Introduction Lung cancer is the leading killer cancer worldwide. There is an urgent need for easy-to-use and robust clinical gene signatures for improved prognosis and treatment prediction. Methods We used a gene expression signature termed the Yin and Yang mean ratio (YMR), which is based on two groups of genes with opposing function, to determine lung cancer prognosis. The YMR signature represents the relative state of an individual tumor on a gene expression spectrum ranging from malignancy to the normal healthy lung. The genes in the YMR signature have therefore been determined independently of survival time, which is different from previous regression models. We then leveraged the cross-platform utility of the YMR signature to optimize the signature into a smaller set of genes that validated the robustness of the signature in many independent lung cancer expression data sets. Results Four Yin and six Yang genes were optimized using 741 NSCLC cases from diverse platforms, including microarray and RNA sequencing. The 10-gene signature demonstrated significant differences in survival in eight individual independent data sets and a larger combined 1346-patient data set. When multivariate analysis taking into account other common predictors of survival was used, the 5-year recurrence-free rate of YMR (p = 6.4 × 10-6, HR =1.71 [1.36-2.16]) was secondary only to stage. The YMR signature significantly separated high-and low-risk patients with stage IA or 1B adenocarcinoma and squamous cell carcinomas of all stages. The YMR signature can also predict the benefit of adjuvant chemotherapy in high-risk patients with stage I NSCLC. Conclusions The YMR signature has great potential for guiding clinical management for NSCLC, particularly early-stage disease. The signature appears more reproducible than older signatures and functions using a variety of common gene expression platforms.
Bibliographical notePublisher Copyright:
© 2016 International Association for the Study of Lung Cancer.
- Gene expression
- Lung cancer
- Yin Yang