ABSTRACT
BACKGROUND: Treatment protocols for nasopharyngeal carcinoma (NPC) developed in the past decade have significantly improved patient survival. In most NPC patients, however, the disease is diagnosed at late stages, and for some patients treatment response is less than optimal. This investigation has two aims: to identify a blood-based gene-expression signature that differentiates NPC from other medical conditions and from controls and to identify a biomarker signature that correlates with NPC treatment response. 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.
Subject(s)
Biomarkers, Tumor , Gene Expression Regulation, Neoplastic , Nasopharyngeal Neoplasms , Transcriptome , Adaptor Proteins, Signal Transducing/blood , Adult , Aged , Antigens, Neoplasm/blood , Biomarkers, Tumor/blood , Biomarkers, Tumor/genetics , Carcinoma , DNA-Binding Proteins , Female , Gene Expression Profiling , Humans , Male , Middle Aged , Nasopharyngeal Carcinoma , Nasopharyngeal Neoplasms/blood , Nasopharyngeal Neoplasms/metabolism , Nasopharyngeal Neoplasms/pathology , Nuclear Proteins , RNA-Binding Proteins/blood , Transcription FactorsABSTRACT
OBJECTIVES: The genetic background of familial combined hyperlipidemia (FCHL) is currently unclear. We propose transcriptional profiling as a complementary tool for its understanding. Two hypotheses were tested: the existence of a disease-specific modification of gene expression in FCHL and the detectability of such a transcriptional profile in blood derived cell lines. METHODS AND RESULTS: We established lymphoblastic cell lines from FCHL patients and controls. The cells were cultured in fixed conditions and their basal expression profile was compared using microarrays; 166 genes were differentially expressed in FCHL-derived cell lines compared with controls, with enrichment in metabolism-related genes. Of note was the upregulation of EGR-1, previously found to be upregulated in the adipose tissue of FCHL patients, the upregulation of DCHR-7, the downregulation of LYPLA2, and the differential expression of several genes previously unrelated to FCHL. A cluster of potential EGR-1-regulated transcripts was also differentially expressed in FCHL cells. CONCLUSIONS: Our data indicate that in FCHL, a disease-specific transcription profile is detectable in immortalized cell lines easily obtained from peripheral blood and provide complementary information to classical genetic approaches to FCHL and/or the metabolic syndrome.