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2014 ; 35
(6
): 1292-300
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Epithelial-mesenchymal transition-associated secretory phenotype predicts
survival in lung cancer patients
#MMPMID24510113
Reka AK
; Chen G
; Jones RC
; Amunugama R
; Kim S
; Karnovsky A
; Standiford TJ
; Beer DG
; Omenn GS
; Keshamouni VG
Carcinogenesis
2014[Jun]; 35
(6
): 1292-300
PMID24510113
show ga
In cancer cells, the process of epithelial-mesenchymal transition (EMT) confers
migratory and invasive capacity, resistance to apoptosis, drug resistance,
evasion of host immune surveillance and tumor stem cell traits. Cells undergoing
EMT may represent tumor cells with metastatic potential. Characterizing the EMT
secretome may identify biomarkers to monitor EMT in tumor progression and provide
a prognostic signature to predict patient survival. Utilizing a transforming
growth factor-?-induced cell culture model of EMT, we quantitatively profiled
differentially secreted proteins, by GeLC-tandem mass spectrometry. Integrating
with the corresponding transcriptome, we derived an EMT-associated secretory
phenotype (EASP) comprising of proteins that were differentially upregulated both
at protein and mRNA levels. Four independent primary tumor-derived gene
expression data sets of lung cancers were used for survival analysis by the
random survival forests (RSF) method. Analysis of 97-gene EASP expression in
human lung adenocarcinoma tumors revealed strong positive correlations with lymph
node metastasis, advanced tumor stage and histological grade. RSF analysis built
on a training set (n = 442), including age, sex and stage as variables,
stratified three independent lung cancer data sets into low-, medium- and
high-risk groups with significant differences in overall survival. We further
refined EASP to a 20 gene signature (rEASP) based on variable importance scores
from RSF analysis. Similar to EASP, rEASP predicted survival of both
adenocarcinoma and squamous carcinoma patients. More importantly, it predicted
survival in the early-stage cancers. These results demonstrate that integrative
analysis of the critical biological process of EMT provides mechanism-based and
clinically relevant biomarkers with significant prognostic value.