Comparison of radiolabeled somatostatin receptor agonist and antagonists in a mouse model of human breast cancer
Bibliographic record
Abstract
1051 Objectives High expression of somatostatin receptor subtype 2a has been shown in a various malignancies including neuroendocrine tumors and breast cancer. Most of reported studies for imaging SST2a expression used mice bearing tumors derived from SST2a transfected cell lines and rat pancreatic cancer cell line (AR42J). The objective of this study was to compare and evaluate 68Ga-DOTA-TATE, 68Ga-NOTA-BASS and 68Ga-NODAGA-LM3 as potent SSt2a agonist and antagonists in a murine model of human breast cancer. Methods 68Ga labeling was performed in HEPES buffer (pH 5.1) via microwave heating for 1 min, followed by HPLC purification. In vitro binding assays were performed using human breast cancer (Zr-75-1) membranes. ZR-75-1 cells were inoculated subcutaneously in NSG mice and dynamic PET/CT imaging and biodistribution studies were carried 1h post injection. Blocking studies were performed to determine the specificity of radioligand to the receptors. Results The radiolabeling yield and purity were more than 99%. Ga-DOTA-TATE showed a high binding affinity of 0.6 nM compared to two other peptides (68Ga-NOTA-BASS 158 nM; 68Ga-NODAGA-LM3 10.7 nM). In vivo studies showed low tumor uptake in 68Ga-NOTA-BASS. Excellent tumor visualization with low background at 1 h post-injection were observed with 68Ga-DOTA-TATE and 68Ga-NODAGA-LM3 with %ID/g of 21 ± 4.2 and 24.4 ± 7.8 respectively. %ID/g of pancreas was higher (31.3 ± 19%) in 68Ga-DOTA-TATE. In blocking studies, the uptake in tumors and pancreas were reduced by >90%. Tumor-to-blood and Tumor-to-muscle ratios were 33 and 52%ID/g respectively with 68Ga-DOTA-TATE and 30 and 41%ID/g with 68Ga-NODAGA-LM3. Conclusions A high tumor to background ratio was achieved in Zr-75-1 tumor model with both 68Ga-DOTA-TATE and 68Ga-NODAGA-LM3 imaging. Despite similar absolute tumor uptake, the tumor-to-muscle ratio of 68Ga-DOTA-TATE was higher than 68Ga-NODAGA-LM3. The ZR-75 human tumor cell line is a promising breast cancer model for SST imaging by PET.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".