UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia, Cheras, Kuala Lumpur, Malaysia.
UKM Medical Molecular Biology Institute, Universiti Kebangsaan Malaysia, Cheras, Kuala Lumpur, Malaysia; Department of Physiology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
PLoS One. 2014 Apr 2;9(4):e92553. doi: 10.1371/journal.pone.0092553. eCollection 2014.
Integrative analyses of multiple genomic datasets for selected samples can provide better insight into the overall data and can enhance our knowledge of cancer. The objective of this study was to elucidate the association between copy number variation (CNV) and gene expression in colorectal cancer (CRC) samples and their corresponding non-cancerous tissues. Sixty-four paired CRC samples from the same patients were subjected to CNV profiling using the Illumina HumanOmni1-Quad assay, and validation was performed using multiplex ligation probe amplification method. Genome-wide expression profiling was performed on 15 paired samples from the same group of patients using the Affymetrix Human Gene 1.0 ST array. Significant genes obtained from both array results were then overlapped. To identify molecular pathways, the data were mapped to the KEGG database. Whole genome CNV analysis that compared primary tumor and non-cancerous epithelium revealed gains in 1638 genes and losses in 36 genes. Significant gains were mostly found in chromosome 20 at position 20q12 with a frequency of 45.31% in tumor samples. Examples of genes that were associated at this cytoband were PTPRT, EMILIN3 and CHD6. The highest number of losses was detected at chromosome 8, position 8p23.2 with 17.19% occurrence in all tumor samples. Among the genes found at this cytoband were CSMD1 and DLC1. Genome-wide expression profiling showed 709 genes to be up-regulated and 699 genes to be down-regulated in CRC compared to non-cancerous samples. Integration of these two datasets identified 56 overlapping genes, which were located in chromosomes 8, 20 and 22. MLPA confirmed that the CRC samples had the highest gains in chromosome 20 compared to the reference samples. Interpretation of the CNV data in the context of the transcriptome via integrative analyses may provide more in-depth knowledge of the genomic landscape of CRC.
对选定样本的多个基因组数据集进行综合分析可以提供更全面的数据洞察,并增强我们对癌症的认识。本研究的目的是阐明结直肠癌(CRC)样本及其相应非癌组织中拷贝数变异(CNV)与基因表达之间的关联。对 64 对来自同一患者的 CRC 样本进行了 Illumina HumanOmni1-Quad 分析的 CNV 谱分析,并使用多重连接探针扩增方法进行了验证。对来自同一组患者的 15 对样本进行了全基因组表达谱分析,使用 Affymetrix Human Gene 1.0 ST 阵列。从两个阵列结果中获得的显著基因然后重叠。为了识别分子途径,将数据映射到 KEGG 数据库。与原发性肿瘤和非癌上皮细胞相比的全基因组 CNV 分析显示,有 1638 个基因获得增益,36 个基因丢失。在肿瘤样本中,20 号染色体 20q12 位置的增益最为明显,频率为 45.31%。与该细胞带相关的基因包括 PTPRT、EMILIN3 和 CHD6。在所有肿瘤样本中,丢失最严重的是 8 号染色体 8p23.2 位置,发生率为 17.19%。在该细胞带中发现的基因包括 CSMD1 和 DLC1。与非癌样本相比,全基因组表达谱显示 CRC 中有 709 个基因上调,699 个基因下调。将这两个数据集整合起来,确定了 56 个重叠基因,它们位于 8 号、20 号和 22 号染色体上。MLPA 证实 CRC 样本与参考样本相比,20 号染色体的增益最高。通过综合分析,在转录组背景下对 CNV 数据进行解释,可能会提供对 CRC 基因组景观更深入的了解。
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