{"id":1140,"date":"2015-10-11T09:06:46","date_gmt":"2015-10-11T07:06:46","guid":{"rendered":"https:\/\/www.endoscopy-campus.com\/en\/literatur\/risikostratifizierung-des-barrett-oesophagus-kaisers-neue-kleider\/"},"modified":"2018-05-03T16:42:32","modified_gmt":"2018-05-03T14:42:32","slug":"risikostratifizierung-des-barrett-oesophagus-kaisers-neue-kleider","status":"publish","type":"literatur","link":"https:\/\/www.endoscopy-campus.com\/en\/literature\/risikostratifizierung-des-barrett-oesophagus-kaisers-neue-kleider\/","title":{"rendered":"Risk stratification in Barrett\u2019s esophagus \u2014 the emperor\u2019s new clothes?"},"content":{"rendered":"

Gastroenterology 2015; online (.doi.org\/10.1053\/j.gastro.2015.07.053)<\/span><\/p>\n\n\n\n\n
Analysis of Dysplasia in Patients With Barrett\u2019s Esophagus Based on Expression Pattern of 90 Genes<\/td>\n<\/tr>\n
Sibu Varghese, Richard Newton, Caryn S. Ross-Innes, Pierre Lao-Sirieix, Kausilia K. Krishnadath, Maria O\u2019Donovan, M. Novelli, Lorenz Wernisch, Jacques Bergman, and Rebecca C. Fitzgerald Cambridge, Amsterdam und London<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Background + Aims<\/b><\/h3>\n

Diagnoses of dysplasia, based on histologic analyses, dictate management decisions for patients with Barrett\u2019s esophagus (BE). However, there is much intra- and inter-observer variation in identification of dysplasia\u2014particularly low-grade dysplasia. We aimed to identify a biomarker that could be used to assign patients with low-grade dysplasia to a low- or high-risk group.<\/p>\n

Methods<\/b><\/h3>\n

We performed a stringent histologic assessment of 150 frozen esophageal tissues samples collected from 4 centers in the United Kingdom (from 2000 through 2006). The following samples with homogeneous diagnoses were selected for gene expression profiling: 28 from patients with nondysplastic BE, 10 with low-grade dysplasia, 13 with high-grade dysplasia (HGD), and 8 from patients with esophageal adenocarcinoma. A leave-one-out cross-validation analysis was used identify a gene expression signature associated with HGD vs nondysplastic BE. Functional pathways associated with gene signature sets were identified using the MetaCore analysis. Gene expression signature sets were validated using gene expression data on BE and esophageal adenocarcinoma accessed through National Center for Biotechnology Information Gene Expression Omnibus, as well as a separate set of samples (n = 169) collected from patients who underwent endoscopy in the United Kingdom or the Netherlands and analyzed histologically.<\/p>\n

Results<\/b><\/h3>\n

We identified an expression pattern of 90 genes that could separate nondysplastic BE tissues from those with HGD (P < .0001). Genes in a pathway regulated by retinoic acid_regulated nuclear protein made the largest contribution to this gene set (P < .0001); the transcription factor MYC regulated at least 30% of genes within the signature (P < .0001). In the National Center for Biotechnology Information Gene Expression Omnibus validation set, the signature separated nondysplastic BE samples from esophageal adenocarcinoma samples (p=.0012). In the UK validation cohort, the signature identified dysplastic tissues with an area under the curve value of 0.87 (95% confidence interval: 0.82-0.93). Of samples with low-grade dysplasia (LGD), 64% were considered high risk according to the 90-gene signature; these patients had a higher rate of disease progression than those with a signature categorized as low risk (P = .047).<\/p>\n

Conclusions<\/b><\/h3>\n

We identified an expression pattern of 90 genes in esophageal tissues of patients with BE that was associated with low- or high-risk for disease progression. This pattern might be used in combination with histologic analysis of biopsy samples to stratify patients for treatment. It would be most beneficial for analysis of patients without definitive evidence of HGD but for whom early endoscopic intervention is warranted.<\/p>\n

\n

Gut 2015; online (doi:10.1136\/gutjnl-2015-309642)<\/p>\n\n\n\n\n\n
Derivation of genetic biomarkers for cancer risk stratification in Barrett\u2019s oesophagus: a prospective cohort study<\/td>\n<\/tr>\n
Margriet R Timmer, Pierre Martinez, Chiu T Lau, Wytske M Westra, Silvia Calpe, Agnieszka M Rygiel, Wilda D Rosmolen, Sybren L Meijer, Fiebo J W ten Kate, Marcel G W Dijkgraaf, Rosalie C Mallant-Hent, Anton H J Naber, Arnoud H A M van Oijen, Lubbertus C Baak, Pieter Scholten, Clarisse J M B\u00f6hmer, Paul Fockens, Carlo C Maley, Trevor A Graham, Jacques J G H M Bergman, Kausilia K Krishnadath<\/td>\n<\/tr>\n
Amsterdam, London, Almere, Hilversum, Alkmaar, Hoofdorp und San Francisco<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Objective<\/b><\/h3>\n

The risk of developing adenocarcinoma in non-dysplastic Barrett\u2019s oesophagus is low and difficult to predict. Accurate tools for risk stratification are needed to increase the efficiency of surveillance. We aimed to develop a prediction model for progression using clinical variables and genetic markers.<\/p>\n

Methods<\/b><\/h3>\n

In a prospective cohort of patients with nondysplastic Barrett\u2019s oesophagus, we evaluated six molecular markers: p16, p53, Her-2\/neu, 20q, MYC and aneusomy by DNA fluorescence in situ hybridisation on brush cytology specimens. Primary study outcomes were the development of high-grade dysplasia or oesophageal adenocarcinoma. The most predictive clinical variables and markers were determined using Cox proportional hazards models, receiver operating characteristic curves and a leave-one-out analysis.<\/p>\n

Results<\/b><\/h3>\n

A total of 428 patients participated (345 men; median age 60 years) with a cumulative follow-up of 2019 patient-years (median 45 months per patient). Of these patients, 22 progressed; nine developed high-grade dysplasia and 13 oesophageal adenocarcinoma. The clinical variables, age and circumferential Barrett\u2019s length, and the markers, p16 loss, MYC gain and aneusomy, were significantly associated with progression on univariate analysis. We defined an \u2018Abnormal Marker Count\u2019 that counted abnormalities in p16, MYC and aneusomy, which significantly improved risk prediction beyond using just age and Barrett\u2019s length. In multivariate analysis, these three factors identified a high-risk group with an 8.7-fold (95% CI 2.6 to 29.8) increased HR when compared with the low-risk group, with an area under the curve of 0.76 (95% CI 0.66 to 0.86).<\/p>\n

Conclusions<\/b><\/h3>\n

A prediction model based on age, Barrett\u2019s length and the markers p16, MYC and aneusomy determines progression risk in non-dysplastic Barrett\u2019s oesophagus.<\/p>\n

What you need to know<\/span><\/h2>\n

The efficacy of surveillance for Barrett\u2019s patients is a matter of controversy, and it is probably due to the low long-term risk of carcinoma developing that no randomized studies have been carried out on the topic.<\/strong> The recently published German guidelines state that surveillance is optional for patients with Barrett\u2019s that has been found to be nonneoplastic at the first two endoscopy examinations. This is a change from the earlier guidelines, which still recommended surveillance unreservedly (1, 2)<\/sup>.<\/p>\n

It would therefore be desirable to have some method of risk stratification to distinguish between patients who need surveillance and those who do not.<\/strong> The majority of patients do not develop any neoplasia during the subsequent course. To date, only excess weight and male sex have been identified as risk factors, and even then only with a moderate increase in risk: in comparison with women, men have a two- to threefold increased risk of malignant degeneration in Barrett\u2019s. The role played by age is a matter of controversy, as are the (known) duration of disease and smoking. An increased BMI or, more likely, increased abdominal fat (waist-to-hip ratio) are apparently also risk factors (3)<\/sup>. Smoking, length of the Barrett\u2019s segment, duration of disease, reflux symptoms, and active inflammation are also thought to be associated with an increased risk of malignant progression. Despite this, it is difficult to establish whether only rather obese men who smoke should receive surveillance. Since Barrett\u2019s is usually diagnosed during an endoscopic examination in which biopsies are taken, a method for primary endoscopic stratification would be desirable.<\/p>\n

Risk markers based on genes or gene profiles are available from smaller studies, but none of these has become comprehensively established to date.<\/strong> Only p53 assessment \u2014 although usually in association with the presence of low-grade dysplasias \u2014 has so far been included in any guidelines (the British ones) (4)<\/sup>. For example, assessment of the methylation status of gene promoters and genetic instability might potentially be interesting markers. In the longer term, it might be possible to use this type of marker, even derived from blood samples, to assess a patient\u2019s risk of progression (5)<\/sup>. To date, however, no tests are available for everyday clinical work that would be capable of allowing certain assessment of the course of disease using risk profiles based on markers for genomic instability, tumor suppressor genes, proliferation markers, cell cycle regulators, etc. (6)<\/sup>. Individually adapted patient surveillance and treatment if needed are thus still not possible for primarily nonneoplastic Barrett\u2019s.<\/p>\n

Several papers based on large databases with follow-up data, from the Netherlands and the United Kingdom, have now been published that aim to derive markers of this type from genetic analyses. In each of the groups of patients mentioned, there was a small subgroup who developed neoplasias during the course, although these were usually low-grade dysplasias. These groups have already been reported on in other studies, including those with treatment for low-grade dysplasia (7, 8)<\/sup>; see also Endoscopy Campus, February 2015 (Low-grade dysplasia in Barrett\u2019s esophagus \u2014 a second opinion is important, but then treatment is needed<\/a>).<\/p>\n

A study mainly conducted in Britain, using a small number of histological findings from various stages of Barrett\u2019s neoplasia, identified an expression pattern consisting of 90 genes that was able to distinguish between nondysplastic Barrett\u2019s (n = 10) and high-grade dysplasias (n = 13)<\/strong>. The gene panel was able to recognize dysplastic tissue in another group (n = 169), with higher sensitivity but lower specificity in the individual analyses. In detail, it made it possible to distinguish between nondysplastic Barrett\u2019s and all neoplasias or neoplasia subgroups (high-grade or low-grade dysplasias) with sensitivities of 86%, 92%, and 64%, and a specificity of 63% \u2014 so that it is not yet suitable for everyday use. For the subgroup of patients with low-grade dysplasia (n = 28), 18 were classified after genetic analysis as high-risk, and five as low-risk. An unclear number of these LGD patients and an equally unclear number of patients with nondysplastic Barrett\u2019s were followed up; the total was 42 patients, 22 of whom were high-risk and 20 low-risk. Twenty-three percent of the high-risk patients versus 5% of the low-risk patients showed progression to high-grade dysplasia or carcinoma. In view of the small number of cases, unclear patient selection and unclear endoscopy findings (visible abnormalities?), this is problematic evidence and difficult to generalize. The follow-up period for the five specific patients is unclear from the paper; a table for all patients shows several years, but in the text the follow-up for another small group with risk stratification and unclear dysplasia status is only 12 months (9)<\/sup>.<\/p>\n

Another study from Amsterdam, on brush cytology in Barrett\u2019s patients without dysplasia and with fluorescence in situ hybridization (FISH) analyses, shows how difficult the clinical application of such methods is in everyday work.<\/strong> In a large group of 428 Barrett\u2019s patients, with follow-up (mean 43 months), including only clinical parameters along with the FISH analyses, a hazard ratio of 8.7 for the development of dysplasias was achieved. Tissue parameters from FISH were analyzed in detail. The combined score, which reached a risk of over 8, included age and Barrett\u2019s segment length, as well as the FISH markers p16, MYC, and aneusomy. Taken separately, however, the individual parameters only reached low hazard ratios, i.e.:<\/p>\n\n\n\n\n\n\n\n\n\n
Parameter<\/th>\nHazard Ratio<\/th>\np<\/th>\n<\/tr>\n<\/thead>\n
Age (continuous, per year)<\/td>\n1.06<\/td>\n0.08<\/td>\n<\/tr>\n
Barrett\u2019s length (continuous, per cm)<\/td>\n1.15<\/td>\n0.01<\/td>\n<\/tr>\n
p16 loss, % (continuous)<\/td>\n1.07<\/td>\n0.006<\/td>\n<\/tr>\n
MYC gain (binary, yes\/no)<\/td>\n1.01<\/td>\n0.048<\/td>\n<\/tr>\n
Aneusomy (%, continuous)<\/td>\n1.23<\/td>\n0.008<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

The study is certainly very laudable, particularly in view of the large number of cases and the relatively long and careful follow-up. Despite that, the everyday usability of the continuous variables is of course only limited at present (a very long Barrett\u2019s segment with a high value for p16 loss and aneusomy has a high risk level, of course, but what about all the moderate values?). You always want a cut-off value here, but the risk is unfortunately not black and white. In addition, there is of course no independent group in whom the values could be tested, and of the 428 evaluable patients (a total of 674 were initially included), only 22 developed high-grade dysplasia or carcinoma during the follow-up period (10)<\/sup>. This is much higher (1.3% per year), however, than otherwise seen in large population-based studies such as the one in Denmark with 11,028 Barrett\u2019s patients (0.12% per year) (11)<\/sup>.<\/p>\n

Despite all the interesting results from the studies described above, we are therefore still awaiting a simple way of distinguishing between \u201cgood and bad Barrett\u2019s\u201d for everyday purposes.<\/strong> However, the studies mentioned, with all their merits and limitations, show how difficult and demanding \u2014 and in addition, methodologically challenging as well \u2014 the analysis and evaluation of the data is. The first study in particular, however, also shows that despite all the admirable laboratory effort and commitment put in, one should always pay attention to the quality of the clinical basis: the case numbers are sometimes quite small and the selection bias unclear.<\/p>\n

 <\/p>\n

References<\/span><\/h2>\n
    \n
  1. www.dgvs.de\/fileadmin\/user_upload\/Leitlinien\/Refluxkrankheit\/DGVS_Empfehlung_fuer_Refluxkrankheit.pdf<\/a><\/li>\n
  2. Koop H, Fuchs KH, Labenz J, Lynen Jansen P, Messmann H, Miehlke S, Schepp W, Wenzl TG; Mitarbeiter der Leitliniengruppe. S2k guideline: gastroesophageal reflux disease guided by the German Society of Gastroenterology: AWMF register no. 021-013 Z Gastroenterol. 2014 Nov;52(11):1299-346.<\/li>\n
  3. Koop H, Schepp W, M\u00fcller-Lissner S, Madisch A, Micklefield G, Messmann H, Fuchs KH, Hotz J. Consen-sus conference of the DGVS on gastroesophageal reflux Z Gastroenterol. 2005 Feb;43(2):163-4.<\/li>\n
  4. de Jonge PJ, van Blankenstein M, Grady WM, Kuipers EJ. Barrett’s oesophagus: epidemiology, cancer risk and implications for management. Gut. 2014 Jan;63(1):191-202.<\/li>\n
  5. Fitzgerald RC, di Pietro M, Ragunath K, Ang Y, Kang JY, Watson P, Trudgill N, Patel P, Kaye PV, Sanders S, O’Donovan M, Bird-Lieberman E, Bhandari P, Jankowski JA, Attwood S, Parsons SL, Loft D, Lagergren J, Moayyedi P, Lyratzopoulos G, de Caestecker J; British Society of Gastroenterology. British Society of Gastroenterology guidelines on the diagnosis and management of Barrett’s oesophagus. Gut. 2014 Jan;63(1):7-42.<\/li>\n
  6. Zeki S, Fitzgerald RC. The use of molecular markers in predicting dysplasia and guiding treatment. Best Pract Res Clin Gastroenterol. 2015 Feb;29(1):113-24.<\/li>\n
  7. Timmer MR, Sun G, Gorospe EC, Leggett CL, Lutzke L, Krishnadath KK, Wang KK. Predictive biomarkers for Barrett’s esophagus: so near and yet so far. Dis Esophagus. 2013 Aug;26(6):574-81.<\/li>\n
  8. Duits LC, Phoa KN, Curvers WL, Ten Kate FJ, Meijer GA, Seldenrijk CA, Offerhaus GJ, Visser M, Meijer SL, Krishnadath KK, Tijssen JG, Mallant-Hent RC, Bergman JJ. Barrett’s oesophagus patients with low-grade dysplasia can be accurately risk-stratified after histological review by an expert pathology panel. Gut. 2015 May;64(5):700-6.<\/li>\n
  9. Phoa KN, van Vilsteren FG, Weusten BL, Bisschops R, Schoon EJ, Ragunath K, Fullarton G, Di Pietro M, Ravi N, Visser M, Offerhaus GJ, Seldenrijk CA, Meijer SL, ten Kate FJ, Tijssen JG, Bergman JJ. Radiofre-quency ablation vs endoscopic surveillance for patients with Barrett esophagus and low-grade dysplasi-a: a randomized clinical trial. JAMA. 2014 Mar 26;311(12):1209-17.<\/li>\n
  10. Varghese S, Newton R, Ross-Innes CS, Lao-Sirieix P, Krishnadath KK, O’Donovan M, Novelli M, Wernisch L, Bergman J, Fitzgerald RC. Analysis of Dysplasia in Patients With Barrett’s Esophagus Based on Expres-sion Pattern of 90 Genes. Gastroenterology. 2015 Aug 3. pii: S0016-5085(15)01085-9.<\/li>\n
  11. Timmer MR, Martinez P, Lau CT, Westra WM, Calpe S, Rygiel AM, Rosmolen WD, Meijer SL, Ten Kate FJ, Dijkgraaf MG, Mallant-Hent RC, Naber AH, van Oijen AH, Baak LC, Scholten P, B\u00f6hmer CJ, Fockens P, Ma-ley CC, Graham TA, Bergman JJ, Krishnadath KK. Derivation of genetic biomarkers for cancer risk stratifi-cation in Barrett’s oesophagus: a prospective cohort study. Gut. 2015 Jun 23. pii: gutjnl-2015-309642.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

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