Excited to share our latest work on an image analysis paradigm that combines cell state and morphology analyses of patient biopsies at single cell resolution to uncover clinically relevant head-and-neck #cancer phenotypes! @CellCellPress cell.com/cell/fulltext/S0092… tweetorial👇
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Using multiparameter analysis of cell state, nuclear shape, cell position and neighborhoods, we generated a single cell phenotypic descriptor and grouped patients based on similarity. Phenotypes correlated with clinical features but were not predictive of survival 🤔
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A breakthrough came when we combined tumor cell phenotypes with similar analysis of the stroma. The survival of patients with pEMT status in their tumor was super sensitive to stromal composition, while patients without EMT were not 😯
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This implied that the tumor cell state impacts cancer-stroma crosstalk. Indeed, spatial transcriptomics identified a signaling hub specifically between pEMT cells and CAFs and identified cancer associated extracellular matrix and EGF-Amphiregulin signaling in this crosstalk.
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Finally we asked if the pEMT cells indeed become more invasive in response to CAFs. This was the case, and the CAF-induced invasiveness could be blocked by inhibiting the EMT state in cancer cells prior to co-culture or by blocking EGF-Amphiregulin. This was seen also in vivo 🤩
Oct 28, 2024 · 4:22 PM UTC
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This was an exciting but challenging project and required strong teamwork! Congratulations to @KaroPunovuori & co-authors for fantastic work and thank you to collaborators @IvaskaLab and our funders @helsinkiuni @maxplanckpress @SuomenAkatemia
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