Abstract
BackgroundTranscriptional regulatory network (TRN) is used to study conditional regulatory relationships between transcriptional factors and genes. However few studies have tried to integrate genomic variation information such as copy number variation (CNV) with TRN to find causal disturbances in a network. Intrahepatic cholangiocarcinoma (ICC) is the second most common hepatic carcinoma with high malignancy and poor prognosis. Research about ICC is relatively limited comparing to hepatocellular carcinoma, and there are no approved gene therapeutic targets yet.MethodWe first constructed TRN of ICC (ICC-TRN) using forward-and-reverse combined engineering method, and then integrated copy number variation information with ICC-TRN to select CNV-related modules and constructed CNV-ICC-TRN. We also integrated CNV-ICC-TRN with KEGG signaling pathways to investigate how CNV genes disturb signaling pathways. At last, unsupervised clustering method was applied to classify samples into distinct classes.ResultWe obtained CNV-ICC-TRN containing 33 modules which were enriched in ICC-related signaling pathways. Integrated analysis of the regulatory network and signaling pathways illustrated that CNV might interrupt signaling through locating on either genomic sites of nodes or regulators of nodes in a signaling pathway. In the end, expression profiles of nodes in CNV-ICC-TRN were used to cluster the ICC patients into two robust groups with distinct biological function features.ConclusionOur work represents a primary effort to construct TRN in ICC, also a primary effort to try to identify key transcriptional modules based on their involvement of genetic variations shown by gene copy number variations (CNV). This kind of approach may bring the traditional studies of TRN based only on expression data one step further to genetic disturbance. Such kind of approach can easily be extended to other disease samples with appropriate data.
Highlights
Transcriptional regulatory network (TRN) is a directed graph describing regulatory effect of transcriptional factors (TFs) on genes’ expression by binding to target DNA
Result: We obtained copy number variation (CNV)-Intrahepatic cholangiocarcinoma (ICC)-TRN containing 33 modules which were enriched in ICC-related signaling pathways
Our work represents a primary effort to construct TRN in ICC, a primary effort to try to identify key transcriptional modules based on their involvement of genetic variations shown by gene copy number variations (CNV)
Summary
Chromosome aberration: CNV We first studied DNA copy number profiles of 125 ICC samples, and found 42 regions with genomic variation including 12 amplified regions and 30 deleted regions. To study biological functions of modules of CNV-ICCTRN involved in, we implemented enrichment analysis based on KEGG signaling pathways, results are shown in Figure 3 and Table S3. Signaling pathway enrichment analysis of differentially expressed genes of CNV-ICC-TRN between two clusters (Table S6) suggested that these two classes had different malignancy features: highly expressed genes in cluster I were enriched to cell adhesion related pathways, such as focal adhesion and tight junction; highly expressed genes in cluster P were enriched to oncogenic signaling pathways such as MAPK signaling, Wnt signaling pathway (Table S7) These results demonstrate the potential application of our network in classification and prognosis analysis of ICC
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