Integration analysis of quantitative proteomics and transcriptomics data identifies potential targets of frizzled-8 protein-related antiproliferative factor in vivo.
What's known on the subject? and What does the study add? Interstitial cystitis (IC) is a prevalent and debilitating pelvic disorder generally accompanied by chronic pain combined with chronic urinating problems. Over one million Americans are affected, especially middle-aged women. However, its aetiology or mechanism remains unclear. No efficient drug has been provided to patients. Several urinary biomarker candidates have been identified for IC; among the most promising is antiproliferative factor (APF), whose biological activity is detectable in urine specimens from >94% of patients with both ulcerative and non-ulcerative IC. The present study identified several important mediators of the effect of APF on bladder cell physiology, suggesting several candidate drug targets against IC. In an attempt to identify potential proteins and genes regulated by APF in vivo, and to possibly expand the APF-regulated network identified by stable isotope labelling by amino acids in cell culture (SILAC), we performed an integration analysis of our own SILAC data and the microarray data of Gamper et al. (2009) BMC Genomics 10: 199. Notably, two of the proteins (i.e. MAPKSP1 and GSPT1) that are down-regulated by APF are involved in the activation of mTORC1, suggesting that the mammalian target of rapamycin (mTOR) pathway is potentially a critical pathway regulated by APF in vivo. Several components of the mTOR pathway are currently being studied as potential therapeutic targets in other diseases. Our analysis suggests that this pathway might also be relevant in the design of diagnostic tools and medications targeting IC.


OBJECTIVE
• To enhance our understanding of the interstitial cystitis urine biomarker antiproliferative factor (APF), as well as interstitial cystitis biology more generally at the systems level, we reanalyzed recently published large-scale quantitative proteomics and in vivo transcriptomics data sets using an integration analysis tool that we have developed.


METHODS
• To identify more differentially expressed genes with a lower false discovery rate from a previously published microarray data set, an integrative hypothesis-testing statistical approach was applied. • For validation experiments, expression and phosphorylation levels of select proteins were evaluated by western blotting.


RESULTS
• Integration analysis of this transcriptomics data set with our own quantitative proteomics data set identified 10 genes that are potentially regulated by APF in vivo from 4140 differentially expressed genes identified with a false discovery rate of 1%. • Of these, five (i.e. JUP, MAPKSP1, GSPT1, PTGS2/COX-2 and XPOT) were found to be prominent after network modelling of the common genes identified in the proteomics and microarray studies. • This molecular signature reflects the biological processes of cell adhesion, cell proliferation and inflammation, which is consistent with the known physiological effects of APF. • Lastly, we found the mammalian target of rapamycin pathway was down-regulated in response to APF.


CONCLUSIONS
• This unbiased integration analysis of in vitro quantitative proteomics data with in vivo quantitative transcriptomics data led to the identification of potential downstream mediators of the APF signal transduction pathway.
The Urological Diseases Research Center, Children's Hospital Boston, Boston, USA.
Wei
W
Yang
Yongsoo
Y
Kim
Taek-Kyun
TK
Kim
Susan K
SK
Keay
Kwang Pyo
KP
Kim
Hanno
H
Steen
Michael R
MR
Freeman
Daehee
D
Hwang
Jayoung
J
Kim
D015153:Blotting, Western; D049109:Cell Proliferation; D002478:Cells, Cultured; D018856:Cystitis, Interstitial / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D004247:DNA / Q000235:genetics*; D005260:Female; D005786:Gene Expression Regulation; D006023:Glycoproteins / Q000235:genetics* / Q000378:metabolism; D006801:Humans; D036341:Intercellular Signaling Peptides and Proteins; D040901:Proteomics / Q000379:methods*; D011956:Receptors, Cell Surface / Q000096:biosynthesis / Q000235:genetics*; D015398:Signal Transduction; D019459:Urothelium / Q000378:metabolism / Q000473:pathology
C529739:Fzd8 protein, human; D006023:Glycoproteins; D036341:Intercellular Signaling Peptides and Proteins; D011956:Receptors, Cell Surface; C490708:antiproliferative factor APF, human; D004247:DNA