Literature DB >> 29484451

PRRT genomic signature in blood for prediction of 177Lu-octreotate efficacy.

Lisa Bodei1,2, Mark S Kidd3, Aviral Singh4, Wouter A van der Zwan5, Stefano Severi6, Ignat A Drozdov3, Jaroslaw Cwikla7, Richard P Baum8,4, Dik J Kwekkeboom8,5, Giovanni Paganelli6, Eric P Krenning8,9, Irvin M Modlin8,10.   

Abstract

BACKGROUND: Peptide receptor radionuclide therapy (PRRT) utilizes somatostatin receptor (SSR) overexpression on neuroendocrine tumors (NET) to deliver targeted radiotherapy. Intensity of uptake at imaging is considered related to efficacy but has low sensitivity. A pretreatment strategy to determine individual PRRT response remains a key unmet need. NET transcript expression in blood integrated with tumor grade provides a PRRT predictive quotient (PPQ) which stratifies PRRT "responders" from "non-responders". This study clinically validates the utility of the PPQ in NETs.
METHODS: The development and validation of the PPQ was undertaken in three independent 177Lu-PRRT treated cohorts. Specificity was tested in two separate somatostatin analog-treated cohorts. Prognostic value of the marker was defined in a cohort of untreated patients. The developmental cohort included lung and gastroenteropancreatic [GEP] NETs (n = 72) from IRST Meldola, Italy. The majority were GEP (71%) and low grade (86% G1-G2). Prospective validation cohorts were from Zentralklinik Bad Berka, Germany (n = 44), and Erasmus Medical Center, Rotterdam, Netherlands (n = 42). Each cohort included predominantly well differentiated, low grade (86-95%) lung and GEP-NETs. The non-PRRT comparator cohorts included SSA cohort I, n = 28 (100% low grade, 100% GEP-NET); SSA cohort II, n = 51 (98% low grade; 76% GEP-NET); and an untreated cohort, n = 44 (64% low grade; 91% GEP-NET). Baseline evaluations included clinical information (disease status, grade, SSR) and biomarker (CgA). NET blood gene transcripts (n = 8: growth factor signaling and metabolism) were measured pre-therapy and integrated with tumor Ki67 using a logistic regression model. This provided a binary output: "predicted responder" (PPQ+); "predicted non-responder" (PPQ-). Treatment response was evaluated using RECIST criteria [Responder (stable, partial and complete response) vs Non-Responder)]. Sample measurement and analyses were blinded to study outcome. Statistical evaluation included Kaplan-Meier survival and standard test evaluation analyses.
RESULTS: In the developmental cohort, 56% responded to PRRT. The PPQ predicted 100% of responders and 84% of non-responders (accuracy: 93%). In the two validation cohorts (response: 64-79%), the PPQ was 95% accurate (Bad Berka: PPQ + =97%, PPQ- = 93%; Rotterdam: PPQ + =94%, PPQ- = 100%). Overall, the median PFS was not reached in PPQ+ vs PPQ- (10-14 months; HR: 18-77, p < 0.0001). In the comparator cohorts, the predictor (PPQ) was 47-50% accurate for SSA-treatment and 50% as a prognostic. No differences in PFS were respectively noted (PPQ+: 10-12 months vs. PPQ-: 9-15 months).
CONCLUSION: The PPQ derived from circulating NET specific genes and tumor grade prior to the initiation of therapy is a highly specific predictor of the efficacy of PRRT with an accuracy of 95%.

Entities:  

Keywords:  Biomarker; Carcinoid; Liquid biopsy; Neuroendocrine; PRRT; Prediction

Mesh:

Substances:

Year:  2018        PMID: 29484451      PMCID: PMC6716527          DOI: 10.1007/s00259-018-3967-6

Source DB:  PubMed          Journal:  Eur J Nucl Med Mol Imaging        ISSN: 1619-7070            Impact factor:   9.236


  40 in total

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4.  Measurement of circulating transcripts and gene cluster analysis predicts and defines therapeutic efficacy of peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors.

Authors:  L Bodei; M Kidd; I M Modlin; S Severi; I Drozdov; S Nicolini; D J Kwekkeboom; E P Krenning; R P Baum; G Paganelli
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6.  PRRT neuroendocrine tumor response monitored using circulating transcript analysis: the NETest.

Authors:  Lisa Bodei; Mark S Kidd; Aviral Singh; Wouter A van der Zwan; Stefano Severi; Ignat A Drozdov; Anna Malczewska; Richard P Baum; Dik J Kwekkeboom; Giovanni Paganelli; Eric P Krenning; Irvin M Modlin
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