PMID- 31217907
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20200225
IS  - 1949-2553 (Electronic)
IS  - 1949-2553 (Linking)
VI  - 10
IP  - 38
DP  - 2019 Jun 4
TI  - 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.
PG  - 3760-3806
LID - 10.18632/oncotarget.26940 [doi]
AB  - 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.
FAU - Yeh, Shan-Ju
AU  - Yeh SJ
AD  - Laboratory of Automatic Control, Signaling Processing, and Systems Biology, 
      Department of Electrical Engineering, National Tsing Hua University, Hsinchu 
      30013, Taiwan.
FAU - Chang, Chien-An
AU  - Chang CA
AD  - Laboratory of Automatic Control, Signaling Processing, and Systems Biology, 
      Department of Electrical Engineering, National Tsing Hua University, Hsinchu 
      30013, Taiwan.
FAU - Li, Cheng-Wei
AU  - Li CW
AD  - Laboratory of Automatic Control, Signaling Processing, and Systems Biology, 
      Department of Electrical Engineering, National Tsing Hua University, Hsinchu 
      30013, Taiwan.
FAU - Wang, Lily Hui-Ching
AU  - Wang LH
AD  - Department of Medical Science, Institute of Molecular and Cellular Biology, 
      National Tsing Hua University, Hsinchu 30013, Taiwan.
FAU - Chen, Bor-Sen
AU  - Chen BS
AD  - Laboratory of Automatic Control, Signaling Processing, and Systems Biology, 
      Department of Electrical Engineering, National Tsing Hua University, Hsinchu 
      30013, Taiwan.
AD  - Department of Electrical Engineering, Yuan Ze University, Chungli 32003, Taiwan.
LA  - eng
PT  - Journal Article
DEP - 20190604
PL  - United States
TA  - Oncotarget
JT  - Oncotarget
JID - 101532965
PMC - PMC6557199
OTO - NOTNLM
OT  - NSCLC
OT  - genetic and epigenetic network
OT  - lung adenocarcinoma
OT  - lung squamous cell carcinoma
OT  - potential drug target
COIS- CONFLICTS OF INTEREST The authors declare that there are no conflicts of interest 
      regarding the publication of this paper.
EDAT- 2019/06/21 06:00
MHDA- 2019/06/21 06:01
PMCR- 2019/06/04
CRDT- 2019/06/21 06:00
PHST- 2019/02/26 00:00 [received]
PHST- 2019/04/29 00:00 [accepted]
PHST- 2019/06/21 06:00 [entrez]
PHST- 2019/06/21 06:00 [pubmed]
PHST- 2019/06/21 06:01 [medline]
PHST- 2019/06/04 00:00 [pmc-release]
AID - 26940 [pii]
AID - 10.18632/oncotarget.26940 [doi]
PST - epublish
SO  - Oncotarget. 2019 Jun 4;10(38):3760-3806. doi: 10.18632/oncotarget.26940. 
      eCollection 2019 Jun 4.