| Literature DB >> 35080790 |
Nicolas Macagno1,2,3,4, Daniel Pissaloux1,5, Arnaud de la Fouchardière1,5, Marie Karanian1,3,5, Sylvie Lantuejoul1,5,6,7, Françoise Galateau Salle1,7, Alexandra Meurgey1,3, Catherine Chassagne-Clement1, Isabelle Treilleux1, Caroline Renard1, Juliette Roussel1, Julie Gervasoni1, Vincent Cockenpot1, Carole Crozes1, Aline Baltres1, Aurélie Houlier1, Sandrine Paindavoine1, Laurent Alberti5, Adeline Duc5, Francois Le Loarer3,8, Armelle Dufresne3,5,9, Mehdi Brahmi3,5,9, Nadège Corradini3,5,10, Jean-Yves Blay3,9,11,12, Franck Tirode1,5,11.
Abstract
Many neoplasms remain unclassified after histopathological examination, which requires further molecular analysis. To this regard, mesenchymal neoplasms are particularly challenging due to the combination of their rarity and the large number of subtypes, and many entities still lack robust diagnostic hallmarks. RNA transcriptomic profiles have proven to be a reliable basis for the classification of previously unclassified tumors and notably for mesenchymal neoplasms. Using exome-based RNA capture sequencing on more than 5000 samples of archival material (formalin-fixed, paraffin-embedded), the combination of expression profiles analyzes (including several clustering methods), fusion genes, and small nucleotide variations has been developed at the Centre Léon Bérard (CLB) in Lyon for the molecular diagnosis of challenging neoplasms and the discovery of new entities. The molecular basis of the technique, the protocol, and the bioinformatics algorithms used are described herein, as well as its advantages and limitations.Entities:
Keywords: FFPE; RNAseq; clustering; fusion transcript; sarcoma; variant analysis
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Year: 2022 PMID: 35080790 DOI: 10.1002/gcc.23026
Source DB: PubMed Journal: Genes Chromosomes Cancer ISSN: 1045-2257 Impact factor: 5.006