Oncolytic influenza virus infection restores immunocompetence of lung tumor-associated alveolar macrophages
Bibliographic record
Abstract
Non-small-cell lung cancer (NSCLC) is the most frequent type of lung cancer and demonstrates high resistance to radiation and chemotherapy. These tumors evade immune system detection by promoting an immunosuppressive tumor microenvironment. Genetic analysis has revealed oncogenic activation of the Ras/Raf/MEK/ERK signaling pathway to be a hallmark of NSCLCs, which promotes influenza A virus (IAV) infection and replication in these cells. Thus, we aimed to unravel the oncolytic properties of IAV infection against NSCLCs in an immunocompetent model in vivo. Using Raf-BxB transgenic mice that spontaneously develop NSCLCs, we demonstrated that infection with low-pathogenic IAV leads to rapid and efficient oncolysis, eliminating 70% of the initial tumor mass. Interestingly, IAV infection of Raf-BxB mice caused a functional reversion of immunosuppressed tumor-associated lung macrophages into a M1-like pro-inflammatory active phenotype that additionally supported virus-induced oncolysis of cancer cells. Altogether, our data demonstrate for the first time in an immunocompetent in vivo model that oncolytic IAV infection is capable of restoring and redirecting immune cell functions within the tumor microenvironment of NSCLCs.
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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".