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子宫内膜癌的新分类:基于基因组的分类在研究和临床护理中的发展及潜在应用。

New classification of endometrial cancers: the development and potential applications of genomic-based classification in research and clinical care.

作者信息

Talhouk A, McAlpine J N

机构信息

Department of Pathology and Laboratory Medicine, University of British Columbia and BC Cancer Agency, Vancouver, BC Canada.

Department of Gynecology and Obstetrics, Division of Gynecologic Oncology, University of British Columbia, 2775 Laurel St. 6th Floor, Vancouver, BC Canada V5Z 1M9.

出版信息

Gynecol Oncol Res Pract. 2016 Dec 13;3:14. doi: 10.1186/s40661-016-0035-4. eCollection 2016.

DOI:10.1186/s40661-016-0035-4
PMID:27999680
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5154099/
Abstract

Endometrial carcinoma (EC) is the fourth most common cancer in women in the developed world. Classification of ECs by histomorphologic criteria has limited reproducibility and better tools are needed to distinguish these tumors and enable a subtype-specific approach to research and clinical care. Based on the Cancer Genome Atlas, two research teams have developed pragmatic molecular classifiers that identify four prognostically distinct molecular subgroups. These methods can be applied to diagnostic specimens (e.g., endometrial biopsy) with the potential to completely change the current risk stratification systems and enable earlier informed decision making. The evolution of genomic classification in ECs is shared herein, as well as potential applications and discussion of the essential research still needed in order to optimally integrate molecular classification in to current standard of care.

摘要

子宫内膜癌(EC)是发达国家女性中第四大常见癌症。根据组织形态学标准对EC进行分类的可重复性有限,需要更好的工具来区分这些肿瘤,并实现针对亚型的研究和临床护理方法。基于癌症基因组图谱,两个研究团队开发了实用的分子分类器,可识别出四个预后不同的分子亚组。这些方法可应用于诊断标本(如子宫内膜活检),有可能彻底改变当前的风险分层系统,并实现更早的知情决策。本文分享了EC基因组分类的进展,以及潜在应用,并讨论了为将分子分类最佳地整合到当前护理标准中仍需开展的关键研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3704/5154099/700eab532e7b/40661_2016_35_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3704/5154099/700eab532e7b/40661_2016_35_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3704/5154099/700eab532e7b/40661_2016_35_Fig1_HTML.jpg

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