Assistant Professor, Department of Medicine
Bio
Dr. Madeleine Torcasso is an Assistant Professor in the Department of Medicine, Section of Hematology and Oncology at the University of Chicago. Her lab investigates spatial patterns of disease within the native tissue environment, bridging scientific discovery and clinical utility. With a focus on tumor-immune and other host-immune interactions, her group develops and applies computational methods to analyze high-dimensional spatial proteomic and transcriptomic data, aiming to uncover how cellular organization and interactions drive disease progression and therapeutic response.
Dr. Torcasso was previously an Eric and Wendy Schmidt AI in Science Fellow at UChicago working under the supervision of Dr. Maryellen Giger and Dr. Marcus Clark at the intersection of imaging -omics and immunology. In 2018, she received her PhD in Biomedical Engineering from Texas A&M University, where she focused on radiative transport modeling for the design of in vivo optical systems.
Artificial intelligence (AI) is becoming an increasingly powerful tool for predicting how breast cancer patients will respond to treatment and whether their cancer is likely to progress. However, many of these AI models function as “black boxes,” meaning they can make accurate predictions without it being clear how they reached their conclusions. This lack of insight limits both doctors’ confidence in using these tools and researchers’ ability to learn from them.
This study focuses on triple-negative breast cancer (TNBC) and aims to uncover the biological features within tumor tissue that AI models use to make their predictions. By connecting AI decision-making to real characteristics of the cancer, this work could help explain why some patients respond to treatment while others do not.
This work could lead to more personalized treatment decisions, the discovery of new biomarkers that predict patient outcomes, and new opportunities for developing future therapies. Rather than simply using AI to make predictions, this research seeks to turn AI into a tool for uncovering new biological insights that can improve breast cancer care.
Madeleine Torcasso, PhD
University of Chicago
Current
Early Investigator
Lamiaa El-Shennawy, PhD
Uptake of Tumor Extracellular Vesicles for Immune Regulation in TNBC
Current
Early Investigator
Andrew Hoffmann, PhD
AI-enabled Profiling of Circulating Tumor-Immune Ecosystems Predicts Breast Cancer Outcomes
Current
Early Investigator
Frederick Howard, MD
Predicting Breast Cancer Recurrence in the Chicagoland Area Using Artificial Intelligence
Why your gift matters
Your gift helps researchers test bold ideas, generate critical data, and take the first steps toward the next major advancement in breast cancer treatment and care.Together, we can accelerate discoveries that save lives.
