Methods And Kits For Monitoring Barrett's Metaplasia

  *US07537894B2*
  US007537894B2                                 
(12)United States Patent(10)Patent No.: US 7,537,894 B2
 Weichselbaum et al. (45) Date of Patent:May  26, 2009

(54)Methods and kits for monitoring Barrett's metaplasia 
    
(75)Inventors: Ralph Weichselbaum,  Chicago, IL (US); 
  Nikolai Khodarev,  Villa Park, IL (US); 
  Eric Kimchi,  Hershey, PA (US); 
  Mitchell Posner,  Chicago, IL (US) 
(73)Assignee:The University of Chicago,  Chicago, IL (US), Type: US Company 
(*)Notice: Subject to any disclaimer, the term of this patent is extended or adjusted under 35 U.S.C. 154(b) by 91 days. 
(21)Appl. No.: 11/367,602 
(22)Filed: Mar.  2, 2006 
(65)Prior Publication Data 
 US 2006/0199210 A1 Sep.  7, 2006 
 Related U.S. Patent Documents 
(60)Provisional application No. 60/658,424, filed on Mar.  2, 2005.
 
(51)Int. Cl. C12Q 001/68 (20060101)
(52)U.S. Cl. 435/6; 536/24.5
(58)Field of Search  None

 
(56)References Cited

 OTHER PUBLICATIONS
  
  Reid et al. Gastrointest Endosc. Clin. N. Am. vol. 13(2), pp. 369-397, 2003). Abstract only. *
  Tockman et al. Cancer Research, vol. 52, pp. 2711s-2718s, 1992. *
  Chang et al. (World J. Gastroenterol, vol. 10(21), pp. 3194-3196, 2004). *
  Yoshida et al. (FEBS Letter, vol. 414(2), pp. 333-337, 1997) Abstract only. *
  Kimos et al. (Int. J. Cancer, vol. 111, pp. 415-417, 2004). *
  Barrett, M.T. et al., “Transcriptional analyses of Barrett's metaplasia and normal upper GI mucosae,” Neoplasia (2002) 4:121-128.
  Basson, C.T. et al., “Identification, characterization, and chromosomal localization of the human homolog (hES) of ES/130,” Genomics (1996) 35:628-631.
  Capo-Chichi, C.D. et al., “Anomalous expression of epithelial differentiation-determining GATA factors in ovarian tumorigenesis,” Cancer Res. (2003) 63:4967-4977.
  Care, A. et al., “HOXB7: a key factor for tumor-associated angiogenic switch,” Cancer Res. (2001) 61:6532-6539.
  Chen, Y.J. et al., “Loss of heterozygosity of chromosome 1q in gastrinomas: occurrence and prognostic significance,” Cancer Res. (2003) 63:817-823.
  Dahlberg, P.S. et al., “Gene expression profiles in esophageal adenocarcinoma,” Ann. Thorac. Surg. (2004) 77:1008-1015.
  Devesa, S.S. et al., “Changing patterns in the incidence of esophageal and gastric carcinoma in the United States,” Cancer (1998) 83:2049-2053.
  Ding, M. et al., “C. elegans ankyrin repeat protein VAB-19 is a component of epidermal attachment structures and is essential for epidermal morphogenesis,” Development (2003) 130:5791-5801.
  Draghici, S. et al., “Global functional profiling of gene expression,” Genomics (2003) 81:98-104.
  Elder, J.T. et al., “Evidence for local control of gene expression in the epidermal differentiation complex,” Exp. Dermatol. (2002) 11:406-412.
  Garcia-Cao, M. et al., “Epigenetic regulation of telomere length in mammalian cells by the Suv39h1 and Suv39h2 histone methyltransferases,” Nat. Genet. (2004) 36:94-99.
  Goldblum, J.R. et al., “Dysplasia arising in Barrett's esophagus: diagnostic pitfalls and natural history,” Semin. Diag. Pathol. (2002) 19:12-19.
  Hitomi, K. et al., “Analysis of epidermal-type transglutaminase (transglutaminase 3) in human stratified epithelia and cultured keratinocytes using monoclonal antibodies,” J. Dermatol. Sci. (2003) 32:95-103.
  Kalinin, A.E. et al., “Epithelial barrier function: assembly and structural features of the cornified cell envelope,” Bioessays (2002) 24:789-800.
  Kaufman, C.K. et al., “GATA-3: an unexpected regulator of cell lineage determination in skin,” Genes Dev. (2003) 17:2108-2122.
  Khodarev, N.N. et al., “Interaction of amifostine and ionizing radiation on transcriptional patterns of apoptotic genes expressed in human microvascular endothelial cells (HMEC),” Int. J. Rad. Oncol. Biol. Phys. (2004) 60:553-563.
  Khodarev, N.N. et al., “Method of RNA purification from endothelial cells for DNA array experiments” Biotechniques (2002) 32:316-320.
  Khodarev, N.N. et al., “Receiver operating characteristic analysis: a general tool for DNA array data filtration and performance estimation,” Genomics (2003) 81:202-209.
  Khodarev, N.N. et al., “STAT1 is overexpressed in tumors selected for radioresistance and confers protection from radiation in transduced sensitive cells,” PNAS USA (2004) 101:1714-1719.
  Kitajima, Y., “Mechanisms of desmosome assembly and disassembly,” Clin. Exp. Dermatol. (2002) 27:684-690.
  Koh, K. et al., “ELT-5 and ELT-6 are required continuously to regulate epidermal seam cell differentiation and cell fusion in C. elegans,” Development (2001) 128:2867-2880.
  Koon, N. et al., “Clustering of molecular alterations in gastroesophageal carcinomas,” Neoplasia (2004) 6:143-149.
  La Celle, P.T. et al., “Human homeobox HOXA7 regulates keratinocyte transglutaminase type 1 and inhibits differentiation,” J. Biol. Chem. (2001) 276:32844-32853.
  Lagergren, J. et al., “Symptomatic gastroesophageal reflux as a risk factor for esophageal adenocarcinoma,” N. Eng. J. Med. (1999) 34:825-831.
  Luo, A. et al., “Discovery of Ca2+-relevant and differentiation associated genes downregulated in esophageal squamous cell carcinoma using cDNA microarray,” Oncogene (2004) 23:1291.
  Mahy, N.L. et al., “Gene density and transcription influence the localization of chromatin outside of chromosome territories detectable by FISH,” J. Cell Biol. (2002) 159:753-763.
  Marenholz, I. et al., “Identification of human epidermal differentiation complex (EDC)-encoded genes by substractive hybridization of entire YACs to a gridded keratinocyte cDNA library,” Genome Res. (2001) 11:341-355.
  McManus, D.T. et al., “Biomarkers of esophageal adenocarcinoma and Barrett's esophagus,” Cancer Res. (2004) 64:1561-1569.
  Merrill, B.J. et al., “Tcf3 and Lef1 regulate lineage differentiation of multipotent stem cells in skin,” Genes Dev. (2001) 15:1688-1705.
  Naora, H. et al., “A serologically identified tumor antigen encoded by a homeobox gene promotes growth of ovarian epithelial cells,” Proc. Natl. Acad. Sci. USA (2001) 98:4060-4065.
  Neglia, M. et al., “Amplification of the pericentromeric region of chromosome 1 in a newly established colon carcinoma cell line,” Cancer Genet. Cytogenet. (2003) 142:99-106.
  Pantou, D. et al., “Cytogenetic profile of unknown primary tumors: clues for their pathogenesis and clinical management,” Neoplasia (2003) 5:23-31.
  Sarkar, S. et al., “A novel ankyrin repeat-containing gene (Kank) located at 9p24 is a growth suppressor of renal cell carcinoma,” J. Biol. Chem. (2002) 277:36585-36591.
  Seery, J.P., “Stem cells of the oesophageal epithelium,” J. Cell Sci. (2002) 115:1783-1789.
  Shaheen, N. et al., “Gastroesophageal reflux, Barrett esophagus and esophageal cancer,” JAMA (2002) 287:1972-1981.
  Shaheen, N.J. et al., “Is there publication bias in the reporting of cancer risk in Barrett's esophagus?” Gastroenterology (2000) 119:333-338.
  Stein, H.J. et al., Barrett's esophagus: pathogenesis, epidemiology, function abnormalities, malignant degeneration, and surgical management, Dysphagia (1993) 8:276-288.
  Stelnicki, E.J. et al., “HOX homeobox genes exhibit spatial and temporal changes in expression during human skin development,” J. Invest. Dermatol. (1998) 110:110-115.
  Swisher, S.G. et al., “Changes in the surgical manangement of esophageal cancer from 1970 to 1993,” Am. J. Surg. (1995) 169:609-614.
  Sy, S.M. et al., “distinct patterns of genetic alterations in adenocarcinoma and squamous cell carcinoma of the lung,” Eur. J. Cancer (2004) 40:1082-1094.
  Tusher, V.G. et al., “Significance analysis of microarrays applied to the ionizing radiation response,” PNAS USA (2001) 98:5116-5121.
  Volpi, E.V. et al., “Large-scale chromatin organization of the major histocompatibility complex and other regions of human chromosome 6 and its response to interferon in interphase nuclei,” J. Cell Sci (2000) 113:1565-1576.
  Williams, R.R. et al., “Subchromosomal positioning of the epidermal differentiation complex (EDC) in keratinocyte and lymphoblast interphase nuclei,” Exp. Cell Res. (2002) 272:163-175.
  Wong, N. et al., “Positional mapping for amplified DNA sequences on 1q21-q22 in hepatocellular carcinoma indicates candidate genes over-expression,” J. Hepatol. (2003) 38:298-306.
  Xu, Y. et al., “Artificial neural networks and gene filtering distinguish between global gene expression profiles of Barrett's esophagus and esophageal cancer,” Cancer Res. (2002) 62:3493-3497.
 
 
     * cited by examiner
 
     Primary Examiner —Larry R. Helms
     Assistant Examiner —Meera Natarajan
     Art Unit — 1643
     Exemplary claim number — 1
 
(74)Attorney, Agent, or Firm — Michael Best & Friedrich LLP

(57)

Abstract

Disclosed are methods and kits for assessing risk of progression of Barrett's esophagus to adenocarcinoma.
7 Claims, 3 Drawing Sheets, and 5 Figures


CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 60/658,424, filed Mar. 2, 2005.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] The invention was made with U.S. Government support under Grant No. CA071933, awarded by The National Institutes of Health. The U.S. Government may have certain rights to this invention.

BACKGROUND OF THE INVENTION

[0003] Barrett's esophagus is a specialized intestinal metaplasia of normal squamous to columnar epithelium, which is thought to be a premalignant transformation and which is found in 80-100% of esophageal adenocarcinoma of the distal esophagus (1). The etiology of Barrett's esophagus is not well understood, but chronic gastroesophageal reflux is considered to be a major contributing factor (2). The presence of Barrett's esophagus increases the risk of developing adenocarcinoma 40 to 125-fold (3). The incidence of adenocarcinoma has increased 3.5-fold over the past 3 decades, which exceeds that of all other types of cancer (4, 5). Patients with adenocarcinomas of the esophagus present with advanced disease, and 5-year survival is approximately 25% (6). Currently, endoscopic surveillance is the only method of identifying patients with early-stage esophageal cancers arising in Barrett's esophagus.
[0004] Identification of biological markers of Barrett's esophagus progression may identify high risk patients for whom endoscopy would be indicated (8). Expressional profiling represents one method of identifying biological markers of Barrett's esophagus (9-12). However, no molecular markers that can be used to identify patients at higher risk for subsequent transformation of Barrett's esophagus to adenocarcinoma have been reported.
[0005] There exists a need in the art for new methods of evaluating the risk of progression of Barrett's esophagus to adenocarcinoma.

BRIEF SUMMARY OF THE INVENTION

[0006] In one aspect, the present invention provides methods of assessing risk of adenocarcinoma in a mammal with Barrett's esophagus. The method involves measuring the level of expression of at least two markers listed in Table 2 in a sample prepared from Barrett's esophageal cells. The level of expression in Barrett's esophageal cells is compared to that of a reference, a difference in the level of expression of a marker being indicative of increased risk of adenocarcinoma.
[0007] In another aspect, the invention provides kits for performing the methods of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0008] FIG. 1A-D shows plots of expression levels of markers as a function of sample type.
[0009] FIG. 2 shows a plot of the ratio of expression levels of two markers as a function of sample type.

DETAILED DESCRIPTION OF THE INVENTION

[0010] The Examples below describe the identification of molecular markers differentially expressed in normal esophageal epithelium, Barrett's esophagus, and esophageal adenocarcinoma. Measuring the level of expression of these markers allows discrimination between normal esophageal epithelium, Barrett's esophagus, and esophageal adenocarcinoma. Quantitation of these markers can be used to identify patients with Barrett's esophagus at increased risk for subsequent progression to adenocarcinoma.
[0011] DNA microarrays were used to evaluate differential gene expression patterns in resected esophageal specimens composed of normal esophageal epithelium, Barrett's esophagus, and adenocarcinoma obtained from the same individual patients. Based on this analysis, 96 genes that are differentially expressed in both Barrett's esophagus and adenocarcinoma were identified (Supplemental Table 2).
[0012] Of the 96 genes differentially expressed in Barrett's esophagus and adenocarcinoma, 21 genes (Table 2) were identified as being potentially useful for evaluating risk of progression from Barrett's esophagus to esophageal adenocarcinoma. These 21 genes were chosen because the change in expression is in the same direction (i.e., up-regulation or down-regulation) in both Barrett's esophagus and to esophageal adenocarcinoma, and because the change in expression is progressive from Barrett's esophagus to esophageal adenocarcinoma (i.e., the markers are up- or down-regulated to a greater degree in esophageal adenocarcinoma than in Barrett's esophagus). Because the change in expression from Barrett's esophagus to esophageal adenocarcinoma is progressive, is reasonably expected that the markers can be used to monitor progression from Barrett's esophagus to esophageal adenocarcinoma.
[0013] Of the 21 genes, six selected genes (GATA6, HOXB7, TCF3, S100A2, SCCA1 and SPRR3) were further evaluated. The level of expression of these genes, as measured by quantitative reverse transcription-PCR (QRT-PCR), discriminated between normal epithelium, Barrett's dysplasia and esophageal adenocarcinomas. It is possible to discriminate between normal epithelium and Barrett's esophagus or esophageal adenocarcinomas using any one of the 21 markers. Analysis of two or more markers permits discrimination Barrett's esophagus and esophageal adenocarcinomas. In the Examples, expression levels of GATA6/SPRR3, HOXB7/SPRR3, and GAT6/HOXB7/SPRR3 were evaluated and found to discriminate between Barrett's esophagus and esophageal adenocarcinomas. Additionally, it is specifically envisioned that any combination of two or more of the 21 markers provided in Table 2 will be useful in the methods of the invention. The markers may be analyzed individually or together in a multiplex.
[0014] In the methods of the invention, the level of gene expression was performed by indirectly measuring the mRNA by quantitative PCR, as described in the Examples. It is envisioned that mRNA, or cDNA prepared from mRNA, could be quantified through standard hybridization techniques using an oligonucleotide complementary to at least a portion of the mRNA or cDNA. Alternatively, the level of gene expression could be assayed using antibody detection methods and an antibody specific for an epitope of one of the gene products (i.e., mRNA or protein) of the 21 markers.
[0015] In the Examples, gene expression was evaluated by comparing expression levels of the 21 markers in normal esophageal epithelium, cells characteristic of Barrett's esophagus, and esophageal adenocarcinoma using resected esophagus samples. It is envisioned that any sample containing cells characteristic of Barrett's esophagus could be used. For example, such cells may be obtained by an esophageal lavage, or scraping or biopsying a portion of the esophagus during endoscopy.
[0016] Marker expression levels in Barrett's esophagus can be evaluated by comparison to a reference. The reference may be normal esophageal epithelium obtained from the same individual, at the same time or at a different time. Alternatively, the reference may be marker expression levels in a sample comprising cells characteristic of Barrett's esophagus obtained from the same individual at a different time, which would permit changes in marker expression levels to be monitored over time. It is also envisioned that comparison of marker expression levels may be made with reference to a normal range established using normal cells from a population of individuals.
[0017] Differences in expression levels between Barrett's esophagus and a reference may be evaluated using any suitable statistical test. As one of skill in the art will appreciate, interpretation of results may be evaluated using different P values, depending on importance of minimizing false positives relative to the importance of minimizing false negatives in a particular application.
[0018] The methods of the invention may conveniently be performed using a kit. The kit may optionally comprise one or more probes for measuring expression at least one marker of Table 2. A probe may include, for example, a primer pair for performing quantitative PCR, an oligonucleotide that hybridizes to an mRNA or cDNA corresponding to one of the markers of Table 2, or an antibody specific for an epitope of an expression product (i.e., mRNA or protein) of a marker listed in Table 2. The kit may include instructions for performing a method according to the present invention.

EXAMPLES

[0019] The following non-limiting Examples are intended to be purely illustrative.
[0020] Clinical samples. Samples of normal, Barrett's, and adenocarcinoma were obtained from fresh pathological specimens of patients with known Barrett's esophagus and esophageal adenocarcinoma who had undergone esophagectomy. These specimens were processed by pathology within 15 minutes of resection. Samples representative of the various gross histologic types were obtained from experienced gastrointestinal pathologists. These samples were labeled and snap frozen in liquid nitrogen and stored at −80° C. for future RNA extraction.
[0021] Preparation of RNA and hybridizations. RNAs were purified by combination of column chromatography and TRizol (GIBCO BRL, MD) purification, as described previously (15). Preparation of labeled cRNA and hybridization with U133A chips was performed according to the manufacturer's instructions (Affymetrix, Calif.). Data were acquired using MAS 5.0 software (Affymetrix) and exported to MS Excel.
[0022] Submission of DNA array data. Data were submitted to the Microarray Analysis and Data Management System (MADAM) database of the University of Chicago, and constructed according to the Minimum Information about a Microarray Experiment (MIAME) recommendations. Data were also submitted to the GEO database (NCBI), with the accession number GSE1420.
[0023] Data analysis. Throughout this section, patients are denoted by the letter i=1, . . . 8, genes by the letter j, and tissue type by the letter k=1, 2, 3 (referring to normal (N), Barrett's esophagus (BE), and adenocarcinoma tumor (ADC).
[0024] For data normalization, the expression levels of each array were multiplied by M/M, where M is the median expression of the array, and M is the overall median expression level. This resealing makes median expression levels equal across all arrays. For data filtration, genes were excluded based on present (P) or absent (A) calls as defined by MAS 5.0. Genes were excluded if Σi=18Ai≧3 for all three tissue types, where Ai indicates whether a transcript is absent (Ai=1) or present (Ai=0). The genes were further filtered based on signal intensities using ROC analysis as previously described (16, 17). The total number of remaining genes was 8636.
[0025] Next, Significance Analysis of Microarrays (SAM) (18) was used to identify genes significantly over- and underexpressed in the three pairwise comparisons of Barrett's/normal, adenocarcinoma/normal, and Barrett's/adenocarcinoma. Significance analysis of microarrays identified genes with statistically significant differences between groups by assigning each gene a score on the basis of the difference in gene expression between two groups (e.g. normal and Barrett's) relative to the adjusted pooled standard deviation of the multiple measurements from both groups. Permutations of the measurements were then used to estimate the false discovery ratio (FDR), the percentage of genes identified by chance. As the cut-off point, a Δ-value was chosen such that the estimated median number of falsely discovered (called) genes was less than or equal to 1, and required at least a 2-fold expression ratio. In contrast to using a cut-off point of a fixed FDR level, this approach resulted in different cut-off Δs and FDR levels for the three comparisons: Barrett's/normal (Δ=1.270, FDR=0.33%), adenocarcinoma/normal, (Δ=1.555, FDR=0.121%) and Barrett's/adenocarcinoma (Δ=0.892, FDR=0.876%). Based on these criteria, 447 genes significantly expressed in adenocarcinoma compared with normal epithelium and 200 genes significantly expressed in Barrett's esophagus compared with normal epithelium were selected. A set of 85 genes was found to have significantly different expression between adenocarcinoma and Barrett's esophagus, of which 45 genes overlapped with genes significantly different in adenocarcinoma versus normal epithelium. Next, expression ratios of all genes between two tissue groups were compared to the reference “same-to-same” distribution in order to identify genes for which the ratios are larger than expected. In a simple case with two normal samples, the “same-to-same” distribution is the distribution of over all genes j (17). This concept was extended to a situation with more than two arrays by considering
[0026]  [see pdf for image]
where K is an even number of normal samples, and Njk represents the expression level of gene j. For every gene j, we consider the
[0027]  [see pdf for image]
possible ways the samples can be separated into two groups, obtaining C=70 possible combinations for each gene based on the 8 arrays, hybridized with RNA from normal tissues. For each of the 70 distributions quantiles q0.005, q0.0025, q0.0975, q0.995, corresponding to nonparametric 95% and 99% confidence limits were computed. Averaging these over the 70 combinations provides cut-off points for where the bulk of the same-to-same log-ratios occur. For each gene j Barrett's/normal and adenocarcinoma/normal (“different-to-same”) log-ratio
[0028]  [see pdf for image]
was then compared to the reference “same-to-same” distributions, and genes with expression ratios outside the cut-off limits were considered to be differentially expressed. Using the geometric mean rather than the non-standardized ratio allowed direct comparisons of the distributions of the “same-to-same” and “different-to-same” hybridizations, adjusting for the fact that the “different-to-same” ratios are based on K pairs of tumor and normal expression levels, and that the “same-to-same” ratios are based only on K normal expression levels. Thus, Lj can be naturally interpreted as the per-patient log-ratio.
[0029] Functional selection and prognosticators analysis. To select functionally significant groups of genes, OntoExpress software was used (19). Functional groups containing at least 3 genes were selected and analyzed using a binomial distribution with a significance level ≦0.05. Combining results of functional and expression-based selections, 214 genes were selected for further study. Two-dimensional hierarchical clustering of these genes was performed based on the estimation of the Euclidian distances by Ward's method using log2 Xijk/ Xj(N), the log-transformed expression levels normalized to the average expression level in the normal tissues, Xj(N). Samples T5 and N8 were removed as outliers. For clustering and data presentation, JMP and TreeView software was used as described previously (20).
[0030] To define genes that correlate with the progression of Barrett's esophagus to adenocarcinoma, the 96 genes expressed in both Barrett's esophagus and adenocarcinoma were considered. These genes were separated into two groups based on average between-patient expression: the first group contained genes which were up-regulated from normal to Barrett's esophagus and further from Barrett's esophagus to adenocarcinoma, and the second group was defined similarly for down-regulated genes. All other potential patterns were excluded from this analysis. The significance of the difference in expression from normal to Barrett's esophagus and from Barrett's esophagus to adenocarcinoma in each group was evaluated by a one-sided paired t-test using a p-value≦0.05 cut-off (taking into account that up- or down-regulated genes in each group had been pre-selected).
[0031] Quantitative reverse-transcription-PCR. cDNA was synthesized using Superscript II® reverse transcriptase (Invitrogen Life Technologies, Carlsbad, Calif., USA) following the manufacturer's instructions. cDNA was diluted 1:10 in sterile nuclease free water (Ambion, Tex.). Quantitative PCR was performed on an ABI 7700 system (Applied Biosystems, Foster City, Calif.) using SYBR Green PCR reagents in a 25 μl reaction mixture containing 2.5 μl 10×SYBR Green PCR buffer, 0.25 μl 10 mM primers, 2 μl dNTP mix, 3 μl 25 mM MgCl2, 0.25 μl AmpErase, 0.125 μl Amplitaq Gold and 2.5 μl of the 1:10 diluted cDNA.
[0032] Primers for selected genes were designed based on UniGene reference sequences using PrimerExpress software (Applied Biosystems, Foster City, Calif.). For the internal control we used GAPDH. PCR was performed for 40 cycles at 95° C. for 15 seconds and 60° C. for one minute after initial incubations at 50° C. for 2 minutes and 95° C. for 10 min.
[0033] All samples were amplified in triplicate reactions. The expression of each individual gene was calculated based on the difference between amplification of the individual mRNA template and the internal control (GAPDH) mRNA template. These differences were measured by delta ct (dct) values as described in the manufacturer's instructions (Applied Biosystems, Foster City, Calif.). dct values were calculated as (ctx-ctGAPDH), where ctx is the ct value of the specific gene X and ctGAPDH is the amplification of the internal control. Fold induction was calculated as 2−dct and therefore was equal to 2−(ctx-ctGAPDH) Ratios of gene X relative to gene Y in the same samples was calculated as: RX/Y=2−(ctX-ctY). These ratios were multiplied by 100,000 to give a range greater than one. Finally, the data was converted to Log10 format to present them in linear scale. The final expressional value (EV) was calculated as:
          EVx/y=Log10[105×{2−(ctX-ctY)}]
[0034] Discrimination between normal esophageal epithelium, Barrett's metaplasia and adenocarcinomas based on expressional profiling. Genes differentially expressed (either up- or down-regulated) in Barrett's esophagus and adenocarcinoma were selected based on the results of the statistical analysis. Compared with normal esophageal epithelium, 200 genes differentially expressed in Barrett's esophagus tissue and 447 genes differentially expressed in the Barrett's esophagus-associated adenocarcinoma were identified. The comparison of genes differentially expressed in Barrett's esophagus and adenocarcinoma showed that 96 genes were commonly overexpressed in Barrett's esophagus and adenocarcinoma. In adenocarcinoma, 351 genes were found to be differentially expressed that are not differentially expressed in Barrett's esophagus; in Barrett's esophagus, 104 genes were found to be differentially expressed that are not differentially expressed in adenocarcinoma. These non-overlapping genes were used in subsequent selection of significant functional groups using OntoExpress software (Table 1). Genes were also selected by comparison of the “same-to-same” and “different-to-same” hybridizations as described above using 99% confidence intervals based on the non-parametric quantile analysis. Combining both approaches, 214 genes (Supplemental Table 1) were selected for two-dimensional hierarchical clustering to show the actual discrimination between normal samples, Barrett's esophagus, and adenocarcinoma. The data were separated into three expressional clusters: cluster 1 (80 genes) contains the genes up-regulated in adenocarcinoma compared with normal epithelium; cluster 2 (63 genes) contains the genes which are sequentially suppressed in Barrett's esophagus and adenocarcinoma compared with the normal epithelium; cluster 3 (71 genes) contains the genes most drastically suppressed in adenocarcinoma compared with normal epithelium and Barrett's esophagus (data not shown).
[0035] Expressional patterns of normal epithelium, Barrett's esophagus and adenocarcinoma include different functional groups of genes. The major functional groups associated with the three major expressional clusters were identified. Cluster 1 was found to contain functional groups of genes associated with immune response, cell-cell signaling and cell-ECM interactions, control of cell cycle/growth/proliferation, and regulation of transcription and receptor activity (see Table 1).
[0036] Cluster 2 was also found to include genes involved in regulating cell cycle/proliferation, as well as genes involved in intracellular transport, bile acid transport, and aldehyde and lipid metabolism. Cluster 3 was found to contain functional groups of genes which may be specifically involved in the development of adenocarcinoma, including ectoderm development/epidermal differentiation, cytoskeleton, control of cell shape and cell-to-cell and cell-to-ECM interactions, Ca2+ binding and metabolism, and a group of proteases and protease inhibitors. Many of these genes are specifically associated with epidermal differentiation and malignant transformation.
[0037] Analysis of genes common to Barrett's and adenocarcinoma. Ninety-six genes were found to be differentially expressed (relative to normal esophageal endothelium) in both Barrett's esophagus and adenocarcinomas (Supplemental Table 2). Of those genes, a subset of 21 genes (Table 2) was chosen as prognostic or diagnostic markers because they are differentially expressed in the same direction (i.e., up- or down-regulated) in both Barrett's esophagus and adenocarcinoma, relative to normal esophageal epithelium, and the changes in expression are progressive from Barrett's esophagus to adenocarcinoma (i.e., expression is up- or down-regulated to a greater degree in adenocarcinoma relative than in Barrett's esophagus).
[0038] Analysis of expression by QRT-PCR. Differential expression as determined by DNA array-based analysis was confirmed for select markers within the group of markers shown in Table 2 using QRT-PCR. Briefly, RNA was purified from surgical samples, and QRT-PCR was performed, as described above, for GATA6, HOXB7, TCF3, S100A2, SCCA1 and SPRR3, with GAPDH as the internal control, using primer pairs having the sequences provided in Table 3. The results are shown in FIGS. 1 and 2. With reference to FIG. 1, panel A shows the expressional value (EV) calculated relative to GAPDH for three transcriptional factors (i.e., GATA6, HOXB7 and TCF3) for individual paired patient samples. Patient samples are identified by patient number and sample type, i.e., normal esophageal epithelium (n), Barrett's dysplasia (b), or esophageal adenocarcinoma (t). The results indicate that these genes are up-regulated in the progression from normal to Barrett's esophagus to adenocarcinoma. Panel B shows expressional value (EV) calculated relative to GAPDH for three genes related to keratinocyte differentiation (i.e., S100A2, SCCA1 and SPRR3) for individual paired patient samples. The results indicate that these genes are down-regulated in the progression from normal to Barrett's esophagus to adenocarcinoma. Four samples (n12, n14, nN17 and t17) failed to amplify specific gene products by PCR and were excluded. These data are consistent with the results from the entire set of tissue types in the microarray analysis, as shown in FIGS. 1C and D, which show the corresponding average values, with the standard deviations indicated by the error bars.
[0039] To select expressional markers correlated with pre-malignant and malignant changes, p values and regression coefficients were calculated for six single genes and combinations of genes (Table 4). Each single marker can significantly discriminate normal esophageal epithelium from adenocarcinoma. However, only HOXB7 can discriminate normal tissues from Barrett's. None of the tested markers used alone can discriminate Barrett's from adenocarcinomas. However, as can be seen from Table 4, combinations of markers (GATA6/SPRR3, HOXB7/SPRR3 and GATA6+HOXB7/SPRR3) permit discrimination of Barrett's from adenocarcinomas. Additionally, mixed effects analysis of variance (ANOVA) models were used to determine whether there are differences in expression of GATA6/SPRR3, HOXB7/SPRR3 and GATA6+HOXB7/SPRR3 combinations between the three groups, accounting for the presence of intra-subject correlation due to the presence of several subjects with multiple samples. These analyses confirmed that the expression levels of these combination markers are significantly different between normal, Barrett and Tumor tissues types (data not shown). Also, for the combinations listed, the correlation between expression and tumor progression is higher than for either gene alone.
[0040] The GATA6/SPRR3 ratio was evaluated as marker of transformation (FIG. 2). As can be seen in FIG. 2, the ratio of GATA6 to SPRR3 progressively increases along the progression from normal epithelium to Barrett's dysplasia to adenocarcinomas. At the 95% confidence interval (dashed line, calculated as the mean of normal epithelium values+1.96 SD), the test has a specificity of 89% (8/9 negatives cases). For Barrett's esophagus, the sensitivity of the test, as measured by the percentage of positive cases, is 28.6% (2/9). For adenocarcinoma, the sensitivity is 100% (7/7). With a cut off level equal to 67% confidence interval (mean+1 SD), the specificity of the test is also equal to 89%, the sensitivity for Barrett's esophagus is 86% (6/7), and the sensitivity for adenocarcinoma is 100% (7/7).
[0041] Each reference cited herein is incorporated by reference in its entirety.

Table 1. Functional groups of genes selected for Barrett's and adenocarcinomas.

[0042] 
[00001] [TABLE-US-00001]
  TABLE 1
 
  Selected functional groups for Barrett's and adenocarcinomas
    Adenocarcinomas
  BARRETT   GO Biological process   GO Molecular function
  GO ID   Function name   GO ID   Function name   GO ID   Function name
 
  GO Biological process   GO:0001558   regulation of cell growth   GO:0003700   transcription factor activity
  GO:0000074   regulation of cell cycle   GO:0006081   aldehyde metabolism   GO:0003821   class II major histocompatibility
  GO:0001501   skeletal development   GO:0006355   regulation of transcription,     complex
  GO:0006812   cation transport     DNA-dependent   GO:0004029   aldehyde dehydrogenase
  GO:0006915   apoptosis   GO:0006461   protein complex assembly     (NAD) activity
  GO:0006935   chemotaxis   GO:0006629   lipid metabolism   GO:0004263   chymotrypsin activity
  GO:0006955   immune response   GO:0006886   intracellular protein transport   GO:0004295   trypsin activity
  GO:0007160   cell-matrix adhesion   GO:0006899   nonselective vesicle transport   GO:0004601   peroxidase activity
  GO:0007166   cell surface receptor linked   GO:0006944   membrane fusion   GO:0004867   serine protease inhibitor activity
    signal transduction   GO:0006979   response to oxidative stress   GO:0004930   G-protein coupled receptor activity
  GO:0007229   integrin-mediated signaling   GO:0007048   oncogenesis   GO:0005152   interleukin-1 receptor antagonist
    pathway   GO:0007398   ectoderm development     activity
  GO:0007267   cell-cell signaling   GO:0007417   central nervous system   GO:0005198   structural molecule activity
  GO:0008151   cell growth and/or     development   GO:0005200   structural constituent of
    maintenance   GO:0008284   positive regulation of cell     cytoskeleton
  GO:0008152   metabolism     proliferation   GO:0005509   calcium ion binding
  GO:0009653   morphogenesis   GO:0008544   epidermal differentiation   GO:0005524   ATP binding
  GO Molecular function   GO:0016049   cell growth   GO:0005525   GTP binding
  GO: 0004716   receptor signaling protein   GO:0019883   antigen presentation,   GO:0008237   metallopeptidase activity
    tyrosine kinase     endogenous antigen   GO:0016301   kinase activity
  GO:0004872   receptor activity   GO:0019885   antigen processing via MHC I   GO:0016853   isomerase activity
  GO:0004895   cell adhesion receptor activity   GO:0045786   negative regulation of cell cycle   GO:0030106   MHC class I receptor activity
  GO:0008201   heparin binding   null   cell shape and cell size control   GO:0045012   MHC class II receptor activity
      GO:0006470   protein amino acid   GO:0004033   aldo-keto reductase activity
        dephosphorylation   GO:0005488   binding
      GO:0006805   xenobiotic metabolism   GO:0008014   calcium-dependent cell adhesion
      GO:0006810   transport   GO:0015125   bile acid transporter activity
      GO:0006955   immune response   GO:0017017   MAP kinase phosphatase activity
      GO:0007155   cell adhesion   GO:0047115   trans-1,2-dihydrobenzene-1,2-diol
      GO:0007156   homophilic cell adhesion     dehydrogenase
      GO:0007267   cell-cell signaling
 

Table 2. Genes progressively up- or down-regulated with the development of adenocarcinoma from Barrett's esophagus.
[0043] 
[00002] [TABLE-US-00002]
  TABLE 2
 
  Genes with progressive changes of expression in Barretts and adenocarcinomas
  id   symbol   name   Ratio (B/N)   Ratio (T/N)
 
      up-regulated genes    
  201301_s_at   ANXA4   ANNEXIN A4   2.28   3.13
  201954_at   ARPC1B   ACTIN-RELATED PROTEIN 2/3 COMPLEX, SUBUNIT 1B   3.20   5.42
  214439_x_at   BIN1   BRIDGING INTEGRATOR 1   2.23   3.26
  202901_x_at   CTSS   CATHEPSIN S   3.08   5.26
  210002_at   GATA6   GATA-BINDING PROTEIN 6   6.27   10.77
  221875_x_at   HLA-F   MAJOR HISTOCOMPATIBILITY COMPLEX, CLASS I, F   2.28   3.35
  204806_x_at   HLA-F   MAJOR HISTOCOMPATIBILITY COMPLEX, CLASS I, F   2.17   3.20
  204779_s_at   HOXB7   HOMEO BOX B7   3.56   5.82
  216973_s_at   HOXB7   HOMEO BOX B7   2.71   4.42
  201422_at   IFI30   INTERFERON-GAMMA-INDUCIBLE PROTEIN 30   2.23   4.11
  212110_at   KIAA0062   SLC39A14: solute carrier family 39 (zinc transporter), member 14   5.26   7.86
  203943_at   KIF3B   KINESIN FAMILY MEMBER 3B   2.27   3.43
  218376_s_at   NICAL   NEDD9 interacting protein with calponin homology and LIM domains   2.03   3.12
  219622_at   RAB20   RAB20, member RAS oncogene family   2.90   4.66
  201206_s_at   RRBP1   RIBOSOME BINDING PROTEIN 1   4.02   5.80
  201204_s_at   RRBP1   RIBOSOME BINDING PROTEIN 1   2.46   3.34
  213811_x_at   TCF3   TRANSCRIPTION FACTOR 3   2.84   4.45
  208998_at   UCP2   UNCOUPLING PROTEIN 2   3.52   6.57
      down-regulated genes
  210020_x_at   CALML3   CALMODULIN-LIKE 3   0.40   0.11
  203585_at   ZNF185   ZINC FINGER PROTEIN 185   0.46   0.17
  213005_s_at   KANK   KIDNEY ANKYRIN REPEAT-CONTAINING PROTEIN   0.49   0.24
  211734_s_at   FCER1A   Fc FRAGMENT OF IgE, HIGH AFFINITY I, RECEPTOR FOR, ALPHA   0.25   0.14
      SUBUNIT
  201848_s_at   BNIP3   BCL2/ADENOVIRUS E1B 19-KD PROTEIN-INTERACTING PROTEIN 3   0.43   0.26
  219100_at   FLJ22559   hypothetical protein   0.48   0.29
 
[0044] 
[00003] [TABLE-US-00003]
  TABLE 3
 
  Primers for detection of genes progressively  
  changing in Barrett's associated
  adenocarcinomas.
  Gene   forward primer   reverse primer
 
  gapdh   TGCACCACCAACTGCTTAGC   GGCATGGACTGTGGTCATGAG  
    SEQ ID NO: 1   SEQ ID NO: 2
 
  gata6   AGCGCGTGCCTTCATCAC   GCAAGTGGTCTGGGCACC
    SEQ ID NO: 3   SEQ ID NO: 4
 
  hoxb7   GGATCTACCCCTGGATGCG   GTCTTTCCGTGAGGCAGAGC
    SEQ ID NO: 5   SEQ ID NO: 6
 
  s100a2   CTGTCTCTGCCACCTGGTCT   CTCAAAGGCATCAACAGTCCT
    SEQ ID NO: 7   SEQ ID NO: 8
 
  serpinb3   TTCATGTTCGACCTGTTCCA   GCAGCTTTTCCTGTGGTGTT
  (SCCA1)   SEQ ID NO: 9   SEQ ID NO: 10
 
  sprr3   ATCCCTGAGCAGCTGAAGAC   CTGCTGTTGAAGCTGAGGTG
    SEQ ID NO: 11   SEQ ID NO: 12
 
  tcf3   GTGACATCAACGAGGCCTTT   CTGCTTTGGGATTCAGGTTC
    SEQ ID NO: 13   SEQ ID NO: 14
 
[0045] 
[00004] [TABLE-US-00004]
  TABLE 4
 
  p values and Pearson's correlation coefficients.
    p values  
    N-     BE-   R
  Gene symbol   ADENOCARCINOMA   N-BE   ADENOCARCINOMA   values
 
  GATA6   0.0014   0.0797   0.1510   0.6909
  HOXB7   0.0001   0.0183   0.1045   0.7657
  TCF3   0.0063   0.2048   0.0769   0.5797
  S100A2   0.0332   0.4123   0.1131   −0.4752
  SCCA1   0.0171   0.3794   0.1184   −0.4551
  SPRR3   0.0011   0.1116   0.1014   −0.6177
  GATA6/SPRR3   1.4662E−06   0.0012   0.0013   0.8732
  HOXB7/SPRR3   4.0369E−06   0.0092   0.0211   0.8176
  GATA6 + HOXB7/SPRR3   1.6406E−06   0.0028   0.0034   0.8628
 
[0046] 
[00005] [TABLE-US-00005]
  SUPPLEMENTAL TABLE 1
 
          5   6
          Expression in   Expression in
          Barrett's   adenocarcinoma
        4   relative to the   relative to
      3   Gene   normal   normal
  1   2   Expressional   number   epithelium   epithelium
  Probe set id   Gene symbol   cluster number   in FIG. 2   [Log2 R (B/N)]   [Log2 R (T/N)]
 
 
  205927_s_at   CTSE   1   1   4.55   4.83
  219580_s_at   TMC5   1   2   4.21   5.46
  210143_at   ANXA10   1   3   5.38   4.62
  203824_at   TM4SF3   1   4   2.73   3.07
  203559_s_at   ABP1   1   5   3.28   3.64
  208161_s_at   ABCC3   1   6   2.43   2.70
  204714_s_at   F5   1   7   2.43   3.27
  209301_at   CA2   1   8   2.56   1.94
  219682_s_at   TBX3   1   9   2.93   1.99
  64408_s_at   CLN6   1   10   3.03   2.82
  201666_at   TIMP1   1   11   1.49   2.04
  220974_x_at   BA108L7.2   1   12   1.34   1.34
  219327_s_at   GPRC5C   1   13   1.14   2.05
  210095_s_at   IGFBP3   1   14   1.55   2.57
  219956_at   GALNT6   1   15   2.77   2.27
  202910_s_at   CD97   1   16   1.57   2.08
  209774_x_at   CXCL2   1   17   1.48   1.65
  207522_s_at   ATP2A3   1   18   2.44   1.43
  202267_at   LAMC2   1   19   2.11   3.01
  210314_x_at   TNFSF13   1   20   2.42   3.18
  219795_at   SLC6A14   1   21   3.03   3.49
  202625_at   LYN   1   22   2.09   2.40
  203058_s_at   PAPSS2   1   23   1.19   1.43
  210754_s_at   LYN   1   24   1.56   1.54
  222303_at   ETS2   1   25   1.74   0.96
  220322_at   IL1F9   1   26   1.93   0.07
  205668_at   LY75   1   27   1.16   1.80
  204363_at   F3   1   28   1.11   0.03
  203510_at   MET   1   29   2.39   3.57
  214235_at   CYP3A5   1   30   2.08   2.59
  202820_at   AHR   1   31   1.86   2.59
  210664_s_at   TFPI   1   32   1.17   1.33
  205289_at   BMP2   1   33   1.62   2.05
  201656_at   ITGA6   1   34   1.79   1.51
  215177_s_at   ITGA6   1   35   1.40   1.02
  221059_s_at   CHST6   1   36   2.43   3.02
  205067_at   IL1B   1   37   2.42   0.84
  210845_s_at   PLAUR   1   38   2.15   2.51
  211924_s_at   PLAUR   1   39   1.99   2.27
  206467_x_at   TNFRSF6B   1   40   1.83   2.44
  39402_at   IL1B   1   41   2.84   1.04
  209417_s_at   IFI35   1   42   1.28   2.04
  201596_x_at   KRT18   1   43   1.62   1.83
  204017_at   KDELR3   1   44   1.98   2.32
  204989_s_at   ITGB4   1   45   1.18   1.16
  207265_s_at   KDELR3   1   46   1.34   1.41
  202831_at   GPX2   1   47   1.31   1.84
  201189_s_at   ITPR3   1   48   1.36   1.71
  202668_at   EFNB2   1   49   1.68   1.84
  212282_at   MAC30   1   50   1.34   2.66
  212281_s_at   MAC30   1   51   1.41   2.67
  212279_at   MAC30   1   52   1.00   2.19
  208829_at   TAPBP   1   53   0.89   1.69
  211529_x_at   HLA-G   1   54   0.85   1.35
  211911_x_at   HLA-B   1   55   0.93   1.34
  208729_x_at   HLA-B   1   56   0.78   1.18
  214459_x_at   HLA-C   1   57   0.86   1.23
  203857_s_at   PDIR   1   58   0.89   1.09
  211528_x_at   HLA-G   1   59   0.81   1.24
  202737_s_at   LSM4   1   60   0.53   1.38
  201063_at   RCN1   1   61   0.75   1.82
  209762_x_at   SP110   1   62   0.63   1.31
  205205_at   RELB   1   63   0.87   1.16
  213258_at   TFPI   1   64   0.99   1.19
  210927_x_at   JTB   1   65   0.46   1.14
  218355_at   KIF4A   1   66   1.04   1.85
  211048_s_at   ERP70   1   67   0.86   1.62
  200699_at   KDELR2   1   68   0.94   1.69
  212761_at   TCF7L2   1   69   0.77   1.24
  201329_s_at   ETS2   1   70   1.01   0.17
  200037_s_at   CBX3   1   71   0.34   1.47
  211208_s_at   CASK   1   72   0.65   1.33
  210052_s_at   TPX2   1   73   0.64   1.55
  204641_at   NEK2   1   74   0.68   1.95
  204670_x_at   HLA-DRB3   1   75   0.63   1.76
  209312_x_at   HLA-DRB3   1   76   0.77   1.80
  208306_x_at   HLA-DRB3   1   77   0.78   1.83
  215193_x_at   HLA-DRB3   1   78   0.88   1.85
  210982_s_at   HLA-DRA   1   79   0.73   1.53
  208894_at   HLA-DRA   1   80   0.53   1.27
  211126_s_at   CSRP2   2   81   −0.77   −1.84
  207030_s_at   CSRP2   2   82   −0.80   −1.63
  203659_s_at   RFP2   2   83   −0.81   −1.26
  221960_s_at   RAB2   2   84   −0.71   −1.53
  202582_s_at   RANBP9   2   85   −0.70   −1.61
  209882_at   RIT1   2   86   −0.85   −1.85
  201454_s_at   NPEPPS   2   87   −0.71   −1.55
  204119_s_at   ADK   2   88   −0.75   −1.59
  208771_s_at   LTA4H   2   89   −0.51   −1.40
  200606_at   DSP   2   90   −0.32   −1.66
  213572_s_at   SERPINB1   2   91   −0.39   −2.30
  212268_at   SERPINB1   2   92   −0.38   −1.63
  202814_s_at   HIS1   2   93   −0.46   −1.27
  200697_at   HK1   2   94   −0.54   −1.47
  208384_s_at   MID2   2   95   −0.66   −1.47
  201192_s_at   PITPN   2   96   −0.60   −1.54
  203081_at   CTNNBIP1   2   97   −0.58   −1.67
  201161_s_at   CSDA   2   98   −0.54   −1.57
  211749_s_at   VAMP3   2   99   −0.39   −1.23
  209157_at   DNAJA2   2   100   −0.60   −1.33
  208951_at   ALDH7A1   2   101   −0.71   −1.40
  208950_s_at   ALDH7A1   2   102   −0.80   −1.47
  201337_s_at   VAMP3   2   103   −0.62   −1.70
  201612_at   ALDH9A1   2   104   −0.85   −1.56
  41644_at   SASH1   2   105   −0.65   −2.01
  213236_at   SASH1   2   106   −1.08   −2.48
  210094_s_at   PARD3   2   107   −0.44   −1.18
  221526_x_at   PARD3   2   108   −0.63   −1.18
  214040_s_at   GSN   2   109   −0.93   −2.37
  202054_s_at   ALDH3A2   2   110   −1.05   −1.70
  202053_s_at   ALDH3A2   2   111   −1.02   −2.19
  209466_x_at   PTN   2   112   −1.43   −2.06
  201041_s_at   DUSP1   2   113   0.22   −1.11
  201044_x_at   DUSP1   2   114   −0.11   −1.59
  202139_at   AKR7A2   2   115   −0.60   −1.20
  209372_x_at   TUBB   2   116   −0.86   −1.77
  215813_s_at   PTGS1   2   117   −0.42   −1.68
  210186_s_at   FKBP1A   2   118   −0.74   −1.24
  200678_x_at   GRN   2   119   −0.92   −1.46
  216041_x_at   GRN   2   120   −0.96   −1.58
  204246_s_at   DCTN3   2   121   −0.73   −1.63
  200886_s_at   PGAM1   2   122   −0.45   −1.62
  204029_at   CELSR2   2   123   −0.75   −2.04
  36499_at   CELSR2   2   124   −0.68   −1.97
  203586_s_at   ARF4L   2   125   −0.44   −2.37
  213848_at   DUSP7   2   126   −0.28   −2.13
  200844_s_at   PRDX6   2   127   −0.86   −1.39
  208751_at   NAPA   2   128   −0.73   −1.20
  202807_s_at   TOM1   2   129   −0.73   −1.39
  214182_at   ARF6   2   130   −0.74   −1.68
  209193_at   PIM1   2   131   −0.96   −1.95
  205172_x_at   CLTB   2   132   −0.65   −1.78
  211043_s_at   CLTB   2   133   −0.44   −1.95
  206284_x_at   CLTB   2   134   −0.65   −1.95
  200863_s_at   RAB11A   2   135   −0.51   −1.58
  200752_s_at   CAPN1   2   136   −0.79   −1.65
  204341_at   TRIM16   2   137   −0.82   −2.50
  204151_x_at   AKR1C1   2   138   0.44   −0.96
  211653_x_at   AKR1C2   2   139   0.37   −1.32
  209699_x_at   AKR1C2   2   140   0.47   −1.03
  216594_x_at   AKR1C1   2   141   0.40   −1.00
  205403_at   IL1R2   2   142   1.24   0.13
  206561_s_at   AKR1B10   2   143   0.58   −1.07
  205549_at   PCP4   3   144   −1.55   −2.80
  218559_s_at   MAFB   3   145   −0.99   −2.39
  204379_s_at   FGFR3   3   146   −0.86   −2.28
  205286_at   TFAP2C   3   147   −0.62   −2.58
  203074_at   ANXA8   3   148   −0.89   −4.35
  203407_at   PPL   3   149   −0.74   −3.93
  202504_at   TRIM29   3   150   −0.65   −3.94
  204942_s_at   ALDH3B2   3   151   −1.33   −5.08
  202345_s_at   FABP5   3   152   −0.24   −2.58
  201012_at   ANXA1   3   153   −0.22   −2.63
  212657_s_at   IL1RN   3   154   −0.43   −3.01
  218677_at   S100A14   3   155   −0.39   −2.56
  201324_at   EMP1   3   156   −0.56   −2.97
  201325_s_at   EMP1   3   157   −0.61   −3.85
  219764_at   FZD10   3   158   −0.50   −2.69
  209191_at   TUBB-5   3   159   −0.77   −2.28
  201348_at   GPX3   3   160   −0.84   −2.71
  205349_at   GNA15   3   161   −0.82   −2.96
  209587_at   PITX1   3   162   −0.94   −3.92
  213279_at   DHRS1   3   163   −1.28   −3.02
  205863_at   S100A12   3   164   −0.59   −3.15
  38158_at   ESPL1   3   165   −1.82   −2.87
  205470_s_at   KLK11   3   166   −0.95   −3.79
  217315_s_at   KLK13   3   167   −0.97   −4.60
  205783_at   KLK13   3   168   −1.41   −4.41
  216243_s_at   IL1RN   3   169   −1.12   −4.53
  204777_s_at   MAL   3   170   −0.74   −5.21
  14599_at   IVL   3   171   −0.68   −4.91
  214549_x_at   SPRR1A   3   172   −0.74   −4.05
  204751_x_at   DSC2   3   173   −0.32   −2.35
  204469_at   PTPRZ1   3   174   −0.03   −1.61
  206032_at   DSC3   3   175   −0.74   −4.05
  206166_s_at   CLCA2   3   176   −0.66   −4.29
  210372_s_at   TPD52L1   3   177   −0.93   −2.87
  203786_s_at   TPD52L1   3   178   −1.11   −3.28
  213135_at   TIAM1   3   179   −0.67   −3.20
  203797_at   VSNL1   3   180   −1.06   −2.72
  207059_at   PAX9   3   181   −1.36   −3.68
  204284_at   PPP1R3C   3   182   −0.68   −3.72
  211726_s_at   FMO2   3   183   −1.01   −2.95
  204614_at   SERPINB2   3   184   −0.77   −4.47
  207602_at   HAT   3   185   −0.63   −3.87
  205595_at   DSG3   3   186   −0.47   −3.58
  209719_x_at   SERPINB3   3   187   −0.36   −3.79
  211906_s_at   SERPINB4   3   188   −0.31   −4.07
  205185_at   SPINK5   3   189   −0.63   −3.03
  210413_x_at   SERPINB4   3   190   0.07   −4.32
  204734_at   KRT15   3   191   −0.92   −7.56
  220431_at   DESC1   3   192   −1.00   −5.02
  220026_at   CLCA4   3   193   −0.61   −5.19
  217528_at   CLCA2   3   194   −0.60   −4.31
  206276_at   E48   3   195   −0.63   −4.18
  209720_s_at   SERPINB3   3   196   −0.32   −3.72
  208539_x_at   SPRR2B   3   197   −0.56   −3.89
  213240_s_at   KRT4   3   198   −0.03   −4.73
  213796_at   SPRR1A   3   199   −0.27   −3.30
  219554_at   RHCG   3   200   −0.61   −6.05
  205014_at   HBP17   3   201   −0.28   −4.24
  203535_at   S100A9   3   202   −0.21   −3.46
  39248_at   AQP3   3   203   −0.42   −3.75
  204268_at   S100A2   3   204   −0.16   −3.42
  202917_s_at   S100A8   3   205   0.00   −2.48
  213680_at   KRT6B   3   206   −0.16   −2.92
  218990_s_at   SPRR3   3   207   −0.07   −3.18
  207935_s_at   KRT13   3   208   −0.19   −3.89
  209126_x_at   KRT6B   3   209   −0.18   −3.52
  201820_at   KRT5   3   210   −0.29   −3.89
  209125_at   KRT6A   3   211   −0.24   −3.32
  205064_at   SPRR1B   3   212   −0.23   −3.25
  209351_at   KRT14   3   213   0.81   −2.17
  220664_at   SPRR2C   3   214   −0.38   −4.25
 
[0047] 
[00006] [TABLE-US-00006]
  SUPPLEMENTAL TABLE 2
 
      Gene   Log2 R   Log2 R
  Probe set ID   Gene name   symbol   (B/N)   (T/N)
 
 
  204272_at   galectin 4   LGALS4   4.90   4.83
  211429_s_atHomo sapiens PRO2275 mRNA   unknown   4.26   4.70
  201839_s_at   tumor-associated calcium signal transducer 1   TACSTD1   3.27   3.76
  209008_x_at   keratin 8   KRT8   2.88   3.00
  209173_atanterior gradient 2 homolog (Xenopus laevis)   AGR2   2.87   3.25
  213059_at   old astrocyte specifically induced substance   OASIS   2.76   2.97
  212444_at   retinoic acid induced 3   RAI3   2.68   2.92
  213036_x_at   ATPase, Ca++ transporting, ubiquitous   ATP2A3   2.67   1.89
  210002_at   GATA binding protein 6   GATA6   2.65   3.43
  212314_at   KIAA0746 protein   KIAA0746   2.58   3.03
  200644_at   MARCKS-like protein   MLP   2.52   3.00
  212110_at   KIAA0062 protein   KIAA0062   2.40   2.98
  205632_s_at   phosphatidylinositol-4-phosphate 5-kinase, type I,   PIP5K1B   2.32   2.52
    beta
  209453_at   solute carrier family 9   SLC9A1   2.08   1.57
  212311_at   KIAA0746 protein   KIAA0746   2.05   2.31
  221766_s_at   chromosome 6 open reading frame 37   C6orf37   2.01   2.37
  201206_s_at   ribosome binding protein 1 homolog 180 kDa (dog)   RRBP1   2.01   2.54
  217989_at   retinal short-chain dehydrogenase/reductase 2   RETSDR2   1.97   2.23
  208891_at   dual specificity phosphatase 6   DUSP6   1.96   1.49
  212143_s_at   insulin-like growth factor binding protein 3   IGFBP3   1.89   2.51
  220532_s_at   LR8 protein   LR8   1.88   2.49
  218113_at   transmembrane protein 2   TMEM2   1.86   1.92
  204779_s_at   homeo box B7   HOXB7   1.83   2.54
  208998_at   uncoupling protein 2   UCP2   1.81   2.72
  210264_at   G protein-coupled receptor 35   GPR35   1.70   1.91
  201954_at   actin related protein 2/3 complex, subunit 1B, 41 kDa   ARPC1B   1.68   2.44
  202901_x_at   cathepsin S   CTSS   1.62   2.40
  219622_at   RAB20, member RAS oncogene family   RAB20   1.53   2.22
  213811_x_at   transcription factor 3   TCF3   1.50   2.15
  200972_at   tetraspan 3   TSPAN-3   1.49   1.50
  218368_s_at   TNF receptor superfamily, member 12A   TNFRSF12A   1.49   1.41
  203028_s_at   cytochrome b-245, alpha polypeptide   CYBA   1.47   2.05
  208892_s_at   dual specificity phosphatase 6   DUSP6   1.47   1.20
  216973_s_at   homeo box B7   HOXB7   1.44   2.14
  212552_at   hippocalcin-like 1   HPCAL1   1.42   1.68
  209270_at   laminin, beta 3   LAMB3   1.37   1.39
  201204_s_at   ribosome binding protein 1 homolog   RRBP1   1.30   1.74
  202180_s_at   major vault protein   MVP   1.30   1.48
  201579_at   FAT tumor suppressor homolog 1   FAT   1.28   1.16
  202369_s_at   translocation associated membrane protein 2   TRAM2   1.20   1.12
  211799_x_at   major histocompatibility complex, class I, C   HLA-C   1.19   1.40
  201301_s_at   annexin A4   ANXA4   1.19   1.65
  221875_x_at   major histocompatibility complex, class I, F   HLA-F   1.19   1.74
  203943_at   kinesin family member 3B   KIF3B   1.18   1.78
  200599_s_at   tumor rejection antigen (gp96) 1   TRA1   1.17   1.52
  201422_at   interferon, gamma-inducible protein 30   IFI30   1.16   2.04
  214439_x_at   bridging integrator 1   BIN1   1.16   1.70
  202838_at   fucosidase, alpha-L-1, tissue   FUCA1   1.14   1.30
  204806_x_at   major histocompatibility complex, class I, F   HLA-F   1.12   1.68
  209295_at   TNF receptor superfamily, member 10b   TNFRSF10B   1.09   1.43
  209635_at   adaptor-related protein complex 1, sigma 1 subunit   AP1S1   1.06   1.53
  203038_at   protein tyrosine phosphatase, receptor type, K   PTPRK   1.04   1.39
  218376_s_at   NEDD9 interacting protein   NICAL   1.02   1.64
  210776_x_at   transcription factor 3   TCF3   1.01   1.46
  217741_s_at   zinc finger protein 216   ZNF216   −1.02   −1.49
  213005_s_at   kidney ankyrin repeat-containing protein   KANK   −1.02   −2.06
  201851_at   SH3-domain GRB2-like 1   SH3GL1   −1.05   −1.39
  220942_x_at   growth and transformation-dependent protein   E2IG5   −1.07   −1.55
  219100_at   hypothetical protein FLJ22559   FLJ22559   −1.07   −1.77
  218205_s_at   MAP kinase-interacting serine/threonine kinase 2   MKNK2   −1.10   −1.29
  220620_at   NICE-1 protein   NICE-1   −1.10   −2.37
  218231_at   N-acetylglucosamine kinase   NAGK   −1.10   −1.76
  203585_at   zinc finger protein 185 (LIM domain)   ZNF185   −1.12   −2.57
  203771_s_at   biliverdin reductase A   BLVRA   −1.14   −1.79
  219090_at   solute carrier family 24, member 3   SLC24A3   −1.15   −2.02
  219597_s_at   dual oxidase 1   DUOX1   −1.16   −2.61
  214279_s_at   NDRG family member 2   NDRG2   −1.18   −2.37
  219104_at   ring finger protein 141   RNF141   −1.18   −2.12
  209872_s_at   plakophilin 3   PKP3   −1.19   −1.90
  201848_s_at   BCL2/adenovirus E1B 19 kDa interacting protein 3   BNIP3   −1.22   −1.92
  55872_at   KIAA1196 protein   KIAA1196   −1.23   −1.45
  57588_at   solute carrier family 24, member 3   SLC24A3   −1.23   −1.85
  212659_s_at   interleukin 1 receptor antagonist   IL1RN   −1.26   −2.52
  215440_s_at   hypothetical protein FLJ10097   FLJ10097   −1.28   −1.89
  207469_s_at   Pirin   PIR   −1.29   −1.43
  202575_at   cellular retinoic acid binding protein 2   CRABP2   −1.29   −2.84
  218935_at   EH-domain containing 3   EHD3   −1.30   −2.39
  210020_x_at   calmodulin-like 3   CALML3   −1.32   −3.13
  203126_at   inositol(myo)-1(or 4)-monophosphatase 2   IMPA2   −1.32   −1.67
  206004_at   transglutaminase 3   TGM3   −1.32   −2.61
  217508_s_at   hypothetical protein MGC12909   MGC12909   −1.36   −1.94
  209465_x_at   pleiotrophin   PTN   −1.37   −2.00
  210096_at   cytochrome P450, family 4, subfamily B, polypeptide 1   CYP4B1   −1.38   −2.94
  219983_at   HRAS-like suppressor   HRASLS   −1.39   −1.73
  219165_at   PDZ and LIM domain 2 (mystique)   PDLIM2   −1.39   −2.27
  206400_at   lectin, galactoside-binding, soluble, 7 (galectin 7)   LGALS7   −1.39   −2.58
  204454_at   leucine zipper, down-regulated in cancer 1   LDOC1   −1.44   −1.22
  221523_s_at   Ras-related GTP binding D   RRAGD   −1.44   −2.13
  219529_at   chloride intracellular channel 3   CLIC3   −1.45   −2.61
  208626_s_at   vesicle amine transport protein 1 homolog   VAT1   −1.55   −1.64
  205623_at   aldehyde dehydrogenase 3 family, memberA1   ALDH3A1   −1.59   −2.64
  211737_x_at   pleiotrophin   PTN   −1.63   −2.27
  218484_at   NADH: ubiquinone oxidoreductase   LOC56901   −1.69   −2.66
  221524_s_at   Ras-related GTP binding D   RRAGD   −1.72   −2.42
  220016_at   hypothetical protein MGC5395   MGC5395   −1.74   −2.20
  211734_s_at   Fc fragment of IgE, high affinity I, receptor   FCER1A   −2.03   −2.82
 

REFERENCES

[0048] 1. Stein H J, Siewert J R. Barrett's esophagus: pathogenesis, epidemiology, functional abnormalities, malignant degeneration, and surgical management. Dysphagia 1993; 8:276-88.
[0049] 2. Lagergren J, Bergstrom R, Lindgren A, Nyren O. Symptomatic gastroesophageal reflux as a risk factor for esophageal adenocarcinoma. N Engl J Med 1999; 34:825-31.
[0050] 3. Shaheen N, Ransohoff D F. Gastroesophageal reflux, Barrett esophagus and esophageal cancer. JAMA 2002; 287:1972-81.
[0051] 4. Shaheen N J, Crosby M A, Bozymski E M, Sandler R S. Is there publication bias in the reporting of cancer risk in Barrett's esophagus? Gastroenterology 2000; 119:333-8.
[0052] 5. Devesa S S, Blot W J, Fraumeni J F Jr. Changing patterns in the incidence of esophageal and gastric carcinoma in the United States. Cancer 1998; 83:2049-53.
[0053] 6. Swisher S G, Hunt K K, Holmes E C, Zinner M J, McFaddwn D W. Changes in the surgical management of esophageal cancer from 1970 to 1993. Am J Surg 1995; 169:609-14.
[0054] 7. Goldblum J R, Lauwers G Y. Dysplasia arising in Barrett's esophagus: diagnostic pitfalls and natural history. Semin Diagn Pathol 2002; 19:12-19.
[0055] 8. McManus D T, Olaru A, Meltzer S J. Biomarkers of esophageal adenocarcinoma and Barrett's esophagus. Cancer Res 2004; 64:1561-9.
[0056] 9. Luo A, Kong J, Hu G, et al. Discovery of Ca2+-relevant and differentiation-associated genes downregulated in esophageal squamous cell carcinoma using cDNA microarray. Oncogene 2004; 23:1291.
[0057] 10. Xu Y, Selaru F M, Yin J, et al. Artificial neural networks and gene filtering distinguish between global gene expression profiles of Barrett's esophagus and esophageal cancer. Cancer Res 2002; 62:3493-7.
[0058] 11. Dahlberg P S, Ferrin L F, Grindle S M, et al. Gene expression profiles in esophageal adenocarcinoma. Ann Thorac Surg 2004; 77: 1008-15.
[0059] 12. Barrett M T, Yeung K Y, Ruzzo W L, et al. Transcriptional analyses of Barrett's metaplasia and normal upper Gl mucosae. Neoplasia 2002; 4:121-8.
[0060] 13. Williams R R, Broad S, Sheer D, Ragoussis J. Subchromosomal positioning of the epidermal differentiation complex (EDC) in keratinocyte and lymphoblast interphase nuclei. Exp Cell Res 2002; 272:163-75.
[0061] 14. Marenholz I, Zirra M, Fischer D F, Backendorf C, Ziegler A, Mischke D. Identification of human epidermal differentiation complex (EDC)-encoded genes by subtractive hybridization of entire YACs to a gridded keratinocyte cDNA library. Genome Res 2001; 11:341-55.
[0062] 15. Khodarev N N, Yu J, Nodzenski E, Murley J S, et al. Method of RNA purification from endothelial cells for DNA array experiments. Biotechniques 2002; 32:316-20.
[0063] 16. Khodarev N N, Park J, Kataoka Y, et al. Receiver operating characteristic analysis: a general tool for DNA array data filtration and performance estimation. Genomics 2003; 81:202-209.
[0064] 17. Khodarev N N, Beckett M, Labay E, Darga T, Roizman B, Weichselbaum R R. STAT1 is overexpressed in tumors selected for radioresistance and confers protection from radiation in transduced sensitive cells. Proc Natl Acad Sci USA 2004; 101:1714-9.
[0065] 18. Tusher V G, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 2001; 98:5116-21.
[0066] 19. Draghici S, Khatri P, Martins R P, Ostermeier G C, Krawetz S A. Global functional profiling of gene expression. Genomics 2003; 81:98-104.
[0067] 20. Khodarev N N, Kataoka Y, Murley J S, Weichselbaum R R, Grdina D J. Interaction of amifostine and ionizing radiation on transcriptional patterns of apoptotic genes expressed in human microvascular endothelial cells (HMEC). Int J Radiat Oncol Biol Phys 2004; 60:553-63.
(57)

Claims

1. A method of assessing risk of adenocarcinoma in a mammal with Barrett's esophagus comprising:
(a) determining the ratio of the expression of GATA6 and SPRR3 in esophageal cells from the mammal; and
(b) comparing the ratio of step (a) to the ratio of expression of GATA6 and SPRR3 in a reference selected from the group consisting of normal esophageal epithelium obtained from the mammal at the same or different time, cells characteristic of Barrett's esophagus obtained from the mammal at a different time, and a normal range established using normal esophageal epithelium obtained from a population of individuals, an increase in the ratio of step (a) relative to the ratio of the reference being indicative of increased risk of adenocarcinoma.
2. The method of claim 1, wherein the level of expression is measured by quantitative reverse transcription-PCR.
3. The method of claim 2, wherein the level of expression is measured by real time PCR.
4. The method of claim 1, wherein the reference is normal esophageal epithelium obtained from the mammal at essentially the same time as the Barrett's esophageal cells.
5. The method of claim 1, wherein the reference is normal esophageal epithelium or second Barrett's esophageal cells obtained from the mammal prior to obtaining the Barrett's esophageal cells of step (a).
6. The method of claim 1, wherein the reference is a panel of normal esophageal epithelium obtained from a population of mammals.
7. The method of claim 1, further comprising determining the expression of a marker selected from the group consisting of HOXB7, TCF3, S100A2, and SCCA.
*****

Download Citation


Sign in to the Lens

Feedback