Spatial biology is an increasingly important capability for multiomics research — so much so that Nature named spatial transcriptomics technology the year in 2020. As the cost of spatial technology continues to decrease, the number of studies implementing the technology has increased exponentially. In 2010, 1,791 publications on PubMed included “spatial biology.” By 2021, that number was 4,588.
This article explores recent breakthroughs made possible by spatial biology, particularly in human disease research. We also discuss the offerings of different spatial providers, and how the second generation of platforms has expanded the field's capabilities.
Spatial biology is the study of transcriptomics and/or proteomics within the cells' native tissue context. With spatial, researchers can understand cellular functions in the context of neighboring cells and the tissue environments surrounding them. This is a valuable tool in cancer research, where the study of heterogeneous tissue environments provides crucial insights into tumor function.
According to Harvard biophysicist Xiaowei Zhuang, “This maintenance of spatial context is crucial for understanding key aspects of cell biology, developmental biology, neurobiology, tumor biology and more." These capabilities give us insights into previously murky cellular functions. "Specialized cell types and their specific organizations are crucially tied to biological activity and remain poorly explored on the scale of whole tissues and organisms."
The information gleaned from spatial approaches has led to seminal insights for precision medicine and revolutionized the study of biology. For example, IHC is typically used to classify tumors as "hot" or immune-responsive, but it has long been known that a subset of patients with "hot tumors" fail to respond to immune checkpoint inhibitors. It is now clear that many of the non-responding "hot" tumors were misclassified as immune-infiltrated.
Spatial biology is already making waves in medical research. With new technologies, it is possible to better understand disease pathogenesis and drug resistance.
Oncologist David Rimm’s group used spatial proteomics to determine that PD-L1 expression in macrophages residing in the tumor microenvironment (TME), not in the cells in the tumor nest, correlated with response to immunotherapy in advanced melanoma. This discovery solved the mystery of those “hot tumors” and has provided more accurate diagnostic and prognostic information in melanoma treatment.
Spatial transcriptomics was essential in identifying the perturbations in autophagy and lysosomal biogenesis in the post-mortem spinal cord tissues of multiple sclerosis patients. The majority of these discoveries used instruments with no single-cell sensitivity. Rather, they profiled cells in neighborhoods. These neighborhoods varied in size based on the analyte (e.g. more cells are needed to detect RNA than protein).
Spatial biology is developing new capabilities all the time. Major updates between first- and second-generation technologies have changed the scope of possibility for spatial researchers.
Early spatial platforms did not have single-cell sensitivity. They typically assigned cell identities using computational methods based on single-cell RNA sequencing experiments of disassociated tissues. The second-generation of spatial platforms is able to identify individual cells and their programs.
This advancement was possible because of a switch from systems with a sequencing readout to imaging-based systems. These newer platforms use the pattern from a series of fluorescent signals from multiplexed in situ hybridization probes to identify the detected transcript or protein. The data generated from imaging is quantitative, and instrument manufacturers all provide tools for rudimentary analysis.
The first generation of profilers were also brilliant tools for biomarker discovery. Second-generation imagers added the ability to directly observe cell-cell communication and ligand-receptor interactions. They also allow researchers to elucidate the programs in every individual cell in the tissue, in the context of their neighbors.
Advancements like this will accelerate research for scientists everywhere. The Human Cell Atlas, for example, is working to create a reference map of human cells. With spatial technology, cellular "ID cards" show which genes are switched on in a cell. Cells can also be mapped to their specific location within organs and tissues. This effort represents a major resource in the future of disease and health research.
It may seem like everyone is offering spatial biology. However, about 50% of the market is dominated by a few key players. This includes the 10x Genomics Xenium™, Akoya’s PhenoCycler™, and NanoString’s CosMx™ (DeciBio).
All platforms are not created equal. Each company is rapidly expanding their content and the plex of their panels. With Xenium from 10x Genomics, customers can select from ~400-plex RNA panels for either human or mouse. 10x also offers specific panels geared towards neuroscience or oncology.
Akoya’s platform is focused solely on proteins with low-plex panels (~50-plex) targeted for the immuno-oncology market. NanoString offers 1,000-plex RNA panels focused on either human immuno-oncology or murine neurobiology. They also have a 68-plex protein panel to elucidate human immune cell content and activation status.
There are many other companies in the spatial arena, including Bruker, Lunaphore, Ultivue, and Vizgen. The key is selecting companies with platforms and panels capable of targeting your research area. Scientists now have abundant options when choosing spatial biology solutions. These include new instruments with single-cell sensitivity for both RNA and protein.
Does every experiment need spatial biology? Of course not! But many could benefit enormously from the ability to answer novel questions.
With the future of spatial biology, we will elevate our understanding of how individual cells are impacted by their neighbors. The next milestone in the field will be robust quantitation of both transcripts and proteins concurrently, in the same tissue section. We may even understand how tissue functions as a compilation of the cells within tissue subcompartments, compartments, and whole organs.