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Tumor Landscape Analysis Preprint
We’re excited to share our lab’s first manuscript, now available on bioRxiv! In our study, Tumor Landscape Analysis: An Ecologically Informed Framework to Understand Tumor Microenvironments, we introduce the Tumor Landscape Analysis (TLA) pipeline—a novel computational approach designed to rethink how we study cancer tissues.
Tumors aren’t random collections of cells; they’re dynamic, evolving ecosystems. Inspired by principles from landscape ecology, TLA allows us to quantitatively capture the spatial organization of tumor microenvironments (TMEs) with a level of detail and interpretability that has been hard to achieve with traditional methods. Rather than treating cells in isolation, TLA looks at the broader architecture, the “ecological landscape”, of tumors, offering methods to measure cellular distributions, tissue fragmentation, and microenvironmental niches.
At the heart of TLA is a powerful set of metrics adapted from ecology. By applying tools like the Morisita-Horn index, Ripley’s H function, and Shannon diversity, we can quantify how tightly different types of cells cluster together, how evenly they are distributed, and how organized—or disorganized—the tissue has become. Importantly, TLA is imaging-agnostic and flexible: it works with whole-cell, point-based, or region-level data across different tumor types and sample formats.
One unique feature of TLA is the identification of local microenvironments (LMEs). Instead of relying on pre-defined biological categories, TLA uses data-driven spatial patterns to map tumor landscapes into reproducible niches, based on local cell type abundance and mixing behavior. These ecological “zones” can help us understand, in a completely unsupervised way, how tumors evolve, adapt, and respond to therapy.
Why does this matter? Because spatial features of the TME—such as cellular diversity, spatial clustering, and landscape fragmentation—are increasingly recognized as critical drivers of therapeutic resistance and disease progression. By translating the physical layout of cells into quantitative, analyzable data, TLA provides a new lens for exploring tumor biology, stratifying risk, and potentially guiding precision oncology strategies.
This work reflects a true team effort, combining expertise in oncology, spatial statistics, computational biology, and evolutionary theory. We are grateful for the support from the Arizona Cancer Evolution Center, Gerstner Family Foundation, the Grand Forks Career Development Award, and Mayo Clinic’s Center for Clinical and Translational Science (CCaTS).
If you’re interested in applying TLA to your own spatial datasets—or just want to learn more—the full pipeline is freely available on our GitHub. We’re looking forward to collaborating with others who share our passion for decoding the spatial complexity of cancer!
Stay tuned as we continue to expand this framework and explore its applications across different cancer types and treatment contexts.
Read the full preprint: Tumor Landscape Analysis on bioRxiv
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What Is Digital Pathology?
You know what they say: the past holds the keys to the future. At Mayo Clinic, that sentiment is more than a poetic notion—it’s the driving force behind a groundbreaking project that’s turning a century’s worth of preserved tissue samples into cutting-edge medical insights.
The Mayo Clinic Magazine article, The Biggest Treasure Hunt You Can Imagine, takes you inside a warehouse where history, innovation, and science collide. This isn’t your average dusty archive. It’s a high-tech hub where custom robots digitize millions of slides—some dating back to the 1800s—unlocking medical mysteries and reshaping patient care as we know it.
From the moment I first saw the scale of Mayo’s Tissue Registry Archive, I felt the magnitude of its potential. As an oncologist deeply involved in pancreatic cancer research, I’ve personally seen how this treasure trove of digitized data is transforming our understanding of disease and improving outcomes for patients facing daunting diagnoses.
Why This Matters: A Century of Hope, Digitized
Most hospitals toss their tissue samples after 10 years. Mayo Clinic? We keep them indefinitely, because we believe every sample holds a piece of the puzzle. This archive isn’t just about preserving the past—it’s about shaping the future.
Here’s how:
- AI Meets Archival Gold: Advanced algorithms are being trained on digitized slides to predict how cancers will respond to treatments. For pancreatic cancer, one of the deadliest malignancies, this means personalized care plans that could save lives.
- Intergenerational Insights: Families returning to Mayo decades later can benefit from tests run on preserved samples of their loved ones, enabling more precise diagnoses and treatment.
- Medical History in Action: Some slides date back to 1891, representing a continuum of care that’s not just historic—it’s revolutionary.
Revolutionizing Pancreatic Cancer Care
I’ve been privileged to dive into this archive to develop a pipeline that predicts risk of recurrence of pancreatic cancer after surgical resection. By analyzing digitized slides from as far back as 1991, we’re uncovering relationships between treatment and the architectural organization of cancer cells and its associated tumor microenvironment.
The result? New, individualized treatment strategies that provide hope where there was once only uncertainty. And that’s just the beginning.
The Bigger Picture
This isn’t just about one disease or one doctor’s research. It’s about empowering patients everywhere to make informed, data-driven decisions about their health. Imagine getting a second opinion informed by decades of insights—not just from your biopsy but from the combined history of tissue samples stored in a digital repository.
As Dr. Joaquín García, one of the project leaders, says, “This discovery effort is like the biggest treasure hunt you can imagine.” And this treasure? It’s made of lives saved, futures transformed, and hope redefined.
Take a Closer Look
Read the full article in Mayo Clinic Magazine and see how a quiet warehouse in Rochester, Minnesota, is fueling a revolution in medicine. This is history in the making—digitally preserved for a healthier tomorrow.
🔗 Click here to read the full article.
Let’s celebrate the brilliance of the past as it shapes the future of patient care. And trust me—this is a treasure hunt worth following.