Integration of physiological tissue models and machine learning to understand genomic instability from oncogene activation to cancer initiation

导致细胞异常生长和癌症发展的基因被称为癌基因。虽然癌基因通常来自细胞基因的突变，但几种可能致癌的病毒，如人乳头瘤病毒(HPV)，会将病毒癌基因带入它们感染的细胞。癌基因可诱导‘复制应激’(称为癌基因诱导的复制应激，简称OI-RS)，其特征是当染色体复制时，DNA复制频繁停滞或减慢。这会导致更多的染色体突变，这被称为基因组不稳定。虽然复制应激在已确定的癌症中很常见，但已发现它也可能发生在癌前和早期癌症组织中，这导致了OI-RS是癌症的初始驱动因素的假说，但目前没有从现有的癌症发展实验模型中直接证明这一点。此外，尚不清楚早期复制压力是如何导致健康细胞癌变的。导致基因组不稳定和癌症的启动机制的发现将在理解细胞癌变原因方面向前迈出重要的一步，并将有助于改进癌症的早期发现和治疗。我们建议使用致癌性HPV感染人皮肤细胞(HPV的天然靶细胞)作为人类组织模型系统来分析从OI-RS和基因组不稳定性到癌症启动的精确步骤。HPV每年导致全球60万癌症，其特点是基因组高度不稳定。感染高危型HPV是早期癌症发展过程中OI-RS和基因组不稳定的一个非常有用的模型，因为病毒癌基因迅速导致复制压力和基因组不稳定。然而，到目前为止，还没有一个团队结合专业知识来建立从HPV感染、复制压力和基因组不稳定到相关人类皮肤模型中癌症形成的准确途径。我们的团队包括一名肿瘤病毒学家、两名细胞生物学家和一名计算科学家。我们共同跨越了从分子到人体组织模型的多个生物学学科，并将带来不同的方法和技术来研究HPV感染模型中的OI-RS。我们的专业知识范围从分子生物化学和细胞生物学到计算生物学和人工智能的应用。重要的是，每个合作伙伴都对复制压力和基因组不稳定如何促进癌症发展有根本兴趣。该项目将首次将不同的背景和学科聚集在一起，以揭示OI-RS、基因组不稳定和癌症发展之间的分子事件。我们将结合单细胞和单分子测序技术以及基于机器学习的复制压力检测来询问从早期在皮肤细胞中建立HPV到发展侵袭性癌细胞的步骤。

Genes that cause abnormal growth of cells and development of cancer are called oncogenes. While oncogenes often arise from mutation of cellular genes, several types of viruses that can cause cancer, such as human papillomavirus (HPV), bring viral oncogenes into the cells they infect. Oncogenes can induce 'replication stress' (called oncogene-induced replication stress or Oi-RS), which is characterised by the frequent stalling or slowing of DNA replication when chromosomes are copied. This causes more mutations in the chromosomes, which is called genomic instability. While replication stress is common in established cancers, it has been discovered that it might also occur in pre-cancerous and early cancer tissues, leading to the hypothesis that Oi-RS is an initial driver of cancer but there is currently no direct evidence for this from existing experimental models of cancer development. Moreover, it is not known how early replication stress causes a healthy cell to become cancerous. Discovery of the initiating mechanisms leading to genomic instability and cancer would provide a vital step forward in understanding what causes cells to become cancerous and will be instrumental in improving early detection and treatment of cancer. We propose to use oncogenic HPV infection of human skin cells, the natural target cell of HPV, as a human tissue model system to analyse the precise steps from Oi-RS and genomic instability to cancer initiation. HPV causes >600,000 cancers per year worldwide that are characterised by high levels of genomic instability. Infection with high-risk types of HPV is a very useful model for Oi-RS and genomic instability during early cancer development, because viral oncogenes rapidly cause replication stress and genomic instability. To date however, no team has yet combined expertise to establish the precise pathways from HPV infection, replication stress and genomic instability, through to cancer formation in relevant human skin models. Our team comprises a tumour virologist, two cell biologists and a computational scientist. Together, we cross multiple biology disciplines from molecules to human tissue models and will bring diverse methods and technologies to investigate Oi-RS in a model of HPV infection. Our expertise ranges from molecular biochemistry and cell biology to computational biology and the application of artificial intelligence. Importantly, the individual partners all have a fundamental interest in how replication stress and genome instability contribute to cancer development. This project will for the first time bring together distinct backgrounds and disciplines to unravel the molecular events between Oi-RS, genomic instability, and cancer development. We will integrate single cell- and single molecule sequencing technology and machine learning-based detection of replication stress to interrogate the steps from early establishment of HPV in skin cells to the development of invasive cancer cells.