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非小细胞肺癌的综合分子特征。

Integrated molecular portrait of non-small cell lung cancers.

机构信息

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

出版信息

BMC Med Genomics. 2013 Dec 3;6:53. doi: 10.1186/1755-8794-6-53.

Abstract

BACKGROUND

Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC.

METHODS

Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC.

RESULTS

At DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1 and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of ~800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944.

CONCLUSIONS

Integrated molecular characterization of AC and SCC helped identify clinically relevant markers and potential drivers, which are recurrent and stable changes at DNA level that have functional implications at RNA level and have strong association with histological subtypes.

摘要

背景

非小细胞肺癌(NSCLC)是癌症死亡的主要原因,它代表了一组异质性的肿瘤,主要包括鳞状细胞癌(SCC)、腺癌(AC)和大细胞癌(LCC)。本研究的目的是利用包括拷贝数改变、mRNA、microRNA 表达和候选基因全测序数据在内的综合基因组数据来描述 AC 和 SCC 之间的分子差异。

方法

对 123 对 NSCLC 患者的肿瘤和非肿瘤组织样本进行比较基因组杂交(CGH)后突变分析、基因表达和 miRNA 微阵列分析。

结果

在 DNA、mRNA 和 miRNA 水平上,我们可以识别出显著区分 NSCLC 各种组织病理学实体的分子标记物。我们使用 aCGH 数据识别出 34 个基因组簇;几个基因在 AC 和 SCC 之间表现出不同的畸变谱,包括 PIK3CA、SOX2、THPO、TP63、PDGFB 基因。基因表达谱分析确定 SPP1、CTHRC1 和 GREM1 为癌症早期诊断的潜在生物标志物,SPINK1 和 BMP7 可用于区分小活检或血液样本中的 AC 和 SCC。通过整合基因组学方法,我们在反复改变的区域中发现了一组三个潜在的驱动基因,即 MRPS22、NDRG1 和 RNF7,这些基因在扩增区域中一致过表达,与基因组中约 800 个基因具有广泛的相关性,并且与组织学类型高度相关。通过网络富集分析,这些潜在驱动基因的靶基因被认为参与 DNA 复制、细胞周期、错配修复、p53 信号通路和其他肺癌相关信号通路,以及许多免疫通路。此外,我们还鉴定了一个潜在的驱动 miRNA hsa-miR-944。

结论

AC 和 SCC 的综合分子特征有助于识别具有临床意义的标志物和潜在的驱动基因,这些基因是 DNA 水平上的反复和稳定变化,在 RNA 水平上具有功能意义,并与组织学亚型有很强的关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/4222074/162da3188a2b/1755-8794-6-53-1.jpg

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