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SUMMARY:Cell state switches and local adaptation in cancer: insights from 
 AI and ecology-inspired approaches - Maria Secrier (University College Lon
 don)
DTSTART:20241024T150000Z
DTEND:20241024T160000Z
UID:TALK222100@talks.cam.ac.uk
CONTACT:Michael Boemo
DESCRIPTION:During tumour development and upon therapy\, cancer cells flex
 ibly switch between proliferation and cell cycle arrest to adapt to intrin
 sic and extrinsic stress. How these plastic switches are governed in the c
 ontext of constrained cancer evolution trajectories and of the tumour micr
 oenvironment remains poorly understood. In this talk\, I will discuss rece
 nt insights we have obtained from bulk\, single cell and spatial transcrip
 tomics datasets into the genomic constraints and gene regulatory programme
 s shaping proliferation and cell cycle arrest switches in cancer. We use l
 arge 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 respons
 e stress\, defining an immune evasive and plastic niche which could be rel
 evant for immunotherapy. Our methods\, EMT-LM and SpottedPy\, can be flexi
 bly applied to classify and characterise plastic cell states and their mic
 roenvironmental niches in cancer.
LOCATION:Lecture Theatre\, Department of Pathology\, Tennis Court Road
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