I'm going to try and show you some of the complexities around modelling this tumour micro environment in vitro.
0:07
It's not an easy task, but we have to try and do to do that in therapeutics.
0:15
So as we've heard today, our understanding of the immune system is really driving forward all the immunotherapy treatments that are currently available.
0:25
And there have been huge advancements, from immunonegatives, numeric antigen receptors from iOmx, then cellular therapies.
0:38
And it's all really advancing immunotherapies and largely immunotherapy aims to use the immune system, natural defences or remove the obstacles that are living from the tumour.
0:53
And there are still considerable challenges.
0:56
It doesn't look like the targets we've got at the moment always work in everybody.
1:04
And we need to find new drug targets and understand the system better.
1:09
And this tumour microenvironment, which was nicely summarised previously, is driven larger by the tumour cells.
1:19
It’s heterogeneous, it can vary from cancer to cancer.
1:22
It can vary from patients to patients and it can even vary stage to stage.
1:26
So it's really a tricky question to try and answer.
1:31
But largely some of these factors here are what drives the tumour microenvironment.
1:35
It's you know that information from cytokines like VEGF and IL 10 and expression of CTLA4 and PDL1
1:43
As well as the reprogramming of T cell that happens in the tumour microenvironment because of the weak antigen signals that it's receiving from the tumour, which drives this conscription with an active and responsive T cell as well as we heard previously about the tumour associated macrophages and myeloid rice press the cells in the T rating which these things Dr approaching on and you can't forget some of the access to the new cells caps.
2:17
And so you know, there really is a need to find physiologically relevant thinking for models to try and understand this.
2:26
And as I said earlier, the checkpoint inhibitors in immunotherapy have paved away for us to try and look at this and they work by harnessing the fact that T cells regulate negative effectors.
2:38
And those are highlighted there in the black box and your T cells go to the activated Sigma 1. The T cell engages with MHT antigen and some of the Co receptors go in red will drive that T cell activation.
3:02
So things like 4-1B and CD4DE and so on and that drives the T cell to the cytotoxic and malignant tumour some of the inhibitory receptors like TIGIT 4 etcetera will check and block that.
3:24
And so how do we model this? It's complex, and how do we understand what's required to model this?
3:32
So does it need to target on both effector cells and target cells?
3:37
Do you need activated cells divisions, do you need specific CP8 cells?
3:43
There's a whole host of questions that we've investigated to try and understand.
3:47
So the example and the concept I'm going to show you is taking CD3 T cells and CD14 monocytes from the same donor.
3:57
And the CD3 T cells were isolated and they were left to rest while CD14 monocytes were differentiated and matured, matured into dendritic cells.
4:08
And then in different combinations, we took T cells to a dendritic cell and painted them with tumour cells and in this example is shown here.
4:18
And when we can Co culture together and look at the tumour cell filling by an IncuCyte analysis, which helps you and how to read out over time of how the tumour cell is being killed or not killed.
4:34
So in this first example, these are traces that we get from IncuCyte and essentially just to guide you through on the X axis is time and on the Y axis you've got either tumour cell growth or we've got apoptosis.
4:50
And in the top right corner, we've got the tumour cells alone to show whether there's any effect of the drugs. In this experiment where we've chosen pembrolizumab, the IgG4 isotope and as a positive control, we've used IL-2/alpha CD28.
5:10
And up here you can see that there's no effect on tumour cells and there's no apoptosis.
5:22
However, when you add stimulated T cells into the mix, so this is stimulated T cells
5:30
See that depository control here in green across all three.
5:32
There's actually no effect on the Pembrolizumab.
5:43
When we a dendritic cell into the mix, see that the scene is slightly different again, we get this effect on the IL-2/alphaCD28.
5:52
So you're now starting to see that there's a window affected and there is a map where it's either in lin with the positive control or it's actually slightly better and you get an enhancement of apoptosis or a reduction in tumour cell growth.
6:12
When we look at these conditions, either the T cell knows. Or the introduction to a dendritic cell into the mix, we can see just by looking at the cytokines that have been made, there's a very big difference.
6:27
So in T cells alone we're not seeing as we much production of cytokines and agile material agents of cells and then getting this abundance affected T cell if we've decided to find particularly, you know interval gamma grand zombie and TNF of children 5 tumour elimination.
6:45
So in summary, essentially without that autonomous mature dendritic cell, we weren't able to show victims of this example.
6:55
And in patients, it's been shown that an interferon gamma signature is positively associated with.
7:05
So those patients respond better to treatment.
7:09
And what we've seen in vitro as well is that if we look at the interferon gamma signature from pelvis map as well as the trim cell growth we're getting, we get a positive foundation as well.
7:21
So this is just to demonstrate to you how we should be trying to look at all the cells that may be part in this environment.
7:31
It might be that you need the PD1 PDL 1 axis to open up that window of effect in this example and may differ and if you do go from the target to target.
7:49
So another area that we can look at in vitro, which is really interesting as well is that of the antigen specific world and antigen specific T cells are in critical to that long term protection.
8:04
Following vaccination against tumours or women in cells, eliminating tumour cells, we build up a long term memory.
8:14
And it's also known that a high frequency of antigen tumour, so specific T cells correlate.
8:21
And so we're trying to use that and, and, and capitalise on that in new therapies that are coming out of vaccines that drive and expand rare antigen populations.
8:33
And preclinical research in this area is really challenging because the quickest frequencies of these antigens cells is really low.
8:42
And we really need to find ways to unlock the simply vitreous system.
8:48
And the way we do this is by generating pools of antigen specific T cells that we can test in vitro.
8:56
So it depends really what you're asked is so where you are in the discovery pipeline, what you want to do.
9:02
So for example, if you want to do predicting the genericity of another vaccine or we wanted to see whether we could drive expansion of ground sick cells or even if you want to do RAG, you know like a hierarchy of cancer vaccine candidates, you would start with a naivety cell population.
9:24
So you'd HLA Nash and isolate your PBMCS and then as shown in the previous example, rest your naivety cells one differentiate more dendritic cell and then prior to co-culture you pulse your DC with the antigen of interest and then co-culture for a few weeks to drive your antigen T cell expansion.
9:51
And we can measure by any spot. The results down the bottom show an example from the previous piece or where we pulse you mart-1 and driven a mart-1 specific antigen population.
10:04
And when we re-stimulate these T cells, you can see in this antibody result are produced at that are correlated with this blue bar.
10:18
If we wanted to test an existing therapy and carry out a functional assessment.
10:40
You would just polyclone antigens.
10:45
So these days many of the multimers would be custom made them and they're very simply labelled which allows you to fact sort a really rare population.
10:56
So again we've used Mart-1 as an example.
10:59
We can see it's very low and there's nothing we can do with that individual.
11:06
And so what we do is we tag these cells closely and polyclone them, we see after a few weeks of expansion you get about a thousandfold expansion and you retain the purity of these cells.
11:31
So to go further to look at what they do in culture, are they actually function killing, and are they able to kill after being in culture.
11:45
So there's a number of ways that we can look at this into culture.
11:49
The first way, probably the easiest way is again in this example using mart-1 as our principle, but we just pulse the peptide onto T2 cells.
12:03
So T2 cells are then also labelled with a fluorescent dye across the CTB.
12:09
See how they are enabled positive CTB and it allows us when you co-culture to see the antigen specific T cells to actually tell them part and determine what the percentage cells is with flow cytometry.
12:23
When you co-culture with the T cells with the mart-1 peptide, you then are able to look at the percentage.
12:33
So this would be, you know a way to calculate it.
12:37
And if you look at an effector to target ratio where you add in different amounts of your antigen specific T cells and you can see that it's dosed by critical and with adding a therapy.
12:49
So you can see that there's an effect probably the most physiologically relevant option is to use endogenously expressive tumour cells.
13:02
And so in this example, we’re using antigen specific environments and possibly this one as well, you're not relying on sort of an HLA mismatch to gripe killing.
13:17
Then you're actually looking at possibly what's going on in vivo.
13:23
And here we've chosen an HLA A2 positive Melanoma cell line and we've used an IncuCyte readout and we label the tumour cells red. And they stay with the alcohol of the co-culture.
13:42
So you distinguish the tumour cells from the CD8T cells, and we've added in a caspase dye so we can determine apoptosis.
13:54
But essentially in these endogenously expressive cells we've been adding CV8 add to specific mart-1 cells.
14:00
You can see that there is a good amount of filling and as a positive control pulse, that's what we get.
14:11
And then if you're not so lucky in terms of you don't have access to a tumour cell that expresses the antigen or you're sure you can actually overexpress your antigen.
14:23
So you can transduce your cells with the antigen of interest using a viral approach.
14:30
And in this case, we've again chosen MelanA.
14:33
And so we've transduced in MelanA to the MelanA, transduced the type cells.
14:42
And here we've done a co-culture with the marked line antigens for T cells on the intra site.
14:49
Again the same places we've got hours on the X axis and tumour cell growth on the Y axis.
14:57
And in orange is the tumour cells that have been the super transduced tumour cells that have been see that they are being built on the wild type cells.
15:14
And that when you add in peptide, that's not sort of a medium amount.
15:28
So this is a 2D environment.
15:32
If you want to look at 3D, which is a way to kind of physiologically mimic some of the tumour microenvironment, we could actually make spheroids.
15:50
But you can see very briefly we've got wild type cells and the MelanA transduced.
15:55
And what I want to highlight is that the MelanA transduce can see that the CD8 cells are storming tumour spheroid, but that can be massively advanced with therapeutic.
16:09
And so in summary, we can test some of these new therapeutics in vitro.
16:17
There's a lot of considerations that need to be made.
16:20
The examples I've showed are what checkpoint inhibitors and specific assays can do, but all of those are likely to need some type of validation or optimization.
16:33
But it is possible to try and do it and model it in vitro.
16:38
Thank you.
