Anita Grigoriadis is a Professor of Molecular and Digital Pathology affiliated with a Comprehensive Cancer Centre, where she leads the Cancer Bioinformatics group. Her research focuses on computational approaches to triple-negative breast cancer (TNBC), genomic instability, and tumor-immune interactions. She collaborates extensively with clinical partners like Professor Andrew Tutt and utilizes high-throughput data to develop biomarkers and therapeutic strategies. Education: Master of Science in Bioinformatics with Systems Biology, UCL University College London (2008) Doctor of Philosophy, University of Salzburg (1997) Master of Natural Science, University of Vienna (1993) Research Focus: Her group investigates TNBC biology through genomic/transcriptomic analysis, machine learning-based histopathology, and immune microenvironment dynamics. Key areas include lymph node alterations in metastasis prediction, drug sensitivity algorithms, and microbial community influences on cancer progression. Research integrates bulk/single-cell transcriptomics, genomics, and multiplexed imaging. Publication Trends: Recent works emphasize tumor microenvironment plasticity, stromal composition in breast cancer prognosis, immune dysregulation in melanoma, and computational pathology innovations. Studies frequently employ multi-omics integration and AI-driven digital pathology. Projects & Leadership: She leads/co-leads 41 projects, including: Wellcome Trust-funded multimodal tissue imaging (2024–2026) CRUK spatial proteogenomics platform for breast cancer detection (2024–2025) EPSRC AI Hub for healthcare causality (2024–2029) She directs PhD training and peer-reviews for journals like Cell Reports Medicine .








