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Cancer Cell Discrimination Using Host-Guest "Doubled" Arrays.

Ngoc D B LeGulen Yesilbag TongaRubul MoutSung-Tae KimMarcos E WilleSubinoy RanaKaren A DunphyD Joseph JerryMahdieh YazdaniRajesh RamanathanCaren M RotelloVincent M Rotello
Published in: Journal of the American Chemical Society (2017)
We report a nanosensor that uses cell lysates to rapidly profile the tumorigenicity of cancer cells. This sensing platform uses host-guest interactions between cucurbit[7]uril and the cationic headgroup of a gold nanoparticle to non-covalently modify the binding of three fluorescent proteins of a multi-channel sensor in situ. This approach doubles the number of output channels to six, providing single-well identification of cell lysates with 100% accuracy. Significantly, this classification could be extended beyond the training set, determining the invasiveness of novel cell lines. The unique fingerprint of these cell lysates required minimal sample quantity (200 ng, ∼1000 cells), making the methodology compatible with microbiopsy technology.
Keyphrases
  • single cell
  • cell therapy
  • induced apoptosis
  • deep learning
  • signaling pathway
  • high throughput
  • cell death
  • cell cycle arrest
  • mesenchymal stem cells
  • cell proliferation
  • bone marrow
  • quality control