Lisa Bodei1,2, Mark S Kidd3, Aviral Singh4, Wouter A van der Zwan5, Stefano Severi6, Ignat A Drozdov3, Anna Malczewska7, Richard P Baum8,4, Dik J Kwekkeboom8,5, Giovanni Paganelli6, Eric P Krenning8,5,9, Irvin M Modlin8,10. 1. Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box 77, New York, NY, 10065, USA. bodeil@mskcc.org. 2. LuGenIum Consortium, Milan, Rotterdam, London, Bad Berka, 54 Portland Place, London, W1B1DY, UK. bodeil@mskcc.org. 3. Wren Laboratories, Branford, CT, USA. 4. Theranostics Center for Molecular Radiotherapy and Imaging, Zentralklinik Bad Berka, Bad Berka, Germany. 5. Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands. 6. Nuclear Medicine and Radiometabolic Units, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, Italy. 7. Department of Endocrinology and Neuroendocrine Tumors, Medical University of Silesia, Katowice, Poland. 8. LuGenIum Consortium, Milan, Rotterdam, London, Bad Berka, 54 Portland Place, London, W1B1DY, UK. 9. Cyclotron Rotterdam BV, Erasmus Medical Center, Rotterdam, The Netherlands. 10. Yale School of Medicine, New Haven, CT, USA.
Abstract
PURPOSE: Peptide receptor radionuclide therapy (PRRT) is effective for metastatic/inoperable neuroendocrine tumors (NETs). Imaging response assessment is usually efficient subsequent to treatment completion. Blood biomarkers such as PRRT Predictive Quotient (PPQ) and NETest are effective in real-time. PPQ predicts PRRT efficacy; NETest monitors disease. We prospectively evaluated: (1) NETest as a surrogate biomarker for RECIST; (2) the correlation of NETest levels with PPQ prediction. METHODS: Three independent 177Lu-PRRT-treated GEP-NET and lung cohorts (Meldola, Italy: n = 72; Bad-Berka, Germany: n = 44; Rotterdam, Netherlands: n = 41). Treatment response: RECIST1.1 (responder (stable, partial, and complete response) vs non-responder). Blood sampling: pre-PRRT, before each cycle and follow-up (2-12 months). PPQ (positive/negative) and NETest (0-100 score) by PCR. Stable < 40; progressive > 40). CgA (ELISA) as comparator. Samples de-identified, measurement and analyses blinded. Kaplan-Meier survival and standard statistics. RESULTS: One hundred twenty-two of the 157 were evaluable. RECIST stabilization or response in 67%; 33% progressed. NETest significantly (p < 0.0001) decreased in RECIST "responders" (- 47 ± 3%); in "non-responders," it remained increased (+ 79 ± 19%) (p < 0.0005). NETest monitoring accuracy was 98% (119/122). Follow-up levels > 40 (progressive) vs stable (< 40) significantly correlated with mPFS (not reached vs. 10 months; HR 0.04 (95%CI, 0.02-0.07). PPQ response prediction was accurate in 118 (97%) with a 99% accurate positive and 93% accurate negative prediction. NETest significantly (p < 0.0001) decreased in PPQ-predicted responders (- 46 ± 3%) and remained elevated or increased in PPQ-predicted non-responders (+ 75 ± 19%). Follow-up NETest categories stable vs progressive significantly correlated with PPQ prediction and mPFS (not reached vs. 10 months; HR 0.06 (95%CI, 0.03-0.12). CgA did not reflect PRRT treatment: in RECIST responders decrease in 38% and in non-responders 56% (p = NS). CONCLUSIONS: PPQ predicts PRRT response in 97%. NETest accurately monitors PRRT response and is an effective surrogate marker of PRRT radiological response. NETest decrease identified responders and correlated (> 97%) with the pretreatment PPQ response predictor. CgA was non-informative.
PURPOSE: Peptide receptor radionuclide therapy (PRRT) is effective for metastatic/inoperable neuroendocrine tumors (NETs). Imaging response assessment is usually efficient subsequent to treatment completion. Blood biomarkers such as PRRT Predictive Quotient (PPQ) and NETest are effective in real-time. PPQ predicts PRRT efficacy; NETest monitors disease. We prospectively evaluated: (1) NETest as a surrogate biomarker for RECIST; (2) the correlation of NETest levels with PPQ prediction. METHODS: Three independent 177Lu-PRRT-treated GEP-NET and lung cohorts (Meldola, Italy: n = 72; Bad-Berka, Germany: n = 44; Rotterdam, Netherlands: n = 41). Treatment response: RECIST1.1 (responder (stable, partial, and complete response) vs non-responder). Blood sampling: pre-PRRT, before each cycle and follow-up (2-12 months). PPQ (positive/negative) and NETest (0-100 score) by PCR. Stable < 40; progressive > 40). CgA (ELISA) as comparator. Samples de-identified, measurement and analyses blinded. Kaplan-Meier survival and standard statistics. RESULTS: One hundred twenty-two of the 157 were evaluable. RECIST stabilization or response in 67%; 33% progressed. NETest significantly (p < 0.0001) decreased in RECIST "responders" (- 47 ± 3%); in "non-responders," it remained increased (+ 79 ± 19%) (p < 0.0005). NETest monitoring accuracy was 98% (119/122). Follow-up levels > 40 (progressive) vs stable (< 40) significantly correlated with mPFS (not reached vs. 10 months; HR 0.04 (95%CI, 0.02-0.07). PPQ response prediction was accurate in 118 (97%) with a 99% accurate positive and 93% accurate negative prediction. NETest significantly (p < 0.0001) decreased in PPQ-predicted responders (- 46 ± 3%) and remained elevated or increased in PPQ-predicted non-responders (+ 75 ± 19%). Follow-up NETest categories stable vs progressive significantly correlated with PPQ prediction and mPFS (not reached vs. 10 months; HR 0.06 (95%CI, 0.03-0.12). CgA did not reflect PRRT treatment: in RECIST responders decrease in 38% and in non-responders 56% (p = NS). CONCLUSIONS:PPQ predicts PRRT response in 97%. NETest accurately monitors PRRT response and is an effective surrogate marker of PRRT radiological response. NETest decrease identified responders and correlated (> 97%) with the pretreatment PPQ response predictor. CgA was non-informative.
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