The Immune “Combination Therapy” of Leukemia Using Adoptive Transfer and TGF-β Blockade.
Bibliographic record
Abstract
Abstract Abstract 3017 The immunosuppressive cytokine Transforming Growth factor-beta (TGF-β), either tumor or T cell-derived, can significantly alter T-dependent immune responses to tumors in mouse models. However, the role of TGF-β neutralization on other cell types of the tumor microenvironment and the ensuing impact on immunotherapies is still unclear. Moreover, pre-clinical models aimed at harnessing the likely synergy between TGF- β signaling blockade and immunotherapy are lacking. Using the TGF- β producing, acute lymphoblastic leukemia/lymphoma cell line EL4, we undertook to characterize how TGF-β affects the leukemic microenvironment and the outcome of adoptive immunotherapy. After inoculation, EL4 cells form large tumor masses that attract a wide variety of leukocytes, including mono-myeloid cells and T lymphocytes (5–10% of tumor cellularity). In order to assess whether TGF-β contributed to shape the leukemic microenvironment, we administered the pan anti-TGF-β antibody 1D11 or isotype control to EL4 bearing mice. Antibodies were administered after leukemic cell inoculation for a period of three weeks (300 μg three times a week). The systemic administration of 1D11 altered the EL-4 leukemia microenvironment. Notably, the concentration of inflammatory cytokines IL-2, GM-CSF and MIP-1α increased along with a trend in the abundance of CD44 positive CD4 T cells and myeloid cells infiltrating the tumors. However, the administration of anti-TGF-β antibody failed to alter tumor growth kinetics or vasculogenesis. These results 1) imply that the mobilization of immune effectors cells following TGF-β neutralization is insufficient and 2) correlate with our in vitro data which showed that TGF-β blockade have no impact on EL4 cells growth and apoptosis. Although insufficient by itself, could the use of TGF-β neutralizing strategies nonetheless improve the outcome of cancer immunotherapies? In order to investigate how inhibition of TGF-β signaling in the microenvironment can alter the outcome of adoptive immunotherapy, we designed an autologous adoptive immunotherapy model of leukemia. We have generated specific anti-EL4 responses using a vaccination and an in vitro restimulation system. Following in vitro stimulation with EL4 cells vs. splenocyte lysate, T cell effectors induced 34.42 % and 4.3% specific lysis respectively against EL4 targets. The injection of these effectors in sub-lethally irradiated leukemia bearing syngeneic hosts led to 50% survival at 120 days post adoptive transfer (n=6) compared to 0% survival in unprimed host. In order to assess whether concomitant TGF-β blockade improves this response, we are currently testing the in vivo efficacy of our strategy in the context of TGF-β neutralization in terms of survival and leukemia infiltration by T cells. The possibility to harness the combined effects of TGF- β signaling blockade and current immunotherapeutic approaches has immediate translational relevance given the numerous anti-TGF modalities currently being developed. Disclosures: No relevant conflicts of interest to declare.
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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) | 0.001 | 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) | 0.001 | 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 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".