The RAS/Raf1/MEK/ERK Signaling Pathway Facilitates VSV-mediated Oncolysis: Implication for the Defective Interferon Response in Cancer Cells
Bibliographic record
Abstract
Vesicular stomatitis virus (VSV) can replicate in malignant cells more efficiently than in normal cells. Although the selective replication appears to be caused by defects in the interferon (IFN) system in malignant cells, the mechanisms which render these cells less responsive to IFN remain poorly understood. Here we present evidence that an activated RAS/Raf1/MEK/ERK pathway plays a critical role in the defects. NIH 3T3 or human primary cells stably expressing active RAS or Raf1 were rapidly killed by VSV. Although IFNalpha treatment no longer protected the RAS- or Raf1-overexpressing cells from VSV infection, responsiveness to IFNalpha was restored following treatment with the mitogen-activated protein kinase kinase (MEK) inhibitor U0126. Similarly, human cancer-derived cell lines became more responsive to IFNalpha in conjunction with U0126 treatment. Intriguingly, dual treatment with both IFNalpha and U0126 severely reduced the levels of viral RNAs in the infected cells. Moreover, cancer cells showed defects in inducing an IFNalpha-responsive factor, MxA, which is known to block VSV RNA synthesis, and U0126 restored the MxA expression. Our observations suggest that activation of the extracellular signal-regulated protein kinase (ERK) signaling leads to the defect in IFNalpha-mediated upregulation of MxA protein, which facilitates VSV oncolysis. In view of the fact that 30% of all cancers have constitutive activation of the RAS/Raf1/MEK/ERK pathway, VSV would be an ideal oncolytic virus for targeting such cancers.
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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 | 0.000 |
| 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".