Frontiers in Cell and Developmental Biology (Apr 2022)

Detection of Structural Variations and Fusion Genes in Breast Cancer Samples Using Third-Generation Sequencing

  • Taobo Hu,
  • Jingjing Li,
  • Jingjing Li,
  • Mengping Long,
  • Jinbo Wu,
  • Zhen Zhang,
  • Fei Xie,
  • Jin Zhao,
  • Houpu Yang,
  • Qianqian Song,
  • Sheng Lian,
  • Jiandong Shi,
  • Xueyu Guo,
  • Daoli Yuan,
  • Dandan Lang,
  • Guoliang Yu,
  • Baosheng Liang,
  • Xiaohua Zhou,
  • Toyotaka Ishibashi,
  • Xiaodan Fan,
  • Weichuan Yu,
  • Depeng Wang,
  • Yang Wang,
  • I-Feng Peng,
  • Shu Wang

DOI
https://doi.org/10.3389/fcell.2022.854640
Journal volume & issue
Vol. 10

Abstract

Read online

Background: Structural variations (SVs) are common genetic alterations in the human genome that could cause different phenotypes and diseases, including cancer. However, the detection of structural variations using the second-generation sequencing was limited by its short read length, which restrained our understanding of structural variations.Methods: In this study, we developed a 28-gene panel for long-read sequencing and employed it to Oxford Nanopore Technologies and Pacific Biosciences platforms. We analyzed structural variations in the 28 breast cancer-related genes through long-read genomic and transcriptomic sequencing of tumor, para-tumor, and blood samples in 19 breast cancer patients.Results: Our results showed that some somatic SVs were recurring among the selected genes, though the majority of them occurred in the non-exonic region. We found evidence supporting the existence of hotspot regions for SVs, which extended our previous understanding that they exist only for single nucleotide variations.Conclusion: In conclusion, we employed long-read genomic and transcriptomic sequencing to identify SVs from breast cancer patients and proved that this approach holds great potential in clinical application.

Keywords