Stroboscopic opto-acoustic scattering (SOAS) flow cytometer for pre-cancerous detection

现在已经很好地描述了大多数恶性肿瘤的发展是一个时间连续体，需要几十年的时间，由于多重突变的积累，恶性表型和克隆优势是逐步获得的。癌症的早期诊断和治疗总是会带来更好的结果。这些癌前阶段的识别可以改善风险分层，更好地部署早期检测技术，甚至可能预防。然而，早期的细胞变化是微妙的，并且只发生在一小部分细胞中，这使得检测这些目标具有挑战性。我们假设，这些癌前细胞的物理特性的改变将允许通过使用先进的传感技术来检测它们，并建议将其用于血癌作为范例。“液体肿瘤”具有简单的样本采集和预定义的癌前状态的好处，即所谓的不确定电位克隆造血（CHIP）。目前，对有症状的患者进行血液中细胞和生化异常的“筛查”。除了大量细胞的蛋白质含量特性外，自动细胞计数器还通过光散射评估物理大小。这样就可以将细胞类型/频率与种群正常范围进行定量比较。然而，他们没有得出定性的措施，因此不太可能找到我们的目标癌前细胞。在诊断标准的另一端，诊断明显的血液系统恶性肿瘤使用复杂的技术组合（组织学，FACS， NGS），这些技术昂贵（在时间和设备上）并且无法进行更广泛的筛查。此外，对于FACS分析，需要事先了解正常细胞和癌前细胞之间的差异蛋白表达，这是目前缺乏的。由于预测癌前细胞的罕见性，使用这些技术分析足够大小的细胞群将遇到吞吐量问题，我们提出的技术将克服这些问题。我们提出了一种创新的方法，使用快速有效的定量鉴定和实时多参数表征悬浮细胞成分的生物物理特性：形状、密度、弹性和可压缩性。这种方法的可伸缩性使得现有的吞吐量限制首次被经济有效地克服。我们提出结合声站立梯度力与新型频闪光声散射层析成像集成到芯片上的实验室设备。新的多参数频闪光声传感器将用于比较异质样品中不同细胞群或亚群的生物物理特性。我们有很高的信心，我们可以实现高达60,000个细胞/秒的分析速率。这样的速度可以在2分钟内分析500 ul的样品（225 - 550万个细胞）。我们提出的声场光学技术提供了在多个长度尺度上并行测量多个细胞的独特能力，这是实现超快速吞吐量的途径。在单细胞水平上提供细胞群体力学特性的信息，为新一代光声传感奠定了基础。更重要的是，它立即为降低癌症发病率开辟了新的临床机会，并可能在其他领域产生影响，如空气颗粒分析，水/土壤微生物传感和生产线工业颗粒传感。

ProblemIt is now well described that most malignancies develop along a time-continuum that takes decades, acquiring the malignant phenotype and clonal dominance in a stepwise-manner due to the accumulation of multiple mutations. Early diagnosis and treatment of cancer invariably leads to better outcomes. Identification of these premalignant phases offers improved risk stratification, better deployment of early detection techniques, and possibly even prevention. However, early cellular changes are subtle, and occur in only a small subpopulation of cells, making detection of these targets challenging. We hypothesise that alterations in the physical characteristics of these pre- malignant cells will allow their detection through the use of advanced sensing techniques, and propose to develop this for blood cancers as an exemplar. "Liquid tumours" have the benefits of simple sample acquisition and a predefined premalignant state, so-called clonal haematopoiesis of indeterminate potential (CHIP). Currently, symptomatic patients are "screened" for cellular and biochemical abnormalities in the blood. Automated cell counters assess physical size through light scatter in addition to protein content properties across large numbers of cells. This allows quantitation of cell types/frequencies in comparison to population normal ranges. However, they derive no qualitative measures and are therefore unlikely to find our target premalignant cells. At the other end of the diagnostic scale, overt haematological malignancies are diagnosed using a complicated combination of techniques (Histology, FACS, NGS) that are costly (in time and equipment) and are not feasible for wider screening. Moreover, regarding FACS analysis, prior knowledge of differential protein expression between normal and premalignant cells would be required that is currently lacking. Due to the predicted infrequency of premalignant cells, analysis of sufficient sized cellular populations using these techniques would encounter issues of throughput that our proposed techniques will overcome. SolutionWe propose an innovative approach using fast and efficient quantitative identification and real-time multi-parametric characterisation of biophysical properties of suspended cell components: shape, density, elasticity and compressibility. The scalability of this approach allows the existing throughput limitation to be cost-effectively overcome for the first time. We propose combining acoustic standing gradient forces with novel stroboscopic opto-acoustic scattering tomography integrated onto a Lab-on-chip device. The new multi-parametric stroboscopic opto-acoustic sensors will be used to compare biophysical properties of different cell populations or sub-populations within heterogeneous samples. We have high confidence that we can achieve analysis rates of up to 60,000 cells/second. Such a rate would allow analysis of a 500 ul sample in under 2 minutes (2.25-5.5M cells). The unique ability that our proposed optical technique with acoustic fields offers to measure multiple cells in parallel over several length scales is the route to ultra-fast throughput. Providing information on the mechanical properties of the cellular population at single-cell levels lays the foundation of a new generation of opto-acoustic sensing. More importantly it immediately opens up new clinical opportunities for reducing cancer rates and could have impacts in other areas such as airborne particle analysis, water/soil microbial sensing and production-line industrial particle sensing.