{"id":"doi:10.1007/s10147-026-03182-0","kind":"review","title":"From cell counts to cellular interactions: Cu-Cyto and the co-localization index as a spatial framework for the tumor immune microenvironment of rectal cancer","authors":["Yamashita K","Nagasaka T","Abe T","Adachi Y","Ito R","Tachibana T","Takahashi T","Kagiyama H","Imai M","Tsuneki T","Ando M","Asano Y","Miyashita K","Otowa Y","Urakawa N","Goto H","Hasegawa H","Kanaji S","Fujita M","Matsuda T","Sasaki R","Fukumoto T","Kakeji Y"],"author_count":23,"year":2026,"published":"2026-09-08","venue":"International journal of clinical oncology","cited_by":0,"doi":"10.1007/s10147-026-03182-0","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1007/s10147-026-03182-0","archive_url":"https://space-kitty.com/papers/doi:10.1007/s10147-026-03182-0","updated":null,"pmid":"42709377","pmcid":null,"openalex_id":null,"pdf_url":null,"abstract":"The tumor immune microenvironment in colorectal cancer has emerged as a major determinant of patient outcome, with tumor-infiltrating lymphocytes, particularly CD8⁺ T cells, mediating antitumor immunity. Standardized density-based metrics such as the Immunoscore have demonstrated prognostic value but cannot capture the spatial interactions among cells that underlie immune-tumor biology. We introduce a deep learning framework that integrates two complementary axes of analysis: Cu-Cyto, a deep learning-based image cytometry platform that detects and classifies approximately twenty cell types from standard immunohistochemistry-stained whole-slide images, using a bit-pattern kernel-filtering algorithm to prevent multi-counting and an off-target labeling strategy for precise nuclear-center localization; and the Co-Localization Index, which converts the classification probabilities and coordinates produced by Cu-Cyto into a single quantitative measure of co-localization between two or three cell types. We illustrate this framework through CD103⁺CD8⁺ tissue-resident memory-like T cells in rectal cancer treated with neoadjuvant chemoradiotherapy: their stromal but not intratumoral density independently predicts relapse-free survival. This divergence, which compartment-aware density alone cannot explain, motivates a metric that captures within-compartment spatial relationships. The Co-Localization Index extends naturally to three-cell interactions, providing a quantitative readout of the tri-cellular biology among CD103⁺CD8⁺ T cells, tumor cells, and stromal components. Prospective validation in independent rectal-cancer cohorts, addressing watch-and-wait organ preservation and adjuvant chemotherapy decisions, will determine whether this spatial-cellular framework translates into routine clinical decision support with potential extension to other solid tumor contexts.","abstract_license":"CC-BY (article license as recorded by Europe PMC; abstract reproduced unmodified apart from markup removal)","license":"CC-BY","is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":[],"details":null,"provenance":"europepmc","attribution":"Abstract of \"From cell counts to cellular interactions: Cu-Cyto and the co-localization index as a spatial framework for the tumor immune microenvironment of rectal cancer\" by Yamashita K, Nagasaka T, Abe T et al., https://doi.org/10.1007/s10147-026-03182-0, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"cancer-immunotherapy","name":"Cancer Immunotherapy","domain_slug":"medicine"}],"cited_in_dossiers":[]}