1. National Health and Medical Research Council Clinical Trials Centre, University of Sydney, New South Wales.
2. School of Medicine, The University of Queensland, Queensland.
3. Cancer Imaging Department, Peter MacCallum Cancer Institute, Victoria.
There is global recognition that there is an increasing need to generate predictive and prognostic biomarkers in various malignancies. Personalised medicine is progressing in certain streams of medical oncology yet remains an elusive goal in oesophagogastric cancer. This article reviews the role of F-18 flurodeoxyglucose PET and various molecular methodologies in exploring potential biomarkers in the management of oesophageal and gastro-oesophageal cancers.
Biomarkers are defined as objectively measurable parameters that predict a biological state or behaviour, such as response to treatment. A prognostic biomarker is a term used to describe the likely course of disease in any one individual. This historically meant an individual who had not been treated before but this definition is increasingly complicated by the use of post-operative therapies, which alter the course of disease. Predictive biomarkers are defined as markers that can identify subpopulations of patients that are likely to respond to a given treatment. This allows for a tailoring of treatment as a specific treatment regimen is chosen for any one individual, as they are more likely to respond to it than the alternatives. Biomarkers are sought in pathology specimens, in blood collected from the affected patient and even using radiological investigations, to document changes that may predict a patient’s progress.
Biomarker research has developed in an attempt to shorten clinical trial duration, but also to provide endpoints that have a biologic relevance to the clinical intervention under study. A pathologic biomarker that is often used as a surrogate endpoint in induction therapy trial design is the “percent pathologic response” in the resected primary tumour after induction therapy has been given. A major histological response to pre-operative chemotherapy or chemoradiotherapy (≤10% residual tumour with the remainder of the lesion replaced by fibrosis including pathological complete response) has been shown to be an independent prognostic factor.1 Several studies have shown no significant difference in survival between patients with a pathological complete response or <10% residual tumour.2,3
In this article, we will review the current status of biomarkers in oesophagogastric cancer, reporting on the evidence to date in oesophageal adenocarcinoma and gastro-oesophageal carcinoma.
There is a considerable body of PET data concerning oesophageal adenocarcinoma, particularly regarding tumours in the gastro-oesophageal junction. The only biomarker that has undergone significant investigation is F-18 fluorodeoxyglucose (FDG) PET.
FDG PET as a prognostic biomarker in the untreated patient reflects the intrinsic biology of the patient’s cancer and is best examined in patients who have no induction therapy but proceed directly to surgery, because of the absence of confounding interventions. Patients with ‘early stage’ disease are the ones most likely to benefit from such an approach. Early stage oesophageal cancer has been defined as T1-2 N0 M0. The stage can only be truly confirmed pathologically, but defining the stage on a resected specimen prohibits the patient from potentially benefiting from an induction therapy approach followed by surgery. Rizk et al examined the utility of FDG PET in patients with surgically resected early-stage oesophageal cancer without induction therapy.4 In this analysis of 50 patients, a median standardised uptake value (SUV) of FDG by the tumour (SUV=4.5) was arbitrarily selected to stratify patients as high or low risk. Those patients with a higher than median SUVmax had a statistically significantly shorter three year survival of 57% compared to the 95% seen in those patients with a lower than median SUV. The patients with a low SUV (<4.5) had a 90% chance of having a T1-2 tumour (24/25) compared to 60% (15/25) in the high SUV group. The incidence of an involved N1 or M1a node was 8% (2/25) in the low SUV group but was 48% (12/25) in the high SUV group. In the 32 patients who were classified pathologically as early stage disease (T1-2N0M0), 22/32 (69%) were in the low SUV group and 10 (31%) were in the highmax SUV group. In the 32 with pathologic T1-2N0 M0 disease, low SUV (<4.5) had a significantly better survival (p=0.023). The implications of this data are that patients with a high SUV should be considered at high risk of recurrence and death. This allows for further preoperative risk stratification beyond the traditional TNM staging and may allow for a more tailored approach to subsequent treatment.
While histological response is a reasonable surrogate for survival in oesophageal adenocarcinoma, this end-point is obtained after the completion of the selected pre-operative therapy and surgery. Thus, non-responders to pre-operative therapy are only identified when the options to change therapy are limited and can only be given post-operatively. Given only 50-60% of patients are fit for post-operative chemotherapy,5 this option has limited value. The prospective study by Ott et al demonstrated that a ≥35% reduction in pre-treatment primary tumour SUVmax found on a second FDG PET scan on day 14 (‘early metabolic response’) and after the first cycle of paclitaxel, cisplatin and 5-Fluorouracil (5-FU) chemotherapy (21/56 patients received CF alone), could predict response to neoadjuvant chemotherapy and survival after resection.6 All patients in the study went on to receive another two cycles of chemotherapy without radiotherapy. Early metabolic response was associated with a major histological response in 44% of patients compared with 5% for non-responders. Similarly, an early metabolic response to therapy was an independent prognostic factor for progression-free survival (PFS).6 Subsequently, Lordick et al reported the only clinical study that has modified therapy based on an early metabolic response.7 The MUNICON trial studied 110 patients with oesophageal adenocarcinoma. Patients that showed an early metabolic response to the first cycle of pre-operative chemotherapy then received a further five cycles of therapy then resection with two-year survival of 75%. Metabolic non-responders on the day 14 PET scan received no further chemotherapy and went directly to surgery resulting in a two-year survival of 60% and no histological responses. MUNICON II added radiotherapy to these non-responders, using the same chemotherapy regimen.8 The result was improved response rates. However, survival rates remained poor, suggesting that FDG PET has utility as a prognostic marker, but in this circumstance was a poor predictive marker.
Rizk et al reported the Memorial Sloan-Kettering Cancer Centre experience of the efficacy of a baseline FDG PET to predict response and survival in patients with gastro-oesophageal cancer undergoing chemoradiotherapy induction.9 They found that although there was no difference in survival, the patients with the higher baseline SUV had higher response rates on the post-induction specimen. The finding that a high SUV at baseline predicts for pathological response rates was independently confirmed by Lordick.7 The interpretation made by Rizk et al was that the patients with a low initial baseline SUV had an inherently better survival from a biological perspective, which was not altered by the addition of induction therapy.9 The patients with the higher SUV initially had a worse prognosis that was improved significantly by the addition of induction therapy. Rizk et al suggests that the FDG PET can predict those high risk patients who are most likely to benefit most from induction therapy.9
The above data suggests FDG PET, when performed with due consideration of the underlying principles, including imaging on the same camera, reconstructing the data with a consistent algorithm and using a consistent time post-injection provides prognostically significant data worthy of consideration as a valid biomarker in oesophageal cancer. In Australia, the DOCTOR trial is exploring the role of adjuvant chemotherapy +/- radiotherapy based on a poor early response to neoadjuvant chemotherapy.10
Research studies aimed at identifying prognostic biomarkers in oesophagogastric cancers have generally used a candidate gene or marker approach in the tumour in order to determine whether an association exists with survival, American Joint Committee on Cancer stage or response to chemotherapy or chemoradiotherapy (reviewed in Lagarde, 2007).11 Although there are potential biomarkers and many demonstrate prognostic value, subsequent replication of these findings is lacking (table 1). Since several molecular alterations can act together to influence tumorigenesis, it is unlikely that a single biomarker alone can accurately predict survival. The following are various methods exploring the evidence for predictive biomarkers in oesophageal adenocarcinoma.
Gene expression profiling is the measurement of gene expression in a given sample, often thousands at once, to give a snapshot of cellular function. In this way, it is hoped that an individual tumour can be characterised to better target investigation of biological pathways and ultimately, facilitate drug design. This has been demonstrated in breast cancer with some signatures predicting survival and response to chemotherapy. 41-43 It is less well advanced in oesophagogastric cancers.
A number of studies have explored the use of mRNA expression profiling to predict survival and/or treatment response in individual oesophageal adenocarcinoma patients, with conflicting results. Real time pathological complete response on 38 pre-treatment endoscopic biopsy sections focused on expression of 5-FU, platinum and taxane related genes and found that high expression levels of MTHFR, CALD1 and MRP1 are related to response and survival.44 Langer et al have since shown that high pre-treatment levels of MRP1 and TS in oesophageal adenocarcinoma, are associated with a poor response to chemotherapy.45 Chemotherapy response was also investigated in a cohort of 47 patients with oesophageal adenocarcinoma in which 86 genes were differentially expressed between responders to neoadjuvant chemoradiotherapy and non-responders.46 The authors showed a significant correlation between the Ephrin B3 receptor and response, but these results are yet to be externally validated. This tyrosine kinase receptor has a role in morphogenesis, tumorigenesis and metastatic potential, angiogenesis and tumour vasculature in the gastrointestinal tract.47 Similarly, Schneider et al showed that DPD, ERCC1, TS, GSPi, HER2 and EGFR mRNA expression was downregulated in response to neoadjuvant chemoradiotherapy for oesophageal cancer.48
Luthra et al reported on an oligonucleotide microassay performed on pre-treatment endoscopic biopsies from 19 patients (16 adenocarcinoma, two SCC, one adenosquamous) prior to trimodal therapy.48 Unsupervised clustering was used to identify associations in the microarray according to response, however no statistically significant associations with gene expression were identified. This may be due to the underlying assumption of the unsupervised clustering method which assumes there is a pattern, even when data is truly random.
Duong et al also conducted a microarray study which analysed the expression profiles in 46 patients (25 with oesophageal adenocarcinoma).49 They were able to identify a 32-gene classifier to predict chemoradiotherapy response for SCC, but a gene signature predictive for oesophageal adenocarcinoma was not identified.
Recently, Peters and colleagues have reported a four-gene prognostic signature (DCK, PAPSS2, SIRT2 and TRIM44) for oesophageal adenocarcinoma and gastro-oesophageal cancer (table 2).50 The discovery phase was undertaken using a 44k cDNA microarray for 75 patients with oesophageal adenocarcinoma of varying stage, and externally validated using tissue microarrays constructed from a separate oesophageal adenocarcinoma and gastro-oesophageal patient cohort (n=371). While the mixture of stages and treatment types may confound the results, the study is of large size and is the only microarray-based biomarker investigation conducted in oesophageal adenocarcinoma that has demonstrated external validation of the prognostic signature.
Copy number variations are a form of structural variation where there is an abnormality in one or more sections of DNA within a cell. The degree of changes in chromosomal numbers within a cell,51 the presence and degree of DNA damage and the proportion of flow cytometric-sorted biopsy fractions that display 4n DNA content,51,52 have been proposed as markers of the progression of Barrett’s Oesophagus to oesophageal adenocarcinoma to be used in conjunction with dysplasia status. Amplifications in several genomic regions can lead to the increased activity of oncogenes (eg. MYC), which promote autonomous cell growth. In order to profile whole genome DNA copy number changes in oesophageal adenocarcinoma, several groups have employed array-based comparative genome hybridisation studies or loss of heterozygosity microsatellite-based methods. The most frequently reported regions of loss are 4q, 5q, 9p, 17p, 18q and Y, while frequent gains are on 7p, 8q and 20q.
Several other studies have looked for gene-based DNA copy number changes in oesophageal adenocarcinoma and found that FHIT, CDKN2A and TP53 are frequently lost, while MYC, MYBL2 and ERBB2 are gained.53,54 High resolution DNA copy number screening using SNP arrays in oesophageal adenocarcinoma tumours have found copy number events to be common, averaging 76 (range, 5-152) per tumour.55 Losses and gains averaged 20 (range, 1-62) and 16 (range, 1-54) per tumour respectively, and copy neutral loss of heterozygosity events averaged 41 (range, 3-75) per oesophageal adenocarcinoma.55 More high resolution studies are still required, particularly those linked to clinical trial outcomes.
Methylation of DNA within CpG islands, or sections of the genome with high levels of the DNA building blocks cytosine and guanine, are being found to occur in a growing number of genes to varying degrees in human cancers, including oesophageal adenocarcinomas.56 In normally differentiated, non-neoplastic tissues these genes are mainly unmethylated. It is thought to be a critical mechanism for tumour suppressor gene silencing and inactivation.57 Circulating tumour cells with methylated CpG islands have been proposed as a prognostic indicator and for tumour detection in colorectal cancer.58
A retrospective analysis of CpG island hypermethylation was assessed in 11 candidate genes in pre-treatment tumour specimens (oesophageal adenocarcinoma 23, oral squamous cell carcinoma 12).59 The patients received neoadjuvant trimodal therapy. A lower number of methylated genes per patient (1.2 versus 2.4, p=0.026) was associated with pathological complete response.
MethyLight assays have been used to identify methylation in the promoter regions of the CDKN2A, HPP1 and RUNX3 genes, and to distinguish Barrett’s Oesophagus tissue at risk of progression to oesophageal adenocarcinoma.60-62 Frequent differences in the methylation profiles for nine cancer related genes in oesophageal adenocarcinoma, compared with normal squamous epithelium, have also been demonstrated,63 as has aberrant methylation of the E-cadherin promoter, which seems to be a common cause of inactivation in adenocarcinomas.64
These data suggest that methylation differences may be suitable candidates for prognostic biomarkers in oesophagogastric cancers.
Somatic mutations are a well recognised phenomenon in tumour biology, often in combination with changes in DNA copy number. TP53 loss of heterozygosity and mutations seem to be relatively early events in neoplastic progression in Barrett’s Oesophagus and TP53 mutation frequency estimates range from 35-69% in oesophageal adenocarcinoma.55,65-68 Although allelic loss of CDKN2A appears to be common, point mutations appear to be rare.69-71 A number of other candidate genes have been explored for somatic mutations in oesophageal adenocarcinoma, including APC, CDH1, CTNNB1, EGFR, FHIT, BRAF, KRAS, TGFB, PIK3CA and PIK3CB.
Recently, Boonstra et al demonstrated that the CDH1 GA/GA phenotype was associated with reduced survival and conversely, the MDM2 T/G phenotype with improved disease-free survival.72 They suggest that the individual differences in germ-line DNA have an impact on disease-free survival in oesophageal adenocarcinoma.
In general however, the reported frequency of somatic mutations identified in the genes studied in oesophageal adenocarcinoma appears to be low. Despite frequent allelic loss of 5q on which APC resides, a very low rate of APC mutations was described in oesophageal cancers.73-76 Similarly, mutations of the E-cadherin,77 FHIT,78 CTNNB1,78 TGFβ,79 and EGFR genes,80,81 were rarely described in adenocarcinomas. A recent report identified activating BRAF mutations in 2/19 tumours and KRAS mutations in 4/19 tumours, suggesting that the disruption of the Raf/MEK/ERK (MAPK) kinase pathway is frequent in oesophageal adenocarcinoma,82 findings supported by other studies.83,84
In summary, only a handful of selected genes have been investigated for somatic mutations in oesophageal adenocarcinoma. The majority of these genes have been selected based on evidence from other cancer types. Although the lack of somatic mutations found in these genes might suggest that the frequency of somatic mutation in oesophageal adenocarcinoma is low, an alternative hypothesis is that a different set of genes is mutated in oesophageal adenocarcinoma, which in part could account for the different disease course and poor survival. The landscape of human genetics is rapidly changing with the advent of massively parallel sequencing technologies.85 The first cancer genomes to be published have revealed thousands of novel somatic mutations and implicated new genes and processes in tumour development and progression.86 Next generation sequencing is particularly appealing because it can detect the full spectrum of genetic variants in cancer, which could allow for a further differentiation which reflects the phenotype. It may also allow for the identification of novel therapeutic targets for future investigation.
Iqbal et al examined various genes in a cohort receiving XELOX and cetuximab as first-line treatment of gastric and gastroesophageal junction adenocarcinoma.87 The genes chosen were related to 5-FU (TYMS, MTHFR) and oxaliplatin (ERCC1, XPD, GSTP1) metabolism, and human epidermal receptor signalling (EGF, HER2, COX2, FCgR2A, FCgR3A). It has shown a statistically significant association between SNPs EGF A+61G rs4444903 and GSTP1 Ile105Val rs1695 and response rate. There was a significant association with MTHFR 1298 A1298C rs1801131 and the overall survival (p=0.044).
ERCC1 gene expression levels have been shown to be predictive of response and survival to platinum-based chemotherapy.88,89 Increased ERCC-1 mRNA expression may be an indicator for non-responsiveness to neoadjuvant CDDP-based chemotherapy.90 Conversely, low intratumoral expression of ERCC1 correlated significantly with better response to neoadjuvant chemoradiotherapy, even though overall survival could not be evaluated due to short follow-up.
A number of biomarkers have been reported in oesophagogastric cancers. While they have been shown to be variously prognostic or predictive in response to treatment, none have been prospectively validated and most are in small patient populations. Integrating these findings into prospective trials will hopefully herald their use in everyday clinical practice and thus, improve the management of oesophagogastric cancer into the future.
1. Mandard AM, Dalibard F, Mandard JC, Marnay J, Henry-Amar M, Petiot JF, et al. Pathologic assessment of tumor regression after preoperative chemoradiotherapy for esophageal carcinoma. Cancer. 1994;73:2680-6.
2. Barbour AP, Jones M, Gonen M, Gotley DC, Thomas J, Thomson DB, et al. Refining esophageal cancer staging after neoadjuvant therapy: importance of treatment response. Ann Surg Oncol. 2008;15:2894-2902.
3. Schneider PM, Baldus SE, Metzger R, Kocher M, Bongartz R, Bollschweiler E, et al. Histomorphologic tumor regression and lymph node metastases determine prognosis following neoadjuvant chemoradiotherapy for esophageal cancer: implications for response classification. Ann Surg.2005;242:684-92.
4. Rizk N, Downey RJ, Akhurst T, Gonen M, Bains MS, Larson S, et al. Preoperative 18[F]-fluorodeoxyglucose positron emission tomography standardized uptake values predict survival after esophageal adenocarcinoma resection. Ann Thorac Surg. 2006;81(3):1076-81.
5. Gebski V, Burmeister B, Smithers BM, Foo K, Zalcberg J, Simes J, et al. Survival benefits from neoadjuvant chemoradiotherapy or chemotherapy in oesophageal carcinoma: a meta-analysis. Lancet Oncol. 2007;8(3):226-34.
6. Ott K, Weber WA, Lordick F, Becker K, Busch R, Herrmann K, et al. Metabolic imaging predicts response, survival, and recurrence in adenocarcinomas of the esophagogastric junction. J Clin Oncol. 2006;24(29):4692-8.
7. Lordick F, Ott K, Krause BJ, Weber WA, Becker K, Stein HJ, et al. PET to assess early metabolic response and to guide treatment of adenocarcinoma of the oesophagogastric junction: the MUNICON phase II trial. Lancet Oncol. 2007;8(9):797-805.
8. Meyer Zum Büschenfelde C, Herrmann K, Schuster T, Geinitz H, Langer R, Becker K, et al. 18F-FDG PET-Guided salvage neoadjuvant radiochemotherapy of adenocarcinoma of the esophagogastric junction: The MUNICON II Trial. J Nucl Med. 2011;52(8):1189-96.
9. Rizk NP, Tang L, Adusumilli PS, Bains MS, Akhurst TJ, Ilson D, et al. Predictive value of initial PET-SUVmax in patients with locally advanced esophageal and gastroesophageal junction adenocarcinoma. J Thorac Oncol. 2009;4(7):875-9.
10. Barbour, AB, Walpole, E, Zalcberg, J. DOCTOR: a randomised phase II trial of pre-operative cisplatin, 5 fluorouracil and docetaxel +/- radiotherapy based on poor early response to standard chemotherapy for resectable adenocarcinoma of the oesophagus and/or OG junction. [Internet] Accessed: [2011 July 17] Available from: http://www.anzctr.org.au/trial_view.aspx?ID=308313
11. Lagarde SM, Kate FJ, Richel DJ, Offerhaus GJ, van Lanschott, JJ. Molecular prognostic factors in adenocarcinoma of the esophagus and gastroesophageal junction. Ann Surg Oncol. 2007;14(2): 977-91.
12. Hainaut P, Hollstein M. P53 and human cancer: the first ten thousand mutations. Adv Cancer Res. 2000;77:81-137.
13. Bhandari P, Bateman AC, Mehta RL, Stacey RS, Johnson P, Cree IA, et al. Prognostic significance of cyclooxygenase-2 (COX-2) expression in patients with surgically resectable adenocarcinoma of the oesophagus. BMC Cancer. 2006;6:134.
14. France M, Drew PA, Dodd T, Watson DI. Cyclo-oxygenase-2 expression in esophageal adenocarcinoma as a determinant of clinical outcome following esophagectomy. Dis Esophagus. 2004;17(2):136-40.
15. Izzo JG, Wu TT, Wu X, Ensor J, Luthra R, Pan J, et al. Cyclin D1 guanine/adenine 870 polymorphism with altered protein expression is associated with genomic instability and aggressive clinical biology of esophageal adenocarcinoma. J Clin Oncol. 2007;25(6):698-707
16. Lorenzen S, Panzram B, Keller G, Lordick F, Herrmann K, Becker K, et al. Association of the VEGF 936C>T polymorphism with FDG uptake, clinical, histopathological and metabolic response in patients with adenocarcinomas of the esophagogastric junction. Mol Imaging Biol. 2011;13:178-86.
17. Stoehlmacher J, Lenz HJ. Cyclooxygenase-2 inhibitors in colorectal cancer. Semin Oncol 2003;30:10-16.
18. Lurje G, Vallbohmer D, Collet PH, Xi H, Baldus SE, Brabender J, et al. COX-2 mRNA expression is significantly increased in acid-exposed compared to nonexposed squamous epithelium in gastroesophageal reflux disease. J Gastrointest Surg. 2007;11:1105-11.
19. Hamoui N, Peters JH, Schneider S, Uchida K, Yang D, Vallbhomer D, et al. Increased acid exposure in patients with gastroesophageal reflux disease influences cyclooxyenase-2 gene expression in the squamous epithelium of the lower esophagus. Arch Surg. 2004;139:712-9.
20. Lurje G, Nagashima F, Zhang W, Yang D, Chang HM, Gordon MA, et al. Polymorphisms in COX-2 and EGFR are associated with progression-free survival independent of K-ras in mCRC patients treated with single agent cetuximab. Clin Cancer Res. 2008;14:7884-95.
21. Zimmerman KC, Sarbia M, Weber AA, Borchard F, Gabbert HE, Schror K. Cyclooxygenase-2 expression in human esophageal carcinoma. Cancer Res. 1999;59:198-204.
22. Tsuji M, DuBois RN. Alterations in cellular adhesion and apoptosis in epithelial cells overexpressing prostaglandin endoperoxide synthase 2. Cell. 1995;83;493-501.
23. Xi H, Baldus SE, Warnecke-Eberz U, Brabender J, Neiss S, Metzger R, et al. High cyclooxygenase-2 expression following neoadjuvant radiochemotherapy is associated with minor histopathologic response and poor prognosis in esophageal cancer. Clin Cancer Res. 2005;11:8341-7.
24. Soussi T, Legros Y, Lubin R, Ory K, Schlichtholtz,B. Multifactorial analysis of p53 alteration in human cancer: a review. Int J Cancer. 1994;27:1-9.
25. Ribeiro U Jr, Finkelstein SD, Safalte-Ribeiro AV, Landreneau RJ, Clarke MR, Bakker A, et al. p53 sequence analysis predicts treatment response and outcome of patients with esophageal carcinoma. Cancer. 1998;83:7-18.
26. Gibson MK, Abraham SC, Wu TT, Burtness B, Heitmiller RF, Heath E, et al. Epidermal growth factor receptor, p53 mutation, and pathological response predict survival in patients with locally advanced esophageal cancer treated with preoperative chemoradiotherapy. Clin Cancer Res. 2003;9:6461-8.
27. Shimada CA, Watanabe G, Yamasaki S, Maeda M, Kawabe A, Kaganoi JI, et al. Histological response of cisplatin predicts patients’ survival in oesophageal cancer and p53 protein accumulation in pretreatment biopsy is associated with cisplatin sensitivity. Eur J Cancer. 2000;36:987-93.
28. Hironaka S, Hasebe T, Kamijo T, Ohtsu A, Boku N, Yoshida S, et al. Biopsy specimen microvessel density is a useful prognostic marker in patients with T92-4)M(0) esophageal cancer treated with chemoradiotherapy. Clin Cancer Res. 2002;8:124-30.
29. Sarbia M, Stahl M, Fink U, Willers R, Seeber S, Gabbert HE. Expression of apoptosis-regulating proteins and outcome of esophageal cancer patients treated by combined therapy modalities. Clin Cancer Res. 1998;4:2991-7.
30. Ambrosini, G, Adida, C, Atieri, DC. A novel anti-apoptosis gene, survivin, expressed in cancer and lymphoma. Nat Med. 1997; 3:917-21.
31. Vallbohmer D, Peters JH, Oh D, Kuramochi H, Shimizu D, Demeester SR, et al. Survivin, a potential biomarker in the development of Barrett’s adenocarcinoma. Surgery. 2005;138:701-6.
32. Vallbohmer D, Kuhn E, Warnecke-Eberz U, Brabender J, Hoffman AC, Metzger R, et al. Failure in downregulation of intratumoural survivin expression following neoadjuvant chemoradiation in esophageal cancer. Pharmacogenomics. 2008;9:681-90.
33. Warnecke-Eberz U, Hokita S, Xi H, Higashi H, Baldus SE, Metzger R, et al. Overexpression of survivin mRNA is associated with a favourable prognosis following neoadjuvant radiochemotherapy in esophageal cancer. Oncol Rep. 2005;13:1241-6.
34. Izzo J, Malhoura U, Wu TT, Ensor J, Luthra R, Lee JH, et al. Association of activated transcription factor NF-kappaB with chemoradiation resistance and poor outcome in esophageal carcinoma. J Clin Oncol. 2006;24:748-54.
35. Izzo JG, Correa AM, Wu TT, Malhotra U, Chao Ck, Luthra R, et al. Pretherapy nuclear factor-kappaB status, chemoradiation, and metastatic progression in esophaegeal carcinoma. Mol Cancer Ther 2006;5:2844-50.
36. Abdel-Latif MM, O’Riordan JM, Ravi N, Kelleher D, Reynolds JV. Activated nuclear factor-kappaB and cytokine profiles in the esophagus parallel tumor regression following neoadjuvant chemoradiotherapy. Dis Esophagus 2005;18:246-52.
37. Nakashima S, Natsugoe S, Matsumoto M, Kijima F, Takebayashi Y, Okumura H, et al. Expression of p53 and p21 is useful for the prediction of preoperative chemotherapeutic effects in esophageal carcinoma. Anticancer Res. 2000;20(3B):1933-7.
38. Gray LH, Conger AD, Ebert M, Hornsey S, Scott OCA. The concentration of oxygen dissolved in tissue at the time of irradiation as a factor of radiotherapy. Br J Radiol 1953;26:638-48.
39. Hockel M, Schlenger K, Aral B, Mitze M, Schaffer U, Vaupel P. Association between tumor hypoxia and malignant progression in advanced cancer of the uterine cervix. Cancer Res 1996;56:4509-15.
40. Brizel DM, Scully SP, Harrelson JM, Layfield LJ, Bean JM, Prosnitz LR, et al. Tumor oxygenation predicts for the likelihood of distant metastases in human soft tissue sarcoma. Cancer Res 1996;56:941-3.
41.Van ‘t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415:530-6.
42. Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351:2817-26.
43. Straver ME, Glas AM, Hannemann J, Wesseling J, van de Vijver MJ, Rutgers EJ, et al. The 70-gene signature as a response predictor for neoadjuvant chemotherapy in breast cancer. Breast Cancer Res Treat. 2010;119:551-8.
44. Langer R, Specht K, Becker K, Ewald P, Bekesch M, Sarbia M, et al. Association of pretherapeutic expression of chemotherapy-related genes with response to neoadjuvant chemotherapy in Barrett carcinoma. Clin Cancer Res. 2005;11:7462-9.
45. Langer R, Ott K, Feith M, Lordick F, Specht K, Hofler H. High pretherapeutic thymidylate synthetise and MRP-1 protein levels are associated with nonresponse to neoadjuvant chemotherapy in oesophageal adenocarcinoma patients. J Surg Oncol. 2010;102:503-8.
46. Schauer M, Janssen KP, Rimkus C, Raggi M, Feith M, Friess H, et al. Microarray-based response prediction in esophageal adenocarcinoma. Clin Cancer Res. 2010;16:330-337.
47. Schneider S, Uchida K, Brabender J, Baldus SE, Yochim J, Danenberg KD, et al. Downregulation of TS, DPD, GST-Pi, EGFR and HER2 gene expression after neoadjuvant three-modailty treatment in patients with esophageal cancer. J Am Coll Surgeons. 2005;200:336-44.
48. Luthra R, Wu TT, Luthra RG, Izzo J, Lopez-Alvarez E, Zhang L, et al. Gene expression profiling of localized esophageal carcinomas: association with pathologic response to preoperative chemoradiation. J Clin Oncol. 2006;24:259-67.
49. Duong C, Greenwalt DM, Kowalczyk A, Ciavarella ML, Raskutti G, Murray WK, et al. Pretreatment gene expression profiles can be used to predict response to neoadjuvant chemoradiotherapy in esophageal cancer. Ann Surg Oncol. 2007;14:3602-9.
50. Peters CJ, Rees JR, Hardwick RH, Hardwick JS, Vowler SL, Ong C-AJ, et al. A 4-gene signature predicts survival of patients with resected adenocarcinoma of the esophagus, junctions and gastric cardia. Gastroenterology. 2020;139:1995-2004.
51. Peters CJ, Rees JR, Hardwick RH, Hardwick JS, Vowler SL, Ong C-AJ, et al. A 4-gene signature predicts survival of patients with resected adenocarcinoma of the esophagus, junctions and gastric cardia. Gastroenterology. 2020;139:1995-2004.
52. Reid BJ, Blount PL, Rabinovitch, PS. Biomarkers in Barrett’s esophagus. Gastrointest Endosc Clin N Am. 2003;13:369-97.
53. Olliver JR, Hardie LJ, Dexter S, Chalmers D, Wild CP. DNA damage levels are raised in Barrett’s oesophageal mucosa relative to the squamous epithelium of the oesophagus. Biomarkers. 2003;8:509-21.
54. Albrecht B, Hausmann M, Zitzelsberger H, Stein H, Siewert JR, Hopt U, et al. Array-based comparative genomic hybridisation for the detection of DNA sequence copy number changes in Barrett’s adenocarcinoma. J Pathol. 2004;203:780-8.
55. Nancarrow DJ, Clouston AD, Smithers BM, Gotley DC, Drew PR, Watson DI, et al. Whole genome expression array profiling highlights differences in mucosal defense genes in Barrett’s esophagus and esophageal adenocarcinoma. PLoS ONE. 2011:6;e22513.
56. Sanz-Ortega J, Valor C, Saez MC, Ortega, L, Sierra E, Poch J, et al. 3p21, 5q21, 9p21 and 17q13 allelic deletions accumulate in the dysplastic spectrum of laryngeal carcinogenesis and precede malignant transformation. Histol Histopathol. 2003;18:1053-7.
57. Brock MV, Gou M, Akiyama Y, Muller A, Wu TT, Montgomery E, et al. Prognostic importance of promoter hypermethylation of multiple genes in esophageal adenocarcinoma. Clin Cancer Res. 2003;9:2912-9.
58. Jones PA, Baylin SB. The fundamental role of epigenetic events in cancer. Nat Rev Genet. 2002;3:415-28.
59. Wallner M, Herbst A, Behrens A, Crispin A, Stieber P, Goke B, et al. Methylation of DNA is an independent prognostic marker in colorectal cancer. Clin Cancer Res 2006;12:7347-52.
60. Hamilton JP, Sato F, Greenwald BD, Suntharalingam M, Krasna MJ, Edelman MJ, et al. Promoter methylation and response to chemotherapy and radiation in esophageal cancer. Clin Gastroenterol Hepatol. 2006;4:701-8.
61. Clement G, Braunschweig R, Pasquier N, Bosman FT, Benhattar J. Methylation of APC, TIMP3 and TERT: a new predictive marker to distinguish Barrett’s oesophagus patients at risk for malignant transformation.J Pathol. 2006;208:100-7.
62. Eads CA, Lord RV, Wickramasinghe K, Long TI, Kurumboor SK, Bernstein L, et al. Epigenetic patterns in the progression of oesophageal adenocarcinoma. Cancer Res. 2001;61:3410-8.
63. Schulmann K, Sterian A, Berki A, Yin J, Sato F, Xu Y, et al. Inactivation of p16, RUNX3 and HPP1 occurs early in Barrett’s-associated neoplastic progression and predicts progression risk. Oncogene. 2005;24:4138-48.
64. Corn PG, Heath EI, Heitmiller R, Fogt F, Forastiere AA, Herman JG, et al. Frequent hypermethylation of the 5’CpG island of E-cadherin in esophageal adenocarcinoma. Clin Cancer Res. 2001;7:2765-9.
65. Gleeson C, Sloan J, McManus D, Maxwell P, Arthur K, Ritchie A, et al. Comparison of p53 and DNA content abnormalities in adenocarcinomas of the oesophagus and gastric cardia. Br J Cancer. 1998;77(2):277-86.
66. Casson AG, Tammemagi M, Eskandarian S, Redson M, McLaughlin J, Ozcelik H. p53 alterations in oesophageal cancer: association with clinicopathological features, risk factors, and survival. Mol Pathol. 1998;51(2):71-9.
67. Schneider PM, Stoeltzing O, Roth JA, Hoelscher AH, Wegerer S, Mizumoto S, et al. P53 mutational status improves estimation of prognosis in patients with curatively resected adenocarcinoma in Barrett’s esophagus. Clin Cancer Res. 2000;6(8):3153-8.
68. Bian YS, Osterheld MC, Bosman FT, Benhattar J, Fontolliet C. p53 gene mutation and protein accumulation during neoplastic progression in Barrett’s esophagus. Mod Pathol. 2001;14(5):397-403.
69. Sengpiel C, Konig IR, Rades D, Noack F, Duchrow M, Schild SE,et al. p53 Mutations in carcinoma of the esophagus and gastroesophageal junction. Cancer Invest. 2009;27:96-104.
70. Gonzalez MV, Artimex ML, Rodrigo L, Lopez-Larrea C, Menendez MJ, Alvarez V, et al. Mutation analysis of the p53, APC, and p16 genes in the Barrett’s oesophagus, dysplasia, and adenocarcinoma. J Clin Pathol. 1997;50(3):212-7.
71. Muzeau F, Flejou JF, Belghiti J, Thomas G, Hamelin R. Infrequent microsatellite instability in oesophageal cancers. Br J Cancer. 1997;75(9):1336-9.
72. Vieth M, Schneider-Stock R, Rohrich K, May A, Ell C, Markwarth A, et al. INK4a-ARF alterations in Barrett’s epithelium, intraepithelial neoplasia and Barrett’s adenocarcinoma. Virchows Arch. 2004;445(2):135-41.
73. Boonstra JJ, Marion R, Tilanus HW, Dinjens WNM. Functional polymorphisms associated with disease-free survival in resected carcinoma of the esophagus. J Gastrointest Surg. 2011;15:48-56.
74. Ogasawara S, Tamura G, Measawa C, Suzuki Y, Ishida K, Satoh N, et al. Common deleted region on the long arm of chromosome 5 in esophageal carcinoma. Gastroenterology. 1996;110(1):52-7.
75. Powell SM, Papadopoulos N, Kinzler KW, Smolinski KM, Meltzer SJ. APC gene mutations in the mutation cluster region are rare in esophageal cancers. Gastroenterology. 1994;107(6):1759-63.
76. Choi YW, Heath EI, Heitmiller R, Forastiere AA, Wu TT. Mutations in beta-catenin and APC genes are uncommon in esophageal and esophagogastric junction adenocarcinomas. Mod Pathol. 2000;13(10):1055-9.
77. Wijnhoven BP, de Both NJ, van Dekken H, Tilanus HW, Dinjens WN. E-cadherin gene mutations are rare in adenocarcinomas of the oesophagus. Br J Cancer. 1999;80(10):1652-7.
78. Zou TT, Lei J, Shi YQ, Yin J, Wang S, Souza RF, et al. FHIT gene alterations in esophageal cancer and ulcerative colitis (UC). Oncogene. 1997;15(1):101-5.
79. Tanaka S, Mori M, Mafune K, Ohno S, Suqimachi K. A dominant negative mutation of transforming growth factor-beta receptor type II gene in microsatellite stable oesophageal carcinoma. Br J Cancer. 2000;82(9):1557-60.
80. Puhringer-Oppermann FA, Stein HJ, Sarbia M. Lack of EGFR gene mutations in exons 19 and 21 in esophageal (Barrett’s) adenocarcinomas. Dis Esophagus. 2007;20(1): 9-11.
81. Kwak EL, Jankowski J, Thayer SP, Lauwers GY, Brannigan BW, Harris PL, et al. Epidermal growth factor receptor kinase domain mutations in esophageal and pancreatic adenocarcinomas. Clin Cancer Res. 2006;12(14 Pt 1):4283-7.
82. Sommerer F, Veith M, Markwarth A, Rohrich K, Vomschloss S, May A, et al. Mutations of BRAF and KRAS2 in the development of Barrett’s adenocarcinoma. Oncogene. 2004;23(2):554-8.
83. Lord RV, O’Grady R, Sheehan C, Field AF, Ward Rl. K-ras codon 12 mutations in Barrett’s oesophagus and adenocarcinomas of the oesophagus and oesophagogastric junction. J Gastroenterol Hepatol. 2000;15(7):730-6.
84. Janmaat ML, Gallegos-Ruiz MI, Rodriguez JA, Meijer GA, Vervenne WL, Richel DJ, et al. Predictive factors for outcome in a phase II study of gefitinib in second-line treatment of advanced esophageal cancer patients. J Clin Oncol. 2006;24(10):1612-9.
85. Mardis ER. Next-generation DNA sequencing methods. Annu Rev Genomics Hum Genet 2008;9:387-402.
86. Chau I, Okines AFC, Gonzalez de Castro D, Saffrey C, Barbachano Y, Wotherspoon A, et al. REAL3: A multicenter randomised phase II/III trial of epirubicin, oxaliplatin, and capecitabine (EOC) versus modified (m) EOC plus panitumumab (P) in advanced Oesophagogastric (OG) cancer – response rate(RR), toxicity, and molecular analysis from phase II. ASCO Meeting Abstracts. 2011;29(15 suppl):4131.
87. Iqbal S, Labonte MJ, Yang D, Zhang W, Bohanes PO, Ning Y, et al. Polymorphisms in EGF a+61G, GSTP Ile105Val, and MTHFR A1298C to predict response and survival in a phase II study for patients with metastatic or unresectable gastric (G) or gastroesophageal junction (GEJ) cancer treated with capecitabine, oxaliplatin (XELOX), and cetuximab. ASCO Meeting Abstracts. 2011;29(15 suppl):4121.
88. Shirota Y, Stoehlmacher J, Brabender J, Xiong YP, Uetake H, Danenberg KD, et al. ERCC1 and thymidylate synthase mRNA levels predict survival for colorectal cancer patients receiving combination oxaliplatin and fluorouracil chemotherapy. J Clin Oncol. 2001;19:4298-4304.
89. Yamada Y, Mizusawa A, Takashima A, Nakamura K, Tsuji Y, Suzuki Y, et al. Molecular prognostic markers in advanced gastric cancer: Correlative study in the Japan Clinical Oncology Group trial JCOG9912. ASCO Meeting Abstracts. 2011; 29(15 suppl):4021.
90. Warnecke-Eberz U, Metzger R, Miyazono F, Baldus SE, Neiss S, Brabender J, et al. High specificity of quantitative excision repair cross-complementing 1 messenger RNA expression for prediction of minor histopathologic response to neoadjuvant radiochemotherapy in esophageal cancer. Clin Cancer Res. 2004;10:3794-9.