Targeting CD73 Enhances the Antitumor Activity of Anti-PD-1 and Anti-CTLA-4 mAbs
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Bibliographic record
Abstract
PURPOSE: Monoclonal antibodies (mAb) that block programmed death (PD)-1 or cytotoxic T lymphocyte antigen (CTLA-4) receptors have been associated with durable clinical responses against a variety of cancer types and hold great potential as novel cancer therapeutics. Recent evidence suggest that targeted blockade of multiple immunosuppressive pathways can induce synergistic antitumor responses. EXPERIMENTAL DESIGN: In this study, we investigated whether targeted blockade of CD73, an ectonucleotidase that catabolizes the hydrolysis of extracellular adenosine monophosphate (AMP) to adenosine, can enhance the antitumor activity of anti-CTLA-4 and anti-PD-1 mAbs against transplanted and chemically induced mouse tumors. RESULTS: Anti-CD73 mAb significantly enhanced the activity of both anti-CTLA-4 and anti-PD-1 mAbs against MC38-OVA (colon) and RM-1 (prostate) subcutaneous tumors, and established metastatic 4T1.2 breast cancer. Anti-CD73 mAb also significantly enhanced the activity of anti-PD-1 mAb against 3-methylcholanthrene (MCA)-induced fibrosarcomas. Gene-targeted mice revealed that single-agent therapies and combinatorial treatments were dependent on host IFN-γ and CD8(+) T cells, but independent of perforin. Interestingly, anti-CD73 mAb preferentially synergized with anti-PD-1 mAb. We investigated the effect of extracellular adenosine on tumor-infiltrating T cells and showed that activation of A2A adenosine receptor enhances PD-1 expression, but not CTLA-4 expression, on tumor-specific CD8+ T cells and CD4+ Foxp3+ T regulatory cells. CONCLUSIONS: Taken together, our study revealed that targeted blockade of CD73 can enhance the therapeutic activity of anti-PD-1 and anti-CTLA-4 mAbs and may thus potentiate therapeutic strategies targeting immune checkpoint inhibitors in general.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it