Direct AKT activation in tumor-infiltrating lymphocytes markedly increases interferon-γ (IFN-γ) for the regression of tumors resistant to PD-1 checkpoint blockade
Bibliographic record
Abstract
Abstract PD-1 immune checkpoint blockade against inhibitory receptors such as receptor programmed cell death-1 (PD-1), has revolutionized cancer treatment. Effective immune reactivity against tumour antigens requires the infiltration and activation of tumour-infiltrating T-cells (TILs). In this context, ligation of the antigen-receptor complex (TCR) in combination with the co-receptor CD28 activates the intracellular mediator AKT (or PKB, protein kinase B) and its downstream targets. PD-1 inhibits the activation of AKT/PKB. Given this, we assessed whether the direct activation of AKT might be effective in activating the immune system to limit the growth of tumors that are resistant to PD-1 checkpoint blockade. We found that the small molecule activator of AKT (SC79) limited growth of a B16 tumor and an EMT-6 syngeneic breast tumor model that are poorly responsive to PD-1 immunotherapy. In the case of B16 tumors, direct AKT activation induced (i) a reduction of suppressor regulatory (Treg) TILs and (ii) an increase in effector CD8+ TILs. SC79 in vivo therapy caused a major increase in the numbers of CD4+ and CD8+ TILs to express interferon-γ (IFN-γ). This effect on IFN-γ expression distinguished responsive from non-responsive anti-tumor responses and could be recapitulated ex vivo with human T-cells. In CD4+FoxP3+Treg TILs, AKT induced IFN-γ expression was accompanied by a loss of suppressor activity, the conversation to CD4+ helper Th1-like TILs and a marked reduction in phospho-SHP2. In CD8+ TILs, we observed an increase in the phospho-activation of PLC-γ. Further, the genetic deletion of the transcription factor T-bet (Tbx21) blocked the increased IFN-γ expression on all subsets while ablating the therapeutic benefits of SC79 on tumor growth. Our study shows that AKT activation therapy acts to induce IFN-γ on CD4 and CD8 TILs that is accompanied by the intra-tumoral conversation of suppressive Tregs into CD4+Th1-like T-cells and augmented CD8 responses.
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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) | 0.002 | 0.001 |
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".