TY - JOUR
T1 - Identification of module biomarkers from the dysregulated ceRNA-ceRNA interaction network in lung adenocarcinoma
AU - Shao, Tingting
AU - Wu, Aiwei
AU - Chen, Juan
AU - Chen, Hong
AU - Lu, Jianping
AU - Bai, Jing
AU - Li, Yongsheng
AU - Xu, Juan
AU - Li, Xia
N1 - Publisher Copyright:
© The Royal Society of Chemistry 2015.
PY - 2015
Y1 - 2015
N2 - Competitive endogenous RNA (ceRNA) represents a novel layer of gene regulation that plays important roles in the physiology and development of diseases such as cancer and its dysregulation could contribute to cancer pathogenesis. Here, we have proposed a computational method to systematically identify genome-wide dysregulated ceRNA-ceRNA interactions by integrating microRNA regulation with expression profiles in cancer and normal tissues by RNA sequencing, as well as considering the details of how the behavior of ceRNAs has changed. These gain or loss dysregulations further assemble into a dysregulated ceRNA-ceRNA network; lncRNAs and pseudogenes are also considered. After applying the method to lung adenocarcinoma, we found that most dysregulations are connected together and formed a lung adenocarcinoma dysregulated ceRNA-ceRNA network (LDCCNet). Our analyses found that ceRNA pairs with gain regulations have consistent expression in cancer, otherwise for loss regulation, it is not necessary. Moreover, ceRNAs with more significant gain regulations (gain ceRNAs) undergo stronger regulation in cancer; thus their expression is more likely to decrease in cancer, while the expression of loss ceRNAs displays a rising trend. Additionally, we found that gain and loss ceRNAs as topological key nodes are implicated in the development of cancer. Finally, dysregulated ceRNA modules were identified, which are significantly enriched with known lung cancer microRNAs. We further found that several modules have the power as diagnostic biomarkers even in three independent datasets. For example, the module with lncRNA RP11-457M11.2 as a center is involved in the epithelial cell morphogenesis process and provides the average AUC values of 0.95. Our study about LDCCNet opens up the possibility of a new biological mechanism in cancer that could serve as a biomarker for diagnosis.
AB - Competitive endogenous RNA (ceRNA) represents a novel layer of gene regulation that plays important roles in the physiology and development of diseases such as cancer and its dysregulation could contribute to cancer pathogenesis. Here, we have proposed a computational method to systematically identify genome-wide dysregulated ceRNA-ceRNA interactions by integrating microRNA regulation with expression profiles in cancer and normal tissues by RNA sequencing, as well as considering the details of how the behavior of ceRNAs has changed. These gain or loss dysregulations further assemble into a dysregulated ceRNA-ceRNA network; lncRNAs and pseudogenes are also considered. After applying the method to lung adenocarcinoma, we found that most dysregulations are connected together and formed a lung adenocarcinoma dysregulated ceRNA-ceRNA network (LDCCNet). Our analyses found that ceRNA pairs with gain regulations have consistent expression in cancer, otherwise for loss regulation, it is not necessary. Moreover, ceRNAs with more significant gain regulations (gain ceRNAs) undergo stronger regulation in cancer; thus their expression is more likely to decrease in cancer, while the expression of loss ceRNAs displays a rising trend. Additionally, we found that gain and loss ceRNAs as topological key nodes are implicated in the development of cancer. Finally, dysregulated ceRNA modules were identified, which are significantly enriched with known lung cancer microRNAs. We further found that several modules have the power as diagnostic biomarkers even in three independent datasets. For example, the module with lncRNA RP11-457M11.2 as a center is involved in the epithelial cell morphogenesis process and provides the average AUC values of 0.95. Our study about LDCCNet opens up the possibility of a new biological mechanism in cancer that could serve as a biomarker for diagnosis.
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U2 - 10.1039/c5mb00364d
DO - 10.1039/c5mb00364d
M3 - Article
C2 - 26325208
AN - SCOPUS:84944244842
SN - 1742-206X
VL - 11
SP - 3048
EP - 3058
JO - Molecular BioSystems
JF - Molecular BioSystems
IS - 11
ER -