Aziz Mohammad Azhar, Periyasamy Sathish, Al Yousef Zeyad, AlAbdulkarim Ibrahim, Al Otaibi Majed, Alfahed Abdulaziz, Alasiri Glowi
Medical Genomics, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.
Bioinformatics, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia.
PLoS One. 2014 Oct 21;9(10):e110134. doi: 10.1371/journal.pone.0110134. eCollection 2014.
Integrated analysis of genomic and transcriptomic level changes holds promise for a better understanding of colorectal cancer (CRC) biology. There is a pertinent need to explain the functional effect of genome level changes by integrating the information at the transcript level. Using high resolution cytogenetics array, we had earlier identified driver genes by 'Genomic Identification of Significant Targets In Cancer (GISTIC)' analysis of paired tumour-normal samples from colorectal cancer patients. In this study, we analyze these driver genes at three levels using exon array data--gene, exon and network. Gene level analysis revealed a small subset to experience differential expression. These results were reinforced by carrying out separate differential expression analyses (SAM and LIMMA). ATP8B1 was found to be the novel gene associated with CRC that shows changes at cytogenetic, gene and exon levels. Splice index of 29 exons corresponding to 13 genes was found to be significantly altered in tumour samples. Driver genes were used to construct regulatory networks for tumour and normal groups. There were rearrangements in transcription factor genes suggesting the presence of regulatory switching. The regulatory pattern of AHR gene was found to have the most significant alteration. Our results integrate data with focus on driver genes resulting in highly enriched novel molecules that need further studies to establish their role in CRC.
基因组和转录组水平变化的综合分析有望更好地理解结直肠癌（CRC）生物学。通过整合转录水平的信息来解释基因组水平变化的功能效应具有迫切需求。利用高分辨率细胞遗传学阵列，我们 earlier 通过对结直肠癌患者的配对肿瘤-正常样本进行“癌症中重要靶点的基因组鉴定（GISTIC）”分析，鉴定出了驱动基因。在本研究中，我们使用外显子阵列数据在基因、外显子和网络三个水平上分析这些驱动基因。基因水平分析显示一小部分基因存在差异表达。通过进行单独的差异表达分析（SAM 和 LIMMA），这些结果得到了加强。发现 ATP8B1 是与 CRC 相关的新基因，在细胞遗传学、基因和外显子水平上均有变化。在肿瘤样本中，发现对应于 13 个基因的 29 个外显子的剪接指数有显著改变。利用驱动基因构建肿瘤组和正常组的调控网络。转录因子基因存在重排，提示存在调控开关。发现 AHR 基因的调控模式改变最为显著。我们的结果整合了以驱动基因为重点的数据，产生了高度富集的新分子，需要进一步研究以确定它们在 CRC 中的作用。
