Abstract
The tumor immune microenvironment plays a critical role in colorectal cancer (CRC) prognosis. However, most studies assess a limited set of immune markers manually in the tumor region, without considering immune heterogeneity across multiple tissue regions. This study aims to enhance CRC prognostic assessment by developing an automated multi-regional immunohistochemistry (IHC) scoring system for 15 immune markers. Two representative tissue cores were extracted from CRC surgical specimens (n = 154) across four regions: tumor center, invasive margin, paracancerous tissues, and normal tissues. IHC staining was performed for 15 immune markers, and digitized slides were analyzed using computational algorithms to classify tissue types (e.g., glands, tumor, and stroma) and identify stained pixels. Immune infiltration was quantified in different tissue types across regions, and a tumor-to-healthy immune ratio (THIR) score was introduced to compare immune marker expression in tumor versus healthy stroma. Associations between IHC scores and overall survival (OS) and relapse-free survival (RFS) were evaluated. Computational models achieved 95.19% accuracy in tissue classification and 97.90% in staining identification. Analysis of 120 IHC scores (15 markers × 8 tissue types) revealed significant immune heterogeneity, with 56 scores correlating with OS and 54 with RFS. Notably, markers such as Granzyme B and CD4 had higher prognostic relevance at the invasive margin than the tumor center, while markers like S100 and CD20 exhibited opposing prognostic effects across regions. Integrating multiple markers significantly improved prognostic accuracy, with the combined marker score in normal stroma providing the most significant risk stratification (log-rank test, p = 1.56e-7, OS). The THIR score also strongly correlated with patient outcomes. This study advances CRC prognostication through automated multi-regional IHC scoring, highlighting the importance of immune heterogeneity across tissue regions. These findings support integrating region-specific immune profiling into clinical workflows for more personalized and precise patient care.