Prognostic and Chemotherapy Predictive Value of Gene-Expression Phenotypes in Primary XXXX .

@entity1 @entity66 @entity420 @entity21864 @entity2220
PURPOSE: Primary @entity2220 remains a @entity66 . Gene-expression phenotypes (GEPs) in @entity420 have potential to provide clinically relevant disease stratification for improved prognosis and treatment prediction, given appropriate clinical and methodologic validation. EXPERIMENTAL DESIGN: 2,395 transcriptional @entity420 profiles were assembled from 17 public cohorts and classified by a nearest centroid @entity21864 classifier into three subtypes: terminal respiratory unit (TRU), proximal-proliferative, and proximal-inflammatory, and additionally scored by five transcriptional metagenes representing different biologic processes, including proliferation. Prognostic- and chemotherapy-predictive associations of the subtypes were analyzed by univariate and multivariate analysis using overall survival or distant metastasis-free survival as endpoints. RESULTS: Overall, GEPs were associated with @entity1 outcome in both univariate and multivariate analyses, although not in all individual cohorts. The prognostically relevant division was between TRU- and non-TRU-classified cases, with expression of proliferation-associated genes as a key prognostic component. In contrast, @entity21864 classification was not predictive of adjuvant chemotherapy response. @entity21864 classification showed stability to random perturbations of genes or samples and alterations to classification procedures (typically <10% of cases/cohort switching subtype). High classification variability (>20% of cases switching subtype) was observed when removing larger or entire fractions of a single subtype, due to gene-centering shifts not addressable by the classifier. CONCLUSIONS: In a large-scale evaluation, we show that GEPs add prognostic value to standard clinicopathologic variables in @entity2220 . Subject to classifier refinement and confirmation in prospective cohorts, GEPs have potential to affect the prognostication of @entity420 @entity1 through a molecularly driven disease stratification. Clin Cancer Res; 1-12.   2015 AACR.
