Abstract 5408: CD73 as a target in cancer immunotherapy
Bibliographic record
Abstract
Abstract It is increasingly being recognised that the tumor microenvironment modulates the effector functions of tumor-infiltrating lymphocytes and consequently suppresses anti-tumor immunity. One immunosuppressive component of the tumor microenvironment is elevated levels of adenosine. The conversion of ATP into adenosine occurs in a stepwise manner essentially through the enzymatic activity of CD39 (NTPDase I) (ATP>AMP) and CD73 (ecto-5′-nucleotidase- AMP>adenosine). CD73 is a glycosylphosphatidyl-inositol (GPI)-linked cell surface enzyme constitutively expressed on endothelial cells, foxp3+ Tregs and subsets of leukocytes, and is considered as the rate-limiting enzyme in the production of extracellular adenosine. We have recently demonstrated that one of the mechanisms contributing to the immunosuppressive accumulation of extracellular adenosine in tumors is the expression of CD73 by tumor cells, but CD73 expression on foxp3+ Tregs is also important for their suppression of anti-tumor immunity. We now report on the role of host-derived CD73 in de novo tumor development in mice. Combinations of anti-CD73 with agonist and T cell checkpoint blockade antibodies demonstrate significant beneficial effects in experimental and de novo models of tumorigenesis. In humans using large cohorts we have shown that CD73 is highest in triple negative breast cancer (TNBC) and expression correlates with an invasion marker and the lack of ER signalling. CD73 expression is also associated with a worse prognosis in TNBC irrespective of treatment and predicts response to anthracycline therapy. The development of CD73 as a target for cancer immunotherapy will be further discussed. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5408. doi:1538-7445.AM2012-5408
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".