Similar Datasets
Project description:Development of PEAC-seq for unbiased in vivo off-target detection
2022-11-14 | GSE179523 | GEO
Project description:A common technique used for sensitive and specific diagnostic virus detection in clinical samples is PCR. However, an unbiased diagnostic microarray containing probes for all human pathogens could replace hundreds of individual PCR-reactions and remove the need for a clear clinical hypothesis regarding a suspected pathogen. We have established such a diagnostic platform for unbiased random amplification and subsequent microarray identification of viral pathogens in clinical samples. We show that Phi29 polymerase-amplification of a diverse set of clinical samples generates enough viral material for successful identification by the Microbial Detection Array developed at the Lawrence Livermore National Laboratory, California, USA, demonstrating the potential of the microarray technique for broad-spectrum pathogen detection. We conclude that this method detects both DNA and RNA virus, present in the same sample, as well as differentiates between different virus subtypes. We propose this assay for unbiased diagnostic analysis of all viruses in clinical samples. 19 clinical samples were analyzed for presence of virus using the MDA microarray. One of the samples is a negative control (water). One HCV-positive serum sample is included twice (HCV+1 and HCV+2).
2011-04-14 | E-GEOD-28597 | biostudies-arrayexpress
Project description:A common technique used for sensitive and specific diagnostic virus detection in clinical samples is PCR. However, an unbiased diagnostic microarray containing probes for all human pathogens could replace hundreds of individual PCR-reactions and remove the need for a clear clinical hypothesis regarding a suspected pathogen. We have established such a diagnostic platform for unbiased random amplification and subsequent microarray identification of viral pathogens in clinical samples. We show that Phi29 polymerase-amplification of a diverse set of clinical samples generates enough viral material for successful identification by the Microbial Detection Array developed at the Lawrence Livermore National Laboratory, California, USA, demonstrating the potential of the microarray technique for broad-spectrum pathogen detection. We conclude that this method detects both DNA and RNA virus, present in the same sample, as well as differentiates between different virus subtypes. We propose this assay for unbiased diagnostic analysis of all viruses in clinical samples.
2011-04-14 | GSE28597 | GEO
Project description: Not available
| S-EPMC6589096 | biostudies-literature
Project description:The accessibility of cell surface proteins makes them tractable for cancer immunotherapy, but identifying suitable targets remains challenging, and resistance to treatment is common. Technical difficulties precluding the use of whole cell proteomic approaches to characterize cell surface proteins include low abundance, hydrophobicity, and a lack of protease cleavage sites. Furthermore, neither whole-cell proteomic nor transcriptomic data can accurately quantify protein expression at the plasma membrane. Resistance to immunotherapies is commonly mediated by downregulation of the target protein, a particular problem when immunotherapies fail to inhibit a specific biological pathway. Here we have used plasma membrane profiling of primary human myeloma cells to identify an unprecedented number of cell surface proteins and quantify for the first time the entire cell surface proteome of a primary cancer. This approach revealed a novel therapeutic target, SEMA4A, which we potently and selectively targeted with an antibody-drug conjugate in vitro and in vivo. Reduction of SEMA4A expression resulted in marked impairment of myeloma cell growth in vitro, indicating that myeloma cells cannot downregulate SEMA4A to avoid detection. Our data therefore reveal not only a novel myeloma target but provide an exemplar of a top-down approach from the unbiased characterization of a cancer cell surface proteome to novel immunotherapeutic target.
2022-01-24 | PXD014165 | Pride
Project description:m6A is the most abundant internal modification in eukaryotic mRNA. It is introduced by METTL3-METTL14 and tunes mRNA metabolism, impacting cell differentiation and development. Precise transcriptome-wide assignment of m6A sites is of utmost importance. However, m6A does not interfere with Watson-Crick base pairing making polymerase-based detection challenging. We developed a chemical biology approach for the precise mapping of methyltransferase (MTase) target sites based on the introduction of a bioorthogonal propargyl group in vitro and in cells. We show that propargyl can be introduced enzymatically by wild-type METTL3-METTL14. Reverse transcription terminated up to 65 % at m6A sites after bioconjugation and purification, hence enabling detection of METTL3-METTL14 target sites by next generation sequencing. Importantly, we implemented metabolic propargyl labeling of RNA MTase target sites in vivo based on propargyl-L-selenohomocysteine and validated different types of known rRNA methylation sites.
2018-02-21 | GSE109298 | GEO
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.
| EGAS00001003964 | EGA
Project description:We developed a new approach called antibody detection of translocations (ADOT) which combines a transcriptional microarray-based approach with a novel antibody-based detection method to detect translocations in cancer. ADOT allows for the accurate and sensitive identification of translocations and provides exon-level information about the fusion transcript. ADOT can detect translocations in poor quality unprocessed total RNA. We demonstrate the feasibility of ADOT by examples in which both known and unknown Ewing sarcoma translocations are identified from cell lines, tumor xenografts, and FFPE primary tumors. These results demonstrate that ADOT may be an effective approach for translocation analysis in clinical specimens with significant RNA degradation and may offer a novel diagnostic tool for translocation-based cancers.
2012-01-31 | GSE35450 | GEO
Project description:To evaluate the effectiveness and accuracy of the ctDNA dual-target test kit in a large case-control cohort for the detection of colorectal cancer and advanced adenomas.
| 2745777 | ecrin-mdr-crc
Project description: Not available
| S-EPMC7305837 | biostudies-literature