Singh Virendra, Singh Laishram Chandreshwor, Vasudevan Madavan, Chattopadhyay Indranil, Borthakar Bibhuti Bhusan, Rai Avdhesh Kumar, Phukan Rup Kumar, Sharma Jagannath, Mahanta Jagadish, Kataki Amal Chandra, Kapur Sujala, Saxena Sunita
1 National Institute of Pathology (ICMR) , New Delhi, India .
2 Bionivid Technology Pvt Ltd , Bangalore, India .
OMICS. 2015 Nov;19(11):688-99. doi: 10.1089/omi.2015.0121. Epub 2015 Oct 23.
Esophageal cancer is a major global health burden with a strong host-environment interaction component and epigenomics underpinnings that remain to be elucidated further. Certain populations such as the Northeast Indians suffer at a disproportionately higher rate from this devastating disease. Promoter methylation is correlated with transcriptional silencing of various genes in esophageal cancer. Very few studies on genome-wide methylation for esophageal cancer exist and yet, no one has carried out an integromics analysis of methylation and gene expression. In the present study, genome-wide methylation was measured in samples collected from the Northeast Indian population by Infinium 450k array, and integration of the methylation data was performed. To prepare a network of genes displaying enriched pathways, together with the list of genes exhibiting promoter hypermethylation or hypomethylation with inversely correlated expression, we performed an integrome analysis. We identified 23 Integrome network enriched genes with relevance to tumor progression and associated with the processes involved in metastasis such as cell adhesion, integrin signaling, cytoskeleton, and extracellular matrix organizations. These included four genes (PTK2, RND1, RND3, and UBL3) with promoter hypermethylation and downregulation, and 19 genes (SEMG2, CD97, CTNND2, CADM3, OMD, NEFM, FBN2, CTNNB1, DLX6, UGT2B4, CCDC80, PZP, SERPINA4, TNFSF13B, NPC1, COL1A1, TAC3, BMP8A, and IL22RA2) with promoter hypomethylation and upregulation. A Methylation Efficiency Index was further calculated for these genes; the top five gene with the highest index were COL1A1, TAC3, SERPINA4, TNFSF13B, and IL22RA2. In conclusion, we recommend that the circulatory proteins IL22RA2, TNFSF13B, SERPINA4, and TAC3 in serum of patients and disease-free healthy controls can be examined in the future as putative noninvasive biomarkers.
食管癌是一项重大的全球健康负担,具有强烈的宿主 - 环境相互作用成分以及尚待进一步阐明的表观基因组学基础。某些人群,如东北印度人,患这种毁灭性疾病的比例特别高。启动子甲基化与食管癌中各种基因的转录沉默相关。关于食管癌全基因组甲基化的研究很少,而且尚未有人对甲基化和基因表达进行整合组学分析。在本研究中,通过Infinium 450k芯片对从东北印度人群收集的样本进行全基因组甲基化测量,并对甲基化数据进行整合。为了构建显示富集通路的基因网络,以及列出具有启动子高甲基化或低甲基化且表达呈负相关的基因列表,我们进行了整合组分析。我们鉴定出23个与肿瘤进展相关且与转移过程(如细胞粘附、整合素信号传导、细胞骨架和细胞外基质组织)相关的整合组网络富集基因。其中包括4个启动子高甲基化且下调的基因(PTK2、RND1、RND3和UBL3),以及19个启动子低甲基化且上调的基因(SEMG2、CD97、CTNND2、CADM3、OMD、NEFM、FBN2、CTNNB1、DLX6、UGT2B4、CCDC80、PZP、SERPINA4、TNFSF13B、NPC1、COL1A1、TAC3、BMP8A和IL22RA2)。进一步计算了这些基因的甲基化效率指数;指数最高的前五个基因是COL1A1、TAC3、SERPINA4、TNFSF13B和IL22RA2。总之,我们建议未来可以检查患者和无病健康对照血清中的循环蛋白IL22RA2、TNFSF13B、SERPINA4和TAC3,作为推定的非侵入性生物标志物。