Background Endocrine malignancies (including thyroid, adrenal, parathyroid, and pancreatic neuroendocrine tumors) are among the fastest growing cancer diagnoses in the United States, but it is difficult to distinguish benign from malignant tumors by routine clinical, laboratory, and imaging studies. So, even patients who have seemingly benign endocrine tumors often choose to undergo surgery to get a definitive diagnosis in the hopes of ruling out cancer. Most patients with endocrine cancers have a relatively good prognosis. However, anywhere from 10% to 40% (depending on tumor type) have aggressive disease which often cannot be reliably determined at the time of initial treatment. Prognostic markers which can reliably risk stratify patients with high risk of recurrence and death would help determine which patients should receive aggressive initial treatment and close follow up. Furthermore, prognostic markers may also help identify which patients are likely to respond to standard therapy and which patients do not respond to standard therapy if a distinct molecular phenotype is identified. Summary We are using a pan-genomic (mRNA and microRNA expression, and global methylation) profiling approach in human tumor tissue samples to identify candidate diagnostic and prognostic markers for endocrine malignancies (thyroid, adrenal, neuroendocrine pancreas). We have completed our analysis of adrenal neoplasm and have identified key changes in mRNA expression and microRNA expression levels, and DNA-methylation that serve as excellent diagnostic markers. Based on these findings, we just opened a clinical trial to test their diagnostic utility in patients with adrenal neoplasm in clinical biopsy samples. We have also used the pan-genomic data to determine the function of the key deregulated genes (KIAA0101, IL13RA2, TOP2A) in adrenocortical carcinoma cells. We have found these genes not only regulate the hallmarks of malignant cell phenotype (cell proliferation, invasion and migration) in vitro but are excellent therapeutic targets in vivo xenograft studies of adrenocoritcal carcinoma (e.g. IL13RA2). We are in the process of integrating the pan-genomic data to understand the main mechanisms of gene expression dysregulation in endocrine cancers.
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