Membrane‐bound HSP70‐engineered myeloma cell‐derived exosomes stimulate more efficient CD8<sup>+</sup> CTL‐ and NK‐mediated antitumour immunity than exosomes released from heat‐shocked tumour cells expressing cytoplasmic HSP70
Bibliographic record
Abstract
Exosomes (EXO) derived from tumour cells have been used to stimulate antitumour immune responses, but only resulting in prophylatic immunity. Tumour-derived heat shock protein 70 (HSP70) molecules are molecular chaperones with a broad repertoire of tumour antigen peptides capable of stimulating dendritic cell (DC) maturation and T-cell immune responses. To enhance EXO-based antitumour immunity, we generated an engineered myeloma cell line J558(HSP) expressing endogenous P1A tumour antigen and transgenic form of membrane-bound HSP70 and heat-shocked J558(HS) expressing cytoplasmic HSP70, and purified EXO(HSP) and EXO(HS) from J558(HSP) and J558(HS) tumour cell culture supernatants by ultracentrifugation. We found that EXO(HSP) were able to more efficiently stimulate maturation of DCs with up-regulation of Ia(b) , CD40, CD80 and inflammatory cytokines than EXO(HS) after overnight incubation of immature bone-marrow-derived DCs (5 × 10⁶ cells) with EXO (100 μg), respectively. We also i.v. immunized BALB/c mice with EXO (30 μg/mouse) and assessed P1A-specific T-cell responses after immunization. We demonstrate that EXO(HSP) are able to stimulate type 1 CD4(+) helper T (Th1) cell responses, and more efficient P1A-specific CD8(+) cytotoxic T lymphocyte (CTL) responses and antitumour immunity than EXO(HS) . In addition, we further elucidate that EXO(HSP) -stimulated antitumour immunity is mediated by both P1A-specific CD8(+) CTL and non-P1A-specific natural killer (NK) responses. Therefore, membrane-bound HSP70-expressing tumour cell-released EXO may represent a more effective EXO-based vaccine in induction of antitumour immunity.
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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 | 0.000 |
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 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".