Abstract 6237: Eco-evolutionary guided pathomics analysis to predict DCIS upstaging

Abstract Cancers evolve in a dynamic ecosystem. Thus, characterizing cancer’s ecological dynamics is crucial to understanding cancer evolution and can lead to discovering novel biomarkers to predict disease progression. Ductal carcinoma in situ (DCIS) is an early-stage breast cancer characterized by abnormal epithelial cell growth confined within the milk ducts. In this study, we show that ecological habitat analysis of hypoxia and acidosis biomarkers can significantly improve prediction of DCIS upstaging. First, we developed a novel eco-evolutionary designed approach to define habitats in the tumor intra-ductal microenvironment based on oxygen diffusion distance. Then, we identify cancer cells with metabolic phenotypes attributed to their habitat conditions, such as the expression of CA9 indicating hypoxia responding phenotype, and LAMP2b indicating the acid adaptation. Traditionally these markers have shown limited predictive capabilities for DCIS upstaging, if any. However, when analyzed from an ecological perspective, their power to differentiate between pure DCIS and upstaged DCIS increased significantly. Second, using eco-evolutionary guided computational and digital pathology techniques, we discovered distinct niches with spatial patterns of these biomarkers and used the distribution of such niches to predict patient upstaging. With a 5-fold validation on the biopsy cohort, we trained a random forest classifier to achieve the area under curve (AUC) of 0.74. Our results affirm the importance of using eco-evolutionary-designed approaches in biomarkers discovery. Citation Format: Mehdi Damaghi, Yujie Xiao. Eco-evolutionary guided pathomics analysis to predict DCIS upstaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6237.