Comparing progression molecular mechanisms between lung adenocarcinoma and lung squamous cell carcinoma based on genetic and epigenetic networks: big data mining and genome-wide systems identification
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Shan-Ju Yeh1, Chien-An Chang1, Cheng-Wei Li1, Lily Hui-Ching Wang2 and Bor-Sen Chen1,3
1 Laboratory of Automatic Control, Signaling Processing, and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
2 Department of Medical Science, Institute of Molecular and Cellular Biology, National Tsing Hua University, Hsinchu 30013, Taiwan
3 Department of Electrical Engineering, Yuan Ze University, Chungli 32003, Taiwan
|Bor-Sen Chen,||email:||[email protected]|
Keywords: lung adenocarcinoma; lung squamous cell carcinoma; NSCLC; genetic and epigenetic network; potential drug target
Received: February 26, 2019 Accepted: April 29, 2019 Published: June 04, 2019
Non-small-cell lung cancer (NSCLC) is the predominant type of lung cancer in the world. Lung adenocarcinoma (LADC) and lung squamous cell carcinoma (LSCC) are subtypes of NSCLC. We usually regard them as different disease due to their unique molecular characteristics, distinct cells of origin and dissimilar clinical response. However, the differences of genetic and epigenetic progression mechanism between LADC and LSCC are complicated to analyze. Therefore, we applied systems biology approaches and big databases mining to construct genetic and epigenetic networks (GENs) with next-generation sequencing data of LADC and LSCC. In order to obtain the real GENs, system identification and system order detection are conducted on gene regulatory networks (GRNs) and protein-protein interaction networks (PPINs) for each stage of LADC and LSCC. The core GENs were extracted via principal network projection (PNP). Based on the ranking of projection values, we got the core pathways in respect of KEGG pathway. Compared with the core pathways, we found significant differences between microenvironments, dysregulations of miRNAs, epigenetic modifications on certain signaling transduction proteins and target genes in each stage of LADC and LSCC. Finally, we proposed six genetic and epigenetic multiple-molecule drugs to target essential biomarkers in each progression stage of LADC and LSCC, respectively.
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