0:05
My name is Brian Serrels.
0:06
I'm the sales specialist for the UK for Lunaphore covering the COMET platform.
0:12
And then Natalie from ACD will take over towards the end and just present a couple of slides on the RNAscope application.
0:21
And so we are both within the Biotechne division, the spatial biology division at Biotechne and to dive straight into the technology.
0:30
We can see here we have the COMET platform on the left hand side.
0:35
This is a, a platform that's been built out for robust spatial multiomics.
0:40
We have 20 reservoirs.
0:43
These are simply 2ml Eppendorf tubes that we can see loaded into the left hand side of the instrument.
0:49
And within each of these tubes we can place two antibodies.
0:52
We always work in antibody pairs, or we can add multiple RNAscope probes, and we'll touch more on the multi omics workflow towards the latter part of the talk.
1:04
And so we load our pairs of antibodies into these 20 reservoirs and then we also have a four slide rotating stage within the instrument and obviously our integrated microscope.
1:15
So the COMET does all of the staining and all of the imaging and data generation within the one instrument.
1:22
Now the way that the Lunaphore COMET technology works is we use standard immunohistochemistry slides.
1:28
And then within the instrument we place this COMET chip on top of the slide.
1:32
Now this chip can be placed anywhere along the long axis of the slide.
1:36
And this essentially is used to create a pressurised microfluidic chamber in which we can carefully control the immuno reaction.
1:45
And so if you think about standard immunohistochemistry where you put your buffer with your antibodies on top of the slide and then you wait on the antibodies to diffuse through and bind to the antigens.
1:55
Here what we're doing is we're adding pressure, but we're also reducing the space between the antibodies and the antigens, which enables us to speed up that immuno reaction.
2:05
So the typical antibody incubation times on COMET are between four and eight minutes.
2:10
And that enables us to cycle fast through the data collection, which means that we can, for example, deliver 20 slides of 20 plex in one five day working week.
2:23
So moving on what's unique about COMET within the market is we use standard off the shelf reagents.
2:31
So it's a very open platform.
2:32
We are not an antibody vendor.
2:34
We have limited antibody panels available for you to buy.
2:39
The idea of COMET is that you can go to any antibody vendor and access the very best clones for your particular research question.
2:49
We also do not pull the antibodies together into 20 or 30 plex pools like some of the other technologies.
2:56
So again, with the COMET, you don't have to be worrying about antibody crosstalk, stearic hindrance because the antibodies are only applied to the tissue in pairs.
3:06
And then also we do not conjugate the antibodies either.
3:09
So we typically follow standard primary secondary antibody where we use standard Alexa fluors.
3:15
So again, there's no requirement to conjugate the antibodies and obviously the volume of antibody you have to use for that process, the time it takes and the associated cost.
3:25
However, the system is completely flexible.
3:27
So if you do wish to use pre conjugated antibodies from a vendor, then you can go and buy them and you can mix and match between conjugated and non-conjugated antibodies all within the same workflow.
3:41
We also have on board easy and guided optimization options.
3:46
So we have provided options to be able to look and determine very quickly what the optimal antibody concentration is within the same tissue.
3:56
So over the course of a couple of cycles you can apply the same antibody pair but at different concentrations and very rapidly understand what the optimal antibody concentrations are for your tissue.
4:07
We also have assay is available to look at the position of the antibodies as well across the cycles very easily.
4:15
So you can understand for example, if you have a low expression target, does that require it to be added earlier on in the cyclic process when you're generating your data.
4:24
And then importantly, this is an end to end fully automated instrument for both RNA and protein detection.
4:32
So the only part of the workflow that you do off the COMET is the dewaxing and the antigen retrieval.
4:37
For example, if you're working with FFP tissue or of course if you're working with fresh frozen tissue, then you can modify that tissue pre-treatment process.
4:46
Now we rely on the process called sequential immunofluorescence where we simply stain in the tissue with the pair of antibodies, use standard secondaries.
4:55
We then obviously image those antibodies and we then you elute those antibodies off the tissue.
5:02
Here again we elute the primary secondary antibody complex.
5:06
We actually wipe the tissue completely clean before we go back in and then stain with the second pair and go through that staining imaging and elusion cycle until we've collected all of the data.
5:17
And by removing those antibodies and because this is a very gentle process, you can actually take these tissue samples forward into other spatial transcriptomics platforms or other sequencing based platforms or for example, other processes like H&E staining, et cetera.
5:35
And so now sort of focusing on the spatial multiomics aspect of the technology, this is where we've combined our standard sequential immunofluorescence together with RNAscope.
5:47
And as I mentioned, both ACD and Lunaphore form the spatial biology division of Biotechne.
5:52
And so that's a stable working relationship that actually future proofs the application with the COMET platform.
5:59
Here of course, we're doing same section multiomics.
6:02
So we're looking at RNA and protein on the same section.
6:05
And importantly we're doing that in a fully protease free workflow.
6:09
So many different spatial biology technologies for RNA detection require the application of protease K, for example, to optimally detect the transcripts.
6:19
Here, using the HiPlex Pro assay available from ACD, we're able to do this combined workflow with no protease requirements whatsoever.
6:27
So there's no requirement to sacrifice the quality of the protein data that you can get back from your tissue.
6:36
When you combine the RNA together with the protein and the workflow, the workflow remains fully automated.
6:43
So all of the RNA component is also done on board the COMET.
6:47
Again, the only thing that remains off is the dewaxing and the antigen retrieval.
6:52
Again, if it's FFPE tissue or it's modified for other things like fresh frozen.
6:56
All of the other part of the workflow is done on the instrument itself.
7:00
Of course, by using the RNAscope, you're able to pick really any RNA target from the RNAscope library.
7:09
You're also able to take advantage of any custom probes that they can build for you.
7:13
So you have complete flexibility around what RNA targets you can analyse and of course with the freedom that already exists on the COMET around being able to go to any vendor to select any IHC validating antibody for the sequential immunofluorescence component.
7:28
Then essentially you can now build completely bespoke assays combining any RNA target with any protein target to be able to really get at your research question.
7:41
And of course this is just to give a bit of basic information on RNAscope.
7:45
I'm certainly not the expert that would be Natalie at the front here.
7:48
But essentially this is technology that relies on these double Z probes.
7:54
And then of course we then have these branches from which we amplify the fluorescent signal, and we detect puncta within the cells in order to be able to look at the individual transcripts and then quantify those transcripts within the single cells to be able to generate single cell transcriptomic based readouts.
8:11
Of course, you can really pick any gene for any species.
8:13
It's a proven application with high specificity and high sensitivity.
8:19
It's the most commonly used application within the low- to mid-plex in situ hybridisation field.
8:26
And of course there are actually I think now over 10,000 peer reviewed publications using ACD RNAscope probes.
8:33
So it really is extremely well validated and already has some approved clinical applications.
8:41
Now thinking about what the workflow actually looks like, this is as I said, a protease fully automated multi omics workflow.
8:49
So here what we do is we're doing the dewaxing and the target retrieval that is done off the instrument in something like a PT module or a Leica BOND for example.
8:59
And then within the instrument itself, in those 2ml Eppendorf tubes that I showed you at the very start, we load the RNAscope probes, and we load the antibodies that we want to use within our multiomics assay.
9:11
The instrument will then do all of the tissue treatment.
9:13
It will do all of the probe hybridisation and the amplification and then do all of the detection image and fluorescent signal cleavage.
9:21
That's all done for the RNAscope probes.
9:24
Within the COMET instrument itself.
9:26
We'll then move forward and seamlessly start doing the protein component where we'll do the sequential immunofluorescence, where we do the staining, imaging, and elusion.
9:34
And then of course, that ends up with all of the images where we do the FOV stitching and the image stacking.
9:40
And it's important to note that the images come off as OME-TIFFs.
9:43
So they contain all of the metadata and they're immediately compatible with common third party software like HALO, Visiopharm, and QuPath.
9:51
So you can just take all of this data and run it through any standard pipelines that you may already have.
9:56
Within those advanced software packages. We also have a software package called HORIZON at Lunaphore.
10:03
This is a more basic analysis package, enables you to do things like cell segmentation, cell type assignment.
10:08
You can do supervised or unsupervised clustering within it.
10:12
It's trained on COMET images, but it's not an advanced software like Visiopharm.
10:17
It's more to give people a simple way to be able to deal with and process these images in an intuitive manner.
10:24
And then if you want to do really advanced analysis, you would move to something like HALO or Visiopharm.
10:31
Then as I mentioned, because of the way we preserve the tissue, the gentle elusion that we do, you can take these tissues forward and you can do H&E staining, you can do downstream transcriptomics applications.
10:41
The tissue is intact and available for use so that you can really maximise what you can draw out of these important clinical tissues.
10:48
And when we move to the multi omics workflow, we're able to do 12 plex RNA with 24 plex protein in one fully automated run on board system.
10:57
And of course what you get at the end of the run is you're able to visualise of course your RNAscope probes.
11:03
These will obviously give you puncta relating to the individual transcripts within the cell.
11:07
And then of course you have all of your protein markers to be able to give you information on the tissue histology and structure with all the different cell types.
11:16
Obviously we can merge these data, and we can start to understand where we can assign the individual transcripts to particular cells and start to look at the gene expression within particular single cells within the tissue microenvironment.
11:31
This is just an example here of a breast carcinoma tissue that's been taken through a 12 Plex RNA, 24 plex protein workflow where we can start to visualise a number of protein markers.
11:42
Here we're looking at CD3 and cytokeratin, and the blue and green are the protein markers.
11:49
And then we've got a number of different RNA markers.
11:51
Just to pull up a couple to show you an example of what it looks like.
11:56
Importantly, one thing we have enabled on the COMET is the ability to do Z sectioning for the RNA component of the workflow.
12:04
Now this is important because you can see here that if we just rely on detecting on one focal plane, we actually lose a certain amount of the data because not all of those puncta are within focus on the single plane.
12:18
So what we do here is we give you the option to be able to take a number of Z steps.
12:22
So essentially you can capture all of these fluorescent spots and focus, we take those Z sections, we compress them down into a maximum intensity projection.
12:31
But essentially what it enables you to do is capture as much of that data as possible so that you've got the most robust data set you can from your tissue.
12:42
And then this has just showed you for example, an unprocessed slide done by standard H&E versus the slide that's been through 12 plex RNA, 24 plex protein.
12:52
And we can see here that the histology of the tissue is very well preserved by the end of the workflow.
12:58
And then just before I hand over to Natalie, then obviously why would you add RNA to your protein panel?
13:03
Well, of course, it's not always the case that you have good antibodies for every particular marker.
13:07
For example with things like secreted molecules like cytokines, chemokines if you want to mark things like the CAR for CAR T cells, then you have the option to be able to mix and match to be able to detect things where otherwise it would be difficult with antibodies.
13:24
So at this point, I'm going to hand over to Natalie who's going to walk you through an example of where RNAscope is being used.
13:35
Thanks, Brian.
13:37
So yes, so as Brian's mentioned sometimes you there isn't an antibody for the target that you're wanting to look at.
13:44
So and that's really where RNAscope can kind of come in and help you.
13:47
So what I'd like to do is just walk through a project that was undertaken by our services laboratory.
13:55
So this was a little while ago, so before Lunaphore joined the Biotechne family.
14:00
So the staining that I'm about to show you wasn't done on the COMET, but ultimately it could be now.
14:07
But this was a project that was done with a company called BluebirdBio.
14:12
And ultimately, what they wanted to do was to really look at the safety and efficacy of two of their CAR T potential therapies.
14:25
So what we did was a project and it's kind of split into sort of three main parts.
14:32
So the first part was actually to kind of look at the CAR targets themselves.
14:39
So we ran some staining looking at BCMA and ROR 1.
14:44
We then also went on and actually designed a probe to the UTR region of their CAR transcript.
14:50
So we were able to then detect their ROR CAR and their BCMA CAR in the preclinical samples, and we were able to duplex this with granzyme B.
15:03
So we were able to look where are the CARs going and are they actually being activated?
15:08
And then the third part of the project was to then kind of go one step further again, look at the CAR, look at the granzyme B and then also couple that with a protein for CD3.
15:18
So we could also understand then what's actually happening with the endogenous T cell population in the tumour microenvironment.
15:33
So this is a bit of a snapshot of the results.
15:38
So in the in the top row, we've got just the single plex RNAscope staining.
15:59
So this is just looking specifically for BCMA antigen, ROR1 antigen.
16:05
So in the tumour tissue for BCMA we can see lots of really nice expression and in the normal tissue negative – happy days, exactly what they wanted to see.
16:18
Unfortunately what happened with the ROR1 was we were seeing expression in the tumour samples.
16:23
We were also seeing expression in the normal tissues, and this is something that they hadn't picked up with their pre work that they've done just with IHC.
16:31
The antibody obviously wasn't sensitive enough.
16:35
So in normal lung, liver, and spleen, we were actually picking up low levels of ROR1 expression and then we moved down to looking at a duplex stain with the CAR targets themselves and the granzyme B target.
16:50
What we can see is in the tumour tissue, we've got the CAR targets coming up in red and the granzyme B in green, showing that the CARs were getting to the tumour exactly as we wanted, and they were being activated in the presence of the BCMA antigen.
17:04
Brilliant.
17:04
Again, exactly what we wanted.
17:07
In the normal tissue you can see the odd CAR has made it into a normal sample, but because there's no presence of the antigen, they haven't been activated.
17:17
In the ROR1, what we see is a slightly different story.
17:20
We're seeing some granzyme B positivity in tumour, but no CAR.
17:24
And unfortunately in the normal, we're seeing CAR has been activated.
17:30
And this actually correlated, they were seeing pulmonary toxicity in the animals.
17:33
So this correlated with what they'd actually seen in the animals.
17:36
And it's based on this data that they canned the ROR1 CAR.
17:42
And so they weren't going to take this forward, but they were going to go forward with the BCMA target.
17:48
And so this is just quickly to show the next stage of the project.
17:52
So again, we're looking at the CAR we've got granzyme B as an ISH marker, interferon gamma as ISH, and then the CD 3 as the protein.
18:02
So this is really kind of helping them see where's my CAR, being able to understand that's CAR, this is endogenous TCR T cell, and it's seeing what's actually going on within the tumour microenvironment.
18:16
OK.
18:17
And I think that's it from us.
18:20
Thank you.
