Stroboscopic opto-acoustic scattering (SOAS) flow cytometer for pre-cancerous detection
Lead Research Organisation:
University of Cambridge
Department Name: Haematology
Abstract
Problem
It 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.
Solution
We 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.
It 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.
Solution
We 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.
Technical Summary
Concentrating abnormal cells within a sensing image frame location, as a form of enrichment, is one of the key aspects of novelty in this proposal, and this refinement will allow us to maximize accuracy and increase throughput., allowing the screening of a large number of cells to ensure that we detect premalignant cells at low levels of frequency.
We will use acoustic fields to enable this sub-cellular selective enrichment in three-dimensional matrices within the entire cell population flow path. Such fields will be created using fully transparent piezoelectric thin films and specially designed transparent electrodes integrated into a glass substrate will allow imaging through the device possible.
This design will enable dynamic spatial modulations of node and anti-node through a shift in frequency along the x-y-z channel axis. This set-up, therefore, has the potential to enable segregation and enrichment of pre-malignant cells, within an elevated enriched z-axis location perpendicular to the flow direction, thereby allowing the analysis of the correct cells within the entire population.
Large-area polarized organic LED illumination and optical snap-shot along the flow path of multiple independent polarized images at the same time for each frame will capture enriched abnormal cells locations, depending on their density and elastic properties controlled by the three-dimensional dynamic shift of the acoustic field. We therefore consecutively, repetitively, and accurately can quantify the biophysical properties of each cell along the large flow direction area.
Here, we predict to be able to capture 99.9% of abnormal cells from a heterogeneous population with an acceptance of 5% of normal cells at unprecedented ultra-high speed.
We will use acoustic fields to enable this sub-cellular selective enrichment in three-dimensional matrices within the entire cell population flow path. Such fields will be created using fully transparent piezoelectric thin films and specially designed transparent electrodes integrated into a glass substrate will allow imaging through the device possible.
This design will enable dynamic spatial modulations of node and anti-node through a shift in frequency along the x-y-z channel axis. This set-up, therefore, has the potential to enable segregation and enrichment of pre-malignant cells, within an elevated enriched z-axis location perpendicular to the flow direction, thereby allowing the analysis of the correct cells within the entire population.
Large-area polarized organic LED illumination and optical snap-shot along the flow path of multiple independent polarized images at the same time for each frame will capture enriched abnormal cells locations, depending on their density and elastic properties controlled by the three-dimensional dynamic shift of the acoustic field. We therefore consecutively, repetitively, and accurately can quantify the biophysical properties of each cell along the large flow direction area.
Here, we predict to be able to capture 99.9% of abnormal cells from a heterogeneous population with an acceptance of 5% of normal cells at unprecedented ultra-high speed.
