小柯机器人

复旦大学石乐明等研究人员合作利用全基因组和全外显子组测序实现癌症突变检测的最佳实践。2021年9月9日，《自然—生物技术》杂志发表了该研究成果。

研究人员报告了对匹配的肿瘤-正常细胞系中体细胞突变的系统研究，从而确定了影响六个不同中心的检测重现性和准确性的因素。利用全基因组测序（WGS）和全外显子组测序（WES），研究人员评估了不同输入量的和肿瘤纯度的不同样本类型的可重复性，以及多种文库构建方案，随后用九种生物信息学管线进行处理。

研究人员发现读数覆盖率和鉴别都会影响WGS和WES的可重复性，但WES的性能受到插入片段大小、基因组拷贝含量和全局不平衡得分（GIV；G>T/C>A）的影响。最后，考虑到文库制备方案、肿瘤内容、读数覆盖率和生物信息学过程的共同作用，研究人员推荐了可操作的做法，可用于提高NGS实验在癌症突变检测中的可重复性和准确性。

据介绍，精准肿瘤学的临床应用需要准确的检验，从而区分真正的癌症特异性突变和二代测序（NGS）每一步引入的错误。迄今为止，还没有一项批量测序研究涉及跨位点重现性的影响，也没有涉及影响变异体识别的生物、技术和计算因素。

附：英文原文

Title: Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing

Author: Xiao, Wenming, Ren, Luyao, Chen, Zhong, Fang, Li Tai, Zhao, Yongmei, Lack, Justin, Guan, Meijian, Zhu, Bin, Jaeger, Erich, Kerrigan, Liz, Blomquist, Thomas M., Hung, Tiffany, Sultan, Marc, Idler, Kenneth, Lu, Charles, Scherer, Andreas, Kusko, Rebecca, Moos, Malcolm, Xiao, Chunlin, Sherry, Stephen T., Abaan, Ogan D., Chen, Wanqiu, Chen, Xin, Nordlund, Jessica, Liljedahl, Ulrika, Maestro, Roberta, Polano, Maurizio, Drabek, Jiri, Vojta, Petr, Kks, Sulev, Reimann, Ene, Madala, Bindu Swapna, Mercer, Timothy, Miller, Chris, Jacob, Howard, Truong, Tiffany, Moshrefi, Ali, Natarajan, Aparna, Granat, Ana, Schroth, Gary P., Kalamegham, Rasika, Peters, Eric, Petitjean, Virginie, Walton, Ashley, Shen, Tsai-Wei, Talsania, Keyur, Vera, Cristobal Juan, Langenbach, Kurt, de Mars, Maryellen, Hipp, Jennifer A., Willey, James C., Wang, Jing, Shetty, Jyoti, Kriga, Yuliya, Raziuddin, Arati, Tran, Bao, Zheng, Yuanting, Yu, Ying, Cam, Margaret, Jailwala, Parthav, Nguyen, Cu, Meerzaman, Daoud, Chen, Qingrong, Yan, Chunhua, Ernest, Ben, Mehra, Urvashi, Jensen, Roderick V., Jones, Wendell, Li, Jian-Liang, Papas, Brian N.

Issue&Volume: 2021-09-09

Abstract: Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor–normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G>T/C>A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

DOI: 10.1038/s41587-021-00994-5

Source: https://www.nature.com/articles/s41587-021-00994-5

Nature Biotechnology：《自然—生物技术》，创刊于1996年。隶属于施普林格·自然出版集团，最新IF：68.164
官方网址：https://www.nature.com/nbt/
投稿链接：https://mts-nbt.nature.com/cgi-bin/main.plex