Limits...
Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action.

Sun J, Zhao M, Jia P, Wang L, Wu Y, Iverson C, Zhou Y, Bowton E, Roden DM, Denny JC, Aldrich MC, Xu H, Zhao Z - PLoS Comput. Biol. (2015)

Bottom Line: The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival.The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin's antidiabetic and anticancer effects.Some results are supported by previous studies.

View Article: PubMed Central - PubMed

Affiliation: School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America; Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.

ABSTRACT
A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin's antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks; 2) provides insights into the molecular mode of metformin; 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets.

No MeSH data available.


Related in: MedlinePlus

A novel metformin action pathway.Solid lines indicate the proposed mechanisms as supported by experimental evidence from literature. The two black dashed lines indicate the drug effects. The red dashed line indicates the relationship is existed but the direction is unknown. The arrows beside the gene names or biological processes indicate the metformin effects. Up-arrows indicate the corresponding genes or processes are up-regulated while the down-arrows indicate the corresponding genes or process are down-regulated.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4470683&req=5

pcbi.1004202.g007: A novel metformin action pathway.Solid lines indicate the proposed mechanisms as supported by experimental evidence from literature. The two black dashed lines indicate the drug effects. The red dashed line indicates the relationship is existed but the direction is unknown. The arrows beside the gene names or biological processes indicate the metformin effects. Up-arrows indicate the corresponding genes or processes are up-regulated while the down-arrows indicate the corresponding genes or process are down-regulated.

Mentions: Starting from above crosstalk subnetwork and the seven key nodes, we manually checked their publications and integrated the experimental evidence for further understanding their roles in the metformin actions. Through careful review, we summarized their function and action together and found that a novel MYC-centered pathway was hidden under the crosstalk subnetwork, which may play important roles in metformin action in T2D and cancer (Fig 7). The Myc-centered pathway included AMPK, STK11, MYC, SP1, and CDKN1A, which formed two small motifs: AMPK-STK11-MYC and MYC-SP1-CDKN1A.


Deciphering Signaling Pathway Networks to Understand the Molecular Mechanisms of Metformin Action.

Sun J, Zhao M, Jia P, Wang L, Wu Y, Iverson C, Zhou Y, Bowton E, Roden DM, Denny JC, Aldrich MC, Xu H, Zhao Z - PLoS Comput. Biol. (2015)

A novel metformin action pathway.Solid lines indicate the proposed mechanisms as supported by experimental evidence from literature. The two black dashed lines indicate the drug effects. The red dashed line indicates the relationship is existed but the direction is unknown. The arrows beside the gene names or biological processes indicate the metformin effects. Up-arrows indicate the corresponding genes or processes are up-regulated while the down-arrows indicate the corresponding genes or process are down-regulated.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4470683&req=5

pcbi.1004202.g007: A novel metformin action pathway.Solid lines indicate the proposed mechanisms as supported by experimental evidence from literature. The two black dashed lines indicate the drug effects. The red dashed line indicates the relationship is existed but the direction is unknown. The arrows beside the gene names or biological processes indicate the metformin effects. Up-arrows indicate the corresponding genes or processes are up-regulated while the down-arrows indicate the corresponding genes or process are down-regulated.
Mentions: Starting from above crosstalk subnetwork and the seven key nodes, we manually checked their publications and integrated the experimental evidence for further understanding their roles in the metformin actions. Through careful review, we summarized their function and action together and found that a novel MYC-centered pathway was hidden under the crosstalk subnetwork, which may play important roles in metformin action in T2D and cancer (Fig 7). The Myc-centered pathway included AMPK, STK11, MYC, SP1, and CDKN1A, which formed two small motifs: AMPK-STK11-MYC and MYC-SP1-CDKN1A.

Bottom Line: The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival.The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin's antidiabetic and anticancer effects.Some results are supported by previous studies.

View Article: PubMed Central - PubMed

Affiliation: School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America; Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.

ABSTRACT
A drug exerts its effects typically through a signal transduction cascade, which is non-linear and involves intertwined networks of multiple signaling pathways. Construction of such a signaling pathway network (SPNetwork) can enable identification of novel drug targets and deep understanding of drug action. However, it is challenging to synopsize critical components of these interwoven pathways into one network. To tackle this issue, we developed a novel computational framework, the Drug-specific Signaling Pathway Network (DSPathNet). The DSPathNet amalgamates the prior drug knowledge and drug-induced gene expression via random walk algorithms. Using the drug metformin, we illustrated this framework and obtained one metformin-specific SPNetwork containing 477 nodes and 1,366 edges. To evaluate this network, we performed the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T2D genome-wide association study (GWAS) dataset, three cancer GWAS datasets, and one GWAS dataset of cancer patients with T2D on metformin. The results showed that the metformin network was significantly enriched with disease genes for both T2D and cancer, and that the network also included genes that may be associated with metformin-associated cancer survival. Furthermore, from the metformin SPNetwork and common genes to T2D and cancer, we generated a subnetwork to highlight the molecule crosstalk between T2D and cancer. The follow-up network analyses and literature mining revealed that seven genes (CDKN1A, ESR1, MAX, MYC, PPARGC1A, SP1, and STK11) and one novel MYC-centered pathway with CDKN1A, SP1, and STK11 might play important roles in metformin's antidiabetic and anticancer effects. Some results are supported by previous studies. In summary, our study 1) develops a novel framework to construct drug-specific signal transduction networks; 2) provides insights into the molecular mode of metformin; 3) serves a model for exploring signaling pathways to facilitate understanding of drug action, disease pathogenesis, and identification of drug targets.

No MeSH data available.


Related in: MedlinePlus