Abstract A054: Anti-CTLA-4 generates memory T-cell with greater expansion and functionality than anti-PD-1
Bibliographic record
Abstract
Abstract Blocking either cytotoxic T-lymphocyte antigen-4 (CTLA-4) or programmed cell death-1 (PD-1) pathway results in distinct T-cell differentiation. We investigated the effects of anti-CTLA-4 and anti-PD-1 on memory T-cell formation in mice. Anti-CTLA-4 generates a more potent memory response than anti-PD-1. Memory T-cells generated by anti-CTLA-4 expand at a greater frequency, have greater cytokine production, and exhibit higher antitumor activity than those generated by anti-PD-1. These memory cells also more frequently differentiate into KLRG1+ effector CD8 T-cells during re-challenge. Additionally, anti-CTLA-4 generates more TCF-1+ memory-like T-cells, while anti-PD-1 results in more TOX+ terminally differentiated T-cells. Together, we provide insights into the long-term effects of these immunotherapies on the immune system. Citation Format: Stephen Mok, Huey Liu, Nana-Ama A.S. Anang, James J Mancuso, Didem Ağaç Çobanoğlu, James P Allison. Anti-CTLA-4 generates memory T-cell with greater expansion and functionality than anti-PD-1 [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A054.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".