Transcription factors down‐stream of Ras as molecular indicators for targeting malignancies with oncolytic herpes virus
Bibliographic record
Abstract
Overactivation in Ras signaling has been under intensive study as the molecular basis for development of cancer. Such overactivation can occur in the presence or absence of mutations in Ras gene resulting in activation of a series of down-stream effectors such as transcription factors. Different studies have shown the activation of Ras down-stream effectors in non-Hodgkin lymphoma (NHL) although mutations in Ras are not prevalent in this malignancy. Since overactivation in Ras signaling also increases permissiveness of cancer cells to infection by oncolytic versions of herpes simplex virus (e.g. R3616), we were interested in evaluating the value of transcription factors down-stream of Ras as molecular indicators for permissiveness to herpes therapy. In order to accomplish this, and also to assess the permissiveness of lymphoma cells to infection with R3616, we used NHL cell lines Daudi, Jurkat, NC37, Raji, Ramos and ST486. Once the levels of phosphorylation (activation) of extracellular-signal regulated kinase (ERK, a Ras effector pathway) and its down-stream transcription factor ELK were evaluated, Raji and NC37 showed a significant increase in the phosphorylation levels of both molecules while ATF2 (another transcription factor down-stream of p38-kinase pathway) seemed to be activated in all studied cells. Raji and NC37 cells were also most permissive cells to infection with R3616 while their permissiveness was decreased upon treatment of cells with an inhibitor of ELK-DNA binding portraying ERK/ELK as a suitable predictive indicator for selection of cancer cells with increased sensitivity to R3616. This study, therefore, for the first time documents permissiveness of lymphoma cells to oncolytic herpes viruses and introduces ELK as a suitable factor for predicting tumor susceptibility to these novel anticancer agents.
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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 | 0.000 | 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) | 0.000 | 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 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".