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• W2989623551 abstract "Abstract Many biology-based precision drugs are available that neutralize aberrant molecular pathways in cancer. Molecular heterogeneity and the lack of reliable companion diagnostic biomarkers for many drugs makes targeted treatment of cancer inaccurate for many individuals. Identifying actionable hyperactive biological pathways in individual cancers may improve this situation. To achieve this we applied a novel targeted RNA next generation sequencing (t/RNA-NGS) technique to surgically obtained glioma tissues. The test combines mutation detection with analysis of biological pathway activities that are involved in tumour behavior in many cancer types (e.g. tyrosine kinase signaling, angiogenesis signaling, immune response, metabolism), via quantitative measurement of transcript levels and splice variants of hundreds of genes. We here present proof of concept that the technique, which uses molecular inversion probes, generates a histology-independent molecular diagnosis and identifies classifiers that are strongly associated with conventional histopathology diagnoses and even with patient prognosis. The test not only confirmed known glioma-associated molecular aberrations but also identified aberrant expression levels of actionable genes and mutations that have so far been considered not to be associated with glioma, opening up the possibility of drug repurposing for individual patients. Its cost-effectiveness makes t/RNA-NGS to an attractive instrument to aid oncologists in therapy decision making." @default.
• W2989623551 created "2019-12-05" @default.
• W2989623551 creator A5008991077 @default.
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• W2989623551 date "2019-11-20" @default.
• W2989623551 modified "2023-10-06" @default.
• W2989623551 title "Mapping actionable pathways and mutations in brain tumours using targeted RNA next generation sequencing" @default.
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• W2989623551 doi "https://doi.org/10.1186/s40478-019-0826-z" @default.
• W2989623551 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6865071" @default.
• W2989623551 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31747973" @default.
• W2989623551 hasPublicationYear "2019" @default.
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