CIRCUSS, a spatial immune receptor computational analysis tool, enables the characterization of therapeutic resistance to cancer immunotherapies 4342

Abstract Description The immune receptor repertoire captures the fingerprint of immune responses shaped by pathogens, malignancies, and autoimmunity. Advances in spatial transcriptomics have enabled the study of immune repertoires within their spatial context, linking cellular localization to functional diversity. To support this, we present CIRCUSS (Comprehensive Immune Receptor Curation and Spatial Sequencing), an open-source Python package that allows for the robust analysis and visualization of spatial immune cell repertories, quantifying T- and B-cell receptor clonal diversity, expansion, and spatial distribution within tissues. CIRCUSS provides tools for annotating immune repertoires, tracking clonotypes across geographies, and detecting immune cell spatial clustering relative to the tumor microenvironment. Its modular, user-friendly commands enable seamless integration of spatial immune repertoire data with transcriptomics and histological analyses, enhancing the biological interpretation of immune responses. We demonstrate CIRCUSS’s utility by analyzing publicly available spatial datasets from targeted and whole transcriptome detection approaches across tissue sections from human lymphoid tissue, brain metastases, renal cell carcinoma, and melanoma uncovering how immune receptor variation and spatial organization drive localized immune responses. CIRCUSS enables novel insights into immune expansion mechanisms and therapeutic resistance, fostering broader exploration of spatial immunology. Funding Sources Research funded by Lustgarten Foundation and Break Through Cancer foundation. Topic Categories Computational and Systems Immunology (COMP)