Review
An overview of esophageal squamous cell carcinoma proteomics
Yi-Jun Qi a ,Wei-Xia Chao a ,Jen-Fu Chiu b ,?
a
Key Laboratory of Cellular and Molecular Immunology,Institute of Immunology,Medical School of Henan University,Kaifeng,Henan 475004,P.R.China b
Open Laboratory for Tumor Molecular Biology,Department of Biochemistry,Shantou University Medical College,Shantou,China,and Department of Anatomy,University of Hong Kong,Hong Kong,P.R.China
A R T I C L E I N F O
A B S T R A C T
Article history:
Received 18January 2012Accepted 18April 2012Available online 27April 2012Esophageal squamous cell carcinoma (ESCC)still remains the leading cancer-caused mortality in northern China,in particular in areas nearby Taihang https://www.doczj.com/doc/f02257362.html,te-stage diagnosis of ESCC increases the mortality and morbidity of ESCC.Therefore,it is imperative to identify biomarkers for early diagnosis,monitoring of tumor progression and identifying potential therapeutic targets of ESCC.Proteomics provides a functional translation of the genome and represents a richer source for the functional description of diseases and biomarkers implicated in cancer.In this review,we discuss the dysregulated proteins associated with ESCC identified by proteomic approaches and aim to enhance our understanding of molecular mechanisms implicated in ESCC development and progression from a proteomics perspective and discuss the potential biomarkers of ESCC as well.
?2012Elsevier B.V.All rights reserved.
Keywords:
Esophageal squamous cell carcinoma Proteomics
Mass spectrometry (MS)
Two-dimensional electrophoresis (2DE)
Stable isotope labeling by amino acids in cell culture (SILAC)
Isobaric tags for relative and absolute quantification (iTRAQ)
Contents
1.Introduction .........................................................3130
2.Proteomic fingerprinting of ESCC by two-dimensional electrophoresis-based proteomics ...............3130
3.Proteomic fingerprinting of ESCC by stable isotope labeling-based proteomics .....................3133
4.Biomarkers of ESCC revealed by surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS)........................................................3134
5.
Clinical relevance of potential protein biomarkers in ESCC .............................
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Abbreviations:EC,esophageal cancer;EAC,esophageal adenocarcinoma;ESCC,esophageal squamous cell carcinoma;2DE,two-dimensional electrophoresis;IHC,immunohistochemistry;TPM,tropomyosin;PRX,peroxiredoxin;SCCA,squamous cell carcinoma antigen;MnSOD,manganese superoxide dismutase;SELDI-TOF-MS,surface enhanced laser desorption/ionization time-of-flight mass spectrometry;SILAC,stable isotope labeling by amino acids in cell culture;iTRAQ,isobaric tags for relative and absolute quantification.?Corresponding author.Tel.:+86134********.E-mail address:jfchiu@hku.hk (J.-F.
Chiu).1874-3919/$–see front matter ?2012Elsevier B.V.All rights reserved.doi:
10.1016/j.jprot.2012.04.025
A v a i l a b l e o n l i n e a t w w w.s c i e n c e d i r e c t.c o m
w w w.e l s e v i e r.c o m /l o c a t e /j p r o t
6.Conclusions (3135)
Acknowledgement (3136)
References (3136)
1.Introduction
Esophageal cancer(EC)ranks as the sixth most common cause of cancer-related mortality worldwide,and there are about 407,000deaths caused by EC in2008[1].Moreover,about half of world's EC cases newly diagnosed each year occurred in China[2].Histologically,esophageal squamous cell carcinoma (ESCC)and esophageal adenocarcinoma(EAC)contribute to more than90%of EC[3].In China,ESCC is the predominant histological subtype and accounts for nearly90%of all EC[4]. The incidence of ESCC is characterized by its striking geographical distribution across the world.In the extremely high incidence areas,e.g.,northern China,EC exceeds100/100, 000/year,while the incidence is less than5/100,000/year in Europe and the USA[5].Recently,changes in the ratio of EAC to ESCC,i.e.,decrease of ESCC incidence and reciprocal increase of EAC incidence has been observed not only worldwide but also in high risk areas in China,pointing to the roles of economic level and lifestyle factors in EC pattern change[6–8].In addition,familial aggregation of ESCC has been reported in high-risk areas for ESCC[9].Taken together, these facts indicate that both genetic susceptibility and environmental risk factors contribute to the etiology of ESCC.
The majority of ESCC patients have advanced metastatic disease at initial diagnosis and are inappropriate for curative resection[10,11].Nevertheless,the overall5-year survival rate is <10%despite significant improvements in surgical techniques and adjuvant chemoradiation[12].In sharp contrast,the5-year survival rate for ESCC patients with endoscopic mucosectomy at early stages,i.e.,carcinoma in situ and intramucosal carcinoma, was100%after endoscopic mucosectomy[13],and surgery gives an overall5-year survival rate of90%[14].Long-term survival has been shown to correlate with stages of EC,as evidenced by 40–62%of5-year survival rate for stages I and IIA contrasting with18–25%for stages IIB and III of EC[15].Clearly,identification of effective biomarkers for early diagnosis,monitoring tumor progression and potential therapeutic targets offers the best chances to lower the morbidity and mortality of ESCC.
Although findings in molecular biology studies have improved our general understanding about the pathogenesis of ESCC,the appropriate biomarkers for high-risk population screening,clinical diagnosis and prognosis have not been identified yet.Therefore,it is imperative to search more effective biomarkers for early diagnosis of ESCC.
It is estimated that the human genome contains about32,000 protein coding genes,which code for100,000to10million proteins due to alternative RNA splicing,overlapping of tran-scription units,post-translational processing and modifications [16,17].Unlike the genome,which is static in certain sense,the proteome of a cell is dynamic and changes over time in terms of protein pattern,protein interactions and modifications triggered by external or internal signals[18,19].More importantly,the proteome is a functional translation of the genome and is the actual manipulator of cellular behavior.Therefore,proteomic profiling of cellular protein constituents should generate the most relevant marker of the functional state of a cell.Proteome represents a much richer source for the functional description of diseases and the discovery of biomarkers implicated in cancer.
2.Proteomic fingerprinting of ESCC by two-dimensional electrophoresis-based proteomics
Two-dimensional electrophoresis(2DE)has been used for over30years now due to its high resolution for separation of complex protein mixtures.In combination with mass spec-trometry,2DE has been so far the most commonly used method for analyzing protein expression and identity.
To date,most studies on ESCC proteomics have used tumor and adjacent non-tumor tissue samples as the primary source to search for biomarkers related with ESCC,followed by immortalized cell lines and malignantly transformed counterparts.Our laboratory used2DE to profile the proteome from ESCC tumors vs.adjacent non-cancer mucosa and proteome from ESCC cell lines vs.immortalized cell line. Comparative analysis and MS for protein identification showed that the over-expressions of tropomyosin isoform4 (TPM4),prohibitin,peroxiredoxin1(PRX1)and manganese superoxide dismutase(MnSOD)were common in ESCC tissues and cancer cell lines;the expressions of stratifin,prohibitin, squamous cell carcinoma antigen1(SCCA1)were correlated inversely with dedifferentiation of ESCC[20,21].Immunohis-tochemistry(IHC)analysis has shown that loss of the expressions of annexin A2and14-3-3σwere45%and64%in ESCC,respectively[22–24].Differential expressions of10 proteins including TPM1,SCCA1,stratifin,peroxiredoxin2 isoform a,alpha B-crystalline,annexin A2,heterogeneous nuclear ribonucleoprotein L,triosephosphate isomerase1 (TPI),laminA/C,and cyclophilin A can be observed as well. Our findings may suggest that these proteins contribute to the multistage process of carcinogenesis,tumor progression,and invasiveness of ESCC.Published in the same issue,Zhou et al. found28proteins aberrantly expressed in ESCC cancer cells with at least three-fold difference between ESCC and normal epithelial cells[25].The overlap between these two studies was quite small.Only expression of SCCA1was commonly down-expressed in ESCC,but transgelin showed increased expression in tumors in our study and decreased expression in Zhou's study.The disparity of proteins identified between these two studies may be due to different sample sources, different methods used by these two groups,such as laser capture microdissection vs.bulk tissues,2D-DIGE vs.silver staining.Taking advantage of another paired cell lines of immortalized SHEE and malignantly transformed SHEEC, Chen et al.documented10up-regulated and10down-regulated proteins associated with ESCC by comparative
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proteomic analysis.Furthermore,brain and reproductive organ-expressed(BRE)protein was verified by RT-PCR and immunoblotting.BRE silencing resulted in decreased expres-sions of prohibitin,cyclin A,CDK2and increased expression of p53[26].Later,five groups reported proteomic signatures associated with ESCC using ESCC samples collected from different regions of China,including high‐risk areas for ESCC such as Linzhou[27],Anyang[28],Xinjiang[29]and low risk areas like Beijing[30]and Guangdong[31],but only four reports[27–30]displayed details of identified proteins.Inter-estingly,more overlap of the identified proteins came from Fu et al.[27],Zhang et al.[28]and our reports[20],which used ESCC samples from Linzhou or Anyang(geographically proximate areas with a distance of70km),the well-known highest areas for ESCC adjacent to Taihang Mountain[27].The commonly identified proteins with the same change in direction included alpha enolase,TPM,tubulin,prohibitin and PRX2,MnSOD and stratifin.Although the prevalence of ESCC in Xinjiang is comparable to Linzhou or Anyang,the protein signatures were distinct,indicative of more important roles of environmental,ethnic or hereditary factors in the carcinogenesis of ESCC[29].It seems that HSP27was a general markers involved in ESCC since four of six studies[25,27,29,30] observed down-expression in ESCC.Only one among seven studies[30]performed survival assay after identifying the candidate proteins by ESCC proteomic profiling.Du et al. reported that over-expression of calreticulin and GRP78could indicate poor prognosis of ESCC[30].Based on47different proteins between ESCC and adjacent normal tissues,Zhang et al.tested the autoantibody response by immunoassay on ESCC serum induced by two over-expressed proteins in ESCC, HSP70and HMGB1and found that the frequency of antibodies to HSP70was significantly increased in ESCC serum(39.1%in ESCC serum vs.1.3%in normal serum)[28].Although2DE is indeed a very useful method for biomarker discovery,more examinations of the biological functions and the clinical relevance of biomarker candidates involved in ESCC are necessary to verify its clinical value.
Two reports presented the proteomic signatures of ESCC with samples from Japan.Nishimori et https://www.doczj.com/doc/f02257362.html,ed the agarose IEF gel in the first dimension,which not only allows for large-scale quantitative comparisons of protein expression but also is able to resolve high molecular mass proteins larger than150kDa[32]. As a result,a different protein pattern was revealed,including a few protein candidates with MW>70kDa.Western blot and IHC verified the different expression of a195kDa protein,periplakin, between cancer and adjacent non-cancer tissues.Not only was the expression of periplakin significantly down-regulated in ESCC but also translocation of periplakin from cell boundaries to cell cytoplasm in tumor was observed.The other research group from Japan used unsupervised classification to analyze the2D-DIGE protein spots and procured the protein signatures most relevant to clinical parameters with progression of ESCC.The authors developed the largest protein database relevant to ESCC,which identified240proteins with expression level associated with carcinogenesis,histological differentiation and the number of lymph node metastases.Furthermore,a signif-icant overlapping was observed between the proteins identified in ESCC with other different types of tumors[33].In addition, Jazii et al.did proteomic profiling using ESCC samples from Iran,another high incidence area for ESCC like northern China,and identified six over-expressed proteins and six under-expressed proteins associated with ESCC[34].However,the authors only used RT-PCR to verify the loss ofβ-tropomyosin in ESCC.The functions of identified proteins associated with the develop-ment and progression of ESCC include cytoskeletal/structural organization,transport,chaperon,oxidoreduction,proliferation, glycolysis,cell motility,transcription,and signal transduction, suggesting multiple dysregulated pathways involved in ESCC. Table1shows the reported differential proteins with various functions in esophageal cancer tissues identified by2DE-based proteomic approach.For better understanding of the pathogen-esis of ESCC and development of biomarkers,integrated and comprehensive studies on these protein candidates are needed.
An alternative approach to identify novel tumor biomarkers is the assessment of immune response elicited by tumor antigen since humoral immune responses to cancer in humans have been shown by the identification of autoantibodies to a variety of intracellular and surface antigens in cancer patients with different types of tumors[35–38].In ESCC,a number of reports have documented the presence of autoantibodies in serum against various proteins,including p53[39],cytokeratins[40], myomegalin[41],TRIM21[42],peroxiredoxin VI proteins[43], HSP70[44],and CDC25B[45].The proteomic-based approach to identify panels of tumor antigens and related autoantibodies was introduced by Brichory et al.in2001,which identified anti-annexin I and II antibodies in sera from patients with lung cancer[46].There have been four articles published by two research groups,which have reported the existence of autoan-tibodies in sera of ESCC patients[43–45,47].The first report was published by Fujita et al.from Japan,who used2DE to resolve protein extracts from ESCC cell line TE-2as tumor antigens and then probed the blot with sera of ESCC patients,healthy controls and patients with other cancers[43].One positive spot was identified as PRX VI by MALDI TOF/TOF MS.The frequency of autoantibodies against PRX VI was50%(15/30)in ESCC,only 6.6%(2/30)in healthy controls and3.3%(1/30)in colon cancer. Two years later,the same research group discovered augmented concentration of HSP70autoantibody in the serum of ESCC patients,which was significantly higher in ESCC patients than gastric and colon cancer,and healthy controls[44].On the other hand,Liu et https://www.doczj.com/doc/f02257362.html,ed ESCC tissue protein extracts and autologous sera to search for autoantibodies in ESCC patients and identified autoantibody CDC25B[45].Furthermore,CDC25B expression was significantly higher in ESCC tissues with positive autoan-tibody CDC25B and significantly correlated with tumor stage. The sensitivity and specificity of autoantibody CDC25B in sera to distinguish134primary ESCC from134healthy controls were 56.7%and91%,respectively.High serum level of CDC25B autoantibodies was significantly correlated with tumor stage(P <0.001)[47].The autoantibody-driven research is indeed a promising approach for the identification of novel serum biomarkers present in ESCC and for the tumor antigen itself, which may aid the diagnosis of ESCC and development of more effective immunotherapies.
Similar to other cancers,development of multiple drug resistance in ESCC is one of major causes of failure to chemotherapy treatment.Furthermore,recent studies have shown that there exists intrinsic sensitivity and resistance to chemotherapy and/or radiotherapy in malignant cells of
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Table1–Reported differential proteins with various functions in esophageal cancer tissues.
Calcium-dependent phospholipid binding,calcium ion binding
Annexin A2↑[30]or↓[29]Annexin A8↓[32]Annexin I↓[25,28,30,32,34]or↑[31] AnnexinV↑[30]AnnexinVI↓[32]Reticulocalbin↑[25]
S100A9↓[25]Syntaxin binding protein↑[29]
Translationally controlled tumor protein↑[31]
Cytoskeleton constituent or binding
TPM↓[20,25,29,32]or↑[27]TPM2↓[28,31,32,34]Apha-actinin4↑[27]
TPM3↑[27]or↓[31]TPM4↑[20]TPM isoform↑[20,27]
Vinculin↓[32]Capping protein,gelsolin-like↓[27]Cofilin1↑[53]
Transgelin↓[25,29,31]or↑[20,28]Desmin↓[25,32]Gamma-actin↑[20]
Smooth muscle protein↓[29]Calponin1,basic↓[32]Tubulin alpha-6,ubiquitous↑[27] Tubulin beta-5chain↑[20,27]Mutant beta-actin↑[30]Beta-actin↑[27]
ACTB protein↑[29]Profilin-1↑[28,31]Periplakin↓[32]
Fascin↑[25]Fascin homolog1↑[53]Caldesmon1isoform1↓[32]
Vimentin↑[32]Keratin6↑[32]Keratin1↑[25,34]
Keratin8↓[25]Keratin13↓[25,28,32]Keratin6A↑[30]
Keratin17↑[28]Cortactin↑[53]Keratin19[28]
Smooth muscle myosin heavy chain11isoform SM1↓[32]
Myosin heavy chain nonmuscle form A↓[32]
F-actin capping protein alpha-1subunit variant[28]
Stress response,chaperone binding
PRO1708↑[30]DnaJ(Hsp40)homolog↑[32]GRP78↑[30]
Gp96↑[25]Calreticulin↑[30,34,53]Fibrin beta↓[29]
Calreticulin precursor↑[28,32,52,53]Heat shock protein90kDa alpha↑[52]Peptidylprolyl isomerase B↑[53]
Alpha-B-Crystalline↓[20,31]DanK-type molecular chaperone HSPAIL↑or↓[30,32]
Heat shock70kDa protein8↓[32]Heat shock protein70kDa↑[28,34,52]
Heat shock protein27kDa↓[25,27,30]or↑[29]
Similar to heat shock cognate71-kDa protein↑[30]
Energy metabolism
Alpha enolase↑[20,27,30]Beta-enolase↑[27,32]M2-type pyruvate kinase↑[27,29,30] GAPDH↑[20]Phosphoglycerate kinase1↑[30,32]Triosephosphate isomerase↑[28,31] Aldolase A↓[32]pyruvate kinase,muscle↓[27]Fructose-bisphosphate aldolase A↓[31]
RNA binding and processing,transcription regulation,translation
Prohibitin↑[20,26]or↓[27]DNA directed RNA polymerase B(ropB)↑[34]
General transcription factor IIH↓[29]Heterogeneous nuclear ribonucleoprotein A2/B1:B1↑[32]
RNA binding motif protein8A↑[25]Heterogeneous nuclear ribonucleoprotein A2/B1:A2↑[32]
Elongation factor Tu↑[20]Translation initiation factor eIF-1A↑[25]
PCNA↑[25,30]TBP-associated factor15↑[53]
Protein binding or midification
TGase↓[25]Serum amyloid P-component[Precursor]↓[31]
Early endosome antigen1↓[29]Crystal structure of recombinant human fibrinogen fragment↑[32]
Transmembrane protein4↑[25]Thrombospondin1↑[53]COMT protein↑[29]
OPTN protein↓[27]Transthyretin[Precursor]↑[31]
Protein degradation
Prosomal protein p30-33k↑[25]Proteasome subunitβtype4↑[25]Proteasome subunitβtype9↓[25] Proteosome↑[29]Ubiquitin C-terminal esterase↑[25]
Similar to ubiquitin-conjugating enzyme E2variant1isoform↓[30]
Ubiquinol-cytochrome C reductase complex core protein2↑[32]
Redox homeostasis
Thioredoxin perosidase↑[25,31]Peroxiredoxin1↑[20,28]or↓Peroxiredoxin2↓[27,34]
MnSOD↑[28,30]
Regulatory light chain of myosin
Myosin light chain3↓[31]Myosin light polypeptide6↑[34]Myosin light chain2↓[34]
Myosin light chain1↓[31]Myosin light chain6B↓[31]Myosin regulatory light chain2↓[31,34]
Proteinase and proteinase inhibitor
Alpha-1-antitrypsin↑[27]Alpha-1-antitrypsin precursor↓[32]Serpin B5precursor↑[31]
Serpin B3↑[31]Cystatin-B↑[28,31]Anhydrase1↓[31]
Carbonic anhydrase3↓[31]SCCA1↓[20,25]Proteinase inhibitor,Clade B↓[25] Cathepsin D↑[29]Matrix metallopeptidase13↑[52]Matrix metallopeptidase1↑[52]
ESCC,which may predict clinical outcome of ESCC patients receiving neoadjuvant chemotherapy.Prior stratification of ESCC patients according to reliable biomarkers could not only save patients unnecessary adverse effects of chemotherapeutic agents but also render patients more able to access alternative curative treatment options.Therefore,it is imperative to define new diagnostic indicators that can reliably predict responses to chemotherapy and radiotherapy in advance.A recent study compared the 2DE gels of a parental esophageal cancer cell line EC109and its resistant sub-cell line EC109/CDDP to determine the different proteins spots,and identified 44proteins poten-tially associate with chemotherapy resistance [48].In another study,radioactive 2DE proteomic comparative analysis was performed using protein extracts of biopsies from 34patients with locally advanced EAC receiving neoadjuvant chemothera-py.Proteins with differential expression between responders and non-responders were classified into two major families,cytoskeleton proteins and molecular chaperon proteins.Further validation by IHC and RT-PCR showed that weak expression of HSP27at protein level and mRNA level were associated with non-response to platin-based chemotherapy [49].Since chemo-therapy resistance is a complex and multi-factorial event,proteomic-based studies enable comprehensive characteriza-tion of resistance phenotypes of malignant cancers,which may lead to the identification of distinguishing biomarkers between responders and non-responders and lay the foundation for further molecular mechanism studies.
3.Proteomic fingerprinting of ESCC by stable isotope labeling-based proteomics
Quantitative proteomics is one of the hot research fields in post-genomic era,which has been used extensively in oncology to identify biomarkers with diagnostic and therapeutic potential.In
traditional 2DE,quantitative information of protein spots on 2DE gels is represented by staining intensity.Although 2DE is a versatile tool for visualization of thousands of proteins,detection of post-translational modified isoforms and protein expression alternations,its inherent limitations,such as low sensitivity,substantial workload,poor reproducibility,limited resolution of membrane or extreme pI and Mr proteins,result in only part of proteome uncovered.In this context,two classes of gel-free MS-based quantitative proteomics methods have been developed,which include extracted ion current (XIC)-based label-free quantification and stable isotope labeling quantification [50].Stable isotope labeling by amino acids in cell culture (SILAC)is an in vivo metabolic labeling method in which stable isotope-labeled amino acids (heavy vs.light amino acids)replace the natural amino acids of preexisting proteome [51].We used SILAC medium to label immortalized cells (NE3and NE6)and cancer cells (EC1,EC109,EC9706)with heavy and light medium,respectively.Electrospray ionization-MS/MS analysis (HPLC-ESI-MS/MS)resulted in 43candidate proteins with differential expression identified with our arbitrary criteria,which contains ratio change >1.5folds,≥2unique peptides for quantification and coefficient of variation <50%.Then,we characterized the cellular protein expression pattern and secretome derived from cisplatin-resistant sub-cell line EC9706/CDDP and its parental sensitive cell line EC9706.By SILAC labeling and MS-based quantification,we identified 74proteins of cellular origin and 57proteins of secretome with altered expression levels.Similar to our ap-proach,Kashyap et https://www.doczj.com/doc/f02257362.html,ed a SILAC-based quantitative proteo-mic approach to compare the secretome of ESCC cells with that of non-neoplastic esophageal squamous epithelial cells and identi-fied 120up-regulated proteins with >2-fold difference in the ESCC secretome [52].In addition to previously known increased ESCC biomarkers,i.e.,matrix metalloproteinase 1,transferrin receptor,and transforming growth factor beta-induced 68kDa,a number of novel proteins showed distinct expression patterns,among
Table 1(continued )
Calcium-dependent phospholipid binding,calcium ion binding
Creatine kinase M-type ↓[31]
Phosphatidylethanolamine-binding protein1↓[31]
Lipid metabolism,carcinogen metabolism Apolipoprotein A-I [Precursor]↑[31]Fatty acid-binding protein ↓[25]Carbonyl reductase 1↑[53]
Carboxylesterase 1↑[53]Signal transduction Stratifin ↓[20,28,30]67kDa laminin receptor ↑[27]
TNF receptor associated factor 7↑[29]
Cdc42↑[29]
Fas-associated via death domain ↑[53]
Miscellaneous
GST M 2↑[25]
(NADP)cytoplasmic ↑[20]Neuronal protein ↑[20]Similar to alpha-fetoprotein ↓[32]Trnasferrin ↓[32]AKR family 1[25]
Adenylate kinase 1↓[29]Galectin-7↓[25]or ↑[31]Trnasferrin receptor ↑[52]
Procollagen-proline ↓[32]GH16431P ↑[34]Chromosome1open reading frame 8↑[29]Transforming growth factor beta ↑[52]Zinc finger protein 410↑[30]LLDBP ↑[29]
Hemoglobin beta chain ↓[30]Myoglobin ↓[31]Immunoglobulin ↑[28,29]
TPM-4-ALK fusion oncoprotein type 2↑[30,34]
Crystal structure of human recombinant procathepsin B ↑[30]Nuclear autoantigenic sperm protein isoform 1↑[32]Peptidyl-prolyl cis-trans isomerase A ↑[31]
↑or ↓indicate up-or down-regulated protein in ESCC,respectively.
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which protein disulfide isomerase family a member3,GDP dissociation inhibitor2,and lectin galactoside binding soluble3 binding protein were further validated by immunoblot analysis and IHC using tissue microarrays.These identified proteins participate in multiple biological functions,including molecular chaperones,cytoskeletal proteins,and members of protein inhibitors family,reducing protein,etc.,suggesting multiple dysregulated pathways involving in ESCC.
Isobaric tags for relative and absolute quantification(iTRAQ) derivatize peptides at the N termini and lysine side chains in a protein digest mixture with multiplex amine reactive isobaric tags,which enables simultaneous peptide identification and relative quantification of up to eight samples.Two parallel pools comprising protein extracts from ESCC and adjacent non-tumor tissues were trypsin-digested to generate peptide mixture followed by iTRAQ labeling,LC-MS/MS and bioinformatic analysis.By virtue of≥2-fold difference and≥2unique peptides for each protein identification,29up-regulated and52down-regulated proteins in ESCC were https://www.doczj.com/doc/f02257362.html,pared with differential proteins identified by2DE-based proteomic ap-proach,a different expression pattern associated with ESCC was revealed and the common proteins with similar change identified by both approach include only tropomyosin,peripla-kin and transgelin.Similar to our approach,researchers from India used pooled ESCC and adjacent normal epithelium tissue samples to identify potential biomarkers implicated in ESCC after iTRAQ labeling and LC-MS/MS analysis.In all,257proteins, including147up-regulated and91down-regulated proteins with>2-fold difference,were identified among a total of687 protein identification between ESCC and adjacent normal epithelia[53].Unlike2DE,ESCC from China and India generated quite similar protein pattern by iTRAQ labeling and LC-MS/MS analysis,which were represented by up-regulated transgelin-2 and down-regulated transgelin verified by Western blot in our group.The results demonstrated that2DE-based and iTRAQ labeling-based proteomic approaches are complementary for screening potential protein markers implicated in ESCC.
4.Biomarkers of ESCC revealed by surface enhanced laser desorption/ionization time-of-flight mass spectrometry(SELDI-TOF-MS)
In addition to2DE-based proteomic studies,SELDI-TOF-MS is an alternative proteomic tool to profile the serum or other body fluids and define potential protein patterns with diagnostic potential.SELDI-TOF-MS uses chip arrays with specific chromatographic surface to retain certain classes of proteins based on their physico-chemical features,such as CM10with a weak-positive ion exchange surface,H50with a hydrophobic surface,IMAC30with a metal-binding surface and Q10with a strong anion exchange surface.After washing off undesired proteins and contaminants,matrix is overlaid on surface-bound proteins for co-crystalization followed by MS spectral https://www.doczj.com/doc/f02257362.html,pared to2DE,SELDI-TOF-MS is well adapted to detect proteins with molecular weight<20kDa and extreme pI and is featured by high tolerance of salts and other impurities,small amount sample,high-throughput and simplicity as well.Wang et https://www.doczj.com/doc/f02257362.html,ed weak cation exchange (WCX2)protein chips and SELDI-TOF-MS to profile130symptom-free serum samples collected from high-incidence area of ESCC in northern China,Linzhou,which included63 subjects with normal esophageal mucosa,40subjects with basal cell hyperplasia,27subjects with dysplasia and30ESCC patients.Biomarker pattern's software identified four protein features at m/z of9306.61,13765.9,2942.15and15953.4, which could distinguish normal esophageal epithelium,basal cell hyperplasia,dysplasia and ESCC with satisfactory diag-nostic accuracy[54].Using WCX2protein chip to profile199 ESCC vs.106healthy control serum samples from Beijing,a diagnostic pattern consisting of12protein peaks(m/z:1028,1 098,1301,2047,2742,3975,4130,4283,4301,5635,6203,13 749)was selected with a sensitivity of91.5%and specificity of 84.4%[55].Although both group using WCX2chips,only one similar peak(13765.9vs13749)was identified by the above two studies,which may be due to different sample origin or possible experimental variation.By SELDI-TOF-MS profiling of 55ESCC and35healthy control serum samples from Jiangsu province using IMAC3chips,25differential protein peaks was identified and21decision trees was subsequently set up to distinguish ESCC in blind testing samples(13ESCC vs.9 healthy controls)with a sensitivity of92.31%and a specificity of66.67%[56].Xinjiang is one of the high-incidence areas for ESCC and comprises different ethnic peoples including Han https://www.doczj.com/doc/f02257362.html,ing CM10protein chips to capture targets from serum samples(139ESCC vs.49healthy controls),SELDI-TOF-MS and bioinformatics analysis resulted in identification of six protein peaks(m/z5667,5709,5876,5979,6043and6102) with a sensitivity and a specificity of97.12%and83.87%, respectively[57].In the case of proteomic signature identified by SELDI-TOF-MS,further purification and identification of discriminatory peaks are necessary for development of simple methods for wider clinical application and to enhance our understanding of the molecular mechanisms of esophageal carcinogenesis as well.
To predict the efficacy of neoadjuvant chemoradiotherapy in the treatment of ESCC,sera from27responders and12non-responders before preoperative chemoradiotherapy were examined by SELDI-TOF-MS with a set of protein chips,i.e., H50,CM10and IMAC-Cu2+.A proteomic classifier comprising four mass peaks,at7420,9112,17,123and12,867m/z was identified with93.3%predicative accuracy in the validation set comprising15ESCC cases[58].Although serum represents a rich source for biomarker discovery,high-abundant proteins in serum,such as albumin and immunoglobulin(Ig)G,would overshadow low-abundance proteins.To maximize binding of relatively low-abundance serum proteins to protein chips, albumin-and IgG-depleted serum of baseline,24-h and48‐h time-point samples from15responders and16non-responders were analyzed by SELDI-TOF-MS with CM10 chips.Among nine differential protein peaks identified,two significant peaks were verified as complement C3a and C4a corresponding to m/z of8928.423and8617.685,respectively. Pretreatment of serum levels of C3a and C4a could predict response to neoadjuvant chemoradiotherapy with a sensitiv-ity and a specificity of78.6%and83.3%,respectively[59].For identification of potential biomarkers,however,SELDI-TOF-MS would require a second dimension of mass spectrometry, or a online EPO-KB tool to identify/predict the possible identities.
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5.Clinical relevance of potential protein biomarkers in ESCC
To answer clinical questions,protein biomarkers identified by proteomic techniques with potential diagnosis and therapeutic targets for ESCC need to be translated into clinical scenario, which is realized by using clinical samples,such as biopsy samples,resected tissue samples,plasma or serum samples, urine samples,saliva samples,etc.The methods used for validation generally comprise Western blot,IHC and ELISA at protein level,and RT-PCR at transcription https://www.doczj.com/doc/f02257362.html,ing2DE-and SILAC/iTRAQ-based quantitative proteomic approaches,we have identified a total of156non-redundant proteins with aberrant expression patterns associated with ESCC,suggesting that these proteins may play functional roles in carcinogenesis of ESCC and may have clinical value.Western blot analysis verified in cancer the decreased expressions of three proteins, i.e.,SCCA1,TPM1and alpha B-crystalline,in accordance with 2DE quantitative results.At the transcription level,SCCA1 mRNA was down-regulated in tumors as well.More important-ly,the expression of SCCA1decreased step by step as a function of the progression of precancer lesions,which suggests that SCCA1may take part in the multistage transformation of ESCC, even in the earliest stages[20].In the2DE-based comparative proteomic study using immortalized and cancer cell model,we selected annexin A2for validation by Western blot and IHC. Stepwise decrease in annexin A2protein expression was observed when epithelial cells were transformed.In poorly differentiated squamous carcinoma,46%(5/11)of ESCC lost annexin A2protein and36%(4/11)expressed at weak intensity [22].In a separate study,IHC was used to determine14-3-3σin 60cases of ESCC,nearby matched normal esophageal epithe-lium,and a variety of ESCC precursor lesions.High level of14-3-3σexpression was found ubiquitously in normal esophageal epithelium with an immunostaining score of8.22in expression. 14-3-3σwas down-regulated stepwise during the multistage development of ESCC.Sixty-four percent of poorly differentiat-ed squamous cancer lost14-3-3σexpression with a score of0.45 [23].In agreement with our results,Ren et al.documented that the expression of14-3-3σin terms of mRNA and protein was markedly down-regulated in ESCC compared with nearby non-cancer tissues.Furthermore,decrease of14-3-3σexpression was correlated with tumor infiltration depth,lymph node metastasis,distant metastasis and lymphovascular invasion and shorter5-year survival rate[24].Among the different proteins identified by SILAC-based quantitative analysis using immortal and cancer cell models,the clinical values of MIF in tumorigenesis of ESCC was determined as well.Not only the increased expression of MIF was detected in cellular proteins but also in the conditioned medium of esophageal cancer cell lines EC1,EC109and EC9706compared with immortal cell lines NE3and NE6.Low frequency and very weak expression of MIF was detected predominantly in basal cells in normal esophage-al epithelium,with an immunostaining score of1.13.Markedly up-regulated expression of MIF occurred in severe dysplasia compared with weak immunostaining in mild and moderate dysplasia.In ESCC,high frequency of intense expression of MIF was observed with a score of5.46.Furthermore,high expression of MIF was significantly correlated with advanced clinical stages.ELISA tests revealed that there was an increase trend in serum level of MIF in clinically advanced stage IV compared to stage I-III.Our findings indicate that MIF may play crucial roles in the malignant transformation and pathogenesis of EC, and MIF may become a potential biomarker for high-risk population screening,assessment of therapeutic efficiency, prognostic evaluation,and molecular targets of developing novel therapeutic regimens as well.Recently,we performed immunostaining of MIF,GRP94and HSP27in archival formalin-fixed tissue samples of82ESCC patients with good and worse prognosis after surgery,and found that over-expressions of MIF and GRP94were aggressively correlated with lymph node metastasis(P=0.047,P=0.016,respectively),tumor-node-metastasis staging(P=0.008,P=0.002,respectively),reduced overall5-year survival rate(mean survival time of MIF,45.72vs.
22.93,P=0.001;mean survival time of GRP94,48.08vs.26.3, P=0.001).In contrast,weak expression of HSP27was correlated with lymph node metastasis(P=0.004)and tumor-node-metastasis staging(P=0.003).The mean overall survival for cases with high level of expression of HSP27was37.91months vs.16.85months for HSP weakly expressed ESCC(P=0.007). Subsequent multivariate analysis by Cox model revealed that over-expressions of MIF and GRP94expression were indepen-dent poor prognostic factors,but not HSP27.In addition to our proteomic results in ESCC,several other reports have examined the clinical value of potential biomarkers,including cytokeratin 14,Annexin I,SCCA1/2,calgulanulin B and HSP60[33],alpha-actinin4and67kDa laminin receptor[43],cathepsin D and PKM2[29],periplakin[32],calreticulin and GRP78[30],galectin-7 [31],anti-CD25B antibody[47].Nevertheless,further extensive studies are still necessary to determine the clinical utility of the identified proteins in tumorigenesis and progression of ESCC.
6.Conclusions
Nowadays,the dilemma for cancer control and management is not due to lack of efficient treatment options but diagnosis at late stages.Obviously,to detect tumors as early as possible is the key for reducing the mortality and morbidity of ESCC.It is believed that development of ESCC from normal esophageal epithelium takes at least about10years,during which diseased epithelium manifests as basal cell hyperproliferation,dyspla-sia,carcinoma in situ,in terms of morphology,and finally evolves to malignant neoplasms.As such,carcinogenesis of ESCC is a multi-stage and dynamic process which accumulates ongoing changes at the level of both gene and protein expression.
Proteomic studies from various research groups worldwide have identified distinct dysregulated protein expression pat-terns associated with ESCC.The discrepancy might reflect the different etiology,different stages of disease and diverse pathways involved,which makes identification of biomarkers for ESCC difficult.In light of a wealth of potential biomarkers associated with ESCC identified so far in the exploratory phase, future large-scale validation studies involving symptom-free patients with precursor lesions in high-incidence area and ESCC patients compared with controls are essential toward clinical application.Therefore,ultimate translation from laboratory
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into bedside for ESCC biomarkers will require close collabora-tion and cooperation between researchers and clinicians to look into the clinical utility in diagnosis at early stage,prognosis and monitoring treatment efficiency for ESCC.
Acknowledgement
This work was supported in part by National Natural Science Founding of China(No.30700366and No.81072039)and Cancer Research UK(to Yi-Jun Qi).
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