RT Journal Article
SR Electronic
T1 SFyNCS detects oncogenic fusions involving non-coding sequences in cancer
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2023.04.03.535462
DO 10.1101/2023.04.03.535462
A1 Xiaoming Zhong
A1 Jingyun Luan
A1 Anqi Yu
A1 Anna Lee-Hassett
A1 Yuxuan Miao
A1 Lixing Yang
YR 2023
UL http://biorxiv.org/content/early/2023/04/06/2023.04.03.535462.abstract
AB Fusion genes are well-known cancer drivers. However, very few known oncogenic fusions involve non-coding sequences. We develop SFyNCS with superior performance to detect fusions of both protein-coding genes and non-coding sequences from transcriptomic sequencing data. We validate fusions using somatic structural variations detected from the genomes. This allows us to comprehensively evaluate various fusion detection and filtering strategies and parameters. We detect 165,139 fusions in 9,565 tumor samples across 33 tumor types in the Cancer Genome Atlas cohort. Among them, 72% of the fusions involve non-coding sequences and many are recurrent. We discover two long non-coding RNAs recurrently fused with various partner genes in 32% of dedifferentiated liposarcomas and experimentally validated the oncogenic functions in mouse model.Competing Interest StatementThe authors have declared no competing interest.