Our New Collaborative Paper is Out

We are excited to share our latest collaborative study: “Integrated Collagen Architecture and Composition Improve Risk Stratification in Triple-Negative Breast Cancer.”

In this work, we combined multimodal histopathology, collagen imaging, and artificial intelligence–based computational analysis to investigate how extracellular matrix (ECM) organization influences disease progression in triple-negative breast cancer (TNBC).

Our findings show that quantitative collagen architecture and composition provide powerful prognostic information beyond conventional clinical markers, improving survival and recurrence risk stratification in TNBC patients. This study highlights the critical role of the tumor microenvironment in cancer progression and demonstrates the potential of AI-driven computational pathology for precision oncology.

This project represents a highly interdisciplinary collaboration across cancer biology, pathology, imaging, and machine learning.

Read the preprint here: