Current advances in esophageal cancer proteomics

BBAPAP-39430; No. of pages: 9; 4C: 2 Biochimica et Biophysica Acta xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

Biochimica et Biophysica Acta journal homepage: www.elsevier.com/locate/bbapap

Current advances in esophageal cancer proteomics☆ Norihisa Uemura a,1, Tadashi Kondo b,⁎,1 a b

Department of Gastroenterological Surgery, Aichi Cancer Center Hospital, 1-1 Kanokoden, chikusa-ku, Nagoya, Aichi 464-8681, Japan Division of Pharmacoproteomics, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan

a r t i c l e

i n f o

Article history: Received 4 June 2014 Received in revised form 4 September 2014 Accepted 9 September 2014 Available online xxxx Keywords: Esophageal cancer Proteomics Biomarker Neoadjuvant therapy Molecular mechanism

a b s t r a c t We review the current status of proteomics for esophageal cancer (EC) from a clinician's viewpoint. The ultimate goal of cancer proteomics is the improvement of clinical outcome. The proteome as a functional translation of the genome is a straightforward representation of genomic mechanisms that trigger carcinogenesis. Cancer proteomics has identified the mechanisms of carcinogenesis and tumor progression, detected biomarker candidates for early diagnosis, and provided novel therapeutic targets for personalized treatments. Our review focuses on three major topics in EC proteomics: diagnostics, treatment, and molecular mechanisms. We discuss the major histological differences between EC types, i.e., esophageal squamous cell carcinoma and adenocarcinoma, and evaluate the clinical significance of published proteomics studies, including promising diagnostic biomarkers and novel therapeutic targets, which should be further validated prior to launching clinical trials. Multi-disciplinary collaborations between basic scientists, clinicians, and pathologists should be established for inter-institutional validation. In conclusion, EC proteomics has provided significant results, which after thorough validation, should lead to the development of novel clinical tools and improvement of the clinical outcome for esophageal cancer patients. This article is part of a Special Issue entitled: Medical Proteomics. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Esophageal cancer (EC) is the fifth for men and the eighth for women, most common cause of cancer-related death worldwide [1]. Despite the use of modern surgical techniques in combination with radiotherapy and chemotherapy, early recurrence is common in patients with advanced disease and the overall 5-year survival rate remains below 40% [2]. In contrast, the 5-year survival rate for patients with early stage lesions after endoscopic or surgical treatment exceeds 90% [3]. Survival substantially decreases with the increase of tumor invasion and the presence of regional lymph node metastases and distant metastases [2]. These clinical facts clearly indicate that early detection is the key to EC cure. However, fewer than 30% of EC patients appeared in the hospital at early stage [4], and early screening modalities are critically needed. For Abbreviations: 2-DE, Two dimensional gel electrophoresis; 2D-DIGE, Two-dimensional difference gel electrophoresis; BRE, Brain and reproductive organ-expressed; COX, Cytochrome c oxidase subunits; CRT, Chemoradiotherapy; EAC, Esophageal adenocarcinoma; EC, Esophageal cancer; ESCC, Esophageal squamous cell carcinoma; HER2, Human epidermal growth factor receptor 2; Hsp, Heat shock protein; KLH, Keyhole limpet hemocyanin; LC-MS/MS, Liquid chromatography-tandem mass spectrometry; MALDI-TOF MS, Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry; SELDITOF MS, Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ☆ This article is part of a Special Issue entitled: Medical Proteomics. ⁎ Corresponding author at: Division of Pharmacoproteomics, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan. Tel.: +81 3 3542 2511; fax: +81 3 3547 5298. E-mail addresses: [email protected] (N. Uemura), [email protected] (T. Kondo). 1 Uemura N and Kondo T contributed equally to this study.

the patients with advanced disease, neoadjuvant therapy has been proved extremely valuable and is established as a standard treatment [5–11]. However, a significant proportion of treated patients (60–70%) do not respond well to neoadjuvant regimens and develop severe adverse effects [10,12]. Thus, risk stratification for neoadjuvant therapy is required to improve treatment quality for patients with EC. Moreover, elucidation of molecular mechanisms underlying the resistance to treatment may lead to novel therapeutic strategies and/or agents. Cancer proteomics has been conducted with the goal to identify diagnostic biomarkers and improve clinical outcome. The biomarkers should be used for early cancer detection and effective prediction of cancer clinical behavior, as well as identification of novel molecular targets involved in tumorigenesis and disease progression [13]. Cancer proteomics is a promising approach because proteome is a functional translation of the genomic aberrations that initiate and promote the disease. Many lines of evidence indicate the discrepancy between protein and mRNA expression, and recent studies demonstrated that protein levels are mainly determined at the translation rather than transcriptional step [14–16]. Posttranslational modifications, protein interactions, activity, and localization are also unique data that can be obtained only by proteomics [17]. Since aberrant protein expression is an important feature of cancerous phenotype, the analysis of cancer proteome can result in the identification of biomarker candidates associated with clinical characteristics and can further understanding of the molecular mechanisms underlying the initiation and progression of EC [18]. In the last decade, the advancement in proteomics has led to a comprehensive understanding of the EC proteome. For example, in

http://dx.doi.org/10.1016/j.bbapap.2014.09.011 1570-9639/© 2014 Elsevier B.V. All rights reserved.

Please cite this article as: N. Uemura, T. Kondo, Current advances in esophageal cancer proteomics, Biochim. Biophys. Acta (2014), http:// dx.doi.org/10.1016/j.bbapap.2014.09.011

2

N. Uemura, T. Kondo / Biochimica et Biophysica Acta xxx (2014) xxx–xxx

two-dimensional gel electrophoresis (2-DE), the separation in the first dimension was improved by the use of immobiline dry strip gels [19], which enabled the isolation and identification of low-expressed proteins by mass spectrometry. Two-dimensional difference gel electrophoresis (2D-DIGE) provided compensation of gel-to-gel variations by the use of an internal standard sample, while the application of highly sensitive fluorescent dyes enabled expression profiling of small protein amounts from laser microdissected tissues [20–22]. The number of detectable protein spots has increased from hundreds to thousands through advances in analytical detection of low-molecular-weight proteins [23]. In addition to gel-based techniques, mass spectrometry and highly sensitive immunodetection methods have also been successfully applied to EC proteomics [24,25] (Fig. 1). In the early 2000s, proteomics studies in EC focused on the comparison between tumor and non-tumor tissues, and a considerable number of proteins with differential expression in esophageal tumors was detected and functionally examined [26–28]. Although these studies provided potential keys to the understanding of molecular background underlying EC development, considerable diversity of biological mechanisms involved in cancer initiation and progression, as well as heterogeneity of esophageal tumors, made it difficult to link the detected proteins to specific clinical and pathological data. Then, clinically oriented proteomics studies, which integrated protein profiling with clinical and pathological observations of primary tumors from different patients, were launched as the next step toward clinical application. Our review focuses on three major topics in EC proteomics: diagnostics, treatment, and molecular mechanisms. We will also consider histological types of EC, namely esophageal squamous cell carcinoma (ESCC) and adenocarcinoma (EAC). It has been shown that the predominant histological type of EC is region-specific. Although ESCC prevails in most of the world, the incidence of EAC now exceeds that of ESCC in Australia, the USA, and some Western European countries (e.g., the UK, Finland, France, and the Netherlands) [29,30]. ESCC and EAC are

also clinically distinct. In a study of 8562 patients who underwent surgical resection, Merkow et al. found that ESCC histology was the only factor predictive of pathologic complete response to neoadjuvant treatment [31], consistent with previous observations showing that histological type might affect response to neoadjuvant chemotherapy and subsequent prognosis for EC patients [32]. Thus, histologically different ESCC and EAC should be discriminated in EC proteomics. Second, we focus on the clinical significance of proteomic studies. We believe that the ultimate goal of cancer proteomics should be to bring solutions to clinical problems and provide a better grasp of situations encountered in clinical practice. Accordingly, we reviewed previous studies of EC proteome from a clinician's viewpoint. 2. Diagnosis 2.1. Early EC detection The most sensitive tool for the early detection of EC is chromoendoscopy with Lugol's dye [33]. During the 1990s, multiple reports demonstrated that endoscopy provided an easy, inexpensive, and sensitive means of detecting early and late squamous cell neoplasia. However, because of an unfavorable balance of risks, benefits, costs, and psychological burden, the implementation of a national endoscopic screening program has not been justified [34]. Currently, there is a need for new, less invasive, and less expensive screening tools, because most gastroenterology facilities would not be able to support the endoscopic screening program [35]. A simple blood test for early EC detection is superior to endoscopy in terms of cost, testability, and invasiveness. In current practice, the greatest clinical benefit would be potentially offered by novel serum biomarkers with high sensitivity and specificity for EC. With this notion, proteomics studies have been conducted to develop EC biomarkers that would allow early cancer detection in blood instead of tissues.

Fig. 1. Workflow of proteomics application to biomarker development in EC. Proteins in surgical specimens are extracted and subjected to gel-based and antibody-based proteomics. The results are verified by immunohistochemistry, and applied to clinical applications [23,24].

Please cite this article as: N. Uemura, T. Kondo, Current advances in esophageal cancer proteomics, Biochim. Biophys. Acta (2014), http:// dx.doi.org/10.1016/j.bbapap.2014.09.011

N. Uemura, T. Kondo / Biochimica et Biophysica Acta xxx (2014) xxx–xxx

2.1.1. ESCC Fan et al. analyzed serum biomarkers associated with ESCC using the ClinProt profiling technology based on mass spectrometry [36]. Tubulin beta chain, filamin A alpha isoform 1, and cytochrome b-c1 complex subunit 1 were identified as ESCC diagnostic serum biomarkers applicable also to stage I disease (Table 1). Zhang et al. compared protein expression profiles in pre-surgery and post-surgery sera of 17 ESCC patients by 2-DE and matrix-assisted laser desorption/ionization time-offlight mass spectrometry (MALDI-TOF MS) [26]. One of the differentially expressed proteins, clusterin, was found to be downregulated in both cancer tissue and pre-surgery serum, which was validated by RT-PCR and Western blotting, suggesting that clusterin is a candidate serum biomarker for ESCC. Liu et al. used 2-DE to examine tumor proteins that elicit humoral response in ESCC patients [37] and detected autoantibodies to oncogene CDC25B phosphatase in 36.29% of ESCC patients, 8.67% of other cancer patients, and none of the healthy controls. Given that anti-CDC25B antibodies were found in patients with both early and late ESCC stages, these antibodies might have clinical utility in ESCC screening and diagnosis. Fujita et al. examined novel tumor antigens in an ESCC cell line and related autoantibodies in sera of ESCC patients by proteomics [38]. The levels of an autoantibody against heat shock protein Hsp70 appeared to be significantly higher in patients with ESCC than in healthy individuals or patients with gastric or colon cancer, suggesting that anti-Hsp70 autoantibody may have clinical utility as a diagnostic marker for ESCC. 2.1.2. EAC Mechref et al. performed glycosylation profiling of serum samples from patients with EAC, high-grade dysplasia, Barrett's esophagus, and healthy individuals and showed that the changes in the relative intensities of three glycan structures predicted EAC with 94% sensitivity and more than 60% specificity [39], suggesting that comparative EAC glycomics can be used for the identification of EAC candidate biomarkers. The survival rate of EC patients remains low largely because of the absence of effective screening markers for early detection. Because patients with early EC stages benefit from endoscopic treatment or minimally invasive esophagectomy as curative resection [40], it is hoped that novel serum biomarkers for early EC detection, as well as less invasive and cheaper screening tools, can be developed through multicenter validation studies. 2.1.3. Perspectives of biomarkers for early detection Cancer proteomics allows identification of early disease biomarkers with high sensitivity and specificity; however, the biomarker clinical

3

utility should be validated in different populations of EC patients. First, the number of cases in the previous studies was limited, and it is questionable whether high biomarker performance observed in the examined cohort could be reproduced in the hospitals without further validation. Second, the reported biomarkers have moderate diagnostic accuracy, and in screening of a low-prevalence disease, such as EC, many persons can have false-positive test results. As these patients will be monitored by expensive and invasive examinations such as imaging and biopsy, in order to avoid this, the accuracy of biomarker performance should be additionally validated in a low-prevalence population. The adverse consequences of high false-positive rate in EC screening should be thoroughly considered before applying the results of biomarker studies to early disease detection. 2.2. Prediction of lymph node metastasis In EC, lymph node metastasis originates from the superficial cancer and spreads quickly from the neck to the abdomen [41]. The status of lymph node metastasis is one of the most critical parameters that affects prognosis and determines treatment strategy. Computed tomography, magnetic resonance imaging, ultrasonography, endoscopic ultrasonography, positron emission tomography, and other methods have been employed for the diagnostics of nodal metastases. Despite the use of such modern diagnostic modalities, the diagnosis of lymph node metastasis has insufficient accuracy. Stiles et al. reported that most patients with cT2-T3N0M0 cancer, a resectable advanced cancer without clinical lymph node metastases, had pathological lymph node metastases and despite induction therapy, more than 50% had persistent nodal disease [42]. The accurate clinical N staging of EC is difficult, and the improvement in diagnostic accuracy could play a crucial role in selecting adequate treatment strategy. The identification of predictive biomarkers for lymph node metastasis would have important clinical implications and could resolve particular concerns regarding diagnostics of lymph node metastasis. 2.2.1. ESCC Hatakeyama et al. examined the ESCC proteome in 72 laser microdissection samples using two-dimensional difference gel electrophoresis (2D-DIGE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) [43]. Protein spots with intensities statistically different between patients without nodal metastasis and patients with more than five lymph node metastases included cancer-associated factors such as alpha-actinin 4, hnRNP K, periplakin, squamous cell carcinoma antigen 1, NudC, and Hsp60; the latter was increased in tumor tissues almost in parallel with the number of lymph node metastases.

Table 1 Summary of biomarker candidates discovered by proteomics in EC. Purpose

Histology

Protein name

Reference

Early detection

ESCC

Prediction of lymph node metastasis

EAC ESCC

tubulin beta chain, filamin A alpha isoform 1, and cytochrome b-c1 complex subunit 1 clusterin autoantibodies to oncogene CDC25B phosphatase autoantibody against heat shock protein Hsp70 glycan structures alpha-actinin 4, hnRNP K, periplakin, squamous cell carcinoma antigen 1, NudC, and Hsp60 alpha-actinin 4 annexin A2, Cdc42 Hsp27 family proteins, HER2 thioredoxin domain-containing protein 4 precursor and cystathionine gamma-lyase COX protein apolipoprotein A-1, serum amyloid A, and transthyretin Hsp27 C4a and C3a transglutaminase 3 calreticulin and a 78-kDa glucose-regulated protein Hsp27 and HER2 apolipoprotein A-I, serum amyloid A, and transthyretin

36 26 37 38 39 43 44 45 46 53 54 55 56 57 23 59 46 60

Prdiction of response to treatments

Prediction of prognosis

EAC ESCC EAC

ESCC and EAC ESCC EAC ESCC and EAC

Please cite this article as: N. Uemura, T. Kondo, Current advances in esophageal cancer proteomics, Biochim. Biophys. Acta (2014), http:// dx.doi.org/10.1016/j.bbapap.2014.09.011

4

N. Uemura, T. Kondo / Biochimica et Biophysica Acta xxx (2014) xxx–xxx

Fu et al. employed proteomics to analyze protein extracts of 12 ESCC specimens from patients with distinctly different tumor stages [44]. Using 2D-GE and MALDI-TOF MS, they identified 18 proteins differentially expressed in tumors compared to matched surrounding normal tissues; among them, the expression of alpha-actinin 4 was shown to be significantly associated with lymph node metastasis by immunohistochemistry analysis using two-tissue microarray blocks that contained 442 primary tumor samples. Because two independent studies consistently identified alpha-actinin 4, it may be a promising biomarker for nodal metastasis. Other proteins related to lymph node metastasis were identified by Feng et al., who reported that the expression of annexin A2 in ESCCs was significantly downregulated and that of Cdc42 upregulated compared with corresponding normal esophagus mucosa; it was also shown that their levels significantly correlated with nodal metastasis [45]. The authors proposed that the aberrant expression of annexin A2 and Cdc42 played a role in the carcinogenesis and metastasis of ESCC. 2.2.2. EAC Berg et al. analyzed expression profiles of 17 cancer-related signaling proteins in a series of 87 formalin fixed and paraffin-embedded EAC tissue samples using a reverse phase protein array [46]. They found a molecular subtype of EAC characterized by low levels of the Hsp27 family proteins and high expression of the human epidermal growth factor receptor 2 (HER2) family members. Patients with this EAC subtype were more likely to have lymph node and distant metastases and short overall survival. Compared with all other EACs, this EAC subtype included significantly more cases positive for pN (lymph node status) and cM (occurrence of distant metastasis): 67% and 15%, respectively. Another new EAC subtype had the opposite pattern: low expression of HER2 proteins and high expression of Hsp27 family members, few pN-positive (21%), and no cM-positive (0%) cases. 2.2.3. Perspectives of biomarkers for lymph node metastasis Cancer proteomics provided promising predictive biomarkers for lymph node metastasis. However, the benefit of these biomarkers remains unproven in clinical settings. First, the significance of correlation between the biomarkers and nodal metastasis should be validated in larger cohorts in multiple institutions. Second, therapeutic strategies for the treatment of biomarker-positive but otherwise negative cases should be established by randomized trials. Nodal metastases undetectable by imaging tests are very small, and the presence of such micrometastases normally has no impact on the prognosis for ESCC patients [47]. For the patients with image-negative nodal micrometastases who are positive in biomarker and pathology tests, the prognostic value of other clinical examinations must be considered when planning for pre-operative therapy. 2.3. Therapy response prediction Patients at the early EC stage can be cured by endoscopic or surgical treatment. However, the patients seen at the hospital usually have a developed disease, and a number of multimodal approaches to the treatment of late EC have been developed. Neoadjuvant chemotherapy, alone or in combination with radiotherapy (CRT), became a standard approach to locally advanced EC [48]. Although favorable response to multimodal treatment results in better clinical outcome, randomized trials of different neoadjuvant regimens for locally advanced cancers have shown modest increase in survival [5–11]. Only those patients who achieved complete histopathologic response seem to significantly benefit from neoadjuvant therapy, whereas most of the treated patients (60–70%) did not respond well and experienced severe adverse effects [10,12]; treatment responses may vary even among patients with the same clinical stage of the disease. The problem is that nonresponsive patients may lose the option of surgical resection after ineffective chemotherapy [49], and their prognosis has been found inferior to

that of patients treated by surgery alone [50]. Thus, to avoid potential morbidity due to ineffective treatment and prevent further disease progression, it is essential to perform accurate risk stratification of EC patients. The clinical significance of response predictions for patients with unresectable EC can be interpreted in a similar fashion. Nonresponding patients with unresectable EC should receive a different treatment at early stages. In this context, the identification of predictive markers is important for the risk stratifications and individualization of multimodality treatments for patients with advanced EC [51]. 2.3.1. ESCC Hayashida et al. used SELDI-MS to analyze proteomic profiles in 27 serum samples from untreated ESCC patients and predict the efficacy of preoperative chemoradiotherapy [52]. The authors found that out of 859 protein peaks, a set of four (at 7,420, 9,112, 17,123, and 12,867 m/z) could be used to distinguish responders from nonresponders with a sensitivity of 100% and 93.3% in the training and validation sets, respectively. Wen et al. investigated the mechanisms of drug resistance in ESCC by comparing expression profiles of a multidrug-resistant ESCC cell line EC 109/CDDP with its parental drug-sensitive cell line using 2D-GE and MALDI-TOF MS [53]. The identified 44 differentially expressed proteins were involved in endoplasmic reticulum stress response, metabolic processes, DNA replication and repair, nucleotide binding, calcium binding, and cytoskeleton formation; among them, thioredoxin domain-containing protein 4 precursor and cystathionine gamma-lyase were validated by western blot and RT-PCR. 2.3.2. EAC In a study of 23 EAC pre-therapeutic biopsy samples, Aichler et al. analyzed proteomic changes associated with response to chemotherapy by MALDI imaging mass spectrometry and LC-MS/MS, and showed that clinical response to cisplatin was associated with defects in cancer cell mitochondrial respiratory chain caused by the loss of specific cytochrome c oxidase (COX) subunits [54]. These results were further validated in an independent study showing that reduced COX protein expression prior to treatment correlated with chemotherapeutic sensitivity and favorable clinical outcomes, whereas unchanged COX expression indicated chemoresistance. Plasma protein profiling in mice with OE19 EAC xenografts that were treated with clinically relevant chemotherapeutic agents epirubicin, cisplatin, or 5-fluorouracil resulted in the identification of apolipoprotein A-1, serum amyloid A, and transthyretin as candidate biomarkers of response to chemotherapy [55]. However, although the results were confirmed in clinical samples, the number of patients with evident pathological response was relatively small; the biomarker pattern could not be compared with other indicators of clinical response and required further validation. To identify predictive biomarkers, Langer et al. analyzed pretherapeutic protein expression profiles in tumor biopsy specimens of 34 EAC patients treated with neoadjuvant chemotherapy [56]. The authors found that the levels of cellular stress response-associated Hsp27 and Hsp60, glucose-regulated proteins 94 and 78, and a number of cytoskeletal proteins differed significantly between responders and nonresponders. Immunohistochemistry and gene expression analysis confirmed a significant association between low Hsp27 expression and resistance to neoadjuvant chemotherapy, suggesting that chemosensitivity may be related to stress-activated inflammatory mechanisms. 2.3.3. ESCC and EAC Maher et al. examined proteomic profiles of ESCC and EAC patients using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) and ELISA [57]. By comparing pre-treatment serum samples from 16 poor responders and 15 good responders, it was found that higher serum levels of complement factors

Please cite this article as: N. Uemura, T. Kondo, Current advances in esophageal cancer proteomics, Biochim. Biophys. Acta (2014), http:// dx.doi.org/10.1016/j.bbapap.2014.09.011

N. Uemura, T. Kondo / Biochimica et Biophysica Acta xxx (2014) xxx–xxx

C4a and C3a were significantly associated with favorable CRT response. The leave-one-out cross-validation analysis confirmed that C4a and C3a could predict the response to neoadjuvant CRT with a sensitivity and specificity of 78.6% and 83.3%, respectively. 2.3.4. Perspectives of treatment response predictive biomarkers Cancer proteomics has provided promising predictive biomarkers for multimodal therapies. Therapeutic resistance is multi-factorial and is associated with several cell signaling mechanisms, including mitochondrial redox [53], respiration [54], and cellular stress response pathways [56]. Proteomics can be a powerful tool in identifying protein biomarkers associated with resistance to anticancer therapy [18]. As EC is a clinically diverse disease and treatment modalities are not fully standardized among hospitals, extensive multi-institutional, large-scale studies are required to validate the clinical utility of predictive biomarker candidates. It is also urgent to develop novel therapeutic approaches for patients with biomarker-predicted resistance to standardized treatment regimens. Thorough investigation of the mechanisms underlying functional association of biomarker proteins with clinical parameters should provide a key to the development of novel effective clinical applications to treat CRT-resistant EC. 2.4. Prognostic prediction Prognostic prediction in EC has important clinical implications because it critically affects decisions regarding the treatment strategy and follow-up schedule. Patients with good prognosis do not require intensive adjuvant therapy or routine follow-up, whereas those with poor prognosis must receive strong adjuvant treatment and be frequently examined. Thus, an accurate risk stratification of EC patients is of paramount importance to prevent further disease progression and reduce morbidity due to ineffective/unnecessary clinical intervention. 2.4.1. ESCC Uemura et al. compared proteomic profiles of ESCC patients with favorable and poor prognosis using 2D-DIGE and mass spectrometry [23] and identified 18 differentially expressed proteins. Of them, transglutaminase 3 expression was validated in 76 primary tumor samples by immunohistochemistry and found to be inversely correlated with shorter patient survival. In search of ESCC prognostic serum biomarkers using SELDI-TOF MS, Jiang et al. found no difference between protein profiles patients with more than 2-year and less than 2-year survival [58]. Furthermore, only 1 protein peak differed significantly between stage III disease patients stratified by this survival criterion. However, Du et al., using 2-DE and MALDI-TOF or LC-ESI MS, found 22 proteins differentially expressed in ESCCs compared to tumor-adjacent normal esophageal tissues [59] and showed that high expression of calreticulin and a 78-kDa glucose-regulated protein were correlated with poor prognosis. 2.4.2. EAC Berg et al. reported that a particular EAC molecular subtype characterized by low levels of the Hsp27 proteins and high HER2 expression correlated with nodal and distant metastases, and short overall survival [46]. 2.4.3. ESCC and EAC Kelly et al. used SELDI-TOF MS to examine EC prognostic biomarkers in plasma of 20 patients with EAC, 1 with ESCC, 2 with poorly differentiated carcinomas, and 1 with severe dysplasia [60]. Apolipoprotein A-I, serum amyloid A, and transthyretin in pre-treatment plasma samples were found to be associated with disease-free survival and overall survival. The authors also reported the correlation of these three proteins with response to chemotherapy in a mouse xenograft model [55]. These data suggest that plasma apolipoprotein A-I, serum amyloid A,

5

and transthyretin are promising candidate prognostic biomarkers that should be validated in EC clinical studies. 2.4.4. Perspectives of prognostic biomarkers Cancer proteomics provided promising prognostic biomarkers for EC. In clinical practice, post-operative EC prognosis has been made based on multiple clinicopathological parameters [61,62]; however, novel biomarkers will be beneficial in the cases when thus made prediction was not confirmed. Clinicopathological characteristics can directly reflect EC malignancy, but more accurate prognosis could be obtained by the combination of traditional clinical parameters with novel molecular biomarkers identified by proteomics. By conducting subgroup analysis based on the state of lymph node metastasis, a significant clinicopathological prognostic factor, Uemura et al. succeeded in discovering a reliable prognostic biomarker [23]. Similarly, Jiang et al. identified a prognostic biomarker by correlation with EC clinical stage [58]. Patients' stratification according to clinical background would allow compensation for the heterogeneity of molecular mechanisms involved in EC and provide a potential to increase the sensitivity and specificity of EC prognostic biomarkers. 3. Treatment: Novel targets and chemotherapeutic drugs The prediction of responses to CRT may help reduce the number of unnecessary treated patients. However, without effective therapies to be offered to nonresponders, the prediction of CRT outcome would be tantamount to abandoning nonresponders to their fate. Significant improvement in overall EC outcome has to be parallel to that for CRT-resistant population; accordingly, there is an urgent need for new effective therapeutic approaches for patients unresponsive to conventional treatment. The identification of reliable prognostic biomarkers through proteomic approaches may identify novel drug targets and lead to the development of new more effective therapeutic strategies for CRT-resistant EC patients [63]. 3.1. ESCC Using 2-DE, Fu et al. compared proteomic profiles of ESCC tumors at different stages and adjacent normal esophageal tissues [44] and identified two proteins, alpha-actinin 4 and a 67-kDa laminin receptor associated with ESCC progression (Table 2). The authors suggested that these candidate biomarkers might be useful for prognostic evaluation, molecular classification, and therapeutic targeting of ESCCs. 3.2. EAC In the analysis of proteomic changes associated with EAC response to chemotherapy, Aichler et al. discovered that favorable response of cancer cells to cisplatin was related to the defects in mitochondrial respiratory complexes caused by the loss of COX subunits [54]. The authors noted that the association between cancer cell respiration and chemosensitivity was consistent with anticancer therapeutics that target the mitochondrial electron transport chain. Vona-Davis et al. used 2-DE to examine the response of Barrett's cancer cells to a novel therapeutic agent keyhole limpet hemocyanin (KLH) [64], an immunostimulatory oxygen-carrying metalloprotein from a marine mollusk Megathura crenulata, which inhibits the growth of Barrett's EC cell lines through both apoptotic and nonapoptotic mechanisms [65,66]. Proteomic profiling showed that KLH downregulated proteins associated with glycolysis and protein synthesis, while upregulating those related to oxidative stress (the Hsp70 proteins and UDP-glucose 6-dydrogenase), indicating the molecular mechanisms of KLH anticancer effects. These results suggest that KLH used as an adjuvant or topical therapy is a promising drug in the treatment of Barrett's adenocarcinoma.

Please cite this article as: N. Uemura, T. Kondo, Current advances in esophageal cancer proteomics, Biochim. Biophys. Acta (2014), http:// dx.doi.org/10.1016/j.bbapap.2014.09.011

6

N. Uemura, T. Kondo / Biochimica et Biophysica Acta xxx (2014) xxx–xxx

Table 2 Summary of key proteins on treatment and molecular mechanisms discovered by proteomics in EC. Purpose

Histology

Protein name

Reference

Novel melecular target

ESCC EAC

Novel chemotheraupeutic drug Elucidation of molecular mechanism underlying carcinogenesis

EAC EC cell line EAC

44 54 67 64 80 81

Elucidation of molecular mechanism underlying histological differentiation

ESCC

alpha-actinin 4 and a 67-kDa laminin receptor COX protein migration-stimulating factor keyhole limpet hemocyanin brain and reproductive organ-expressed protein Rho GDP dissociation inhibitor 2, alpha-enolase, lamin A/C, and nucleoside-diphosphate kinase A cathepsin D and aldo-ketoreductases 1C2 and 1B10 stratifin, prohibitin, and squamous cell carcinoma antigen 1 annexin A2 cathepsin D

Hu et al. screened a mouse-derived antibody library generated against EC endothelial cells to identify proteins that participate in tumor angiogenesis [67]. Through selection of monoclonal antibodies that reacted with EC cell-surface antigens and influenced tumor cell behavior, they identified the antibody against migration-stimulating factor (MSF), which significantly suppressed tumor growth through inhibition of human tumor-related angiogenesis. These results indicate that MSF may be a target for the anti-angiogenic treatment of esophageal cancer. 3.3. Perspectives of novel therapeutics identified by EC proteomics Protein profiling resulted in the identification of novel therapeutic targets, which can lead to a significant improvement of EC prognosis, especially for nonresponders diagnosed by predictive protein biomarkers. In other solid tumors, several targeted therapeutic agents, such as bevacizumab and cetuximab in colorectal cancer [68], lapatinib and trastuzumabin in breast cancer [69,70], and imatinib and sunitinib in gastrointestinal stromal tumor [71,72] have been widely used in clinical practice. In EC, the addition of anti-HER2 antibody trastuzumab to the platinum and fluoropyrimidine doublet regimen is adopted as the standard care for HER2-positive tumors of the esophagogastric junction [73] . Therapies targeting epidermal growth factor receptor and vascular endothelial growth factor remain under active investigation but have yet to definitively demonstrate clinically significant benefits for EC patients [74]. Multiple molecular targets remain of interest in EC, including mammalian target of rapamycin, c-MET, insulin-like growth factor, and cytotoxic T-lymphocyte antigen 4 [74]. Clinical application of targeted therapies in EC is less advanced than in other solid tumors, and further proteome studies are required to identify more promising molecules. 4. Molecular mechanisms Elucidation of disease molecular mechanisms is directly linked to the development of novel diagnostic biomarkers and therapeutic targets that would bring significant benefits to cancer patients. In the molecular mechanistic analysis, proteomics provides tools essential to the discovery of signaling paradigms that trigger tumor initiation and promote cancer progression. The transformation from normal esophageal epithelium to invasive EC is a multistep process caused by accumulation of multiple genetic alterations [75], mainly involving the Wnt, cell cycle, and Notch pathways [76]. Despite many genetic studies, the exact molecular mechanisms underlying carcinogenesis and tumor progression in EC remain unclear [77–79], and comprehensive protein expression profiling provided by cancer proteomics should contribute to our understanding of EC biology. Proteomics has identified numerous intriguing biomarkers for early cancer diagnostics and prediction of nodal metastasis, treatment response, and prognosis, which are critically involved in each process and require further mechanistic characterization.

82 83 84 85

4.1. Carcinogenesis To explore carcinogenic mechanisms through protein profiling, Chen et al. examined soluble proteins differentially expressed in EC and non-cancerous cells using 2-DE and MALDI-TOF MS [80]. Among 20 differentially expressed protein spots, brain and reproductive organ-expressed (BRE) protein was selected and functionally analyzed using small interference RNA (Table 2). BRE silencing upregulated tumor-suppressor p53 and downregulated prohibitin, cyclin A, and CDK2, suggesting that BRE plays an important role in mediating antiapoptotic and proliferative responses in EC cells. The insight into potential mechanisms underlying the progression from Barrett's metaplasia to EAC was gained by Zhao et al. [81], who found that Rho GDP dissociation inhibitor 2, alpha-enolase, lamin A/C, and nucleoside-diphosphate kinase A were upregulated at both mRNA and protein levels in EAC compared to Barrett's metaplasia. The results suggest that the identified proteins play a role in EAC development and may be candidate biomarkers of the progression from Barrett's metaplasia to EAC. Breton et al. used 2-DE and MALDI-TOF MS to examine proteomic profiles of 10 esophageal cell lines representing distinct stages in EAC development [82]. Among 33 differentially expressed proteins, the increased levels of cathepsin D and aldo-ketoreductases 1C2 and 1B10 in metaplastic and dysplastic cell lines were confirmed by Western blotting and qRT-PCR. The expression patterns of these proteins analyzed from esophageal epithelium from patients with non-erosive and erosive gastroesophageal reflux disease, Barrett's esophagus, and EAC, suggest the contribution to EAC development through effects on apoptosis, transport of bile acids, and retinoid metabolism. Further mechanistic and clinical investigations are required to fully elucidate the role of these molecules in EAC. 4.2. Histological differentiation Using 2-DE and MALDI-TOF MS, Qi et al. examined protein changes associated with the degree of ESCC differentiation [83] and found that the expression of stratifin, prohibitin, and squamous cell carcinoma antigen 1 directly correlated with ESCC differentiation. The same group also reported that the expression of annexin A2 was step-wise downregulated during malignant transformation of epithelial cells [84]: in poorly differentiated ESCCs, annexin A2 was either not detected (46%) or had low expression levels (36%). Furthermore, it has been shown that overexpression of cathepsin D inversely correlated with ESCC differentiation [85]. The significant changes in the expression of these proteins may indicate that many pathways are involved in ESCC dedifferentiation. 4.3. Perspectives of proteomics approach to EC molecular mechanisms Cancer proteomics has resulted in the identification of proteins involved in cancer initiation and progression; further investigation of

Please cite this article as: N. Uemura, T. Kondo, Current advances in esophageal cancer proteomics, Biochim. Biophys. Acta (2014), http:// dx.doi.org/10.1016/j.bbapap.2014.09.011

N. Uemura, T. Kondo / Biochimica et Biophysica Acta xxx (2014) xxx–xxx

the identified molecules may provide deeper understanding of EC-related mechanisms and contribute to the development of novel therapeutic strategies. However, the current state of cancer proteomics indicates fundamental problems and the need for improvement. Although proteomics provides a unique opportunity of generating comprehensive information regarding cellular proteome, it has not been fully realized in cancer research. At present, cancer proteomics focuses on a limited portion of proteome, thus excluding some potentially important molecules, and consequently, it has not yet provided pathway-wide and molecular family-wide analyses. Furthermore, in EC, proteomics has been mostly applied to analyze expression levels, leaving out important proteome features such as posttranslational modifications, molecular interactions, activity, and localization, which should be extensively examined in association with EC clinical and pathological features. Finally, although cancer proteomics provides high-throughput assessment of protein expression, subsequent functional analysis remains labor-intense and low-scale. As a consequence, only a small number of proteins are further investigated, and potentially valuable molecules may be filtered through functional assessment. All these issues should be resolved by continuous technological advances.

[7]

[8]

[9] [10]

[11]

[12]

[13] [14]

[15]

5. Conclusions Cancer proteomics has provided a number of promising diagnostic biomarkers and novel therapeutic targets, as well as intriguing proteins underlying the molecular mechanisms of carcinogenesis and progression of EC. Although individual proteins seem to be promising, the number of clinical samples examined by proteomics has been limited, and multi-institutional validation studies are required to launch clinical trials of biomarkers and therapeutic targets. In parallel with confirming proteomic data, biomarker-based therapeutic strategies integrating the diverse clinical features of ES should be developed. Current studies have shed a light on limited aspects of the EC proteome, and comprehensive analysis will be possible with further technological progress. For example, novel antibody production engineering systems that allow generate appropriate antibody for immunohistochemistry will facilitate the discovery of biomarker candidates as well as the validation study. In addition to improving the performance of proteomic modalities, interdisciplinary collaboration is essential to obtain research data that will benefit patients with EC. Conflicts of interest The authors report no conflicts of interest. Role of the funding source No funding was received for this review.

[16] [17]

[18]

[19]

[20] [21]

[22]

[23]

[24]

[25] [26]

[27]

References [1] A. Jemal, F. Bray, M.M. Center, J. Ferlay, E. Ward, D. Forman, Global cancer statistics, CA Cancer J. Clin. 61 (2011) 69–90. [2] T.W. Rice, V.W. Rusch, C. Apperson-Hansen, M.S. Allen, L.Q. Chen, J.G. Hunter, K.A. Kesler, S. Law, T.E. Lerut, C.E. Reed, J.A. Salo, W.J. Scott, S.G. Swisher, T.J. Watson, E.H. Blackstone, Worldwide esophageal cancer collaboration, Dis. Esophagus 22 (2009) 1–8. [3] Y. Shimizu, H. Tsukagoshi, M. Fujita, M. Hosokawa, M. Kato, M. Asaka, Long-term outcome after endoscopic mucosal resection in patients with esophageal squamous cell carcinoma invading the muscularis mucosae or deeper, Gastrointest. Endosc. 56 (2002) 387–390. [4] T.W. Rice, G. Zuccaro Jr., D.J. Adelstein, L.A. Rybicki, E.H. Blackstone, J.R. Goldblum, Esophageal carcinoma: depth of tumor invasion is predictive of regional lymph node status, Ann. Thorac. Surg. 65 (1998) 787–792. [5] J.D. Urschel, H. Vasan, A meta-analysis of randomized controlled trials that compared neoadjuvant chemoradiation and surgery to surgery alone for resectable esophageal cancer, Am. J. Surg. 185 (2003) 538–543. [6] I.G. Kaklamanos, G.R. Walker, K. Ferry, D. Franceschi, A.S. Livingstone, Neoadjuvant treatment for resectable cancer of the esophagus and the gastroesophageal

[28]

[29]

[30]

[31]

[32]

7

junction: a meta-analysis of randomized clinical trials, Ann. Surg. Oncol. 10 (2003) 754–761. R.A. Malthaner, R.K. Wong, R.B. Rumble, L. Zuraw, C. Members of the Gastrointestinal Cancer Disease Site Group of Cancer Care Ontario's Program in Evidence-based, Neoadjuvant or adjuvant therapy for resectable esophageal cancer: a systematic review and meta-analysis, BMC Med. 2 (2004) 35. F. Fiorica, D. Di Bona, F. Schepis, A. Licata, L. Shahied, A. Venturi, A.M. Falchi, A. Craxi, C. Camma, Preoperative chemoradiotherapy for oesophageal cancer: a systematic review and meta-analysis, Gut 53 (2004) 925–930. S.E. Greer, P.P. Goodney, J.E. Sutton, J.D. Birkmeyer, Neoadjuvant chemoradiotherapy for esophageal carcinoma: a meta-analysis, Surgery 137 (2005) 172–177. V. Gebski, B. Burmeister, B.M. Smithers, K. Foo, J. Zalcberg, J. Simes, G. Australasian Gastro-Intestinal Trials, Survival benefits from neoadjuvant chemoradiotherapy or chemotherapy in oesophageal carcinoma: a meta-analysis, Lancet Oncol. 8 (2007) 226–234. X.H. Xu, X.H. Peng, P. Yu, X.Y. Xu, E.H. Cai, P. Guo, K. Li, Neoadjuvant chemotherapy for resectable esophageal carcinoma: a meta-analysis of randomized clinical trials, Asian Pac. J. Cancer Prev. 13 (2012) 103–110. N.P. Nguyen, S.P. Krafft, V. Vinh-Hung, P. Vos, F. Almeida, S. Jang, M. Ceizyk, A. Desai, R. Davis, R. Hamilton, H. Modarresifar, D. Abraham, L. Smith-Raymond, Feasibility of tomotherapy to reduce normal lung and cardiac toxicity for distal esophageal cancer compared to three-dimensional radiotherapy, Radiother. Oncol. 101 (2011) 438–442. M. Tyers, M. Mann, From genomics to proteomics, Nature 422 (2003) 193–197. G. Chen, T.G. Gharib, C.C. Huang, J.M. Taylor, D.E. Misek, S.L. Kardia, T.J. Giordano, M.D. Iannettoni, M.B. Orringer, S.M. Hanash, D.G. Beer, Discordant protein and mRNA expression in lung adenocarcinomas, Mol. Cell. Proteomics 1 (2002) 304–313. S. Varambally, J. Yu, B. Laxman, D.R. Rhodes, R. Mehra, S.A. Tomlins, R.B. Shah, U. Chandran, F.A. Monzon, M.J. Becich, J.T. Wei, K.J. Pienta, D. Ghosh, M.A. Rubin, A.M. Chinnaiyan, Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression, Cancer Cell 8 (2005) 393–406. S.P. Gygi, Y. Rochon, B.R. Franza, R. Aebersold, Correlation between protein and mRNA abundance in yeast, Mol. Cell. Biol. 19 (1999) 1720–1730. R.E. Banks, M.J. Dunn, D.F. Hochstrasser, J.C. Sanchez, W. Blackstock, D.J. Pappin, P.J. Selby, Proteomics: new perspectives, new biomedical opportunities, Lancet 356 (2000) 1749–1756. L. Smith, M.J. Lind, K.J. Welham, L. Cawkwell, G. Cancer Biology Proteomics, Cancer proteomics and its application to discovery of therapy response markers in human cancer, Cancer 107 (2006) 232–241. F. Sabounchi-Schutt, J. Astrom, I. Olsson, A. Eklund, J. Grunewald, B. Bjellqvist, An immobiline DryStrip application method enabling high-capacity two-dimensional gel electrophoresis, Electrophoresis 21 (2000) 3649–3656. M. Unlu, M.E. Morgan, J.S. Minden, Difference gel electrophoresis: a single gel method for detecting changes in protein extracts, Electrophoresis 18 (1997) 2071–2077. R. Tonge, J. Shaw, B. Middleton, R. Rowlinson, S. Rayner, J. Young, F. Pognan, E. Hawkins, I. Currie, M. Davison, Validation and development of fluorescence twodimensional differential gel electrophoresis proteomics technology, Proteomics 1 (2001) 377–396. T. Kondo, M. Seike, Y. Mori, K. Fujii, T. Yamada, S. Hirohashi, Application of sensitive fluorescent dyes in linkage of laser microdissection and two-dimensional gel electrophoresis as a cancer proteomic study tool, Proteomics 3 (2003) 1758–1766. N. Uemura, Y. Nakanishi, H. Kato, S. Saito, M. Nagino, S. Hirohashi, T. Kondo, Transglutaminase 3 as a prognostic biomarker in esophageal cancer revealed by proteomics, Int. J. Cancer 124 (2009) 2106–2115. N. Uemura, Y. Nakanishi, H. Kato, M. Nagino, S. Hirohashi, T. Kondo, Antibody-based proteomics for esophageal cancer: identification of proteins in the nuclear factorkappaB pathway and mitotic checkpoint, Cancer Sci. 100 (2009) 1612–1622. Y.J. Qi, W.X. Chao, J.F. Chiu, An overview of esophageal squamous cell carcinoma proteomics, J. Proteome 75 (2012) 3129–3137. L.Y. Zhang, W.T. Ying, Y.S. Mao, H.Z. He, Y. Liu, H.X. Wang, F. Liu, K. Wang, D.C. Zhang, Y. Wang, M. Wu, X.H. Qian, X.H. Zhao, Loss of clusterin both in serum and tissue correlates with the tumorigenesis of esophageal squamous cell carcinoma via proteomics approaches, World J. Gastroenterol. 9 (2003) 650–654. G. Zhou, H. Li, D. DeCamp, S. Chen, H. Shu, Y. Gong, M. Flaig, J.W. Gillespie, N. Hu, P.R. Taylor, M.R. Emmert-Buck, L.A. Liotta, E.F. Petricoin III, Y. Zhao, 2D differential in-gel electrophoresis for the identification of esophageal scans cell cancer-specific protein markers, Mol. Cell. Proteomics 1 (2002) 117–124. X. Chen, N. Li, S. Wang, J. Hong, M. Fang, J. Yousselfson, P. Yang, R.A. Newman, R.A. Lubet, C.S. Yang, Aberrant arachidonic acid metabolism in esophageal adenocarcinogenesis, and the effects of sulindac, nordihydroguaiaretic acid, and alpha-difluoromethylornithine on tumorigenesis in a rat surgical model, Carcinogenesis 23 (2002) 2095–2102. C. Lepage, B. Rachet, V. Jooste, J. Faivre, M.P. Coleman, Continuing rapid increase in esophageal adenocarcinoma in England and Wales, Am. J. Gastroenterol. 103 (2008) 2694–2699. H. Pohl, H.G. Welch, The role of overdiagnosis and reclassification in the marked increase of esophageal adenocarcinoma incidence, J. Natl. Cancer Inst. 97 (2005) 142–146. R.P. Merkow, K.Y. Bilimoria, M.D. McCarter, W.B. Chow, C.Y. Ko, D.J. Bentrem, Use of multimodality neoadjuvant therapy for esophageal cancer in the United States: assessment of 987 hospitals, Ann. Surg. Oncol. 19 (2012) 357–364. E. Bollschweiler, R. Metzger, U. Drebber, S. Baldus, D. Vallbohmer, M. Kocher, A.H. Holscher, Histological type of esophageal cancer might affect response to neo-adjuvant radiochemotherapy and subsequent prognosis, Ann. Oncol. 20 (2009) 231–238.

Please cite this article as: N. Uemura, T. Kondo, Current advances in esophageal cancer proteomics, Biochim. Biophys. Acta (2014), http:// dx.doi.org/10.1016/j.bbapap.2014.09.011

8

N. Uemura, T. Kondo / Biochimica et Biophysica Acta xxx (2014) xxx–xxx

[33] A.B. Lopes, R.B. Fagundes, Esophageal squamous cell carcinoma—precursor lesions and early diagnosis, World J. Gastrointest. Endosc. 4 (2012) 9–16. [34] L.B. Gerson, P.W. Groeneveld, G. Triadafilopoulos, Cost-effectiveness model of endoscopic screening and surveillance in patients with gastroesophageal reflux disease, Clin. Gastroenterol. Hepatol. 2 (2004) 868–879. [35] E.L. Bird-Lieberman, R.C. Fitzgerald, Early diagnosis of oesophageal cancer, Br. J. Cancer 101 (2009) 1–6. [36] N.J. Fan, C.F. Gao, X.L. Wang, Tubulin beta chain, filamin A alpha isoform 1, and cytochrome b-c1 complex subunit 1 as serological diagnostic biomarkers of esophageal squamous cell carcinoma: a proteomics study, OMICS J. Integr. Biol. 17 (2013) 215–223. [37] W.L. Liu, G. Zhang, J.Y. Wang, J.Y. Cao, X.Z. Guo, L.H. Xu, M.Z. Li, L.B. Song, W.L. Huang, M.S. Zeng, Proteomics-based identification of autoantibody against CDC25B as a novel serum marker in esophageal squamous cell carcinoma, Biochem. Biophys. Res. Commun. 375 (2008) 440–445. [38] Y. Fujita, T. Nakanishi, Y. Miyamoto, M. Hiramatsu, H. Mabuchi, A. Miyamoto, A. Shimizu, T. Takubo, N. Tanigawa, Proteomics-based identification of autoantibody against heat shock protein 70 as a diagnostic marker in esophageal squamous cell carcinoma, Cancer Lett. 263 (2008) 280–290. [39] Y. Mechref, A. Hussein, S. Bekesova, V. Pungpapong, M. Zhang, L.E. Dobrolecki, R.J. Hickey, Z.T. Hammoud, M.V. Novotny, Quantitative serum glycomics of esophageal adenocarcinoma and other esophageal disease onsets, J. Proteome Res. 8 (2009) 2656–2666. [40] S.S. Biere, M.I. van Berge Henegouwen, K.W. Maas, L. Bonavina, C. Rosman, J.R. Garcia, S.S. Gisbertz, J.H. Klinkenbijl, M.W. Hollmann, E.S. de Lange, H.J. Bonjer, D.L. van der Peet, M.A. Cuesta, Minimally invasive versus open oesophagectomy for patients with oesophageal cancer: a multicentre, open-label, randomised controlled trial, Lancet 379 (2012) 1887–1892. [41] Y. Tachimori, Y. Nagai, N. Kanamori, N. Hokamura, H. Igaki, Pattern of lymph node metastases of esophageal squamous cell carcinoma based on the anatomical lymphatic drainage system, Dis. Esophagus 24 (2011) 33–38. [42] B.M. Stiles, F. Mirza, A. Coppolino, J.L. Port, P.C. Lee, S. Paul, N.K. Altorki, Clinical T2-T3N0M0 esophageal cancer: the risk of node positive disease, Ann. Thorac. Surg. 92 (2011) 491–496 (discussion 496–498). [43] H. Hatakeyama, T. Kondo, K. Fujii, Y. Nakanishi, H. Kato, S. Fukuda, S. Hirohashi, Protein clusters associated with carcinogenesis, histological differentiation and nodal metastasis in esophageal cancer, Proteomics 6 (2006) 6300–6316. [44] L. Fu, Y.R. Qin, D. Xie, H.Y. Chow, S.M. Ngai, D.L. Kwong, Y. Li, X.Y. Guan, Identification of alpha-actinin 4 and 67 kDa laminin receptor as stage-specific markers in esophageal cancer via proteomic approaches, Cancer 110 (2007) 2672–2681. [45] J.G. Feng, Q. Liu, X. Qin, Y.H. Geng, S.T. Zheng, T. Liu, I. Sheyhidin, X.M. Lu, Clinicopathological pattern and Annexin A2 and Cdc42 status in patients presenting with differentiation and lymphnode metastasis of esophageal squamous cell carcinomas, Mol. Biol. Rep. 39 (2012) 1267–1274. [46] D. Berg, C. Wolff, R. Langer, T. Schuster, M. Feith, J. Slotta-Huspenina, K. Malinowsky, K.F. Becker, Discovery of new molecular subtypes in oesophageal adenocarcinoma, PLoS One 6 (2011) e23985. [47] F. Sato, Y. Shimada, Z. Li, G. Watanabe, M. Maeda, M. Imamura, Lymph node micrometastasis and prognosis in patients with oesophageal squamous cell carcinoma, Br. J. Surg. 88 (2001) 426–432. [48] K. Almhanna, R. Shridhar, K.L. Meredith, Neoadjuvant or adjuvant therapy for resectable esophageal cancer: is there a standard of care? Cancer Control 20 (2013) 89–96. [49] N.S. Blencowe, A.G. McNair, C.R. Davis, S.T. Brookes, J.M. Blazeby, Standards of outcome reporting in surgical oncology: a case study in esophageal cancer, Ann. Surg. Oncol. 19 (2012) 4012–4018. [50] G.W. Dittrick, J.M. Weber, R. Shridhar, S. Hoffe, M. Melis, K. Almhanna, J. Barthel, J. McLoughlin, R.C. Karl, K.L. Meredith, Pathologic nonresponders after neoadjuvant chemoradiation for esophageal cancer demonstrate no survival benefit compared with patients treated with primary esophagectomy, Ann. Surg. Oncol. 19 (2012) 1678–1684. [51] D. Vallbohmer, A.H. Holscher, S. DeMeester, T. DeMeester, J. Salo, J. Peters, T. Lerut, S.G. Swisher, W. Schroder, E. Bollschweiler, W. Hofstetter, A multicenter study of survival after neoadjuvant radiotherapy/chemotherapy and esophagectomy for ypT0N0M0R0 esophageal cancer, Ann. Surg. 252 (2010) 744–749. [52] Y. Hayashida, K. Honda, Y. Osaka, T. Hara, T. Umaki, A. Tsuchida, T. Aoki, S. Hirohashi, T. Yamada, Possible prediction of chemoradiosensitivity of esophageal cancer by serum protein profiling, Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 11 (2005) 8042–8047. [53] J. Wen, B. Zheng, Y. Hu, X. Zhang, H. Yang, Y. Li, C.Y. Zhang, K.J. Luo, X. Zang, Y.F. Li, X.Y. Guan, J.H. Fu, Comparative proteomic analysis of the esophageal squamous carcinoma cell line EC109 and its multi-drug resistant subline EC109/CDDP, Int. J. Oncol. 36 (2010) 265–274. [54] M. Aichler, M. Elsner, N. Ludyga, A. Feuchtinger, V. Zangen, S.K. Maier, B. Balluff, C. Schone, L. Hierber, H. Braselmann, S. Meding, S. Rauser, H. Zischka, M. Aubele, M. Schmitt, M. Feith, S.M. Hauck, M. Ueffing, R. Langer, B. Kuster, H. Zitzelsberger, H. Hofler, A.K. Walch, Clinical response to chemotherapy in oesophageal adenocarcinoma patients is linked to defects in mitochondria, J. Pathol. 230 (2013) 410–419. [55] P. Kelly, V. Appleyard, K. Murray, F. Paulin, D. Lamont, L. Baker, S. Suttie, D. Exon, A. Thompson, Detection of oesophageal cancer biomarkers by plasma proteomic profiling of human cell line xenografts in response to chemotherapy, Br. J. Cancer 103 (2010) 232–238. [56] R. Langer, K. Ott, K. Specht, K. Becker, F. Lordick, M. Burian, K. Herrmann, A. Schrattenholz, M.A. Cahill, M. Schwaiger, H. Hofler, H.J. Wester, Protein expression profiling in esophageal adenocarcinoma patients indicates association of heat-shock protein 27 expression and chemotherapy response, Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 14 (2008) 8279–8287.

[57] S.G. Maher, D.T. McDowell, B.C. Collins, C. Muldoon, W.M. Gallagher, J.V. Reynolds, Serum proteomic profiling reveals that pretreatment complement protein levels are predictive of esophageal cancer patient response to neoadjuvant chemoradiation, Ann. Surg. 254 (2011) 809–816 (discussion 816–807). [58] H. Jiang, X.H. Wang, X.M. Yu, Z.G. Zheng, Detection and prognostic analysis of serum protein expression in esophageal squamous cell cancer, Asian Pac. J. Cancer Prev. 13 (2012) 1579–1582. [59] X.L. Du, H. Hu, D.C. Lin, S.H. Xia, X.M. Shen, Y. Zhang, M.L. Luo, Y.B. Feng, Y. Cai, X. Xu, Y.L. Han, Q.M. Zhan, M.R. Wang, Proteomic profiling of proteins dysregulted in Chinese esophageal squamous cell carcinoma, J. Mol. Med. 85 (2007) 863–875. [60] P. Kelly, F. Paulin, D. Lamont, L. Baker, S. Clearly, D. Exon, A. Thompson, Pre-treatment plasma proteomic markers associated with survival in oesophageal cancer, Br. J. Cancer 106 (2012) 955–961. [61] H. Igaki, H. Kato, Y. Tachimori, Y. Nakanishi, T. Shimoda, Surgery for clinical T3 carcinomas of the upper thoracic oesophagus and the need for new strategies, Br. J. Surg. 92 (2005) 1235–1240. [62] H. Igaki, Y. Tachimori, H. Kato, Improved survival for patients with upper and/or middle mediastinal lymph node metastasis of squamous cell carcinoma of the lower thoracic esophagus treated with 3-field dissection, Ann. Surg. 239 (2004) 483–490. [63] M. Kavallaris, G.M. Marshall, Proteomics and disease: opportunities and challenges, Med. J. Aust. 182 (2005) 575–579. [64] L. Vona-Davis, T. Vincent, S. Zulfiqar, B. Jackson, D. Riggs, D.W. McFadden, Proteomic analysis of SEG-1 human Barrett's-associated esophageal adenocarcinoma cells treated with keyhole limpet hemocyanin, J. Gastrointest. Surg. Off. J. Soc. Surg. Aliment. Tract. 8 (2004) 1018–1023. [65] D.W. McFadden, D.R. Riggs, B.J. Jackson, L. Vona-Davis, Keyhole limpet hemocyanin, a novel immune stimulant with promising anticancer activity in Barrett's esophageal adenocarcinoma, Am. J. Surg. 186 (2003) 552–555. [66] J.R. Harris, J. Markl, Keyhole limpet hemocyanin: molecular structure of a potent marine immunoactivator, Rev. Eur. Urol. 37 (Suppl. 3) (2000) 24–33. [67] H. Hu, Y. Ran, Y. Zhang, Z. Zhou, S.J. Harris, L. Yu, L. Sun, J. Pan, J. Liu, J. Lou, Z. Yang, Antibody library-based tumor endothelial cells surface proteomic functional screen reveals migration-stimulating factor as an anti-angiogenic target, Mol. Cell. Proteomics 8 (2009) 816–826. [68] J. Tol, M. Koopman, A. Cats, C.J. Rodenburg, G.J. Creemers, J.G. Schrama, F.L. Erdkamp, A.H. Vos, C.J. van Groeningen, H.A. Sinnige, D.J. Richel, E.E. Voest, J.R. Dijkstra, M.E. Vink-Borger, N.F. Antonini, L. Mol, J.H. van Krieken, O. Dalesio, C.J. Punt, Chemotherapy, bevacizumab, and cetuximab in metastatic colorectal cancer, N. Engl. J. Med. 360 (2009) 563–572. [69] D.J. Slamon, B. Leyland-Jones, S. Shak, H. Fuchs, V. Paton, A. Bajamonde, T. Fleming, W. Eiermann, J. Wolter, M. Pegram, J. Baselga, L. Norton, Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2, N. Engl. J. Med. 344 (2001) 783–792. [70] J. Baselga, I. Bradbury, H. Eidtmann, S. Di Cosimo, E. de Azambuja, C. Aura, H. Gomez, P. Dinh, K. Fauria, V. Van Dooren, G. Aktan, A. Goldhirsch, T.W. Chang, Z. Horvath, M. Coccia-Portugal, J. Domont, L.M. Tseng, G. Kunz, J.H. Sohn, V. Semiglazov, G. Lerzo, M. Palacova, V. Probachai, L. Pusztai, M. Untch, R.D. Gelber, M. Piccart-Gebhart, A.S.T. Neo, Lapatinib with trastuzumab for HER2-positive early breast cancer (NeoALTTO): a randomised, open-label, multicentre, phase 3 trial, Lancet 379 (2012) 633–640. [71] G.D. Demetri, M. von Mehren, C.D. Blanke, A.D. Van den Abbeele, B. Eisenberg, P.J. Roberts, M.C. Heinrich, D.A. Tuveson, S. Singer, M. Janicek, J.A. Fletcher, S.G. Silverman, S.L. Silberman, R. Capdeville, B. Kiese, B. Peng, S. Dimitrijevic, B.J. Druker, C. Corless, C.D. Fletcher, H. Joensuu, Efficacy and safety of imatinib mesylate in advanced gastrointestinal stromal tumors, N. Engl. J. Med. 347 (2002) 472–480. [72] G.D. Demetri, A.T. van Oosterom, C.R. Garrett, M.E. Blackstein, M.H. Shah, J. Verweij, G. McArthur, I.R. Judson, M.C. Heinrich, J.A. Morgan, J. Desai, C.D. Fletcher, S. George, C.L. Bello, X. Huang, C.M. Baum, P.G. Casali, Efficacy and safety of sunitinib in patients with advanced gastrointestinal stromal tumour after failure of imatinib: a randomised controlled trial, Lancet 368 (2006) 1329–1338. [73] Y.J. Bang, E. Van Cutsem, A. Feyereislova, H.C. Chung, L. Shen, A. Sawaki, F. Lordick, A. Ohtsu, Y. Omuro, T. Satoh, G. Aprile, E. Kulikov, J. Hill, M. Lehle, J. Ruschoff, Y.K. Kang, G.A.T.I. To, Trastuzumab in combination with chemotherapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancer (ToGA): a phase 3, open-label, randomised controlled trial, Lancet 376 (2010) 687–697. [74] P.M. Boland, B. Burtness, Esophageal carcinoma: are modern targeted therapies shaking the rock? Curr. Opin. Oncol. 25 (2013) 417–424. [75] P.H. Riegman, K.J. Vissers, J.C. Alers, E. Geelen, W.C. Hop, H.W. Tilanus, H. van Dekken, Genomic alterations in malignant transformation of Barrett's esophagus, Cancer Res. 61 (2001) 3164–3170. [76] Y. Song, L. Li, Y. Ou, Z. Gao, E. Li, X. Li, W. Zhang, J. Wang, L. Xu, Y. Zhou, X. Ma, L. Liu, Z. Zhao, X. Huang, J. Fan, L. Dong, G. Chen, L. Ma, J. Yang, L. Chen, M. He, M. Li, X. Zhuang, K. Huang, K. Qiu, G. Yin, G. Guo, Q. Feng, P. Chen, Z. Wu, J. Wu, L. Ma, J. Zhao, L. Luo, M. Fu, B. Xu, B. Chen, Y. Li, T. Tong, M. Wang, Z. Liu, D. Lin, X. Zhang, H. Yang, J. Wang, Q. Zhan, Identification of genomic alterations in oesophageal squamous cell cancer, Nature 509 (2014) 91–95. [77] E.P. Xing, G.Y. Yang, L.D. Wang, S.T. Shi, C.S. Yang, Loss of heterozygosity of the Rb gene correlates with pRb protein expression and associates with p53 alteration in human esophageal cancer, Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 5 (1999) 1231–1240. [78] L.D. Wang, Y.R. Qin, Z.M. Fan, D. Kwong, X.Y. Guan, G.S. Tsao, J. Sham, J.L. Li, X.S. Feng, Comparative genomic hybridization: comparison between esophageal squamous cell carcinoma and gastric cardia adenocarcinoma from a high-incidence area for both cancers in Henan, northern China, Dis. Esophagus 19 (2006) 459–467. [79] K.F. Kwong, Molecular biology of esophageal cancer in the genomics era, Surg. Clin. North Am. 85 (2005) 539–553.

Please cite this article as: N. Uemura, T. Kondo, Current advances in esophageal cancer proteomics, Biochim. Biophys. Acta (2014), http:// dx.doi.org/10.1016/j.bbapap.2014.09.011

N. Uemura, T. Kondo / Biochimica et Biophysica Acta xxx (2014) xxx–xxx [80] H.B. Chen, K. Pan, M.K. Tang, Y.L. Chui, L. Chen, Z.J. Su, Z.Y. Shen, E.M. Li, W. Xie, K.K. Lee, Comparative proteomic analysis reveals differentially expressed proteins regulated by a potential tumor promoter, BRE, in human esophageal carcinoma cells, Biochem. Cell Biol. Biochim. Biol. Cell. 86 (2008) 302–311. [81] J. Zhao, A.C. Chang, C. Li, K.A. Shedden, D.G. Thomas, D.E. Misek, A.P. Manoharan, T.J. Giordano, D.G. Beer, D.M. Lubman, Comparative proteomics analysis of Barrett metaplasia and esophageal adenocarcinoma using two-dimensional liquid mass mapping, Mol. Cell. Proteomics 6 (2007) 987–999. [82] J. Breton, M.C. Gage, A.W. Hay, J.N. Keen, C.P. Wild, C. Donnellan, J.B. Findlay, L.J. Hardie, Proteomic screening of a cell line model of esophageal carcinogenesis identifies cathepsin D and aldo-keto reductase 1C2 and 1B10 dysregulation in

9

Barrett's esophagus and esophageal adenocarcinoma, J. Proteome Res. 7 (2008) 1953–1962. [83] Y. Qi, J.F. Chiu, L. Wang, D.L. Kwong, Q.Y. He, Comparative proteomic analysis of esophageal squamous cell carcinoma, Proteomics 5 (2005) 2960–2971. [84] Y.J. Qi, Q.Y. He, Y.F. Ma, Y.W. Du, G.C. Liu, Y.J. Li, G.S. Tsao, S.M. Ngai, J.F. Chiu, Proteomic identification of malignant transformation-related proteins in esophageal squamous cell carcinoma, J. Cell. Biochem. 104 (2008) 1625–1635. [85] Z. Liu, J.G. Feng, A. Tuersun, T. Liu, H. Liu, Q. Liu, S.T. Zheng, C.G. Huang, G.D. Lv, I. Sheyhidin, X.M. Lu, Proteomic identification of differentially-expressed proteins in esophageal cancer in three ethnic groups in Xinjiang, Mol. Biol. Rep. 38 (2011) 3261–3269.

Please cite this article as: N. Uemura, T. Kondo, Current advances in esophageal cancer proteomics, Biochim. Biophys. Acta (2014), http:// dx.doi.org/10.1016/j.bbapap.2014.09.011