Sulfated Lactosyl Archaeol Archaeosomes Synergize with Poly(I:C) to Enhance the Immunogenicity and Efficacy of a Synthetic Long Peptide-Based Vaccine in a Melanoma Tumor Model
Bibliographic record
Abstract
Cancer remains a leading cause of morbidity and mortality worldwide. While novel treatments have improved survival outcomes for some patients, new treatment modalities/platforms are needed to combat a wider variety of tumor types. Cancer vaccines harness the power of the immune system to generate targeted tumor-specific immune responses. Liposomes composed of glycolipids derived from archaea (i.e., archaeosomes) have been shown to be potent adjuvants, inducing robust, long-lasting humoral and cell-mediated immune responses to a variety of antigens. Herein, we evaluated the ability of archaeosomes composed of sulfated lactosyl archaeol (SLA), a semi-synthetic archaeal glycolipid, to enhance the immunogenicity of a synthetic long peptide-based vaccine formulation containing the dominant CD8+ T cell epitope, SIINFEKL, from the weakly immunogenic model antigen ovalbumin. One advantage of immunizing with long peptides is the ability to include multiple epitopes, for example, the long peptide antigen was also designed to include the immediately adjacent CD4+ epitope, TEWTSSNVMEER. SLA archaeosomes were tested alone or in combination with the toll-like receptor 3 (TLR3) agonist Poly(I:C). Overall, SLA archaeosomes synergized strongly with Poly(I:C) to induce robust antigen-specific CD8+ T cell responses, which were highly functional in an in vivo cytolytic assay. Furthermore, immunization with this vaccine formulation suppressed tumor growth and extended mouse survival in a mouse melanoma tumor model. Overall, the combination of SLA archaeosomes and Poly(I:C) appears to be a promising adjuvant system when used along with long peptide-based antigens targeting cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".