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An Integrative Approach for Mapping Differentially Expressed Genes and Network Components Using Novel Parameters to Elucidate Key Regulatory Genes in Colorectal Cancer.

Sehgal M, Gupta R, Moussa A, Singh TR - PLoS ONE (2015)

Bottom Line: The microarray analyses facilitated differential expression of 631 significant genes employed in the progression of disease and supplied interesting associated up and down regulated genes like jun, fos and mapk1.These novel parameters can assist in scrutinizing candidate markers for diseases having known biological pathways.Further, investigating and targeting these proposed genes for experimental validations, instead being spellbound by the complicated pathway will certainly endow valuable insight in a well-timed systematic understanding of CRC.

View Article: PubMed Central - PubMed

Affiliation: Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology (JUIT), Waknaghat, Solan, H.P. 173234, India.

ABSTRACT
For examining the intricate biological processes concerned with colorectal cancer (CRC), a systems biology approach integrating several biological components and other influencing factors is essential to understand. We performed a comprehensive system level analysis for CRC which assisted in unravelling crucial network components and many regulatory elements through a coordinated view. Using this integrative approach, the perceptive of complexity hidden in a biological phenomenon is extensively simplified. The microarray analyses facilitated differential expression of 631 significant genes employed in the progression of disease and supplied interesting associated up and down regulated genes like jun, fos and mapk1. The transcriptional regulation of these genes was deliberated widely by examining transcription factors such as hnf4, nr2f1, znf219 and dr1 which directly influence the expression. Further, interactions of these genes/proteins were evaluated and crucial network motifs were detected to associate with the pathophysiology of CRC. The available standard statistical parameters such as z-score, p-value and significance profile were explored for the identification of key signatures from CRC pathway whereas a few novel parameters representing over-represented structures were also designed in the study. The applied approach revealed 5 key genes i.e. kras, araf, pik3r5, ralgds and akt3 via our novel designed parameters illustrating high statistical significance. These novel parameters can assist in scrutinizing candidate markers for diseases having known biological pathways. Further, investigating and targeting these proposed genes for experimental validations, instead being spellbound by the complicated pathway will certainly endow valuable insight in a well-timed systematic understanding of CRC.

No MeSH data available.


Related in: MedlinePlus

Significance profile for all 4–8 node generated sub-graphs based on normalized z-scores.The motif significance profile evidently exemplifies that when the complexity in CRC pathway increases, the interactions among the nodes and intricacy in recognition of genes amplifies immensely. Lesser the node size, it becomes easy to annotate the nodes (genes) and their associations with stronger statistical significance (greater normalized z-scores).
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pone.0133901.g007: Significance profile for all 4–8 node generated sub-graphs based on normalized z-scores.The motif significance profile evidently exemplifies that when the complexity in CRC pathway increases, the interactions among the nodes and intricacy in recognition of genes amplifies immensely. Lesser the node size, it becomes easy to annotate the nodes (genes) and their associations with stronger statistical significance (greater normalized z-scores).

Mentions: The calculated SP was then superlatively plotted on a graph against the different motifs as illustrated in Fig 7. The motif SP graph clearly depicts that as the number of nodes in a motif increase, the complexity increases and further the trend declines representing smaller normalized z-score values towards large motif sizes. Based upon this SP profile analysis we suggest that network motifs with smaller node size (3 or 4) are more functionally allied towards their role in pathways while motifs of larger size (> = 5 nodes) are less functional (Fig 7). It is believed that the observed trend might be similar in many such biological networks if analyzed.


An Integrative Approach for Mapping Differentially Expressed Genes and Network Components Using Novel Parameters to Elucidate Key Regulatory Genes in Colorectal Cancer.

Sehgal M, Gupta R, Moussa A, Singh TR - PLoS ONE (2015)

Significance profile for all 4–8 node generated sub-graphs based on normalized z-scores.The motif significance profile evidently exemplifies that when the complexity in CRC pathway increases, the interactions among the nodes and intricacy in recognition of genes amplifies immensely. Lesser the node size, it becomes easy to annotate the nodes (genes) and their associations with stronger statistical significance (greater normalized z-scores).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4519280&req=5

pone.0133901.g007: Significance profile for all 4–8 node generated sub-graphs based on normalized z-scores.The motif significance profile evidently exemplifies that when the complexity in CRC pathway increases, the interactions among the nodes and intricacy in recognition of genes amplifies immensely. Lesser the node size, it becomes easy to annotate the nodes (genes) and their associations with stronger statistical significance (greater normalized z-scores).
Mentions: The calculated SP was then superlatively plotted on a graph against the different motifs as illustrated in Fig 7. The motif SP graph clearly depicts that as the number of nodes in a motif increase, the complexity increases and further the trend declines representing smaller normalized z-score values towards large motif sizes. Based upon this SP profile analysis we suggest that network motifs with smaller node size (3 or 4) are more functionally allied towards their role in pathways while motifs of larger size (> = 5 nodes) are less functional (Fig 7). It is believed that the observed trend might be similar in many such biological networks if analyzed.

Bottom Line: The microarray analyses facilitated differential expression of 631 significant genes employed in the progression of disease and supplied interesting associated up and down regulated genes like jun, fos and mapk1.These novel parameters can assist in scrutinizing candidate markers for diseases having known biological pathways.Further, investigating and targeting these proposed genes for experimental validations, instead being spellbound by the complicated pathway will certainly endow valuable insight in a well-timed systematic understanding of CRC.

View Article: PubMed Central - PubMed

Affiliation: Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology (JUIT), Waknaghat, Solan, H.P. 173234, India.

ABSTRACT
For examining the intricate biological processes concerned with colorectal cancer (CRC), a systems biology approach integrating several biological components and other influencing factors is essential to understand. We performed a comprehensive system level analysis for CRC which assisted in unravelling crucial network components and many regulatory elements through a coordinated view. Using this integrative approach, the perceptive of complexity hidden in a biological phenomenon is extensively simplified. The microarray analyses facilitated differential expression of 631 significant genes employed in the progression of disease and supplied interesting associated up and down regulated genes like jun, fos and mapk1. The transcriptional regulation of these genes was deliberated widely by examining transcription factors such as hnf4, nr2f1, znf219 and dr1 which directly influence the expression. Further, interactions of these genes/proteins were evaluated and crucial network motifs were detected to associate with the pathophysiology of CRC. The available standard statistical parameters such as z-score, p-value and significance profile were explored for the identification of key signatures from CRC pathway whereas a few novel parameters representing over-represented structures were also designed in the study. The applied approach revealed 5 key genes i.e. kras, araf, pik3r5, ralgds and akt3 via our novel designed parameters illustrating high statistical significance. These novel parameters can assist in scrutinizing candidate markers for diseases having known biological pathways. Further, investigating and targeting these proposed genes for experimental validations, instead being spellbound by the complicated pathway will certainly endow valuable insight in a well-timed systematic understanding of CRC.

No MeSH data available.


Related in: MedlinePlus