0:28
So thank you very much to the organisers, for inviting me to deliver this talk and for all of you to attending.
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I'm going to be presenting Hawk Biosystems, which is a biotechnology company based in the north of Spain.
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And originally we were a spin off from the Francis Crick Institute and the Cancer Research UK.
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Today I'm going to be talking about QF-Pro, which is our technology.
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I will explain the basics, some application research applications and its clinical value.
0:57
So at Hawk we want to bring researchers with the specific tools to discover protein functionality within tissue samples such as FFPE based in tissue samples.
1:10
And we have come along with our technology that doesn't look just at protein expression, but it looks at protein functionality because we believe that proteins make a difference when they act through interactions or through post-translational modifications.
1:25
So at the end of the day, QF Pro is combining these three circles and is bringing together spatial localization, interactomics and activation profiles.
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So explaining the basics of the technology.
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QF-Pro stands for quantifying functions in proteins and it is simplified and enhanced FRET-FLIM bio-imaging technology.
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FRET stands for Forster Resonance Energy Transfer that is coupled with Fluorescence Lifetime Imaging Microscopy.
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Basically it's a two-site immuno fluorescence assay where we have our two primary antibodies targeting in this case if we are looking at approaching protein interaction would be the two different proteins.
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Then we have our two secondary fragments that are conjugated to specific fluorophores.
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We have one fluorophore, the donor that is labelled with actually it's a green fluorophore, sorry.
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And then we have our acceptor fluorophore, which is a red fluorophore.
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Whenever these two are within 10 nanometres of distance, there is an energy transfer from the donor to the acceptor.
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And this is what we can quantify and what we call QF-Pro score.
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And if we can look at the representative images here, we label TIGIT with the green fluorophore and then its partner CD155 with the red dye.
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And if you look at the kind of pink cells, those are the regions where the two proteins are interacting.
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And of course, apart from these images, we can also provide a specific score that quantifies this interaction level.
2:59
So the main benefits that our technology is bringing is basically the high sensitivity that it has.
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FRET has been in the field for many years, but we had a problem with the autofluorescence of the tissue, but we overcame this problem by amplifying the signal of the acceptor fluorophore and we have a higher signal to noise ratio overcoming this limitation.
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Also since it is a two-site assay where we are using two different primary antibodies, we have this huge specificity because you will only expect to see an interaction when the two antibodies are targeting the very specific targets.
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Then we have a high dynamic range because due to the spectroscopic nature of the assay.
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And this is because we are not looking at the intensity of the fluorophores, we're not measuring intensity.
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What we measure is the lifetime of the fluorophore, which is an intrinsic property of the fluorophore.
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Then these quantitative values are very reproduced and reproducible due to the lifetime measurements.
4:04
Of course we can spatially map and localise all these events across the sample.
4:09
And since it is a two-site immunofluorescence assay, it is very easily integrated in any laboratory workflow.
4:17
So as a comparative diagram with other technologies, because FRET works at distances of one to 10 nanometres, we are looking at specific protein-protein interaction and not just proximity events.
4:30
And as I mentioned, due to the spectroscopic nature of the assay, we have a really high sensitivity and detection rates.
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We develop our end-to-end solution so that these technologies can be integrated in any laboratory.
4:48
So starting from our reading kits, which kind of stain FFPE tissue samples or cell lines, it contains everything that is necessary to do the staining except for the primary antibodies.
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So that way we leave the assay open to any target of interest.
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You can select your two primary antibodies, then you will have all the buffers, secondary reagents, multimedia, so everything that is necessary to run the whole process.
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Then whenever you have your samples ready, you're going to do the readout in our FLIM microscope.
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I don't know if you have ever seen a FLIM but they're huge microscopes.
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They take up a really big desk.
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They need to be in a dark room, AC cooling system.
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But we have overcome all these limitations and we integrated all these into a bench stock microscope that can be placed anywhere.
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You just have to lift the lid that is up there, put inside your in your slides and then you will just run the assay.
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And finally we have our software analytics that will guide you is also a very friendly user software that will guide you through the whole process of the acquisition of the samples.
5:53
And the output that we are delivering is as I mentioned a spatial image where you will get the interaction profiles of your proteins and then the QF-Pro score that would give you this interaction and how much these interactions are happening.
6:08
So we believe that QF-Pro is bringing in a whole new family of functional biomarkers because we are looking at all these type of events.
6:18
So from protein protein interaction to post translational modifications.
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We can also look at protein-DNA interaction and receptor heterodimerization.
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So we believe that coming from the fundamental research, we can move along to the translational to the drug development.
6:34
And finally, our final goal is to go into the clinical diagnostics, and I wanted us to also to show some application examples that we have performed in our laboratory.
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The first one, we wanted to look at the interaction level between E-Cadherin and Beta-Catenin, which is an intracellular interaction.
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To do so, we targeted the two proteins with specific primary antibodies.
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We conjugated them with our secondary reagents and performed our assay.
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This was performed in FFPE tissue samples of breast cancer patients.
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So as you can see in the patient representative image of patient number one, it has expression of Beta-Catenin in green, E-Cadherin in blue, however, we don't see any kind of interaction at all.
7:18
If we move to patient number 2 again, we see the expression levels of the two proteins and the interaction as in red pixels.
7:26
But a real strength relies on is our quantitative score.
7:30
Here you can see again that all the regions that we took for each patient have each independent score.
7:36
And it's a value that you will get from these experiments.
7:40
And if we were to overlay or merge these images, we would imply that they're interacting because there will be an overlay between beta-catenin and E-Cadherin.
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But actually they are not interacting.
7:52
So I we really believe this is our strength.
7:57
In another case, we look at the interaction between MHC2 and LAG3.
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Again, we label with our primary antibodies, secondary reagents, perform the assay.
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And again, we can say that in phase number 1 we can hardly see expression of MHC 2. We don't see many interactions.
8:15
And moving into phase 2 even though there's a lot of MHC 2 expression, there are only some regions where the two proteins are actually interacting.
8:27
And it's not only about looking at the interactions.
8:29
We can also inhibit some interactions.
8:32
So in this case, we performed this experiment in cell lines.
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We first look at the interaction between TIGIT and CD155, and then we treated the cell with a blocking antibody to disrupt its interaction.
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And what we could see is the cells had all these red pixels implying that they're interacting.
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And whenever we are de-blocking antibody, we lose this signal and again we have the QF Pro score.
8:59
This is an example of a post translational modification.
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So how do we look at these types of modifications?
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Basically what we do is target the whole protein with one primary antibody and then the specific residue that we want to be looking at with another one.
9:15
So in this case we wanted to look at a Akt/PKB and we tagged the 308 residue. To induce the activation state of Akt in these cell lines, we induce them with EGF at different time points and what we could see was a really nice time dose response.
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And again we have these nice images.
9:46
And a final example would be how to use this assay to identify which compound would block a specific phosphorylation state of another protein.
9:57
So we treat it with three different compounds at three different concentrations, and we could see again these those dose-response curves in these three examples.
10:08
So we developed QF-Pro to make it as versatile as possible.
10:12
And we want we wanted to bring as many kind of biomarkers to look at in the in a single sample.
10:20
So for now, what we can say is that if we take PD-1 or PD-L1 as an example, we can be looking at signal A that would be PD-1, then signal B: PD-L1, of course the interaction between those two.
10:32
And then if we were to look at T cell infiltration, we can also be looking at CD3 in the far right channel.
10:39
And of course, we can stain for that.
10:42
Right now, we are very excited because we are implementing our multiplexing capabilities and we can do sequential rounds of staining.
10:49
And for now, we can go up to three functional states and a total of nine biomarkers which are expression profiles.
10:58
This is an example of our multiplexing capabilities and in this case we did an immune checkpoint profile of an FFPE tissue sample of a patient.
11:09
In the first round we wanted to characterise the PD1, PD-L1 interaction.
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Then in our second round, we look at CTLA for CD80 and finally we look at LAG-3 MHC 2.
11:21
But what is more important is these quantitative data that we are getting here.
11:25
We believe that in the future this might help clinicians to decide which would be the best therapy for each specific patient.
11:34
So I have gone through some of our validated biomarkers.
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This is the list of the ones that we have disclosed in the laboratory.
11:43
We have many others.
11:44
We are happy to find many other new biomarkers.
11:47
And yeah, and finally, I've come to the part that I think is the most exciting, which is the clinical validation that QF-Pro has.
11:57
So we did this in the field of immuno oncology.
12:03
And as you are all aware, there's an unmet clinical need in immuno oncology because we're missing so many patients where only 12 to 25% of solid tumours are responding to immune checkpoint inhibitor therapies.
12:18
So effectively predicting which patients will respond to these therapies remains a challenge and we have tried to overcome this limitation.
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So what we did was we perform a retrospective clinical study.
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We did it in NSCLC.
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So it was a cohort of 188 patients.
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They were all treated with anti PD-1 PD-L1 therapies.
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And we look at the interaction level between PD-1 and PD-L1 with our QF pro assay.
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This was published in the Journal of Clinical Oncology in 2023.
12:55
So normally whenever a patient comes into clinic, they will get their biopsy done.
12:59
And for now pathologies do the PD-L1 TPS score by immunohistochemistry, which is the gold standard.
13:06
However, we know that the certification based on this analysis are not very good.
13:13
If you can see here the overall survival are not a don't have a significant value comparing PD-L1 high PD-L1 low and we thought OK, but the immunotherapy is targeting actually the interaction.
13:27
Why don't we look at the interaction to see if we could more efficiently stratify patients based on this?
13:33
And this is what we did with QF Pro.
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And strikingly what we could see is that those patients that had high level of PD-1 PD-L1 interaction did much better when treating them with immunotherapies, immuno checkpoint inhibitor therapies compared to those ones that have low interaction levels.
13:52
So QF Pro could predict patient response to immune checkpoint inhibitors much better than PD-L1 TPS.
13:59
And critically what we could do in this the clinical trial was to find our cut-off value.
14:05
So we knew that those patients that had 2.1% QF-Pro score are higher.
14:11
Those were those ones that had a high score and then there was underneath this number were the low ones.
14:20
And if we go into a little bit of more detail into these results and we compare the PD-L1 TPS score low or high and the QF-Pro score low or high, we could see that there are 22.5% of patients that are receiving immune checkpoint inhibitor therapies and are not responding to them.
14:42
So these patients are having all these adverse events associated to immunotherapy.
14:54
So it is very important for these patients to be treated with other type of therapies.
14:59
And on the other side of the coin, we have 24.5% of patients that would respond to immunotherapy and then they are being missed.
15:07
They are not receiving their correct therapy.
15:11
So as a take home message, we right now know that 47% of patients diagnosed with lung cancer are not being treated adequately and we're missing these two groups of patients.
15:23
So finally, we have proven that with QF-Pro, we could triple the immunotherapy checkpoint inhibitor therapies efficacy and potentially we could double the survival rates of these patients.
15:37
Now in an independent cohort of 67 patients, again in NSCLS, we performed the same experiment, but in this case, we also look at the interaction level between CD80 and CTLA-4.
15:51
Again, they were all treated with anti PD-1 PD-L1 therapies and what we could see is that those patients that had high level for both biomarkers, so for PD1 PD-L1 and CTLA4 CD80 had a very better survival course compared to those ones that had low levels for both immune checkpoints.
16:11
We look at the overall survival and we could see also this trend in the progression free survival.
16:16
So we believe this is also opening a potential discovery of novel biomarkers in the immuno oncology field.
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And of course it's not only about NSCLC.
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We believe we can translate this data to any other solid tumour.
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Actually we're trying to implement this in Melanoma, renal cell carcinoma, prostate cancer and so on.
16:41
And of course, we also believe that in the future patients will get a whole immune profile and depending on the status of the immuno checkpoints, they will receive their specific treatment.
16:52
And this is something that can be performed with our QF-Pro assay.
16:57
And just as a summary, it's not just about oncology.
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We can implement this into many other clinical domains or research domains, cardiovascular disease, neurodegenerative disease and so on.
17:12
Anything that can be targeted with two primary antibodies can be looked at with our assay.
17:17
We have developed our end-to-end solutions.
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So we have our reading kits, our microscope and the software.
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We also provide in house services.
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So in the case you want to send us your sample, we'll do the labelling, acquisition and the analysis and we'll give a report back.
17:34
And of course, we offer companion diagnostics to pharmaceutical companies.
17:41
So thank you very much for attending.
17:44
I'll be very happy to take any questions, or you can visit us our booth number 11. Thank you very much.