Fusion discovery in breast cancer cell line
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE52643 | GEO | 2013/11/22
SECONDARY ACCESSION(S): PRJNA229558
REPOSITORIES: GEO
Similar Datasets
Project description:SnowShoes-FTD, a fusion transcript discovery tool, was used to identify fusions in breast cancer cell lines using the RNA-Seq data Total RNA extracted from cell lines. The total RNA was used for construction of RNA-Seq library for RNA-Sequencing.
2013-11-22 | E-GEOD-52643 | biostudies-arrayexpress
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.
2017-10-31 | GSE100769 | 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. We performed RNASeq on RNA from nine matched pairs of fresh-frozen and FFPE tissues from breast cancer patients. The goal was to test the RiboZeroGold ScriptSeq complete low input library preparation kit for degraded RNA samples.
2013-12-06 | E-GEOD-51124 | biostudies-arrayexpress
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
Project description: Not available
| S-ECPF-GEOD-52643 | biostudies-other
Project description:Transcriptionally active ESR1 fusions promote endocrine therapy (ET)-resistant growth and metastasis of estrogen receptor-alpha positive (ERα+) breast cancer. Currently, there are no targeted treatment options for tumors harboring active fusions because the ESR1 ligand binding domain (LBD) has been replaced with non-drug binding sequences from the 3’ partner gene. A mass spectrometry (MS)-based Kinase Inhibitor Pulldown Assay (KIPA) demonstrated an increase of multiple receptor tyrosine kinases including RET in T47D cells expressing active ESR1 fusions. Integrated proteogenomics defined tumor subsets that could be responsive to RET and CDK4/6 directed therapy from 22 biologically heterogeneous ERα+ patient-derived xenograft (PDX) tumors. Inhibition of RET by repurposing an FDA-approved drug significantly suppressed ESR1 fusion-driven growth of cell, PDX-derived organoid (PDXO) and PDX models. CDK4/6 inhibitor treatment showed similar tumor reductions to RET inhibition. Here, we reveal therapeutic kinase vulnerabilities in ESR1 fusion-driven tumors, which will lay the framework for future clinical trials.
2023-10-24 | PXD033339 | Pride
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
2013-05-31 | E-GEOD-45133 | biostudies-arrayexpress
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:MLL-fusions represent a large group of leukemia drivers, whose diversity originates from the vast molecular heterogeneity of C-terminal fusion partners of MLL protein. While studies of selected MLL-fusions have revealed critical molecular pathways, unifying mechanisms across all MLL-fusions remain poorly understood. We present the first comprehensive survey of protein-protein interactions of seven distantly related MLL-fusion proteins: MLL-AF1p, MLL-AF4, MLL-AF9, MLL-CBP, MLL-EEN, MLL-ENL and MLL-GAS7.
2018-05-25 | PXD009338 | Pride
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
2020-01-16 | PXD013461 | Pride