Our projects span the translational spectrum — from patient care to molecular discovery and computational innovation — all centered around improving outcomes for individuals with breast cancer. By combining clinical insights with data-driven methodologies, we explore how tumors evolve, resist treatment, and respond to new therapeutic strategies.
Each project is shaped by collaboration — across disciplines within the lab and with external partners in academia, healthcare, and industry. Together, we aim to translate biological understanding into real-world clinical benefit. To learn more about our ongoing projects or to explore collaborative opportunities, please get in touch with us. We welcome new ideas, partnerships, and perspectives that can drive innovation in breast cancer research.
Clinical studies are essential for improving breast cancer care by translating discoveries into evidence-based treatments. In this section, we present our portfolio of investigator-led and collaborative studies that evaluate new therapies, optimize existing regimens, and refine treatment intensity to maximize benefit while minimizing toxicity. Across these trials, we integrate robust clinical endpoints with translational analyses, linking patient outcomes to tumor biology, biomarkers, and treatment response to accelerate precision medicine for people with breast cancer.
Contact person: Alexios Matikas (alexios.matikas@ki.se)
One of our research themes centers on advancing data-driven and AI-based analyses in breast cancer, spanning biomarker discovery and validation, methodological development, and critical evaluation of artificial intelligence approaches. Within this theme, we develop and benchmark new computational methods, validate emerging biomarkers for patient prognostication and therapy response, and systematically compare AI models to understand their strengths, limitations, and clinical relevance. Our work integrates handcrafted pathomics with machine learning, deep learning, foundation models, and multimodal analyses of histopathology, spatial and molecular data, and clinical information, contributing to state-of-the-art digital pathology and supporting more precise and personalized breast cancer care.
Contact person: Nikos Tsiknakis (nikolaos.tsiknakis@ki.se)
Associated members: Georgios Manikis, Evangelos Tzoras, Kang Wang, Maria Angeliki Toli
