美国加州大学洛杉矶分校Paul C. Boutros等研究人员合作完成单样本肿瘤亚克隆重建的众包基准测试。这一研究成果于2024年6月11日在线发表在国际学术期刊《自然—生物技术》上。
研究人员表示,亚克隆重建算法利用大量DNA测序数据来量化肿瘤演化参数,从而评估癌症是如何开始、发展和应对选择性压力的。
附:英文原文
Title: Crowd-sourced benchmarking of single-sample tumor subclonal reconstruction
Author: Salcedo, Adriana, Tarabichi, Maxime, Buchanan, Alex, Espiritu, Shadrielle M. G., Zhang, Hongjiu, Zhu, Kaiyi, Ou Yang, Tai-Hsien, Leshchiner, Ignaty, Anastassiou, Dimitris, Guan, Yuanfang, Jang, Gun Ho, Mootor, Mohammed F. E., Haase, Kerstin, Deshwar, Amit G., Zou, William, Umar, Imaad, Dentro, Stefan, Wintersinger, Jeff A., Chiotti, Kami, Demeulemeester, Jonas, Jolly, Clemency, Sycza, Lesia, Ko, Minjeong, Wedge, David C., Morris, Quaid D., Ellrott, Kyle, Van Loo, Peter, Boutros, Paul C.
Issue&Volume: 2024-06-11
Abstract: Subclonal reconstruction algorithms use bulk DNA sequencing data to quantify parameters of tumor evolution, allowing an assessment of how cancers initiate, progress and respond to selective pressures. We launched the ICGC–TCGA (International Cancer Genome Consortium–The Cancer Genome Atlas) DREAM Somatic Mutation Calling Tumor Heterogeneity and Evolution Challenge to benchmark existing subclonal reconstruction algorithms. This 7-year community effort used cloud computing to benchmark 31 subclonal reconstruction algorithms on 51 simulated tumors. Algorithms were scored on seven independent tasks, leading to 12,061 total runs. Algorithm choice influenced performance substantially more than tumor features but purity-adjusted read depth, copy-number state and read mappability were associated with the performance of most algorithms on most tasks. No single algorithm was a top performer for all seven tasks and existing ensemble strategies were unable to outperform the best individual methods, highlighting a key research need. All containerized methods, evaluation code and datasets are available to support further assessment of the determinants of subclonal reconstruction accuracy and development of improved methods to understand tumor evolution.
DOI: 10.1038/s41587-024-02250-y
Source: https://www.nature.com/articles/s41587-024-02250-y
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