Mapping Cells and Tissues Using Spatial Technologies

The ability to assess gene or protein expression across cell types while retaining spatial information lends a powerful new perspective to cell-cell interactions and tissue organization. Spatial mapping is allowing the posing of new questions and the testing of new hypotheses, for example, in different regions of brain tissue, or distinct cancer and immune cell populations within tumor microenvironments. The value of spatial biology is still being realized, allowing greater insights in fields such as cellular heterogeneity, disease biology, and cell atlasing. This article illustrates with research examples how scientists are mapping tissues today using spatial technologies.

Transcript-based spatial mapping

The Visium Spatial Gene Expression platform from 10x Genomics is geared toward discovery work in fresh frozen or fixed tissues, with the option of protein co-detection using immunofluorescence. “Visium generates spatial whole transcriptome data across large areas of tissue sections in a single shot, using next-generation sequencing as a readout,” says Jacob Stern, Director of Product Management at 10x Genomics. “People use it in many sorts of ways, and its strengths come out when you're using it for hypothesis generation.”

As such, Visium is ideally suited for cell atlasing. A recent study used Visium to investigate the cellular organization of white adipose tissue. “The composition of white adipose tissue is a clinically interesting question, given the role that it plays in a number of metabolic disorders,” notes Stern. Attempting to establish a reference atlas for the tissue, the researchers identified over 60 cell subpopulations, as well as cell-cell interactions, and associations between metabolic states and specific cell types.

Researchers at Helmholtz Institute in Germany recently used Visium in their investigations of pediatric medulla blastomas with chromothripsis, a cancer type known to have very poor prognoses. The team used Visium to generate mechanistic hypotheses using differences between patients whose cancers were more or less likely to recur. “They gained a reasonable mechanistic understanding of what might be happening, and developed a hypothesis based on tumor microtubes,” which are thought to be involved in mechanisms of tumor resistance to treatment, says Stern. “This gives them a direction for future work, such as testing novel therapeutic options in this area of acute clinical need.”

Protein-based spatial mapping

Another spatial mapping method relies on the detection of proteins using fluorescently labeled antibodies. Akoya Biosciences’ PhenoCycler^® System is an integrated spatial biology platform for ultrahigh-plex staining, imaging, and mapping human tissues at subcellular resolution. Their platform is designed to capture whole-slide images, rather than just regions of interest, for an unbiased approach to spatial phenotyping. “The large image capture area combined with the ultrahigh-plexing capability provides a wealth of data from millions of cells at single-cell resolution,” says Niyati Jhaveri, Manager of Content Development at Akoya Biosciences. Researchers use Akoya’s PhenoCode Discovery Panels—sets of validated, ready-to-use PhenoCycler antibodies conjugated to unique oligonucleotide barcodes—to profile immune cells, lymphocytes, tissue architecture, and tumor microenvironments.

In collaboration with Arutha Kulasinghe, from the University of Queensland, and VisioPharm, Akoya’s technology was recently used to study responses and resistance to immunotherapies in cutaneous squamous cell carcinoma (cSCC), by examining the phenotypes and functional states of immune, epithelial, and stromal cells. “We identified differential metabolic activation signatures in immune and tumor cells in immunotherapy-sensitive and immunotherapy-resistant cSCC cases respectively,” says Jhaveri. “Furthermore, by employing spatial analysis, we have the ability to define cellular neighborhoods specific to a particular group of patients and/or treatment, and conduct proximity analysis, which allows us to examine the distances between tumor and immune cells to obtain a more profound understanding of tissue form and function.”

To address the heterogeneity of tumors, Akoya offers customization and flexibility in panel design, with probes against immune checkpoints and markers of inflammation, angiogenesis, invasion, metastasis, proliferation, and apoptosis. A 100+ plex panel was recently used in the spatial mapping of over 850,000 cells in a type of head and neck tumor. “Four unique niches marked by infiltration of cytotoxic immune cells and expression of resistance and invasion markers were identified in the same tumor, underlying the competing microenvironments of immune activation and tumor progression that correlated with the partial response to immunotherapy in this patient,” says Bassem Ben Cheikh, Senior Data Scientist and Technical Group Lead at Akoya Biosciences. “This study emphasized the need for ultrahigh-plex single-cell spatial tools for discovering new biomarkers of prognostic significance.”

Complementary methods

While spatial mapping by either transcriptomics or proteomics can be used for discovery work, the two modes can also be complementary. The spatial proteomics platform CellScape from Canopy Biosciences maps proteins using immunofluorescence detection with high resolution and a wide dynamic range. “We think of CellScape as complementary to spatial transcriptomics, which people can use to identify interesting proteins and pathways that they want to probe in more detail,” says Thomas Campbell, Associate Director of Product Management at Canopy Biosciences. “Then they look at the subset of identified protein targets in more detail, zeroing in with more specific research questions using CellScape.”

Canopy achieves high-plex assays through an iterative staining and imaging process, and high resolution from a proprietary image acquisition pipeline developed to generate High Dynamic Range images with an 8-log dynamic range. In this process, they image the same sample multiple times using different exposure times, then create a composite image using a normalized exposure time displaying both brighter and dimmer values. “This allows us to be much more quantitative than other platforms that have a 2- to 3-log range,” says Campbell. “This is really important for not only detecting the presence of analytes but also quantifying their expression, especially when you have high expressers and low expressers within the same sample.”

CellScape is often used for discovery work, such as immune profiling in oncology or immunology applications, comparing diseased versus healthy tissues. “Researchers use CellScape to characterize differences by deep immune profiling, looking at relative abundance of different immune cells, and how immune cells are spatially distributed within a sample,” says Campbell.

In fact, the spatial distribution of immune cells near or within tumors may reveal valuable information, as Campbell notes ongoing efforts to correlate the spatial distributions of immune cells in tumor samples to patients’ clinical outcomes. “It's not just the presence of immune cells in tumors, but also how those immune cells might be infiltrating the tumor within the tissue, that could be predictive of clinical outcomes,” he says. “These questions are inherently spatial, and they can really only be addressed with that spatial context.”

With each new tool in the spatial mapping tool chest, the relative locations of tumor and immune cells will gain greater—and better-understood—significance.