Meta-analysis of gene expression for development and validation of a diagnostic biomarker panel for Oral Squamous Cell Carcinoma. (October 2019)

• Record Type: Journal Article
• Authors: Makarov, Vladimir; Gorlin, Alex
• Is Part Of: Computational biology and chemistry. Volume 82(2019)
• Page Start: 74
• Page End: 79
• Publication Date: 2019-10
• Subjects: Biomarker -- Microarray -- Gene expression -- Classification -- Oral Squamous Cell Carcinoma; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2019.06.008
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights Present a diagnostic biomarker panel for Oral Squamous Cell Carcinoma. Use meta-analysis of gene expression data and sort features with a dichotomy power metric. Results are reproducible - concordant with earlier studies. Explain irreproducibility of molecular biomarkers for this cancer seen in earlier studies. Abstract: We use a newly developed feature extraction and classification method to analyze previously published gene expression data sets in Oral Squamous Cell Carcinoma and in healthy oral mucosa in order to find a gene set sufficient for diagnoses. The feature selection technology is based on the relative dichotomy power concept published by us earlier. The resulting biomarker panel has 100% sensitivity and 95% specificity, is enriched in genes associated with oncogenesis and invasive tumor growth, and, unlike marker panels devised in earlier studies, shows concordance with previously published marker genes.