Suppr超能文献

肾上腺皮质癌:基因组和分子生物学分析新时代的曙光。

Adrenocortical carcinoma: the dawn of a new era of genomic and molecular biology analysis.

机构信息

Endocrinology Unit, Department of Clinical and Experimental Biomedical Sciences "Mario Serio", University of Florence, Viale Pieraccini, 6, 50139, Florence, Italy.

出版信息

J Endocrinol Invest. 2018 May;41(5):499-507. doi: 10.1007/s40618-017-0775-y. Epub 2017 Oct 28.

Abstract

Over the last decade, the development of novel and high penetrance genomic approaches to analyze biological samples has provided very new insights in the comprehension of the molecular biology and genetics of tumors. The use of these techniques, consisting of exome sequencing, transcriptome, miRNome, chromosome alteration, genome, and epigenome analysis, has also been successfully applied to adrenocortical carcinoma (ACC). In fact, the analysis of large cohorts of patients allowed the stratification of ACC with different patterns of molecular alterations, associated with different outcomes, thus providing a novel molecular classification of the malignancy to be associated with the classical pathological analysis. Improving our knowledge about ACC molecular features will result not only in a better diagnostic and prognostic accuracy, but also in the identification of more specific therapeutic targets for the development of more effective pharmacological anti-cancer approaches. In particular, the specific molecular alteration profiles identified in ACC may represent targetable events by the use of already developed or newly designed drugs enabling a better and more efficacious management of the ACC patient in the context of new frontiers of personalized precision medicine.

摘要

在过去的十年中,新型高通量基因组方法的发展为分析生物样本提供了非常新的见解,有助于理解肿瘤的分子生物学和遗传学。这些技术包括外显子组测序、转录组、miRNome、染色体改变、基因组和表观基因组分析,也已成功应用于肾上腺皮质癌 (ACC)。事实上,对大量患者的分析将 ACC 分为具有不同分子改变模式的不同亚群,与不同的结果相关,从而为恶性肿瘤提供了一种新的分子分类,与经典的病理分析相关。提高我们对 ACC 分子特征的认识不仅将导致更好的诊断和预后准确性,而且还将确定更具体的治疗靶点,以开发更有效的抗癌药物。特别是在 ACC 中确定的特定分子改变谱可能代表通过使用已经开发或新设计的药物靶向的事件,从而在个性化精准医学的新前沿为 ACC 患者提供更好、更有效的管理。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验