BackgroundPreviously we demonstrated that an mRNA signature reflecting cellular proliferation had strong prognostic value. As clinical applicability of signatures can be controversial, we sought to improve our marker's clinical utility by validating its biological relevance, reproducibility in independent data sets and applicability using an independent technique.
MethodsTo facilitate signature evaluation with quantitative PCR (qPCR) a novel computational procedure was used to reduce the number of signature genes without significant information loss. These genes were validated in different human cancer cell lines upon serum starvation and in a 168 xenografts panel. Analyses were then extended to breast cancer and non-small-cell lung cancer (NSCLC) patient cohorts.
ResultsExpression of the qPCR-based signature was dramatically decreased under starvation conditions and inversely correlated with tumour volume doubling time in xenografts. The signature validated in breast cancer (hazard ratio (HR)=1.63, P<0.001, n=1820) and NSCLC adenocarcinoma (HR=1.64, P<0.001, n=639) microarray data sets. Lastly, qPCR in a node-negative, non-adjuvantly treated breast cancer cohort (n=129) showed that patients assigned to the high-proliferation group had worse disease-free survival (HR=2.25, P<0.05).
ConclusionWe have developed and validated a qPCR-based proliferation signature. This test might be used in the clinic to select (early-stage) patients for specific treatments that target proliferation.