Please use this identifier to cite or link to this item: https://doi.org/10.1038/s41467-017-01430-6
Title: An extracellular matrix-related prognostic and predictive indicator for early-stage non-small cell lung cancer
Authors: Lim, S.B
Tan, S.J
Lim, W.-T 
Lim, C.T 
Keywords: cancer
cells and cell components
chemotherapy
detection method
disease treatment
gene
prediction
respiratory disease
survival
tumor
adjuvant chemotherapy
Article
cancer prognosis
cancer survival
controlled study
early cancer
extracellular matrix
gene expression
human
human tissue
low risk population
microarray analysis
non small cell lung cancer
oncogene
outcome assessment
overall survival
predictive validity
recurrence free survival
scoring system
algorithm
biology
cancer staging
extracellular matrix
gene expression profiling
genetic database
genetics
genomics
Kaplan Meier method
lung tumor
multigene family
non small cell lung cancer
personalized medicine
prognosis
risk factor
tumor marker
Algorithms
Biomarkers, Tumor
Carcinoma, Non-Small-Cell Lung
Chemotherapy, Adjuvant
Computational Biology
Databases, Genetic
Extracellular Matrix
Gene Expression Profiling
Genomics
Humans
Kaplan-Meier Estimate
Lung Neoplasms
Multigene Family
Neoplasm Staging
Precision Medicine
Prognosis
Risk Factors
Issue Date: 2017
Publisher: Nature Publishing Group
Citation: Lim, S.B, Tan, S.J, Lim, W.-T, Lim, C.T (2017). An extracellular matrix-related prognostic and predictive indicator for early-stage non-small cell lung cancer. Nature Communications 8 (1) : 1734. ScholarBank@NUS Repository. https://doi.org/10.1038/s41467-017-01430-6
Abstract: The prognosis and prediction of adjuvant chemotherapy (ACT) response in early-stage non-small cell lung cancer (NSCLC) patients remain poor in this era of personalized medicine. We hypothesize that extracellular matrix (ECM)-associated components could be potential markers for better diagnosis and prognosis due to their differential expression in 1,943 primary NSCLC tumors as compared to 303 normal lung tissues. Here we develop a 29-gene ECM-related prognostic and predictive indicator (EPPI). We validate a robust performance of the EPPI risk scoring system in multiple independent data sets, comprising a total of 2,071 early-stage NSCLC tumors. Patients are stratified according to the universal cutoff score based on the EPPI when applied in the clinical setting; the low-risk group has significantly better survival outcome. The functional EPPI gene set represents a potential genomic tool to improve patient selection in early-stage NSCLC to further derive the best benefits of ACT and prevent unnecessary treatment or ACT-associated morbidity. © 2017 The Author(s).
Source Title: Nature Communications
URI: https://scholarbank.nus.edu.sg/handle/10635/174381
ISSN: 2041-1723
DOI: 10.1038/s41467-017-01430-6
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