Tumor-derived exosomes: the next generation of promising cell-free vaccines in cancer immunotherapy
Bibliographic record
Abstract
Identification of immunogenic tumor antigens that are efficiently processed and delivered by dendritic cells to prime the immune system and to induce an appropriate immune response is a research hotspot in the field of cancer vaccine development. High biosafety is an additional demand. Tumor-derived exosomes (TEXs) are nanosized lipid bilayer encapsulated vesicles that shuttle bioactive information to the tumor microenvironment facilitating tumor progression. However, accumulating evidence points toward the capacity of TEXs to efficiently stimulate immune responses against tumors provided they are appropriately administered. After briefly describing the function of exosomes in cancer biology and their communication with immune cells, we summarize in this review in vitro and preclinical studies eliciting the potency of TEXs in inducing effective anti-tumor responses and recently modified strategies further improving TEX-vaccination efficacy. We interpret the available data as TEXs becoming a lead in cancer vaccination based on tumor antigen-selective high immunogenicity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".