Abstract 724: A novel heterologous prime boost vaccine system drives tumor specific and potent CD8 T cell responses for cancer immunotherapy
Bibliographic record
Abstract
Abstract Tumor-specific neoantigens (TSNAs) are present in a majority of tumor types and are key targets for T cells released by immune checkpoint blockade therapy. Given that TSNAs are non-self antigens, they are particularly attractive cancer vaccine targets. We have developed a potent heterologous prime/boost immunization approach to deliver predicted TSNAs to patients, which is comprised of a replication incompetent chimpanzee adenoviral vector (ChAdV) for the prime vaccination and a self-replicating, synthetic viral vector (srRNA) for repeated boost vaccinations. The ChAdV vector is similar in design to other adenoviral vectors that have demonstrated induction of high titer, polyfunctional and durable CD4 and CD8 T-cell responses against non-self antigens that protected humans against infections. The srRNA vector is based on Venezuelan equine encephalitis virus (VEE), where sequences encoding the structural proteins of VEE were deleted and replaced by a TSNA expression cassette. For delivery in vivo, the srRNA is formulated with a lipid nanoparticle (LNP), which facilitates efficient cellular uptake of the RNA and enhances antigen expression as well as the resulting immune response. We demonstrate that the srRNA vector effectively replicates in vitro and in vivo resulting in durable and high levels of antigen expression. To characterize the vectors in pre-clinical animal models, a prototypical expression cassette that encodes multiple mouse MHC class I tumor antigens as well as Mamu-A01 restricted class I antigens for monitoring immune responses in mice and non-human primates (NHPs) was introduced into both vector systems. We demonstrate that immunization of mice with either vector results in strong antigen-specific CD8 T-cell responses against the encoded murine epitopes. The heterologous prime/boost approach provided a statistically significant survival advantage to tumor bearing mice when compared to untreated mice. The potency of the immunization platform was also assessed in Indian rhesus macaques and the platform demonstrated a quick onset of T-cell responses 1 week post ChAdV prime vaccination with peak T-cell responses against all delivered Mamu-A01 restricted class I antigens at 2-3 weeks. Such ChAdV primed T-cell responses were effectively boosted by the LNP formulated srRNA vector. Co-administration of anti-CTLA4 with the vaccine demonstrated enhanced vaccine induced immune response. These data demonstrate that the heterologous prime/boost platform effectively programs robust T-cell immunity toward encoded non-self antigens in NHPs, which is a highly predictive model of vaccine responses in humans. This vaccine platform is targeted for entry into clinical trials in mid 2018. Citation Format: Wade Blair, Gijsbert Grotenbreg, Ciaran Scallan, Amy Rappaport, Renee Greer, Leonid Gitlin, Kieu Lam, James Heyes, Anne Van Abbema, Hadley Hanson, Petra Schreiner, karin Jooss. A novel heterologous prime boost vaccine system drives tumor specific and potent CD8 T cell responses for cancer immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 724.
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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) | 0.003 | 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".