Gene expression and regulation in endocrine cancers

背景内分泌恶性肿瘤(包括甲状腺、肾上腺、胰腺、甲状旁腺和神经内分泌癌)是美国增长最快的癌症诊断之一，但常规的临床、实验室和影像检查很难区分良、恶性肿瘤。因此，即使是看似良性的内分泌肿瘤患者，也往往选择接受手术以获得明确的诊断，希望排除癌症。大多数内分泌癌患者预后相对较好。然而，任何地方都有10%到40%(取决于肿瘤类型)患有侵袭性疾病，这在最初治疗时往往无法可靠地确定。预后标志物可以可靠地对复发和死亡风险较高的患者进行风险分层，这将有助于确定哪些患者应该接受积极的初始治疗和密切随访。此外，如果确定了不同的分子表型，预后标记物也可能有助于确定哪些患者可能对标准治疗有反应，哪些患者对标准治疗没有反应。摘要我们正在人类肿瘤组织样本中使用泛基因组(mRNA和microRNA表达，以及全球甲基化)分析方法，以确定内分泌恶性肿瘤(甲状腺、肾上腺、神经内分泌胰腺)的候选诊断和预后标志物。将使用几种策略来识别和验证标记物。高维生物信息学方法将被用来确定分子分类是否足够准确，用于诊断和预后带有临床随访数据的注释良好的样本。候选标记物将在独立的样本集中进行验证，以测试其诊断和预后的准确性。此外，体外肿瘤活检样本、血清标志物的动物模型和临床肿瘤活检样本将用于验证候选的诊断和预后标志物，并确定其临床应用价值。内分泌癌发生和发展的分子基础尚不清楚。鉴于我们将拥有泛基因组表达谱数据，我们将确定microRNA错误表达和或表观遗传(启动子甲基化)变化是否解释了内分泌癌中发现的去调控基因。然后，将使用功能基因组方法在体外测试内分泌癌中失调基因的主要microRNA调节因子，以确认它们在基因表达调节中的作用。基于全球甲基化图谱研究，对于可能受启动子甲基化调控的基因，我们将在细胞系中使用基因特异性启动子甲基化分析和去甲基剂处理，以破译表观遗传基因表达调控在内分泌癌中的重要性。在内分泌癌细胞的体外模型中，这种整合的生物信息学方法和功能基因组学方法有望阐明内分泌癌基因表达解除调控的主要机制。

Background Endocrine malignancies (including thyroid, adrenal, pancreas, parathyroid, and neuroendocrine cancers) 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). Several strategies will be used for marker identifications and validation. High dimensional bioinformatics approach will be used to determine if molecular classification is accurate enough for diagnosis and prognosis in well annotated samples with clinical follow up data. The candidate markers will be validated in an independent sample set to test their diagnostic and prognostic accuracy. Furthermore, ex vivo tumor biopsy samples, animal models for serum markers and clinical tumor biopsy samples will be used to validate candidate diagnostic and prognostic markers and determine their clinical utility. The molecular basis for endocrine cancer initiation and progression is poorly understood. Given we will have pan-genomic expression profiling data, we will determine whether microRNA misexpression and or epigenetic (promoter methylation) changes account for the genes found to be deregulated in endocrine cancers. The master microRNA regulators of genes dysregulated in endocrine cancers will then be tested in vitro using functional genomic approaches to confirm their role in gene expression regulation. For genes possibly regulated by promoter methylation based on the global methylation profiling studies, we will use gene specific promoter methylation analysis and demethylating agent treatment in cell lines to decipher the importance of epigenetic gene expression regulation in endocrine cancers. It is hoped such an integrated bioinformatics approach and functional genomics approach in in vitro models of endocrine cancer cells will shed light on the main mechanisms of gene expression deregulation in endocrine cancers.