Pneumologie 2012; 66 - A605
DOI: 10.1055/s-0032-1315528

Circulating microRNAs associated with early relapse in early-stage NSCLC

S Kaduthanam 1, S Gade 1, T Muley 1, M Meister 1, JC Brase 1, M Johannes 1, F Herth 1, H Dienemann 1, H Sültmann 1, R Kuner 1
  • 1Heidelberg

Background: In early-stage tumors the outcome is critically determined by metastatic spread: About 30–50% of patients encounter a recurrence after surgery of lung cancer. The stratification of early-stage lung cancer with high risk for recurrence will improve therapy management and patient care. The aim of the study was to identify microRNAs in serum associated with early relapse in non-small cell lung cancer.

Material and methods: Serum samples and RNA extracts were collected from 232 patients including NSCLC disease and control samples. We performed qRT-PCR based microRNA screening from a subset of 40 patients with early or late relapse. Few microRNA candidates were further validated in serum samples of an independent patient cohort (n=114), and additionally analyzed in late stage NSCLC, COPD disease and benign controls. For a subset of NSCLC patients, we compared microRNA abundance between tissue and serum of the same individuals.

Results: The screening experiment revealed ten circulating microRNAs potentially associated with early relapse in NSCLC. One of these microRNAs was verified in an independent patient cohort. This microRNA was found to be upregulated in patients with early relapse, especially in patients with NSCLC stage I and II. However, more frequent relapse events were observed in NSCLC stage IIIa. Multivariate analysis using stage information and microRNA expression revealed improved stratification of NSCLC patients with early relapse. Additionally, circulating microRNAs were also influenced by non-malignant disease like COPD. No significant correlation was observed between serum and tissue microRNA abundance of the same individuals.

Conclusions: MicroRNAs may be promising prognostic biomarkers in early stage lung cancer. The combination of biomarker profiles, clinical and epidemiological parameters may improve the diagnosis of severe cancer diseases and therapy assessment.