FICAN Science Webinar ”Novel computational approaches to the spatial analysis of cancer”
Published 20.3.2026
These nationwide webinars aim to share information about cancer research and its results conducted in various regions and foster collaboration and discussion for the benefit of cancer patients throughout Finland.
22.04 @ 15:00 – 16:00
Time: Wed 22.4. at 15-16
Topic: Novel computational approaches to the spatial analysis of cancer
Speaker: Valerio Izzi, Associate professor, Faculty of Biochemistry and Molecular Medicine (ECM-Hypoxia Unit), University of Oulu; GeneCellNano Flagship PI.
Get to know the Speaker:
This time the webinar is organised by FICAN North. The seminar will be held online (Microsoft Teams) and is open to everyone interested in cancer research.
Link: Join the meeting (Teams)
Abstract
Spatial transcriptomics enables in situ analysis of tumor ecosystems but remains limited by resolution constraints, insufficient integration of extracellular matrix (ECM) biology, and clustering approaches that inadequately capture spatial topology. Additionally, while spatial methods should be conductive to user interaction and interfacing with multiple domains of biomedical sciences, they remain computationally heavy and mostly used retrospectively, to discover dependencies and guide new experiments, thus not really integrating with wet-lab workflows. Better computational models are needed to overcome these limitations and provide interactive experiences to biomedical researchers. In this context, my lab specializes in super-resolution visualization of spatial transcriptomics data, enabling sub-spot exploration while preserving quantitative accuracy, ECM-aware spatial modeling to uncover how ECM organization structures tumor growth and immune landscapes, and advanced AI systems to produce topology-aware clustering that captures biologically coherent tumor ecosystems.
Relevat references for this talk:
- NaVis: a virtual microscopy framework for interactive, high-resolution navigation of spatial transcriptomics data. Oshinjo A., Wu J., Petrov P, Izzi V. bioRxiv 2026.02.18.706509; doi: https://doi.org/10.64898/2026.02.18.706509
- MatriCom, a single-cell RNA-sequencing data mining tool to infer cell-extracellular matrix interactions. Lamba R, Paguntalan AM, Petrov PB, Naba A, Izzi V.J Cell Sci. 2025 Jul 1;138(13):jcs263927. doi: 10.1242/jcs.263927. Epub 2025 Jul 11.PMID: 40501363
- Matrisome AnalyzeR – a suite of tools to annotate and quantify ECM molecules in big datasets across organisms. Petrov PB, Considine JM, Izzi V, Naba A.J Cell Sci. 2023 Sep 1;136(17):jcs261255. doi: 10.1242/jcs.261255. Epub 2023 Sep 4.
