Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
Sci Rep. 2016 Nov 30;6:38037. doi: 10.1038/srep38037.
Sequencing-based breast cancer diagnostics have the potential to replace routine biomarkers and provide molecular characterization that enable personalized precision medicine. Here we investigate the concordance between sequencing-based and routine diagnostic biomarkers and to what extent tumor sequencing contributes clinically actionable information. We applied DNA- and RNA-sequencing to characterize tumors from 307 breast cancer patients with replication in up to 739 patients. We developed models to predict status of routine biomarkers (ER, HER2,Ki-67, histological grade) from sequencing data. Non-routine biomarkers, including mutations in BRCA1, BRCA2 and ERBB2(HER2), and additional clinically actionable somatic alterations were also investigated. Concordance with routine diagnostic biomarkers was high for ER status (AUC = 0.95;AUC(replication) = 0.97) and HER2 status (AUC = 0.97;AUC(replication) = 0.92). The transcriptomic grade model enabled classification of histological grade 1 and histological grade 3 tumors with high accuracy (AUC = 0.98;AUC(replication) = 0.94). Clinically actionable mutations in BRCA1, BRCA2 and ERBB2(HER2) were detected in 5.5% of patients, while 53% had genomic alterations matching ongoing or concluded breast cancer studies. Sequencing-based molecular profiling can be applied as an alternative to histopathology to determine ER and HER2 status, in addition to providing improved tumor grading and clinically actionable mutations and molecular subtypes. Our results suggest that sequencing-based breast cancer diagnostics in a near future can replace routine biomarkers.
基于测序的乳腺癌诊断有可能替代常规生物标志物，并提供分子特征，从而实现个体化精准医疗。在这里，我们研究了基于测序的和常规诊断生物标志物之间的一致性，以及肿瘤测序在多大程度上提供了临床可操作的信息。我们对 307 名乳腺癌患者的肿瘤进行了 DNA 和 RNA 测序，并在多达 739 名患者中进行了复制。我们开发了模型，以从测序数据中预测常规生物标志物（ER、HER2、Ki-67、组织学分级）的状态。还研究了非常规生物标志物，包括 BRCA1、BRCA2 和 ERBB2（HER2）中的突变，以及其他临床可操作的体细胞改变。ER 状态（AUC=0.95；AUC（复制）=0.97）和 HER2 状态（AUC=0.97；AUC（复制）=0.92）与常规诊断生物标志物的一致性很高。转录组学分级模型能够准确地对组织学分级 1 级和组织学分级 3 级的肿瘤进行分类（AUC=0.98；AUC（复制）=0.94）。在 5.5%的患者中检测到 BRCA1、BRCA2 和 ERBB2（HER2）的临床可操作突变，而 53%的患者具有与正在进行或已完成的乳腺癌研究相匹配的基因组改变。基于测序的分子谱分析除了提供改进的肿瘤分级和临床可操作的突变和分子亚型外，还可以替代组织病理学来确定 ER 和 HER2 状态。我们的结果表明，基于测序的乳腺癌诊断在不久的将来可以替代常规生物标志物。
