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University of Cambridge > Talks.cam > Computational and Systems Biology Seminar Series > Cell state switches and local adaptation in cancer: insights from AI and ecology-inspired approaches
Cell state switches and local adaptation in cancer: insights from AI and ecology-inspired approachesAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Michael Boemo. During tumour development and upon therapy, cancer cells flexibly switch between proliferation and cell cycle arrest to adapt to intrinsic and extrinsic stress. How these plastic switches are governed in the context of constrained cancer evolution trajectories and of the tumour microenvironment remains poorly understood. In this talk, I will discuss recent insights we have obtained from bulk, single cell and spatial transcriptomics datasets into the genomic constraints and gene regulatory programmes shaping proliferation and cell cycle arrest switches in cancer. We use large language models applied to single cell data and methods inspired from ecology applied to spatial transcriptomics to identify and characterise a G0 arrested, hybrid EMT state with hallmarks of unfolded protein response stress, defining an immune evasive and plastic niche which could be relevant for immunotherapy. Our methods, EMT -LM and SpottedPy, can be flexibly applied to classify and characterise plastic cell states and their microenvironmental niches in cancer. This talk is part of the Computational and Systems Biology Seminar Series series. This talk is included in these lists:Note that ex-directory lists are not shown. |
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