Article

Biomarkers in Barrett's esophagus and esophageal adenocarcinoma: predictors of progression and prognosis.

MRC Cancer Cell Unit, Hutchison-MRC Research Centre, Box 197/ Hills Road, Cambridge, CB20XZ, United Kingdom.
World Journal of Gastroenterology (Impact Factor: 2.55). 12/2010; 16(45):5669-81.
Source: PubMed

ABSTRACT Barrett's esophagus is a well-known premalignant lesion of the lower esophagus that is characterized by intestinal metaplasia of the squamous epithelium. It is clinically important due to the increased risk (0.5% per annum) of progression to esophageal adenocarcinoma (EA), which has a poor outcome unless diagnosed early. The current clinical management of Barrett's esophagus is hampered by the lack of accurate predictors of progression. In addition, when patients develop EA, the current staging modalities are limited in stratifying patients into different prognostic groups in order to guide the optimal therapy for an individual patient. Biomarkers have the potential to improve radically the clinical management of patients with Barrett's esophagus and EA but have not yet entered mainstream clinical practice. This is in contrast to other cancers like breast and prostate for which biomarkers are utilized routinely to inform clinical decisions. This review aims to highlight the most promising predictive and prognostic biomarkers in Barrett's esophagus and EA and to discuss what is required to move the field forward towards clinical application.

0 Bookmarks
 · 
91 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: BACKGROUND Esophageal adenocarcinoma (EAC) is associated with a dismal prognosis. The identification of cancer biomarkers can advance the possibility for early detection and better monitoring of tumor progression and/or response to therapy. The authors present results from the development of a serum-based, 4-protein (biglycan, myeloperoxidase, annexin-A6, and protein S100-A9) biomarker panel for EAC.METHODSA vertically integrated, proteomics-based biomarker discovery approach was used to identify candidate serum biomarkers for the detection of EAC. Liquid chromatography-tandem mass spectrometry analysis was performed on formalin-fixed, paraffin-embedded tissue samples that were collected from across the Barrett esophagus (BE)-EAC disease spectrum. The mass spectrometry-based spectral count data were used to guide the selection of candidate serum biomarkers. Then, the serum enzyme-linked immunosorbent assay data were validated in an independent cohort and were used to develop a multiparametric risk-assessment model to predict the presence of disease.RESULTSWith a minimum threshold of 10 spectral counts, 351 proteins were identified as differentially abundant along the spectrum of Barrett esophagus, high-grade dysplasia, and EAC (P<.05). Eleven proteins from this data set were then tested using enzyme-linked immunosorbent assays in serum samples, of which 5 proteins were significantly elevated in abundance among patients who had EAC compared with normal controls, which mirrored trends across the disease spectrum present in the tissue data. By using serum data, a Bayesian rule-learning predictive model with 4 biomarkers was developed to accurately classify disease class; the cross-validation results for the merged data set yielded accuracy of 87% and an area under the receiver operating characteristic curve of 93%.CONCLUSIONS Serum biomarkers hold significant promise for the early, noninvasive detection of EAC. Cancer 2014. © 2014 American Cancer Society.
    Cancer 08/2014; · 5.20 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Barrett's esophagus is the strongest risk for esophageal adenocarcinoma (EAC). Metaplasia in patients with BE may progress to dysplasia and then invasive carcinoma. Well-defined diagnostic, progressive, predictive, and prognostic biomarkers are needed to identify the presence of the disease, estimate the risk of malignant transformation, and predict the therapeutic outcome and survival of EAC patients. There are many predictive and prognostic markers that lack substantial validation, and do not allow stratification of patients with gastroesophageal reflux disease in clinical practice for outcome and effectiveness of therapy. In this short review we summarize the current knowledge regarding possible biomarkers, focusing on the pathophysiologic mechanisms to improve prognostic and therapeutic approaches.
    World journal of gastrointestinal pathophysiology. 11/2014; 5(4):450-6.
  • [Show abstract] [Hide abstract]
    ABSTRACT: BACKGROUND Esophageal adenocarcinoma (EAC) is associated with a dismal prognosis. The identification of cancer biomarkers can advance the possibility for early detection and better monitoring of tumor progression and/or response to therapy. The authors present results from the development of a serum-based, 4-protein (biglycan, myeloperoxidase, annexin-A6, and protein S100-A9) biomarker panel for EAC.METHODSA vertically integrated, proteomics-based biomarker discovery approach was used to identify candidate serum biomarkers for the detection of EAC. Liquid chromatography-tandem mass spectrometry analysis was performed on formalin-fixed, paraffin-embedded tissue samples that were collected from across the Barrett esophagus (BE)-EAC disease spectrum. The mass spectrometry-based spectral count data were used to guide the selection of candidate serum biomarkers. Then, the serum enzyme-linked immunosorbent assay data were validated in an independent cohort and were used to develop a multiparametric risk-assessment model to predict the presence of disease.RESULTSWith a minimum threshold of 10 spectral counts, 351 proteins were identified as differentially abundant along the spectrum of Barrett esophagus, high-grade dysplasia, and EAC (P<.05). Eleven proteins from this data set were then tested using enzyme-linked immunosorbent assays in serum samples, of which 5 proteins were significantly elevated in abundance among patients who had EAC compared with normal controls, which mirrored trends across the disease spectrum present in the tissue data. By using serum data, a Bayesian rule-learning predictive model with 4 biomarkers was developed to accurately classify disease class; the cross-validation results for the merged data set yielded accuracy of 87% and an area under the receiver operating characteristic curve of 93%.CONCLUSIONS Serum biomarkers hold significant promise for the early, noninvasive detection of EAC. Cancer 2014. © 2014 American Cancer Society.
    Cancer 08/2014; · 5.20 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Background:Oesophageal adenocarcinoma or Barrett's adenocarcinoma (EAC) is increasing in incidence and stratification of prognosis might improve disease management. Multi-colour Fluorescence in situ hybridisation (FISH) investigating ERBB2, MYC, CDKN2A and ZNF217 has recently shown promising results for the diagnosis of dysplasia and cancer using cytological samples.Methods:To identify markers of prognosis we targeted four selected gene loci using multi-colour FISH applied to a tissue microarray containing 130 EAC samples. Prognostic predictors (P1, P2, P3) based on genomic copy numbers of the four loci were statistically assessed to stratify patients according to overall survival in combination with clinical data.Results:The best stratification into favourable and unfavourable prognoses was shown by P1, percentage of cells with less than two ZNF217 signals; P2, percentage of cells with fewer ERBB2- than ZNF217 signals; and P3, overall ratio of ERBB2-/ZNF217 signals. Median survival times for P1 were 32 vs 73 months, 28 vs 73 months for P2; and 27 vs 65 months for P3. Regarding each tumour grade P2 subdivided patients into distinct prognostic groups independently within each grade, with different median survival times of at least 35 months.Conclusions:Cell signal number of the ERBB2 and ZNF217 loci showed independence from tumour stage and differentiation grade. The prognostic value of multi-colour FISH-assays is applicable to EAC and is superior to single markers.British Journal of Cancer advance online publication, 22 May 2014; doi:10.1038/bjc.2014.238 www.bjcancer.com.
    British journal of cancer. 05/2014;

Full-text (2 Sources)

Download
18 Downloads
Available from
Jun 4, 2014