Heterologous prime-boost cellular vaccination induces potent antitumor immunity against triple negative breast cancer
Bibliographic record
Abstract
Introduction: Triple negative breast cancer (TNBC) is the most aggressive and hard-to-treat subtype of breast cancer, affecting 10-20% of all women diagnosed with breast cancer. Surgery, chemotherapy and hormone/Her2 targeted therapies are the cornerstones of treatment for breast cancer, but women with TNBC do not benefit from these treatments. Although the prognosis is dismal, immunotherapies hold significant promise in TNBC, even in wide spread disease because TNBC is infiltrated with more immune cells. This preclinical study is proposing to optimize an oncolytic virus-infected cell vaccine (ICV) based on a prime-boost vaccination strategy to address this unmet clinical need. Methods: We used various classes of immunomodulators to improve the immunogenicity of whole tumor cells in the prime vaccine, followed by their infection with oncolytic Vesicular Stomatitis Virus (VSVd51) to deliver the boost vaccine. For in vivo studies, we compared the efficacy of a homologous prime-boost vaccination regimen to a heterologous strategy by treating 4T1 tumor bearing BALB/c mice and further by conducting re-challenge studies to evaluate immune memory responses in surviving mice. Due to the aggressive nature of 4T1 tumor spread (akin to stage IV TNBC in human patients), we also compared early surgical resection of primary tumors versus later surgical resection combined with vaccination. Results: results demonstrated that immunogenic cell death (ICD) markers and pro-inflammatory cytokines were released at the highest levels following treatment of mouse 4T1 TNBC cells with oxaliplatin chemotherapy and influenza vaccine. These ICD inducers also contributed towards higher dendritic cell recruitment and activation. With the top ICD inducers at hand, we observed that treatment of TNBC-bearing mice with the influenza virus-modified prime vaccine followed by VSVd51 infected boost vaccine resulted in the best survival. Furthermore, higher frequencies of both effector and central memory T cells along with a complete absence of recurrent tumors were observed in re-challenged mice. Importantly, early surgical resection combined with prime-boost vaccination led to improved overall survival in mice. Conclusion: Taken together, this novel cancer vaccination strategy following early surgical resection could be a promising therapeutic avenue for TNBC patients.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".