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Molecular profiling of neuroendocrine tumours to predict response and toxicity to peptide receptor radionuclide therapy - 02/09/20

Doi : 10.1016/S1470-2045(20)30323-5 
Lisa Bodei, MD a, , Heiko Schöder, MD a, Richard P Baum, ProfMD b, Ken Herrmann, MD c, Jonathan Strosberg, MD d, Martyn Caplin, ProfMD e, Kjell Öberg, ProfMD f, Irvin M Modlin, ProfMD g
a Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA 
b CURANOSTICUM, Center for Advanced Radiomolecular Precision Oncology, Wiesbaden, Germany 
c Department of Nuclear Medicine, Essen University Hospital, University of Duisburg-Essen, Essen, Germany 
d Department of Gastrointestinal Oncology, Moffitt Cancer Center, Tampa, FL, USA 
e Neuroendocrine Tumour Unit, Department of Gastroenterology, Royal Free Hospital, London, UK 
f Department of Endocrine Oncology, University Hospital, Uppsala, Sweden 
g Department of Surgery, Yale University School of Medicine, Yale University, New Haven, CT, USA 

*Correspondence to: Dr Lisa Bodei, Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USAMolecular Imaging and Therapy ServiceDepartment of RadiologyMemorial Sloan Kettering Cancer CenterNew YorkNY10065USA

Summary

Peptide receptor radionuclide therapy (PRRT) is a type of radiotherapy that targets peptide receptors and is typically used for neuroendocrine tumours (NETs). Some of the key challenges in its use are the prediction of efficacy and toxicity, patient selection, and response optimisation. In this Review, we assess current knowledge on the molecular profile of NETs and the strategies and tools used to predict, monitor, and assess the toxicity of PRRT. The few mutations in tumour genes that can be evaluated (eg, ATM and DAXX) are limited to pancreatic NETs and are most likely not informative. Assays that are transcriptomic or based on genes are effective in the prediction of radiotherapy response in other cancers. A blood-based assay for eight genes (the PRRT prediction quotient [PPQ]) has an overall accuracy of 95% for predicting responses to PRRT in NETs. No molecular markers exist that can predict the toxicity of PRRT. Candidate molecular targets include seven single nucleotide polymorphisms (SNPs) that are susceptible to radiation. Transcriptomic evaluations of blood and a combination of gene expression and specific SNPs, assessed by machine learning with algorithms that are tumour-specific, might yield molecular tools to enhance the efficacy and safety of PRRT.

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Vol 21 - N° 9

P. e431-e443 - septembre 2020 Retour au numéro
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