Rare subclonal sequencing of breast cancers indicates putative metastatic driver mutations are predominately acquired after dissemination.

IF 10.4 1区 生物学 Q1 GENETICS & HEREDITY
Matthew R Lawrence-Paul, Tien-Chi Pan, Dhruv K Pant, Natalie N C Shih, Yan Chen, George K Belka, Michael Feldman, Angela DeMichele, Lewis A Chodosh
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引用次数: 0

Abstract

Background: Evolutionary models of breast cancer progression differ on the extent to which metastatic potential is pre-encoded within primary tumors. Although metastatic recurrences often harbor putative driver mutations that are not detected in their antecedent primary tumor using standard sequencing technologies, whether these mutations were acquired before or after dissemination remains unclear.

Methods: To ascertain whether putative metastatic driver mutations initially deemed specific to the metastasis by whole exome sequencing were, in actuality, present within rare ancestral subclones of the primary tumors from which they arose, we employed error-controlled ultra-deep sequencing (UDS-UMI) coupled with FFPE artifact mitigation by uracil-DNA glycosylase (UDG) to assess the presence of 132 "metastasis-specific" mutations within antecedent primary tumors from 21 patients. Maximum mutation detection sensitivity was ~1% of primary tumor cells. A conceptual framework was developed to estimate relative likelihoods of alternative models of mutation acquisition.

Results: The ancestral primary tumor subclone responsible for seeding the metastasis was identified in 29% of patients, implicating several putative drivers in metastatic seeding including LRP5 A65V and PEAK1 K140Q. Despite this, 93% of metastasis-specific mutations in putative metastatic driver genes remained undetected within primary tumors, as did 96% of metastasis-specific mutations in known breast cancer drivers, including ERRB2 V777L, ESR1 D538G, and AKT1 D323H. Strikingly, even in those cases in which the rare ancestral subclone was identified, 87% of metastasis-specific putative driver mutations remained undetected. Modeling indicated that the sequential acquisition of multiple metastasis-specific driver or passenger mutations within the same rare subclonal lineage of the primary tumor was highly improbable.

Conclusions: Our results strongly suggest that metastatic driver mutations are sequentially acquired and selected within the same clonal lineage both before, but more commonly after, dissemination from the primary tumor, and that these mutations are biologically consequential. Despite inherent limitations in sampling archival primary tumors, our findings indicate that tumor cells in most patients continue to undergo clinically relevant genomic evolution after their dissemination from the primary tumor. This provides further evidence that metastatic recurrence is a multi-step, mutation-driven process that extends beyond primary tumor dissemination and underscores the importance of longitudinal tumor assessment to help guide clinical decisions.

乳腺癌的罕见亚克隆测序表明,假定的转移性驱动突变主要是在扩散后获得的。
背景:乳腺癌进展的进化模型在原发肿瘤内预先编码转移潜能的程度上存在差异。虽然转移性复发往往蕴藏着假定的驱动突变,但使用标准测序技术却无法在其先前的原发肿瘤中检测到这些突变,这些突变是在扩散之前还是之后获得的仍不清楚:为了确定最初通过全外显子组测序被认为是转移灶特异性的推定转移驱动突变实际上是否存在于产生这些突变的原发肿瘤的罕见祖先亚克隆中,我们采用了误差控制超深度测序(UDS-UMI)以及通过尿嘧啶-DNA糖基化酶(UDG)减轻FFPE伪影的方法来评估21名患者的前原发肿瘤中是否存在132个 "转移灶特异性 "突变。最大突变检测灵敏度约为原发肿瘤细胞的1%。研究人员建立了一个概念框架,以估算突变获得的替代模型的相对可能性:结果:29%的患者确定了负责播种转移的原发肿瘤亚克隆,这与包括 LRP5 A65V 和 PEAK1 K140Q 在内的几种可能的播种转移驱动因素有关。尽管如此,93% 的假定转移驱动基因的转移特异性突变仍未在原发肿瘤中检测到,96% 的已知乳腺癌驱动基因的转移特异性突变也未在原发肿瘤中检测到,包括 ERRB2 V777L、ESR1 D538G 和 AKT1 D323H。令人震惊的是,即使在那些发现了罕见祖先亚克隆的病例中,87%的转移特异性假定驱动基因突变仍未被检测到。建模结果表明,在原发肿瘤的同一罕见亚克隆系中连续获得多个转移特异性驱动突变或乘客突变的可能性很小:我们的研究结果有力地表明,转移驱动基因突变是在原发肿瘤扩散之前,但更常见的是在扩散之后,在同一克隆系中连续获得和选择的,而且这些突变具有生物学意义。尽管档案原发肿瘤取样存在固有的局限性,但我们的研究结果表明,大多数患者的肿瘤细胞在从原发肿瘤扩散后会继续经历与临床相关的基因组进化。这进一步证明了转移性复发是一个多步骤的、突变驱动的过程,它超越了原发肿瘤的扩散,并强调了纵向肿瘤评估的重要性,有助于指导临床决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Genome Medicine
Genome Medicine GENETICS & HEREDITY-
CiteScore
20.80
自引率
0.80%
发文量
128
审稿时长
6-12 weeks
期刊介绍: Genome Medicine is an open access journal that publishes outstanding research applying genetics, genomics, and multi-omics to understand, diagnose, and treat disease. Bridging basic science and clinical research, it covers areas such as cancer genomics, immuno-oncology, immunogenomics, infectious disease, microbiome, neurogenomics, systems medicine, clinical genomics, gene therapies, precision medicine, and clinical trials. The journal publishes original research, methods, software, and reviews to serve authors and promote broad interest and importance in the field.
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