Introduction of a new recombinant vaccine based on GRP78 for breast cancer immunotherapy and evaluation in a mouse model
Bibliographic record
Abstract
Introduction: Breast cancer is one of the most prevalent malignancies in women. Several treatment options are available today, including surgery, chemotherapy, and radiotherapy. Immunotherapy, as a highly specific therapy, involves adaptive immune responses and immunological memory. In our present research, we used the recombinant C-terminal domain of the GRP78 (glucose- regulated protein 78) protein to induce an immune response and investigate its therapeutic impact in the 4T1 breast cancer model. Methods: 4T1 tumor cells. Subsequently, tumor size and survival rate measurements, MTT, and cytokine assays were performed. Results: The animals receiving the cGRP78 vaccine showed significantly more favorable survival and slower tumor growth rates compared with unvaccinated tumor-bearing mice as the negative control mice. Circulating levels of tumoricidal cytokines such as IFNγ were higher, whereas tolerogenic cytokines such as IL-2, 6, and 10 either did not increase or had a decreasing trend in mice receiving cGRP78. Conclusion: cGRP78 vaccines generated potent immunotherapeutic effects in a breast cancer mouse model. This novel strategy of targeting the GRP78 protein can promote the development of cancer vaccines and immunotherapies for breast cancer malignancies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".