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Distinct In Vitro Binding Profile of the Somatostatin Receptor Subtype 2 Antagonist [ 177 Lu]Lu-OPS201 Compared to the Agonist [ 177 Lu]Lu-DOTA-TATE.

Rosalba MansiPascale PlasGeorges VauquelinMelpomeni Fani
Published in: Pharmaceuticals (Basel, Switzerland) (2021)
Treatment of neuroendocrine tumours with the radiolabelled somatostatin receptor subtype 2 (SST 2 ) peptide agonist [ 177 Lu]Lu-DOTA-TATE is effective and well-established. Recent studies suggest improved therapeutic efficacy using the SST 2 peptide antagonist [ 177 Lu]Lu-OPS201. However, little is known about the cellular mechanisms that lead to the observed differences. In the present in vitro study, we compared kinetic binding, saturation binding, competition binding, cellular uptake and release of [ 177 Lu]Lu-OPS201 versus [ 177 Lu]Lu-DOTA-TATE using HEK cells stably transfected with the human SST 2 . While [ 177 Lu]Lu-OPS201 and [ 177 Lu]Lu-DOTA-TATE exhibited comparable affinity (K D , 0.15 ± 0.003 and 0.08 ± 0.02 nM, respectively), [ 177 Lu]Lu-OPS201 recognized four times more binding sites than [ 177 Lu]Lu-DOTA-TATE. Competition assays demonstrated that a high concentration of the agonist displaced only 30% of [ 177 Lu]Lu-OPS201 bound to HEK-SST 2 cell membranes; an indication that the antagonist binds to additional sites that are not recognized by the agonist. [ 177 Lu]Lu-OPS201 showed faster association and slower dissociation than [ 177 Lu]Lu-DOTA-TATE. Whereas most of [ 177 Lu]Lu-OPS201 remained at the cell surface, [ 177 Lu]Lu-DOTA-TATE was almost completely internalised inside the cell. The present data identified distinct differences between [ 177 Lu]Lu-OPS201 and [ 177 Lu]Lu-DOTA-TATE regarding the recognition of receptor binding sites (higher for [ 177 Lu]Lu-OPS201) and their kinetics (faster association and slower dissociation of [ 177 Lu]Lu-OPS201) that explain, to a great extent, the improved therapeutic efficacy of [ 177 Lu]Lu-OPS201 compared to [ 177 Lu]Lu-DOTA-TATE.
Keyphrases
  • signaling pathway
  • pet imaging
  • machine learning
  • cell death
  • mass spectrometry
  • transcription factor
  • binding protein
  • induced apoptosis
  • big data
  • neuroendocrine tumors