Radionuclide Molecular Imaging of EpCAM Expression in Triple-Negative Breast Cancer Using the Scaffold Protein DARPin Ec1.
Anzhelika VorobyevaEkaterina A BezverkhniaiaElena KonovalovaAlexey A SchulgaJavad GarousiOlga VorontsovaAyman AbouzayedAnna OrlovaSergey Mikhailovich DeyevVladimir TolmachevPublished in: Molecules (Basel, Switzerland) (2020)
Efficient treatment of disseminated triple-negative breast cancer (TNBC) remains an unmet clinical need. The epithelial cell adhesion molecule (EpCAM) is often overexpressed on the surface of TNBC cells, which makes EpCAM a potential therapeutic target. Radionuclide molecular imaging of EpCAM expression might permit selection of patients for EpCAM-targeting therapies. In this study, we evaluated a scaffold protein, designed ankyrin repeat protein (DARPin) Ec1, for imaging of EpCAM in TNBC. DARPin Ec1 was labeled with a non-residualizing [125I]I-para-iodobenzoate (PIB) label and a residualizing [99mTc]Tc(CO)3 label. Both imaging probes retained high binding specificity and affinity to EpCAM-expressing MDA-MB-468 TNBC cells after labeling. Internalization studies showed that Ec1 was retained on the surface of MDA-MB-468 cells to a high degree up to 24 h. Biodistribution in Balb/c nu/nu mice bearing MDA-MB-468 xenografts demonstrated specific uptake of both [125I]I-PIB-Ec1 and [99mTc]Tc(CO)3-Ec1 in TNBC tumors. [125I]I-PIB-Ec1 had appreciably lower uptake in normal organs compared with [99mTc]Tc(CO)3-Ec1, which resulted in significantly (p < 0.05) higher tumor-to-organ ratios. The biodistribution data were confirmed by micro-Single-Photon Emission Computed Tomography/Computed Tomography (microSPECT/CT) imaging. In conclusion, an indirectly radioiodinated Ec1 is the preferable probe for imaging of EpCAM in TNBC.
Keyphrases
- cell adhesion
- cell cycle arrest
- circulating tumor cells
- computed tomography
- induced apoptosis
- pet imaging
- high resolution
- binding protein
- positron emission tomography
- cell death
- poor prognosis
- end stage renal disease
- small molecule
- breast cancer cells
- type diabetes
- dual energy
- endoplasmic reticulum stress
- image quality
- ejection fraction
- oxidative stress
- fluorescence imaging
- electronic health record
- risk assessment
- contrast enhanced
- insulin resistance
- machine learning
- cell proliferation
- tissue engineering
- quantum dots
- transcription factor
- cancer therapy
- peritoneal dialysis
- climate change
- deep learning
- pet ct