High-grade serous ovarian cancer: exploiting a living biobank to delineate mechanisms underlying disease-specific chromosome instability

25年前，当发现由于潜在的染色体不稳定(CIN)，即染色体的持续获得和丢失和/或结构重排的获得时，我们对癌症基因组学的理解发生了范式转变。事实上，现在人们普遍认为CIN是肿瘤异质性、表型适应性和耐药性的主要驱动因素。在过去的20年里，我们了解了大量关于染色体复制和分离的分子机制，以及相关的细胞周期检查点控制。然而，直接参与这些过程的基因的致癌突变极其罕见，这意味着我们对CIN获取的基本原理，即它如何在面临选择压力的情况下驱动肿瘤发生和改变轨迹的理解仍然更加有限。因此，我们的目标是了解这些原理，以便将CIN作为治疗的靶点。尽管付出了巨大的努力，但多种因素阻碍了进展。由于实验上的可控性，机械论研究通常集中在有限数量的已建立的癌细胞系上，但它们往往具有有限的临床注释，不能反映疾病的异质性，并且缺乏治疗前/后的对应物。此外，最适合长期细胞培养的更合适的亚克隆产生相对稳定的核型。其他混杂因素是由于广泛的体外繁殖而引起的遗传漂移，以及忽视疾病特异性CIN途径的可能性的肿瘤部位不可知论哲学。另一个限制是缺乏非转化的、核型稳定的模型系统来代表起源细胞来概括CIN途径。虽然癌症测序项目可以分析大量临床注释的样本，但依赖档案活检会导致间质污染，单细胞方法在技术上具有挑战性，并且不可能用功能实验来检验新的假设。虽然对空间分辨的活检组织进行测序可以重建进化轨迹，但匹配的化疗初治、正在治疗和复发样本的纵向队列不太常见。此外，分离耐药克隆的祖细胞是不可能的。因此，为了定义CIN如何驱动肿瘤发生和耐药性的基本原理，我们现在提出一种具有几个关键好处的全新方法，以解决迄今阻碍进展的限制。重要的是，我们将采取疾病特异性的方法，专注于高级别浆液性卵巢癌(HGSOC)，其中CIN是关键驱动因素，获得性耐药是关键的临床挑战。首先，我们将利用患者来源的卵巢癌模型(OCM)的活生物库，这可能是原代HGSOC细胞培养的最大和最多样化的集合。OCM是早期传代的、纯化的肿瘤部分，具有HGSOC的特征和异质性。与能够实现广泛增殖潜力的细胞培养系统相结合，OCMS可以进行多种组学，包括单细胞组学、高分辨率细胞生物学研究和药物敏感性分析。随着生物库的成熟，我们正在组装纵向队列，即来自化疗前、化疗中和化疗后活检的OCM。第二，由于HGSOC起源于输卵管上皮细胞，我们建立了这些细胞的FNE1模型系统。FNE1细胞是非转化的，在核型上是稳定的，但我们已经证明，引入HGSOC特定的遗传损伤足以诱导CIN，产生类似于我们患者衍生模型的核型。第三，为了分离耐药后代的祖细胞，我们将结合最先进的基于条形码的谱系追踪技术和我们的纵向OCM来研究对化疗的克隆动力学。

25 years ago, our understanding of cancer genomics underwent a paradigm shift when it was discovered that cancer cell karyotypes are in a state of constant flux due to underlying chromosome instability (CIN), ie continuous gain and loss of chromosomes and/or acquisition of structural rearrangements. And indeed, it is now widely accepted that CIN is a major driver of tumour heterogeneity, phenotypic adaptation and drug resistance.In the last two decades, we have learnt a great deal about the molecular mechanisms responsible for chromosome replication and segregation, as well as the associated cell cycle checkpoint controls. However, oncogenic mutations in genes directly involved in these processes are extremely rare, meaning our understanding of the basic principles governing the acquisition of CIN, how it drives tumorigenesis and alters trajectories in the face of selective pressures remains more limited. Thus we aim to understand these principles in order to exploit CIN as a therapeutic target.Despite intense efforts, multiple factors have hindered progress. Mechanistic studies typically focus on a limited number of established cancer cell lines, due to experimental tractability, yet they tend to have limited clinical annotation, do not reflect disease heterogeneity, and lack pre-/post- treatment counterparts. Moreover, outgrowth of fitter subclones best suited for long-term cell culture yields relatively stable karyotypes. Additional confounding factors are genetic drift due to extensive in vitro propagation, and a tumour-site agnostic philosophy that ignores the possibility of disease-specific CIN pathways. Another limitation is the lack of non-transformed, karyotypically-stable model systems that represent the cell-of-origin to recapitulate CIN pathways.While cancer sequencing projects can analyse large cohorts of clinically annotated samples, reliance on archival biopsies results in stromal contamination, single-cell approaches are technically challenging, and testing emerging hypotheses with functional experiments is impossible. While sequencing spatially resolved biopsies allows reconstruction of evolutionary trajectories, longitudinal cohorts of matched chemo-naïve, on-treatment and relapse samples are less common. Moreover, isolating progenitors of drug-resistant clones is impossible.Therefore, to define the basic principles governing how CIN drives tumorigenesis and drug resistance, we now propose a fundamentally fresh approach with several key benefits to address the limitations that have hindered progress to date. Importantly, we will take a disease-specific approach, focusing on high-grade serous ovarian cancer (HGSOC), where CIN is the key driver and acquired drug resistance the key clinical challenge.Firstly, we will exploit our living biobank of patient-derived ovarian cancer models (OCMs), possibly the largest and most diverse collection of primary HGSOC cell cultures. OCMs are early passage, purified tumour fractions that possess the hallmarks and heterogeneity of HGSOC. Coupled with a cell culture system that enables extensive proliferative potential, OCMs are amenable to multi-omics, including single-cell omics, high-resolution cell biology studies and drug-sensitivity profiling. As the biobank matures, we are assembling longitudinal cohorts, ie OCMs derived from biopsies taken before, during and after chemotherapy.Secondly, as HGSOC originates from fallopian tube epithelial cells, we have established the FNE1 model system of these cells. FNE1 cells are non-transformed and karyotypically stable, but we have shown that introducing HGSOC-specific genetic lesions is sufficient to induce CIN, yielding karyotypes similar to those of our patient-derived models.And thirdly, to isolate the progenitors of drug-resistant descendants, we will combine a state-of-the-art barcode-based lineage tracing technology with our longitudinal OCMs to study clonal dynamics in response to chemotherapy.