Methods to predict progression of Barrett's Esophagus to high grade dysplasia esophageal adenocarcinoma
11391737 · 2022-07-19
Assignee
Inventors
Cpc classification
G01N2333/70596
PHYSICS
G01N2400/00
PHYSICS
International classification
Abstract
In some embodiments, a method for aiding prediction of the likelihood of progression from Barrett's esophagus to high grade dysplasia or esophageal adenocarcinoma in a subject, is disclosed. The method can include (a) providing an oesophagal sample from said subject (b) determining if said sample stains abnormally with Aspergillus oryzae lectin; (c) determining if there is a DNA content abnormality in said sample; and (d) determining if there is low grade dysplasia in said sample; wherein if (b) is abnormal and (c) is abnormal and low grade dysplasia is present, then an increased likelihood of progression is determined. The disclosed subject matter also relates to an apparatus, and to different uses of certain materials.
Claims
1. A method for determining likelihood of progression from Barrett's esophagus to high grade dysplasia or esophageal adenocarcinoma in a human subject with Barrett's esophagus using an assay device, which includes a biomarker panel, the method comprising: (a) providing an oesophagal sample from said human subject, and using the sample for detection of fragments of biomarkers in the sample; (b) staining said sample with biotinylated Aspergillus oryzae lectin (AOL) and determining whether the stained sample produces an abnormal stain based on determination of a staining score, the staining requires an assay that stains, the biotinylated Aspergillus oryzae lectin is Aspergillus oryzae lectin, which is labelled with biotin; and (c) determining if a DNA copy number in said sample is abnormal using image cytometry DNA analysis, the DNA copy number diploid being normal, and the DNA copy number tetraploidy or aneuploidy being abnormal; and (d) determining if there is low grade dysplasia in said sample, wherein, in a first determination, if (b) is abnormal and (c) is abnormal and low grade dysplasia is present, then the likelihood of said progression is determined to be higher for said human subject compared to the likelihood of said progression for an equivalent subject, in a second determination, demonstrating all of the following: a normal stain in step (b); a normal DNA copy in step (c) and no low grade dysplasia, wherein: step (d) includes histological examination of the sample, and scoring one of the presence and absence of low grade dysplasia using a Vienna scale, the assay device includes the biomarker panel including a material, which binds to and has affinity for AOL, and the determining whether the stained sample produces an abnormal stain based on determination of the staining score includes: staining a plurality of components, the plurality of components includes apical membrane, pan membranous, epithelial mucous globules and epithelial cytoplasm; determining a level of staining by the AOL, for each component, by: (a) grading the intensity of the stain and the percentage of the area stained at said intensity, and (b) producing, based on the level of the staining for each component, an H score; and comparing for each component, of the plurality of components, to determine if the H score is abnormal, the comparing including: the H score considered abnormal if highest score for apical membrane, epithelial mucous globules or epithelial cytoplasm was 4-12, or pan membranous was >0; based on the comparing, dichotomizing each of the components of the staining score into one of normal and abnormal; summing, the results of the dichotomizing, to provide an overall abnormal score for the components; and comparing the overall abnormal score to a reference to determine if the stained sample is abnormal.
2. A method according to claim 1, further comprising step (e) determining if staining for CA 19-9 produces an abnormal stain, wherein if (b) is abnormal and (c) is abnormal and low grade dysplasia is present, and if (e) is abnormal then the likelihood of progression to esophageal adenocarcinoma is determined to be greater than if (e) is normal.
3. An assay, which includes a biomarker panel, for selecting a treatment regimen for a human subject with Barrett's esophagus, said assay comprising (a) providing an oesophagal sample from said human subject, and using the sample for detection of fragments of biomarkers in the sample; (b) staining said sample with biotinylated Aspergillus oryzae lectin (AOL) and determining whether the stained sample produces an abnormal stain based on determination of a staining score, wherein the staining requires an assay that stains, the biotinylated Aspergillus oryzae lectin is Aspergillus oryzae lectin, which is labelled with biotin; (c) determining if a DNA copy number in said sample is abnormal using image cytometry DNA analysis, the DNA copy number diploid being normal, and the DNA copy number tetraploidy or aneuploidy being abnormal; and (d) determining if there is low grade dysplasia in said sample, wherein: if (b) is abnormal and (c) is abnormal and low grade dysplasia is present, then a treatment regimen including-surveillance is selected, step (d) includes histological examination of the sample, and scoring one of the presence and absence of low grade dysplasia using a Vienna scale, the assay device includes the biomarker panel including a material, which binds to and has affinity for AOL, and the determining whether the stained sample produces an abnormal stain based on determination of the staining score includes: staining a plurality of components, the plurality of components includes apical membrane, pan membranous, epithelial mucous globules and epithelial cytoplasm; determining a level of staining by the AOL, for each component, by: (a) grading the intensity of the stain and the percentage of the area stained at said intensity, and (b) producing, based on the level of the staining for each component, an H score; and comparing for each component, of the plurality of components, to determine if the H score is abnormal, the comparing including: the H score considered abnormal if highest score for apical membrane, epithelial mucous globules or epithelial cytoplasm was 4-12, or pan membranous was >0; based on the comparing, dichotomizing each of the components of the staining score into one of normal and abnormal; summing, the results of the dichotomizing, to provide an overall abnormal score of for the components; and comparing the overall abnormal score to a reference to determine if the stained sample is abnormal.
4. A method according to claim 1, wherein said sample comprises formalin fixed paraffin embedded material.
5. A method according to claim 1 wherein step (c) comprises determining the DNA copy number by image cytometry DNA analysis and inferring from said determination whether said DNA copy number is abnormal.
6. A method for treating a human subject with Barrett's esophagus, which includes a biomarker panel, the method comprising: (a) providing an oesophagal sample from said human subject, and using the sample for detection of fragments of biomarkers in the sample; (b) determining if staining said sample with biotinylated Aspergillus oryzae lectin (AOL) produces an abnormal stain based on determination of a staining score, wherein the staining requires an assay that stains, the biotinylated Aspergillus oryzae lectin is Aspergillus oryzae lectin, which is labelled with biotin, (c) determining if a DNA copy number in said sample is abnormal using image cytometry DNA analysis, the DNA copy number diploid being normal, and the DNA copy number tetraploidy and aneuploidy being abnormal; and (d) determining if there is low grade dysplasia in said sample, wherein: if (b) is abnormal and (c) is abnormal and low grade dysplasia is present, then treating said subject with increased surveillance for progression from Barrett's esophagus to high grade dysplasia or esophageal adenocarcinoma, step (d) includes histological examination of the sample, and scoring one of the presence and absence of low grade dysplasia using a Vienna scale, the assay device includes the biomarker panel including a material, which binds to and has affinity for AOL, and the determining if staining said sample with biotinylated Aspergillus oryzae lectin (AOL) produces an abnormal stain based on determination of a staining score includes: staining a plurality of components, the plurality of components includes apical membrane, pan membranous, epithelial mucous globules and epithelial cytoplasm; determining a level of staining by the AOL, for each component, by: (a) grading the intensity of the stain and the percentage of the area stained at said intensity, and (b) producing, based on the level of the staining for each component, an H score; and comparing for each component, of the plurality of components, to determine if the H score is abnormal, the comparing including: the H score considered abnormal if highest score for apical membrane, epithelial mucous globules or epithelial cytoplasm was 4-12, or pan membranous was >0; based on the comparing, dichotomizing each of the components of the staining score into one of normal and abnormal; summing, the results of the dichotomizing, to provide an overall abnormal score for the components; and comparing the overall abnormal score to a reference to determine if the stained sample is abnormal.
7. The method according to claim 1, wherein the oesophagal sample is provided on a glass slide.
8. The method according to claim 3, wherein the oesophagal sample is provided on a glass slide.
9. The method according to claim 6, wherein the oesophagal sample is provided on a glass slide.
10. The method according to claim 1, wherein the biomarker panel includes a polypeptide marker.
Description
BRIEF DESCRIPTION OF THE FIGURES
(1)
(2)
(3) The invention is now described by way of example. These examples are intended to be illustrative, and are not intended to limit the appended claims.
EXAMPLES
Summary of the Examples
(4) Methods: A nested case control study within the population-based Northern Ireland BE Register, (1993-2005). Cases (n=89) who progressed to EAC or HGD ≥6 months following diagnosis of BE were matched to non-progressor controls (n=291) for age/sex and year of BE diagnosis. Established (abnormal DNA content, p53 and cyclin A expression) and novel biomarkers (sialyl Lewis A and CD-15 expression, Aspergillus oryzae lectin (AOL) binding and Wheat germ agglutinin (WGA) lectin binding were assessed in paraffin embedded tissue from first BE diagnosis. Conditional logistic regression analysis was applied to investigate risk of progression.
(5) Results: After a mean 6.7 (±3.2) years of follow-up, dysplasia and 7 biomarkers contributed to the risk of EAC/HGD in a multivariable analysis. Using a backward selection technique, a panel comprising low grade dysplasia and 2 biomarkers (abnormal DNA ploidy and AOL) was optimal for distinguishing progressors and non-progressors. When combined into a risk score for dysplastic (0-3) or non-dysplastic BE (0-2), the adjusted OR for progression was 3.74 (95% CI 2.43-5.79) and 2.99 (95% CI 1.72-5.20) for each point increase, respectively.
(6) Conclusion: A panel of 3 biomarkers (sometimes discussed as 2 molecular biomarkers (DNA/AOL) plus dysplasia) can distinguish both dysplastic and non-dysplastic BE patients at higher risk for future development of EAC and HGD.
Example 1: Identification of Biomarker Panel
(7) Using the population based Northern Ireland Barrett's Oesophagus Register (NIBR), we constructed a nested case-control study to investigate a panel of established and novel biomarkers on routinely collected paraffin embedded samples. One aim of this study was to determine whether dysplasia, DNA copy number, p53, cyclin A and the more recently described glycan targets (CA19-9, CD-15, WGA, AOL), were predictive of future progression to EAC from BE. Another aim was to create a biomarker panel which could be used as a quantitative risk stratification tool.
(8) The methods arising from this study will be useful in a future phase 4 study.
(9) Study Design
(10) A nested case-control study was conducted within the Northern Ireland Barrett's Oesophagus Registry (NIBR), (20-22). The NIBR is a population-based register of all 9,329 adults diagnosed with columnar-lined oesophagus between 1993 and 2005 throughout Northern Ireland. Within the NIBR, 4,306 patients with a visible columnar lined segment displayed Specialized Intestinal Metaplasia (SIM) on biopsy and, for the purposes of this study, this definition was used for diagnosis of BE. Cases were BE patients from the NIBR who developed EAC, gastric cardia malignancies or HGD at least 6 months after their initial BE diagnosis. Cancer outcomes were identified by matching the NIBR to the Northern Ireland Cancer Registry database of oesophageal and gastric malignancies diagnosed up to 31 Dec. 2005. Gastric cardia cancers arising in BE patients were considered to be cases, as these are likely to be categorised as EAC cases under TNM7 HGD outcomes were identified as 2 separate clinical diagnoses within 12 months or 3 separate diagnoses of HGD regardless of time period. Each case was matched to up to 5 controls who were BE patients who had not developed EAC or HGD by the study censor date of 31 Dec. 2005, based on age (±5 years), sex and year of BE diagnosis. Ethical approval was granted by the regional ethics committee in Northern Ireland (REC No 07/NIR02/109).
(11) Histopathology Review
(12) All index and outcome biopsies were reviewed blindly by two independent expert gastrointestinal pathologists (MN & DM), and scored using the Vienna scale (23). Complete agreement was achieved in 84% of samples scored, with discrepancies resolved by discussion and a re-evaluation of the slide where necessary. Cases and controls were excluded if they did not have an index BE biopsy available for review taken ≥6 months prior to their HGD or cancer diagnosis. Any index BE samples that were scored by pathologists as having either no evidence of SIM or evidence of HGD and EAC (Vienna score of 4-5) at the outset of the study were excluded from the study. The histological diagnosis of the outcome biopsy was confirmed by both pathologists in 88% of EAC, 100% of gastric cardia and 83% of HGD outcome biopsies. Reasons for outcome biopsies not being histologically verified included no biopsy available or no HGD or EAC present in the tissue section cut from the outcome biopsy.
(13) Image Cytometry DNA Analysis
(14) One 40 μm section was cut from FFPE tissue and nuclear monolayers were prepared as previously described (24). The monolayer was then acid hydrolysed and stained with Feulgen-Schiff reagent using standardized methodology (13). All slides were given unique code identifiers and studied using an automated image cytometric analyser (Room 4, East Sussex, UK) that consists of a microscope (Axioplan 2, Zeiss, Jena, Germany), a 546-nm green filter, and a black-and-white, high-resolution digital camera (AxioCam MRm, Zeiss, Jena, Germany). Optical density and nuclear area were measured and integrated optical density of each nucleus was calculated as previously described (25). A histogram representing the DNA content was produced and analysed according to European Society for Analytical Cellular Pathology (ESACP) guidelines (26). DNA Ploidy-related parameters such as DNA index (DI) and percentages of cells exceeding 5c (5c ER) and 9c (9c ER) were also noted. All histograms were reported blindly by two of three independent observers (JD, DO and MN). Consensus was reached in all cases.
(15) Immunohistochemistry
(16) Immunohistochemistry was performed for p53 (1/50 dilution, retrieval H1 30 min, DO7, Leica, Milton Keynes), Cyclin A (1/50 dilution, retrieval H1 10 min, Leica), Sialyl Lewis a (BOND ready, retrieval H1 20 min, Leica) and CD15 (BOND ready, retrieval H2 20 min, Leica) on 4 μm section using the BOND autostainer (Leica, Milton Keynes, UK) following manufacturer instructions. Stained sections were then counterstained with a light haematoxylin stain.
(17) Histochemistry
(18) Slides were de-paraffinised according to standard procedures, placed in a humidified incubation chamber and 5 μg/mL of lectin (WGA or AOL) applied, followed by incubation at 37° C. for 15 minutes. WGA was obtained as Biotinylated wheat germ from Vector labs Catalog number V0428. AOL was prepared using AOL purchased from Tokyo Chemical Industry UK Ltd L0169, which was labelled with biotin using ProtOn labelling kit PLK-1202. The un-bound lectin was washed off by immersion in running water (2×30 mins), and mounted with Prolong Gold antifade reagent with DAPI (Invitrogen, Paisley, UK). The lectin-stained slides were scanned using Applied Imaging Ariol® (Genetex Ltd, Hampshire, UK).
(19) p53 was stained with Leica Novocastra antibody clone D07.
(20) CD15 was stained with Leica Novocastra antibody Carb-1 PA0039.
(21) CA19-9 (SL.sup.a or sLe.sup.a) was stained with Leica Novocastra antibody 241:5:1:4 PA0424.
(22) Cyclin A was stained with Leica Novocastra antibody clone 6E6.
(23) Scoring of Histo- and Immunohistochemistry
(24) p53 was scored as significant or non-significant. Strong, dark staining or total absent of staining next to normal background stain were significant. The percentage of cyclin A positive compared to negative epithelial surface cells was calculated. A cut off of 1% was used for significance.
(25) Slides stained for CD15, SL.sup.a, AOL and WGA were graded for intensity (0-3) and for the % of the area stained at this intensity (0-4). The H score (0-12), derived by multiplying intensity and area scores was calculated (0-12) (27) and provides more accurate scoring compared to either the intensity or area score alone. Four epithelial compartments were assessed: the apical epithelial membrane (apical part of the epithelial cell membrane which is exposed to the oesophageal lumen); pan membranous, epithelial mucous globule (globular collections of staining within the cytoplasm) and epithelial cytoplasm).
(26) Statistical Analysis
(27) Baseline characteristics between cases and controls were compared using independent t-tests for continuous variables and chi-squared tests for categorical variables. Conditional logistic regression was conducted to estimate odds ratios for neoplastic progression and corresponding 95% confidence intervals for each biomarker investigated. In analyses where a case failed to be assigned a biomarker score, both the case and its corresponding controls were excluded from that analysis. Multivariate analysis was adjusted for age, sex, year of BE diagnosis, and the presence of dysplasia (as scored by two expert pathologists).
(28) The True Positive Rate (TPR) or sensitivity and False Positive Rate (FPR) or 1-specificity of biomarkers, were calculated by dividing the number of cases and controls, scored as abnormal by the total number of cases and controls scored for that biomarker. Positive Predictive Value (PPV) and Negative Predictive Value (NPV) for the entire cohort of individuals with BE were estimated from the nested case-control design, based upon the prevalence of cancer and HGD outcomes amongst the SIM positive patients at index Barrett's oesophagus diagnosis from the entire 1993-2005 population-based NIBR cohort (28).
(29) Logistic regression was used to combine the seven biomarkers along with dysplasia, year of BE, age and sex into a risk score. Each biomarker score was dichotomised into abnormal or normal. For DNA copy number, p53 and cyclin A this was on the basis of a priori knowledge (for example for DNA copy number diploid normal, tetraploidy or aneuploidy abnormal). For CA 19-9, WGA, AOL and CD-15, each of the four components of the staining score were dichotomised into normal/abnormal based on the most frequent median distribution amongst controls and then summed to give an overall abnormal score of 0-4 for each biomarker.
(30) To evaluate the performance of models, predicted probabilities were used to calculate the area under the receiver operating characteristic (ROC) curves (the c statistic) and to calculate the discrimination slope (the difference in mean predicted probability in the cases compared with the controls) (29). The performance of a clinical model (containing only dysplasia, year of BE, age and sex) was compared with the performance of a biomarker model containing all seven biomarkers (along with dysplasia year of BE, age and sex) using the c statistic and integrated discrimination improvement (IDI) (30). The IDI measures how much the biomarker model leads to increased estimated risks of cancer (or HGD) for cases and decreased estimated risks for controls, compared with the clinical model without biomarkers. Internal validation was conducted on the c statistics using bootstrap methods. Specifically, the model was estimated in a bootstrap sample and the c statistics was calculated in the bootstrap sample and in the original sample. This process was repeated 200 times and the average difference in performance in the bootstrap sample and in the original sample was calculated (the optimism) and subtracted from the apparent performance to estimate the internally validated performance (31).
(31) A reduced model was selected using the stepwise backward selection procedure (using a cut off of 0.5), retaining age, year of BE and sex in the model. The internally validated c statistic for this model was calculated as described previously but after applying the stepwise selection procedure to each bootstrap sample. Validation of the model was conducted using logistic regression, rather than conditional logistic regression, for simplicity, but estimates from the logistic and conditional logistic models were similar (results not shown). Additional stratified analyses were repeated removing individuals without dysplasia at index biopsy.
(32) Patient Demographics
(33) After a mean (SD) follow-up period of 6.7 (3.3) years, 56 EAC, 13 gastric cardia cancers and 25 HGD cases were diagnosed within the study cohort. After review by two expert pathologists, five cases (2 EAC, 1 gastric cardia cancer and 2 HGD cases) were found to have evidence of HGD or EAC at their initial BE diagnosis and were therefore excluded from analysis, leaving 89 cases. Table 1 shows the characteristics of these 89 cases and their 291 matched controls. Cases and controls did not differ by matching criteria (age, sex and year of BE diagnosis), nor laboratory of origin or length of BE segment, although the latter was unknown for approximately half of participants. Significantly more cases were diagnosed as having indefinite or low grade dysplasia at their first BE diagnosis compared with controls, (20.2% versus 2.4% respectively), (p<0.001).
(34) Conclusions
(35) This population based phase 3 biomarker study has revealed a new combination panel for assessment of risk to progression from both dysplastic and non-dysplastic BE to EAC. The combination panel of 7 biomarkers represents a significant step to individualise patient risk and is advantageous due to the use of relatively simple techniques that can be carried out on formalin fixed tissue. Furthermore analysis of a simplified 3 biomarker panel model showed a significant stepwise increase risk of progression for AOL, DNA content abnormalities and presence of LGD.
(36) This work was strengthened by the study design, using a well described cohort with long term follow up and in which all biomarker analysis was undertaken blinded to the outcome. The NIBR is a valuable population based resource, with over 4,000 adults diagnosed with visible columnar-lined oesophagus and SIM within Northern Ireland (population 1.8 million). The 89 cases of progression to HGD/EAC from BE represent a substantially larger number of endpoints than previous longitudinal studies of biomarkers in BE from other centres (32, 33). The majority of these patients were Caucasian middle aged males, which is concordant with previous epidemiological studies of BE. Importantly samples were collected as part of routine clinical care and hence are applicable to everyday practice. A weakness of this study is that limited biopsies were available for analysis and hence it was not possible to achieve data for all of the biomarkers in every patient.
(37) Of the validated biomarkers, DNA content abnormalities measured by image cytometry were most predictive of HGD/cancer progression (OR=3.22; 95% CI 1.73-6.00; P<0.001). DNA ploidy abnormalities have been evaluated in prospective trials of patients with BE, representing phase 4 biomarker development (10, 11, 34). A landmark study by the Reid group demonstrated that patients who had both HGD and aneuploidy or tetraploidy had a five year cancer risk of 66%, compared to 42% with HGD alone and 28% with DNA ploidy abnormalities alone. Patients who had no cytometric abnormality (DNA diploid) and did not have HGD had a five year cancer risk of zero. [Reid et al., 2000b] The same group went on to evaluate the role of a chromosomal instability panel, combining 9pLOH, 17pLOH and DNA ploidy abnormalities. [30] The combination of all three was a better predictor of progression to EAC than any one biomarker alone (RR=38.7; 95% CI=10.8-138.5; p<0.001). These markers are not used in most centres however, as they require a combination of platforms that would be difficult to perform outside of specialist research centres. DNA content flow cytometry particularly is associated with inter laboratory variability, quality control issues and significant set up and running costs (35). The use of image cytometry rather than flow cytometry in this study therefore represents an advance as image cytometry is cheaper, easier to set up and has potential for automation. Although new single platform techniques to measure chromosomal instability, such as SNP and gene chip arrays (36), are being developed that may provide rapid throughput of FFPE material, the accuracy and cost implications for surveillance programmes remains unclear.
(38) Of the novel biomarkers involved in glycan expression, CA19-9 and the lectin AOL were significant predictors of cancer development, although only AOL was included as a significant independent biomarker of neoplastic progression in the final reduced model. Both CA19-9 and AOL have previously been shown to be upregulated in the progression from metaplasia through dysplasia to cancer in Phase 2 studies (19, 37). AOL can be readily assessed following lectin histochemistry which is cheaper and simpler to perform than immunohistochemistry and ploidy techniques. However, AOL is also overexpressed in almost a quarter of BE controls who did not progress, thus limiting its specificity. Nevertheless, the intriguing possibility also exists that it may be possible to evaluate AOL positive areas endoscopically, as previously demonstrated for WGA lectin (19).
(39) The strongest predictor of cancer progression was the presence of LGD by 2 expert GI pathologists (OR=11.33; 95% CI 3.97-32.36; p<0.01), although the overall presence in the cohort when assessed >5 years prior to progression was small (2.8%). In terms of the level of agreement between pathologists, 84% (21/25 patients) of LGD were scored by both specialist GI pathologists on first review, with consensus agreement of all 25 samples upon discussion/re-review. This is comparable with the Dutch consensus study (38) and more favourable than the study by Wani et al. (39).
(40) The difficulty in grading LGD and the uncertainty of the risk of cancer in these patients (38, 39) has led to great debate about the advantages and disadvantages of treating LGD, particularly with the advent of minimally invasive endoscopic therapies (40, 41). The complexity of the issue is illustrated by the contrasting conclusions of two recent studies. In a Dutch study biopsies from 147 patients with LGD diagnosed by local hospital pathologists were reviewed by two expert GI pathologists. The initial diagnosis of LGD by the community pathologist was confirmed by one of the specialist GI pathologists in only 15% of patients (22/147), and the incidence rate of HGD or EAC in this consensus group was high at 13.4% (95% CI 3.5-23.2) per annum. In contrast, a study performed in the USA concluded that the risk of progression to HGD and EAC was no different from non-dysplastic BE even when consensus was reached. There are methodological differences which may affect these data, but overall it highlights the clinical challenges in the diagnosis of LGD. The possibility of utilising DNA ploidy and AOL analysis to more objectively determine the LGD patients at highest risk of progression requiring intensive surveillance or intervention is therefore appealing.
(41) Abnormal cyclin A and p53 expression measured by IHC did not confer a significantly increased risk of HGD/EAC progression in multivariate analysis. The presence of TP53 did however show a significant risk in EAC alone (OR=1.95; 95% CI 1.04-3.67). A previous smaller case-control study from the NIBR of 29 patients who progressed to EAC and 6 patients who progressed to HGD, had shown that TPS3 expression was associated with a higher increased risk of progression (OR=11.7, 95% CI, 1.93-71.4). [41] In a more recent case control study of 54 BE patients, 27 of whom progressed to HGD/EAC and 27 non-progressors, moderate p53 overexpression was also associated with a significantly increased risk of progression with a HR of 6.5 (95% CI, 2.5-17.1) (42). The interpretation of these results is limited by inter laboratory variability of TP53 IHC (43). The gold standard for measurement of p53 mutations is gene sequencing, which is more specific than TP53 IHC, although this is not routinely available and would be technically difficult given the small size and heterogeneity inherent to endoscopic biopsy. p53 expression measured by IHC is a relatively simple technique that is widely available in pathology laboratories, and in our phase 3 study we were able to demonstrate a small but significant risk to cancer progression but this was lost when combined with HGD. The utility of p53, when compared to the other biomarkers in our panel, is therefore likely to be limited. Cyclin A negativity, which has been previously been postulated as a marker of low risk of progression was of borderline significance which dropped out on multivariate analysis. It was interesting that the association with cyclin A was stronger in the ‘EAC only’ outcomes though, suggesting it may be more useful at identifying patients in the later stages of progression from HGD to cancer.
(42) We have demonstrated that the combination of multiple biomarkers confer a higher risk of progression than any one biomarker alone. Using the combination panel, 67% of cases had 2-4 abnormal markers on the index biopsies. In other words, although the presence of a positive biomarker panel confers a greater risk of progression to HGD/EAC in this study, a third of patients without these abnormalities could still progress. This may be explained by sampling error, both from biopsy at endoscopy and when cutting additional sections from archival FFPE tissue blocks. There may also be a temporal effect if the biopsies at baseline were taken too early before the onset of cancer. When we evaluated the risk of progression in HGD/EAC diagnosed within or after the median time to progression of 3.6 years, there was a trend for AOL to be a better marker of later progression than DNA copy number or LGD. Importantly, on adjusted analysis none of the tests for interaction between markers and follow-up time were significant, as the numbers involved were too small for meaningful analysis. Caution must therefore be exercised in the interpretation of a negative biomarker panel and a reduction of the frequency of endoscopic surveillance on the basis of our panel could not be recommended until these markers are investigated in future Phase 4/5 studies.
(43) With the introduction of minimally invasive endoscopic therapy for the ablation of BE, there is an increasing need to risk stratify patients accurately, as treatment may be offered at an earlier stage. The biomarker panel described here therefore has practical clinical implications and further provides a useful algorithm for risk stratification—
(44) i. No dysplasia and panel negative Risk unknown. Continue current surveillance interval.
(45) ii. No dysplasia and panel positive
(46) Moderate-High risk according to panel. Increase surveillance and consider minimally invasive therapy if >2 positive.
(47) iii. Consensus LGD/IND+any one biomarker positive
(48) High risk. Consider minimally invasive therapy.
(49) The combination of dysplasia scoring, DNA ploidy status and AOL may provide significant economic savings as the LGD group, which currently equates to an annual surveillance interval according to AGA guidelines, may be more accurately stratified by biomarkers into a moderate risk group with standard surveillance and higher risk group for ablation. This strategy would benefit from being evaluated in a phase V biomarker study before uptake into routine clinical practice.
(50) In conclusion this study has demonstrated that a 7 biomarker panel is a clinically applicable and useful tool for risk stratification in BE. Our results further demonstrate that a reduced panel of 3 biomarkers is advantageous over a clinical model using pathological dysplasia diagnosis, age and sex alone in identifying BE patients at risk of developing HGD/EAC. Our results are consistent with previous longitudinal studies of single biomarkers, including TP53 abnormalities and DNA content abnormalities. That our panel can be undertaken on paraffin embedded tissue and was undertaken on clinical rather than research samples increase its wider application. This panel could be applied to biopsies of BE at diagnosis, has the potential to guide surveillance and therapeutic intervention with expected public health and financial benefit.
Example 2
(51)
(52) In one embodiment the finding of (no dysplasia, but AOL OR aneuploidy positive) could lead to recommendation to have slightly more frequent surveillance e.g. annual rather than 2-3 yearly. However it must be noted that surveillance intervals are being lengthened in general in most current guidelines to 3-5 years for low risk.
(53) TABLE-US-00005 TABLE 1 Characteristics of cases and matched controls Cases Controls Characteristic n = 89 (%) n = 291 (%) p-value Gender Male 67 (75.3) 218 (74.9) 0.94 Female 22 (24.7) 73 (25.1) Age at BE diagnosis (mean ± SD, years) 63.8 ± 11.9 63.8 ± 11.3 0.99 Length BE segment Long 43 (48.3) 141 (48.45) 0.59 Short 1 (1.1) 9 (3.1) Unknown 45 (50.6) 141 (48.45) Laboratory of origin Altnagelvin 21 (23.6) 46 (15.8) 0.27 Antrim 19 (21.3) 79 (27.1) Belfast City 11 (12.3) 52 (17.9) Craigavon 7 (7.9) 16 (5.5) Royal Victoria 31 (34.8) 98 (33.7) Vienna score of index BE* 1 71 (79.8) 284 (97.6) <0.001 2-3 18 (20.2) 7 (2.4) *Vienna score 1: intestinal metaplasia; 2-3: indefinite or low grade dysplasia, as scored by two expert gastrointestinal pathologists.
(54) TABLE-US-00006 TABLE 2 Adjusted risk of progressing from BE according to markers in the initial oesophageal biopsies Cancer + HGD Cancer only Cases Controls TPR FPR Estimated Estimated Adjusted Adjusted Marker N n (95% CI) (95% CI) PPV NPV OR (95% CI) OR (95% CI) ‘Standard’ Dysplasia None 56 262 0.31 0.08 0.08 0.98 1.00 1.00 Indefinite/LGD 25 22 (0.21- (0.05- 22.69 (6.47- 24.86 (5.57- Unknown 8 7 0.42) 0.12) 79.53) 111.04) p for trend 7.30 (2.06- 6.03 (1.47- 25.81) 24.79) 0.001 0.007 ‘Expert’ Dysplasia None 71 284 0.20 0.02 0.15 0.98 1.00 1.00 Indefinite/LGD 18 7 (0.13- (0.01- 11.78 (4.31- 13.22 (3.67- p for trend 0.30) 0.05) 32.18) 47.59) <0.001 <0.001 DNA copy number Diploid 44 201 0.44 0.15 0.06 0.99 1.00 1.00 Abnormal.sup.a 34 35 (0.33- (0.11- 3.22 (1.73- 3.03 (1.57-5.83) p for trend 0.55) 0.21) 6.00) 0.001 <0.001 Cyclin A Negative/Low % 59 205 0.25 0.16 0.03 0.98 1.00 1.00 positive.sup.b 20 39 (0.16- (0.12- 1.32 (0.66- 1.73 (0.81-3.69) Positive 0.37) 0.21) 2.66) 0.16 p for trend 0.43 p53 0 (None) 18 83 1.00 1.00 1 (Focal) 25 103 1.02 (0.48- 0.87 (0.39-1.91) 2 (Diffuse) 20 62 2.16) 1.21 (0.50-2.94) 3 (intense) 15 30 1.39 (0.63- 3.61 (1.39-9.37) p for trend 3.09) 0.02 2-3 v. 0-1 0.45 0.33 0.03 0.98 2.12 (0.87- 1.95 (1.04-3.67) (0.34- (0.28- 5.16) 0.57) 0.39) 0.08 1.60 (0.91- 2.82) CA19-9 Lectin.sup.c 0-1 scores 33 151 1.00 1.00 abnormal 34 91 1.44 (0.81- 1.38 (0.75-2.54) 2-3 scores 18 29 2.58) 2.49 (0.98-6.31) abnormal 3.32 (1.48- 0.05 4 scores abnormal.sup.d 0.61 0.44 0.03 0.99 7.43) 1.56 (0.88-2.76) p for trend (0.50- (0.38- 0.004 2-4 v. 0-1 0.71) 0.50) 1.77 (1.04- 3.00) WGA.sup.c 0-1 scores 15 63 1.00 1.00 abnormal 61 189 1.43 (0.68- 1.54 (0.70-3.36) 2-3 scores 2 1 3.01) / abnormal 9.33 (0.69- 0.36 4 scores abnormal.sup.e 0.81 0.75 0.02 0.99 126.21) 1.53 (0.70-3.34) p for trend (0.70- (0.69- 0.11 2-4 v. 0-1 0.88) 0.80) 1.46 (0.69- 3.06) CD-15.sup.c 0-1 scores 63 186 1.00 1.00 abnormal 14 63 0.50 (0.24- 0.52 (0.24-1.16) 2-3 scores 9 15 1.03) 1.37 (0.48-3.92) abnormal 1.84 (0.69- 0.92 4 scores abnormal.sup.e 0.27 0.30 0.02 0.98 4.90) 0.70 (0.36-1.36) p for trend (0.18- (0.24- 0.77 2-4 v. 0-1 0.38) 0.36) 0.74 (0.41- 1.33) AOL.sup.c 0-1 scores 42 177 1.00 1.00 abnormal 39 61 3.17 (1.74- 3.38 (1.74-6.55) 2-3 scores 0 2 5.77) / abnormal / 0.001 4 scores abnormal.sup.e 0.48 0.26 0.04 0.99 0.002 3.38 (1.74-6.55) p for trend (0.37- (0.21- 3.10 (1.71- 2-4 v. 0-1 0.59) 0.32) 5.63) Legend for Table 2: TPR: True Positive Rate, equivalent to sensitivity. FPR: False Positive Rate, equivalent to 1-specificity. PPV: Positive Predictive Value. NPV: Negative Predictive Value. TPR, FPR, PPV and NPV refer to analysis of cancer and HGD cases. Adjustments: age, gender, year BE diagnosis. All other biomarkers were further adjusted for dysplasia. .sup.aAbnormal includes aneuploid, tetraploid, aneuploid & tetraploid and hypodiploid .sup.bLow % positive defined as <1% positive. .sup.cCA19-9, WGA, CD-15 and AOL all had four components of tissue staining assessed: apical membrane, pan membranous, epithelial mucous globules and epithelial cytoplasm. .sup.dBiomarker scores considered abnormal if highest score for apical membrane, epithelial mucous globules or epithelial cytoplasm was 0-<4, or pan membranous was 0. .sup.eBiomarker scores considered abnormal if highest score for apical membrane, epithelial mucous globules or epithelial cytoplasm was 4-12, or pan membranous was >0.
(55) TABLE-US-00007 TABLE 3 Adjusted risk of progressing from BE according to markers in the initial oesophageal biopsies Individuals without dysplasia at Cancer outcomes only Full sample (51 cases, 118 controls) initial biopsy (39 cases, 87 controls) (36 cases, 85 controls) Con- Full model* Con- Full model* Con- Full model* Cases trols adjusted OR Cases trols adjusted OR Cases trols adjusted OR Variable (%) (%) (95% CI) (%) (%) (95% CI) (%) (%) (95% CI) Dysplasia 10 (20%) 5 (4%) 2.57 (0.62, 10.72) 8 (22%) 3 (4%) 6.28 (1.08, 36.49) DNA copy 25 (49%) 18 (15%) 4.93 (2.09, 11.61) 15 (38%) 13 (15%) 4.46 (1.69, 11.71) 16 (44%) 14 (16%) 3.91 (1.35, 11.31) number abnormal Cyclin A 12 (24%) 24 (20%) 1.29 (0.48, 3.47) 7 (18%) 22 (25%) 0.81 (0.28, 2.37) 8 (22%) 17 (20%) 1.00 (0.30, 3.45) abnormal P53 21 (41%) 33 (28%) 1.61 (0.72, 3.60) 14 (36%) 24 (28%) 1.84 (0.74, 4.58) 15 (42%) 17 (20%) 3.54 (1.28, 9.81) abnormal CA199 30 (59%) 58 (49%) 1.28 (0.54, 3.01) 21 (54%) 42 (48%) 1.15 (0.44, 2.95) 19 (53%) 45 (53%) 0.61 (0.22, 1.71) abnormal WGA 41 (80%) 91 (77%) 0.95 (0.37, 2.47) 29 (74%) 66 (76%) 0.75 (0.27, 2.07) 29 (81%) 66 (78%) 0.99 (0.30, 3.30) abnormal CD15 13 (25%) 38 (32%) 0.95 (0.36, 2.49) 11 (29%) 25 (29%) 1.04 (0.37, 2.94) 9 (25%) 27 (32%) 0.63 (0.19, 2.12) abnormal AOL 25 (49%) 24 (20%) 3.78 (1.69, 8.37) 15 (38%) 17 (20%) 2.97 (1.20, 7.35) 16 (44%) 13 (15%) 4.84 (1.67, 14.04) abnormal Model performance c statistic Basic 0.62 (0.53, 0.72) 0.52 (0.41, 0.63) 0.66 (0.54, 0.77) model† Basic model 0.78 (0.71, 0.86) 0.73 (0.64, 0.82) 0.80 (0.72, 0.88) plus all biomarkers shown Internally validated c statistic§ Basic 0.56 (0.47, 0.66) 0.43 (0.32, 0.54) 0.59 (0.47, 0.70) model† Basic model 0.71 (0.64, 0.79) 0.63 (0.53, 0.74) 0.70 (0.62, 0.78) plus all biomarkers shown Discrim- ination slope Basic 0.07 0.00 0.09 model† Basic model 0.22 0.13 0.25 plus all biomarkers shown IDI 0.15 0.13 0.16 *Full model contains age at diagnosis, sex, year of BE and all biomarkers shown. †Basic model contains dysplasia (except in subgroup excluding dysplasia), age at diagnosis, sex and year of BE. §See methods for more details.
(56) TABLE-US-00008 TABLE 4 Adjusted risk of progressing from BE according to markers in the initial oesophageal biopsies model based upon backward selection. Individuals without dysplasia at Cancer outcomes only Full sample (71 cases, 197 controls) initial biopsy (54 cases, 149 controls) (52 cases, 146 controls) Reduced Reduced Reduced Con- model* Con- model* Con- model* Cases trols adjusted OR Cases trols adjusted OR Cases trols adjusted OR Variable (%) (%) (95% CI) (%) (%) (95% CI) (%) (%) (95% CI) Dysplasia 14 (20%) 6 (3%) 4.30 (1.36, 13.65) 10 (19%) 4 (3%) 5.63 (1.43, 22.18) DNA copy 32 (45%) 28 (14%) 3.05 (1.61, 5.82) 19 (34%) 23 (15%) 3.25 (1.55, 6.81) 20 (38%) 23 (16%) 2.73 (1.24, 6.03) number abnormal AOL 32 (45%) 44 (22%) 4.27 (2.16, 8.43) 22 (39%) 32 (21%) 2.78 (1.38, 5.59) 22 (42%) 27 (18%) 3.13 (1.46, 6.72 abnormal Model performance c statistic Basic model† 0.63 (0.54, 0.70) 0.51 (0.42, 0.60) 0.64 (0.55, 0.73) Basic model 0.75 (0.68, 0.81) 0.68 (0.59, 0.77) 0.72 (0.64, 0.81) plus AOL and IC DNA Internally validated c statistic§ Basic model† 0.57 (0.48, 0.64) 0.42 (0.33, 0.51) 0.57 (0.48, 0.66) Basic model 0.69 (0.62, 0.75) 0.57 (0.48, 0.66) 0.68 (0.60, 0.77) plus AOL and IC DNA Discrim- ination slope Basic model† 0.08 0.00 0.09 Basic model 0.18 0.12 0.15 plus AOL and IC DNA IDI 0.10 0.12 0.06 *Reduced model contains age at diagnosis, sex, year of BE, AOL and IC DNA. †Basic model contains (except in subgroup excluding dysplasia), age at diagnosis, sex and year of BE. §See methods for more details.
(57) TABLE-US-00009 TABLE 5 Risk scores of BE individuals scored as abnormal for dysplasia, DNA copy number and AOL. Risk True False score positive positive count Cases Controls Cut off rate rate All BE 0 19 126 ≥0 versus <0 100% 100% 1 35 64 ≥1 versus <1 73% 36% 2 8 7 ≥2 versus <2 24% 4% 3 9 0 ≥3 versus <3 13% 0% OR per point increase *= 3.74 (2.43, 5.79), P < 0.001 Non-dysplastic BE 0 19 98 >0 versus <0 100% 100% 1 33 47 >1 versus <1 66% 34% 2 4 4 >2 versus <2 7% 3% OR per point increase *= 2.99 (1.72, 5.20), P < 0.001 *Adjusted for age, sex and year of BE.
REFERENCES
(58) 1. Vial M, Grande L, Pera M. Epidemiology of adenocarcinoma of the esophagus, gastric cardia, and upper gastric third. Recent Results Cancer Res. 2010; 182:1-17. 2. Kadri S R, Lao-Sirieix P, O'Donovan M, et al. Acceptability and accuracy of a non-endoscopic screening test for Barrett's oesophagus in primary care: cohort study. Bmj. 2010; 341:c4372. 3. Group MRCOCW. Surgical resection with or without preoperative chemotherapy in oesophageal cancer: a randomised controlled trial. Lancet. 2002 May 18; 359(9319):1727-33. 4. Sikkema M, de Jonge P J, Steyerberg E W, et al. Risk of esophageal adenocarcinoma and mortality in patients with Barrett's esophagus: a systematic review and meta-analysis. Clin Gastroenterol Hepatol. 2010 March; 8(3):235-44; quiz e32. 5. Desai T K, Krishnan K, Samala N, et al. The incidence of oesophageal adenocarcinoma in non-dysplastic Barrett's oesophagus: a meta-analysis. Gut. 2011 Oct. 13. 6. Yousef F, Cardwell C, Cantwell M M, et al. The incidence of esophageal cancer and high-grade dysplasia in Barrett's esophagus: a systematic review and meta-analysis. Am J Epidemiol. 2008 Aug. 1; 168(3):237-49. 7. Reid B J, Li X, Galipeau P C, et al. Barrett's oesophagus and oesophageal adenocarcinoma: time for a new synthesis. Nat Rev Cancer. 2010 February; 10(2):87-101. 8. Sullivan Pepe M, Etzioni R, Feng Z, et al. Phases of biomarker development for early detection of cancer. J Natl Cancer Inst. 2001 Jul. 18; 93(14):1054-61. 9. Lao-Sirieix P, Lovat L, Fitzgerald R C. Cyclin A immunocytology as a risk stratificataion tool for Barrett's esophagus surveillance. Clin Cancer Res. 2007; 13(2):659-65. 10. Reid B J, Levine D S, Longton G, et al. Predictors of progression to cancer in Barrett's esophagus: baseline histology and flow cytometry identify low- and high-risk patient subsets. Am J Gastroenterol. 2000 July; 95(7):1669-76. 11. Rabinovitch P S, Longton G, Blount P L, et al. Predictors of progression in Barrett's esophagus III: baseline flow cytometric variables. Am J Gastroenterol. 2001 November; 96(11):3071-83. 12. Dunn J M, Mackenzie G D, Oukrif D, et al. Image cytometry accurately detects DNA ploidy abnormalities and predicts late relapse to high-grade dysplasia and adenocarcinoma in Barrett's oesophagus following photodynamic therapy. Br J Cancer. 2010 May 25; 102(11):1608-17. 13. Chao D L, Sanchez C A, Galipeau P C, et al. Cell Proliferation, Cell Cycle Abnormalities, and Cancer Outcome in Patients with Barrett's Esophagus: A Long-term Prospective Study. Clinical Cancer Research. 2008 Nov. 1, 2008; 14(21):6988-95. 14. Casson A G, Tammemagi M, Eskandarian S, et al. p53 alterations in oesophageal cancer: association with clinicopathological features, risk factors, and survival. Mol Pathol. 1998 April; 51(2):71-9. 15. Ribeiro U, Finkelstein S D, Safatle-Ribeiro A V, et al. p53 sequence analysis predicts treatment response and outcome of patients with esophageal carcinoma. Cancer. 1998:83(1):7-18. 16. Kuroki T, Fujiwara Y, Nakamori S, et al. Evidence for the presence of two tumour-suppressor genes for hepatocellular carcinoma on chromosome 13q. Br J Cancer. 1995 August; 72(2):383-5. 17. Jorgensen T, Berner A, Kaalhus O, et al. Up-regulation of the oligosaccharide sialyl LewisX: a new prognostic parameter in metastatic prostate cancer. Cancer Res. 1995 May 1; 55(9):1817-9. 18. Futamura N, Nakamura S, Tatematsu M, et al. Clinicopathologic significance of sialyl Le(x) expression in advanced gastric carcinoma. Br J Cancer. 2000 December; 83(12):1681-7. 19. Bird-Lieberman E L, Neves A A, Lao-Sirieix P, et al. Molecular imaging using fluorescent lectins permits rapid endoscopic identification of dysplasia in Barrett's esophagus. Nature Med. 2011; In Press. 20. Murray L, Watson P, Johnston B, et al. Risk of adenocarcinoma in Barrett's oesophagus: population based study. Bmj. 2003 Sep. 6:327(7414):534-5. 21. Coleman H, Bhat S, Murray L et al. Increasing incidence of Barrett's oesophagus: a population-based study. European Journal of Epidemiology. 2011; 26(9):739-45. 22. Bhat S, Coleman H G, Yousef F, et al. Risk of malignant progression in Barrett's esophagus patients: results from a large population-based study. J Natl Cancer Inst. 2011 Jul. 6; 103(13):1049-57. 23. Schlemper R J, Riddell R H, Kato Y, et al. The Vienna classification of gastrointestinal epithelial neoplasia. Gut. 2000 Aug. 1, 2000:47(2):251-5. 24. Pretorius M E, Waehre H, Abeler V M, et al. Large scale genomic instability as an additive prognostic marker in early prostate cancer. Cell Oncol. 2009:31(4):251-9. 25. Bondi J, Pretorius M, Bukholm L et al. Large-scale genomic instability in colon adenocarcinomas and correlation with patient outcome. Apmis. 2009 October; 117(10):730-6. 26. Haroske G, Book J P, Danielsen H, et al. Fourth updated ESACP consensus report on diagnostic DNA image cytometry. Anal Cell Pathol. 2001; 23(2):89-95. 27. Cronin J, McAdam E, Danikas A, et al. Epidermal growth factor receptor (EGFR) is overexpressed in high-grade dysplasia and adenocarcinoma of the esophagus and may represent a biomarker of histological progression in Barrett's esophagus (BE). Am J Gastroenterol. 2011 January; 106(1):46-56. 28. Baker S G, Kramer B S, Srivastava S. Markers for early detection of cancer: statistical guidelines for nested case-control studies. BMC Med Res Methodol. 2002; 2:4. 29. Steyerberg E W. Clinical prediction models: A practical approach to development, validation and updating: Springer; 2008. 30. Pencina M J, D'Agostino R B, Sr., D'Agostino R B, Jr., et al. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008 Jan. 30:27(2):157-72; discussion 207-12. 31. Steyerberg E W, Harrell F E, Jr., Borsboom G J, et al. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol. 2001 August; 54(8):774-81. 32. Galipeau P C, Li X, Blount P L, et al. NSAIDs modulate CDKN2A, TP53, and DNA content risk for progression to esophageal adenocarcinoma. PLoS Med. 2007 February; 4(2):e67. 33. Schulmann K, Sterian A, Berki A, et al. Inactivation of p16, RUNX3, and HPP1 occurs early in Barrett's-associated neoplastic progression and predicts progression risk. Oncogene. 2005 Jun. 9; 24(25):4138-48. 34. Reid B J, Prevo L J, Galipeau P C, et al. Predictors of progression in Barrett's esophagus II: baseline 17p (p53) loss of heterozygosity identifies a patient subset at increased risk for neoplastic progression. Am J Gastroenterol. 2001 October; 96(10):2839-48. 35. Reid B J, Blount P L, Rubin C E. et al. Flow-cytometric and histological progression to malignancy in Barrett's esophagus: prospective endoscopic surveillance of a cohort. Gastroenterology. 1992 April; 102(4 Pt 1):1212-9. 36. Paulson T G, Maley C C, Li X, et al. Chromosomal instability and copy number alterations in Barrett's esophagus and esophageal adenocarcinoma. Clin Cancer Res. 2009 May 15:15(10):3305-14. 37. Bird-Lieberman E L, Dunn J M, P. L-S, et al. Phase 2 and phase 3 multicentre studies demonstrate the potential for glycans as predictive biomarkers in Barrett's oesophagus Gut. 2011; 60(Suppl 1):A169-70. 38. Hvid-Jensen F, Pedersen L, Drewes A M, et al. Incidence of Adenocarcinoma among Patients with Barrett's Esophagus. N Engl J Med. 2011 Oct. 13:365(15):1375-83. 39. Wani S, Falk G W, Post J, et al. Risk Factors for Progression of Low-Grade Dysplasia in Patients With Barrett's Esophagus. Gastroenterology. 2011 October; 141 (4):1179-86 el. 40. Bulsiewicz W J, Shaheen N J. The role of radiofrequency ablation in the management of Barrett's esophagus. Gastrointest Endosc Clin N Am. 2011 January; 21 (1):95-109. 41. Spechler S J, Sharma P, Souza R F, et al. American Gastroenterological Association medical position statement on the management of Barrett's esophagus. Gastroenterology. 2011 March; 140(3):1084-91. 42. Sikkema M, de Jonge P J, Steyerberg E W, et al. Risk of Esophageal Adenocarcinoma and Mortality in Patients With Barrett's Esophagus: A Systematic Review and Meta-Analysis. Clin Gastroenterol Hepatol. 2009 Oct. 19. 43. Alsner J, Jensen V, Kyndi M, et al. A comparison between p53 accumulation determined by immunohistochemistry and TP53 mutations as prognostic variables in tumours from breast cancer patients. Acta Oncol. 2008; 47(4):600-7.
(59) All publications mentioned in the above specification are herein incorporated by reference. Various modifications and variations of the described aspects and embodiments of the present invention will be apparent to those skilled in the art without departing from the scope of the present invention. Although the present invention has been described in connection with specific preferred embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention which are apparent to those skilled in the art are intended to be within the scope of the following claims.