Molecular Classification and Prognostication of Adrenocortical Tumors by Transcriptome Profiling
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- 15 January 2009
- journal article
- Published by American Association for Cancer Research (AACR) in Clinical Cancer Research
- Vol. 15 (2), 668-676
- https://doi.org/10.1158/1078-0432.ccr-08-1067
Abstract
Purpose: Our understanding of adrenocortical carcinoma (ACC) has improved considerably, yet many unanswered questions remain. For instance, can molecular subtypes of ACC be identified? If so, what is their underlying pathogenetic basis and do they possess clinical significance? Experimental Design: We did a whole genome gene expression study of a large cohort of adrenocortical tissues annotated with clinicopathologic data. Using Affymetrix Human Genome U133 Plus 2.0 oligonucleotide arrays, transcriptional profiles were generated for 10 normal adrenal cortices (NC), 22 adrenocortical adenomas (ACA), and 33 ACCs. Results: The overall classification of adrenocortical tumors was recapitulated using principal component analysis of the entire data set. The NC and ACA cohorts showed little intragroup variation, whereas the ACC cohort revealed much greater variation in gene expression. A robust list of 2,875 differentially expressed genes in ACC compared with both NC and ACA was generated and used in functional enrichment analysis to find pathways and attributes of biological significance. Cluster analysis of the ACCs revealed two subtypes that reflected tumor proliferation, as measured by mitotic counts and cell cycle genes. Kaplan-Meier analysis of these ACC clusters showed a significant difference in survival (P < 0.020). Multivariate Cox modeling using stage, mitotic rate, and gene expression data as measured by the first principal component for ACC samples showed that gene expression data contains significant independent prognostic information (P < 0.017). Conclusions: This study lays the foundation for the molecular classification and prognostication of adrenocortical tumors and also provides a rich source of potential diagnostic and prognostic markers.Keywords
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This publication has 55 references indexed in Scilit:
- Advances in Male ContraceptionEndocrine Reviews, 2008
- Disrupting insulin-like growth factor signaling as a potential cancer therapyMolecular Cancer Therapeutics, 2007
- NCBI GEO: mining tens of millions of expression profiles--database and tools updateNucleic Acids Research, 2006
- A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancersNature Genetics, 2006
- Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profilesProceedings of the National Academy of Sciences of the United States of America, 2005
- Mining for regulatory programs in the cancer transcriptomeNature Genetics, 2005
- Gene-expression profiles predict survival of patients with lung adenocarcinomaNature Medicine, 2002
- Gene expression profiling predicts clinical outcome of breast cancerNature, 2002
- Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implicationsProceedings of the National Academy of Sciences of the United States of America, 2001
- Distinct types of diffuse large B-cell lymphoma identified by gene expression profilingNature, 2000