cliniCIN: Targeting the roots of chromosomal instability in cancer

目标：通过使用正在进行的突变过程的特征作为药物反应的生物标记物来克服染色体高度不稳定的癌症的基因组复杂性。背景：染色体不稳定是大多数致命性癌症的特征。高度不稳定的肿瘤几乎没有生物标志物来指导治疗决定，患者的存活率几十年来没有改善。我的团队开创了使用全基因组DNA拷贝数模式剖析染色体不稳定性的方法，即所谓的CIN签名，这是不同类型不稳定性和潜在突变过程的特征。在试点研究中，我们发现CIN签名可以预测药物反应。签名分析关注的是原因，而不是染色体不稳定的后果，因此代表着与以前的个性化医学方法的根本背离。方法：在这里，我正在建立在我开发的基因组和计算技术的基础上，为治疗染色体高度不稳定的癌症设计生物标记物。我提出了一种新的单细胞DNA测序方法来从单个细胞中的独特事件中识别正在进行的突变过程。这种药物基因组测试是一项重大进步，因为它允许将正在进行的突变过程与已灭绝的突变过程分开，这些突变过程正在积极地促进癌症的发展，这些突变过程在基因组中留下了标记，但不再活跃。我将在一项全面的实验计划中，在五种高度不稳定的癌症(食道癌、肺癌、胰腺癌、卵巢癌和三阴性乳腺癌)中系统地识别药物反应的强大和预测生物标记物，并在接受新辅助治疗的患者中测量肿瘤微环境中CIN的异质性。影响：这个开创性的项目将导致对具有不同类型染色体不稳定的癌症如何对药物做出反应以及如何利用基因组复杂性为未满足临床需求的癌症患者造福的基本见解。

GOAL: Overcoming the genomic complexity of cancers with high chromosomal instability by using signatures of ongoing mutational processes as biomarkers for drug response.BACKGROUND: Chromosomal instability is a hallmark of most lethal cancers. Highly unstable tumours have few biomarkers to guide treatment decisions and patient survival has not improved for decades. My team pioneered approaches to dissect chromosomal instability using genome-wide DNA copy number patterns, so called CIN signatures, which are characteristic for different types of instability and underlying mutational processes. In pilot studies we found that CIN signatures predict drug response. Signature analysis focuses on the cause, rather than the consequence of chromosomal instability, and thus represents a radical departure from previous personalised medicine approaches. APPROACH: Here, I am building on genomic and computational technologies I have developed to design biomarkers for treating cancers with high chromosomal instability. I propose a novel single cell DNA sequencing approach to identify ongoing mutational processes from unique events in individual cells. This pharmacogenomic test is a major advance, because it allows to separate ongoing mutational processes, which are actively contributing to cancer development, from extinct mutational processes, which left marks in the genome but are no longer active. I will systematically identify robust and predictive biomarkers of drug response in a comprehensive experimental plan across five highly unstable cancers (esophageal, lung, pancreatic, ovarian and triple negative breast cancer) and measure the heterogeneity of CIN across tumour microenvironments in patients undergoing neo-adjuvant treatment. IMPACT: This pioneering project will result in fundamental insights into how cancers with different types of chromosomal instability react to drugs and how to exploit genomic complexity for patient benefit in cancers of unmet clinical need.