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分子分类作为胰腺癌的预后因素和治疗决策指导。

Molecular classification as prognostic factor and guide for treatment decision of pancreatic cancer.

机构信息

Département d'Oncologie Moléculaire, Centre de Recherche en Cancérologie de Marseille, INSERM UMR1068, CNRS UMR7258, Aix-Marseille Université, Marseille, France; Faculté de Médecine, Aix-Marseille Université, Marseille, France; Département de Chirurgie Générale et Viscérale, AP-HM, Marseille, France.

Département d'Oncologie Moléculaire, Centre de Recherche en Cancérologie de Marseille, INSERM UMR1068, CNRS UMR7258, Aix-Marseille Université, Marseille, France; Faculté de Médecine, Aix-Marseille Université, Marseille, France; Département d'Oncologie Médicale, Institut Paoli-Calmettes, Marseille, France.

出版信息

Biochim Biophys Acta Rev Cancer. 2018 Apr;1869(2):248-255. doi: 10.1016/j.bbcan.2018.02.001. Epub 2018 Feb 28.

Abstract

Clinico-pathological factors fail to consistently predict the outcome after pancreatic resection for pancreatic ductal adenocarcinoma (PDAC). PDACs show a high level of inter- and intra- tumor genetic heterogeneity. A molecular classification should help sort patients into less heterogeneous and more appropriate groups regarding the metastatic risk and the therapeutic response, with the consequences of better predicting evolution and better orienting the treatment. PDAC can be classified based on mutational subtypes and 18gene alterations. Whole-genome sequencing identified mutational signatures, mutational burden and hyper-mutated tumors with specific DNA repair defects. Their overlap/similarities allow the definition of molecular subtypes. DNA and RNA classifications can be used in prognosis assessment. They are useful in therapeutic choice for they allow the design of approaches that can predict the respective drug sensitivity of each molecular subtype. This review provides a comprehensive analysis of available molecular classifications in PDAC and how this can help guide clinical decisions.

摘要

临床病理因素不能始终如一地预测胰腺导管腺癌 (PDAC) 手术后的结果。PDAC 显示出高水平的肿瘤内和肿瘤间遗传异质性。分子分类应该有助于将患者分为转移风险和治疗反应较低异质性和更合适的组,从而更好地预测疾病进展并更好地指导治疗。PDAC 可以基于突变亚型和 18 个基因改变进行分类。全基因组测序确定了突变特征、突变负担和具有特定 DNA 修复缺陷的超突变肿瘤。它们的重叠/相似性允许定义分子亚型。DNA 和 RNA 分类可用于预后评估。它们在治疗选择中很有用,因为它们允许设计可以预测每个分子亚型各自药物敏感性的方法。这篇综述全面分析了 PDAC 中现有的分子分类,以及如何帮助指导临床决策。

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