Following are a strategy that I try to apply transcription factor binding site analysis to finding upstream signaling pathway of certain genes:
I have a list of co-expressed genes in cancer, then I do the transcription factor binding site (TFBS) analysis to find the enriched TFBSs located on those genes’ promoter. Following I go to a pathway database, find out pathways that those corresponding TFs are involved in respectively. Finally I combine another data to conclude that those co-expressed genes are potentially regulated by certain pathways including corresponding TF.
Can anyone share articles about using similar strategy as mentioned? Especially review articles. Many thanks.
Not a review, but something similar to that what you describe:
Article Inferring statin-induced gene regulatory relationships in pr...
This review by Sorin Draghici might be useful to you, http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3794382/
Both the mapping of enriched TFBS to co-regulated genes, and the regulation of TFs documented in curated signal transduction pathways have many potential pitfalls, so I'm not a huge fan of this approach. Some tools such as ModuleMiner, are free, but some of the more powerful pathway analysis tools such as Ingenuity and iPathwayGuide require licenses. If you can get access, the upside is that at least the analysis is fast, and you get a quick idea of whether it might be worth looking more carefully at some specific pathways. In general, though, there are too many assumptions built in to these types of analysis to get insightful findings into transcriptional networks.
Daniel, thank you for referring to my review. I have one small note to add. iPathway-Guide is actually completely free for now. You can do an unlimited number of full analyses that include the identification of significantly impacted pathways, identification of putative mechanisms that explain all observed expression changes, full GO analysis with dynamic hierarchical navigation, miRNAs, drugs, diseases, etc. https://apps.advaitabio.com/oauth-provider/login
Sorin- wonderful news that there is a window for free usage of the iPathway-Guide tool! Thanks for posting this correction.
RNA microarray analysis in prenatal mouse cochlea reveals novel IGF-I target genes: implication of MEF2 and FOXM1 transcription factors.
Sanchez-Calderon H, Rodriguez-de la Rosa L, Milo M, Pichel JG, Holley M, Varela-Nieto I.
PLoS One. 2010 Jan 25;5(1):e8699. doi: 10.1371/journal.pone.0008699.
PMID:
20111592
[PubMed - indexed for MEDLINE]
Thanks for everyone’s help.
Maria- Thanks for your sharing.
Daniel- Your information is really helpful. I will try to know more about ModuleMiner and iPathwayGuide.
As you mentioned, strategies like what I said may have potential pitfalls, so now I’m trying to find another strategies for analysis of translational regulation. By the way, thanks for sharing me the review article because I’m looking for review papers about pathway analysis as well.
Sorin- Thanks for your wonderful review. It provides me many conceptions and much information about pathway analysis which I need.
Yu-le- if you are open to designing new experiments to address this question, you might consider the TRAP technology to examine which mRNAs are translated in your cancer cells of interest.
Cell type-specific mRNA purification by translating ribosome affinity purification (TRAP).Heiman M, Kulicke R, Fenster RJ, Greengard P, Heintz N.Nat Protoc. 2014;9(6):1282-91. doi: 10.1038/nprot.2014.085.
Thanks for everyone’s help again.
Isabel- Thank you for your article. I will check those tools which are mentioned in your article.
Cohen- Thanks for your sharing. Actually, I am looking for some articles related to computational methods. Sorry for that I didn't define my question clearly.
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