No abstract

Adverse drug reactions are a significant clinical and economic problem in surgical intensive care units.

BackgroundConsidering previous data and the need to incorporate new biomarkers for the prognosis of solid tumours into the clinic, our aim in this work consists of evaluating the potential clinical use of telomeres and telomerase in non-small cell lung cancer (NSCLC).MethodsTelomere status was established by determination of telomere length using the Terminal Restriction Fragment length method, and telomerase activity by the Telomeric Repeat Amplification Protocol in 142 NSCLCs and their corresponding control samples, obtained from patients submitted to surgery. Group-oriented curves for disease-free survival were calculated according to the Kaplan-Meier method considering telomere length, T/N ratio (telomere length in tumour to control tissue) and telomerase activity.ResultsOverall, tumours had significantly shorter telomeres compared with telomeres in control tissues (P = 0.027). More than 80 % of NSCLCs displayed telomerase activity. Regarding prognosis studies, patients whose tumours showed a mean telomere length (MTL) <7.29 Kb or T/N ratio <0.97 showed a significantly poor clinical evolution (P = 0.034 and P = 0.040, respectively). As result of a Cox multivariate analysis including pathologic state and lymph node dissemination, the MTL and T/N ratio emerged as independent significant prognostic factors.ConclusionsTelomerase activity was identified as a marker of poor prognosis. The novel finding of this study is the independent prognosis role of a specific telomere status in NSCLC patients. According to our results, telomere function may emerge as a useful molecular tool that allow to select groups of NSCLC patients with different clinical evolution, in order to establish personalized therapy protocols.

Favorable prognosis in completely resected NSCLC is determined by a B-cell-mediated immune response. It can be differently scored by a 50-gene expression profile or by CD20 immunostaining. That prognosis information not reflected by traditional classifications may become a new tool for determining individualized adjuvant therapies.