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

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

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=10

YEAR=2022

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2022.854640

DOI=10.3389/fcell.2022.854640

ISSN=2296-634X

ABSTRACT=<p><bold>Background:</bold> 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.</p><p><bold>Methods:</bold> 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.</p><p><bold>Results:</bold> 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.</p><p><bold>Conclusion:</bold> 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.</p>