Abstract A154: Inhibition of eIF4E with Ribavirin suppresses EMT and breast cancer invasiveness.
Bibliographic record
Abstract
Abstract The eukaryotic translation initiation factor 4E (eIF4E) is an oncogene that drives cellular transformation, tumorigenesis and metastasis by facilitating nuclear export and translation of specific mRNAs, including cyclins, c-myc, matrix metalloproteinases (MMPs), VEGF and others. eIF4E is commonly overexpressed and/or activated in cancer, and we and others have shown that high eIF4E expression in primary and metastatic breast cancers correlates with poor prognosis. Recent studies have shown that Ribavirin, an old antiviral drug, can inhibit oncogenic transformation mediated by eIF4E and exert antitumor activity in cancer cell lines, animal models, and patients with acute myeloid leukemia (AML) that express elevated eIF4E. Dramatic clinical responses in AML correlated with reduced eIF4E level and activity. Ribavirin is thus the first drug to date with antitumor activity linked to direct inhibition of eIF4E in patients. In this study, we have evaluated the potential anti-metastatic activity of ribavirin. We first assessed the role of eIF4E in the epithelial-to-mesenchymal transition (EMT), a process enabling metastasis. We showed that either knockdown of eIF4E or Ribavirin treatment attenuate EMT induced by TGFβ in normal mammary epithelial cells, blocking the increase of mesenchymal markers as well as MMP-9 secretion and decreasing cell migration and invasion. We then studied the effects of eIF4E targeting on triple negative breast cancer cells in vitro and in vivo. We have previously shown that ribavirin suppresses breast cancer cell proliferation and this is associated with a decrease in known eIF4E targets. Using human and murine cell lines, we further observed a reduction in several mesenchymal markers, including N-cadherin, fibronectin and snail, following knockdown or chemical inhibition of eIF4E. Moreover, ribavirin significantly reduced tumor cell motility and invasion through Matrigel. Interestingly, overexpression of snail in MDA-MB-231 cells blunts their response to ribavirin, suggesting its involvement downstream of eIF4E. The activity of ribavirin against mammary tumors in vivo was assessed in two syngeneic mouse models, MT2186 and 66cl4, which form tumors in FVB and Balb/c mice, respectively. A non-toxic and clinically relevant dose of Ribavirin caused a striking reduction in MT2186 tumor growth, which correlated with reduced Ki-67 staining and reduced clonogenic potential of cells isolated from ribavirin treated tumors. Growth of the more aggressive and highly metastatic 66cl4 tumors was modestly affected; with only a slight delay in primary tumor growth. However, preliminary data suggest that ribavirin significantly suppresses the formation of 66cl4 lung metastases. Importantly, we measured MMP levels in plasma and found a selective increase in MMP-9 with growth of tumors over time, which was suppressed in the ribavirin treated mice. Future studies will further define the mechanism responsible for the anti-metastatic activity of ribavirin in this model. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):A154. Citation Format: Audrey Emond, Sonia V. Del Rincon, Bonnie Huor, Filippa Pettersson, Wilson H. Miller. Inhibition of eIF4E with Ribavirin suppresses EMT and breast cancer invasiveness. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr A154.
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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) | 0.003 | 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".