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Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies

Despite its wide-ranging benefits, whole-transcriptome or RNA exome profiling is challenging to implement in a clinical diagnostic setting. The Unified Assay is a comprehensive workflow wherein exome-enriched RNA-sequencing (RNA-Seq) assays are performed on clinical samples and analyzed by a series...

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Autores principales: Walsh, P. Sean, Hao, Yangyang, Ding, Jie, Qu, Jianghan, Wilde, Jonathan, Jiang, Ruochen, Kloos, Richard T., Huang, Jing, Kennedy, Giulia C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866839/
https://www.ncbi.nlm.nih.gov/pubmed/36675685
http://dx.doi.org/10.3390/jpm13010024
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author Walsh, P. Sean
Hao, Yangyang
Ding, Jie
Qu, Jianghan
Wilde, Jonathan
Jiang, Ruochen
Kloos, Richard T.
Huang, Jing
Kennedy, Giulia C.
author_facet Walsh, P. Sean
Hao, Yangyang
Ding, Jie
Qu, Jianghan
Wilde, Jonathan
Jiang, Ruochen
Kloos, Richard T.
Huang, Jing
Kennedy, Giulia C.
author_sort Walsh, P. Sean
collection PubMed
description Despite its wide-ranging benefits, whole-transcriptome or RNA exome profiling is challenging to implement in a clinical diagnostic setting. The Unified Assay is a comprehensive workflow wherein exome-enriched RNA-sequencing (RNA-Seq) assays are performed on clinical samples and analyzed by a series of advanced machine learning-based classifiers. Gene expression signatures and rare and/or novel genomic events, including fusions, mitochondrial variants, and loss of heterozygosity were assessed using RNA-Seq data generated from 120,313 clinical samples across three clinical indications (thyroid cancer, lung cancer, and interstitial lung disease). Since its implementation, the data derived from the Unified Assay have allowed significantly more patients to avoid unnecessary diagnostic surgery and have played an important role in guiding follow-up decisions regarding treatment. Collectively, data from the Unified Assay show the utility of RNA-Seq and RNA expression signatures in the clinical laboratory, and their importance to the future of precision medicine.
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spelling pubmed-98668392023-01-22 Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies Walsh, P. Sean Hao, Yangyang Ding, Jie Qu, Jianghan Wilde, Jonathan Jiang, Ruochen Kloos, Richard T. Huang, Jing Kennedy, Giulia C. J Pers Med Article Despite its wide-ranging benefits, whole-transcriptome or RNA exome profiling is challenging to implement in a clinical diagnostic setting. The Unified Assay is a comprehensive workflow wherein exome-enriched RNA-sequencing (RNA-Seq) assays are performed on clinical samples and analyzed by a series of advanced machine learning-based classifiers. Gene expression signatures and rare and/or novel genomic events, including fusions, mitochondrial variants, and loss of heterozygosity were assessed using RNA-Seq data generated from 120,313 clinical samples across three clinical indications (thyroid cancer, lung cancer, and interstitial lung disease). Since its implementation, the data derived from the Unified Assay have allowed significantly more patients to avoid unnecessary diagnostic surgery and have played an important role in guiding follow-up decisions regarding treatment. Collectively, data from the Unified Assay show the utility of RNA-Seq and RNA expression signatures in the clinical laboratory, and their importance to the future of precision medicine. MDPI 2022-12-22 /pmc/articles/PMC9866839/ /pubmed/36675685 http://dx.doi.org/10.3390/jpm13010024 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Walsh, P. Sean
Hao, Yangyang
Ding, Jie
Qu, Jianghan
Wilde, Jonathan
Jiang, Ruochen
Kloos, Richard T.
Huang, Jing
Kennedy, Giulia C.
Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies
title Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies
title_full Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies
title_fullStr Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies
title_full_unstemmed Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies
title_short Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies
title_sort maximizing small biopsy patient samples: unified rna-seq platform assessment of over 120,000 patient biopsies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866839/
https://www.ncbi.nlm.nih.gov/pubmed/36675685
http://dx.doi.org/10.3390/jpm13010024
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