Abstract 857: Anti-tumor and anti-metastatic activity of the eIF4E-targeted drug ribavirin in human and murine models of breast cancer.
Bibliographic record
Abstract
Abstract The eukaryotic translation initiation factor 4E (eIF4E) is an oncogene that facilitates nuclear export and translation of specific mRNAs, including cyclins, c-myc, VEGF, MMPs and others. eIF4E can thus promote cell survival as well as the aggressive tumor cell behavior associated with metastasis. We and others have shown that eIF4E is frequently overexpressed in primary and metastatic breast cancers, and high expression correlates with poor prognosis, especially in patients with luminal B-type tumors. Ribavirin is an old antiviral drug that has also been shown to inhibit eIF4E and to reduce the clonogenic potential of cancer cells with elevated eIF4E. Ribavirin inhibits nuclear export and/or translation of eIF4E mRNA targets both in vitro and in vivo. In patients with acute myeloid leukemias expressing elevated eIF4E, ribavirin caused dramatic clinical responses, which correlated with reduced eIF4E level and activity. We have shown that ribavirin inhibits proliferation of breast cancer cells in vitro and in vivo at clinically relevant and non-toxic concentrations. Tumor cells isolated from ribavirin treated mice have significantly reduced clonogenic potential and cell lines exposed to ribavirin show reduced ability to grow as mammospheres. In this study, we further investigated the effects of ribavirin on the metastatic activities of murine and human breast cancer cells. We used MT2186, a cell line derived from a mammary tumor that developed in a MMTV-PyMT transgenic mouse, as well as human cell lines known to form metastatic tumors in mice. We found that ribavirin potently suppresses cell motility and invasion. This was accompanied by reduced secretion of MMP2 and -9 by MT2186 cells. Ribavirin also reduced levels of phosphorylated eIF4E and Akt. We further assessed the effect of Ribavirin on a process that closely resembles metastasis, the epithelial-to-mesenchymal transition (EMT). Consistent with the ability of ribavirin to suppress migration and invasion of tumor cells, ribavirin inhibited TGF-β induced EMT in normal, immortalized mammary epithelial cells. Ribavirin reduced both TGF-β induced cell motility and the increased expression of several mesenchymal markers. These changes correlated with a loss of TGF-β induced eIF4E phosphorylation. Our data suggest that ribavirin acts independently of the transcriptional response to TGF-β, since phosphorylation of Smad2 remained intact. Importantly, we also found in our tumor cell lines that ribavirin reduced basal expression of key proteins involved in EMT. Taken together, our data suggest that inhibition of eIF4E with ribavirin may inhibit breast cancer metastasis by directly suppressing cell migration and invasion, and by preventing the transition of cells from an epithelial to a mesenchymal, more metastatic phenotype. A Phase I/II clinical trial of Ribavirin in patients with metastatic solid tumors is currently ongoing. Citation Format: Filippa Pettersson, Audrey Emond, Bonnie Huor, Sonia del Rincon, Wilson H. Miller. Anti-tumor and anti-metastatic activity of the eIF4E-targeted drug ribavirin in human and murine models of breast cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 857. doi:10.1158/1538-7445.AM2013-857
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".