Integrating Tumor and Stromal Gene Expression Signatures With Clinical Indices for Survival Stratification of Early-Stage Non-Small Cell Lung Cancer

J Natl Cancer Inst. 2015 Aug 18;107(10):djv211. doi: 10.1093/jnci/djv211. Print 2015 Oct.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Apoptosis Regulatory Proteins / analysis
  • Biomarkers, Tumor / analysis*
  • Carcinoma, Non-Small-Cell Lung / chemistry*
  • Carcinoma, Non-Small-Cell Lung / mortality*
  • 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 / chemistry*
  • Lung Neoplasms / mortality*
  • 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
  • Transcriptome*
  • United States / epidemiology

Substances

  • Apoptosis Regulatory Proteins
  • BCAM protein, human
  • Biomarkers, Tumor
  • Cell Adhesion Molecules
  • DNA-Binding Proteins
  • FAIM protein, human
  • GINS1 protein, human
  • Germinal Center Kinases
  • Glucose Transporter Type 1
  • Histocompatibility Antigens Class I
  • KRT6A protein, human
  • Keratin-6
  • Lutheran Blood-Group System
  • MAD2L1 protein, human
  • Mad2 Proteins
  • Nuclear Proteins
  • Receptors, Fc
  • SLC2A1 protein, human
  • Histone Demethylases
  • KDM6A protein, human
  • Protein-Serine-Threonine Kinases
  • Fc receptor, neonatal