Abstract B032: Targeting the PD-1/PD-L1 immune evasion axis with DNA aptamers
Bibliographic record
Abstract
Abstract Blocking the immunoinhibitory PD-1:PD-L1 pathway using monoclonal antibodies has led to dramatic clinical responses by reversing tumor immune evasion and provoking robust and durable anti-tumor responses. Anti-PD-1 antibodies have now been approved for the treatment of melanoma, and are being clinically tested in a number of other tumor types as both a monotherapy and as part of combination regimens. Here, we report the development of DNA aptamers as synthetic, non-immunogenic antibody mimics, which bind specifically to the murine extracellular domain of PD-1 and block the PD-1:PD-L1 interaction. These aptamers did not bind to closely related proteins including human PD-1. One such aptamer, MP7, functionally inhibits the PD-L1-mediated suppression of IL-2 secretion in primary murine T-cells. A PEGylated form of MP7 retains the ability to block the PD-1:PD-L1 interaction, and significantly suppresses the growth of PD-L1+ colon carcinoma cells in-vivo with a potency equivalent to an antagonistic anti-PD-1 antibody. Importantly, the anti-PD-1 DNA aptamer treatment was not associated with off-target TLR-9-related immune responses. Due to the inherent advantages of aptamers including their lack of immunogenicity, low cost, long shelf life, and ease of synthesis, such PD-1 antagonistic aptamers may represent an attractive alternative over antibody-based anti PD-1 therapeutics. Citation Format: Aaron Prodeus, Jean Gariepy. Targeting the PD-1/PD-L1 immune evasion axis with DNA aptamers. [abstract]. In: Proceedings of the CRI-CIMT-EATI-AACR Inaugural International Cancer Immunotherapy Conference: Translating Science into Survival; September 16-19, 2015; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(1 Suppl):Abstract nr B032.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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; both teacher heads agree on what is shown here.
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".