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2016 ; 7
(42
): 68688-68707
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Constructing Bayesian networks by integrating gene expression and copy number
data identifies NLGN4Y as a novel regulator of prostate cancer progression
#MMPMID27626693
Gong Y
; Wang L
; Chippada-Venkata U
; Dai X
; Oh WK
; Zhu J
Oncotarget
2016[Oct]; 7
(42
): 68688-68707
PMID27626693
show ga
To understand the heterogeneity of prostate cancer (PCa) and identify novel
underlying drivers, we constructed integrative molecular Bayesian networks
(IMBNs) for PCa by integrating gene expression and copy number alteration data
from published datasets. After demonstrating such IMBNs with superior network
accuracy, we identified multiple sub-networks within IMBNs related to biochemical
recurrence (BCR) of PCa and inferred the corresponding key drivers. The key
drivers regulated a set of common effectors including genes preferentially
expressed in neuronal cells. NLGN4Y-a protein involved in synaptic adhesion in
neurons-was ranked as the top gene closely linked to key drivers of myogenesis
subnetworks. Lower expression of NLGN4Y was associated with higher grade PCa and
an increased risk of BCR. We show that restoration of the protein expression of
NLGN4Y in PC-3 cells leads to decreased cell proliferation, migration and
inflammatory cytokine expression. Our results suggest that NLGN4Y is an important
negative regulator in prostate cancer progression. More importantly, it
highlights the value of IMBNs in generating biologically and clinically relevant
hypotheses about prostate cancer that can be validated by independent studies.