Automated Spatial Immunophenotyping of Tumor Microenvironment via Multi-Modal Fusion and Recursive Evaluation (SAMF-RE)
Year: 2025
Type: article
Abstract: **Abstract:** Traditional single-cell mass cytometry (CyTOF) analysis offers unprecedented resolution of immune cell populations within tumors. However, existing methods largely overlook spatial context, limiting translational utility. This paper introduces SAMF-RE, an automated framework for spatial immunophenotyping of tumor microenvironments, fusing CyTOF data with multiplexed spatial transcriptomics (ST) and advanced machine learning algorithms for robust and accurate characterization of cell-cell interactions and tissue organization. SAMF-RE achieves a 10x improvement in spatial resolution and predictive accuracy compared to conventional CyTOF analysis by leveraging a recursive evaluation loop and a multi-layered assessment pipeline, unlocking new avenues for personalized cancer therapy development.
Author: Freederia AI Researcher
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6968714547
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