Novel imaging strategies to investigate 3D tumour invasion at the molecular level

癌症是世界范围内死亡的主要原因之一，尽管我们对癌症的了解和治疗方法的改进有所增加，但许多晚期癌症仍然无法治愈。这些死亡大多是由于转移，通过级联事件，癌细胞逃离原发肿瘤，获得细胞特征，使它们能够在身体的其他部位定居。这一过程的几个潜在机制尚不清楚，需要开发新的生物学模型来模拟这些复杂的肿瘤生态系统中的细胞相互作用。到目前为止，我们对癌症基本分子原理的大部分理解都来自单层二维细胞培养模型的实验。虽然价格低廉且易于成像，但它们并不能代表细胞在体内环境中实际相互作用的方式。近年来，三维细胞培养（即球体）具有重要意义，因为它们可以提供更逼真的环境来模拟生物相互作用。不幸的是，随着这些3D细胞培养物的相对大小、异质性和复杂性的增加，它在使用任何光学技术成像时都施加了严重的限制。折射率的局部变化引起光学像差和散射，再加上吸收，导致光学分辨率的严重下降，以及信号和对比度的损失。该奖学金的主要目标是开发新的光学成像策略，这将首次实现对肿瘤衍生球体模型的完整询问，以了解癌细胞如何与原发肿瘤分离，逃避免疫监视并侵入周围组织。成像平台将基于光片荧光显微镜（LSFM），以实现高速体积成像能力。在伦敦国王学院先前进行的研究的基础上，该系统将结合荧光寿命成像（FLIM）来提取功能信息，这将有助于了解正在发生的分子相互作用。设计的几个方面将考虑包括自适应光学元件（即空间光调制器）的结合，以抵消照明和检测路径中的像差效应。利用这项技术，并与许多生命科学家密切合作，将构建肿瘤球体培养物，以密切模仿肿瘤微环境（TME）。将研究这一TME的几个方面，包括(i)癌细胞的细胞运动和迁移以及（ii）它们对细胞外基质结构建模的影响（iii）免疫细胞在肿瘤进展中的作用。对这些多变量和多维数据的分析是一个巨大的挑战，许多传统的机器学习和深度学习技术将被探索。仪器的发展，以成像，提取和分析大型3D细胞培养模型的功能信息的无创，高速和高分辨率是至关重要的，将进一步提高我们对细胞和细胞外基质（ECM）之间相互作用的细胞复杂性的理解。这将有助于构建更复杂的球体结构来模拟体内条件，并具有巨大的潜力，有助于开发特定的抗癌疗法，彻底改变患者的治疗方法和结果。

Cancer is the one of the major causes of deaths worldwide and despite our increased understanding and the development of more improved treatments, many advanced cancers are still incurable. The majority of these deaths are due to metastasis whereby through cascading events, cancer cells escape the primary tumour, acquiring cellular characteristics which enable them to colonise other parts of the body. Several underlying mechanisms of this process are not understood and require the development of new biological models which can mimic cellular interactions within these complex tumour ecosystems. Until now most of our understanding of the basic molecular principles of cancer have come from experimentation with single layer 2D cell culture models. Whilst inexpensive and easy to image, they are not representative of the way cells actually interact in an in vivo environment. 3D cell cultures (i.e. spheroids), have gained great significance in recent years as they can provide a much more realistic environment to simulate biological interactions. Unfortunately as the relative size, heterogeneity and hence complexity of these 3D cell cultures increases, it imposes severe limitations when imaging with any optically based technique. Local variations in refractive index induce optical aberrations and scattering, and coupled with absorption, lead to severe a degradation in optical resolution, as well as a loss in signal and contrast. The key objective of this fellowship is to develop novel optical imaging strategies which will enable for the first time, the complete interrogation of tumour derived spheroid models, to understand how cancer cells to dissociate from the primary tumour, evade immune surveillance and invade surrounding tissues. The imaging platform will be based on light sheet fluorescence microscopy (LSFM) to enable high-speed volumetric imaging capability. Building on previously conducted research at King's College London, the system will incorporate fluorescence lifetime imaging (FLIM) to allow functional information to be extracted, which will be instrumental in gaining an understanding of the molecular interactions taking place. Several aspects of the design will be considering including the incorporation of adaptive optical elements (i.e. spatial light modulator) to counteract aberrative effects in both the illumination and detection paths. Using this technology and working in close collaboration with a number of life scientists, tumour spheroid cultures will be constructed to closely imitate the tumour microenvironment (TME). Several aspects of this TME will be examined including (i) cell motility and migration of cancer cells and (ii) their effects on the structural modelling of the extra cellular matrix (iii) the role of immune cells in tumour progress.Analysis of this multivariate and multidimensional data represents a huge challenge and a number of conventional machine learning and deep learning techniques will be explored. The development of instrumentation to image, extract, and analyse functional information of large 3D cell culture models non-invasively, at high-speed and at high resolution is vital and will further improve our understanding of cellular complexities of interactions between cells and the Extracellular Matrix (ECM). This will serve to assist in the construction of more complex spheroid structures to mimic in vivo conditions and has enormous potential to aid in the development on specific anti-cancer therapies, revolutionising patient treatments and outcomes.