Isolated Peptide from Spider Venom Modulates Dendritic Cells In Vitro: A Possible Application in Oncoimmunotherapy for Glioblastoma
Bibliographic record
Abstract
Dendritic cells (DCs) vaccine is a potential tool for oncoimmunotherapy. However, it is known that this therapeutic strategy has failed in solid tumors, making the development of immunoadjuvants highly relevant. Recently, we demonstrated that Phoneutria nigriventer spider venom (PnV) components are cytotoxic to glioblastoma (GB) and activate macrophages for an antitumor profile. However, the effects of these molecules on the adaptive immune response have not yet been evaluated. This work aimed to test PnV and its purified fractions in DCs in vitro. For this purpose, bone marrow precursors were collected from male C57BL6 mice, differentiated into DCs and treated with venom or PnV-isolated fractions (F1—molecules < 3 kDa, F2—3 to 10 kDa and F3—>10 kDa), with or without costimulation with human GB lysate. The results showed that mainly F1 was able to activate DCs, increasing the activation-dependent surface marker (CD86) and cytokine release (IL-1β, TNF-α), in addition to inducing a typical morphology of mature DCs. From the F1 purification, a molecule named LW9 was the most effective, and mass spectrometry showed it to be a peptide. The present findings suggest that this molecule could be an immunoadjuvant with possible application in DC vaccines for the treatment of GB.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".