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2017 ; 17
(1
): 447
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Identifying global expression patterns and key regulators in epithelial to
mesenchymal transition through multi-study integration
#MMPMID28651527
Parsana P
; Amend SR
; Hernandez J
; Pienta KJ
; Battle A
BMC Cancer
2017[Jun]; 17
(1
): 447
PMID28651527
show ga
BACKGROUND: Epithelial to mesenchymal transition (EMT) is the process by which
stationary epithelial cells transdifferentiate to mesenchymal cells with
increased motility. EMT is integral in early stages of development and wound
healing. Studies have shown that EMT could be a critical early event in tumor
metastasis that is involved in acquisition of migratory and invasive properties
in multiple carcinomas. METHODS: In this study, we used 15 published gene
expression microarray datasets from Gene Expression Omnibus (GEO) that represent
12 cell lines from 6 cancer types across 95 observations (45 unique samples and
50 replicates) with different modes of induction of EMT or the reverse
transition, mesenchymal to epithelial transition (MET). We integrated multiple
gene expression datasets while considering study differences, batch effects, and
noise in gene expression measurements. A universal differential EMT gene list was
obtained by normalizing and correcting the data using four approaches, computing
differential expression from each, and identifying a consensus ranking. We
confirmed our discovery of novel EMT genes at mRNA and protein levels in an in
vitro EMT model of prostate cancer - PC3 epi, EMT and Taxol resistant cell lines.
We validate our discovery of C1orf116 as a novel EMT regulator by siRNA knockdown
of C1orf116 in PC3 epithelial cells. RESULTS: Among differentially expressed
genes, we found known epithelial and mesenchymal marker genes such as CDH1 and
ZEB1. Additionally, we discovered genes known in a subset of carcinomas that were
unknown in prostate cancer. This included epithelial specific LSR and S100A14 and
mesenchymal specific DPYSL3. Furthermore, we also discovered novel EMT genes
including a poorly-characterized gene C1orf116. We show that decreased expression
of C1orf116 is associated with poor prognosis in lung and prostate cancer
patients. We demonstrate that knockdown of C1orf116 expression induced expression
of mesenchymal genes in epithelial prostate cancer cell line PC3-epi cells,
suggesting it as a candidate driver of the epithelial phenotype. CONCLUSIONS:
This comprehensive approach of statistical analysis and functional validation
identified global expression patterns in EMT and candidate regulatory genes,
thereby both extending current knowledge and identifying novel drivers of EMT.