Prediction of survival in resected non-small cell lung cancer using a protein-expression based risk model: Implications for personalized chemoprevention and therapy
A partir d'une base de données portant sur 370 patients ayant subi une résection d'un cancer du poumon non à petites cellules (durée médiane de suivi : 5,3 ans), cette étude définit un modèle, basé sur des indicateurs cliniques et des biomarqueurs, pour prédire le risque de récidive
Purpose: Patients with resected non-small cell lung cancer (NSCLC) are at risk for recurrence of disease but we do not have tools to predict which patients are at highest risk. We set out to create a risk model incorporating both clinical data and biomarkers.
Methods: We assembled a comprehensive database with archival tissues and clinical follow-up from patients with NSCLC resected between 2002-2005. Twenty-one proteins identified from our preclinical studies as related to lung carcinogenesis were investigated, including pathways related to metabolism, DNA repair, inflammation and growth factors. Expression of proteins was quantified using immunohistochemistry. Immunohistochemistry was chosen because it is widely available and can be performed on formalin-fixed paraffin-embedded specimens. Cox models were fitted to estimate effects of clinical factors and biomarkers on recurrence free survival (RFS) and overall survival (OS).
Results: 370 patients are included in our analysis. With median follow-up of 5.3 years, median overall survival is 6.4 years. 209 cases with recurrence or death were observed. Multicovariate risk models for RFS and OS were developed including relevant biomarkers, age and stage. Increased expression of pAMPK, pmTOR, EpCAM, and CASK were significant (p<0.05) predictors for favorable RFS; insulin receptor, CXCR2, and IGF1R predicted for unfavorable RFS. Significant (p<0.05) predictors for favorable OS include pAMPK, pmTOR, and EpCAM; CXCR2 and FEN1 predicted unfavorable OS.
Conclusions: We have developed a comprehensive risk model predictive for recurrence in our large retrospective database, which is one of the largest reported series of resected NSCLC.
Clinical Cancer Research , résumé, 2013