Peptide Receptor Radionuclide Therapy Targeting the Somatostatin Receptor: Basic Principles, Clinical Applications and Optimization Strategies
Abstract
:Simple Summary
Abstract
1. Peptide Receptor Radionuclide Therapy: Concept and Early Development
2. Current Evidence
2.1. Indications
2.2. Efficacy and Outcome
2.2.1. Response Assessment
2.2.2. 90Y-DOTATOC
2.2.3. 177Lu-DOTATATE
2.2.4. NETTER-1 Trial
2.2.5. Lung NET
2.3. Effect on Symptoms
3. Toxicity
4. Optimization
4.1. Dose-Effect Concept and Individualized Dosimetry
4.2. Combination Therapies
4.2.1. Tandem and Duo PRRT
4.2.2. ChemoPRRT
First Author | Design | n | Subtype | Setting | Compound | Chemo | ORR | DCR | CR | PR | MR | SD | PD | Criteria | Median PFS (mo) | Median OS (mo) | Grade 3/4 Hemato-Toxicity | Comments |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ballal [120] | R | 88 | Grade 1-2-3 GEP-CUP-other-NET/neural crest | Imaging progression/Biochemical progression | 177Lu-DOTATATE | capecitabine | 43% | 93% | 0% | 34% | 9.1% | 50% | 6.8% | RECIST 1.1 | NR | NR | 1% | |
Kong [119] | R | 63 | Grade 1-2 GEP-lung-thymus-CUP-NET | Biochemical or imaging progression > Uncontrolled symptoms | 177Lu-DOTATATE | 5-FU | 39% | 68% | 0% | 30% | 9% | 29% | 32% | RECIST 1.1 | NA | NR | NA | 63 of the 68 included patients received chemoPRRT (response rates did not differentiate between pt receiving monotherapy PRRT and chemoPRRT) |
Kashyap [123] | R | 52 | Grade 1-2-3 GEP-CUP-NET | Imaging or biochemical progression/Uncontrolled symptoms | 177Lu-DOTATATE | 5-FU | 30% | 98% | 2% | 28% | - | 68% | 2% | RECIST 1.1 | 48 | NR | 6% | FDG-positive disease |
Nicolini [124] | P | 37 | Grade 1-2-3 GEP-NET | Progressive metastatic or inoperable NETs | 177Lu-DOTATATE | capecitabine | 30% | 85 | 0% | 30% | - | 55% | 15% | RECIST 1.1 | 31 | NR | 16% | FDG-positive disease |
Claringbold [116] | P | 34 | Well-differentiated GEP-lung NET | Imaging progression/highly advanced metastatic disease and substantial symptoms | 177Lu-DOTATATE | CAPTEM | 53% | 91% | 15% | 38% | - | 38% | 9% | RECIST 1.1 | 31 | NR | 6% | Predominantly grade 1 NETs |
Claringbold [115] | P | 33 | Well- or moderately differentiated EP-lung-CUP NET | Imaging progression | 177Lu-DOTATATE | capecitabine | 24% | 94% | 0% | 24% | - | 70% | 6% | RECIST 1.1 | NR | NR | 3% | |
Claringbold [118] | P | 30 | Grade 1-2 pNET | Imaging progression | 177Lu-DOTATATE | CAPTEM | 80% | 100% | 13% | 67% | - | 20% | 0% | RECIST 1.1 | 48 | NR | 10% TBC 10% RBC |
4.2.3. Targeted Molecular Therapy
4.2.4. SSA
4.2.5. Radiosensitizers
4.3. Novel Vector Molecules and Radionuclides
4.3.1. Somatostatin Receptor Antagonists
4.3.2. Evans Blue
4.3.3. Alpha-Emitters
4.4. Administration through the Hepatic Artery
5. Response Prediction
5.1. Molecular Testing
5.2. Imaging
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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SSTR Affinity | |||||
---|---|---|---|---|---|
Somatostatin Analogue | SSTR 1 | SSTR 2 | SSTR 3 | SSTR 4 | SSTR 5 |
111In-DTPA-octreotide [5] | >10,000 | 22 ± 3.6 | 182 ± 13 | >1000 | 237 ± 52 |
90Y-DOTATOC [5] | >10,000 | 11 ± 1.7 | 389 ± 135 | >10,000 | 114 ± 29 |
90Y-DOTATATE [5] | >10,000 | 1.6 ± 0.4 | >1000 | 523 ± 239 | 187 ± 50 |
177Lu-DOTATATE [6] | >1000 | 2.0 ± 0.8 | 162 ± 16 | >1000 | >1000 |
177Lu-DOTA-JR11 [7] | >1000 | 0.73 ± 0.15 | >1000 | >1000 | >1000 |
First Author | Design | n | Subtype | Setting | Compound | ORR | DCR | CR | PR | MR | SD | PD | Criteria | Median PFS (mo) | Median OS (mo) | Comments |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Cohorts | ||||||||||||||||
Imhof [23] | P | 1109 | GEP-lung-other-CUP NET/neural crest | Disease progression | 90Y-DOTATOC | 34% | 39% | 1% | 34% | - | 5% | 61% | Simplified response criteria 1 | NA | NA | |
Brabander [45] | R | 443 | GEP-lung-other-CUP NET | Imaging progression/clinical progression/high tumor load | 177Lu-DOTATATE | 39% | 83% | 2% | 37% | - | 43% | 12% | RECIST 1.1 | 29 | 63 | |
Hörsch [46] | R + P | 450 | EP-lung-CUP-NEN | Progression/locally advanced disease/metastatic disease | 90Y/177Lu-DOTATOC/ DOTATATE | 35% | 95% | 7% | 28% | - | 59% | 5% | RECIST 1.1 | 41 | 59 | |
Kwekkeboom [47] | P | 310 | GEP-NET | Imaging progression 43%/Other | 177Lu-DOTATATE | 46% | 80% | 2% | 28% | 16% | 35% | 20% | SWOG | 33 | 46 | |
Garske-Roman [48] | P | 200 | GEP-lung-CUP-other NET/NEC/neural crest | Progression (81%) > first line treatment metastatic rectal NETs or bronchopulmonary carcinoids (19%) | 177Lu-DOTATATE | 24% | 92% | 1% | 24% | - | 68% | 4% | RECIST 1.1 | 27 | 43 | |
Hamiditabar [49] | P | 143 | GEP-lung-other-CUP NET/neural crest | Imaging progression | 177Lu-DOTATATE | 8% | 55% | 0% | 8% | - | 46% | 38% | RECIST | NR | NR | |
Mariniello [50] | R | 114 | lung-NET | Imaging progression (78%) > other | 90Y-DOTATOC/ 177Lu-DOTATATE/90Y-DOTATOC + 177Lu-DOTATATE | 27% | 67% | 0% | 13% | 13% | 41% | 33% | RECIST | 28 | 59 | |
Kunikowska [51] | R | 103 | EP-lung-CUP-other NET/neural crest | Metastatic, inoperable disease | 90Y-DOTATATE 177Lu-DOTATATE | 24% | 88% | 2% | 22% | - | 64% | 12% | RECIST 1.1 + SRS | 30 | 90 | Tandem PRRT |
Fröss-Baron [52] | R | 102 | pNET | Imaging progression (90%) > intolerance to previous therapies (8%) > pseudo-neoadjuvant (2%) | 177Lu-DOTATATE | 49% | 91% | 4% | 45% | - | 44% | 7% | RECIST 1.1 | 24 | 42 | |
Ezziddin [53] | R | 74 | GEP-NET | Imaging progression (76%) > clinical progression (22%) > uncontrolled disease under SSA (11%) | 177Lu-DOTATATE | 37% | 89% | 0% | 37% | 18% | 35% | 11% | mSWOG | 26 | 55 | |
Pfeifer [54] | R | 69 | GEP-lung-CUP NET | Imaging progression (81%) > intolerance previous therapies (19%) | 90Y-DOTATOC 177Lu-DOTATOC | 24% | 56% | 7% | 16% | - | 62% | 15% | RECIST | 29 | NR | |
Campana [55] | R of P database | 69 | GEP-NET | Imaging progression (51%)/advanced disease not suitable for radical surgery/residual disease after debulking surgery | 90Y-DOTATOC 177Lu-DOTATATE | 28% | 78% | 0% | 28% | - | 51% | 23% | RECIST | 28 | NA | |
Ezziddin [56] | R | 68 | pNET | Imaging progression (68%) > high tumor burden (19%) > clinical progression (13%) | 177Lu-DOTATATE | 60% | 85% | 0% | 60% | 12% | 13% | 15% | mSWOG | 34 | 53 | |
Sabet [57] | R | 61 | SI-NET | Imaging progression (75%) > clinical progression (25%) | 177Lu-DOTATATE | 13% | 92% | 0% | 13% | 31% | 48% | 8% | mSWOG | 33 | 61 | |
Sansovini [58] | P | 60 | pNET | Imaging progression/unresectable or metastatic disease | 177Lu-DOTATATE | 30% | 82% | 7% | 23% | - | 52% | 18% | SWOG | 29 | NR | |
Kunikowska [59] | P | 59 | EP-lung-CUP-other NET/neural crest | Clinical progression/imaging progression/ biochemical progression | 90Y-DOTATATE 177Lu-DOTATATE | 24% | 89% | 2% | 22% | - | 65% | 6% | RECIST 1.1 | 32 | 82 | Tandem PRRT |
Vinjamuri [60] | R | 57 | GEP-lung-other-CUP NET | Clinical progression (45%) > imaging progression (33%) > clinical and imaging progression (22%) | 90Y-DOTATOC 90Y-DOTATATE | 25% | 72% | 0% | 25% | - | 47% | 29% | RECIST | NA | 46 | |
Baum [61] | R | 56 | GEP-lung-CUP-other NET | Imaging progression | 177Lu-DOTATOC | 34% | 66% | 16% | 18% | - | 32% | 34% | RECIST 1.1 | 17 | 34 | |
Del Prete [62] | P | 52 | GEP-lung-CUP-NET/neural crest | Progressive and/or symptomatic NET | 177Lu-DOTATATE | 36% | 82% | 0% | 18% | 18% | 46% | 18% | RECIST 1.1 | 16 | NR | Only 11 patients were available for response assessment |
Bodei [63] | P | 51 | EP-lung-CUP NET/neural crest | Imaging progression > other | 177Lu-DOTATATE | 29% | 82% | 2% | 27% | 26% | 27% | 18% | RECIST | median TTP = 36 mo | NR | |
Zidan and Iravani [64] | R | 48 | lung-NET | Imaging progression (98%) > uncontrolled symptoms (2%) | 177Lu-DOTATATE | 20% | 88% | 0% | 20% | - | 68% | 12% | RECIST 1.1 | 23 | 59 | 33% patients received chemo-PRRT |
Paganelli [65,66] | P | 43 | GE-NET | Imaging progression | 177Lu-DOTATATE | 7% | 84% | 0% | 7% | - | 77% | 16% | SWOG | 60 | 82 | |
Pauwels [43] | R of P trial | 43 | GEP-CUP-other NET | Clinical/imaging progression | 90Y-DOTATOC | 0% | 55% | 0% | 0% | - | 55% | 45% | RECIST 1.1 | 14 | 22 | |
Ianniello [67] | P | 34 | lung-NET | Imaging progression | 177Lu-DOTATATE | 15% | 62% | 3% | 12% | - | 47% | 38% | SWOG | 19 | 49 | |
Zandee [68] | R | 34 | functioning pNET | Imaging progression (41%) > symptom reduction (27%) > imaging progression and symptom reduction (24%) > high tumor burden (9%) | 177Lu-DOTATATE | 59% | 78% | 3% | 56% | - | 24% | 18% | RECIST 1.1 | 18 | NA | 71% reduction of syndrome-specific symptoms after PRRT |
Zandee [69] | R | 30 | neural crest | Symptomatology/imaging progression/high tumor burden. | 177Lu-DOTATATE | 23% | 85% | 0% | 23% | - | 68% | 10% | RECIST 1.1 | 30 | NR | |
RCT | ||||||||||||||||
Strosberg [70,71] | RCT | 116 | midgut-NET | Imaging progression | 177Lu-DOTATATE | 18% | NA | 1% | 17% | - | NA | NA | RECIST 1.1 | NR | 48 |
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Ahmadi Bidakhvidi, N.; Goffin, K.; Dekervel, J.; Baete, K.; Nackaerts, K.; Clement, P.; Van Cutsem, E.; Verslype, C.; Deroose, C.M. Peptide Receptor Radionuclide Therapy Targeting the Somatostatin Receptor: Basic Principles, Clinical Applications and Optimization Strategies. Cancers 2022, 14, 129. https://doi.org/10.3390/cancers14010129
Ahmadi Bidakhvidi N, Goffin K, Dekervel J, Baete K, Nackaerts K, Clement P, Van Cutsem E, Verslype C, Deroose CM. Peptide Receptor Radionuclide Therapy Targeting the Somatostatin Receptor: Basic Principles, Clinical Applications and Optimization Strategies. Cancers. 2022; 14(1):129. https://doi.org/10.3390/cancers14010129
Chicago/Turabian StyleAhmadi Bidakhvidi, Niloefar, Karolien Goffin, Jeroen Dekervel, Kristof Baete, Kristiaan Nackaerts, Paul Clement, Eric Van Cutsem, Chris Verslype, and Christophe M. Deroose. 2022. "Peptide Receptor Radionuclide Therapy Targeting the Somatostatin Receptor: Basic Principles, Clinical Applications and Optimization Strategies" Cancers 14, no. 1: 129. https://doi.org/10.3390/cancers14010129
APA StyleAhmadi Bidakhvidi, N., Goffin, K., Dekervel, J., Baete, K., Nackaerts, K., Clement, P., Van Cutsem, E., Verslype, C., & Deroose, C. M. (2022). Peptide Receptor Radionuclide Therapy Targeting the Somatostatin Receptor: Basic Principles, Clinical Applications and Optimization Strategies. Cancers, 14(1), 129. https://doi.org/10.3390/cancers14010129