Morphology Driven High-Plex Spatial Analysis of Tissue Microenvironments

Hello, everybody, and welcome to today's live broadcast, Morphology-Driven High-Plex Spatial Analysis of Tissue Microenvironments, presented by Dr. Mathias Holpert and Tracy DeGeer. I'm Christy Jewell of LabRoots, and I will be your moderator for today's event. Today's educational web seminar is brought to you by LabRoots and sponsored by Leica Biosystems and NanoString. For more information on our sponsors, please visit leicabiosystems.com and nanostring.com. Now let's get started. I would like to remind everyone that today's event is interactive. We encourage you to participate by submitting as many questions as you want at any time you want during the presentation. To do so, simply type them in the ask a question box and click send. We will answer as many questions as we have time for at the end of the presentation. If you have trouble seeing or hearing the presentation, click on the Support tab found at the top right of the presentation window or report your problem by using the Ask a Question box located on the far left of your screen. This presentation is educational and thus offers continuing education credits. Please click on the Continuing Education Credits tab located at the top right of the presentation window and follow the process to obtain your credits. I would now like to introduce today's presenters, Dr. Mathias Holpert, Senior Product Application Scientist, NanoString, and Traci DeGeer, Director, Advanced Staining Innovation, Leica Biosystems. For complete biographies on our speakers, please visit the Biography tab at the top of your screen. Welcome, Dr. Holpert. Welcome, Tracy. Dr. Holpert, you may now kick off our presentation.

Thanks a lot for the introduction. Let me first introduce our company to you just briefly. NanoString was founded in 2003 as headquarters in Seattle and focuses on getting as much information out of as little tissue as possible. In addition to research products, we have two platforms now. We also do have an improved diagnostic test for breast cancer. are running on our encounter platform, the Prosigna test. NanoString has a long history of multiplex gene expression assays. And in this paper by Merck, they performed a gene expression analysis of FFPE samples with a goal to identify a signature that can predict response to an entire PD-1 blockade. They identified an 18 gene signature that they call the GEP, but which we refer to as the tumor inflammation signature or the TIS signature. And in the graph at the bottom of this slide, you can see a comparison of progression-free survival on the y-axis and the TIS score on the x-axis. Patients with non-inflamed tumors on the left of this graph rarely respond to the PD-1 blockade treatment of the study, and almost all of them, or almost all of the responders, have inflamed tumors. But that said, if you look at the quadrant at the lower right of that graph, there are still many patients with inflamed tumors that do not respond at all.

We already know several parameters that can predict for response to a certain treatment, but to be able to increase this prediction, we still need to fill the funnel, and we need to find more candidate biomarkers. The challenge with heterogeneous tissue is that the biggest portion of it is usually not relevant to the disease and study and will simply dilute the signal that might then reveal a difference in expression levels between two patient groups. And if you focus your analysis on, let's say, the immune microenvironment in immuno-oncology research, you will reveal markers that may predict a therapeutic response, but that would otherwise be lost when you study the whole tissue at once. The spatial context is crucial for biomarker discovery, which is also reflected in the development of the Immunoscore, part of which is determined by the cell type, the cell density, and the location of the immune cells. With the location, the spatial context comes into play. The current paradigm forces a trade-off. If you want to run high Plex gene expression analysis or protein expression analysis, you lose the spatial information. But on the other hand, if you do imaging analysis, that is usually done in a low Plex fashion and has rather poor quantification.

Given the cellular complexity and the ever-expanding combinations of therapeutic strategies, there is a critical need to attain more biological information from limiting amounts of clinical samples. And one researcher with exactly this problem was one of our earliest collaborators, Dr. Aubrey Thompson from the Mayo Clinic in Florida. He did receive two slides per patient out of the FinXX trial and triple-negative breast cancer, and he wants to find new biomarkers that predict which patients are more likely to benefit from capecitabine adjuvant treatment. And out of those two slides he had, he decided to use one of these precious slides per patient on running a bulk gene expression analysis with the breast cancer B360 panel from NanoString and then use the remaining slide per patient for a high plex spatial protein analysis. The breast cancer 360 panel studies 770 genes, but with those 770 genes, it also includes a lot of gene signatures, like the tumor inflammation signature, but also a lot of other gene signatures that are analyzed at the same time together with these single genes.

On the left of this slide, you see the clustering of the expression of what he got out of his study using the BC360 signatures and across the samples, showing distinct clusters across all those annotated signatures. And when you look specifically for gene expression changes, which is shown on the right on this slide, between patients with longer survival, left in this graph on the right, and shorter survival on the right in this graph, a strong immune signature is revealed in the capecitabine cohort that is predictive of longer survival.

These immune signatures suggest a deeper interrogation into the immune microenvironment may reveal additional candidates. To look into the immune microenvironment, to see immune cells that associate with response, the GeoMx platform was used to separate the tumor microenvironment into a CD45 and a CD68-enriched region, physically separating it from the tumor compartment. spatial profiling of over 30 proteins reveals significant heterogeneity that can then be leveraged to reveal new candidates. On the left, you see CD45 enriched stromal, and on the right, you see the CD68 enriched stromal. And what you can see is that they do look different, meaning that you have two different fractions in front of you. And that was a good result from the start. The preliminary analysis of the CD68-enriched stroma revealed increased expression of IDO1 and PD-L2, among other markers that are associated with a positive response, while increased expression of the stromal protein fibronectin was associated with poor prognosis, on the very left of this graph. The bulk gene expression analysis also revealed an association of increased PD-L2 expression with longer or prolonged survival, which is a good proof of concept, so the same result, basically, as a spatial study. Without the spatial context, the even more relevant marker, IDL1, would have been lost, so wouldn't have been revealed, because it's only relevant in the CD68-enriched regions.

How does this system work? The GeoMx Digital Spatial Analyzer can detect protein and RNA, and to do so, it uses either antibodies linked to a small DNA barcode or ISH probes linked to a DNA barcode that then reveals the identity of the probe it is linked to. In both cases, either protein or RNA, the linker is cleavable by ultraviolet light. In the case of protein detection, if you stain an FFPE tissue slide, there's a larger panel of these barcoded antibodies and then shine UV light on only a small area of the tissue, all barcodes will be cleaved off in that area and can then be picked up to quantify the amount of barcodes or the amount of antibodies that are bound to this specific part of the tissue. Using standard IHC methodologies, tissue sections are stained with a mixture of fluorescently labeled on the top. And what you see on the bottom is the DNA labeled of bar-coded antibodies. So simply mix them and then do very similar to IHC staining with them. The presently labeled antibodies are used to reveal the morphology of the tissue that can then be used to identify regions of interest to quantify the larger panel of bar-coded antibodies that are bound in each of these regions of interest. The bar-coded antibodies are simply invisible, and the presently labeled antibodies are the ones that you see on the slide to select the regions you're interested in.

This slide shows you the workflow that is applied in a typical genomics assay. The slide preparation protocol can be automated using the Leica BOND RX platform to minimize the steps needed to be done manually in the lab. After the slide prep and staining of the slides in a fashion very similar to normal IHC protocols, the slides are then inserted into the genomics platform, which can analyze four slides in parallel. The first thing the instrument does is that it generates a 20x high-resolution fluorescent scan of the slide using the fluorescent morphology markers that have been applied. Directly on the scan, so on your screen, you can then draw your regions of interest, and once this is done, the instrument will shine you rely on the first region of interest, or ROI, and collect the cleaved of barcodes from this particular region of the tissue using a microprint, and deposit those barcodes in a microwell plate within the instrument. And then the stage moves to the next ROI, shines UV light on it, flips up the barcodes, and deposits them in the next one of the microwell plate. And this process is repeated until all the barcodes from all ROIs have been collected and deposited in the collection plate. And after this is finished, the barcodes in each well will be quantified using NanoStrings encounter system. The counts are then transferred back into the GeoMx system, which then links the counts to the ROI they have been collected from and allows complex data analysis. That's a full software solution that is integrated into the system. As you can see in the graph on the right, the automated slide PEP workflow using the Leica BOND RX platform is highly consistent with the manual assay, and it reduces hands-on time by about four-fold, and at the same time improves precision and consistency during the sample PEP stage.

But how can we make sure that UV light only shines on the selected areas on the tissue? I will use two digital micromirror devices in the GeoMx system that consists of millions of tiny mirrors, and each of these can be adjusted or will be adjusted automatically to ensure the light only shines on the tissue where you selected your reasons of interest. And in addition to just drawing circles to predict these areas, we can also make use of an algorithm that can create a mask to shine light depending on the fluorescent staining on your tissue. And like you see in this example in the middle, a mask can be created that adjusts to your sample to shine light on only where the yellow fluorescence is, and therefore only the barcodes from, for example, your tumor area will be cleaved off, while in the second step, we can create another mask that then will shine light on the remaining cells in the ROI to represent the expression in the tumor microenvironment. And each sample will then end up in a separate well of the collection plate, physically separating them from each other. It can easily separate tumors from tumor microenvironment, for example. The reasons of interest, or ROI selection, is what makes the DSP technology powerful and versatile. You can draw either geometric shapes of your choice on the tissue, or you can use the built-in software algorithms, which I just showed you in the previous slide, to separate tissue by different segmentations. Or you can also select rare cell types, which are interspersed throughout your ROI, or which is not yet included in the software, you can do contour fields or graded patterns. This slide shows you a profile of different geometric ROIs that have been selected based on staining with various fluorescent morphology markers. And without going into any detail, on the heat map on the lower left, you see that FE3 ROIs selected from a similar area just based on a fluorescent morphology marker. This tissue shows similar pattern on the heat map while being completely different from ROIs taken from other areas of the tissue based on other fluorescent morphology markers. That's a proof of principle.

To get the most out of your assay, we offer fully annotated panels for both protein and RNA assays. To allow maximum flexibility, we did design the antibody panels in a modular way, allowing us to choose and pick modules to add to a core set of reagents. We offer about a 50-plex antibody assay for immuno-oncology-related questions and about 30-plex antibody assay for neuroscience with modules for other Parkinson's or Alzheimer's research. The encounter-based RNA assay on the top right features a list of 84 genes around immuno-oncology research, and all our panels, protein and RNA, allow the addition of custom markers that can then be added to the existing content. And soon to come on the lower right on this slide, is a larger panel of next generation sequencing readout that will allow the profiling of about 1,500 RNA targets.

The GeoMx DSP provides an integrated environment, so it allows a seamless flow through the experimental workflow. From scanning a slide and selecting the segments of interest on the GeoMx system, and coordinating with the encounter to count and profile each segment to the QC and analyzing the data. As you can see on the top right on the screen, the imaging part is coming from the GeoMx system, the counts are coming from the encounter system, and then they're integrated into each other to give you the best out of your analysis. This slide shows the workflow of measuring high-plex proteins or RNA on the genomic system. If quantification then done on the encounter system or soon to be released, next-generation sequencing. A next-generation sequencing readout allows for theoretically unlimited plexing. Here you can see early data generated from three distinct ROIs on the same tissue. Compared to a bulk NGS assay profile on the left, you can see that each of these ROIs does generate a distinct gene expression profile if you look closely at the slide on the right. The first larger NSA for next-generation sequencing readout that we are going to launch early next year is based on three panels that we currently offer for our ENCOUNTER platform, choosing about 500 genes each out of our PAN cancer pathways, immune profiling, and IO-360 panels. And this allows us to spatially study the biology of tumor, immune, and microenvironment with a highly annotated assay.

The representation of data of 1500-1600 genes generated by this assay could be represented by such a Reactome map, as you can see here. Each of these little trees that you see represents a major pathway to allow an easy visualization of what is happening in the tissue. In this example, you can see two invasive margins on the bottom being analyzed, and while the invasive margin on the right shows all blue, meaning that low, that the expression is low. The invasive margin on the left has a much brighter pattern, which means that we can find a much higher expression level there. Or, in other words, the invasive margin on the right is inactive, while the invasive margin on the left is active. Regardless of how it's implemented, the cloud architecture of the GeoMx system allows many users to interact with the system at the same time. While only one user can actively control the instrument physically in the lab, many users can be aligning images, selecting regions of interest to profile, or analyzing their data simultaneously so they can log in from remote from their desk, don't have to be physically standing in front of the instrument to do so. To summarize, the GeoMx system has numerous advantages. It can analyze multiple analytes on the same tissue slice in a single pass with high multiplexing capabilities. It can run spatial high plex analysis on both protein and RNA. The counts are quantitative and can be analyzed in the integrated full software package that comes with the instrument. The resolution is very high, meaning that the digital micromirrors can shine light on a specific about one square micrometer region, allowing us to pick single cells from our eyes. And as we are only touching the tissue by light, UV light, the whole process is non-destructive, so your precious tissue slice can be used for other analysis afterwards. It's not destroyed. And the throughput is high enough to run the system in a chemical environment. this. I'm at the end of my presentation. I'm happy to take questions later, but now I'd like to pass on the presentation to Traci DeGeer. Thank you.

Thank you very much, Mathias, for that kind introduction. And my name is Traci DeGeer, and I am the Director of Innovation for Leica Biosystems. And with that, I get to work with the BOND RX instrument, which is the instrument that NanoString used to develop their assay on. We're going to talk a little bit about how an instrument like the BOND RX can be used to do routine research or translational research, or if you're a partner like NanoString, can be used to do all the wonderful things that NanoString did. Let's go ahead and get started.

The BOND RX instrument is built around freedom to discover. And when you consider freedom to discover, there are three things that we talk about under freedom to discover. It's explored your ideas, which as researchers, that's something everyone wants to do, is to be able to explore the way that we envision research goes. Any idea that we have in our head, we want to be able get out there for the world. Accelerate your testing program so to be able to do things in a timely fashion. If you're someone like NanoString or another small biotech company, you want to be able to commercialize the things that you discover so that you can share those with the world. That's the three pillars that the BOND RX stands on, is to explore your ideas, accelerate your testing program, and hopefully commercialize what you had in your head that you wanted to share with the world.

Let's start by exploring your ideas and talk a little bit about what that looks like if you're a researcher. When you think about exploring your ideas, I come out of the research lab and one of the things that is the most fun about being a researcher is to be able to take something that you have in your head and get it out there to either publish or to show to other people. But one of the things that can frustrate you as a researcher is that inability to get it out of your head and get it where you want it, especially if you're trying to build, to build something on a piece of automation and you can't get it to do what you want it to do. One of the things that the instrument is, is very, very flexible. It lets you run third party assays. Things like the NanoString assay. You get to use the same flexible software that NanoString, and other partners use. You also have a lot of things that Leica provides as well. There's detection, there's open detection containers. All of those provide flexibility to the system so that researchers themselves can try to get what's in their head out onto a piece of automation for consistency's sake. Because if you want to publish it, then you want it to look the same again so that someone can reproduce what you did. And that is sort of the hallmark of research. There are lots of things in the instrument that you can do. You can do circulating tumor cells, you can do mRNA, you can do microRNAs. The instrument has a lot of capabilities. Then you have the capabilities to sort of shape your own research a little bit. So that's exploring your ideas. The technology has been around for a long time.

The BOND RX has a long history. It was first introduced in 2011. And as the instrument has grown, based off what we've heard from the customers, we've added additional flexibility year over year. to sort of shape that instrument into what researchers told us they wanted it to be. And we've worked with our partners to add additional things so that we can keep up with the times and allow researchers to keep innovating with us. There are a lot of possibilities for what you can do. You can multiplex, you can do probe work, you can do fluorescence. It's kind of working with your imagination a little bit, and then working with the technical support teams, and then working with partners like NanoString that give you the latest and greatest in technology.

Now, there are a lot of customization options that are available on the instrument. You can do pre-staining customization, you can do antigen retrieval customization, staining customization. And as you look at the procedures that were shown back to PIAS, you saw some of the work that they do to customize things to fit the procedures that they need, and they continue to work with us to add to that customization in order to make their procedure the best that it can be. You can also customize within the procedure. If you needed a longer dewax or needed to change something, you can do those pieces as well. You can customize your antigen retrieval. You can change incubation times and temperatures. So those are all flexibility features that were added to the instrument to give researchers in the laboratory more flexibility, but to also give our partners flexibility to bring new assays to you. Now, when you look at other things that are available in exploring your ideas, you can do any marker you want to on there. If you wanted to bring in third-party antibodies, you can do that. If you want to use antibodies from the Leica portfolio, you can do that. If you want to make an antibody of your own, you can do that. You can create your own detection systems. You can use the same type of detection that our partners use when they use the open detection. to create something that works for you.

And then there's a new feature in the latest version of software that gives you the ability to select your dispense type. That used to be a feature that you had to have a technical support person come in and adjust for you. It's available right in the software now so that you don't have to wait on us to come to you. You can make those adjustments on your own now. But the technical support people are happy to guide you if you have questions. And then you have something called the temperature toolbox. Now the temperature toolbox has been around for quite some time. It lets you do selections of temperatures within the staining protocol. But not everybody had the temperature toolbox installed on their instrument. It's now a regular part of the procedure so that you can choose the temperatures that you want things to incubate at. And that makes that flexibility all that much better.

Now, the second pillar that we talked about in the beginning was accelerate your test program. And speed is not something you usually associate with the research laboratory because unless you're a high throughput research laboratory, we don't rely as much on speed. At least I know the research lab that I came out of didn't. We weren't as pushed for speed as a hospital laboratory who had clinical patients going through. But where speed is important for research laboratories is if you take an assay that takes days and days to run and you can compress that time. If you look at something like the NanoString assay, that you're doing a lot of hand steps, if you do it manually, and then you have an overnight incubation, and then you get to go on to the GeoMx GSP, that is a lot of hand time that you have to dedicate someone to be with your slides. But if you can take some of that hand time out and dedicate that to an instrument, that frees up that person to go on and do other important tasks in the laboratory, or to do other research, or to do analysis, or things that are very important to that laboratory that may have to be delayed somewhere because you've got them doing other tasks.

There is speed in the laboratory for research. It's just not looked at the same way as what you would look at it if you were a clinical laboratory. The instrument does give you that speed factor. in the fact that it can take tasks that would normally have to be done manually and move those somewhere else in some of these longer assays that we do as researchers. There's also efficiency in that. Because if you're better allocating your staff to do things more efficiently, then you can get your analysis done quicker. You can get your papers published a little easier. You can get all those things that are important to the running of a research laboratory and the longevity of the research laboratory and recognition sometimes of your laboratory. The instrument itself helps you be efficient. It's got the three drawers that each work like an independent instrument. If you have more than one team that is using the instrument, then the teams can share the instrument a little easier. because they don't necessarily all have to be there at the same time. It's easy to remove and add reagents. It's easy to start slides if they are not all using the same trace. You've got the onboard bulk reagents that you can see from across the room. When they need attention, the backlit, the BOND RX, it helps you gauge when things need to be added and removed for bulk fluids so that you don't run your bulk fluids out.

And then the instrument itself is not a huge instrument and has a reasonable footprint that you can slide into place. One of the things that happened with the latest update of the software was a little bit more friendly look and feel to the front. I did not start out on this instrument. I have run several different types of instruments in my research life, but I like the look and feel of it. It was a very intuitive look and feel. It's a very easy instrument to learn as a researcher, which is always good because you've got a million things going on in your head at the same time. You can see the bulk fluids on the instrument. You can see the drawers. You can see where all your reagents are in the trays. I like that because I don't want to have to spend a lot of time looking for things. And that made things very easy for me. And when you're doing development work like NanoString did, it lets them help, lets them keep up with things as they were walking by visually. So that's a big plus. If you're a researcher, it's also a big plus if you're someone who is a partner who is doing development work.

These are the bottles we were just talking about that are backlit. This was a new feature when the BOND RX 6.0 came out. It was developed by a group called Backburner out of Melbourne. They come up with things that aggravate customers and then ways to solve those. This was something that had aggravated people was that they had trouble telling when their fluids, because all the fluids are clear, were running low. Someone down there came up with the idea of putting lights behind them and making them more visible and then changing the configuration of some of the bottles. That has been something that was internal innovation for people, but it was based off customers and researchers said it irritated them. Something that's important to researchers, at least I know it was important to me, is consistency in results. Because if you're going to publish, you must be able to get the same result repeatedly. For groups like NanoString who are going to commercialize, you must have consistency. You can't commercialize a product that doesn't show consistency. Part of the consistency on the instrument comes from the cover tiles. That covertile technology allows your tissue to stay moist. It also allows an even pull through of reagents. That gives you consistency. They're also easy to take care of, and it keeps delicate tissues in place. and preserves them, that allows us to do some of the unique things you saw in the slide that showed all the technologies and things that people had run, things like CTCs. That covertile technology allows for that to happen.

Now these are some of the partners that run on the BOND RX. There are partnerships with everything from CTC companies to multiplexing companies to the wonderful partnership that we have with NanoString and their multiplexing technology and their GeoMx DSP. And I know that Mathias took you through this earlier, but this is one of the wonderful things about having a partnership with a company like NanoString is if you look at all of the things that go into making a slide that goes onto the DSP happen, then BOND RX is a wonderful piece of that because it takes away time-consuming preparation pieces. Baking, de-waxing, epitope retrieval, enzyme pre-treatment. All those pieces can be run on the automation so that you get that consistency piece, but you also free up people to do other things that are important to the laboratory during that time. Then you can do your overnight in your RNA or your protein. Then once that is done, you can go on to the DSP.

There is a fully automated version of the RNA coming. They're being worked on right now. Hopefully you will see that in the not-too-distant future. Then the commercialization piece. And this is where NanoString is right now with us. That's an ideal of balancing act between being able to use those open detection pieces that NanoString uses, custom protocols, which is something that you'll see going through the different protocols on the instrument, the standard bulk reagents, and you get that run-to-run consistency. Freedom and flexibility plus consistent results. That gives researchers the ability to publish. It gives them the ability to do posters, all these wonderful things that we as researchers like to put out to show off the wonderful work that we do. Some companies that have been in this cycle with us for a while, you've got the ability to be on the BOND RX to do co-marketing agreements like NanoString has done. We've had partners that have gone on to go from being on the BOND RX to make it into the clinical world on the BOND III. That's the hope of all our partners is to go that direction. Commercializing is a wonderful thing. We love to do the co-marketing partnerships that we have with companies like NanoString. What we like to see is that companies come through these partnerships with us. This is sort of a list of where our partnerships have gone. You get to the end and hopefully we'll see more of you in this pipeline. Thank you very much for your time and attention and I'll now open the floor for questions.

Thank You Traci and welcome back Dr. Holpert. Thank you for your presentations and now let's start our live Q&A portion of the webinar. To our audience if you have any questions you'd like to ask please do so now. Just click on that ask a question box located on the far left of your screen and click send. Let's get started. Dr. Holpert, let's start with you. Here's our first question. Can you customize or add in targets or antibodies to your assays?

Yeah, thank you. Well, that's a very good question that comes up rather often. As we know, we can design our panels as good as we want to. We will always be missing that one target that a particular researcher wants. We made all our panels customizable. The protein panels and the RNA panels like shown on this slide over here can be customized. You can add in your own markers and to do so or either we can label them with the necessary barcodes, DNA barcodes for that or while we partnered up with Abcam for the protein part, we can look at the whole IHC validated antibody portfolio, and they can label them directly to the genomics barcodes and then ship them to you. They do the custom labeling for you.

Thank you, Dr. Holpert. Now, next question. How many fluorescent markers can I use?

Yeah, the instrument has four fluorescent channels, so basically, it's a microscope that has four fluorescent channels. One of them we tend to use as a DNA marker, the DNA dye, which is used in the FITC channel, and that leaves us three other options to put in morphology markers.

Thank you. Let's see, our next question, we've got so many questions coming in. Here we go. How do you normalize?

The system has a full data analysis software integrated, and you can use that to normalize in multiple ways. Unfortunately, there is no one normalization that fits all. The software allows you to normalize in multiple ways. You can normalize by area of the ROI that you took or the segment. You can normalize by the amount of nuclei in those regions of interest. You can normalize by housekeepers, which are always added to our panels. And you can normalize by background subtraction. There are the necessary IgGs in the case of protein or negative probes for the RNA panel are also integrated. We kind of have it all in there. Use it or leave it, housekeepers, IgG, whatever you like, it's all in there. And then it's up to you what you want to use in the end.

Thank you, Dr. Holpert. Okay, we have another question here. Traci, this one's for you. How do you add new reagents onto the BOND RX for assays like NanoString?

That's a very good question. For assays like the NanoString, there are open reagent containers that you can use. They can either be full containers or there are titration containers that can be used for adding reagents. If you look at the HAF protocol that is used by NanoString, that has areas that they add their own reagents to during the pre-steps. For enzymes and things like that you can use those, or you can use the ones that LICA already has in the full protocol that's being developed. that relies on the open detection containers, and it also relies on open antibody and probe containers. If you're using very small amounts of those, the titration containers are good places to put those items, depending on the number of slides that you're running.

Thank you, Traci. Our next question. How can you optimize segmentation for different cell size or different cell shape like glia versus lymphocytes?

Yeah, that is easily done with the software. The algorithm, once you select your ROI and you want to do segmentation, you do so on the fluorescent markers that you apply to the slide, that you stained your slide with. If you're using a gill cell marker or a lymphocyte marker labeled in different fluorescent colors, the segmentation algorithm will pick up the colors. You can basically segment red cells into one. well in the end, and then green cells in the other well in the end. You can go like that. If you want to normalize that in the end, you can either go by nuclear count, then you have the size of the cells dealt with, or you can do housekeepers or whatever you like. But the segmentation algorithm takes care of that very nicely, and you can always tweak that manually if it doesn't go to your liking.

Thank you, Dr. Holpert. And thank you, Traci DeGeer, both for your informative presentations today, and thank you for your Q&A. I do want to remind the audience of those questions we did not answer today, and those that come in during the on-demand period will be answered by our speakers via the contact information you provided at the time of registration. Again, I would like to thank LabRoots, our sponsor, and Leica Biosystems and NanoString for underwriting today's educational webcast. This webcast can be viewed on demand, and LabRoots will alert you via e-mail when it's available for replay. We encourage you to share that e-mail with your colleagues who may have missed today's live event. That's all for now, and we hope to see you again soon. Have a great day.