Advances in technology and the reduced costs accompanying them have accelerated the pace of biological research to levels that we almost can’t keep up with. Just as an iPhone from a year ago is already outdated, biological techniques that only recently were made possible are being surpassed by their successors. This is good news for patients, researchers and the pharmaceutical industry.
Take single-cell analysis methods, for example. They have enabled critical discoveries, such as the importance of cell population shifts in disease or the rare cell type that is the missing link in our understanding of why someone gets a disease and why (or why not) they respond to certain treatments. Yet single-cell analysis is akin to DNA sequencing—incredibly powerful, but only a one-dimensional view. To understand the complete story of disease etiology, and therefore how to treat disease, we must move beyond the first dimension toward the era of spatial transcriptomics.
“As we begin to fill in the dark corners of biology through the construction of cell atlases, we increasingly understand how much we don’t know.”
Francisco Avila Cobos, ZS Discovery
Understanding how cells are organized in space
Spatial transcriptomics shines where single-cell techniques fall short. “As we begin to fill in the dark corners of biology through the construction of cell atlases, we increasingly understand how much we don’t know. We don’t know how cells are organized in space, how they interact with one another and how perturbations to these relationships affect health and disease,” said Francisco Avila Cobos.
Spatial transcriptomics is poised to enhance our understanding of human health and disease. And just as single-cell analysis ushered in a new set of challenges for the industry regarding how to extract biological discoveries from an exciting new set of data, spatial transcriptomics will do the same. Patterns for navigating this transition exist—we’ve successfully moved from microarrays to bulk sequencing to single-cell sequencing. It requires an intelligent combination of technical prowess and biological acumen, along with an expert guide for navigating the intersection.
“Spatial transcriptomics will be a key part of how we arrive at the ‘Holy Grail’ of biology: Full 3D models of cells, organs and even organisms. It will be like immersing yourself in a movie with a VR headset, rather than simply sitting on the couch and watching a flat screen,” explained Pascal Nordgren Timshel.
“Spatial transcriptomics will be a key part of how we arrive at the ‘Holy Grail’ of biology: Full 3D models of cells, organs and even organisms.”
Pascal Nordgren Timshel, ZS Discovery
Spatial transcriptomics in drug discovery
As of April of this year, more than 15 phase 2 clinical trials described an intention to use single-cell sequencing, already transforming the way we discover and develop drugs. It is only a matter of time before spatial transcriptomics follows. Because single-cell technologies require dissociating cells from tissues, destroying spatial information, these technologies miss out on hidden—yet key—information that spatial transcriptomics can reveal. Take cancer, for example. Several elegant studies have demonstrated the importance of spatial transcriptomics in identifying tumor architecture and tumor microenvironment-specific characteristics that affect treatment response.
“Three tumors may have the same cell type composition, but they may be an inflamed tumor, a desert tumor and an excluded tumor, each with completely different responses to immunotherapy,” explained Christina Bligaard Pedersen. “This information simply is not available from single-cell RNA-seq data.”
Spatial transcriptomics can also enable scientists to make major inroads for neurological diseases, such as Alzheimer’s disease and Parkinson’s disease. For example, spatial transcriptomics has been used to identify and locate a population of cells highly susceptible to neurodegeneration in Parkinson’s disease and also to establish expression changes induced by plaques in Alzheimer’s. Spatially resolved single-cell atlas efforts that have demonstrated the complex cellular diversity of the entire mouse brain reveal the untapped potential for determining how brain cells interact in space and how that affects health and disease.
The next omics revolution
Spatial transcriptomics is making some pretty big promises, but fulfilling these promises depends on several considerations. First, and perhaps most importantly, spatial transcriptomics is not mutually exclusive to single-cell sequencing—or other technologies. Much like bulk RNA-seq supports single-cell sequencing efforts, single-cell sequencing plays a powerful supportive role for spatial transcriptomics. The researchers who localized vulnerable neurons in Parkinson’s to a specific brain region did so by combining spatial and single-cell data—and this is just one example.
“There is no one piece that will lead to a complete understanding of biology, as it is inherently complex and to some extent, messy,” said Cobos. “However, we can use spatial transcriptomics to discover new pieces of the puzzle. It will be even more exciting in combination with other emerging technologies, such as proteomics.”
Analyzing and contextualizing spatial transcriptomics in this way is not an easy task. As with other omics technologies, new technologies and tools are developed seemingly every day. “At ZS, we bring innovation to our clients by making these new data types accessible,” explained Thomas Skot Jensen. “We do this both through hands-on analysis and by considering the holistic aspect of what is needed, such as building pipelines for data processing and tools for biological discovery.”
The not-so-distant future in human 3D models
Armed with the ability to use spatial and other technologies to their fullest, we predict that the field, including our collaborators and clients, will arrive at the first full human 3D model in the next decade. The computational power and resources are there, but their application still needs to mature and optimize. And as with all new technologies, academic researchers are likely to play a critical role in establishing the reliability of these approaches. Once they do, it won’t be long until they become mainstream across all top biopharmaceutical organizations.
When imagining what could be done with 3D models, an exciting new frontier in drug discovery and development emerges. For example, spatial sampling over time could be used to simulate treatment outcomes and even metastasis of different cancer types—long before a candidate drug enters clinical trials. They could be used to characterize how human and microbial cells interact, providing important insight into the gut-brain axis, or to visualize how new drugs interact with the blood-brain barrier, enabling researchers to develop effective drugs for currently incurable neurological conditions.
As we support scientists in their transition to this next frontier of research, despite the fact that it’s still early days, we conclude that the famous quote from Nobel laureate Sydney Brenner holds true once again: "Progress in science depends on new techniques, new discoveries and new ideas, probably in that order."
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