Abstract 1726: A novel delivery platform containing up to 14 neoantigens can induce robust immune responses in a single formulation
Bibliographic record
Abstract
Abstract Neoantigens are emerging targets for personalized cancer vaccines that provide patient specific cancer immunotherapies. Many algorithms have been developed to select the most immunogenic neoantigens to include, however not all neoantigens chosen will generate equivalent immune responses, nor may they induce effective anti-tumour activity. To maximize immunological activity, selected peptides should be delivered simultaneously in a formulation that can stimulate potent, sustained immune responses to many different peptides. The DepoVaxTM platform is an oil-based system that uses lipids to incorporate many different types of antigens and adjuvants into a single formulation. Using a set of neoantigens identified from murine B16-F10 melanoma, we optimized a DepoVax formulation method that allows us to incorporate up to 14 neoantigens with a polynucleotide based adjuvant in a single formulation. These selected neoantigens irrespective of their solubility and hydrophobicity were formulated in DepoVax with the contents completely soluble in oil. C57BL/6 mice were vaccinated with 14 synthetic long peptide neoantigens (each 27 amino acids in length) prepared in DepoVax or in an aqueous formulation containing poly ICLC adjuvant. The immune responses were assessed eight days later by IFN-γ ELISPOT using splenocytes. Several of the peptides generated strong immune responses that were significantly higher in mice vaccinated with the DepoVax formulation compared to the aqueous formulation. To assess the contribution of CD8+ and CD4+ T cell responses, splenocytes from vaccinated mice were stimulated with an immunogenic peptide and intracellular IFN-γ/TNF-α producing CD8+ or CD4+ T cells were detected by flow cytometry. The highest production of TNF-α was detected by CD8+ T cells. Biological activity of the vaccines was assessed after one month storage at -20, 5 and 25 °C by IFN-γ ELISPOT assay; no significant difference was detected compared to the initial results. Analytical characterization of 14 peptides in DepoVax carried out using high-performance liquid chromatography (RP-HPLC), detected no significant chemical modifications or degradation of peptides after storage at -20 °C for up to 3 months compared to the initial results. These results demonstrate that the DepoVax platform can incorporate at least 14 neoantigens in a single formulation. Neoantigens formulated in DepoVax are stable for at least 3 months and our manufacturing method can incorporate peptides with a wide range of physical and chemical characteristics. This formulation generates strong CD8+ T cell responses, in excess of those induced by an aqueous formulation. The DepoVax platform is a promising solution to inducing robust immune responses to multiple neoantigens in a single formulation. Citation Format: Valarmathy Kaliaperumal, Genevieve Weir, Rajkannan Rajagopalan, Arthvan Sharma, Heather Torrey, Alecia MacKay, Ava Vila-Leahey, Cynthia Tram, Andrea Penwell, Leeladhar Sammatur, Marianne Stanford. A novel delivery platform containing up to 14 neoantigens can induce robust immune responses in a single formulation [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 1726.
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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 | 0.000 |
| 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".