High throughput techniques for characterizing the expression profile of Barrett's esophagus

Esophageal cancer metabolite biomarkers detected by LC-MS and NMR methods

Background

Esophageal adenocarcinoma (EAC) is a rarely curable disease and is rapidly rising worldwide in incidence. Barret's esophagus (BE) and high-grade dysplasia (HGD) are considered major risk factors for invasive adenocarcinoma. In the current study, unbiased global metabolic profiling methods were applied to serum samples from patients with EAC, BE and HGD, and healthy individuals, in order to identify metabolite based biomarkers associated with the early stages of EAC with the goal of improving prognostication.

Methodology/Principal Findings

Serum metabolite profiles from patients with EAC (n = 67), BE (n = 3), HGD (n = 9) and healthy volunteers (n = 34) were obtained using high performance liquid chromatography-mass spectrometry (LC-MS) methods. Twelve metabolites differed significantly (p<0.05) between EAC patients and healthy controls. A partial least-squares discriminant analysis (PLS-DA) model had good accuracy with the area under the receiver operative characteristic curve (AUROC) of 0.82. However, when the results of LC-MS were combined with 8 metabolites detected by nuclear magnetic resonance (NMR) in a previous study, the combination of NMR and MS detected metabolites provided a much superior performance, with AUROC = 0.95. Further, mean values of 12 of these metabolites varied consistently from healthy controls to the high-risk individuals (BE and HGD patients) and EAC subjects. Altered metabolic pathways including a number of amino acid pathways and energy metabolism were identified based on altered levels of numerous metabolites.

Conclusions/Significance

Metabolic profiles derived from the combination of LC-MS and NMR methods readily distinguish EAC patients and potentially promise important routes to understanding the carcinogenesis and detecting the cancer. Differences in the metabolic profiles between high-risk individuals and the EAC indicate the possibility of identifying the patients at risk much earlier to the development of the cancer.

Metabolomics study of esophageal adenocarcinoma

OBJECTIVE

The objective of this study was to detect and evaluate reliable metabolite markers for screening and monitoring treatment of patients with esophageal adenocarcinoma (EAC) by studying metabolomics. The sensitivity and specificity of the study were evaluated not only for EAC but also for Barrett esophagus and high-grade dysplasia, which are widely regarded as precursors of EAC.

METHODS

Profiles of metabolites in blood serum were constructed using nuclear magnetic resonance spectroscopy and statistical analysis methods. The metabolite biomarkers discovered were selected to build a predictive model that was then used to test the classifications accuracies.

RESULTS

Eight metabolites showed significant differences in their levels in patients with cancer and in the control group on the basis of Student t test. A partial least-squares discriminant analysis model built on these metabolites provided excellent classifications of patients with cancer and the control group, with the area under the receiver operating in a characteristic curve of >0.85 for both training and validation sample sets. Evaluated by the same model, the Barrett esophagus samples were of mixed classification, and the high-grade dysplasia samples were classified primarily as cancer samples. A pathway study indicated that altered energy metabolism and changes in the trochloroacetic acid cycle were the dominant factors in the biochemistry of EAC.

CONCLUSIONS

1H nuclear magnetic resonance-based metabolite profiling analysis was shown to be an effective approach to differentiating between patients with EAC and healthy subjects. Good sensitivity and selectivity were shown by using the 8 metabolite markers discovered to predict the classification of samples from the healthy control group and the patients with the disease. Serum metabolic profiling may have potential for early diagnosis of EAC and may enhance our understanding of its mechanisms.

Pharmacokinetics and pharmacogenomics in esophageal cancer chemoradiotherapy

Esophageal cancer is one of the most lethal malignancies. Surgical resection of the tumor from the primary site has been the standard treatment, especially for localized squamous cell carcinoma, but considerable clinical efforts during the last decade have resulted in novel courses of treatment. These options include chemoradiotherapy, consisting of a continuous infusion of 5-fluorouracil (5-FU), cisplatin (CDDP), and concurrent radiation. Given the substantial inter- and/or intra-individual variation in clinical outcome, future improvements will likely require the incorporation of a novel anticancer drug, pharmacokinetically guided administration of CDDP or 5-FU, and identification of potential responders by patient genetic profiling prior to treatment. In this review, the latest information on incidence, risk factors, biomarkers, therapeutic strategies, and the pharmacokinetically guided or genotype-guided administration of CDDP and 5-FU is summarized for future individualization of esophageal cancer treatment.

Differential gene expression in normal esophagus and Barrett's esophagus

PURPOSE

As the premalignant lesion of human esophageal adenocarcinoma (EAC), Barrett's esophagus (BE) is characterized by intestinal metaplasia in the normal esophagus (NE). Gene expression profiling with microarray and serial analysis of gene expression (SAGE) may help us understand the potential molecular mechanism of human BE.

METHODS

We analyzed three microarray datasets (two cDNA arrays and one oligonucleotide array) and one SAGE dataset with statistical tools, significance analysis of microarrays (SAM) and SAGE(Poisson), to identify individual genes differentially expressed in BE. Gene set enrichment analysis (GSEA) was used to identify a priori defined sets of genes that were differentially expressed. These gene sets were grouped according to either certain signaling pathways (GSEA curated), or the presence of consensus binding sequences of known transcription factors (GSEA motif). Immunohistochemical staining (IHC) was used to validate differential gene expression.

RESULTS

Both SAM and SAGE(Poisson) identified 68 differentially expressed genes (55 BE genes and 13 NE genes) with an arbitrary cutoff ratio (> or =4-fold). With IHC on matched pairs of NE and BE tissues from 6 patients, these genes were grouped into 6 categories: category I (25 genes only expressed in BE), category II (5 genes only expressed in NE), category III (8 genes expressed more in BE than in NE), and category IV (2 genes expressed more in NE than in BE). Differential expression of the remaining genes was not confirmed by IHC either due to false discovery (category V), or lack of proper antibodies (category VI). Besides individual genes, the TGFbeta pathway and several transcription factors (CDX2, HNF1, and HNF4) were identified by GSEA as enriched pathways and motifs in BE. Apart from 9 target genes known to be up-regulated in BE, IHC staining confirmed up-regulation of 19 additional CDX1 and CDX2 target genes in BE.

CONCLUSION

Our data suggested an important role of CDX1 and CDX2 in the development of BE. The IHC-confirmed gene list will lead to future studies on the molecular mechanism of BE.