PO.BCS01.03 · 生物信息与计算
利用连接读长预测晚期前列腺癌中的染色体外DNA
Leveraging linked-reads to predict extrachromosomal DNA in advanced prostate cancer
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
前列腺癌是一种每年影响数百万男性的复杂疾病。近期研究揭示,前列腺癌的激素依赖性源于雄激素受体(AR)的高表达和基因扩增,并可能由染色体外DNA(ecDNA)驱动。由于癌症中拷贝数和结构变异的复杂性,利用全基因组测序(WGS)数据将ecDNA与其他扩增模式(例如通过断裂-融合-桥循环产生的HSR)区分开来仍具挑战性。这在FFPE中更为复杂,因为这种样本类型往往面临核酸片段化、DNA交联和脱氨基的风险,进一步使变异发现复杂化。
在本研究中,我们探究了来自两种Dovetail连接读长化学方法——LinkPrep™(一种基于Tn5、兼容细胞和新鲜冷冻组织的方法)和Dovetail®-FFPE(一种基于MNase-HiC、兼容FFPE的方法)——的结构变异和连接模式能否预测ecDNA的存在。我们使用四个已知具有ecDNA或HSR的癌症细胞系对我们的方法进行了基准测试,然后将该技术应用于保存在FFPE中的临床转移性去势抵抗性前列腺癌(mCRPC)病例。我们生成了约30x覆盖度的文库,并使用BWA进行比对、Hi-C breakfinder进行结构变异分析、DeepSomatic进行SNV和InDel检测、Purple进行CNV分析,以及一个内部脚本进行ecDNA检测。AmpliconArchitect用于正交鸟枪法WGS以预测ecDNA。
通过分析从扩增子到基因组其他位置的长程连接,我们的方法正确识别了所有四个细胞系中ecDNA的存在(或不存在),并在临床mCRPC FFPE队列中对具有AR扩增子的样本做出了ecDNA预测。采用了两种分析方法来预测ecDNA的存在:一种新颖的基于Z-score的方法,量化扩增子上观察到的与预期接触分布的差异(ecDNA相比HSR增加5.7倍);以及一种log2比值检验,比较染色体内与染色体间的扩增子连接接触(ecDNA相比HSR增加3倍)。两种方法均被发现在低至5x覆盖度时仍然稳健。最后,对于疑似整合扩增子的样本,通过位点特异性与总扩增子连接的比较来估计每个位点整合的所有扩增子的百分比。
除ecDNA预测外,Dovetail文库还能检测涵盖全范围致癌驱动改变的变异,包括SNVs/InDels、拷贝数和结构变异。与mCRPC队列的新鲜冷冻WGS衍生的真值集相比,Dovetail®-FFPE文库成功召回了纯合PTEN缺失、TMPRSS2::ERG融合以及BRCA2、TP53和KMT2C基因的致癌突变。我们的研究结果表明,Dovetail文库为研究人员在新鲜冷冻和FFPE组织中进行全面的遗传变异发现提供了一个强大的平台。
查看英文原文 English abstract
Prostate cancer is a complex disease that affects millions of men each year. Recent research has revealed that the hormone-dependent nature of prostate cancer stems from the high expression and genetic amplification of the androgen receptor (AR) and may be driven by extrachromosomal DNA (ecDNA). Identifying ecDNA from other modes of amplification (e.g. HSR via breakage-fusion-bridge cycles) using whole-genome sequencing (WGS) data remains challenging due to the complexity of copy number and structural variation in cancer. This is compounded in FFPE where this sample type is often at risk of nucleic acid fragmentation, DNA crosslinks, and deamination further complicating variant discovery.
In this study we investigated if structural variants and linkage patterns derived from two Dovetail linked read chemistries, LinkPrep™ (a Tn5-based method compatible with cells and fresh-frozen tissue) and Dovetail®-FFPE (an MNase-HiC-based method compatible with FFPE), could predict the presence of ecDNA. We benchmarked our approach using four cancer cell lines with known ecDNA or HSR, then applied this technique to clinical metastatic castration-resistant prostate cancer (mCRPC) cases stored in FFPE. We generated libraries at ~30x coverage and utilized BWA for alignment, Hi-C breakfinder for structural variants, DeepSomatic for SNV and InDel detection, Purple for CNVs, and an in-house script for ecDNA detection. AmpliconArchitect was used on orthogonal shotgun WGS to predict ecDNA.
By analyzing the long-range linkage from amplicons to elsewhere in the genome, our method correctly identified the presence (or absence) of ecDNAs in all four cell lines and made ecDNA predictions across the samples with AR amplicons among the clinical mCRPC FFPE cohort. Two analytical methods were employed to predict ecDNA presence: a novel Z-score-based method that quantifies the observed difference from expected contact distribution across the amplicon (ecDNA 5.7-fold increase vs. HSR) and a log2-ratio test comparing intra- vs. inter-chromosomal amplicon-linked contacts (ecDNA 3-fold increase vs. HSR). Both methods were found to be robust down to 5x coverage. Finally, for samples with suspected integrated amplicon(s), the percentage of all amplicons integrated at each site is estimated through site-specific vs. total amplicon linkage.
In addition to ecDNA prediction , Dovetail libraries detect variants across the full range of oncogenic driver alterations, including SNVs/InDels, copy number, and structural variants. Comparing against a fresh frozen, WGS-derived truth set for the mCRPC cohort, and Dovetail®-FFPE libraries successfully recalled homozygous P TEN deletions, TMPRSS2 ::ERG fusions, and oncogenic mutations to BRCA2 , TP53 , and KMT2C genes. Our findings show that Dovetail libraries provide researchers with a powerful platform for comprehensive genetic variation discovery in both fresh-frozen and FFPE tissues.
利益披露 Disclosure
A. Fortuna,
Dovetail Genomics Employment, Stock Option.
N. Fredriksson,
Cantata Bio, LLC Employment.
M. Bhakta,
Cantata Bio, LLC Employment.
R. Mannan, None..
F. Su, None..
R. Wang, None..
Y. Wu, None..
X. Cao, None.
L. Munding,
Cantata Bio, LLC Employment, Stock Option.
J. Z. Sanborn,
Cantata Bio, LLC Employment, Stock Option.