Deciphering the Immunomodulatory Capacity of Oncolytic Vaccinia Virus to Enhance the Immune Response to Breast Cancer
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Vaccinia virus (VACV) is a double-stranded DNA virus that devotes a large portion of its 200 kbp genome to suppressing and manipulating the immune response of its host. Here, we investigated how targeted removal of immunomodulatory genes from the VACV genome impacted immune cells in the tumor microenvironment with the intention of improving the therapeutic efficacy of VACV in breast cancer. We performed a head-to-head comparison of six mutant oncolytic VACVs, each harboring deletions in genes that modulate different cellular pathways, such as nucleotide metabolism, apoptosis, inflammation, and chemokine and interferon signaling. We found that even minor changes to the VACV genome can impact the immune cell compartment in the tumor microenvironment. Viral genome modifications had the capacity to alter lymphocytic and myeloid cell compositions in tumors and spleens, PD-1 expression, and the percentages of virus-targeted and tumor-targeted CD8+ T cells. We observed that while some gene deletions improved responses in the nonimmunogenic 4T1 tumor model, very little therapeutic improvement was seen in the immunogenic HER2/neu TuBo model with the various genome modifications. We observed that the most promising candidate genes for deletion were those that interfere with interferon signaling. Collectively, this research helped focus attention on the pathways that modulate the immune response in the context of VACV oncolytic virotherapy. They also suggest that the greatest benefits to be obtained with these treatments may not always be seen in “hot tumors.”
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it