Thomassen Mads, Tan Qihua, Burton Mark, Kruse Torben A
Department of Clinical Genetics, Odense University Hospital and Human Microarray Centre (HUMAC), University of Southern Denmark, Odense, Denmark.
Cancer Inform. 2013 Nov 25;12:203-19. doi: 10.4137/CIN.S12840. eCollection 2013.
Breast tumors have been described by molecular subtypes characterized by pervasively different gene expression profiles. The subtypes are associated with different clinical parameters and origin of precursor cells. However, the biological pathways and chromosomal aberrations that differ between the subgroups are less well characterized. The molecular subtypes are associated with different risk of metastatic recurrence of the disease. Nevertheless, the performance of these overall patterns to predict outcome is far from optimal, suggesting that biological mechanisms that extend beyond the subgroups impact metastasis.
We have scrutinized publicly available gene expression datasets and identified molecular subtypes in 1,394 breast tumors with outcome data. By analysis of chromosomal regions and pathways using "Gene set enrichment analysis" followed by a meta-analysis, we identified comprehensive mechanistic differences between the subgroups. Furthermore, the same approach was used to investigate mechanisms related to metastasis within the subgroups. A striking finding is that the molecular subtypes account for the majority of biological mechanisms associated with metastasis. However, some mechanisms, aside from the subtypes, were identified in a training set of 1,239 tumors and confirmed by survival analysis in two independent validation datasets from the same type of platform and consisting of very comparable node-negative patients that did not receive adjuvant medical therapy. The results show that high expression of 5q14 genes and low levels of TNFR2 pathway genes were associated with poor survival in basal-like cancers. Furthermore, low expression of 5q33 genes and interleukin-12 pathway genes were associated with poor outcome exclusively in ERBB2-like tumors.
The identified regions, genes, and pathways may be potential drug targets in future individualized treatment strategies.
乳腺肿瘤已通过具有普遍不同基因表达谱的分子亚型进行描述。这些亚型与不同的临床参数和前体细胞起源相关。然而,各亚组之间存在差异的生物学途径和染色体畸变的特征尚不明确。分子亚型与该疾病转移复发的不同风险相关。尽管如此,这些总体模式预测预后的性能远非最佳,这表明超出亚组范围的生物学机制会影响转移。
我们仔细研究了公开可用的基因表达数据集,并在1394例有预后数据的乳腺肿瘤中确定了分子亚型。通过使用“基因集富集分析”分析染色体区域和途径,随后进行荟萃分析,我们确定了各亚组之间全面的机制差异。此外,采用相同方法研究亚组内与转移相关的机制。一个显著发现是,分子亚型占与转移相关的大多数生物学机制。然而,除了这些亚型之外,在一个包含1239例肿瘤的训练集中还发现了一些机制,并在来自同一类型平台且由未接受辅助治疗的非常可比的淋巴结阴性患者组成的两个独立验证数据集中通过生存分析得到了证实。结果表明,5q14基因的高表达和TNFR2途径基因的低水平与基底样癌的不良生存相关。此外,5q33基因和白细胞介素-12途径基因的低表达仅与ERBB2样肿瘤的不良预后相关。
所确定的区域、基因和途径可能是未来个体化治疗策略中的潜在药物靶点。