0:00
Well, thanks again to the organisers.
0:03
I think Oxford Global is really one of the best meetings.
0:06
I like the focused approach with what Oxford Global do.
0:11
And of course, they really invested in technology such as spatial and, you know, bringing in key opinion leaders for those and then clearly technologies such as afforded with what we have at NeoGenomics.
0:27
So it's a great opportunity for us to highlight what we have and the type of services that we can provide for you guys.
0:33
So one of the nice things about what I do in my job is that I get to do pet projects.
0:38
I oversee scientific affairs, which means I oversee a lot of the clinical trials, but I can also bring in, you know, relevant areas of science based on what I'm reading in the literature and put together projects for that.
0:50
And it serves as additional collateral for some of our capabilities, of course.
0:54
So the talk today, and it's quite a long title, unfortunately, spatial proteomic characterization of renal cell carcinomas identifies metabolic reprogramming of the tumour microenvironment associated with disease progression.
1:06
This is very new data.
1:08
In fact, I just got the data last week.
1:10
So I've spent most of the weekend actually pulling it together for this talk.
1:14
A lot of it is still in evolution.
1:17
We're going to have several posters at SITC and then there'll be ongoing work presented at ACR and hopefully ASCO next year as well.
1:26
So this is what we'll cover very briefly, what the what it is that we actually do with our pharma services at NeoGenomics.
1:32
Then I'll spend quite a bit of time discussing our whole tissue capabilities enabled with Paletrra, that is our branding name for the actual assay workflow.
1:42
But really in essence, it's enabled by the RareCyte Cytefinder.
1:45
And of course the team at RareCyte are here today as well.
1:49
We'll spend a little bit of time going through, you know, what makes us unique with this particular image analysis and whole slide capability.
1:58
But then I'll spend the rest of the talk really going taking a deep dive into that case study associated with renal cell carcinomas.
2:06
And what we've done is really taken different stages of those renal cell carcinomas.
2:11
That's the TNM staging of renal cell carcinomas.
2:14
So stages one through 4 and really kind of dived into, you know what makes those different stages unique as far as the tumour microenvironment, but you know, with a focus on metabolic programming.
2:26
So NeoGenomics, what it is that we do, we're actually three companies in one, to be quite honest with you.
2:31
I oversee scientific affairs within pharma services, that's highlighted at the bottom.
2:38
And so of course we're one of the leading providers for kind of clinical trial services overall.
2:43
So we can really traverse your projects really from preclinical stage through IND and then of course those clinical phases.
2:51
And I'll highlight several of the modalities that we currently support.
2:56
We have several sites within the US.
2:58
Of course, I primarily reside in the US, but we also have a UK footprint within Cambridge, UK.
3:05
Now we harmonise with actually our oncology data solutions group.
3:10
You can think about this similar to real world data.
3:14
We are one of the largest testing labs for PD-L1 testing.
3:18
So we have access to all that images and so that lends itself to quite a lot of success for our data oncology service team.
3:26
And of course we've got several publications on plate.
3:28
Of course, the largest part of the business is clinical and clinical services.
3:32
So this would be our diagnostic side of things where a lot of those conversations are happening with the oncologists.
3:38
So of course those approved medications and those approved biomarkers, specifically c-MET testing, EGFR-1, you know, all those biomarkers that you know well and love within literature and that's certainly afforded by our clinical team.
3:53
So really in 2025, we can think a little bit more strategically about some of the testing modalities as well as the therapeutic solutions.
4:03
And we've kind of, you know, formed a lot of marketing around offering solutions for cell therapies, although that's been a challenging environment of late.
4:13
And but there's some I think really good opportunity based on the car team meeting that was just had in Boston.
4:19
So I think there's some, I think they recognise some of the challenges with manufacturing and some of the testing for that.
4:26
One of the biggest areas of research and certainly from a clinical trial perspective now is affording different solutions for ADCs.
4:35
There's a lot of novel ADCs on the market right now.
4:38
There's 15 approved, there's over 200 in clinical trials.
4:42
So by far and away ADCs is what we get asked a lot about.
4:46
And so it's been able to have different modalities that can support those trials and also molecular target therapies.
4:53
So this in essence now has been able to target the undruggable and now of course there are several and novel therapies for that.
5:01
Now we come into it because we have what's called comprehensive lab services that can certainly support your trial needs.
5:08
Specifically, we have one of the largest team of pathologists on site primarily out of our California site to support your IHC assays, but we can also support FISH, cytogenetics.
5:21
Our flow based assays can be out of both California and Cambridge, UK. Genomics, that's out of several sites.
5:27
Actually it's the UK, it's our RTP site within North Carolina as well as our Houston site.
5:35
Now what we're going to speak about today is you know what it is we have under the umbrella of both pathology and spatial analysis.
5:44
So there's several platforms that we currently support at NeoGenomics and what dictates one over the other is really heavily dependent on the biological question that you wish to address and the type of exploratory assay you wish to use, of course.
6:01
So we support the nano string or now the Bruker Spatial Biology, GeoMx Digital Spatial Profiler.
6:07
Many of you are probably aware of it.
6:09
Certainly go up and see the guys upstairs.
6:12
I used to work at Nanostring for many years.
6:14
I'm very well acquainted with that specific platform.
6:17
But certainly for a whole transcriptome or even the cancer transcriptome, and now they've got the proteome, that's certainly, you know, you get a whole lot of information and a whole lot of biomarkers.
6:28
But one has to start thinking about triaging those biomarkers now into a handful of meaningful biomarkers that one can move forward with to address your biology.
6:38
It is a great tool from an exploratory perspective and kind of discovering perhaps Nova markers, but now we have to triage that.
6:45
And so I would recommend our Paletrra, which I'll get into, but we also support the Akoya phenol imager.
6:52
And so again, you can now start asking you know the questions about proof of concept and using that more meaningful and handful of markers now as part of your clinical trial.
7:02
And then we also support CDX development.
7:04
Now of course I'm well aware that there's not a CDX for spatial and that will probably be years in the making.
7:09
In fact, we have not moved beyond the immuno score for spatial, but certainly we can entertain that with a lot of our off the shelf IHC menu and certainly we have a lot of experience with that as well.
7:21
And what I cover there is that this is all enabled really with our team of pathologists, our team of scientists, including myself and a wide team of bioinformaticians.
7:33
And so to dive on into Paletrra, really you can think of it like chevrons like this all the way from assay development and verification through integrated visualisation and analysis.
7:44
But it's not linear.
7:45
I mean, at the end of the day, we do so much QC and quality control, not just of the tissue, but of every step of the way.
7:53
And again, we involve the pathologist, we involve the data, we involve the scientists as well.
7:59
And then we move into our multiplexing and image acquisition.
8:02
So this is the cyclic immunofluorescence using Cy3, Cy5 fluorophores, we stain, we can do up to 60 markers.
8:09
We have a proprietary dye and activation step.
8:12
We have now transitioned from what used to be region of interest analysis to now whole slide imaging.
8:17
And that really again is enabled by the use of the Cytefinder from the guys at RareCyte.
8:22
And so we've just transitioned all our previous panels now into our whole slide imaging panels.
8:28
And now we're expanding our menu as well for more validated markers.
8:32
Right now we have about 300 validated markers.
8:34
You can create your own custom panel, or you can use one of our verified off the shelf panels.
8:40
We've also developed our own image analysis tool for this and our own AI algorithm for this.
8:47
And I'll go into aspects of that, but we just launched a white paper for Paletrra a couple of weeks ago.
8:54
So if anybody's interested, it goes into a little bit more details than the time afforded with this presentation.
8:59
So certainly reach out to us or come and see us upstairs.
9:03
So this is an example of the type of images that you're going to get from us.
9:07
And again, we give you a comprehensive report depending on the biological question that you're trying to address.
9:12
So we can do up to 60 markers in a single tissue section.
9:15
This is an example of whole tissue imaging of colorectal cancer.
9:20
And here you can home in on certain B cell, T cell markers.
9:24
And of course, again, those panels you can create yourself with your markers of interest or use one of our off the shelves.
9:31
So when we think about it, and again, there's a lot of nuance, with that goes into our AI as well as image analysis.
9:37
But you know, when you think about advanced spatial analytics, you want to be able to, we can put together a lot of these specific reports for you.
9:46
It's not just hey, we're going to do coexpressions, we're going to do intensities.
9:50
This is very prescription for your specific needs.
9:53
So again, if you have a question you wish to address, there'll be a lot of back and forth and consultation with our team, including myself.
10:00
And again, some of that slide level outputs.
10:02
Of course you want the densities, you want the percent positivity, H scores, but just some of the more nuanced readouts such as proximity analysis.
10:13
Again, it's knowing who your neighbours are, that neighbourhood composition is extremely important.
10:19
It's the coexpressions as well.
10:21
And I'll allude to that as we get to the case study.
10:25
So again, Paletrra we actually create, we don't do actual H&Es for the most part.
10:30
We create a virtual H&E and that's, and this is well established in the field Now for spatial, it's a pseudo blend of both DAPI and the autofluorescence channel.
10:38
And of course our pathologists will obviously select all the tumour relevant regions of that tissue and home in as well on any specifics associated with the quality of that tissue.
10:49
But again, you go from the virtual H&E to your actual multiplexing.
10:54
So I'm going to get into a specific case study now.
10:58
If anybody studied biochemistry back in the 80s and early 90s like I did and read Stryer from cover to cover, this was a popular figure that was in Stryer back in the day.
11:11
And here we are 35 plus years later and now the Krebs cycle has come back in vogue in a big way, and it will come back in an even bigger way next year.
11:22
I fully predict that metabolism is going to be intimately related in a lot of cancers and certainly metabolic phenotypes.
11:29
You'll see a lot of that, especially now with all the GLPs.
11:33
And now they're going to be used within some of that cancer testing.
11:36
But renal cell carcinoma is really described as a metabolic disease actually.
11:40
And to be honest with you, some of that cellular metabolism may actually play quite a significant role in some of that immune responses and maybe some of that immune response or lack thereof that you see with the overall prognosis of renal cell carcinoma.
11:54
So it really does affect the ability of T cells to maybe function within the tumour microenvironment.
12:01
And so it's really this aspect that we wanted to fundamentally address with our specific tumour type.
12:07
And so here's our goal.
12:08
And again, I'll let you read that, but we use a couple of different methodologies.
12:12
Obviously, we included the spatial Paletrra, again to look at specific immune signalling and some of the markers from that.
12:19
But we also included the Nanostring or rather Broker Spatial biology metabolic pathways panel.
12:24
It's a great panel to actually address some of those specific metabolic signalling pathways that were just highlighted within aspects of that TCA cycle.
12:34
So again, this is the overall methodology.
12:37
Again, we had to produce sequential slides.
12:39
So one of the slides was dedicated for our Paletrra staining and again with imaging using the RareCyte Cytefinder.
12:46
And then sequential neighbouring slide was used for the Nanostring analysis.
12:50
And you can see our biomarkers that we use for this specific panel on the right hand side.
12:55
And CA9 was specifically used as that tumour marker for renal cell carcinoma cause PanCK is not the obvious choice for that.
13:04
Just very quickly, because this is very new data.
13:08
We did some differential expression analysis using the Nanostring metabolic panel.
13:14
We saw huge differences that you can see on the left hand side, huge differences between stage 1 and 2.
13:21
But those differences were quite tempered in stages 3 and 4.
13:25
So something's clearly going on.
13:26
You get this burst of immune response and then you lack that immune response.
13:30
So again, and we also saw very high levels of antigen presentation cells in stages 4 and stages 3.
13:38
But again, there's a bit of a paradox here because whilst we're seeing all that increase in antigen presentation, what we're probably seeing is some immune evasion as well.
13:48
And that's exactly what we really wanted to look into with our spatial study.
13:52
Again, I'm just going to go through the biomarkers of the specific coexpressions that we actually addressed and what that phenotype alludes to.
13:59
And so this is an example, it kind of came out a bit weird colour wise here, but I hope you can see some of the profound differences that we saw between stages 1, 2, 3 and 4.
14:07
And of course, you start saying infiltrations and T cells and immune cells as you get to stage two and three, which is almost lacking now by the time you get to stage 4, by stage 4, and it's probably no surprise, you see that increase in overall tumour and vasculature.
14:24
In fact, it really is quite a vascular tumour to be quite honest with you.
14:27
And then obviously has the degree of metastasis that is typically associated with stage 4 tumours.
14:33
So again, let's home in on this.
14:35
So again, I'm not going to pour through every box plot.
14:37
Hopefully you can see some of the changes between in stage 1, 2, 3 and 4.
14:41
It's colour coded.
14:42
Stage 1 is blue, and stage 4 is red.
14:45
But if you look at the right to, excuse me, the left hand side, you can see that really infiltration in those CD 31 positive cells indicative of that increased vasculature associated with Stage 4.
14:58
You can see also some of the coexpressions that we actually saw specifically here.
15:04
I'll draw your attention to some of the coexpressions.
15:06
You've got an increase in, for example, T cells and cytotoxic T cells, and that's great.
15:12
And you've got an increase in CD4 cells, but unfortunately you've got these inhibitory ligands.
15:18
So now you've got an increase in later stages with expression, for example, of FOXP3.
15:23
And you've also got expression of LAG3, indicative of immune suppression.
15:27
As you go into stage 2 and into stage 3, and that's exactly what we see here.
15:34
And this cluster map actually mirrors, if you remember the genomic readout from the nano string panel and you saw this burst of information between stages one and two.
15:44
That's exactly what we see here from the spatial side of things, again looking at a small cohort and that those coexpressions are actually tempered again between stages 1 and 3 and 1 and 4.
15:57
But again, this really this burst of immune activity that we see between stages 1 and 2.
16:06
So let's look at this and from a spatial perspective, again, this is our virtual H&E.
16:10
This is a stage 3 male presentation.
16:16
And now we start homing in on specific phenotypes.
16:18
So here what we're looking at again is looking at T regs.
16:21
So we've got FOXP3, CD3, CD4, CD8, and CA9 as our tumour marker and in magenta hope you can see that's your cytotoxic T cells and you've got T helper cells.
16:34
All looks great, but we also have an infiltration of T regs.
16:39
Now looking at lag three expression again, LAG3 in as coexpressed as a rule marker for immune suppression.
16:47
That's exactly what we're seeing here.
16:50
This is looking at coexpression with PD1 and again PD1 inhibitory ligand.
16:55
So again, I think you can start to see that we're having very, even though you've got that immune response, it's an inhibitory immune response.
17:03
Again, you're what you're seeing is actually immune suppression.
17:07
And again, this is another example with PD1, and this is PD1 in concert with cytotoxic T cells.
17:15
And this is LAG3 again being expressed on cytotoxic T cells.
17:21
And again, this is LAG3 and in combination with PD1, again on specific T cells.
17:27
So it's a very nice image with different markers, but again, I think it tells a very nice story of suppression.
17:34
And again, if we compare that now with what we're seeing in stage 4, this is a stage 4 male.
17:38
Again, this is our virtual H&E.
17:41
Now you can see that abundance of vasculature as demonstrated by the increase in CD31 positive cells.
17:51
CD31 is in yellow.
17:52
That's exactly what we see throughout this entire tumour of stage fours.
17:56
And we also start seeing an increase in the M2 macrophages.
18:00
So we're using a couple of markers for that in this case as CD206 and CD68.
18:07
And that's exactly what we see here is an increase.
18:10
Again, you've got some T cells there.
18:11
It's very not as many as you actually see in stages 2 and 3.
18:16
Again, you've got a very suppressed phenotype and now we start seeing those increase in macrophages.
18:21
So again if we go back and again here, we're also seeing an increase in that exhausted phenotype as demonstrated by the increase in LAG3 coexpressed cytotoxic T cells.
18:33
So we go back to our representative images just to kind of really conclude what we're actually seeing in these later stages, especially stages 2 and 3 is an immunosuppressive tumour microenvironment and it's really demonstrated by coexpression with these inhibitory ligands specifically with T regs, PD1, but also LAG3.
18:53
And what we're seeing in stage 4 is that increased vasculature as well as associated M2 macrophages.
18:59
So of course those tumours at this point are not going to respond to a whole lot of stuff unless you have potentially anti VEGF type therapeutics.
19:09
But there's certainly room for intervention from a therapeutic perspective in stages 1 and 2.
19:17
So just to conclude again to summarise, really our Paletrra is our whole slide imaging again enabled using the RareCyte Cytefinder again to really provide some of those deeper insights into the tumour microenvironment.
19:33
Our team is really wholly focused on robustness of the assay.
19:38
Again, it's the quality control that is built in all the way from assay development and your tissue all the way through to the specific analytics.
19:47
And again, this is enabled really by the pathology and scientific expertise.
19:51
Now we have both off the shelf and custom abilities and it's really about taking that biomarker forward into your clinical trial and perhaps even developing that specific biomarker for a potential companion diagnostic.
20:05
Just a few case studies from recent publications and you can see very nicely how spatial was integrated into other assays.
20:14
I mean this demonstrates quite nicely.
20:16
Using spatial exactly why the tumour regressed, but this specific autologous new antigen specific T cell therapy from biotech that was published in Nature Medicine earlier this year.
20:29
GSK also used it to show very nicely why you get tumour regression and again, looking at that specific paper at Natural Killer Cell Infiltration.
20:41
And then Infinity also just recently published within their MARIO 3 trial, again, the use of spatial and you know, they had quite a broad panel that for some of their specific trial needs.
20:53
And so I'll just highlight our off the shelf, but certainly I have a brochure upstairs if anybody's interested.
20:58
And certainly I'll give you an idea of some of the markers that we have specifically validated, but we have over 300 markers for that too.
21:08
And thank you for your time and attention.
