10x Genomics’ 2022 Spatial Biology Symposium Review: The New Xenium, Visium and Chromium Study Trifecta with Michael Schnall-Levin, CTO

October 27, 2022
DeciBio Q&A
Research Tools

I'm joined here by Michael Schnall-Levin, the Chief Technology Officer of 10x Genomics — very well known for being the leader in single cell genomics and analysis, and also for its growing spatial omics division with their Visium platform, and also Xenium platform for in situ analysis launching soon. Today, the 10x Genomics 2022 Spatial Biology Symposium is meant to showcase the progress of the spatial omics division of their company in connection to a packed lineup of key speakers showcasing various exciting biology applications and also revealing some of 10x’s future roadmap in the space. Thanks for joining Michael. With so many major developments happening today, what are some of the key takeaways you would like viewers to learn from the 2022 Spatial Biology Symposium?

Today, we're really showcasing a lot of customer work done on our Visium platform. We recently launched the CytAssist along with a new version of our Visium FFPE product that's been really exciting, with people taking that up and getting good results. Then, we're about to launch our Xenium platform. The big thing we are talking about today is a study (Janesick et al. 2022 - DOI: https://doi.org/10.1101/2022.10.06.510405) we put out this past week where we took our Chromium, Visium and Xenium platforms and actually ran them all together on a FFPE (formalin-fixed paraffin-embedded) human breast cancer tissue section to showcase the power of combining all these technologies. This study showed the capability, of all of these technologies, to do really interesting things and all work on the relevant samples (Figure 1).

Figure 1: Experimental design utilizing all three major 10x Genomics platforms. Excerpt from publication: A single FFPE tissue block was analyzed with a trio of complementary technologies. Top: the Chromium Fixed RNA Profiling workflow (scFFPE-seq), with the Miltenyi FFPE Tissue Dissociation protocol. Middle: Visium CytAssist enabled whole transcriptome analysis with spatial context, and was readily integrated with single cell data from serially adjacent FFPE tissue sections. Bottom: The novel Xenium In Situ platform used a microscopy based read-out. A 5 μm tissue section was sectioned onto a Xenium slide, followed by hybridization and ligation of specific DNA probes to target mRNA, followed by rolling circle amplification. The slide was placed in the Xenium Analyzer instrument for multiple cycles of fluorescent probe hybridization and imaging. Each gene has a unique optical signature, facilitating decoding of the target gene, from which a spatial transcriptomic map was constructed across the entire tissue section. The Xenium data could be easily registered with post-Xenium IF / H&E images (as the workflow is non-destructive to the tissue) and integrated with scFFPE-seq and Visium data.

That's fascinating and touches on a lot of different developments. At Xperience 2022, you announced a Visium product suite with the CytAssist facilitating FFPE sample preparations and Visium HD enabling single cell resolution spatial studies. There was also the Xenium for in situ analysis. Now, you're already touching on the fact that 10x has been floating the idea of using all three platforms in a combined way for studies — in this case for clinical applications. Could you speak to how the three platforms were used and what the added value was of combining Chromium, Visium and Xenium in a single study?

Yeah, absolutely. First, basically, the first round product on all three of these platforms enables applicability towards FFPE. On the Chromium side, we released our Fixed RNA Profiling (scFFPE-seq) product where we showed a glimpse earlier this year that was capable of measuring dissociated FFPE samples. Also as you mentioned, the CytAssist and Xenium had been built specifically for FFPE.

What we see when we run all three of these is the ability to really go deep on a sample and go back and forth between some of the strengths of the different platforms. Chromium is really good at surveying all the different cells present in a sample and going really deep on each of those cells. Xenium is really good at doing targeted transcription measurements and Visium is really good at doing broad spatial measurement of whole transcriptome discovery applications.

One example of this: we have research we released where we had breast cancer that was marked double positive rather than a triple positive. Inside this cancer, there is a really tiny cluster of cells we could find because of Xenium. Then, we could go back with Visium transcriptional programs that are different in these clusters themselves. We could find with Chromium different parts within this cancer and different clusters that had varying biology, then take those back spatially in Xenium and start asking questions about how those were spatially organized or immune cells, for example. Back to that (Figure 2).

I think it's a glimpse into what you can really do with these technologies. We think it really shows the power of them.

Figure 2: Excerpt from publication: Figure 7. Visium and Xenium integration derive differentially expressed genes in a triple-positive receptor ROI. (A) Xenium spatial plot for ERBB2 (HER2 - gray), ESR1 (estrogen receptor - green), and PGR (progesterone receptor - magenta) decoded transcripts. (B) Closer view of triple-positive ROI. © Corresponding H&E image. (D) Cell types contained within ROI reveal that this is a DCIS #2 tumorepithelium. (E) Individual Xenium spatial plots from (B). (F) Chromium scFFPE-seq yields only about 30 cells that are positive for PGR, but these cells do not express ERBB2 or ESR1. (G) Triple-positive region is identified in Visium (given a priori knowledge from Xenium) and is (H) part of a distinct cluster (see Fig. 2B). (I) Spot interpolation (see Supp. Fig. 9) provides cell type frequencies within each Visium spot. Color code legend is shown in (D). (J) Visium H&E and four representative differentially expressed genes in the tumor epithelium (94 genes; log2FC >1.5; p-value < 0.05) revealed by Visium data across the whole-transcriptome.

Wow, so really zoning in on important target cells or molecules that you're looking for and then really layering in different multiomics information. That is a great use case in oncology and it is going to be very exciting to hear and read about. I'm sure it will be talked about as taking the next step in spatial analyses.

Referring back to Xperience 2022, you announced a few planned commercial launches in the Visium suite with the CytAssist and Visium HD. Now that we're further down the line, it would be great to hear how those product launches are coming along. What has been the major feedback you've heard?

We launched CytAssist in the middle of this year, so it's still pretty early but so far the early feedback from people has been really positive. People have really good data back as well as it's really simplified the workflow.

That was the original impetus for building CytAssist because with tissue handling, there's a whole set of procedures people have already worked out and the CytAssist allows you to utilize everything that's standard there with various FFPE samples, but then get spatial information. The earliest customers have really validated that and said the data they're getting back is really nice and the workflows have been good.

So, it’s early days, but we're really excited about the feedback we're getting and we're excited about the ability to open up different kinds of samples that would have been challenging to run in a more manual workflow.

In a lot of our talks at Decibio when we're speaking to users of your platform, people are always wanting FFPE clinical sample compatibility on the single cell analysis side. Spatial so far really offers that answer to them. Do you find that your platforms are being applied more in clinical settings now? With recent developments like the Visium CytAssist, has there been a push into clinical and translational research spaces with your devices?

It's still not true clinical diagnostics, but it's increasingly clinical research and clinically motivated research on human samples from a variety of diseases like cancer, autoimmune disease, and infectious disease. We're hearing from customers and starting to see in early studies that these tools are very powerful in understanding why some treatments work. Why do some treatments work for a little while and then stop working? And really teasing apart the molecular basis for that applicability to sample types like FFPE, but also just a set of products that make it easy to collect, store and get data from clinically collected samples is really important. People have been asking us about that and I think these new products are addressing a lot of those needs we've been hearing about for years.

Of course, it's a very exciting proposition, especially for global clinical biobanks filled with FFPE-preserved samples that have been untouchable to the degree of single cell resolution or spatial analysis. This is really opening up some promising research avenues.

I get asked this question a lot, and it’s a trend that is starting to emerge in a lot of our talks, but Visium HD really promises the ability for single cell resolution in spatial analyses. As a leader in single cell analyses, what do you see as the evolving dynamic between spatial technologies and single cell technologies as spatial technologies get closer to single cell resolution and even achieve it in the future?

I think we'll have to see how it plays out to some degree. Part of our mentality here is we're going to drive all these technologies as fast and as far as we can take them, listen to where customers want them to go, and see how that plays out.

I think there are some uncertainties in certain applications on which are the best products to use. I think what we're seeing a lot of right now is people really see the value in using these things together because they provide different kinds of information. Even as spatial resolution gets higher and you start really getting more kinds of single cell scale measurements, there's the ability with a dissociated single cell platform to do really efficient broad surveys of all the cell types that are present in biological samples; that's something that's inherent in the way that technology works. We showcase in this preprint that it's really nice to be able to do that broad survey and then also use various parts of that tissue and do really deep spatial characterization.

We'll see how that plays out. Maybe in some cases, people will purely use spatial or purely single cell, but I think for now we're seeing a fair amount of joint usage.

I'm sure that as you've shown in your white paper there are a lot of potential use cases and benefits from using all these platforms together.

Visium is largely based on transcriptome analyses and we find that is typically the main readout of a lot of users, but now there are added protein or proteogenomic, multiomic capabilities where you can look at both protein and transcription data simultaneously. Have you seen a higher degree of people transition towards these multiomics offerings? What has been the reception and adoption of Visium’s multiomic capabilities?

I think across the board, both in single cell and spatial technologies, people are increasingly interested in doing multiomics and especially doing RNA and protein. Or on the single cell side, we also have joint transcriptional and epigenomic readouts. I think it's not necessarily utilized in every case, but I think there’s a growing number of people who want to use that for a variety of questions.

I think proteins are particularly useful as very canonical markers and for certain types of cells they can be really additive on top of RNA information, but right now you can go a lot broader with RNA than protein alone, which can be a very targeted type of data that doesn't really allow you to do nearly as kind of broad or powerful types of questions without having very specific questions in mind.

Of course, and then going back to Xenium, the newest product and third in the trifecta of 10x Genomics platforms for lack of a better term, is really focused on in situ, multiomics analysis. Would you be able to speak to what inspired Xenium’s development? Now that you're further into trial testing and hearing feedback on some of your commercial rollouts so far, what is the plan surrounding your product roadmap and where do you think it will be adopted most?

We've been watching different kinds of spatial technologies for a while and doing internal investigations. We were all watching in situ analysis for years and it became increasingly clear it offers a set of capabilities, particularly the ability to go to extremely high subcellular resolution, that is hard to do with any other kind of technology. That's where a few years ago we got really serious, did our acquisitions, and really started the Xenium program in full. I think what we're seeing is the extremely high resolution and the ability to marry the molecular data with morphological data and imaging data like H&E (hematoxylin and eosin) is something that gets people really excited.

Again, it's early days with these technologies and people are still wanting to get their hands on them, but I think there are a lot of translational questions people really want to ask. They are extremely excited to do cancer studies, of course, and look at immuno-oncology, what are the states of all the immune cells and what is the signaling that's happening between the immune cells and the cancer cells. Neurological diseases, autoimmune diseases as well as even some basic characterization of natural and non-diseased biology. Just being able to go to extremely high resolution, we're hearing really broad interest in a large set of applications.

It seems it is already spanning all types of different applications and that seems to be a trend with your other platforms as well, but largely oncology, immunology and autoimmune diseases, neurology — a lot of those really big disease research areas.

Now, coming back to today with the Spatial Biology Symposium, you have a lot of great speakers. For example, Paige Porret, who did this first gene-edited pig-to-human kidney turn xenotransplantation, George Church, all these other researchers that have done great work with 10x Genomics. Are these all members of your Clinical Translational Research Network (CTRN)? What is your relationship to the different speakers at the symposium?

You know, there are a variety of relationships. George Church was a founder of ReadCoor, which was one of the companies we acquired en route to building the Xenium platform. The other members at the event are all really powerful scientists who were either part of companies we acquired or have served as advisors, and then a number of the people are customers who are showcasing the science they've been doing with the platform.

That's fascinating. ReadCoor and Cartana were part of those big 2020 acquisitions to lay out the proprietary chemistry as a basis for Xenium are what I believe the story follows. And it's great that you still have a close working relationship with the founders and people who are involved in making those companies.

Something that stands out from these presentations, especially the xenotransplantation study, is seeing Visium already breaking into such a very clinical stage procedure and analyses. That's very promising and an exciting achievement for 10x Genomics.

Yeah, absolutely. That's one of those studies we are getting really excited about and really, to your earlier question, is an early sign of the true applicability of these technologies to human health. Obviously, we love early basic biology discovery as well, but it is really motivating to see these technologies can almost immediately be applied to this very late-stage translational and clinically relevant research. You can see the early signs there's likely going to be a deep, direct clinical utility of these technologies, but people need to work their way through what are the clear signals they're trying to go after in different diseases and how do we best utilize this technology.

This may be a slightly different topic, but at DeciBio we've been doing research on your company and will soon be publishing our 2022 Single Cell Market Report, which will be released soon as well as our new 2022 Spatial Omics Market Report, which is a big reason why we're very happy to be seeing you today. It is a big development in the field to get to speak to 10x Genomics on a day when you're doing your Spatial Biology Symposium,

We have a number of clinical trials where we see 10x analytics platforms being used. Are you directly involved in any clinical trials or are these largely researchers who tend to be using your platform?

For the vast majority of cases, these are customers who are using our platform, but we like to stay close to people and make sure we can help them be successful. We're eager to stay engaged in some of these studies so we can learn how these technologies are being best utilized in clinical trials and what are the implications for downstream clinical work. For the most part, though, these are really customers who are coming to us and saying: “Hey, this is really cool. I can use your products and in this study, and I'm starting to find really interesting stuff.”

Do you tend to directly collaborate with them? Is it a hands-on relationship or they're kind of paving the way with what's possible?

It's usually them paving the way and then we like to stay scientifically close to our customers. That's generally a lightweight relationship in most cases, where it's really just talking to them, staying up to date with them and being willing to hop on the phone if they have questions about how to best design their study and utilize the technologies.

We like to maintain those really nice touchpoints. Usually, it's very much selling these products into these studies and then showing the really cool biology that can be done.

Of course, researchers have to develop the use cases for these technologies and white papers, but that's something that stands out about 10x and is always great. Technical customer support, which is so important for these research and clinical applications to pave the way for other potential applications.

This may be a slightly difficult question, but we have entered a recent economic downturn that has seriously affected a lot of biotechnology companies and limiting their operations. It'd be great to hear how 10x Genomics is handling these unprecedented times and how that's affected any product roadmaps.

We basically try and stay mission motivated. The world around us and economic dynamics can change. Obviously, this year we've had to tighten our belts a little bit and make sure we're being more diligent with some of our spending, but for the most part, it really has not created any major shift for us and we haven't changed our worldview.

We see the products we're building and the things we're working on are absolutely needed by the world, which we're hearing from all of our customers. The stock market can go up and down, but at the end of the day, we are trying to build impactful products. That’s what we really try to focus on.

That's what we love to hear because you really are helping out with developing such transformative technologies and others want to pursue that lane of research with you as well.

As we are nearing the end of time here, you have a busy day ahead. It's going to be a lot of fascinating talks. Are there any final takeaways for what you really want people to walk away from remembering from this 2022 Spatial Biology Symposium?

It’s really that these technologies are increasingly powerful at looking at human disease. This capability now to look at really difficult samples like FFPE across all three platforms and the value you gain from doing all three of them is immense.

We're really excited to see some customers do joint studies, see people take what we've done and take it way further in their hands looking at combinations of Chromium, Visium and Xenium, demonstrating all the biology they can find and ultimately use this to help cure diseases.

That's great. We will be closely following these developments and the evolving relationship between these three platforms, seeing the emerging use cases. I'm sure we'll have some interesting talks with different stakeholders in the field about how this trend continues to emerge. Thanks so much for your time.

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