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高级别神经内分泌肿瘤的基因组学:具有高级别特征的高分化神经内分泌肿瘤(G3 NET)和不同解剖部位的神经内分泌癌(NEC)。

Genomics of High-Grade Neuroendocrine Neoplasms: Well-Differentiated Neuroendocrine Tumor with High-Grade Features (G3 NET) and Neuroendocrine Carcinomas (NEC) of Various Anatomic Sites.

机构信息

Pathology Unit, Department of Medicine and Surgery, University of Insubria, Varese, Italy.

Institute of Pathology, University Hospital and University of Lausanne, Lausanne, Switzerland.

出版信息

Endocr Pathol. 2021 Mar;32(1):192-210. doi: 10.1007/s12022-020-09660-z. Epub 2021 Jan 12.

DOI:10.1007/s12022-020-09660-z
PMID:33433884
Abstract

High-grade neuroendocrine neoplasms (HG-NENs) are clinically aggressive diseases, the classification of which has recently been redefined. They now include both poorly differentiated NENs (neuroendocrine carcinoma, NECs) and high proliferating well-differentiated NENs (called grade 3 neuroendocrine tumors, G3 NETs, in the digestive system). In the last decade, the "molecular revolution" that has affected all fields of medical oncology has also shed light in the understanding of HG NENs heterogeneity and has provided new diagnostic and therapeutic tools, useful in the management of these malignancies. Considering the kaleidoscopic aspects of HG NENs in various anatomical sites, this review systematically addresses the genomic landscape of such neoplasm throughout the more common thoracic and digestive locations, as well as it will consider other rare but not exceptional primary sites, including the skin, the head and neck, and the urogenital system. The revision of the available literature will then be oriented to understand the translational relevance of molecular data, by analyzing conceptual issues, clinicopathological correlations, and unmet needs in this field.

摘要

高级别神经内分泌肿瘤(HG-NENs)是临床侵袭性疾病,其分类最近已重新定义。它们现在既包括分化差的神经内分泌肿瘤(神经内分泌癌,NEC),也包括高增殖分化良好的神经内分泌肿瘤(消化系统中称为 3 级神经内分泌肿瘤,G3 NET)。在过去的十年中,影响所有肿瘤医学领域的“分子革命”也揭示了 HG NEN 异质性,并提供了新的诊断和治疗工具,有助于这些恶性肿瘤的治疗。鉴于不同解剖部位的 HG NEN 具有千变万化的特征,本综述系统地阐述了这些肿瘤在更常见的胸内和消化系统部位的基因组图谱,并将考虑其他罕见但并非异常的原发部位,包括皮肤、头颈部和泌尿生殖系统。然后,通过分析概念问题、临床病理相关性和该领域的未满足需求,对现有文献进行复习,以了解分子数据的转化相关性。

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