Carcinoembryonic Antigen as a Target for Therapeutic Anticancer Vaccines: A Review
Bibliographic record
Abstract
PURPOSE: To describe the features of carcinoembryonic antigen (CEA) that are important for its use in vaccination approaches and review the clinical experience with therapeutic vaccines targeting CEA. METHODS: A PubMed search was performed on CEA, along with various qualifiers such as cancer vaccines, epitopes, and function. Relevant articles were reviewed. RESULTS: CEA is a member of the immunoglobulin supergene family and may play a role in tumorigenesis. CEA protein is processed and presented on major histocompatibility complex (MHC) proteins for multiple alleles, including HLA A2, A3, and A24. T lymphocytes from healthy volunteers and cancer patients can recognize the processed epitopes of CEA and can become activated to lyse CEA-expressing tumors. Therapeutic vaccination approaches that have targeted CEA include vaccination with recombinant CEA protein, CEA anti-idiotype antibodies, and dendritic cells pulsed with agonist epitopes of CEA. Humoral responses have predominantly been induced with the first two approaches, whereas CD4 and CD8 responses, disease stabilization, and even objective clinical responses have been seen with the dendritic cell approach. Recently, CEA-poxvirus vectors encoding CEA and costimulatory molecules such as B7.1 have been shown to be safe and to induce increases in the frequency of T-cell precursors that recognize processed epitopes of CEA presented on MHC class 1 molecules. Disease stabilization has been seen in up to 37% of patients treated with these vaccines. CONCLUSION: Tolerance to CEA in patients with cancer can be overcome with several different vaccination approaches, and such vaccinations are safe and immunologically active. Poxvirus-based vaccines can reproducibly generate T-cell responses to CEA and to tumors expressing CEA. Clinical activity has been seen with poxvirus or dendritic cell approaches. Other approaches are also being explored.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".