Abstract B125: Neutralizing acidosis with L-DOS47 urease immunoconjugate enhances responses to anti-PD1 checkpoint blockade in a preclinical orthotopic model of pancreatic adenocarcinoma
Bibliographic record
Abstract
Abstract Background: Acidosis in the tumor microenvironment is an important immunosuppressive mechanism that leads to tumor growth. We have shown that neutralization of tumor pH using sodium bicarbonate improves responses to immune checkpoint blockade (ICB) in pre-clinical models, but phase I/IIa clinical trials failed due to poor patient compliance. Thus, we aimed to test clinically translatable agents to neutralize tumor acidity and improve cancer outcomes in response to ICB. We tested L-DOS47, a targeted urease immunoconjugate designed to directly neutralize tumor acidity that has been well-tolerated in phase I/IIa trials. The nanobody component of L-DOS47 binds carcinoembryonic antigen cell adhesion molecule 6 (CEACAM6), a cell surface protein highly expressed in gastrointestinal and lung cancers; the urease moiety cleaves endogenous urea into two NH4+ and one CO2 thereby raising local pH. Materials and Methods: Immunohistochemistry screening for CEACAM6 expression and L-DOS47 binding was performed on tumor microarrays from pancreatic ductal adenocarcinoma (PDAC) cases (n=10 plus 2 normal tumor adjacent cases). We established a preclinical in vivo PDAC model by orthotopically inoculating human CEACAM6-expressing KPC961 into immunocompetent mice. Pharmacodynamic studies were performed using chemical exchange saturation transfer-magnetic resonance imaging (CEST-MRI) to measure tumor extracellular pH (pHe) at baseline (pre-L-DOS47) and at various time points post-L-DOS47 (4, 18, 24, 48, 72 and 96 hours). Mean tumor pHe and histograms of pHe distributions were compared among groups. Additional biological replicates were conducted to assess therapeutic efficacy. For these experiments, mice were randomized, after measurable tumors are established, into groups with equal tumor volume averages to initiate twice-weekly therapies with 300 µg anti-PD1 or 90 µg/kg L-DOS47 monotherapies, 300 µg anti-PD1 + 90 µg/kg L-DOS47 compared to a control group receiving no therapy. Tumor volumes were measured weekly by ultrasound imaging up to 4 weeks. Results: Immunohistochemistry screening of patient tumor microarrays confirmed high CEACAM6 expression and L-DOS47 binding to PDAC tissues. CEST-MRI results showed that L-DOS47 increased tumor pHe from 4h to 96h post-injection; however, pHe increases were only evident in tumors with baseline pHe ≤ 6.60. Efficacy studies in the PDAC model showed that the combination of anti-PD1 + L-DOS47 significantly reduced tumor growth when compared with control, L-DOS47 and anti-PD1 groups at week 3 (p<.0001; <.0001 and 0.0368, respectively) and week 4 (p<.0001; <.0001 and 0.0142, respectively). Conclusion: These studies provide strong evidence that L-DOS47, by neutralizing acidic tumor pH, significantly improves responses to anti-PD1 immunotherapy. Citation Format: Bruna V Jardim-Perassi, Pietro Irrera, Dominique Abrahams, Christopher J Whelan, Matthew S Beatty, Samantha R Byrne, Andrew A Odeja, Dario L Longo, Young Ou, Kim Gaspar, Martin Koebel, Shari A Pilon-Thomas, Christof Boehler, Gabrielle M Siegers, Robert J Gillies, Arig A Ibrahim-Hashim. Neutralizing acidosis with L-DOS47 urease immunoconjugate enhances responses to anti-PD1 checkpoint blockade in a preclinical orthotopic model of pancreatic adenocarcinoma [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B125.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 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".