PathVisions 2026: Mapping Cancer’s Cellular Ecosystem

Researchers combine AI, digital pathology, and spatial biology to study cancer at higher dimensions

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MIFSpace is an open-source computational framework for integrating multiplex immunofluorescence images from adjacent tissue sections.
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The framework expands the effective marker space for high-dimensional cellular phenotyping and spatial biology.
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MIFSpace uses quantitative cross-panel concordance analysis to assess marker consistency across nonidentical tissue sections.
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The researchers aim to use MIFSpace to study tumor immune neighborhoods, immune exclusion, and multicellular ecosystems related to immunotherapy response and resistance.
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The researchers envision MIFSpace supporting biomarker discovery and precision oncology by integrating cellular identities, spatial relationships, and molecular measurements.

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