Computational immune synapse analysis reveals T-cell interactions in distinct tumor microenvironments.

Area of Science:

• Immunology
• Computational Biology
• Oncology

Background:

• The tumor microenvironment (TME) significantly influences cancer progression and treatment outcomes.
• Multiplex imaging technologies are advancing, but methods to analyze TME cellular interactions are underdeveloped.

Purpose of the Study:

• To develop and validate a novel computational approach for analyzing immune synapse interactions within the TME.
• To demonstrate the utility of this method across different cancer types and imaging modalities.

Main Methods:

• Development of multipronged computational immune synapse analysis (CISA) for automated detection of T-cell synaptic interactions.
• Application of CISA to multiplex imaging data, including imaging mass cytometry (IMC) and histocytometry.
• Validation across human melanoma and breast cancer datasets.

Main Results:

• CISA successfully detected T-cell:antigen-presenting cell (APC) synapses in melanoma IMC data.
• T-cell:macrophage synapse formation correlated with T-cell proliferation in melanoma histocytometry images.
• Quantifications of T-cell:B-cell synapses in breast cancer IMC data predicted improved patient survival.

Conclusions:

• Spatially resolved cell-cell synaptic interactions in the TME hold significant biological and clinical importance.
• CISA provides a robust and versatile method for quantifying these interactions across diverse imaging modalities and cancer types.
• This computational approach enhances the understanding of TME dynamics and their impact on patient outcomes.