Abstract 3106: Elucidating molecular mechanisms linking microRNA-206 loss to tumor progression and metastasis
Bibliographic record
Abstract
Abstract Metastasis is the leading cause of cancer-related deaths, and this occurs when tumor cells invade basement membranes and blood vessels to colonize other tissues. Metastasis is facilitated by extracellular matrix (ECM)-degrading structures called invadopodia. Recently, several microRNAs (miRNAs) have been identified as tumor and metastasis suppressor genes. Loss of expression of miR-206 has been correlated with poor prognosis in gastric cancer, breast cancer, rhabdomyosarcoma and melanoma. A previous study by others has demonstrated that restoring miR-206 expression in human breast cancer cells was sufficient to block metastasis in tumor xenograft assays. However, the targets of miR-206 that cause metastasis in these cancer models have not been fully characterized. Here, we have tested the effects of miR-206 on invadopodia in metastatic cancer cells, and identified a novel target that may explain this effect. Transducer of Cdc42-mediated Actin assembly-1 (Toca-1) is an adaptor protein that promotes formation of invadopodia and metastasis in breast cancer models, and has a predicted miR-206 binding site within the 3′ UTR of Toca-1 transcripts. To test whether the high levels of Toca-1 expression that we have observed in metastatic cancer cell lines was due to loss of miR-206, we rescued miR-206 expression using transient, stable or inducible approaches in MDA-MB-231 breast cancer, A375 melanoma, and H1299 lung cancer cell lines. In each cell model, Toca-1 expression was reduced upon miR-206 expression at both the mRNA and protein levels, thus validating Toca-1 as a new target of miR-206. Further testing of the phenotypes induced by miR-206 rescue revealed dramatic defects in ECM degradation and cell invasion in breast cancer and melanoma cell models. In subcutaneous tumor xenograft assays, stable rescue of miR-206 in H1299 tumors led to defects in tumor growth compared to those expressing a scrambled control miRNA. In addition, miR-206 expression caused a dramatic reduction in the numbers of lung metastases. We are currently extending this to our melanoma models and inducible models to define changes in metastasis-related targets of miR-206 that are aberrantly expressed in metastatic cancers. In conclusion, our study demonstrates for the first time a link between miR-206 and suppression of invadopodia formation via Toca-1 silencing, which likely contributes to the metastasis suppressing activity of miR-206 in multiple cancer types. Citation Format: Kathleen D. Watt, Peter Truesdell, Andrew W. Craig. Elucidating molecular mechanisms linking microRNA-206 loss to tumor progression and metastasis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3106. doi:10.1158/1538-7445.AM2015-3106
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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 | 0.001 |
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".