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首页> 外文期刊>BMC Medical Genomics >Integrated molecular portrait of non-small cell lung cancers
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Integrated molecular portrait of non-small cell lung cancers

机译：非小细胞肺癌的综合分子画像

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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, CTHRC1and 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.
机译：背景技术非小细胞肺癌（NSCLC）是导致癌症死亡的主要原因，它代表了一组异质性肿瘤，主要包括鳞状细胞癌（SCC），腺癌（AC）和大细胞癌（LCC）。这项研究的目的是利用整合的基因组数据，包括拷贝数变化，mRNA，microRNA表达和候选基因全测序数据来表征AC和SCC之间的分子差异。方法对123例NSCLC患者的肿瘤和非肿瘤组织样本进行比较基因组杂交，然后进行突变分析，基因表达和miRNA芯片分析。结果在DNA，mRNA和miRNA的水平上，我们可以鉴定出明显区分NSCLC各种组织病理学实体的分子标记。我们使用aCGH数据鉴定了34个基因组簇。几个基因在AC和SCC之间表现出不同的像差图谱，包括PIK3CA，SOX2，THPO，TP63，PDGFB基因。基因表达谱分析确定SPP1，CTHRC1和GREM1是早期诊断癌症的潜在生物标志物，而SPINK1和BMP7则可以区分小活检或血液样本中的AC和SCC。使用整合的基因组学方法，我们在反复改变的区域中发现了三个潜在驱动基因MRPS22，NDRG1和RNF7的列表，它们在扩增区域中始终过度表达，与整个基因组中平均约800个基因具有广泛的相关性。与组织学类型高度相关。使用网络富集分析，这些潜在驱动程序的目标被认为与DNA复制，细胞周期，错配修复，p53信号通路和其他肺癌相关的信号通路以及许多免疫学途径有关。此外，我们还确定了一种潜在的驱动程序miRNA hsa-miR-944。结论AC和SCC的综合分子表征有助于鉴定临床相关的标志物和潜在驱动因素，这些标志物和潜在驱动因素在DNA水平上是反复且稳定的变化，在RNA水平上具有功能意义，并与组织学亚型密切相关。

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