Hofsli Eva
Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim N-7489, Norway.
Pituitary. 2006;9(3):165-78. doi: 10.1007/s11102-006-0262-5.
The fascinating, but often unpredictable, biology of neuroendocrine tumors (NETs) make the management of these malignancies a real challenge. The more recent development of high-throughput genomic and proteomic techniques, have opened a window to an increased knowledge of the biology of NETs. This review will discuss genes thought to play a role in the context of NE tumor biology, with particularly attention to those that may be potential new diagnostic and prognostic markers, as well as therapeutic targets. NETs constitute a heterogeneous group of neoplasm that may arise in virtually every topographic localization in the body, as a consequence of malignant transformation of various types of NE cells. Since NETs arising in the gastroenteropancreatic (GEP) or bronchopulmonary system are by far the most common, this review focuses on these entities, but lines are drawn to other NETs as well. Although large-scale gene expression analysis undoubtly have raised interesting new hypothesis concerning genes thought to play a role in tumor biology, discrepancies observed between studies and various platforms used, emphasizes the need to not only standardize the way microarray data are reported, but also to introduce standards in sample taking, processing and study design. In addition, the recognition of the complexity of the human proteome, with regard to generation of multiple isoforms from one gene, has created additional challenges. However,some goals have been reached already, as new knowledge has been translated into development of novel promising therapeutics.
神经内分泌肿瘤(NETs)迷人却往往不可预测的生物学特性,使得对这些恶性肿瘤的管理成为一项真正的挑战。高通量基因组学和蛋白质组学技术的最新发展,为增进对NETs生物学特性的了解打开了一扇窗口。本综述将讨论在神经内分泌肿瘤生物学背景中被认为发挥作用的基因,尤其关注那些可能成为潜在新诊断和预后标志物以及治疗靶点的基因。NETs是一组异质性肿瘤,由于各种类型的神经内分泌细胞发生恶性转化,几乎可出现在身体的每个解剖部位。由于起源于胃肠胰(GEP)或支气管肺系统的NETs最为常见,本综述聚焦于这些实体,但也会涉及其他NETs情况。尽管大规模基因表达分析无疑提出了有关在肿瘤生物学中发挥作用的基因的有趣新假说,但研究之间以及所使用的各种平台之间观察到的差异,凸显了不仅要规范微阵列数据报告方式,还要在样本采集、处理和研究设计方面引入标准的必要性。此外认识到人类蛋白质组的复杂性,即一个基因可产生多种异构体,带来了更多挑战。然而,随着新知识已转化为新型有前景疗法的开发,已经取得了一些成果。