Objective: Sporadic adrenocortical tumors are common, but their pathogenesis is poorly elucidated. Several mRNA profiling and comparative genome hybridization (CGH) studies have been performed on adrenocortical tumors to date. Meta-analysis of these results may be warranted due to the low number of tumor samples examined in several individual studies. Here, we present an integrative meta-analysis of gene expression microarray and CGH studies performed to date on sporadic adrenocortical tumors, including our own data.
Methods: Raw data of whole genome microarray studies from altogether 164 tumors (97 benign, 67 malignant) and 18 normal tissues were regrouped and reanalyzed. Significant gene sets and cytogenetic changes from publications without available genomic data were also examined including 269 benign, 215 malignant tumor and 30 normal tissues. In our experimental study (approved by the Ethical Committee of the Health Council), 11 tumor and 4 normal samples were analyzed by parallel mRNA and CGH profiling. Data were examined by an integrative bioinformatics approach (GeneSpring, Gene Set Enrichment Analysis and Ingenuity Pathway Analysis softwares) searching for common gene expression changes and paralleling chromosome aberrations.
Results: A two-gene signature (overexpression of anillin and underexpression of 5-hydroxytryptamine receptor 2B) was identified as a predictor of malignancy. Both meta-analysis of available mRNA and CGH profiling data and our experimental study revealed the involvement of three major pathogenetic pathways that could be relevant in adrenocortical tumorigenesis: i) cell cycle, ii) retinoic acid signaling (including lipopolysaccharide/Toll like receptor 4 pathway), iii) complement and antigen presentation. The observation that the same pathways were found by both approaches supports the feasibility of in silico meta-analysis.
Conclusions: These pathways include novel, previously undescribed pathomechanisms of adrenocortical tumors, and associated gene products may serve as diagnostic markers of malignancy and potential therapeutic targets.