interrogate a specific genomic region of interest at very high depth of coverage and identify less prevalent, rare mutations in heterogeneous clinical samples. However, the mutation detection levels are limited by the error rate of the sequencing technology as well as by the availability of variant-calling algorithms with high statistical power and low false positive rates. We demonstrate that we can robustly detect mutations at 0.1% fractional representation. This represents accurate detection of one mutant per every 1000 wild-type alleles. To achieve this sensitive level of mutation detection, we integrate a high accuracy indexing strategy and reference replication for estimating sequencing error variance. We employ a statistical model to estimate the error rate at each position of the reference and to quantify the fraction of variant base in the sample. Our method is highly specific (99%) and sensitive (100%) when applied to a known 0.1% sample fraction admixture of two synthetic DNA samples to validate our method. As a clinical application of this method, we analyzed nine clinical samples of H1N1 influenza A and detected an oseltamivir (antiviral therapy) resistance mutation in the H1N1 neuraminidase gene at a sample fraction of 0.18%.
| S-EPMC3245950 | biostudies-literature
Project description:The identification of recurrent gene rearrangements in the clinical laboratory is the cornerstone for risk stratification and treatment decisions in many malignant tumors. Studies have reported that targeted next-generation sequencing assays have the potential to identify such rearrangements; however, their utility in the clinical laboratory is unknown. We examine the sensitivity and specificity of ALK and KMT2A (MLL) rearrangement detection by next-generation sequencing in the clinical laboratory. We analyzed a series of seven ALK rearranged cancers, six KMT2A rearranged leukemias, and 77 ALK/KMT2A rearrangement-negative cancers, previously tested by fluorescence in situ hybridization (FISH). Rearrangement detection was tested using publicly available software tools, including Breakdancer, ClusterFAST, CREST, and Hydra. Using Breakdancer and ClusterFAST, we detected ALK rearrangements in seven of seven FISH-positive cases and KMT2A rearrangements in six of six FISH-positive cases. Among the 77 ALK/KMT2A FISH-negative cases, no false-positive identifications were made by Breakdancer or ClusterFAST. Further, we identified one ALK rearranged case with a noncanonical intron 16 breakpoint, which is likely to affect its response to targeted inhibitors. We report that clinically relevant chromosomal rearrangements can be detected from targeted gene panel-based next-generation sequencing with sensitivity and specificity equivalent to that of FISH while providing finer-scale information and increased efficiency for molecular oncology testing.
| S-EPMC4078366 | biostudies-literature
Project description:Half of prostate cancers harbor gene fusions between TMPRSS2 and members of the ETS transcription factor family. To date, little is known about the presence of non-ETS fusion events in prostate cancer. We used next-generation transcriptome sequencing (RNA-seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes ETV1 and ERG, and four involving non-ETS genes such as CDKN1A (p21), CD9, and IKBKB (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene RSRC2. The novel gene fusions are found to be of low frequency, but, interestingly, the non-ETS fusions were all present in prostate cancer harboring the TMPRSS2-ERG gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement-prone phenotype.
| S-EPMC3012926 | biostudies-literature
Project description:The laboratory diagnosis of infectious diseases, especially those caused by mixed infections, is challenging. Routinely, it requires submission of multiple samples to separate laboratories. Advances in next-generation sequencing (NGS) have provided the opportunity for development of a comprehensive method to identify infectious agents. This study describes the use of target-specific primers for PCR-mediated amplification with the NGS technology in which pathogen genomic regions of interest are enriched and selectively sequenced from clinical samples. In the study, 198 primers were designed to target 43 common bovine and small-ruminant bacterial, fungal, viral, and parasitic pathogens, and a bioinformatics tool was specifically constructed for the detection of targeted pathogens. The primers were confirmed to detect the intended pathogens by testing reference strains and isolates. The method was then validated using 60 clinical samples (including tissues, feces, and milk) that were also tested with other routine diagnostic techniques. The detection limits of the targeted NGS method were evaluated using 10 representative pathogens that were also tested by quantitative PCR (qPCR), and the NGS method was able to detect the organisms from samples with qPCR threshold cycle (CT ) values in the 30s. The method was successful for the detection of multiple pathogens in the clinical samples, including some additional pathogens missed by the routine techniques because the specific tests needed for the particular organisms were not performed. The results demonstrate the feasibility of the approach and indicate that it is possible to incorporate NGS as a diagnostic tool in a cost-effective manner into a veterinary diagnostic laboratory.
| S-EPMC6018347 | biostudies-literature
Project description:Equine infectious disease outbreaks may have profound economic impact, resulting in losses of millions of dollars of revenue as a result of horse loss, quarantine, and cancelled events. Early and accurate diagnosis is essential to limit the spread of infectious diseases. However, laboratory detection of infectious agents, especially the simultaneous detection of multiple agents, can be challenging to the clinician and diagnostic laboratory. Next-generation sequencing (NGS), which allows millions of DNA templates to be sequenced simultaneously in a single reaction, is an ideal technology for comprehensive testing. We conducted a proof-of-concept study of targeted NGS to detect 62 common equine bacterial, viral, and parasitic pathogens in clinical samples. We designed 264 primers and constructed a bioinformatics tool for the detection of targeted pathogens. The designed primers were able to specifically detect the intended pathogens. Results of testing 27 clinical samples with our targeted NGS assay compared with results of routine tests (assessed as a group) yielded positive percent agreement of 81% and negative percent agreement of 83%, overall agreement of 81%, and kappa of 0.56 (moderate agreement). This moderate agreement was likely the result of low sensitivity of some primers. However, our NGS assay successfully detected multiple pathogens in the clinical samples, including some pathogens missed by routine techniques.
| S-EPMC7953111 | biostudies-literature
Project description:Antibiotic resistance (AR) is an epidemic of increasing magnitude requiring rapid identification and profiling for appropriate and timely therapeutic measures and containment strategies. In this context, ciprofloxacin is part of the first-line of countermeasures against numerous high consequence bacteria. Significant resistance can occur via single nucleotide polymorphisms (SNP) and deletions within ciprofloxacin targeted genes. Ideally, use of ciprofloxacin would be prefaced with AR determination to avoid overuse or misuse of the antibiotic. Here, we describe the development and evaluation of a panel of 44 single-stranded molecular inversion probes (MIPs) coupled to next-generation sequencing (NGS) for the detection of genetic variants known to confer ciprofloxacin resistance in Bacillus anthracis, Yersinia pestis, and Francisella tularensis. Sequencing results demonstrate MIPs capture and amplify targeted regions of interest at significant levels of coverage. Depending on the genetic variant, limits of detection (LOD) for high-throughput pooled sequencing ranged from approximately 300-1800 input genome copies. LODs increased 10-fold in the presence of contaminating human genome DNA. In addition, we show that MIPs can be used as an enrichment step with high resolution melt (HRM) real-time PCR which is a sensitive assay with a rapid time-to-answer. Overall, this technology is a multiplexable upfront enrichment applicable with multiple downstream molecular assays for the detection of targeted genetic regions.
| S-EPMC4865750 | biostudies-literature