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Associating GWAS Information with the Notch Signaling Pathway Using Transcription Profiling.

Hicks C, Pannuti A, Miele L - Cancer Inform (2011)

Bottom Line: However, they offer limited insights about the biological mechanisms by which SNPs confer risk.We then investigated their expression, along with 32 genes involved in the Notch signaling pathway using two publicly available gene expression data sets from the Caucasian (42 cases and 143 controls) and Asian (43 cases and 43 controls) populations.Pathway prediction and network modeling confirmed that Notch receptors and genes involved in the Notch signaling pathway interact with genes containing SNPs associated with risk for breast cancer.

View Article: PubMed Central - PubMed

Affiliation: Cancer Institute, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS 39216, USA.

ABSTRACT
Genome-wide association studies (GWAS) have identified SNPs associated with breast cancer. However, they offer limited insights about the biological mechanisms by which SNPs confer risk. We investigated the association of GWAS information with a major oncogenic pathway in breast cancer, the Notch signaling pathway. We first identified 385 SNPs and 150 genes associated with risk for breast cancer by mining data from 41 GWAS. We then investigated their expression, along with 32 genes involved in the Notch signaling pathway using two publicly available gene expression data sets from the Caucasian (42 cases and 143 controls) and Asian (43 cases and 43 controls) populations. Pathway prediction and network modeling confirmed that Notch receptors and genes involved in the Notch signaling pathway interact with genes containing SNPs associated with risk for breast cancer. Additionally, we identified other SNP-associated biological pathways relevant to breast cancer, including the P53, apoptosis and MAP kinase pathways.

No MeSH data available.


Related in: MedlinePlus

Color codes indicating the biological process in which genes reported in figures 4–7 are involved.
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Related In: Results  -  Collection


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f3-cin-2011-093: Color codes indicating the biological process in which genes reported in figures 4–7 are involved.

Mentions: To formally test the hypothesis that candidate genes containing SNPs associated with risk for breast cancer interact with genes involved in the Notch signaling pathway, we performed pathway prediction and network modeling. As a first step, we performed pathway prediction and network modeling using the 71 candidate genes confirmed in the Causation population and all genes involved in the Notch signaling pathway. In addition we modeled the biological relationships of the genes in the predicted pathways and networks using Gene Ontology information and experimental information derived from the literature by text mining using the module built in the Osprey System. The key for GO information characterizing genes in the predicted pathways and networks according to the biological process in which they are involved is presented in Figure 3. The results of pathway prediction and network modeling for the Caucasian population are presented in Figure 4. For easy interpretation throughout the figures, names of candidate genes (ie, genes containing SNPs associated with risk for breast cancer) are shown in red. Names of genes involved in the Notch signaling pathway are shown in blue, while names of the new set of genes not identified by GWAS are shown in black. Nodes represent the genes and the vertices represent the interactions.


Associating GWAS Information with the Notch Signaling Pathway Using Transcription Profiling.

Hicks C, Pannuti A, Miele L - Cancer Inform (2011)

Color codes indicating the biological process in which genes reported in figures 4–7 are involved.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3091413&req=5

f3-cin-2011-093: Color codes indicating the biological process in which genes reported in figures 4–7 are involved.
Mentions: To formally test the hypothesis that candidate genes containing SNPs associated with risk for breast cancer interact with genes involved in the Notch signaling pathway, we performed pathway prediction and network modeling. As a first step, we performed pathway prediction and network modeling using the 71 candidate genes confirmed in the Causation population and all genes involved in the Notch signaling pathway. In addition we modeled the biological relationships of the genes in the predicted pathways and networks using Gene Ontology information and experimental information derived from the literature by text mining using the module built in the Osprey System. The key for GO information characterizing genes in the predicted pathways and networks according to the biological process in which they are involved is presented in Figure 3. The results of pathway prediction and network modeling for the Caucasian population are presented in Figure 4. For easy interpretation throughout the figures, names of candidate genes (ie, genes containing SNPs associated with risk for breast cancer) are shown in red. Names of genes involved in the Notch signaling pathway are shown in blue, while names of the new set of genes not identified by GWAS are shown in black. Nodes represent the genes and the vertices represent the interactions.

Bottom Line: However, they offer limited insights about the biological mechanisms by which SNPs confer risk.We then investigated their expression, along with 32 genes involved in the Notch signaling pathway using two publicly available gene expression data sets from the Caucasian (42 cases and 143 controls) and Asian (43 cases and 43 controls) populations.Pathway prediction and network modeling confirmed that Notch receptors and genes involved in the Notch signaling pathway interact with genes containing SNPs associated with risk for breast cancer.

View Article: PubMed Central - PubMed

Affiliation: Cancer Institute, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS 39216, USA.

ABSTRACT
Genome-wide association studies (GWAS) have identified SNPs associated with breast cancer. However, they offer limited insights about the biological mechanisms by which SNPs confer risk. We investigated the association of GWAS information with a major oncogenic pathway in breast cancer, the Notch signaling pathway. We first identified 385 SNPs and 150 genes associated with risk for breast cancer by mining data from 41 GWAS. We then investigated their expression, along with 32 genes involved in the Notch signaling pathway using two publicly available gene expression data sets from the Caucasian (42 cases and 143 controls) and Asian (43 cases and 43 controls) populations. Pathway prediction and network modeling confirmed that Notch receptors and genes involved in the Notch signaling pathway interact with genes containing SNPs associated with risk for breast cancer. Additionally, we identified other SNP-associated biological pathways relevant to breast cancer, including the P53, apoptosis and MAP kinase pathways.

No MeSH data available.


Related in: MedlinePlus