In:
European Journal of Nuclear Medicine and Molecular Imaging, Springer Science and Business Media LLC, Vol. 49, No. 10 ( 2022-08), p. 3557-3570
Abstract:
Patients undergoing prophylactic central compartment dissection (PCLND) for papillary thyroid cancer (PTC) are often overtreated. This study aimed to determine if molecular fluorescence-guided imaging (MFGI) and spectroscopy can be useful for detecting PTC nodal metastases (NM) and to identify negative central compartments intraoperatively. Methods We used a data-driven prioritization strategy based on transcriptomic profiles of 97 primary PTCs and 80 normal thyroid tissues (NTT) to identify tumor-specific antigens for a clinically available near-infrared fluorescent tracer. Protein expression of the top prioritized antigen was immunohistochemically validated with a tissue microarray containing primary PTC ( n = 741) and NTT ( n = 108). Staining intensity was correlated with 10-year locoregional recurrence-free survival (LRFS). A phase 1 study (NCT03470259) with EMI-137, targeting MET, was conducted to evaluate safety, optimal dosage for detecting PTC NM with MFGI, feasibility of NM detection with quantitative fiber-optic spectroscopy, and selective binding of EMI-137 for MET. Results MET was selected as the most promising antigen. A worse LRFS was observed in patients with positive versus negative MET staining (81.9% versus 93.2%; p = 0.02). In 19 patients, no adverse events related to EMI-137 occurred. 0.13 mg/kg EMI-137 was selected as optimal dosage for differentiating NM from normal lymph nodes using MFGI ( p 〈 0.0001) and spectroscopy ( p 〈 0.0001). MFGI identified 5/19 levels (26.3%) without NM. EMI-137 binds selectively to MET. Conclusion MET is overexpressed in PTC and associated with increased locoregional recurrence rates. Perioperative administration of EMI-137 is safe and facilitates NM detection using MFGI and spectroscopy, potentially reducing the number of negative PCLNDs with more than 25%. Clinical trial registration. NCT03470259.
Type of Medium:
Online Resource
ISSN:
1619-7070
,
1619-7089
DOI:
10.1007/s00259-022-05763-3
Language:
English
Publisher:
Springer Science and Business Media LLC
Publication Date:
2022
detail.hit.zdb_id:
2098375-X
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