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Accession IconGSE12368

Analysis of adrenocortical tumors identify IGF2 and Ki-67 as useful in differentiating carcinomas from adenomas

Organism Icon Homo sapiens
Sample Icon 32 Downloadable Samples
Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

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Description
Purpose: The management of adrenocortical tumors (ACTs) is complex, compounded by the difficulty in discriminating benign from malignant tumors using conventional histology. The Weiss score is the current most widely used system for ACT diagnosis but it has limitations, particularly with ACTs with a score of 3. The am of this study was to identify molecular markers whose expression can discriminate adrenocortical carcinomas (ACCs) from adrenocortical adenomas (ACAs) by microarray gene expression profiling and to determine their clinical applicability by using immunohistochemistry (IHC). Experimental design: Microarray gene expression profiling was used to identify 7 molecular markers which were significantly differentially expressed between ACCs and ACAs. These results were confirmed with quantitative PCR for all 7 genes and IHC for 3 protein. Results: Microarray gene expression profiling was able to accurately categorize ACTs into ACCs and ACAs. All 7 genes were strong discriminators of ACCs from ACAs on qPCR. IHC with IGF2, MAD2L1, CCNB1 and Ki-67, but not ACADVL or ALOX15B, had high diagnostic accuracy in differentiating ACCs from ACAs. The best results however were obtained with a combination of IGF2 and Ki-67 with 96% sensitivity and 100% specificity in diagnosing ACCs. Conclusion: Microarray gene expression profiling accurately differentiates ACCs from ACAs. The combination of IGF2 and Ki-67 IHC is also highly accurate in distinguishing between the 2 groups and is particularly helpful in ACTs with Weiss score of 3.
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