PO.BCS01.13 · 生物信息与计算
癌症中情境依赖性的功能性非整倍体
Context dependent functional aneuploidy in cancer
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景:非整倍体表现出强烈的癌症类型特异性,然而其机制基础仍不明确。经典事件如卵巢癌中的8q获得或乳腺癌中的17p缺失突显了反复出现的模式,但标准的98%染色体臂覆盖规则掩盖了有意义的CNV边界。我们假设跨肿瘤反复出现的断点提供了对非整倍体更具功能性的定义。为解决这一问题,我们开发了BAGEL,它通过使用BISCUT断点而非固定的染色体臂阈值来定义CNV片段,从而量化拷贝数改变。
方法:我们使用BISCUT绘制了38种癌症类型中反复出现的CNV断点,并在涵盖多个测序平台和分割算法的九个数据集(APOLLO、CPTAC3、CGCI、TARGET、DepMap、PCAWG、TCGA及两个内部队列)中对其进行了验证。BAGEL衍生的非整倍体评分在TCGA高级别卵巢癌中通过Cox和Kaplan-Meier分析检验其预后价值,并在PCAWG中进行验证。通过整合DepMap CRISPR筛选并使用混合效应模型对必需性差异建模来评估功能效应。使用来自结直肠肿瘤以及乳腺和肺癌细胞系的TAD渗透评分量化染色质约束。
结果:BAGEL通过直接从共享断点定义CNV片段,取代了武断的98%染色体臂规则。断点高度可重复(平均偏差 = 0.089),包括八个HGSOC队列中34个几乎相同的位点。通过多变量Cox进行的预后建模显示,断点定义的非整倍体在HGSOC和乳腺浸润性癌中均能强烈预测生存,基于TCGA数据集构建的模型两者的p<0.0001,并在PCAWG数据集中显示出一致的趋势(HGSOC的5年OS p = 0.085,乳腺浸润性癌p = 0.026)。584个癌症对之间的混合效应建模显示,在123个染色体臂中,癌症类型与断点事件的存在之间存在显著交互作用(FDR < 0.05),表明非整倍体样本与非非整倍体样本之间的CRISPR必需性差异在不同癌症类型间存在显著差异。Hi-C衍生的TAD渗透评分在肿瘤和细胞系数据集中显示出一致的结构约束。断点表现出对TAD边界微弱但可重复的偏好,尤其是对于负选择的事件,表明三维基因组结构塑造了可允许的CNA断点位置。
结论:断点定义的非整倍体捕捉了反复出现的、受生物学约束的CNV片段,揭示了癌症类型特异性的选择压力,识别了与非整倍体相关的基因必需性转变,并暴露了对TAD边界可重复的位置偏好。这些发现表明非整倍体演化是由选择性适应压力和三维染色质结构共同塑造的。
查看英文原文 English abstract
Background: Aneuploidy shows strong cancer-type specificity, yet its mechanistic basis remains unclear. Classic events like 8q gain in ovarian cancer or 17p loss in breast cancer highlight recurrent patterns, but the standard 98% arm-coverage rule obscures meaningful CNV boundaries. We hypothesised that recurrent breakpoints across tumours provide a more functional definition of aneuploidy. To address this, we developed BAGEL, which quantifies copy-number alterations by defining CNV segments using BISCUT breakpoints rather than fixed chromosome-arm thresholds.
Methods: We mapped recurrent CNV breakpoints across 38 cancer types using BISCUT and validated them across nine datasets spanning multiple sequencing platforms and segmentation algorithms (APOLLO, CPTAC3, CGCI, TARGET, DepMap, PCAWG, TCGA and two in-house cohorts). BAGEL-derived aneuploidy scores were tested for prognostic value using Cox and Kaplan-Meier analyses in TCGA high-grade ovarian cancer, with validation in PCAWG. Functional effects were assessed by integrating DepMap CRISPR screens and modelling essentiality differences using mixed-effects models. Chromatin constraints were quantified using TAD penetration scores from colorectal tumours and breast and lung cancer cell lines.
Results: BAGEL replaced the arbitrary 98% arm rule by defining CNV segments directly from shared breakpoints. Breakpoints were highly reproducible (mean deviation = 0.089), including 34 nearly identical sites across eight HGSOC cohorts. Prognostic modelling by multivariate cox showed that Breakpoint-defined aneuploidy strongly predicted survival in both HGSOC and breast invasive carcinoma, with TCGA dataset-built model p<0.0001 for both and showed consistent trend in PCAWG dataset (5 year OS p = 0.085 for HGSOC and p = 0.026 for breast invasive carcinoma). Mixed-effects modelling between 584 cancer-pairs showed significant interaction between cancer type and presence of breakpoint event in 123 arms (FDR < 0.05), indicating that the CRISPR essentiality difference between aneuploid and non-aneuploid samples varies substantially across cancer types. Hi-C-derived TAD penetration scores demonstrated consistent structural constraints across tumour and cell-line datasets. Breakpoints showed a subtle but reproducible bias toward TAD boundaries, particularly for negatively selected events, indicating that 3D genome architecture shapes permissible CNA breakpoint positions.
Conclusions: Breakpoint-defined aneuploidy captures recurrent, biologically constrained CNV segments, reveals cancer-type-specific selective pressures, identifies aneuploidy-linked gene-essentiality shifts, and exposes a reproducible positional bias toward TAD boundaries. These findings demonstrate that aneuploidy evolution is shaped jointly by selective fitness pressures and 3D chromatin architecture.
利益披露 Disclosure
P. L. S. Hung, None..
S. S. Liu, None..
T. N. Wei, None..
L. S. K. Lau, None..
K. Liu, None..
K. K. L. Chan, None..
H. Lu, None.