0:29
Thank you very much and thank you very much for coming.
0:34
So as goes with the title, the main aim of my talk today is to try and understand how spatial multiomics, especially same section spatial multiomics could be applicable to you in the development of novel therapies for oncology and otherwise.
0:52
So just taking a step back, one of the big aims with the company at its like founding was to make sure we develop a technology where we can bring together multiple assays on one slide.
1:06
And the idea here was that we could go past the old understanding that we need to combine multiple assays on the various different formats and bring them into one Multiplex assay.
1:18
So this allows us to bring all the different biomarkers and assay types available into one.
1:25
And the idea here is that we by combining all of this, we could get like deeper insights into cell interactions.
1:35
Cells also include details like cell morphology and spatial positioning all into one.
1:43
And hopefully with this, we would move forward by accelerating the development of novel therapeutics for patient care as well that is done with the kind of traditional pathology slides.
1:59
So we wanted to 1st understand if Multiplex immunofluorescence was actually applicable to the clinical world.
2:04
And so we ran a survey with a number of clinicians across the world and we found that almost 47% of them responded saying that they envision Multiplex immunofluorescence as a modality for like clinical diagnostics and it has some clinical use in the future.
2:24
And they also stated some top requirements that they had in order to move the technology into the clinical space.
2:33
Understandably, some of the top ones around clinical utility and performance followed by automation and standardisation.
2:41
But actually the one area that we're going to focus in a bit more today and it was also something that was in our kind of top five in terms of the responses was multiomics capability.
2:53
And this was this suggested to us that in addition to the standard proteomics that you have access through with IHC in pathology, a lot of clinicians were also interested in like bringing in RNA and transcriptomic data into that to aid with their analysis of patient samples that are coming in.
3:16
So just to give a brief overview of the suite of like products that we have.
3:21
So we have the COMET at the top and that's a fully automated assay platform.
3:30
We like pride ourselves in being like very fast in terms of acquiring new data.
3:38
And I think that's the big distinguishing factor.
3:40
There are other technologies that allow you to expand the number of targets.
3:44
You can see on the same slide with us, it's the ability to kind of like once you've gone ahead and you've like narrowed down the number of targets, you can then go ahead and run through a huge volume of samples with those designated RNA and protein targets.
4:01
And also the technology at its core is very similar to IHC with the exception of glyco fluorophore instead of therapy.
4:09
And so you can take IHC optimised antibodies and you can bring them onto the COMET relatively easily.
4:16
And so that's one of the big advantages with the instrument.
4:19
And we also have our own in-house image analysis like solution, but it's an open platform.
4:24
So we encourage people to use anything that works really well for them.
4:28
And ultimately and the discussion of today will be the multiomics aspect, which was added to our portfolio after our acquisition, which was by BioTechne.
4:37
And so we joined forces with ACD from BioTechne and ACD being one of the biggest RNA probe providers that's around.
4:47
They also supply RNA probes for clinical diagnostics.
4:52
And so they were all known for their like robustness and reproducibility.
4:58
So we ask ourselves why multiomics?
5:01
So standard IHC and even like Multiplex proteomics gives you a lot of insight already into the patient sample.
5:07
We can look by looking at like multiple markers, we can understand cell like localization, cell interactions, but we can go a little bit beyond that and we can look at like markers that are otherwise not like available with standard proteomics.
5:21
And so we can look at things like secreted molecules.
5:28
We can look at infectious agents.
5:30
This is particularly helpful in oncology cases that are like that can be driven by an infectious agent, so for example, HPV.
5:41
And so being able to kind of combine both of these on the same slide allows us to bring RNA localization and Multiplex proteomics onto the same section.
5:50
And this gives you a far greater insight into the state of that cell and also other underlying factors that might affect your ultimate decision.
6:03
So this is a brief overview of the multiomics workflow.
6:10
The whole thing is automated with the exception of the manual preprocessing where you have your dewaxing and antigen retrieval.
6:18
We have an optimised antigen like retrieval like protocols especially designed for RNA scope so that we can then combine RNA scope with our standard proteomics.
6:29
So we start off with RNA detection and this is with RNA Scope HiPlex Pro.
6:35
And over here you have the detection of up to 12 RNA targets.
6:39
And this is then followed by a standard sequential immunofluorescence.
6:45
And all of this is then stitched and combined on the computer itself with Horizon software.
6:53
And you get one stitched image that's being like flat field, like corrected as well in an OMT format.
7:00
And so you can then use that data as you see fit.
7:06
The good thing here is at the end of it, you can also use the slide for other downstream applications.
7:10
And two of them like notably are IHC and H&E.
7:14
And this is great benefit to our clinical users who use H&Es quite often for the diagnosis.
7:26
And all of this takes about like 30 hours approximately.
7:31
So that's 12 RNA markers and 28 protein markers.
7:35
And so you could get the results the next day.
7:38
So now we'll go through some examples of this data.
7:43
And so here we have an example where we Co localise HAVCR2 and TIM-3 both the gene marker and then the kind of corresponding like protein as well.
7:56
So you can look at you can look at your RNA expression along with the protein expression to get a deeper understanding of you know, is this something you'd expect to see?
8:10
Is one missing? If so, why?
8:12
And there are of course differences with RNA expression and protein expression, they don't always correlate with each other.
8:19
But if that's something that's known, that's something you can validate as well.
8:22
If you're able to like visualise both at the same time on the same slide.
8:28
And interestingly, we can also work, we also work downstream of other instruments and a great example here is the Xenium.
8:36
So according to understanding, a lot of our end users use the Xenium to get a very broad understanding of different RNA targets to try and narrow down the number of targets they want to look at.
8:50
And once they do, they then take the exact same slide, which is also compatible with the COMET and they run a seqIF stain on it.
8:59
And so now you have your Xenium data and you have the Multiplex immunofluorescence data and you can stitch all of that together, the combination of image A and R and you can get one combined image.
9:12
And so this gives you a huge opportunity to look at a vast amount of data from a single slide.
9:19
And it also makes much better use of the same tissue sample as well, because in some cases tissue availability is a big issue.
9:31
The resolution of the COMET allows you to go down to the a level where you can understand the like localization of your proteins and your RNA markers.
9:45
And you can then combine, for example, like ECM markers with cytokines and then cell like phenotype like markers as well.
9:56
And you can bring all of that together.
9:58
The way you do that, the way you analyse that's all down to your individual like use cases.
10:02
But we give you the technology to enable that. Spatial multiomics has been used already.
10:14
So we have Werewolf Therapeutics and they've ran spatial multiomics to understand changes in the tumour microenvironment when they implement some of the inducible cytokine molecules.
10:33
And so the full paper is available there and the whole methodology is also available there.
10:39
So please go have a read when you have some time.
10:42
But yes, it's, there's great potential here on the drug development side to expand the understanding that current pharma users have and expand their data analysis capacity by combining both spatial proteomics and spatial multiomics on one.
11:01
And so just to reiterate, you can do all of this on the exact same section of tissue.
11:08
The whole process is fully automated.
11:10
So there's no steps in the middle where there's any kind of manual processing.
11:13
So you can let the process run, for example, overnight and come back the next day and you would have your data.
11:20
There's a huge library of RNA targets.
11:23
I think there's definitely over 10,000 and ACDs RNA scope also allows for custom probe development as well.
11:34
And so you could practically run any kind of target that you like with the with these options.
11:41
And ultimately it is fast.
11:44
So as I said, you can run a full 28 Plex with 12 RNA markers within about 30 hours.
11:51
And if that's done in a fully automated way, you'd have your results the next day.
11:59
I mentioned Horizon before.
12:01
So we've been internally trying to develop algorithms to count the RNA dots.
12:09
The way RNA is usually quantified is through these distinct punctuated dots and each one of these is one transcript.
12:18
So there's a lot of there's a lot of potential there to be able to count these and also to like localise them to specific cells or specific tissue components.
12:28
And we are building in this analysis into Horizon to enable our end users to do that as well.
12:33
And we actually currently like rolling this out to all our current COMET and Horizon users as well.
12:38
And you'll be available to anyone else that joins.
12:42
And as I mentioned before, even after the full spatial multiomics, protocol, you can then take the same section and for example, you can stain it with a standard H&E.
12:55
Again, from a clinical perspective, this is really it's a really kind of helpful tool.
12:59
A lot of standard clinical diagnosis is still based on your like H&E.
13:04
And so being able to run a H&E after all of this and then combine those into one image that you can switch between is a huge advantage because clinicians will be able to identify certain morphological characteristics and then correlate that with the protein expression and your RNA expression as well.
13:22
And we are doing some work with bringing spatial multiomics to fresh frozen sections and we presented some initial proof of concept data at CITI last year.
13:36
So feel free to kind of stop by the booth and we can go through like some of that data as well.
13:44
And so as I said, if you need any more information around the technology, around the applications or any other kind of like questions you might have, feel free to stop by the booth and we'll be happy to answer them.
13:53
Thank you.
