PO.BCS01.14 · 生物信息与计算

用于分析癌症测序数据的快速且经济高效的云端流程

Fast and cost-effective cloud-based pipelines to analyze cancer sequencing data

编号 6881 展板 25 时间 4/22 09:00–12:00 区域 Section 3 主讲 Samuel Wiseman, BA

分会场 Network Biology and Precision Medicine

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作者与单位 Authors & Affiliations

Sam Wiseman¹, Samantha Van Seters¹, Saveliy Belkin¹, David I. Heiman¹, Vasuki Narasimha Swamy¹, Antonia Kowalewski¹, Scott Ritterbush¹, Zachary Everton¹, Ron Solan¹, Chip Stewart¹, David Lehotzky¹, Luis Antonio Corchete Sanchez¹, Xavi Loinaz¹, Haruna Tomono¹, Andrew D. Cherniack¹, Gengchao Wang¹, Brian P. Danysh¹, Young Seok Ju², Esther Rheinbay¹, Gad Getz¹

¹Broad Institute, Cambridge, MA,²Inocras Inc., San Diego, CA

摘要 Abstract

中文摘要

随着TCGA队列高质量重测序数据的发布，科学界获得了深化对癌症潜在成因理解并开辟其治疗途径的机会。凭借在这些队列上的丰富经验，我们开发了（i）能够准确表征已测序癌症数据中变异的先进计算流程，以及（ii）能够在云端快速且经济高效地运行这些流程的基础设施。通过结合成熟的工具和可降低假阳性判定可能性的专用过滤器，我们的流程经过多年使用不断打磨，并在众多癌症研究中广泛运行。TCGA队列带来了独特的挑战，其包含超过8,000对深度覆盖、无PCR的全基因组测序（WGS）肿瘤-正常配对样本，需要对我们的流程基础设施进行大规模扩展。自2025年初以来，对各个工具的增强以及对我们云端工作流引擎的改进，使流程执行的时间和成本降低了50%以上，使我们能够在不到1个月的时间内表征超过8,000对样本。此项工作检测出超过2.62亿个突变和117万个结构变异，我们相信这些数据将为癌症生物学和潜在治疗靶点提供深刻见解。

查看英文原文 English abstract

With the release of high-quality resequencing of the TCGA cohorts, the scientific community has gained an opportunity to deepen its understanding of cancer's underlying causes and create paths forward for its treatment. Well-experienced with these cohorts, we have developed (i) state-of-the-art computational pipelines that accurately characterize variants in sequenced cancer data, as well as (ii) the infrastructure to run these pipelines quickly and cost-effectively in the cloud. Using a combination of established tools and specialized filters that reduce the likelihood of false calls, our pipelines have been honed over years of use and run extensively in numerous cancer studies. The TCGA cohort presented a unique challenge of >8,000 deep coverage, PCR-free whole-genome-sequenced (WGS) tumor-normal pairs, requiring a massive upscaling of our pipeline infrastructure. Enhancements to individual tools and refinements of our cloud-based workflow engine have reduced the time and cost of our pipeline execution by more than 50% since the start of 2025, allowing us to characterize more than 8,000 of the pairs in less than 1 month. This undertaking detected more than 262 million mutations and 1.17 million structural variants that we believe will provide deep insight into cancer biology and potential therapeutic targets.

利益披露 Disclosure

S. Wiseman, None.. S. Van Seters, None.. S. Belkin, None.. D. I. Heiman, None.. V. Narasimha Swamy, None.. A. Kowalewski, None.. S. Ritterbush, None.. Z. Everton, None.. R. Solan, None.. C. Stewart, None.. D. Lehotzky, None.. L. Corchete Sanchez, None.. X. Loinaz, None.. H. Tomono, None. A. D. Cherniack, Bayer ). G. Wang, None.. B. P. Danysh, None.. Y. Ju, None. E. Rheinbay, Inocras, Inc. ). G. Getz, IBM ). Pharmacyclics/Abbvie ). Bayer ). Genentech ). Calico ). Ultima Genomics ). Inocras Inc. ). Google ). Kite ). Novartis ). Broad Institute Patent. Scorpion Therapeutics Employment, g., Board of Directors, non-salaried role), Stock. Predicta Biosciences Employment, g., Board of Directors, non-salaried role), Stock. Antares Therapeutics Stock.

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