Synthesis and Evaluation of Two Long-Acting SSTR2 Antagonists for Radionuclide Therapy of Neuroendocrine Tumors
Bibliographic record
Abstract
Somatostatin receptor subtype 2 (SSTR2) has become an essential target for radionuclide therapy of neuroendocrine tumors (NETs). JR11 was introduced as a promising antagonist peptide to target SSTR2. However, due to its rapid blood clearance, a better pharmacokinetic profile is necessary for more effective treatment. Therefore, two JR11 analogs (8a and 8b), each carrying an albumin binding domain, were designed to prolong the blood residence time of JR11. Both compounds were labeled with lutetium-177 and evaluated via in vitro assays, followed by in vivo SPECT/CT imaging and ex vivo biodistribution studies. [177Lu]Lu-8a and [177Lu]Lu-8b were obtained with high radiochemical purity (>97%) and demonstrated excellent stability in PBS and mouse serum (>95%). [177Lu]Lu-8a showed better affinity towards human albumin compared to [177Lu]Lu-8b. Further, 8a and 8b exhibited binding affinities 30- and 48-fold lower, respectively, than that of the parent peptide JR11, along with high cell uptake and low internalization rate. SPECT/CT imaging verified high tumor accumulation for [177Lu]Lu-8a and [177Lu]Lu-JR11 at 4, 24, 48, and 72 h post-injection, but no tumor uptake was observed for [177Lu]Lu-8b. Ex vivo biodistribution studies revealed high and increasing tumor uptake for [177Lu]Lu-8a. However, its extended blood circulation led to an unfavorable biodistribution profile for radionuclide therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".