Radioimmunotherapy of PANC-1 human pancreatic cancer xenografts in NOD/SCID or NRG mice with Panitumumab labeled with Auger electron emitting, 111In or β-particle emitting, 177Lu
Bibliographic record
Abstract
Abstract Background Epidermal growth factor receptors (EGFR) are overexpressed on > 90% of pancreatic cancers (PnCa) and represent an attractive target for the development of novel therapies, including radioimmunotherapy (RIT). Our aim was to study RIT of subcutaneous (s.c.) PANC-1 human PnCa xenografts in mice using the anti-EGFR monoclonal antibody, panitumumab labeled with Auger electron (AE)-emitting, 111In or β-particle emitting, 177Lu at amounts that were non-toxic to normal tissues. Results Panitumumab was conjugated to DOTA chelators for complexing 111In or 177Lu (panitumumab-DOTA-[111In]In and panitumumab-DOTA-[177Lu]Lu) or to a metal-chelating polymer (MCP) with multiple DOTA to bind 111In (panitumumab-MCP-[111In]In). Panitumumab-DOTA-[177Lu]Lu was more effective per MBq exposure at reducing the clonogenic survival in vitro of PANC-1 cells than panitumumab-DOTA-[111In]In or panitumumab-MCP-[111In]In. Panitumumab-DOTA-[177Lu]Lu caused the greatest density of DNA double-strand breaks (DSBs) in the nucleus measured by immunofluorescence for γ-H2AX. The absorbed dose in the nucleus was 3.9-fold higher for panitumumab-DOTA-[177Lu]Lu than panitumumab-DOTA-[111In]In and 7.7-fold greater than panitumumab-MCP-[111In]In. No normal tissue toxicity was observed in NOD/SCID mice injected intravenously (i.v.) with 10.0 MBq (10 μg; ~ 0.07 nmoles) of panitumumab-DOTA-[111In]In or panitumumab-MCP-[111In]In or in NRG mice injected i.v. with 6.0 MBq (10 μg; ~ 0.07 nmoles) of panitumumab-DOTA-[177Lu]Lu. There was no decrease in complete blood cell counts (CBC) or increased serum alanine aminotransferase (ALT) or creatinine (Cr) or decreased body weight. RIT inhibited the growth of PANC-1 tumours but a 5-fold greater total amount of panitumumab-DOTA-[111In]In or panitumumab-MCP-[111In]In (30 MBq; 30 μg; ~ 0.21 nmoles) administered in three fractionated amounts every three weeks was required to achieve greater or equivalent tumour growth inhibition, respectively, compared to a single amount of panitumumab-DOTA-[177Lu]Lu (6 MBq; 10 μg; ~ 0.07 nmoles). The tumour doubling time (TDT) for NOD/SCID mice with s.c. PANC-1 tumours treated with panitumumab-DOTA-[111In]In or panitumumab-MCP-[111In]In was 51.8 days and 28.1 days, respectively. Panitumumab was ineffective yielding a TDT of 15.3 days vs. 15.6 days for normal saline treated mice. RIT of NRG mice with s.c. PANC-1 tumours with 6.0 MBq (10 μg; ~ 0.07 nmoles) of panitumumab-DOTA-[177Lu]Lu increased the TDT to 20.9 days vs. 11.5 days for panitumumab and 9.1 days for normal saline. The absorbed doses in PANC-1 tumours were 8.8 ± 3.0 Gy and 2.6 ± 0.3 Gy for panitumumab-DOTA-[111In]In and panitumumab-MCP-[111In]In, respectively, and 11.6 ± 4.9 Gy for panitumumab-DOTA-[177Lu]Lu. Conclusion RIT with panitumumab labeled with Auger electron-emitting, 111In or β-particle-emitting, 177Lu inhibited the growth of s.c. PANC-1 tumours in NOD/SCID or NRG mice, at administered amounts that caused no normal tissue toxicity. We conclude that EGFR-targeted RIT is a promising approach to treatment of PnCa.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".