Spatial Biology

• Identify spatial relationships between cancer cells, immune cells, and stroma.
   
• Characterize immune infiltration (e.g., T-cell proximity to tumor cells).
   
• Predict response to immunotherapies based on spatial biomarker patterns.

• Understand cell-type distributions and gene expression in specific brain regions.
   
• Study diseases like Alzheimer’s, Parkinson’s, and multiple sclerosis with spatial transcriptomic profiles.
   
• Map neural circuits and glial-neuron interactions.

• Track spatial gene expression during embryogenesis or tissue development.
   
• Understand how tissues organize and differentiate over time.

• Identify spatially resolved drug targets.
   
• Assess how drug treatment alters cellular neighborhoods.
   
• Detect spatial biomarkers that predict efficacy or resistance.

• Map host-pathogen interactions in infected tissues.
   
• Understand immune responses to infection at a tissue level.
   
• Study granulomas, abscesses, or inflamed tissue with multiplex profiling.

• Combine spatial biology with single-cell RNA-seq to add spatial context.
   
• Integrate proteomic and transcriptomic signals within tissues.

• Tailor therapies based on the spatial characteristics of individual patients' tissues.
   
• Improve diagnostic accuracy in pathology through spatial profiling.

• Reveal how cells communicate and organize in 2D and 3D spaces.
   
• Study spatial gradients of cytokines, chemokines, and other signaling molecules.

• Analyze extracellular matrix organization and spatial remodeling.
   
• Profile fibrotic niches and their relation to tissue damage.

Investigate spatial tissue-level patterns in population-level disease studies.