高分辨率基因组图谱定义了多发性骨髓瘤患者不同的临床-病理发生亚组。

High-resolution genomic profiles define distinct clinico-pathogenetic subgroups of multiple myeloma patients.

作者信息

Carrasco Daniel R, Tonon Giovanni, Huang Yongsheng, Zhang Yunyu, Sinha Raktim, Feng Bin, Stewart James P, Zhan Fenghuang, Khatry Deepak, Protopopova Marina, Protopopov Alexei, Sukhdeo Kumar, Hanamura Ichiro, Stephens Owen, Barlogie Bart, Anderson Kenneth C, Chin Lynda, Shaughnessy John D, Brennan Cameron, Depinho Ronald A

机构信息

Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA.

出版信息

Cancer Cell. 2006 Apr;9(4):313-25. doi: 10.1016/j.ccr.2006.03.019.

DOI:10.1016/j.ccr.2006.03.019

PMID:16616336

Abstract

To identify genetic events underlying the genesis and progression of multiple myeloma (MM), we conducted a high-resolution analysis of recurrent copy number alterations (CNAs) and expression profiles in a collection of MM cell lines and outcome-annotated clinical specimens. Attesting to the molecular heterogeneity of MM, unsupervised classification using nonnegative matrix factorization (NMF) designed for array comparative genomic hybridization (aCGH) analysis uncovered distinct genomic subtypes. Additionally, we defined 87 discrete minimal common regions (MCRs) within recurrent and highly focal CNAs. Further integration with expression data generated a refined list of MM gene candidates residing within these MCRs, thereby providing a genomic framework for dissection of disease pathogenesis, improved clinical management, and initiation of targeted drug discovery for specific MM patients.

摘要

为了确定多发性骨髓瘤（MM）发生和进展的潜在遗传事件，我们对一组MM细胞系以及带有预后注释的临床标本进行了反复拷贝数改变（CNA）和表达谱的高分辨率分析。为证明MM的分子异质性，使用专为阵列比较基因组杂交（aCGH）分析设计的非负矩阵分解（NMF）进行的无监督分类揭示了不同的基因组亚型。此外，我们在反复出现且高度集中的CNA中定义了87个离散的最小共同区域（MCR）。与表达数据的进一步整合产生了一份位于这些MCR内的MM基因候选物的精确列表，从而为剖析疾病发病机制、改善临床管理以及针对特定MM患者开展靶向药物发现提供了一个基因组框架。