A Viral Vaccine Encoding Prostate-Specific Antigen Induces Antigen Spreading to a Common Set of Self-Proteins in Prostate Cancer Patients
Bibliographic record
Abstract
PURPOSE: We previously reported a randomized phase II clinical trial combining a poxvirus-based vaccine encoding prostate-specific antigen (PSA) with radiotherapy in patients with localized prostate cancer. Here, we investigate whether vaccination against PSA induced immune responses to additional tumor-associated antigens and how this influenced clinical outcome. EXPERIMENTAL DESIGN: Pretreatment and posttreatment serum samples from patients treated with vaccine + external beam radiation therapy (EBRT) versus EBRT alone were evaluated by Western blot and serologic screening of a prostate cancer cDNA expression library (SEREX) to assess the development of treatment-associated autoantibody responses. RESULTS: Western blotting revealed treatment-associated autoantibody responses in 15 of 33 (45.5%) patients treated with vaccine + EBRT versus 1 of 8 (12.5%) treated with EBRT alone. SEREX screening identified 18 antigens, which were assembled on an antigen array with 16 previously identified antigens. Antigen array screening revealed that 7 of 33 patients (21.2%) treated with vaccine + EBRT showed a vaccine-associated autoantibody response to four ubiquitously expressed self-antigens: DIRC2, NDUFS1, MRFAP1, and MATN2. These responses were not seen in patients treated with EBRT alone, or other control groups. Patients with autoantibody responses to this panel of antigens had a trend toward decreased biochemical-free survival. CONCLUSIONS: Vaccine + EBRT induced antigen spreading in a large proportion of patients. A subset of patients developed autoantibodies to a panel of four self-antigens and showed a trend toward inferior outcomes. Thus, cancer vaccines directed against tumor-specific antigens can trigger autoantibody responses to self-proteins, which may influence the efficacy of vaccination.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".