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癌症中与早期和晚期基因组不稳定性相关的不同分子谱

英文原题:Distinct molecular profiles associated with early vs late genome instability in cancer.

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Distinct molecular profiles associated with early vs late genome instability in cancer.

PubMed 2026/04/06(内容时间) Sci Rep Q1 · IF 4.9(JCR 2025)

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中文摘要

癌症标志性表型出现的时间顺序可能影响肿瘤行为和预后。在先前的工作中,我们使用变异等位基因频率(VAF)分析推断了超过30,000个肿瘤中标志性特征的获得顺序,识别出两种主要的进化轨迹:一种以早期基因组不稳定性(EGI)为特征,另一种以晚期基因组不稳定性(LGI)为特征。这些轨迹与不同的生存结局相关。

在此,我们利用癌症基因组图谱(TCGA)的数据,研究区分这两组的分子和微环境特征。我们发现,EGI肿瘤表现出更高的非整倍性,并富集与同源重组缺陷相关的突变特征,特别是SBS3,而LGI肿瘤则显示出更多与环境相关的特征,包括与紫外线暴露和卤代烷烃相关的特征。免疫分析显示,活化的肥大细胞、树突状细胞和NK细胞在EGI肿瘤中富集,而静息肥大细胞与LGI肿瘤强烈相关。EGI肿瘤的干性评分也显著更高,而上皮-间质转化(EMT)指标在两组之间没有差异。这些发现表明,基因组不稳定的时间与不同的突变过程、免疫状态和可塑性特征相关。理解这些差异可能为肿瘤进化提供见解,并为基于标志性特征排序的分层治疗干预提供机会。

展开英文摘要原文

The temporal order in which cancer hallmark phenotypes emerge can influence tumor behavior and prognosis. In prior work, we used variant allele frequency (VAF) analysis to infer hallmark acquisition order in over 30,000 tumors, identifying two dominant evolutionary trajectories: one characterized by early genome instability (EGI) and the other by late genome instability (LGI). These trajectories were associated with distinct survival outcomes.

Here, we investigate the molecular and microenvironmental features that differentiate these two groups, using data from The Cancer Genome Atlas (TCGA).

We show that EGI tumors exhibit higher aneuploidy and are enriched for mutational signatures linked to homologous recombination deficiency, particularly SBS3, while LGI tumors show greater prevalence of environmentally associated signatures, including those linked to UV exposure and haloalkanes.

Immune profiling revealed that activated mast cells, dendritic cells, and NK cells are enriched in EGI tumors, whereas resting mast cells are strongly associated with LGI tumors. Stemness scores were also significantly higher in EGI tumors, while epithelial-mesenchymal transition (EMT) metrics did not differ between groups.

These findings suggest that the timing of genome instability is associated with distinct mutational processes, immune states, and plasticity features. Understanding these differences may provide insight into tumor evolution and offer opportunities for stratified therapeutic intervention based on hallmark ordering.

论文信息

作者
Gourmet L、Lam J、Pennycuick A、Zapata L、Mallick P、Walker-Samuel S
第一作者单位
Centre for Computational Medicine, University College London, London, UK.United Kingdom
通讯作者单位
Centre for Computational Medicine, University College London, London, UK. simon.walkersamuel@ucl.ac.uk.United Kingdom
期刊
Scientific reports2026 Apr 6
原文标识
PubMed 41942602 · DOI 10.1038/s41598-026-44528-y