Artificial intelligence-based spatial analysis of tertiary lymphoid structures and clinical significance for endometrial cancer.

ABSTRACT: With the incorporation of immune checkpoint inhibitors into the treatment of endometrial cancer (EC), a deeper understanding of the tumor immune microenvironment is critical. Tertiary lymphoid structures (TLSs) are considered favorable prognostic factors for EC, but the significance of their spatial distribution remains unclear. B cell receptor repertoire analysis performed using six TLS samples located at various distances from the tumor showed that TLSs in distal areas had more shared B cell clones with tumor-infiltrating lymphocytes. To comprehensively investigate the distribution of TLSs, we developed an artificial intelligence model to detect TLSs and determine their spatial locations in whole-slide images. Our model effectively quantified TLSs, and TLSs were detected in 69% of the pa

SUBMITTER: Suzuki H 

PROVIDER: S-EPMC11787133 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature