A robust prognostic gene expression signature for early stage lung adenocarcinoma

BackgroundStage I lung adenocarcinoma is usually not treated with adjuvant chemotherapy; however, around half of these patients do not survive 5 years. Therefore, a reliable prognostic biomarker for early stage patients would be critical to identify those most likely to benefit from early additional treatments. Several studies have searched for gene expression prognostic biomarkers for lung adenocarcinoma, but these have not yielded a widely accepted prognosticator.ResultsWe analyzed gene expression from seven published lung adenocarcinoma cohorts for which we included only stage I and II patients who were not given adjuvant therapy. Seven genes consistently obtained statistical significance in Cox regression for overall survival. The combined signature has a weighted mean hazard ratio of 3.2 in all cohorts and 3.0 (C.I. 1.3–7.4, p < 0.01) in an independent validation cohort and is strongly correlated with previously published signatures of chromosomal instability and cell cycle progression.ConclusionsThe new prognostic signature, if validated prospectively, may enable better stratification and treatment of early stage lung cancer patients.

[1]  Igor Jurisica,et al.  Prognostic and predictive gene signature for adjuvant chemotherapy in resected non-small-cell lung cancer. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[2]  S Senan,et al.  2nd ESMO Consensus Conference on Lung Cancer: early-stage non-small-cell lung cancer consensus on diagnosis, treatment and follow-up. , 2014, Annals of oncology : official journal of the European Society for Medical Oncology.

[3]  Ash A. Alizadeh,et al.  Abstract PR09: The prognostic landscape of genes and infiltrating immune cells across human cancers , 2015 .

[4]  Zoltan Szallasi,et al.  Paradoxical relationship between chromosomal instability and survival outcome in cancer. , 2011, Cancer research.

[5]  Z. Szallasi,et al.  Correction of technical bias in clinical microarray data improves concordance with known biological information , 2008, Genome Biology.

[6]  I. Wistuba,et al.  Validation of a Molecular and Pathological Model for Five-Year Mortality Risk in Patients with Early Stage Lung Adenocarcinoma , 2014, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[7]  Igor Jurisica,et al.  Validation of a Histology-Independent Prognostic Gene Signature for Early-Stage, Non–Small-Cell Lung Cancer Including Stage IA Patients , 2014, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[8]  M. Cronin,et al.  A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. , 2004, The New England journal of medicine.

[9]  S. Paik.  Development and clinical utility of a 21-gene recurrence score prognostic assay in patients with early breast cancer treated with tamoxifen. , 2007, The oncologist.

[10]  Elisabeth Brambilla,et al.  Ectopic Activation of Germline and Placental Genes Identifies Aggressive Metastasis-Prone Lung Cancers , 2013, Science Translational Medicine.

[11]  Colin N. Dewey,et al.  RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome , 2011, BMC Bioinformatics.

[12]  Z. Szallasi,et al.  A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers , 2006, Nature Genetics.

[13]  Igor Jurisica,et al.  Gene expression–based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study , 2008, Nature Medicine.

[14]  Mats Lambe,et al.  Biomarker Discovery in Non–Small Cell Lung Cancer: Integrating Gene Expression Profiling, Meta-analysis, and Tissue Microarray Validation , 2012, Clinical Cancer Research.

[15]  E. Felip,et al.  Early stage and locally advanced (non-metastatic) non-small-cell lung cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. , 2010, Annals of oncology : official journal of the European Society for Medical Oncology.

[16]  Steven J. M. Jones,et al.  Comprehensive molecular profiling of lung adenocarcinoma , 2014, Nature.

[17]  Satoru Miyano,et al.  Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas. , 2012, Cancer research.

[18]  Z. Szallasi,et al.  Biasogram: Visualization of Confounding Technical Bias in Gene Expression Data , 2013, PloS one.

[19]  Edward S. Kim,et al.  Validation of a Proliferation-Based Expression Signature as Prognostic Marker in Early Stage Lung Adenocarcinoma , 2013, Clinical Cancer Research.

[20]  Nam Huh,et al.  Prediction of Recurrence-Free Survival in Postoperative Non–Small Cell Lung Cancer Patients by Using an Integrated Model of Clinical Information and Gene Expression , 2008, Clinical Cancer Research.