Abstract 3418: Regulation of Dicer expression by Sox4 and its role in melanoma cell invasion and patient survival
Bibliographic record
Abstract
Abstract Deregulated expression of Sox4 transcription factor has been observed in various types of cancers. We previously reported reduced expression of Sox4 in metastatic melanoma and its role in suppression of cell migration and invasion. We also demonstrated binding of Sox4 to the promoter sequence of Dicer, an RNase involved in maturation of miRNAs. Interestingly, altered expression of Dicer has also been reported in different types of cancers. However, the potential mechanisms which regulate Dicer expression and its potential significance in melanoma are unknown. Here we studied the regulation of Dicer expression by Sox4 and its role in suppression of melanoma invasion. Our data revealed a reduced expression of Dicer mRNA and protein upon Sox4 knockdown. On the other hand, overexpression of Sox4 increased Dicer expression at both mRNA and protein levels. We found that knockdown of Dicer, similar to Sox4 knockdown, enhances the matrigel invasion ability of melanoma cells by at least 2-fold. However, cell growth assays showed that Dicer knockdown does not have a major effect on the growth rate of melanoma cells. In addition, we revealed that overexpression of exogenous Dicer can abrogated the enhanced melanoma cells invasion upon Sox4 knockdown. Furthermore, we examined the expression of Dicer protein in different stages of melanocytic lesions by tissue microarray (TMA) and immunohistochemistry using a construct containing 30 normal nevi, 87 dysplastic nevi, 262 primary and 135 metastatic melanomas. Our data revealed that Dicer expression is inversely correlated with melanoma progression (P<0.0001). Accordingly, the number of samples with positive staining for Dicer reduced from 100% in normal nevi to 85% in dysplastic nevi and 87% in primary melanoma and further reduced to 65% in metastatic melanoma. Expression of Dicer was also negatively correlated with the American Joint Committee on Cancer (AJCC) staging of the melanoma samples (P=0.0004). Strikingly, reduced Dicer expression was correlated with a poorer overall and disease-specific 5-year survival of patients (P=0.015 and 0.0029, respectively). Multivariate Cox regression analysis revealed that reduced Dicer expression is an independent prognostic factor to predict patient outcome (P=0.030). In addition, we analyzed the possible correlation between the expression of Sox4 and Dicer in melanoma TMA samples and found a significant correlation between expression of these markers (P=0.009), further indicating the regulation of Dicer expression by Sox4. Our results pinpoint the regulation of Dicer expression by Sox4 and the critical role of Dicer and probably the miRNA machinery in the suppression of melanoma metastasis. Our data also suggest that Dicer might be a suitable marker for the prognosis of melanoma patients and a potential therapeutic target for human melanoma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3418. doi:1538-7445.AM2012-3418
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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) | 0.004 | 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".