乳腺癌基因结构变异：第三代测序

　　结构变异是人类基因组常见的遗传改变，可能导致不同的表现型和疾病，包括癌症。不过，目前常用的第二代测序读取长度较短，限制了对结构变异的检测效能。

　　2022年4月13日，瑞士《细胞与发育生物学前沿》在线发表北京大学人民医院胡涛波、吴金波、谢菲、赵进、杨后圃、王殊等学者联合复旦大学生命科学学院人类表型组研究院、北京希望组生物科技有限公司、北京大学肿瘤医院、香港中文大学、北京大学公共卫生学院、香港科技大学的研究报告，开发了采用第三代测序技术检测乳腺癌样本基因结构变异和融合基因的方法。该研究获得科技部批准的中国人类遗传资源国际合作科学研究《应用第三代测序技术对家族性乳腺癌基因结构变异的检测及功能研究》项目资助（国科遗办审字〔2022〕GH0041号）。

　　该研究开发了用于长读取测序的28基因组，并将其用于英国牛津大学纳米孔技术和美国太平洋生物科学平台，通过对19例乳腺癌患者的肿瘤、癌旁组织和血液样本进行长读取基因组和转录组测序，分析了28个乳腺癌相关基因存在的结构变异。

　　结果发现，某些不可遗传的基因结构变异反复出现于某些特定基因内含子，这些证据支持基因组存在结构变异热点区域，而既往研究大多只关注单核苷酸变异的热点区域。

　　因此，该研究结果表明，采用长读取基因组和转录组测序，可确定乳腺癌患者的基因结构变异，并证实该方法对临床应用具有巨大的潜力。

Front Cell Dev Biol. 2022 Apr 13;10:854640.

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

Taobo Hu, 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 Ishibashi8, Xiaodan Fan, Weichuan Yu, Depeng Wang, Yang Wang, I-Feng Peng, Shu Wang.

Peking University People's Hospital, Beijing, China; School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, China; GrandOmics Inc., Beijing, China; Peking University Cancer Hospital, Beijing, China; The Chinese University of Hong Kong, Sha Tin, China; School of Public Health, Peking University, Beijing, China; Hong Kong University of Science and Technology, Kowloon, Hong Kong, China.

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.

DOI: 10.3389/fcell.2022.854640