Long-read sequencing identifies novel structural variations in colorectal cancer.
Luming XuXingyue WangXiaohuan LuFan YangZhibo LiuHongyan ZhangXiaoqiong LiShaoBo TianLin WangZheng WangPublished in: PLoS genetics (2023)
Structural variations (SVs) are a key type of cancer genomic alterations, contributing to oncogenesis and progression of many cancers, including colorectal cancer (CRC). However, SVs in CRC remain difficult to be reliably detected due to limited SV-detection capacity of the commonly used short-read sequencing. This study investigated the somatic SVs in 21 pairs of CRC samples by Nanopore whole-genome long-read sequencing. 5200 novel somatic SVs from 21 CRC patients (494 SVs / patient) were identified. A 4.9-Mbp long inversion that silences APC expression (confirmed by RNA-seq) and an 11.2-kbp inversion that structurally alters CFTR were identified. Two novel gene fusions that might functionally impact the oncogene RNF38 and the tumor-suppressor SMAD3 were detected. RNF38 fusion possesses metastasis-promoting ability confirmed by in vitro migration and invasion assay, and in vivo metastasis experiments. This work highlighted the various applications of long-read sequencing in cancer genome analysis, and shed new light on how somatic SVs structurally alter critical genes in CRC. The investigation on somatic SVs via nanopore sequencing revealed the potential of this genomic approach in facilitating precise diagnosis and personalized treatment of CRC.
Keyphrases
- single cell
- rna seq
- copy number
- single molecule
- genome wide
- high throughput
- papillary thyroid
- end stage renal disease
- poor prognosis
- squamous cell
- dna methylation
- chronic kidney disease
- ejection fraction
- epithelial mesenchymal transition
- atomic force microscopy
- cystic fibrosis
- squamous cell carcinoma
- computed tomography
- young adults
- childhood cancer
- oxidative stress
- transforming growth factor
- binding protein
- dna damage response
- prognostic factors
- mass spectrometry
- case report
- solid state
- dna damage
- risk assessment
- transcription factor
- combination therapy
- data analysis
- long non coding rna
- dna repair
- genome wide analysis
- quantum dots