High-dimensional spatial biology approach to study tumor budding Group Zlobec In our Innosuisse-funded project together with Lunaphore technologies, we are establishing a high-dimensional protein expression panel to investigate the nature of tumor buds and their microenvironment under native and treatment scenarios. We investigate the “active” state of tumor buds and their relationship to Epithelial-Mesenchymal Transition (EMT). Most importantly, the clinical relevance of different budding phenotypes, stromal changes and immune cell contexture by utilizing our well-documented patient collectives and ngTMA®. Data analysis is critical, and we aim to develop streamlined pipelines to evaluate these multiplexed fluorescent images using in-house deep learning algorithms and commercially available and open-source software.. Tumor microenvironment in colorectal cancer at 20x magnification: a, Panck (red) and Vimentin (green); b, CD20 (pink) and CD3 (yellow); c, E-cadherin (green) and CDX2 (red).
Digital pathology & AI to gain novel insghts into colorectal cancer Group Zlobec Our Sinergia project uses AI to harness the power of histopathology images, genomics (focusing on STRs), and pharmacoscopy to gain novel insights into colorectal cancer biology and understand their impact on clinical outcomes. We investigate morphomolecular relationships, including the CMS classification, and intratumoral heterogeneity in order to learn new interpretable & clinically important features from histopathology images. We use various computational methods, including graphs and deep learning) to evaluate the structural and spatial patterns at the tumor invasion front in neoadjuvantly treated patients. We’ve extended our scope to understanding CMS using spatial transcriptomic and protein expression analysis. The tumor microenvironment, with its complex stromal patterns and immune contexture are important focus points. Collaborators on this project include M. Rodriguez (IBM Research), M. Anisimova (ZHAW), B. Snijder (ETH Zürich), A. Fischer (HES-SO & UniFribourg) and V. Koelzer (UniZürich). Epithelial cell and lymphocyte graphs in colorectal cancer.
Building tools for computer-assisted diagnostics Group Zlobec In addition to exploratory tissue analysis, our team builds, tests and validates in-house, open-source and commercially available algorithms for potential diagnostic use and workflow integration. We are currently running a comparative study on the impact of scanners and performance of different software for Ki-67 detection and quantification. We use deep learning methods for segmentation and metastatic detection in lymph nodes, and streamline processes lab and data analysis processes, for e.g from scanning to construction of “next-generation Tissue Microarrays®” (www.ngtma.com) to visual presentation of results and analysis. We use graphs and geometric deep learning to learn about tumor budding and lymphocytes, and as part of our collaboration with the International Budding Consortium, generate hot-spot detection and tumor budding quantification algorithms in early stage pT1 cancers. Computational Analysis of Colorectal Cancer Metastases in Lymph Nodes.
New insights into tumor immune evasion published in Science The Institute of Pathology has supported EPFL's work on FMRP deficiency in solid tumours, which has just been published in Science. Click here to read all about it.
Dr. Hannah Williams joins our group! Hannah joins us from the Beatson Institute for Cancer Research UK and Dana-Farber Cancer Institute, where she has extensive experience in the application and analysis of spatial modalities for cancer. Her work at the Institute for Pathology will involve exploring epithelial heterogeneity and plasticity in solid tumours.
SITC 2022 poster by our post-doc Cansaran S. Demir Fantastic work by Cansaran and the team, establishing a 25+ plex panel with Lunaphore technologies to investigate tumor budding in colorectal cancer: "Characterization of tumor budding and the tumor microenvironment in colorectal cancer using hyperplex immunofluorescence"
Graphs for colorectal cancer discovery Catch this interview with our PhD student Ana Leni Frei and discover what graphs are and why these can be used for colorectal cancer research using histopathology images.
