Coupling live-cell imaging and in situ isolation of the same single cell to profile the transient states of predicted drug-tolerant cells
Résumé
Cell response variability is a starting point in cancer drug resistance that has been difficult to analyze because the tolerant cell states are short lived. Here, we present fate-seq, an approach to isolate single cells in their transient states of drug sensitivity or tolerance before profiling. The drug response is predicted in live cells, which are laser-captured by microdissection before any drug-induced change can alter their states. This framework enables the identification of the cell-state signatures causing differential cell decisions upon treatment.
Domaines
Biochimie, Biologie Moléculaire Bio-Informatique, Biologie Systémique [q-bio.QM] Intelligence artificielle [cs.AI] Bio-informatique [q-bio.QM] Biotechnologie Apprentissage [cs.LG] Modélisation et simulation Traitement des images [eess.IV] Traitement du signal et de l'image [eess.SP] Biologie cellulaire Sciences du Vivant [q-bio] Cancer Ingénierie biomédicale Pharmacologie Systèmes dynamiques [math.DS]| Origine | Publication financée par une institution |
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