Abstract PR010: Developing a safe and potent tumor-targeting gated CAR-T cell therapy for DIPG: A deadly pediatric brain tumor
Bibliographic record
Abstract
Abstract Background: DIPG (Diffuse Intrinsic Pontine Glioma) is an aggressive pediatric brain tumor that infiltrates the pons and is uniformly fatal. Curative surgery is not possible, radiation therapy provides only temporary relief, and chemotherapy is not effective. There is a great interest in applying Chimeric Antigen Receptor (CAR) expressing T cells and CAR-T cell strategies to solid tumors like DIPG; however, doing so will require novel approaches in CAR-T cell design to make this therapy effective. We recently identified CD99 as a highly expressed antigen in DIPG cells and an immunotherapy target in DIPG. A major obstacle in CAR-T cell therapy for solid tumors is the absence of true “tumor only” antigens, as most antigens are shared among multiple normal cells. CD99 is expressed in other normal cells. Therefore, combinatorial targeting of numerous antigens has the potential to overcome the lack of tumor-specific antigens. Hypothesis: Given that DIPG cells uniquely express the combination of B7-H3 and CD99 at high levels, we propose that CAR-T cells capable of specifically recognizing this combination will offer specificity to DIPG cells while safeguarding normal tissues expressing either antigen alone. We then developed a novel bicistronic CAR construct that employs Boolean logic to 'gate' the function of CAR-T cells according to 'AND' rules, where two distinct antigens are necessary for CAR-T cell activation. In our model, we used our novel CD99 CAR (based on 10D1-antibody-based ScFv) in conjunction with B7-H3 CAR (enoblituzumab antibody-based scFv). We created two 'AND' CAR-T cells using different co-stimulatory domains and successfully tested the specificity and functionality of our 'AND' CARs. Results: The “AND” CAR-T cells 1) showed enhanced tumor cell killing when co-cultured with DIPG tumor cells; 2) demonstrated no functionality against either single antigen-expressing cells, suggesting the specificity of the AND CAR-T in targeting dual-antigen-expressing tumor cells and 3) a single low dose of “AND” CAR-T cells delivered either IV or intrathecally completely cleared DIPG in the murine models with a significant increase in animal survival while either antigen targeting monovalent CAR-T cells showed only temporary clearance of tumor as the tumor relapsed after treatment. In addition, during the meeting, we will discuss the results obtained concerning the potency of the “AND” CARs developed against DIPG tumors. Topics will include the engineering design of the “AND” CAR-T cells to overcome CD99-driven fratricide, increased CAR-T persistence in vivo, and the mechanism behind the enhanced efficacy of our “AND” CAR-T cells against heterogeneously expressed tumor target antigens. Conclusion: The results from this study will significantly advance the development of effective immunotherapy for patients with DIPG. It emphasizes the importance of target antigen density heterogeneity and employs logic-gating to enhance tumor clearance and increase specificity, thereby reducing the risks associated with targeting shared antigens. Citation Format: Sujatha Venkataraman, Ilango Balakrishnan, Lillie Leach, Krishna Madhavan, Angela Pierce, Joshua Michlin, Joshua Obrecht, Breauna Brunt, Terry Fry, Rajeev Vibhakar, Eric.M Kohler. Developing a safe and potent tumor-targeting gated CAR-T cell therapy for DIPG: A deadly pediatric brain tumor [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr PR010.
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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) | 0.001 | 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".