Prediction of postoperative recurrence-free survival in non–small cell lung cancer by using an internationally validated gene expression model
R Mitra, J Lee, J Jo, M Milani, JN McClintick… - Clinical cancer …, 2011 - aacrjournals.org
Clinical cancer research, 2011•aacrjournals.org
Purpose: This study was performed to discover prognostic genomic markers associated with
postoperative outcome of stage I to III non–small cell lung cancer (NSCLC) that are
reproducible between geographically distant and demographically distinct patient
populations. Experimental Design: American patients (n= 27) were stratified on the basis of
recurrence and microarray profiling of their tumors was performed to derive a training set of
44 genes. A larger Korean patient validation cohort (n= 138) was also stratified by …
postoperative outcome of stage I to III non–small cell lung cancer (NSCLC) that are
reproducible between geographically distant and demographically distinct patient
populations. Experimental Design: American patients (n= 27) were stratified on the basis of
recurrence and microarray profiling of their tumors was performed to derive a training set of
44 genes. A larger Korean patient validation cohort (n= 138) was also stratified by …
Abstract
Purpose: This study was performed to discover prognostic genomic markers associated with postoperative outcome of stage I to III non–small cell lung cancer (NSCLC) that are reproducible between geographically distant and demographically distinct patient populations.
Experimental Design: American patients (n = 27) were stratified on the basis of recurrence and microarray profiling of their tumors was performed to derive a training set of 44 genes. A larger Korean patient validation cohort (n = 138) was also stratified by recurrence and screened for these genes. Four reproducible genes were identified and used to construct genomic and clinicogenomic Cox models for both cohorts.
Results: Four genomic markers, DBN1 (drebrin 1), CACNB3 (calcium channel beta 3), FLAD1 (PP591; flavin adenine dinucleotide synthetase), and CCND2 (cyclin D2), exhibited highly significant differential expression in recurrent tumors in the training set (P < 0.001). In the validation set, DBN1, FLAD1 (PP591), and CACNB3 were significant by Cox univariate analysis (P ≤ 0.035), whereas only DBN1 was significant by multivariate analysis. Genomic and clinicogenomic models for recurrence-free survival (RFS) were equally effective for risk stratification of stage I to II or I to III patients (all models P < 0.0001). For stage I to II or I to III patients, 5-year RFS of the low- and high-risk patients was approximately 70% versus 30% for both models. The genomic model for overall survival of stage I to III patients was improved by addition of pT and pN stage (P < 0.0013 vs. 0.010).
Conclusion: A 4-gene prognostic model incorporating the multivariate marker DBN1 exhibits potential clinical utility for risk stratification of stage I to III NSCLC patients. Clin Cancer Res; 17(9); 2934–46. ©2011 AACR.
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