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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 |
Appears in Collections: | Elements Staff Publications |
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