1. Integrating Tumor and Stromal Gene Expression Signatures With Clinical Indices for Survival Stratification of Early-Stage Non-Small Cell Lung Cancer.
- Author
-
Gentles AJ, Bratman SV, Lee LJ, Harris JP, Feng W, Nair RV, Shultz DB, Nair VS, Hoang CD, West RB, Plevritis SK, Alizadeh AA, and Diehn M
- Subjects
- Adult, Aged, Apoptosis Regulatory Proteins analysis, Carcinoma, Non-Small-Cell Lung pathology, Cell Adhesion Molecules analysis, DNA-Binding Proteins analysis, Datasets as Topic, Female, Flow Cytometry, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Germinal Center Kinases, Glucose Transporter Type 1 analysis, Histocompatibility Antigens Class I analysis, Histone Demethylases analysis, Humans, Kaplan-Meier Estimate, Keratin-6 analysis, Lung Neoplasms pathology, Lutheran Blood-Group System analysis, Mad2 Proteins analysis, Male, Middle Aged, Neoplasm Staging, Nuclear Proteins analysis, Polymerase Chain Reaction methods, Predictive Value of Tests, Prognosis, Protein Serine-Threonine Kinases analysis, Receptors, Fc analysis, SEER Program, United States epidemiology, Biomarkers, Tumor analysis, Carcinoma, Non-Small-Cell Lung chemistry, Carcinoma, Non-Small-Cell Lung mortality, Lung Neoplasms chemistry, Lung Neoplasms mortality, Transcriptome
- Abstract
Background: Accurate survival stratification in early-stage non-small cell lung cancer (NSCLC) could inform the use of adjuvant therapy. We developed a clinically implementable mortality risk score incorporating distinct tumor microenvironmental gene expression signatures and clinical variables., Methods: Gene expression profiles from 1106 nonsquamous NSCLCs were used for generation and internal validation of a nine-gene molecular prognostic index (MPI). A quantitative polymerase chain reaction (qPCR) assay was developed and validated on an independent cohort of formalin-fixed paraffin-embedded (FFPE) tissues (n = 98). A prognostic score using clinical variables was generated using Surveillance, Epidemiology, and End Results data and combined with the MPI. All statistical tests for survival were two-sided., Results: The MPI stratified stage I patients into prognostic categories in three microarray and one FFPE qPCR validation cohorts (HR = 2.99, 95% CI = 1.55 to 5.76, P < .001 in stage IA patients of the largest microarray validation cohort; HR = 3.95, 95% CI = 1.24 to 12.64, P = .01 in stage IA of the qPCR cohort). Prognostic genes were expressed in distinct tumor cell subpopulations, and genes implicated in proliferation and stem cells portended poor outcomes, while genes involved in normal lung differentiation and immune infiltration were associated with superior survival. Integrating the MPI with clinical variables conferred greatest prognostic power (HR = 3.43, 95% CI = 2.18 to 5.39, P < .001 in stage I patients of the largest microarray cohort; HR = 3.99, 95% CI = 1.67 to 9.56, P < .001 in stage I patients of the qPCR cohort). Finally, the MPI was prognostic irrespective of somatic alterations in EGFR, KRAS, TP53, and ALK., Conclusion: The MPI incorporates genes expressed in the tumor and its microenvironment and can be implemented clinically using qPCR assays on FFPE tissues. A composite model integrating the MPI with clinical variables provides the most accurate risk stratification., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)
- Published
- 2015
- Full Text
- View/download PDF