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Identification of Biomarker and Co-Regulatory Motifs in Lung Adenocarcinoma Based on Differential Interactions.

Zhao N, Liu Y, Chang Z, Li K, Zhang R, Zhou Y, Qiu F, Han X, Xu Y - PLoS ONE (2015)

Bottom Line: Moreover, several biological functions (i.e., cell cycle, signaling pathways and hemopoiesis) associated with the three motifs were found to be frequently targeted by the drugs for lung adenocarcinoma.A 10-gene biomarker (UBC, SRC, SP1, MYC, STAT3, JUN, NR3C1, RB1, GRB2 and MAPK1) was selected from the joint motif, and a survival analysis indicated its significant association with survival.The genes, regulators and regulatory motifs detected in this work will provide potential drug targets and new strategies for individual therapy.

View Article: PubMed Central - PubMed

Affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.

ABSTRACT
Changes in intermolecular interactions (differential interactions) may influence the progression of cancer. Specific genes and their regulatory networks may be more closely associated with cancer when taking their transcriptional and post-transcriptional levels and dynamic and static interactions into account simultaneously. In this paper, a differential interaction analysis was performed to detect lung adenocarcinoma-related genes. Furthermore, a miRNA-TF (transcription factor) synergistic regulation network was constructed to identify three kinds of co-regulated motifs, namely, triplet, crosstalk and joint. Not only were the known cancer-related miRNAs and TFs (let-7, miR-15a, miR-17, TP53, ETS1, and so on) were detected in the motifs, but also the miR-15, let-7 and miR-17 families showed a tendency to regulate the triplet, crosstalk and joint motifs, respectively. Moreover, several biological functions (i.e., cell cycle, signaling pathways and hemopoiesis) associated with the three motifs were found to be frequently targeted by the drugs for lung adenocarcinoma. Specifically, the two 4-node motifs (crosstalk and joint) based on co-expression and interaction had a closer relationship to lung adenocarcinoma, and so further research was performed on them. A 10-gene biomarker (UBC, SRC, SP1, MYC, STAT3, JUN, NR3C1, RB1, GRB2 and MAPK1) was selected from the joint motif, and a survival analysis indicated its significant association with survival. Among the ten genes, JUN, NR3C1 and GRB2 are our newly detected candidate lung adenocarcinoma-related genes. The genes, regulators and regulatory motifs detected in this work will provide potential drug targets and new strategies for individual therapy.

No MeSH data available.


Related in: MedlinePlus

The survival analysis of ten hub genes of Joint.The “+” stands for the censoring samples. The X axis and Y axis respectively stands for observation time (months) and percent of survival people. Red and Green curves are high-risk group and low-risk group. The sources of data sets are on the top of each graph. Concordance Index (CI) and p-value are in the bottom-left insets.
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pone.0139165.g003: The survival analysis of ten hub genes of Joint.The “+” stands for the censoring samples. The X axis and Y axis respectively stands for observation time (months) and percent of survival people. Red and Green curves are high-risk group and low-risk group. The sources of data sets are on the top of each graph. Concordance Index (CI) and p-value are in the bottom-left insets.

Mentions: Finally, to estimate the effect on prognosis of the 10-gene biomarker, survival analysis was performed to evaluate the potential for their correlation to lung adenocarcinoma. We selected four data sets for the survival analysis from the TCGA and GEO databases and from two literature sources (Fig 3). The results showed that the biomarker could easily distinguish the high-risk and low-risk groups in each of the four data sets. All of the p-values were significant (p-value = 9.27x10-5 for PMID: 18641660, p-value = 7.85x10-3 for GEO: GSE13213, p-value = 6.68x10-4 for TCGA lung adenocarcinoma, and p-value = 3.69x10-4 for PMID: 19525976). This suggested that the biomarker was tightly associated with lung adenocarcinoma.


Identification of Biomarker and Co-Regulatory Motifs in Lung Adenocarcinoma Based on Differential Interactions.

Zhao N, Liu Y, Chang Z, Li K, Zhang R, Zhou Y, Qiu F, Han X, Xu Y - PLoS ONE (2015)

The survival analysis of ten hub genes of Joint.The “+” stands for the censoring samples. The X axis and Y axis respectively stands for observation time (months) and percent of survival people. Red and Green curves are high-risk group and low-risk group. The sources of data sets are on the top of each graph. Concordance Index (CI) and p-value are in the bottom-left insets.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4581687&req=5

pone.0139165.g003: The survival analysis of ten hub genes of Joint.The “+” stands for the censoring samples. The X axis and Y axis respectively stands for observation time (months) and percent of survival people. Red and Green curves are high-risk group and low-risk group. The sources of data sets are on the top of each graph. Concordance Index (CI) and p-value are in the bottom-left insets.
Mentions: Finally, to estimate the effect on prognosis of the 10-gene biomarker, survival analysis was performed to evaluate the potential for their correlation to lung adenocarcinoma. We selected four data sets for the survival analysis from the TCGA and GEO databases and from two literature sources (Fig 3). The results showed that the biomarker could easily distinguish the high-risk and low-risk groups in each of the four data sets. All of the p-values were significant (p-value = 9.27x10-5 for PMID: 18641660, p-value = 7.85x10-3 for GEO: GSE13213, p-value = 6.68x10-4 for TCGA lung adenocarcinoma, and p-value = 3.69x10-4 for PMID: 19525976). This suggested that the biomarker was tightly associated with lung adenocarcinoma.

Bottom Line: Moreover, several biological functions (i.e., cell cycle, signaling pathways and hemopoiesis) associated with the three motifs were found to be frequently targeted by the drugs for lung adenocarcinoma.A 10-gene biomarker (UBC, SRC, SP1, MYC, STAT3, JUN, NR3C1, RB1, GRB2 and MAPK1) was selected from the joint motif, and a survival analysis indicated its significant association with survival.The genes, regulators and regulatory motifs detected in this work will provide potential drug targets and new strategies for individual therapy.

View Article: PubMed Central - PubMed

Affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.

ABSTRACT
Changes in intermolecular interactions (differential interactions) may influence the progression of cancer. Specific genes and their regulatory networks may be more closely associated with cancer when taking their transcriptional and post-transcriptional levels and dynamic and static interactions into account simultaneously. In this paper, a differential interaction analysis was performed to detect lung adenocarcinoma-related genes. Furthermore, a miRNA-TF (transcription factor) synergistic regulation network was constructed to identify three kinds of co-regulated motifs, namely, triplet, crosstalk and joint. Not only were the known cancer-related miRNAs and TFs (let-7, miR-15a, miR-17, TP53, ETS1, and so on) were detected in the motifs, but also the miR-15, let-7 and miR-17 families showed a tendency to regulate the triplet, crosstalk and joint motifs, respectively. Moreover, several biological functions (i.e., cell cycle, signaling pathways and hemopoiesis) associated with the three motifs were found to be frequently targeted by the drugs for lung adenocarcinoma. Specifically, the two 4-node motifs (crosstalk and joint) based on co-expression and interaction had a closer relationship to lung adenocarcinoma, and so further research was performed on them. A 10-gene biomarker (UBC, SRC, SP1, MYC, STAT3, JUN, NR3C1, RB1, GRB2 and MAPK1) was selected from the joint motif, and a survival analysis indicated its significant association with survival. Among the ten genes, JUN, NR3C1 and GRB2 are our newly detected candidate lung adenocarcinoma-related genes. The genes, regulators and regulatory motifs detected in this work will provide potential drug targets and new strategies for individual therapy.

No MeSH data available.


Related in: MedlinePlus