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Next Generation Sequencing for Gene Fusion Analysis in Lung Cancer: A Literature Review

Gene fusions have a pivotal role in non-small cell lung cancer (NSCLC) precision medicine. Several techniques can be used, from fluorescence in situ hybridization and immunohistochemistry to next generation sequencing (NGS). Although several NGS panels are available, gene fusion testing presents mor...

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Detalles Bibliográficos
Autores principales: Bruno, Rossella, Fontanini, Gabriella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7460167/
https://www.ncbi.nlm.nih.gov/pubmed/32726941
http://dx.doi.org/10.3390/diagnostics10080521
Descripción
Sumario:Gene fusions have a pivotal role in non-small cell lung cancer (NSCLC) precision medicine. Several techniques can be used, from fluorescence in situ hybridization and immunohistochemistry to next generation sequencing (NGS). Although several NGS panels are available, gene fusion testing presents more technical challenges than other variants. This is a PubMed-based narrative review aiming to summarize NGS approaches for gene fusion analysis and their performance on NSCLC clinical samples. The analysis can be performed at DNA or RNA levels, using different target enrichment (hybrid-capture or amplicon-based) and sequencing chemistries, with both custom and commercially available panels. DNA sequencing evaluates different alteration types simultaneously, but large introns and repetitive sequences can impact on the performance and it does not discriminate between expressed and unexpressed gene fusions. RNA-based targeted approach analyses and quantifies directly fusion transcripts and is more accurate than DNA panels on tumor tissue, but it can be limited by RNA quality and quantity. On liquid biopsy, satisfying data have been published on circulating tumor DNA hybrid-capture panels. There is not a perfect method for gene fusion analysis, but NGS approaches, though still needing a complete standardization and optimization, present several advantages for the clinical practice.