학술논문
Systematic discovery of gene fusions in pediatric cancer by integrating RNA-seq and WGS.
Document Type
Article
Author
van Belzen, Ianthe A. E. M.; Cai, Casey; van Tuil, Marc; Badloe, Shashi; Strengman, Eric; Janse, Alex; Verwiel, Eugène T. P.; van der Leest, Douwe F. M.; Kester, Lennart; Molenaar, Jan J.; Meijerink, Jules; Drost, Jarno; Peng, Weng Chuan; Kerstens, Hindrik H. D.; Tops, Bastiaan B. J.; Holstege, Frank C. P.; Kemmeren, Patrick; Hehir-Kwa, Jayne Y.
Source
Subject
*GENE fusion
*CHILDHOOD cancer
*TUMOR suppressor genes
*WHOLE genome sequencing
*RNA sequencing
*ONCOLOGY
*GENETIC code
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Language
ISSN
1471-2407
Abstract
Background: Gene fusions are important cancer drivers in pediatric cancer and their accurate detection is essential for diagnosis and treatment. Clinical decision-making requires high confidence and precision of detection. Recent developments show RNA sequencing (RNA-seq) is promising for genome-wide detection of fusion products but hindered by many false positives that require extensive manual curation and impede discovery of pathogenic fusions. Methods: We developed Fusion-sq to overcome existing disadvantages of detecting gene fusions. Fusion-sq integrates and "fuses" evidence from RNA-seq and whole genome sequencing (WGS) using intron–exon gene structure to identify tumor-specific protein coding gene fusions. Fusion-sq was then applied to the data generated from a pediatric pan-cancer cohort of 128 patients by WGS and RNA sequencing. Results: In a pediatric pan-cancer cohort of 128 patients, we identified 155 high confidence tumor-specific gene fusions and their underlying structural variants (SVs). This includes all clinically relevant fusions known to be present in this cohort (30 patients). Fusion-sq distinguishes healthy-occurring from tumor-specific fusions and resolves fusions in amplified regions and copy number unstable genomes. A high gene fusion burden is associated with copy number instability. We identified 27 potentially pathogenic fusions involving oncogenes or tumor-suppressor genes characterized by underlying SVs, in some cases leading to expression changes indicative of activating or disruptive effects. Conclusions: Our results indicate how clinically relevant and potentially pathogenic gene fusions can be identified and their functional effects investigated by combining WGS and RNA-seq. Integrating RNA fusion predictions with underlying SVs advances fusion detection beyond extensive manual filtering. Taken together, we developed a method for identifying candidate gene fusions that is suitable for precision oncology applications. Our method provides multi-omics evidence for assessing the pathogenicity of tumor-specific gene fusions for future clinical decision making. [ABSTRACT FROM AUTHOR]