Abstract 215: A novel framework for deciphering 3D genome structure in colorectal cancer

Abstract Background: The spatial organization of chromatin is a fundamental determinant of epigenomic landscape which is widely investigated using high-throughput chromosome conformation capture (HiC) technique. To address challenges associated with the resolution and variability of HiC technique, we applied a novel workflow, HiC-ECC (HiC Enhance, Compare, and Call). This approach not only enhances HiC data quality but also enables the identification of biologically significant chromatin interactions and genome structural features. By integrating advanced computational tools with a focus on colorectal cancer (CRC) biology, this study sheds light on the 3D genome architecture of CRC organoids and its implications for patient stratification and therapeutic targeting. Methods: We applied the HiC-ECC workflow to a cohort of 15 patient-derived CRC organoid models, including samples derived from primary tumors and metastatic sites in the lung and liver. The workflow involved initial data preprocessing to generate high-quality chromatin contact matrices and ensure rigorous quality control. To enhance the resolution of HiC datasets, we utilized deep learning-based methods, enabling more accurate identification of chromatin interactions. Comparative analyses were conducted to identify differential chromatin interaction patterns and conserved structural features across the cohort. Chromatin architecture was further characterized by delineating topologically associating domains (TADs) and clustering them to reveal common and sample-specific interaction networks, offering insights into the hierarchical organization of 3D genome structures. Results: Our analysis revealed four distinct subtypes of CRC organoids based on their 3D genome architecture, revealing a novel approach to interrogate heterogeneity within CRC. This subtyping was driven by differential chromatin interaction patterns and structural features, including unique TADs and conserved regulatory elements. Comparative analysis highlighted subtype-specific chromatin interaction networks, suggesting distinct epigenomic landscapes that correlate with tumor progression and metastatic potential. Conclusion: This study enhances our understanding of CRC epigenomics and lays the groundwork for integrating chromatin architecture into patient stratification and precision therapy. Citation Format: Amin Nooranikhojasteh, Jakob Zerbs, Ghazaleh Tavallaee, Elias Orouji. A novel framework for deciphering 3D genome structure in colorectal cancer [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 215.