A method for detecting significant genomic regions associated with oral squamous cell carcinoma using aCGH

DNA Copy Number Selection Using Robust Structured Sparsity-Inducing Norms

Array comparative genomic hybridization (aCGH) is a newly introduced method for the detection of copy number abnormalities associated with human diseases with special focus on cancer. Specific patterns in DNA copy number variations (CNVs) can be associated with certain disease types and can facilitate prognosis and progress monitoring of the disease. Machine learning techniques have been used to model the problem of tissue typing as a classification problem. Feature selection is an important part of the classification process, because many biological features are not related to the diseases and confuse the classification tasks. Multiple feature selection methods have been proposed in the different domains where classification has been applied. In this work, we will present a new feature selection method based on structured sparsity-inducing norms to identify the informative aCGH biomarkers which can help us classify different disease subtypes. To validate the performance of the proposed method, we experimentally compare it with existing feature selection methods on four publicly available aCGH data sets. In all empirical results, the proposed sparse learning based feature selection method consistently outperforms other related approaches. More important, we carefully investigate the aCGH biomarkers selected by our method, and the biological evidences in literature strongly support our results.

Genome-wide approaches (GWA) in oral and craniofacial diseases research

Oral Diseases (2012) Underlying molecular genetic mechanisms of diseases can be deciphered with unbiased strategies using recently developed technologies enabling genome-wide scale investigations. These technologies have been applied in scanning for genetic variations, gene expression profiles, and epigenetic changes for oral and craniofacial diseases. However, these approaches as applied to oral and craniofacial conditions are in the initial stages, and challenges remain to be overcome, including analysis of high throughput data and their interpretation. Here, we review methodology and studies using genome-wide approaches in oral and craniofacial diseases and suggest future directions.

Role of insulin-like growth factor-II mRNA-binding protein-3 in invadopodia formation and the growth of oral squamous cell carcinoma in athymic nude mice

BACKGROUND

The invadopodia are specialized structures that degrade the extracellular matrix (ECM) and promote cell invasion and metastasis. Understanding the forms and functions of invadopodia should facilitate the proper identification of novel targets for antiinvasive therapy.

METHODS

To understand the role of insulin-like growth factor-II mRNA-binding protein-3 (IMP-3) in invadopodia formation and cancer invasion, we performed IMP-3 gene silencing, invadopodia formation, ECM degradation assay, zymography, western blot, and mouse xenograft.

RESULTS

We demonstrate that invadopodia evidenced ECM degradation activity in oral squamous cell carcinoma (OSCC). Downregulation of IMP-3 inhibited invadopodia formation, ECM degradation, and tumor growth and invasiveness. Epidermal growth factor receptor (EGFR) signaling may perform a critical function in invadopodia formation, ECM degradation, IMP-3, and cortactin expression.

CONCLUSION

IMP-3 may be intimately correlated with cancer invasion through invadopodia in oral cancer. The overexpression of IMP-3 in oral cancer was predictive of a high correlation with cancer growth and invasion.