Skip to main content
SpringerLink
Log in

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

  • Original Article
  • Published:
European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

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%.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Modlin IM, Oberg K, Chung DC, Jensen RT, de Herder WW, Thakker RV, et al. Gastroenteropancreatic neuroendocrine tumours. Lancet Oncol. 2008;9:61–72.

  2. Pavel M, Valle JW, Eriksson B, Rinke A, Caplin M, Chen J, et al. ENETS consensus guidelines for the standards of care in neuroendocrine neoplasms: systemic therapy - biotherapy and novel targeted agents. Neuroendocrinology. 2017;105:266–80.

    Article  PubMed  CAS  Google Scholar 

  3. Faggiano A, Lo Calzo F, Pizza G, Modica R, Colao A. The safety of available treatments options for neuroendocrine tumors. Expert Opin Drug Saf. 2017;16:1149–61.

    Article  PubMed  CAS  Google Scholar 

  4. Oberg K, Krenning E, Sundin A, Bodei L, Kidd M, Tesselaar M, et al. A Delphic consensus assessment: imaging and biomarkers in gastroenteropancreatic neuroendocrine tumor disease management. Endocrine connections. 2016;5:174–87.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Bodei L, Kwekkeboom DJ, Kidd M, Modlin IM, Krenning EP. Radiolabeled Somatostatin analogue therapy of gastroenteropancreatic cancer. Semin Nucl Med. 2016;46:225–38.

    Article  PubMed  Google Scholar 

  6. Cives M, Strosberg J. Radionuclide therapy for Neuroendocrine tumors. Curr Oncol Rep. 2017;19:9.

    Article  PubMed  CAS  Google Scholar 

  7. Brabander T, van der Zwan WA, Teunissen JJM, Kam BLR, Feelders RA, de Herder WW, et al. Long-term efficacy, survival, and safety of [177Lu-DOTA0,Tyr3]octreotate in patients with gastroenteropancreatic and bronchial neuroendocrine tumors. J Clin Oncol : Off J Am Assoc Cancer Res. 2017;23:4617–24.

    CAS  Google Scholar 

  8. Sansovini M, Severi S, Ambrosetti A, Monti M, Nanni O, Sarnelli A, et al. Treatment with the radiolabelled somatostatin analog Lu-DOTATATE for advanced pancreatic neuroendocrine tumors. Neuroendocrinology. 2013;97:347–54.

    Article  PubMed  CAS  Google Scholar 

  9. Ezziddin S, Khalaf F, Vanezi M, Haslerud T, Mayer K, Al Zreiqat A, et al. Outcome of peptide receptor radionuclide therapy with 177Lu-octreotate in advanced grade 1/2 pancreatic neuroendocrine tumours. Eur J Nucl Med Mol Imaging. 2014;41:925–33.

    Article  PubMed  CAS  Google Scholar 

  10. Mariniello A, Bodei L, Tinelli C, Baio SM, Gilardi L, Colandrea M, et al. Long-term results of PRRT in advanced bronchopulmonary carcinoid. Eur J Nucl Med Mol Imaging. 2016;43:441–52.

    Article  PubMed  CAS  Google Scholar 

  11. Strosberg J, El-Haddad G, Wolin E, Hendifar A, Yao J, Chasen B, et al. Phase 3 trial of 177Lu-Dotatate for midgut neuroendocrine tumors. N Engl J Med. 2017;376:125–35.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Kwekkeboom DJ, Kam BL, van Essen M, Teunissen JJ, van Eijck CH, Valkema R, et al. Somatostatin-receptor-based imaging and therapy of gastroenteropancreatic neuroendocrine tumors. Endocr Relat Cancer. 2010;17:R53–73.

    Article  PubMed  CAS  Google Scholar 

  13. Imhof A, Brunner P, Marincek N, Briel M, Schindler C, Rasch H, et al. Response, survival, and long-term toxicity after therapy with the radiolabeled somatostatin analogue [90Y-DOTA]-TOC in metastasized neuroendocrine cancers. J Clin Oncol. 2011;29:2416–23.

    Article  PubMed  CAS  Google Scholar 

  14. Sabet A, Dautzenberg K, Haslerud T, Aouf A, Sabet A, Simon B, et al. Specific efficacy of peptide receptor radionuclide therapy with (177)Lu-octreotate in advanced neuroendocrine tumours of the small intestine. Eur J Nucl Med Mol Imaging. 2015;42:1238–46.

    Article  PubMed  CAS  Google Scholar 

  15. Kwekkeboom DJ, de Herder WW, Kam BL, van Eijck CH, van Essen M, Kooij PP, et al. Treatment with the radiolabeled somatostatin analog [177 Lu-DOTA 0,Tyr3]octreotate: toxicity, efficacy, and survival. Clin Canc Res: Off J Am Assoc Cancer Res. 2008;26:2124–30.

    CAS  Google Scholar 

  16. Kidd M, Drozdov I, Modlin I. Blood and tissue neuroendocrine tumor gene cluster analysis correlate, define hallmarks and predict disease status. Endocr Relat Cancer. 2015;22:561–75.

    Article  PubMed  CAS  Google Scholar 

  17. Bodei L, Kidd M, Modlin IM, Severi S, Drozdov I, Nicolini S, et al. Measurement of circulating transcripts and gene cluster analysis predicts and defines therapeutic efficacy of peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors. Eur J Nucl Med Mol Imaging. 2016;43:839–51.

    Article  PubMed  CAS  Google Scholar 

  18. Ballman KV. Biomarker: predictive or prognostic? J Clin Oncol. 2015;33:3968–71.

    Article  PubMed  CAS  Google Scholar 

  19. Beaver JA, Tzou A, Blumenthal GM, McKee AE, Kim G, Pazdur R, et al. An FDA perspective on the regulatory implications of complex signatures to predict response to targeted therapies. Clin Cancer Res. 2017;23:1368–72.

    Article  PubMed  CAS  Google Scholar 

  20. Cwikla JB, Bodei L, Kolasinska-Cwikla A, Sankowski A, Modlin IM, Kidd M. Circulating transcript analysis (NETest) in GEP-NETs treated with Somatostatin analogs defines therapy. J Clin Endocrinol Metab. 2015;100:E1437–45.

    Article  PubMed  CAS  Google Scholar 

  21. Bodei L, Cremonesi M, Grana CM, Fazio N, Iodice S, Baio SM, et al. Peptide receptor radionuclide therapy with (177)Lu-DOTATATE: the IEO phase I-II study. Eur J Nucl Med Mol Imaging. 2011;38:2125–35.

    Article  PubMed  CAS  Google Scholar 

  22. Bosman FT. WHO classification of tumours of the digestive system. 4th ed. Lyon: IARC Press, 2010

    Google Scholar 

  23. Travis WD, Brambilla E, Muller-Hermelink HK, Harris CC (ed). Pathology and genetics of tumours of the lung, pleura, thymus and heart. Geneva: WHO Press, 2004

  24. Li XJ, Hayward C, Fong PY, Dominguez M, Hunsucker SW, Lee LW, et al. A blood-based proteomic classifier for the molecular characterization of pulmonary nodules. Sci Transl Med. 2013;5:207ra142.

    PubMed  PubMed Central  Google Scholar 

  25. Vachani A, Pass HI, Rom WN, Midthun DE, Edell ES, Laviolette M, et al. Validation of a multiprotein plasma classifier to identify benign lung nodules. J Thorac Oncol. 2015;10:629–37.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Kaijser J, Sayasneh A, Van Hoorde K, Ghaem-Maghami S, Bourne T, Timmerman D, et al. Presurgical diagnosis of adnexal tumours using mathematical models and scoring systems: a systematic review and meta-analysis. Hum Reprod Update. 2014;20:449–62.

    Article  PubMed  Google Scholar 

  27. Vickers AJ, Van Calster B, Steyerberg EW. Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests. BMJ. 2016;352:i6. https://doi.org/10.1136/bmj.i6.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Frank R, Hargreaves R. Clinical biomarkers in drug discovery and development. Nat Rev Drug Discov. 2003;2:566–80.

    Article  PubMed  CAS  Google Scholar 

  29. Oksuz MO, Winter L, Pfannenberg C, Reischl G, Mussig K, Bares R, et al. Peptide receptor radionuclide therapy of neuroendocrine tumors with (90)Y-DOTATOC: is treatment response predictable by pre-therapeutic uptake of (68)Ga-DOTATOC? Diagnos Interven Imaging 2014;95:289-300.

  30. Gabriel M, Oberauer A, Dobrozemsky G, Decristoforo C, Putzer D, Kendler D, et al. 68Ga-DOTA-Tyr3-octreotide PET for assessing response to somatostatin-receptor-mediated radionuclide therapy. J Nucl Med: Off Publ, Soc Nucl Med. 2009;50:1427–34.

    Article  CAS  Google Scholar 

  31. Blaickner M, Baum RP. Relevance of PET for pretherapeutic prediction of doses in peptide receptor radionuclide therapy. PET Clin. 2014;9:99–112.

    Article  PubMed  Google Scholar 

  32. Wu Y, Pfeifer AK, Myschetzky R, Garbyal RS, Rasmussen P, Knigge U, et al. Induction of Anti-Tumor Immune Responses by Peptide Receptor Radionuclide Therapy with (177)Lu-DOTATATE in a Murine Model of a Human Neuroendocrine Tumor. Diagnostics (Basel, Switzerland). 2013;3:344–55.

    Google Scholar 

  33. Yang Z, Tang LH, Klimstra DS. Effect of tumor heterogeneity on the assessment of Ki67 labeling index in well-differentiated neuroendocrine tumors metastatic to the liver: implications for prognostic stratification. Am J Surg Pathol. 2011;35:853–60.

    Article  PubMed  Google Scholar 

  34. Sansovini M, Severi S, Ianniello A, Nicolini S, Fantini L, Mezzenga E, et al. Long-term follow-up and role of FDG PET in advanced pancreatic neuroendocrine patients treated with 177Lu-D OTATATE. Eur J Nucl Med Mol Imaging. 2017;44:490–9.

    Article  PubMed  CAS  Google Scholar 

  35. Ezziddin S, Attassi M, Yong-Hing CJ, Ahmadzadehfar H, Willinek W, Grunwald F, et al. Predictors of long-term outcome in patients with well-differentiated gastroenteropancreatic neuroendocrine tumors after peptide receptor radionuclide therapy with 177Lu-octreotate. J Nucl Med. 2014;55:183–90.

    Article  PubMed  CAS  Google Scholar 

  36. Ezziddin S, Sabet A, Heinemann F, Yong-Hing CJ, Ahmadzadehfar H, Guhlke S, et al. Response and long-term control of bone metastases after peptide receptor radionuclide therapy with (177)Lu-octreotate. J Nucl Med. 2011;52:1197–203.

    Article  PubMed  Google Scholar 

  37. Haug AR, Auernhammer CJ, Wangler B, Schmidt GP, Uebleis C, Goke B, et al. 68Ga-DOTATATE PET/CT for the early prediction of response to somatostatin receptor-mediated radionuclide therapy in patients with well-differentiated neuroendocrine tumors. J Nucl Med: Off Publ, Soc Nucl Med. 2010;51:1349–56.

    Article  CAS  Google Scholar 

  38. Yang Z, Tang LH, Klimstra DS. Gastroenteropancreatic neuroendocrine neoplasms: historical context and current issues. Semin Diagn Pathol. 2013;30:186–96.

    Article  PubMed  Google Scholar 

  39. Valli A, Rodriguez M, Moutsianas L, Fischer R, Fedele V, Huang HL, et al. Hypoxia induces a lipogenic cancer cell phenotype via HIF1alpha-dependent and -independent pathways. Oncotarget. 2015;6:1920–41.

    Article  PubMed  Google Scholar 

  40. Olsson AH, Yang BT, Hall E, Taneera J, Salehi A, Nitert MD, et al. Decreased expression of genes involved in oxidative phosphorylation in human pancreatic islets from patients with type 2 diabetes. Eur J Endocrinol. 2011;165:589–95.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Day TF, Mewani RR, Starr J, Li X, Chakravarty D, Ressom H, et al. Transcriptome and proteome analyses of TNFAIP8 knockdown cancer cells reveal new insights into molecular determinants of cell survival and tumor progression. Methods Mol Biol. 2017;1513:83–100.

    Article  PubMed  CAS  Google Scholar 

  42. Hill RP. The changing paradigm of tumour response to irradiation. Br J Radiol. 2017;90:20160474.

    Article  PubMed  Google Scholar 

  43. Kidd M, Modlin IM. Therapy: the role of liquid biopsies to manage and predict PRRT for NETs. Nat Rev Gastroenterol Hepatol. 2017;14:331–2.

    Article  PubMed  Google Scholar 

Download references

Funding

Work was performed with an unrestricted grant from the LuGenIum consortium of independent research.

Author information

Authors and Affiliations

  1. Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box 77, New York, NY, 10065, USA

    Lisa Bodei

  2. LuGenIum Consortium, Milan, Rotterdam, London, Bad Berka, 54 Portland Place, London, W1B1DY, UK

    Lisa Bodei, Richard P. Baum, Dik J. Kwekkeboom, Eric P. Krenning & Irvin M. Modlin

  3. Wren Laboratories, Branford, CT, USA

    Mark S. Kidd & Ignat A. Drozdov

  4. Theranostics Center for Molecular Radiotherapy and Imaging, Zentralklinik Bad Berka, Bad Berka, Germany

    Aviral Singh & Richard P. Baum

  5. Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands

    Wouter A. van der Zwan & Dik J. Kwekkeboom

  6. Nuclear Medicine and Radiometabolic Units, Instituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, Italy

    Stefano Severi & Giovanni Paganelli

  7. University of Warmia and Mazury, Olsztyn, Poland

    Jaroslaw Cwikla

  8. Cyclotron Rotterdam BV, Erasmus University Medical Center, Rotterdam, The Netherlands

    Eric P. Krenning

  9. Yale School of Medicine, New Haven, USA

    Irvin M. Modlin

Authors
  1. Lisa Bodei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mark S. Kidd
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aviral Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wouter A. van der Zwan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Stefano Severi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ignat A. Drozdov
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jaroslaw Cwikla
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Richard P. Baum
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Dik J. Kwekkeboom
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Giovanni Paganelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Eric P. Krenning
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Irvin M. Modlin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lisa Bodei.

Ethics declarations

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all participants in the study.

Conflict of interest

LB and GP have received consultancy fees from Ipsen and Advanced Accelerator Applications (AAA). EPK and DJK received support from AAA outside the submitted work. MK is employed by Wren Laboratories that undertook the molecular testing. IMM is a consultant for Wren Laboratories. All others have nothing to disclose.

Electronic supplementary material

ESM 1

(DOCX 367 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bodei, L., Kidd, M.S., Singh, A. et al. PRRT genomic signature in blood for prediction of 177Lu-octreotate efficacy. Eur J Nucl Med Mol Imaging 45, 1155–1169 (2018). https://doi.org/10.1007/s00259-018-3967-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00259-018-3967-6

Keywords

Search

Navigation