METHODOLOGY/PRINCIPAL FINDINGS: We profiled gene expression changes in the airway wall using a large animal model of physical injury comprising bronchial brush biopsy in anaesthetised sheep. The experimental design featured sequential studies in the same animals over the course of a week and yielded data relating to the response at 6 hours, and 1, 3 and 7 days after injury. Notable features of the transcriptional response included the early and sustained preponderance of down-regulated genes associated with angiogenesis and immune cell activation, selection and differentiation. Later features of the response included the up-regulation of cell cycle genes at d1 and d3, and the latter pronounced up-regulation of extracellular matrix-related genes at d3 and d7.
CONCLUSIONS/SIGNIFICANCE: It is possible to follow the airway wall response to physical injury in the same animal over the course of time. Transcriptional changes featured coordinate expression of functionally related genes in a reproducible manner both within and between animals. This characterisation will provide a foundation against which to assess the perturbations that accompany airway disease pathologies of comparative relevance.
METHODS: RNA was isolated from peripheral whole blood samples (2 x 10 ml) collected from NPC patients/controls (EDTA vacutainer). Gene expression patterns from 99 samples (66 NPC; 33 controls) were assessed using the Affymetrix array. We also collected expression data from 447 patients with other cancers (201 patients) and non-cancer conditions (246 patients). Multivariate logistic regression analysis was used to obtain biomarker signatures differentiating NPC samples from controls and other diseases. Differences were also analysed within a subset (n=28) of a pre-intervention case cohort of patients whom we followed post-treatment.
RESULTS: A blood-based gene expression signature composed of three genes - LDLRAP1, PHF20, and LUC7L3 - is able to differentiate NPC from various other diseases and from unaffected controls with significant accuracy (area under the receiver operating characteristic curve of over 0.90). By subdividing our NPC cohort according to the degree of patient response to treatment we have been able to identify a blood gene signature that may be able to guide the selection of treatment.
CONCLUSION: We have identified a blood-based gene signature that accurately distinguished NPC patients from controls and from patients with other diseases. The genes in the signature, LDLRAP1, PHF20, and LUC7L3, are known to be involved in carcinoma of the head and neck, tumour-associated antigens, and/or cellular signalling. We have also identified blood-based biomarkers that are (potentially) able to predict those patients who are more likely to respond to treatment for NPC. These findings have significant clinical implications for optimizing NPC therapy.