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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 KEGG&GO annotations of the three motifs.The Venn diagram indicates the number of pathways and GO terms that the three motifs annotated to. (B,C) The barplot of the total genes of the top ten terms that the three motifs annotated to. Green represents triplet, red represents crosstalk and blue represents joint. For the whole annotations, see S3 Table.
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pone.0139165.g002: The KEGG&GO annotations of the three motifs.The Venn diagram indicates the number of pathways and GO terms that the three motifs annotated to. (B,C) The barplot of the total genes of the top ten terms that the three motifs annotated to. Green represents triplet, red represents crosstalk and blue represents joint. For the whole annotations, see S3 Table.

Mentions: From the quantitative viewpoint, the functions of the co-expression and interaction subnets were more extensive and these two subnets had several functions in common (Fig 2). There were 11, 38, and 57 genes annotated to the cell cycle pathway for triplet, crosstalk, and joint, respectively. There were 26 and 18 genes annotated to the NSCLC pathway for crosstalk and joint, while triplet did not have any genes annotated to NSCLC (S3 Table). All the results suggested that we needed to pay more attention to crosstalk and joint.


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 KEGG&GO annotations of the three motifs.The Venn diagram indicates the number of pathways and GO terms that the three motifs annotated to. (B,C) The barplot of the total genes of the top ten terms that the three motifs annotated to. Green represents triplet, red represents crosstalk and blue represents joint. For the whole annotations, see S3 Table.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0139165.g002: The KEGG&GO annotations of the three motifs.The Venn diagram indicates the number of pathways and GO terms that the three motifs annotated to. (B,C) The barplot of the total genes of the top ten terms that the three motifs annotated to. Green represents triplet, red represents crosstalk and blue represents joint. For the whole annotations, see S3 Table.
Mentions: From the quantitative viewpoint, the functions of the co-expression and interaction subnets were more extensive and these two subnets had several functions in common (Fig 2). There were 11, 38, and 57 genes annotated to the cell cycle pathway for triplet, crosstalk, and joint, respectively. There were 26 and 18 genes annotated to the NSCLC pathway for crosstalk and joint, while triplet did not have any genes annotated to NSCLC (S3 Table). All the results suggested that we needed to pay more attention to crosstalk and joint.

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