MicroRNAs offer tools to identify and treat invasive cancers. Using highly invasive isogenic oral squamous cell carcinoma (OSCC) cells, established using in vitro and in vivo selection protocols from poorly invasive parental cell populations, we used microarray expression analysis to identify a relative and specific decrease in miR-491-5p in invasive cells. Lower expression of miR-491-5p correlated with poor overall survival of patients with OSCCs. miR-491-5p overexpression in invasive OSCC cells suppressed their migratory behavior in vitro and lung metastatic behavior in vivo. We defined the G-protein-coupled receptor kinase-interacting protein 1 (GIT1)-as a direct target gene for miR-491-5p control. GIT1 overexpression was sufficient to rescue miR-491-5p-mediated inhibition of migration/invasion and lung metastasis. Conversely, GIT1 silencing phenocopied the ability of miR-491-5p to inhibit migration/invasion and metastasis of OSCC cells. Mechanistic investigations indicated that miR-491-5p overexpression or GIT1 attenuation reduced focal adhesions, with a concurrent decrease in steady-state levels of paxillin, phospho-paxillin, phospho-FAK, EGF/EGFR-mediated extracellular signal-regulated kinase (ERK1/2) activation, and MMP2/9 levels and activities. In clinical specimens of OSCCs, GIT1 levels were elevated relative to paired normal tissues and were correlated with lymph node metastasis, with expression levels of miR-491-5p and GIT1 correlated inversely in OSCCs, where they informed tumor grade. Together, our findings identify a functional axis for OSCC invasion that suggests miR-491-5p and GIT1 as biomarkers for prognosis in this cancer. Cancer Res; 74(3); 751-64. Ó2013 AACR.

Most cases of oral squamous cell carcinoma (OSCC) develop from visible oral potentially malignant disorders (OPMDs). The latter exhibit heterogeneous subtypes with different transformation potentials, complicating the early detection of OSCC during routine visual oral cancer screenings. To develop clinically applicable biomarkers, we collected saliva samples from 96 healthy controls, 103 low-risk OPMDs, 130 high-risk OPMDs, and 131 OSCC subjects. These individuals were enrolled in Taiwan’s Oral Cancer Screening Program. We identified 302 protein biomarkers reported in the literature and/or through in-house studies and prioritized 49 proteins for quantification in the saliva samples using multiple reaction monitoring-MS. Twenty-eight proteins were successfully quantified with high confidence. The quantification data from non-OSCC subjects (healthy controls + low-risk OPMDs) and OSCC subjects in the training set were subjected to classification and regression tree analyses, through which we generated a four-protein panel consisting of MMP1, KNG1, ANXA2, and HSPA5. A risk-score scheme was established, and the panel showed high sensitivity (87.5%) and specificity (80.5%) in the test set to distinguish OSCC samples from non-OSCC samples. The risk score >0.4 detected 84% (42/50) of the stage I OSCCs and a significant portion (42%) of the high-risk OPMDs. Moreover, among 88 high-risk OPMD patients with available follow-up results, 18 developed OSCC within 5 y; of them, 77.8% (14/18) had risk scores >0.4. Our four-protein panel may therefore offer a clinically effective tool for detecting OSCC and monitoring high-risk OPMDs through a readily available biofluid.

BackgroundThe epithelial-to-mesenchymal transition (EMT) process results in a loss of cell-cell adhesion, increased cell mobility, and is crucial for enabling the metastasis of cancer cells. Recently, the enzyme SIRT1 has been implicated in a variety of physiological processes; however, its role in regulating oral cancer metastasis and EMT is not fully elucidated. Here, we propose a mechanism by which the enzyme sirtuin1 (SIRT1) regulates the EMT process in oral cancer by deacetylating Smad4 and repressing the effect of TGF-β signaling on matrix metalloproteinase-7 (MMP7).MethodsThe roles of SIRT1 in tumor cell migration/invasion and metastasis to the lungs were investigated using the Boyden chamber assay and orthotopic injections, respectively. RNA interference was used to knockdown either SIRT1 or Smad4 expression in oral squamous cell carcinoma (OSCC) cell lines. Immunoblotting, zymographic assays, and co-immunoprecipitation were used to examine the effects of SIRT1 overexpression on MMP7 expression and activity, as well as on SIRT1/ Smad4 interaction.ResultsWe found that compared with normal human oral keratinocytes (HOKs), SIRT1 was underexpressed in OSCC cells, and also in oral cancer tissues obtained from 14 of 21 OSCC patients compared with expression in their matched normal tissues. Overexpression of SIRT1 inhibited migration of OSCC cells in vitro, as well as their metastasis to the lung in vivo. Furthermore, up-regulation of SIRT1 in metastatic OSCCs significantly inhibited the migration and invasion abilities of OSCC cells, while concomitantly increasing the expression of E-cadherin, and decreasing the expressions of mesenchymal markers. We also identified Smad4, a TGF-β-activated transcription factor, as a direct target protein for SIRT1. Overexpression of SIRT1 in OSCC cells led to decreased levels of acetylated Smad4, and inhibition of TGF-β-induced signaling. By associating and deacetylating Smad4, SIRT1 enzyme can influence MMP7 expression, MMP enzyme activity, and consequently, cell migration, invasion, and tumor metastasis in OSCCs.ConclusionsThese findings provide a valuable insight into the potential role of the SIRT1 enzyme in regulating cell migration and invasion in oral squamous cell carcinoma. Our findings suggest the SIRT1/Smad4/MMP7 pathway as a target for oral cancer driven by EMT.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-4598-13-254) contains supplementary material, which is available to authorized users.

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This study adopted an integrated procedure that combines the clustering and classification features of data mining technology to determine the differences between the symptoms shown in past cases where patients died from or survived oral cancer. Two data mining tools, namely decision tree and artificial neural network, were used to analyze the historical cases of oral cancer, and their performance was compared with that of logistic regression, the popular statistical analysis tool. Both decision tree and artificial neural network models showed superiority to the traditional statistical model. However, as to clinician, the trees created by the decision tree models are relatively easier to interpret compared to that of the artificial neural network models. Cluster analysis also discovers that those stage 4 patients whose also possess the following four characteristics are having an extremely low survival rate: pN is N2b, level of RLNM is level I-III, AJCC-T is T4, and cells mutate situation (G) is moderate.

Abstract-In this paper we present JST, a tool that automatically generates a high coverage test suite for industrial strength Java applications. This tool uses a numeric-string hybrid symbolic execution engine at its core which is based on the Symbolic Java PathFinder platform. However, in order to make the tool applicable to industrial applications the existing generic platform had to be enhanced in numerous ways that we describe in this paper. The JST tool consists of newly supported essential Java library components and widely used data structures; novel solving techniques for string constraints, regular expressions, and their interactions with integer and floating point numbers; and key optimizations that make the tool more efficient. We present a methodology to seamlessly integrate the features mentioned above to make the tool scalable to industrial applications that are beyond the reach of the original platform in terms of both applicability and performance. We also present extensive experimental data to illustrate the effectiveness of our tool.

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