The Use of Pharmacogenomics for Selection of Therapy in Non-Small-Cell Lung Cancer

Abstract

INTRODUCTIONPerformance status (PS) is the only known clinical predictor of outcome in patients with advanced non-small-cell lung cancer (NSCLC), although pharmacogenomic markers may also correlate with outcome. The aim of our study was to correlate clinical and pharmacogenomic measures with overall survival.METHODSThis was an IRB approved, retrospective study in which the medical records of 50 patients with advanced NSCLC from 1998–2008 were reviewed, and gender, race, PS, and chemotherapy regimens were documented. Stromal expression of pharmacogenomic markers (VEGFR, ERCC1, 14-3-3σ, pAKT, and PTEN) was measured. Clinical factors and pharmacogenomics markers were compared to overall survival using a Cox proportional hazards model.RESULTSForty patients received platinum-based therapy. Median age was 65 years. Improved PS, female gender, and gemcitabine therapy were significantly associated with longer overall survival (P = 0.004, P = 0.04, and P = 0.003, respectively). Age was not associated with survival. Caucasians had better overall survival in comparison to African Americans with median survival of 14.8 months versus 10.4 months (P = 0.1). Patients treated with platinum-based therapy had better survival of 15 months versus 8 months for non-platinum based therapy (P = 0.01). There was no significant association between any of the pharmacogenomics markers and overall survival other than in patients treated with platinum, in whom ERCC1 negativity was strongly associated with longer survival (P = 0.007).CONCLUSIONERCC1 negativity with platinum therapy, gemcitabine therapy, good PS, and female gender all correlated with improved overall survival in patients with advanced NSCLC.

Organotypic three-dimensional cancer cell cultures mirror drug responsesin vivo: lessons learned from the inhibition of EGFR signaling

“…This knowledge is instrumental for predicting the efficacy of targeted drugs in individual patients [ 9 , 10 ]. The overall aim is the optimization of clinical outcomes through the effective personalization of treatment [ 11 , 12 ].…”