Antigen Density Matters: Advancing Immune-Targeted Cancer Therapies

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So today I'm going to talk about antigen density and just a couple of our new technologies at RoukenBio. 

 
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So before I begin with the science, I'd just like to go and just talk a little bit about RoukenBio. 

 
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So we are immunology based CRO, we've recently rebranded at the end of last year with the focus to kind of harmonise our resources and our tools that are available. 

 
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We were previously Antibody Analytics, and I think that gave a lot of the community the wrong impressions that we manufactured antibodies and characterised them. 

 
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That was only a that was a bit of a misconception. 

 
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We characterised antibodies, but we're CRO immunology based cell therapy. 

 
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Thank you. 

 
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So just a brief history about the company. 

 
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We were founded in 2015, so we're almost at the 10 year mark. 

 
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We started off with biosimilar characterisation. 

 
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Our immunology services was launched in 2018. 

 
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We then launched our R&D department in 2019. 

 
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Our selling engineering services came online in 2020 and then we launched our IndEx-2 platform, which I'm going to talk about today. 

 
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We had a huge NorthEdge investment, we opened our new discovery centre just outside of Glasgow and we have rapidly expanded in the last couple of years, going from about 30 staff to now over 100. 

 
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And a lot of our staff are sourced from academic institutions, Glasgow University, further afield. 

 
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So these are some of the establishing therapeutics that we've worked on. 

 
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So monoclonal antibodies, bispecifics, multispecifics, immuno-cytokines, cell therapies, targeted protein degraders, small molecules, and we've recently been branching into nanoparticles and peptides as well. 

 
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So these are just some of the tools and resources that are available at our CRO. 

 
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We have thousands of human PBMC cell banks. 

 
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We have access to fresh blood, disease state material tissue now from the human tissue bank. 

 
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We have hundreds of engineered cell lines. 

 
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We've got access to recallable donors and we've got the latest technology and our in house engineering services. 

 
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Obviously we have patents associated with them as well. 

 
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We have GMP ready assay, potency assays as well available, but we're not a GMP facility. 

 
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So this is what I wanted to talk about today. 

 
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So the key challenges in developing tumour target therapies lies in identifying optimal tumour antigens. 

 
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So these antigens aren't often cancer specific. 

 
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They can be over expressed cancer cell lines, but they can also be lowly expressed, and they can be expressed in healthy tissue as well. 

 
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So efficient treatment can be more difficult. 

 
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This contributes to immune evasion that can down relate expression of target antigens that we're interested in and that's termed antigen escape and that applies to multiple modalities. 

 
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So immune cell therapies, engagers, antibody drug conjugates, multi specific and bispecific antibodies and conventional monoclonals. 

 
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And this is just a little snip from the current FDA guidelines, just saying that obviously undesired targeted and healthy and normal tissue can express the intended target. 

 
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And these on target off tumour effects are obviously of critical concern. 

 
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So the traditional methods for assessing antigen density include a collection of a panel of cancer cell lines. 

 
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They may have a similar genetic background, or they may be varied. 

 
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These cell lines would be put into a functional assay. 

 
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And obviously there's limitations to this method. 

 
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Access cost, expression range can be limited. 

 
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And obviously the one of the main concerns is your cell line background. 

 
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If you've got a lot of variation there, how do you know between your controls that you're really seeing what you're seeing? 

 
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So what would the ideal system be? 

 
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So we would look for ideally a common genetic background, a large dynamic range of expression from a couple of 100 cells up to millions perhaps, something that was finely titratable and availability of a genetically matched negative parental control. 

 
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So this is our solution. 

 
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We filed a patent on this a couple of years ago. 

 
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So it's freshly launched as we say. 

 
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So the IndEx-2 platform is an inducible cell line platform which uses its chemical proximity based. 

 
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It's from plants. 

 
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It's actually something that plants would go through in a stress response. 

 
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So it's fairly inert chemically in terms of mammalian cells. 

 
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So this antigen expression is highly sensitive, titratable. 

 
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When we add our chemical inducer, we can induce from say a couple of 100 receptors up to round about a million. 

 
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That's not in every cell line obviously. 

 
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But we then employ these cell lines in functional assays, and we can get a variety of readouts, whether it's kinetic based, impedance, whether it's fluid cytometry based, multiplex cytokine based. 

 
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And then we're actually able to determine a threshold of activation for a compound. 

 
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And that would be through our statistical analysis using these functional assays. 

 
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And so this is just a little bit more of an introduction. 

 
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So our cell lines are generally CHO-K1 background, but the system can be applied to any cell line, and we tend to use CHO-K1 just because it has no human antigens present. 

 
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So you've got a blank slate to work with, but any cell line would actually be appropriate if the concerns there are you may have an antigen that's already expressed that might compete or might be the antigen that you're trying to induce. 

 
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So considerations on knockout may have to be considered. 

 
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But CHO-K1, obviously as I say, blank slate, it's great to work with. 

 
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So we induce our, we introduce our induction cassettes and our antigen through lentivirus. 

 
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And you can see here we've got an example of a couple of different receptors, HER2 EpCAM BCMA and CD19 and all are finely tuneable. 

 
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So this platform can also be applied to two antigens at the same time. 

 
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So our dual expression, we've got an example here, CD19 through abscisic acid and CD22 through indole-acetic acid. 

 
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These two are completely independent of each other. 

 
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However, they're co-expressed on the same cell line. 

 
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And again, this lovely graph on the right hand side receptors per cell, highly titratable but very similar to each other. 

 
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So this can be applied to bispecifics or CAR Ts. 

 
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So this is an example of some data we ran with an OR CAR Ts whether the CD22 or CD19 antigen would bind to the target cell line. 

 
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We used the inducible dual expression CD22, CD19. 

 
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Hope that in a functional assay, we looked at target cell cytolysis and cytokine analysis and you can see here there's a nice trend between the receptors increase in receptors per cell increased IFN gamma and specific cytosis as well. 

 
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This is an example of AND and CAR T where both receptors must engage simultaneously. 

 
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And again you can see when we pop it in the same functional assay, there's a slightly different pattern here that emerges. 

 
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But again, it's highly titratable IFN, gamma secretion and specific cytolysis. 

 
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So the next thing I wanted to talk about was our single cell interaction cytometry. 

 
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So I'd like to compare differences in SPR flow cytometry and this new technology as well. 

 
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So some of the challenges with SPR is cell mobilisation and limited detection depth specifically as well, your target that you're applying to the chip might have a certain fold or a certain format that you need to mimic, and it might be quite difficult. 

 
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So you might actually not get desired antigen binding. 

 
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So flow cytometry obviously been around for a long time. 

 
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It's a fixed endpoint. 

 
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There's tedious workflows and you don't get those sensitive kinetic measurements you do with SPR. 

 
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So the single cell interaction cytometry bridges that gap. 

 
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We're able to trap cells and do real time binding kinetics. 

 
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So this is our instrument. 

 
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It's the heliXcyto. 

 
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It's made by Bruker. 

 
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It's automated analysis. 

 
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You get association kinetics and dissociation kinetics, so very similar to SPR, but because you're looking at cells in their natural environment on the cell the protein is expressed as it naturally would be. 

 
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You can look at affinities and avidities as well. 

 
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This is just a couple of snips of the internal chip in the cell. 

 
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You can see these lovely little nano cages and they trap the cells 1 cell at a time within these cages. 

 
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They're different chips, have different cage numbers on them. 

 
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I think the maximum is about 8 cages per chip, but as you can see, this particular one has five cages, so you can actually analyse 5 cells at the same time. 

 
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So this is just an example of a current workflow. 

 
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So you would load your cells into the microfluidic injection. 

 
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You would then trap the cells. 

 
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The cells are not adhered, they're not immobilised in any way, they're just contained within the cage. 

 
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You would then flow over your analyte which you would fluorescently label and very similar to SPR completely open system with buffer, you would then measure the association in real time and then you would flow over your dissociation buffer which didn't contain your analyte and you can then measure the dissociation in real time as well. 

 
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And then once you're finished with your experiment, you can just discard yourselves to waste. 

 
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So this is just an example of some data that we've generated recently using nivolumab, a PD-1 checkpoint inhibitor. 

 
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And we just analysed it on some T cells. 

 
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You can see in the orange on the left hand graph here the association of two different concentrations of nivolumab .5 and five nanomolar. 

 
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And then you can see the blue line, this dissociation curve and you can see that the curve here has like a biphasic fit. 

 
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So the initial dissociation is very rapid followed by a much slower dissociation. 

 
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And that's really where the avidities come in. 

 
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And we're able to notice the difference in dissociation rates associated with a one to one antigen to cell interaction versus an antibody completely interacting at all binding sites. 

 
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So that's really where your avidity measurements come into play. 

 
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So this is just an example with HER2. 

 
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So we used our IndEx-2 selling to increase antigen expression of HER2 on a CHO background different concentrations of abscisic acid. 

 
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We can see increased expression on the left hand side here of HER2 against our parental which is the bottom histogram, the bottom left hand side there. 

 
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And you can see we've got a couple of different concentrations of ABA along the bottom and a nice correlation with the number of receptors per cell. 

 
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So this is just some examples using trastuzumab bound to the fixed CHO cells that expressed HER2. 

 
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And you can see at the top left hand side, we have very large receptor numbers, almost one and a half million going down to 800,000, down to 100,000 and down to very low levels 600,000. 

 
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Our wild type control which was not transduced and our uninduced control which is the IndEx-2 inducible cell line, but we haven't added the ABA chemical inducer. 

 
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So you can see here a lovely correlation between the number of receptors and the dissociation curves. 

 
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So it takes much longer if you increase the receptors to get that dissociation rate to fall. 

 
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So HER2 expression effects levels of the signal amplitude and this is just a nice graph basically representing what we've just seen. 

 
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So the increased number of receptors means that the signal amplitude per cell increases, and it takes much longer to dissociate from the cells. 

 
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So what can we decipher from this? 

 
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HER2 expression will affect kinetic rates. 

 
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High expression may increase avidity. 

 
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You can see here along the bottom the higher number of receptors, the longer the half-life in terms of the dissociation rate and that affects your measurements in terms of your kinetic dissociation rates. 

 
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So this platform can also be applied to difficult to express targets. 

 
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So some transmembrane folding here CD20 and we've added rituximab labelled to the red fluorophore. 

 
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So the heliXcyto is able to take two measurements simultaneously, one in the green fluorescence and one in red. 

 
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So we directly labelled with a red fluorophore here and we're just measuring rituximab binding to the CHO CD20 expressing cells. 

 
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And you can see here compared to literature the bottom right hand side, the dissociation rates next to that weaklings are slightly different there. 

 
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So in summary, our IndEx-2 platform engineered to mimic tumour associated antigen targeting. 

 
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Its titratable expression of antigens allows precise control over receptor density enhancing therapeutic sophisticate assessments. 

 
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The platform is particularly beneficial to CAR Ts and multi specific engagers. 

 
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It addresses logistical efforts, costs and changes associated with antigen density. 

 
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It's suitable for antigen threshold assessments and it's suitable for on target off tumour effects and the single cell interaction cytometry provides that necessary in between gap that we have between SPR and flow cytometry. 

 
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You have real time binding kinetics on the cell. 

 
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The target is naturally expressed in its form and that offers deeper insights into receptor expression and avidity. 

 
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The receptor density can also influence signal strength, therapeutic engagement and is a crucial consideration. 

 
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So a little bit more about RoukenBio, some of our advanced instrumentation. 

 
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We have high spec flow cytometers. 

 
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We now have the heliXcyto. 

 
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We have latest plate readers, automated isolation. 

 
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We have our Hidex Sense Plate Readers as well. 

 
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We have Multiplex capabilities SPR, we have the Biacore 8K, and our excellent Excellence Real Time Cell Analyzer is obviously a useful tool to use with IndEx-2 for your TDCC assessments. 

 
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And that is us. 

 
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If you'd like to talk more, head over to the booth and speak to Jamie. 

 
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We're happy to discuss any of these with you.