通过基因表达谱分析对小肠和胰腺神经内分泌肿瘤进行鉴别。
Differentiation of small bowel and pancreatic neuroendocrine tumors by gene-expression profiling.
机构信息
Department of Surgery, University of Iowa Carver College of Medicine, Iowa City, IA 52242-1086, USA.
出版信息
Surgery. 2012 Dec;152(6):998-1007. doi: 10.1016/j.surg.2012.08.040.
BACKGROUND
Between 10% and 20% of patients with neuroendocrine tumors (NETs) present with metastases of unknown primary site. Because knowledge of the primary site has important implications for treatment, we set out to define gene-expression profiles to differentiate between small-bowel NETs (SBNETs) and pancreatic NETs (PNETs).
METHODS
RNA was extracted from tumor and normal tissues in 11 patients with SBNETs and 15 patients with PNETs, and qPCR was performed for 367 GPCR genes. Differentially expressed genes were identified using the RT2 Profiler. Whole genome expression analysis was performed on 11 SBNETs, 5 PNETS, and corresponding normal tissues. Statistical significance was evaluated by the Student t test and ANOVA.
RESULTS
Whole-genome analysis revealed 173 significantly differentially expressed genes in SBNETs and normal tissues and in 52 in PNETs. GPCR arrays identified 28 genes in SBNETs and 18 in PNETs, with significant expression differences from normal tissues. In all SBNETs, 2 genes were significantly upregulated by more than fivefold: OXTR and GPR113. No PNETs shared this profile, whereas 73% had a greater than fivefold downregulation of ADORA1 and SCTR. These genes also allowed for determination of the primary site in 8 of 10 liver metastases.
CONCLUSION
Differential expression patterns using as few as 2 to 4 GPCR genes successfully discriminated primary sites in small bowel and pancreatic NETs.
背景
10%到 20%的神经内分泌肿瘤（NET）患者存在不明原发灶转移。由于原发灶的知识对治疗有重要影响，我们着手定义基因表达谱，以区分小肠 NET（SBNET）和胰腺 NET（PNET）。
方法
从 11 例 SBNET 患者和 15 例 PNET 患者的肿瘤和正常组织中提取 RNA，并对 367 个 GPCR 基因进行 qPCR。使用 RT2 Profiler 识别差异表达基因。对 11 例 SBNET、5 例 PNET 和相应的正常组织进行全基因组表达分析。通过 Student t 检验和 ANOVA 评估统计学意义。
结果
全基因组分析显示 SBNET 和正常组织之间有 173 个明显差异表达的基因，而 PNET 中有 52 个。GPCR 芯片在 SBNET 中鉴定出 28 个基因，在 PNET 中鉴定出 18 个基因，与正常组织的表达差异显著。在所有 SBNET 中，有 2 个基因的上调超过五倍：OXTR 和 GPR113。没有 PNET 具有这种特征，而 73%的 PNET 中 ADORA1 和 SCTR 的下调超过五倍。这些基因还可以确定 10 例肝转移中的 8 例的原发灶。
结论
使用多达 2 到 4 个 GPCR 基因的差异表达模式成功区分了小肠和胰腺 NET 的原发灶。
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