HER2-Specific Vaccines for HER2-Positive Breast Cancer Immunotherapy
Bibliographic record
Abstract
Anti-human epidermal growth factor receptor-2 (HER2) immunization can be elicited by vaccination with DNA encoding the extra- or intra-cellular domain (ECD or ICD) of HER2, naked or encap-sulated in viral vectors. HER2-peptides derived from ECD or ICD of HER2, and HER2-pulsed dendritic cells (DCs) or engineered DCs expressing HER2, respectively. We performed a computer- based literature search which includes but is not limited to the following keywords: breast cancer, immunotherapy, HER2-peptide vaccine, HER2-DNA vaccine, HER-DC vaccine, HER2 vaccine, and HER2/neu, in PubMed, Medline, EMBO and Google Scholar; data from recently reported clinical trials were also included. Drawing upon this synthesis of literature, this work summarizes the de-velopment and current trend in experimental and clinical investigations in HER2-positive breast cancer using HER2-specific vaccine and immunotherapy, focusing especially on: (i) DNA-; (ii) peptide-; and (iii) DC-based vaccines. It addresses interventions that have been applied to overcome immunotolerance thereby to improve treatment outcomes. These include blocking the inhibitory cytotoxic T lymphocyte-associated protein-4 (CTLA-4), which is expressed at high levels by regulatory T (Treg) cells, or complete Treg depletion to improve T-cell activation. Moreover, modulatory interventions can provide further improvement in the efficacy of HER2-specific vaccine. The interventions include the use of immunogenic adjuvants such as cytokines interleukin-12 (IL-12), tumor necrosis factor (TNF)-α and granulocyte-macrophage colony-stimulating factor (GM-CSF), the use of Toll-like receptor (TLR) ligands and tetanus toxin’s universal epitopes such as the CD4+ help T (Th)-epitope P30, and the use of either chimeric or heterogenous xenogeneic HER2. Combining active HER2-vaccination with adoptive trastuzumab antibody immunotherapy is likely to increase the effectiveness of each approach alone. The development of effective HER2-vaccines for breast cancer remains a critical challenge. Though these novel interventions seem promising, further investigation is still needed since the results are preliminary. Furthermore, the review discusses the challenges and future perspectives in HER2-vaccine research and development.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".