Application of gene expression profiling in molecular classification of multiplemyeloma
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摘要: 多发性骨髓瘤（multiple myeloma，MM）是一种具有高度异质性的恶性浆细胞疾病。在过去的几年里，随着新药的出现患者的生存已得到极大的改善，但在分子分型及预后评估方面仍面临挑战。以基因表达谱（gene expression profiling，GEP）技术为基础的转录组学研究在很大程度上有助于破译MM的复杂性，为MM的分子分型提供新的视角。基因表达谱芯片可以检测编码和非编码基因的表达、突变和新的转录组修饰，提供更多不同骨髓瘤亚群治疗和预后的新信息。目前，已在多项临床试验中发现基因表达谱可以作为独立的预后因素评估不同队列患者的预后。尽管目前临床上尚未将基因表达谱整合到骨髓瘤的诊断和治疗中，但多个研究中心已开展针对骨髓瘤的表达谱数据研究。通过对公共数据库表达谱数据进行聚类分析，建立临床预后模型，在疾病的动态演变中识别高风险和低风险患者，预测治疗敏感性，找寻新的治疗靶点，使得从转录组水平上制定个体化治疗成为可能。本文就基因表达谱技术在骨髓瘤分子分型中的应用展开综述。Abstract: Multiple myeloma (MM) is a highly heterogeneous malignant plasma cell disease. Although the survival of patients has been significantly improved with the advent of new drugs in the past few years, molecular classification and prognostic evaluation are still challenging. Transcriptome studies based on gene expression profiling help decipher the complexity of MM, providing a new perspective for the molecular classification of MM. Gene expression profiling can assess the expression of coding and noncoding genes, mutations, and novel transcriptome modifiers, providing additional information about the treatment and prognosis of different MM subgroups. Gene expression profiling has been confirmed as an independent prognostic factor in multiple clinical trials to evaluate the prognosis of patients in different cohorts. Although gene expression profiling has not yet been clinically integrated into diagnosis and treatment, expression profiling data for myeloma have been studied at several research centers. Through cluster analysis of expression profiling data in public databases, clinical prognostic models are established to identify high-risk and low-risk patients in the dynamic evolution of the disease, predict treatment sensitivity, and find new therapeutic targets, making it possible to develop individualized treatment at the transcriptome level. This article reviews the application of gene expression profiling in the molecular classification of myeloma.
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Key words:
- multiple myeloma (MM) /
- gene expression profiling /
- microarray /
- transcriptome
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表 1 多发性骨髓瘤TC五组分型
分组 原发易位 基因断裂点 cyclin D 染色体倍性 初诊发生率（%） TC1 11q13 CCND1 D1 非超二倍体 15 6p21 CCND3 D3 非超二倍体 3 TC2 无 无 D2 超二倍体 37 TC3 无 无 D2 超二倍体=非超二倍体 22 TC4 4p16 FGFR3/MMSET D2 非超二倍体>超二倍体 16 TC5 16q23 c-maf D2 非超二倍体 5 20q11 mafB D2 非超二倍体 2 
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表 2 多发性骨髓瘤的TC8组分型
分组 原发易位 基因断裂点 cyclin D 未治患者发生率（%） 复发患者发生率（%） 6p21 6p21 CCND3 D3 3 3 11q13 11q13 CCND1 D1 16 17 D1 无 无 D1 34 10 D1+D2 无 无 D1+D2 6 17 D2 无 无 D2 17 20 无 无 无 无 2 3 4p16 4p16 FGFR3/MMSET D2 15 23 maf 16q23，20q11 MAF，MAFB D2 7 7
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