A combined ultrahigh plex whole slide staining and imaging system for a multiuser advanced imaging facility
Lead Research Organisation:
University of Leicester
Department Name: Cancer Studies and Molecular Medicine
Abstract
Pathology is a clinical discipline, whereby consultant doctors can look under a microscope at different pieces of human tissue which have been removed from patients during surgery, and help make an accurate diagnosis of the disease. Typically, this is achieved by looking at the structure and architecture of the tissue, or looking for individual proteins to see if there is more or less of those proteins. This allows us to delineate where these proteins are expressed, e.g. at the membrane, in the cytoplasm, or in the nucleus of a cell. These technologies and techniques are used by basic, translational and clinical researchers alike.
More recently however, there has been a shift in the way that we can visualise different proteins under a microscope in a piece of tissue. Moving away from detecting single proteins, we can now look at multiple proteins of interest at once using a process called multiplexed immunofluorescence (mIF). Current mainstream technology allows for the combined detection up to 7-9 proteins with relative ease, in a high throughput setting. Any more than this, and technical difficulties start to occur.
The ability to detect multiple proteins in the same piece of tissue, allows the researcher to look for novel protein expression patterns in different pathologies, for example: a) are multiple different proteins expressed in the same cells? b) Does this expression change depending on where in the tissue the cells are located? c) What cells are present and where in the tissue? Moreover, in a piece of human tissue, there are multiple different cell types present, these could be for example, cancer cells, and the patient's own individual immune cells all nestled together and communicating with each other. Having the ability to decipher what cell types express what proteins and where, the abundance of different cell types present and under what disease states can help to inform us about potential markers of drug resistance/sensitivity for specific diseases, and infer the mechanisms by which disease progresses.
mIF can now be achieved evaluating over 100 markers in the same piece of tissue using ultrahigh-plex imaging , giving unprecedented insight into how the spatial geography of tissue, different cell types and disease states are interconnected. What's more, this process is fast, and capable of analysing every single cell on a microscope slide, compared to alternative methods which typically only allow for the high throughput evaluation of specific regions of interest (ROI) within a given piece of tissue. This means the way researchers analyse data is completely unbiased. The ability to evaluate such high level data in an unbiased way would greatly enhance our ability to progress biomarker and drug discovery, and validate any identified biomarkers or druggable targets in different disease pathologies. More specifically, the technology will allow researchers to decipher the potential roles that specific immune cells have in disease progression, and drug resistance in multiple disease indications, for example: cancer, nephropathy, and asthma.
To evaluate such complex data, advanced image analysis software, driven by artificial intelligence (AI) is required to robustly analyse ultrahigh-plex images in a reproducible and timely manner. Software to identify every cell in the tissue, and analyse protein expression rapidly and accurately in each cell is now commercially available. By installing one of these ultrahigh-plex systems and the associated required software infrastructure at the Leicester Advanced Imaging Facility, we aim to promote world-class translational research, and biomarker and drug discovery, making it accessible to academia and industrial partners.
More recently however, there has been a shift in the way that we can visualise different proteins under a microscope in a piece of tissue. Moving away from detecting single proteins, we can now look at multiple proteins of interest at once using a process called multiplexed immunofluorescence (mIF). Current mainstream technology allows for the combined detection up to 7-9 proteins with relative ease, in a high throughput setting. Any more than this, and technical difficulties start to occur.
The ability to detect multiple proteins in the same piece of tissue, allows the researcher to look for novel protein expression patterns in different pathologies, for example: a) are multiple different proteins expressed in the same cells? b) Does this expression change depending on where in the tissue the cells are located? c) What cells are present and where in the tissue? Moreover, in a piece of human tissue, there are multiple different cell types present, these could be for example, cancer cells, and the patient's own individual immune cells all nestled together and communicating with each other. Having the ability to decipher what cell types express what proteins and where, the abundance of different cell types present and under what disease states can help to inform us about potential markers of drug resistance/sensitivity for specific diseases, and infer the mechanisms by which disease progresses.
mIF can now be achieved evaluating over 100 markers in the same piece of tissue using ultrahigh-plex imaging , giving unprecedented insight into how the spatial geography of tissue, different cell types and disease states are interconnected. What's more, this process is fast, and capable of analysing every single cell on a microscope slide, compared to alternative methods which typically only allow for the high throughput evaluation of specific regions of interest (ROI) within a given piece of tissue. This means the way researchers analyse data is completely unbiased. The ability to evaluate such high level data in an unbiased way would greatly enhance our ability to progress biomarker and drug discovery, and validate any identified biomarkers or druggable targets in different disease pathologies. More specifically, the technology will allow researchers to decipher the potential roles that specific immune cells have in disease progression, and drug resistance in multiple disease indications, for example: cancer, nephropathy, and asthma.
To evaluate such complex data, advanced image analysis software, driven by artificial intelligence (AI) is required to robustly analyse ultrahigh-plex images in a reproducible and timely manner. Software to identify every cell in the tissue, and analyse protein expression rapidly and accurately in each cell is now commercially available. By installing one of these ultrahigh-plex systems and the associated required software infrastructure at the Leicester Advanced Imaging Facility, we aim to promote world-class translational research, and biomarker and drug discovery, making it accessible to academia and industrial partners.
Technical Summary
We aim to install a combined ultrahigh-plex whole slide staining and imaging system at the multi-user Leicester AIF for use by UoL researchers Midlands Innovation researchers and industrial partners. We also aim to set up an artificial intelligence (AI) driven advanced digital spatial profiling analysis suite essential for robust image analysis. AIF has one slide scanner, an Akoya Biosciences PhenoImager HT (PIHT), a high throughput system limited to 8 markers on a single slide, which is used at 80% capacity. There is strong demand from users of the PIHT, wider Leicester research community, local Universities, and collaborators, including industrial partners to increase capabilities of our spatial profiling infrastructure to enable 1) a larger array of markers on a single slide 2) using whole slide imaging 3) reproducible and robust imaging with increased speed.
An Akoya Biosciences PhenoCycler Fusion (PCF) will achieve these goals, simultaneously aligning with current digital analysis infrastructure. PCF allows for robust automated staining and imaging of whole slides (18 mm x 35 mm), at single cell resolution (250 nm) resulting in unbiased imaging, increased reproducibility, speed and throughput, due to walk away automation coupled to parallel image and data processing. Flexible workflow design allows for adaptable protocols, from ultrahigh-plex protein based panels for hypothesis free biomarker discover to smaller focused panels for high-throughput biomarker validation. This is achieved via iterative reveal, image, remove steps using oligonucleotide barcoded antibodies, and fluorophore conjugated complimentary oligonucleotide reporters. From Q3 2022 the PCF will also be compatible with RNA based markers with no required hardware upgrades. Together, the features of PCF fulfil the requirements of AIF to provide state-of-the-art advanced digital pathology imaging solutions to a wide range of researchers working within the MRC remit.
An Akoya Biosciences PhenoCycler Fusion (PCF) will achieve these goals, simultaneously aligning with current digital analysis infrastructure. PCF allows for robust automated staining and imaging of whole slides (18 mm x 35 mm), at single cell resolution (250 nm) resulting in unbiased imaging, increased reproducibility, speed and throughput, due to walk away automation coupled to parallel image and data processing. Flexible workflow design allows for adaptable protocols, from ultrahigh-plex protein based panels for hypothesis free biomarker discover to smaller focused panels for high-throughput biomarker validation. This is achieved via iterative reveal, image, remove steps using oligonucleotide barcoded antibodies, and fluorophore conjugated complimentary oligonucleotide reporters. From Q3 2022 the PCF will also be compatible with RNA based markers with no required hardware upgrades. Together, the features of PCF fulfil the requirements of AIF to provide state-of-the-art advanced digital pathology imaging solutions to a wide range of researchers working within the MRC remit.
