High Resolution 3D Spatial Architecture
Center for Cellular Language Intelligence
Linghua Wang, M.D., Ph.D.
Executive Director and Head
The Center for Cellular Language Intelligence decodes the cellular language of cancer by uncovering how cells organize, communicate, function and adapt across space and time and within tumor ecosystems, then translating those insights into actionable advances to improve patient care.
Cancer is not just a collection of malignant cells, but rather a dynamic ecosystem in which cancer cells, immune cells, stromal cells and other components are continuously reorganizing and interacting across space and time. These spatial organization patterns and intercellular interactions shape how tumors grow, spread, evade the immune system and respond to or resist treatment.
Recent advances in spatial multi-omics, molecular imaging, spatial functional genomics, 3D modeling and artificial intelligence (AI) now make it possible to decode the biological language of intercellular interactions. This reveals how cells are organized within tissues, how cell organization and interactions evolve during disease progression and therapy and how these changes influence clinical outcomes.
The Center for Cellular Language Intelligence (CCLI) brings these capabilities together in an integrated framework to uncover the spatial principles and signaling hubs that drive tumor behavior and therapeutic response and to translate those insights into actionable advances for patients.
This video (with no sound) shows some of the center's work with 3D spatial architecture.
Executive Director & Head
Linghua Wang, M.D., Ph.D.
Professor of Genomic Medicine
We will decode the cellular language of cancer to turn complex tissue ecosystems into scalable, clinically deployable biomarkers and therapeutic strategies.
Learn more about the center's researchCCLI Strategic Goals
Cross-Institute by Design
CCLI is a central hub connecting UT MD Anderson's specialized strengths to accelerate the translation of discoveries into patient benefit.
CCLI is a central hub that connects UT MD Anderson’s strengths in single-cell and spatial biology, data science, immunobiology, cell therapy and therapeutics development to accelerate the translation of discovery into patient benefit. By linking spatial ecosystem profiling, computational modeling, causal validation and clinical translation within a single integrated framework, CCLI is positioned to tackle high-impact questions that no individual lab or standalone program can address alone.
The center also works closely with UT MD Anderson’s leading institutes, divisions and strategic initiatives — including the James P. Allison Institute™, the Institute for Data Science in Oncology, the Institute for Cell Therapy Discovery & Innovation, Therapeutics Discovery and Strategic Research Programs, such as the Strategic Research Initiative Development (STRIDE) program — to advance biomarkers, therapeutic targets and translational strategies that improve cancer care.
CCLI Strategic Goals
Decode the cellular language of cancer across space and time
Systematically characterize how diverse cancer, immune and stromal cell populations and states, along with other key components of the tumor ecosystem, organize, communicate and adapt within tissues and across disease stages and therapeutic contexts.
Advance from descriptive atlases to causal understanding
Identify the key signals, pathways and organizational control hubs that drive tumor ecosystem behavior by integrating spatial discovery with functional genomics and perturbation-based validation.
Anchor research in clinically meaningful settings
Design research projects around high-impact clinical questions by strategically selecting patient cohorts and clinical contexts to maximize translational relevance and impact.
Leverage artificial intelligence (AI) to extract meaningful signals and identify drivers
Apply advanced AI approaches to extract biologically meaningful and clinically actionable signals from hyper-dense cell communication networks, generate testable hypotheses and identify high-probability drivers of disease.
Translate ecosystem insights into actionable biomarkers and therapeutic targets
Convert spatial discoveries and tissue ecosystem insights into deployable biomarkers, predictive models and therapeutic hypotheses that enable earlier detection, smarter prevention and more precise treatment strategies.
Establish the standard for cellular language intelligence
Build reproducible study design principles, data resources and translational pipelines that strengthen collaboration and accelerate breakthroughs.