Gene expression signatures that can discriminate oral leukoplakia subtypes and squamous cell carcinoma
ABSTRACT The purpose of this study is to generate a classifier for oral squamous cell carcinoma (OSCC) and leukoplakias (LPs), and evaluate its diagnostic potential. In order to identify marker gene candidates, differential gene expression between LPs and OSCCs were examined by cDNA microarray. The expression of 118 marker gene candidates was further evaluated by quantitative reverse transcription-PCR (QRT-PCR) analyses of 27 OSCC and 19 LP tissues. We identified 12 up-regulated and 15 down-regulated marker genes in OSCCs compared to LPs. Using Fisher's linear discriminant analysis (LDA), we demonstrated that 11-gene predictors among this novel marker set could best distinguish OSCCs from LPs (>97% accuracy), whereas a further seven of these gene predictors could be utilized to distinguish higher grade (higher than moderate) from lower grade (lower than mild) dysplasias (>95% accuracy). These predictor gene sets provide multigene classifiers for the diagnosis of pre-cancerous to cancerous transition of oral malignancy.
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ABSTRACT: While the recent advent of new technologies in biology such as DNA microarray and next-generation sequencer has given researchers a large volume of data representing genome-wide biological responses, it is not necessarily easy to derive knowledge that is accurate and understandable at the same time. In this study, we applied the Classification Based on Association (CBA) algorithm, one of the Class Association Rule mining techniques, to the TG-GATEs database, where both toxicogenomic and toxicological data of more than 150 compounds in rat and human are stored. We compared the generated classifiers between CBA and linear discriminant analysis (LDA) and showed that CBA is superior to LDA in terms of both predictive performances (accuracy: 83% for CBA vs. 75% for LDA, sensitivity: 82% for CBA vs. 72% for LDA, specificity: 85% for CBA vs. 75% for LDA) and interpretability.Toxicology Reports 11/2014; DOI:10.1016/j.toxrep.2014.10.014
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ABSTRACT: Recent technological advances now permit the study of the entire cancer genome, which can elucidate complex pathway interactions that are not apparent at the level of single genes. In this review, the authors describe innovations that have allowed for whole-exome/genome analysis of genetic and epigenetic alterations and of changes in gene expression. Studies using next-generation sequencing, array comparative genomic hybridization, methylation arrays, and gene expression profiling are reviewed, with a particular focus on findings from recent whole-exome sequencing projects. A discussion of the implications of these data on treatment and future goals for cancer genomics is included.Otolaryngologic Clinics of North America 08/2013; 46(4):545-66. DOI:10.1016/j.otc.2013.04.001 · 1.34 Impact Factor
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ABSTRACT: Early and accurate diagnosis of oral potentially malignant lesions (OPML) is of critical importance in preventing malignant transformation. Although histopathological interpretation of the degree of epithelial dysplasia is considered the gold standard for diagnosis, this method is subjective and lacks sensitivity. Therefore, many attempts have been made to identify objective molecular biomarkers to improve diagnosis. Microarray technology has the advantage of screening the expression of the whole genome making it one of the best tools for searching for novel biomarkers. However, microarray studies of OPMLs are limited, and no review has been published to highlight and compare their findings. In this paper, we systematically review all studies that have incorporated microarray analyses in the investigation of gene profile alterations in OPMLs and suggest a set of commonly dysregulated genes across multiple gene expression profile studies. This list of common genes may help focus selection of markers for further analysis regarding their importance in the diagnosis and prognosis of OPMLs.Clinical Medicine Insights: Oncology 10/2013; 7:279-290. DOI:10.4137/CMO.S12950