Ontology highlight
ABSTRACT:
PROVIDER: PRJNA560281 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR9969960_1.fastq.gz | Fastqsanger.gz | |||
| SRR9969960_2.fastq.gz | Fastqsanger.gz | |||
| SRR9969961_1.fastq.gz | Fastqsanger.gz | |||
| SRR9969961_2.fastq.gz | Fastqsanger.gz | |||
| SRR9969952_1.fastq.gz | Fastqsanger.gz |
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Project description:Development and Verification of an RNA-Seq Assay for the Detection of Gene Fusions in Tumors
| PRJNA436593 | ENA
Project description:Copy number alterations (CNAs) play a fundamental role in cancer development and constitute a potential tool for tailored treatments. The CNAs recognition in formalin fixed paraffin embedded (FFPE) material, to date, relies on fluorescence in situ hybridization, but the introduction of large-scale next-generation sequencing (NGS) has dramatically improved their discovery at genome-wide level. The detection of CNAs by NGS in FFPE material is, nonetheless, a complex issue, which still requires validation studies. Herein, the CNAs detection by a widely used NGS assay (Oncomine Comprehensive Assay plus®, OCA+) were evaluated in 14 FFPE samples mirroring diagnostic daily practice and compared to a whole-genome assay. OCA+, a targeted DNA panel, showed lower CNAs detection sensitivity and equal specificity for gains and losses. According to proprietary software pipeline, OCA+ accurately identify gains characterized by CN ≥5,2. A much less robust threshold (CN ≤1.18) was identified that maximized the difference between true and false positive losses. Orthogonal FISH tests validated seven CNAs characterized by CN gain ≥6 or complete loss. Considering the CNAs growing significance in precision medicine, our findings further prompt towards a robust validation of NGS detection in FFPE materials.
2025-02-12 | GSE277695 | GEO
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.
2014-12-01 | GSE56512 | GEO
Project description:Analyses of gene expression profiling in Nodular fasciitis tumors harboring USP6 fusions Total RNA was obtained from FFPE tissues tumors and profiled using Illumina expression arrays
2016-06-30 | E-GEOD-78991 | biostudies-arrayexpress
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.
2018-04-01 | GSE111320 | GEO
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:Using whole genome mRNA expression profiling of primary human tumors and unsupervised hierarchical cluster analyses, 3 novel molecular subsets (basal, luminal and p53-like subsets) of muscle-invasive bladder cancer (MIBC) were identified. 23 MVAC treated samples were used for the validation of three MIBC subsets MVAC cohort consisted of 23 FFPE pretreatment tumors (TURs) from a Phase III clinical trial were used to validate 3 molecular subsets including basal, luminal and p53-like subsets We used Illumina cDNA-mediated Annealing, Selection, Extension, and Ligation (DASL) assay that is specifically designed for the gene expression of RNA that is extracted from FFPE.
2014-02-10 | E-GEOD-52219 | biostudies-arrayexpress
Project description:OncoScan™ CNV FFPE Assay data for desmoid tumors
| PRJNA1052113 | ENA
Project description:Objection: To evaluate a qPCR-based 32-gene expression assay to determine the cell-of-origin (COO) of diffuse large B-cell lymphoma (DLBCL) with formalin-fixed paraffin-embedded (FFPE) tissue. Methods: The most established subtyping algorithm, the COO model, categorizes DLBCL into activated B-cell (ABC) and germinal center B-cell (GCB)-like subgroups through gene expression profiling. Biopsy of DLBCL patients with paired FFPE and fresh frozen tissue were collected to assign COO based on the immunohistochemistry (IHC) algorithm (Han’s algorithm), qPCR-based 32-gene expression assay (DLBCL-COO assay) and global gene expression profiling with RNA-seq. Results: The DLBCL-COO assay demonstrated a significantly superior concordance of COO determination with the “gold standard” RNA-seq, comparing with the IHC assignment with Han’s algorithm (91.9% versus 77.5%; P = 0.005). Furthermore, overall survival of GCB patients defined by DLBCL-COO assay was superior significantly towards the ABC patients (Figure 2B, P = 0.023). This effect was not seen when tumors were classified by IHC algorithm. Conclusions: The DLBCL-COO assay provides flexibility and accuracy in DLBCL subtype characterization. These subtype distinctions should help guiding prognostic and therapeutic options for the patients in our daily practice.
2020-04-22 | GSE147986 | GEO
Project description:Advantages of RNA-Seq over array based platforms are quantitative gene expression and discovery of expressed single nucleotide variants (eSNVs) and fusion transcripts from a single platform, but the sensitivity for each of these characteristics is unknown. We measured gene expression in a set of manually degraded RNAs, nine pairs of matched fresh-frozen, and FFPE RNA isolated from breast tumor with the hybridization based, NanoString nCounter, (226 gene panel) and with whole transcriptome RNA-Seq using RiboZeroGold ScriptSeq V2 library preparation kits. We performed correlation analyses of gene expression between samples and across platforms. We then specifically assessed whole transcriptome expression of lincRNA and discovery of eSNVs and fusion transcripts in the FFPE RNA-Seq data. For gene expression in the manually degraded samples, we observed Pearson correlation of >0.94 and >0.80 with NanoString and ScriptSeq protocols respectively. Gene expression data for matched fresh-frozen and FFPE samples yielded mean Pearson correlations of 0.874 and 0.783 for NanoString (226 genes) and ScriptSeq whole transcriptome protocols respectively. Specifically for lincRNAs, we observed superb Pearson correlation (0.988) between matched fresh-frozen and FFPE pairs. FFPE samples across NanoString and RNA-Seq platforms gave a mean Pearson correlation of 0.838. In FFPE libraries, we detected 53.4% of high confidence SNVs and 24% of high confidence fusion transcripts. Sensitivity of fusion transcript detection was not overcome by an increase in depth of sequencing up to 3-fold (increase from ~56 to ~159 million reads). Both NanoString and ScriptSeq RNA-Seq technologies yield reliable gene expression data for degraded and FFPE material. The high degree of correlation between NanoString and RNA-Seq platforms suggests discovery based whole transciptome studies from FFPE material will produce reliable expression data. The RiboZeroGold ScriptSeq protocol performed particularly well for lincRNA expression from FFPE libraries but detection of eSNV and fusion transcripts was less sensitive.
2013-12-06 | GSE51124 | GEO