Spatial biology began as a revolutionary idea in the late 2000s—massively parallel identification of the molecules of life in their native contexts to unlock the secrets of cellular organization and tissue function (Lee, 2014). One of the earliest concepts was using a short DNA barcode to map trillions of synaptic connections in the human brain (Marblestone, 2014). It was bold, elegant, and full of promise. Over the years, incredible advances have allowed us to visualize thousands of RNA, proteins, and other molecules with unprecedented spatial resolution. Yet, as the field matures, a critical question remains: can we turn these breakthroughs into transformative tools that shape discoveries and improve patient outcomes?
My journey with spatial biology began long before the term existed. As a graduate student in the 1990s, I studied cell signaling and oncogenes—mutated proteins essential for normal development. Their evocative names—“wingless,” “roughened,” and “hedgehog”—reflected the dramatic changes they caused in the body shapes of flies. I became fascinated not only with their biological functions but also with their potential role in shaping broader patterns of morphogenesis.
My thesis attempted to connect gene regulation and signaling dynamics to mathematical models of how cell interactions drive basic morphogenic processes. To test these ideas, I wanted a method to profile gene expression at the single-cell level within its spatial context and tools like synthetic gene circuits to observe and tune these processes. Around that time, The Matrix was released, sparking my imagination. I envisioned translating gene expression and cell signaling events into a 3D spatial matrix of dynamically flowing genetic signals. Years later, while developing FISSEQ in the Church laboratory (photo below), the iconic “bullet” scene from The Matrix became a recurring metaphor in my presentations.
After completing my thesis, I returned to clinical studies, but my fascination with synthetic biology and morphogenesis lingered. While caring for the same patient, I met my future wife on the hospital floor. Over the next two decades, we shared hundreds of heartbreaking stories about her cancer patients and witnessed firsthand the powerful impact of precision oncology, NGS, and immunotherapies. Through her, I began to question my scientific priorities, driven not just by infinite curiosity, but by a focus on patient outcomes. I began to see survival not as a metric of time, but in the milestones patients hoped to reach: attending their dream school, watching their children graduate, or walking down the aisle. These moments became the lens through which I saw everything—including spatial biology.
As someone who has been immersed in spatial biology since the late 1990s, I am proud of how the field has become a cornerstone of molecular science. High-resolution imaging, single-cell RNA profiling, and multiplexed protein analyses have revealed cellular landscapes in exquisite detail. Yet, for all its progress, the field remains largely descriptive. We excel at answering “what” and “where,” but struggle with “how,” “why,” and “what now?”
This is not a critique of the incredible work being done, but a recognition of the challenges in moving from discovery to impact. The bottlenecks are not just technical; they are conceptual and strategic. High-resolution imaging technologies, while powerful, are painfully slow. To build statistically robust datasets across thousands of samples, we need radical improvements in speed and scalability, without sacrificing resolution and sensitivity. Vast amounts of data are generated, but tools to integrate these findings into functional contexts remain limited. Describing spatial patterns and cellular interactions is one thing; linking them to molecular mechanisms or clinical outcomes at scale is another.
To truly impact patients, spatial biology must leave the lab and enter the clinic. This means simplifying workflows, reducing costs, earning the trust of pathologists, and focusing on actionable insights clinicians can use.
To truly impact patients, spatial biology must leave the lab and enter the clinic. This means simplifying workflows, reducing costs, earning the trust of pathologists, and focusing on actionable insights clinicians can use. Incremental improvements in resolution or multiplexing often overshadow the urgent need for breakthroughs in functionality. The field risks becoming enamored with technological advances that fail to address pressing biological or clinical questions.
To move beyond the plateau, we need to think differently. Doubling down on existing strengths will not suffice; we must reimagine the foundations of the field. New imaging paradigms—computational imaging, novel materials for signal amplification, or even non-optical approaches—could break the throughput barriers we face today. These innovations must be pursued aggressively.
Spatial data must evolve from static maps to dynamic insights. Functional studies—manipulating molecules in situ and observing phenotypic outcomes—are critical for understanding the mechanisms that underlie cellular behavior. Technologies must be designed with clinical translation in mind. This means asking questions like: How can we integrate spatial proteomics into routine diagnostics? What workflows will enable clinicians to make better decisions at the bedside?
The next breakthroughs in spatial biology will not just come from physics, engineering, and computer science, and it needs massive innovations in user interface/experience, high impact applications, and business models that support scalable data collection. Multidisciplinary collaborations are essential to overcome current limits. We need to break down silos and foster partnerships across research, pharma, and clinical teams to ensure spatial biology fulfills its promise.
Imagine a world where spatial biology seamlessly connects genotype to actionable phenotype in situ, across thousands of genes, drug targets, and samples, providing clinicians and researchers with meaningful, real-world insights. Tools that make this vision a reality could be accessible not only to elite research labs but also to hospitals and clinics worldwide, democratizing the impact of spatial biology.
This vision is possible, but it demands a shift in priorities. We must resist the allure of incrementalism and focus on transformative ideas that address the field’s deepest limitations. The promise of spatial biology remains immense. To realize it, we need to think outside the box and never stop challenging the status quo. This is the beginning of an era where spatial biology could redefine our understanding of life and disease. The revolution is far from over—let’s challenge the boundaries and turn vision into reality.