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65 年的双螺旋:综合基因组学时代的内分泌肿瘤分类。

65 YEARS OF THE DOUBLE HELIX: Classification of endocrine tumors in the age of integrated genomics.

机构信息

Divisions of Anatomic Pathology and Molecular & Genomic PathologyDepartments of Pathology and Internal Medicine, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA

出版信息

Endocr Relat Cancer. 2018 Aug;25(8):T171-T187. doi: 10.1530/ERC-18-0116.

DOI:10.1530/ERC-18-0116
PMID:29980645
Abstract

The classification of human cancers represents one of the cornerstones of modern pathology. Over the last century, surgical pathologists established the current taxonomy of neoplasia using traditional histopathological parameters, which include tumor architecture, cytological features and cellular proliferation. This morphological classification is efficient and robust with high reproducibility and has served patients and health care providers well. The most recent decade has witnessed an explosion of genome-wide molecular genetic and epigenetic data for most cancers, including tumors of endocrine organs. The availability of this expansive multi-dimensional genomic data, collectively termed the cancer genome, has catalyzed a re-examination of the classification of endocrine tumors. Here, recent cancer genome studies of various endocrine tumors, including those of the thyroid, pituitary and adrenal glands, pancreas, small bowel, lung and skin, are presented with special emphasis on how genomic insights are impacting endocrine tumor classification.

摘要

人类癌症的分类是现代病理学的基石之一。在上个世纪,外科病理学家使用传统的组织病理学参数建立了目前的肿瘤分类,这些参数包括肿瘤结构、细胞学特征和细胞增殖。这种形态分类方法效率高、稳健,具有高度的可重复性,为患者和医疗保健提供者提供了良好的服务。在过去的十年中,大多数癌症(包括内分泌器官的肿瘤)的全基因组分子遗传和表观遗传数据呈爆炸式增长。这种广泛的多维基因组数据的出现,统称为“癌症基因组”,促使人们重新审视内分泌肿瘤的分类。在这里,我们介绍了各种内分泌肿瘤(包括甲状腺、垂体和肾上腺、胰腺、小肠、肺和皮肤的肿瘤)的最新癌症基因组研究,特别强调了基因组见解如何影响内分泌肿瘤的分类。

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65 YEARS OF THE DOUBLE HELIX: Classification of endocrine tumors in the age of integrated genomics.65 年的双螺旋:综合基因组学时代的内分泌肿瘤分类。
Endocr Relat Cancer. 2018 Aug;25(8):T171-T187. doi: 10.1530/ERC-18-0116.
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引用本文的文献

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Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms.机器学习:放射组学在内分泌肿瘤中的应用与最新进展
J Oncol. 2021 Oct 11;2021:8615450. doi: 10.1155/2021/8615450. eCollection 2021.