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Systematic comparison of nonmelanoma skin cancer microarray datasets reveals lack of consensus genes
Author(s) -
Van Haren R.,
Feldman D.,
Sinha A.A.
Publication year - 2009
Publication title -
british journal of dermatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.304
H-Index - 179
eISSN - 1365-2133
pISSN - 0007-0963
DOI - 10.1111/j.1365-2133.2009.09338.x
Subject(s) - microarray , basal cell carcinoma , skin cancer , dna microarray , microarray analysis techniques , biology , gene chip analysis , gene , computational biology , gene expression , bioinformatics , cancer , basal cell , genetics , medicine , pathology
Summary Background DNA microarray technology has revealed vast numbers of gene expression alterations associated with human malignancies. Assigning validity and biological significance to these changes, however, remains a considerable hurdle. Recently, microarray analysis has been applied to the study of nonmelanoma skin cancer. Objectives To compare experimental data rigorously in order to strengthen conclusions regarding the pathogenesis of basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), and to evaluate systematically the experimental and statistical parameters that may impact the degree of consensus among differentially expressed genes (DEGs) between studies. Methods We performed a systematic comparison of 10 studies that applied DNA microarray technology to study BCC/SCC. Results A total of 1133 DEGs collectively reported across the studies were compared, and 64 DEG overlaps were found: 18 DEG overlaps in SCC vs. SCC study comparisons, 18 DEG overlaps in BCC vs. BCC study comparisons and 28 DEG overlaps in BCC vs. SCC study comparisons. We documented differences in several experimental methods that may account for the relative lack of consensus between studies, including sample type, tissue procurement/handling, microarray chip and statistical analysis. The two most dysregulated biological pathways across all studies involved genes with enzymatic and structural/adhesion functions. Conclusions DEGs that were found to overlap across two or more studies and biological pathways with the largest representation of DEGs across studies may be particularly relevant to disease pathogenesis and serve as targets for future therapy. In future work, more consistent experimental methods across laboratories may improve the validity of reported DEGs and strengthen conclusions drawn from microarray data.