Review Article
Head and Neck Cancer Proteomic Advances and Biomarker Achievements ´ vio Luiz Franco, PhD Taia Maria Berto Rezende, PhD; Mirna de Souza Freire, BS; and Octa
Tumors of the head and neck comprise an important neoplasia group, the incidence of which is increasing in many parts of the world. Recent advances in diagnostic and therapeutic techniques for these lesions have yielded novel molecular targets, uncovered signal pathway dominance, and advanced early cancer detection. Proteomics is a powerful tool for investigating the distribution of proteins and small molecules within biological systems through the analysis of different types of samples. The proteomic profiles of different types of cancer have been studied, and this has provided remarkable advances in cancer understanding. This review covers recent advances for head and neck cancer; it encompasses the risk factors, pathogenesis, proteomic tools that can help in understanding cancer, and C 2010 American Cancer Society. new proteomic findings in this type of cancer. Cancer 2010;116:4914–25. V KEYWORDS: head and neck cancer, proteomics, cancer risk factors, cancer pathogenesis, diagnostic biomarkers.
Head and neck cancer (HNC) is a term that encompasses epithelial malignancies that arise in the paranasal sinuses, nasal cavity, oral cavity, pharynx, and larynx. Almost all of these epithelial malignancies are squamous cell carcinomas (SCCs) of the head and neck (HNSCCs), for which the most important risk factors are tobacco and alcohol consumption.1 HNSCCs initiate from the mucosal surface, whereas non-SCCs initiate from other cell types (eg, adenocarcinomas that come from glandular cells). Successful treatment of those patients depends on early detection and correct therapy for each cancer phase. Development of novel, potentially efficacious anticancer agents and identification of biomarkers depend on further elucidation of molecular events in HNC development.2 Cancer can be regarded as a deviation from normal signaling toward a more deregulated state that results in cellular proliferation.3 Although each individual mutation may induce specific cancer phenotypes, it is the interaction of the functional changes in transcription and proteins that produce the characteristics of cancer.4 Alteration in the content and functional state of the proteins with many linkages may shift the equilibrium state of the protein-signaling network to enhance a survival advantage of the affected cells. Searching for such hub proteins is the main purpose of cancer proteomics. Low-abundance tissue-specific proteins can be useful as diagnostic markers.3 The focus of this review is to discuss general aspects of HNC in the light of proteomics, a potent biological tool that can help in early cancer diagnosis, treatment, and prognosis. Epidemiology The number of new cases of HNC in the United States was 40,490 in 2006, accounting for about 3% of adult malignancies. The worldwide incidence exceeds half a million cases annually.5 Oral SCC (OSCC) is the most common HNC and accounts for >300,000 new cancer cases worldwide annually.6 Cancer of the upper aerodigestive tract ranks as the third most frequent group of neoplasms among males and the fourth most frequent among females in developing countries. High-risk regions for oral cavity cancer include Melanesia (subregion of Oceania) and south-central Asia, western and southern Europe, and southern Africa. For laryngeal cancer, southern and eastern Europe, South America, and western Asia stand out.7 A slight decrease in the overall incidence of HNC has been detected in the past 2 decades; however, an increase in cancer in the base of the tongue and tonsillar cancer has been noted, which could be more pronounced in young adults in the USA and European countries.8
Corresponding author: Octa´vio Luiz Franco, SGAN Quadra 916, Mo´dulo B, Av. W5 Norte. 70.790-160-Brası´lia – DF, Brazil; Fax: (011) 55-61-3347-4797;
[email protected] Center of Proteomic and Biochemical Analyses, Post-Graduation in Biotechnology and Genomical Sciences, Catholic University of Brasilia, Brasilia-DF, Brazil DOI: 10.1002/cncr.25245, Received: August 27, 2009; Revised: November 10, 2009; Accepted: January 5, 2010, Published online July 21, 2010 in Wiley Online Library (wileyonlinelibrary.com)
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Main HNC Risk Factors The risk factors for HNC are especially represented by tobacco consumption in various forms (smoked or chewed) and use of the betel quid—a preparation of various ingredients, including tobacco and the seeds of the betel palm, wrapped in a betel leaf. The upper aerodigestive tract is the first compartment of the human body that makes contact with the harmful components of tobacco smoke. The passage of the smoke, whether in an active or passive smoker, determines some alterations in the aerodigestive area that is directly exposed to its harmful action. Tobacco contains more than 50 components, including aromatic polycyclic hydrocarbon, tobacco specific nitrosamines, aromatic amines, and aldehydes, which are responsible for neoplastic buccal epithelium transformation.9 One of the first steps in the development of head and neck neoplasia may be the link between these compounds and the mucosal cell’s DNA.10 The metabolism of chemicals occurs in 2 phases. In phase 1, hydrolyzes, reductions, and oxidization reactions occur mainly by the enzymatic group P-450, producing reactive and toxic substances. The oxidative stress induces glutathione S-transferase transcription to eliminate the xenobiotics.11 Although most of these enzymes are hepatic, there is evidence of them in the buccal mucosal, where they develop their oxidative activity.12 The toxic metabolites produced in phase 1 link to macromolecules such as DNA, RNA, and protein-forming complexes that promote genetic instability, mutation, and the beginning of the carcinogenesis process.13 Phase 1 products may be directly excreted or undergo phase 2 enzyme action. Glutathione S-transferases are the main enzymatic components responsible for the metabolism of phase 2. After the glucuronidation, sulfation, methylation, and conjunction reactions, the xenobiotic agents are inactivated and become hydrosoluble, being easily excreted.13 Some studies link cytochrome P450 family 1, subfamily A (CYP1A1) and CYP2E1 genotype to a susceptibility to oral cancer, but others have failed to confirm this association.14 Jaber et al observed that tobacco has an independent role in the etiology of oral epithelial dysplasia, although alcohol is principally only important in conjunction with tobacco use.15 However, Schlecht et al observed among nonsmokers that alcohol in fact acts both as an independent risk factor and as a promoter of oral, pharyngeal, and esophageal cancers.16 Alcohol is a cancer promoter via 1 or more of the following mechanisms: 1) increased permeability of mucosal cells to tobacco smoke carcinogens because of solubilization by alcohol; 2) pres-
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ence of low levels of carcinogenic substances in alcoholic beverages; or 3) cellular injury produced by ethanol metabolites.17 Alcohol acts independently, as well as in synergy with tobacco, in oral carcinogenesis. Tobacco and alcohol effects are not only risk factors for developing primary cancer, but also for developing second primary cancers.18 Therefore, avoiding tobacco and alcohol is the most desirable way not only to prevent primary oral cancers, but also to reduce risk of second cancers of the aerodigestive system. HNSCC has also been associated with genetic polymorphisms in genes that encode human enzymes related to toxic substance metabolism, and that also affect the individual’s susceptibility to noxious effects of carcinogenic chemistry.19 Bondy et al demonstrated in vitro that mutagenicity assays suggest that familial factors may be important in a predisposition to HNSCC.20 Conversely, human papillomavirus has been reported to be associated with HNSCC in patients without a history of tobacco or alcohol consumption.21 Diet and nutrition are also risk factors for HNSCC. Although the individual responsible micronutrients have not been formally identified, vegetables and fruits that protect against oral cancer and precancer are rich in b-carotene, vitamin C, and vitamin E, with antioxidant properties.22 Epidemiological studies from northern China, parts of Africa, and Iran show environmental factors including nutritional zinc deficiency, which is associated with a restricted diet and exposure to carcinogenic N-nitrosamines, in the etiology of esophageal cancer.23 Pathogenesis Molecular changes in HNC occur through multiple steps, each characterized by the sequential stimulation of additional genetic defects, followed by clonal expansion. The genetic alterations observed are mainly because of oncogene activation and tumor suppressor gene inactivation leading to deregulation of cell proliferation and death.24 The histological evolution from normal epithelium to invasive carcinoma includes hyperplasia, mild dysplasia, and severe dysplasia or in situ carcinoma.2 Growth regulators and tumor suppressor genes act as transducers of negative growth signals. Genetic alterations involving the tumor suppressor genes p16 and p53 are frequently observed in HNC.24 Inactivating the p16 gene might confer cell growth defects, contributing to the tumorigenic process, because of its involvement in cell cycle regulation, including cell cycle arrest and apoptosis. Conversely, TSG p53 has a role in maintaining genomic
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stability, cell cycle progression, cellular differentiation, DNA repair, and apoptosis, so it is called the ‘‘guardian of the genome.’’25 Moreover, p53 plays an important role in cell-cycle control and in the induction of apoptosis. The gene can be inactivated by several mechanisms, including occasional mutations, deletions, and binding with cellular and viral proteins in different kinds of cancer, among them SCC.25 Moreover, epidermal growth factor receptor (EGFR) protein expression is elevated in 90% or more cases of HNSCC,26 developing a central role in HNSCC biology.27 The EGFR ligand binding results in a molecular cascade, covering the receptor-linked tyrosine kinase activation and many downstream pathways, which regulate proliferation, differentiation, migration/motility, adhesion, prevention of apoptosis, angiogenesis, metastatic potential, enhanced survival, and gene transcription.2 To date, 3 major mitogen-activated protein kinase (MAPK) subfamilies have been described: extracellular signal-regulated kinase (ERK) 1 and 2, p38-MAPK, and c-jun amino-terminal kinase stress activated protein kinase, although other MAPK members have been identified (eg, ERK5 and ERK7).28 Each MAPK pathway comprises a 3-layer kinase module, in which each element is activated by serial phosphorylations on tyrosine and threonine residues and inactivated by dephosphorylation by specific phosphatases.29 Angiogenesis is also fundamental to cancer growth and metastasis, and it is regulated by many endogenous proangiogenic and antiangiogenic factors, such as vascular endothelial growth factor and its receptors.30 This process includes degradation of the extracellular matrix, endothelial cell proliferation, migration, and assembly of endothelial cells into higher order structures.31 Malignant cells from HNSCC evade immune recognition and inhibit or exploit antitumor immune defenses. In this way, these cells escape from immune-mediated destruction. Patients with HNSCC showed reduced peripheral blood concentrations of CD3þ, CD4þ, and CD8þ T cells, which might persist even several years after curative surgery.32 Many mechanisms for immune evasion have been proposed, including escape from immune recognition and elimination caused by tumor factors,33 impaired T-lymphocyte activity, activity of immunosuppressive cells, and cytokine-mediating local and systemic effects.2 It has been postulated that Th2-like cytokines, like interleukin (IL)-434 and IL-13,35 in addition to others, were responsible for HNSCC growth pattern and could
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be responsible for their active spread.35 As a consequence of Th2-like cytokines’ profile, a suppression of Th1 cytokine genes was reported to increase tumor load and lymph node invasion.24 Bose et al36 showed low levels of Th1 cytokine (IL-12 and interferon [IFN]c), and high levels of Th2 cytokine (IL-4 and IL-10) secretion in culture supernatant of HNSCC peripheral blood mononuclear cells. According to this study, the combination of Th2 cytokines is able to suppress temporarily the generation of IFNc-producing cells without affecting the polarity of T cells, and these actions occurred via STAT1 and STAT4 activation.36 Other important cytokines involved in HNSCC include IL-27, which has a potent ability to induce antitumor-specific activity and is mainly mediated through CD8þ T cells with enhanced cytotoxic T lymphocytes activity,37 and granulocyte macrophage colony-stimulating factor, which presents antitumor activity.38 As shown, the cytokines involved in HNSCC play an important role in this process and could be targeted for immunotherapy.
Technological Tools That Can Help the Understanding of Cancer Cell Growth: A Spotlight on Proteomics Among oncological research on the use of genomic tools during the past decade, there has been a strong drive toward proteomics. Proteomics indicates proteins expressed by a genome and is the systematic analysis of protein profiles of tissue, at a specific time point.39 Differentiated protein expression identification permits the association of these peptides with different physiologic events that have happened in the cells, tissue, and organs.40 Many cancer biomarkers are the manifestation of differences in post-transcriptional splicing, post-translational modifications, or both. Thus, proteomic tools are increasingly used in the postgenomic era to discover new cancer biomarkers (Fig. 1).41 Proteomics is mainly based on protein separation using 2-dimensional (2D) differential in-gel electrophoresis. Two-dimensional gels provide high-resolution expression, profiling thousands of proteins from 1 tissue sample.42 The differential in-gel electrophoresis technique is aimed at improving reproducibility.43 To analyze the samples in differential in-gel electrophoresis, 2 pools of protein extracts are labeled covalently with fluorescent cyanine dyes, Cy3 and Cy5, respectively. These labeled proteins are mixed and separated in the same 2D gel, minimizing the reproducibility problem.
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Figure 1. Schematic figure shows head and neck squamous cell carcinoma (HNSCC) patient sample origin and main proteomic techniques used for studies. Numbers show the main head and neck cancer location: 1, paranasal sinuses; 2, nasal cavity; 3, oral cavity; 4, larynx; 5, pharynx. MALDI indicates matrix-assisted laser desorption/ionization; DIGE, differential in-gel electrophoresis; 2D, 2-dimensional; LC, liquid chromatography; iTRAQ, isobaric tag for relative and absolute quantitation; MS, mass spectrometry; ToF, time of flight.
Identification of proteins differentially expressed in the tumor samples can be performed using mass spectrometry (MS). Proteomic analysis can assist both in the identification of biomarkers and proteins whose upregulation or down-regulation was perhaps instrumental to the pathogenesis of the malignancy.44 Furthermore, affinity bead-based purification has been developed to make proteomic procedures suitable for general MS analysis. Chemical chromatographic surfaces selectively purify certain subsets of proteins, allowing unbound impurities to be removed by washing with buffers. Proteins are typically enzymatically digested after elution and before matrix-assisted laser desorption/ ionization (MALDI) time of flight (ToF) MS analysis, among other forms of MS.45 MALDI-ToF MS sensitively and precisely separates target proteins according to their mass-dependent velocities (m/z). Surface enhanced laser desorption/ionization (SELDI) ToF MS uses chip-based protein sample arrays with different chemical chromatographic surfaces to selectively bind proteins with specific chemical properties, such as hydrophobic, cationic-anionic, or metal-binding molecules, whereas nonspecifically bound proteins or impurities are removed by washing with buffers.46 Because SELDI ToF MS analysis rapidly screens many samples at a time, it may be suitable for clinical use and screening for novel biomarkers.47 Tissue arrays, another important technique, allow the simultaneous in situ analysis of many tumors on the DNA, RNA, and protein levels using in situ hybridization or immunohistochemistry.48 This technique can provide an efficient, high-throughput method for evaluation of protein expression in large cohort studies using archival formalin-fixed, paraffin-embedded tissue. Tissue arrays
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have been used in breast, kidney, prostate, bladder, and human fibroblastic tumors in previous studies.48 Despite tissue heterogeneity, the protein expression in the disk might not be representative for the entire tumor.49 These new technologies have been used successfully to quantitatively and qualitatively characterize existing cancer markers in prostate cancer50 and to detect several disease-associated proteins in tissue samples51 or complex biological specimens, such as serum,52 cerebrospinal fluid,51 nipple aspirates,53 pancreatic juice,54 saliva,55 and urine.56 Although these technologies have demonstrated their suitability, they still provide only limited information about the spatial variability of the cancer proteome. The protein composition of a malignant tumor varies qualitatively and quantitatively. This stems from the intrinsic heterogeneity of solid tumors, the local inflammatory response, neovascularization, the development of a desmoplastic stroma, and so forth.57 A new approach to increase the diagnostic specificity and to characterize the cancer proteome profile in situ is MALDI imaging, which allows the detection of proteins in the tissue section and the analysis of their spatial distribution without prefractionation.58 It allows an immediate evaluation of the putative significance of a biomarker, that is, the mass of interest can be allocated to histoanatomical structures such as tumor cells, tumor stroma, tumor vessels, and inflammation. HNC Proteomic Findings Even after some cancer findings, the survival rates for patients with HNSCC have remained unchanged over the past 30 years.59 Prognosis and treatment are influenced by the stage of disease at diagnosis. Patients with HNSCC
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often present with advanced stage disease, which is associated with a poorer prognosis and requires more aggressive therapy, which in turn results in increased functional disability.60 Research efforts directed at improving early detection of malignancy have focused on the identification of genetic alterations and tumor biomarkers. Conventional diagnostic techniques, including direct inspection or increasingly sophisticated imaging technology, such as positron emission tomography-computer tomography, are limited in their ability to detect HNSCC at its earliest stages and are ineffective for use as a screening tool in high-risk populations.61 Biomarkers associated with HNSCC have revealed considerable variety in protein expression, and as a consequence, there is a variety of potential biomarkers (Table 1). These potential biomarkers present different biochemical functions to gain their antitumor activity. However, the current literature emphasizes the major abundant proteins, whereas little information is available for less abundant proteins that can be the key to discovering HNSCC markers. Another important point is that the study of HNC involves different tissues and systems, so the search for specific biomarkers must be related to each tissue. These reasons are probably related to the finding that until now, these potential biomarkers are not ready to be clinically used. Tissue Biomarker Studies Differential in-gel electrophoresis technique was used for the identification of esophageal squamous cell cancer-specific protein markers by Zhou et al.62 Both esophageal cancer and normal squamous epithelium cells were procured from the same esophageal tumor sample by laser capture microdissection.62 2D gel images and MS were performed, and a down-regulation of protein annexin I and an up-regulation of tumor rejection antigen in esophageal squamous cell cancer were observed. This result demonstrates that the 2D differential in-gel electrophoresis technique, in combination with MS, is a powerful tool for the molecular characterization of cancer progression and identification of cancer-specific protein markers. Koike et al performed proteomic profiling between human normal oral keratinocytes and OSCC-derived cell lines (HSC-2 and HSC-3) using fluorescent 2D differential in-gel electrophoresis and MALDI ToF peptide mass fingerprinting.63 Some of the differential proteins between the groups included annexin A1, heat shock protein 27, lamin A/C, interleukin 1 receptor antagonist, serine-proteinase inhibitor clade B5, stathmin 1, and
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superoxide dismutase 2. In the following year, this group selected 1 of the above up-regulated proteins— stathmin—to correlate its presence with tumor progression and poor prognosis.64 They evaluated the state of stathmin protein and mRNA expression in OSCCderived cell lines and human primary OSCC. A significant increase in stathmin expression was reported in all examined OSCC-derived cell lines compared with human normal oral keratinocytes. In immunohistochemistry, 65% of the OSCC was positive for stathmin, and no immunoreaction was observed in corresponding normal tissues. Moreover, stathmin expression status was correlated with the stage of TNM grading, and a statistical correlation was found between protein expression status and disease-free survival. These results suggested that the expression of stathmin could contribute to cancer progression/prognosis, and that stathmin may have potential as a biomarker and a therapeutic target for OSCC. These results were in accordance with the high level of stathmin expression in many types of cancer, including leukemia and lymphoma,65 prostate carcinoma,66 ovarian carcinoma,67 Wilms tumor,68 breast carcinoma,69 and adenoid cystic carcinoma of the salivary glands.70 To identify potential biomarkers for laryngeal SCC, Sewell et al compared the protein profile of laryngeal cancer tissue with normal mucosal samples using 2D gel electrophoresis and MS.44 The differentially expressed proteins were stratifin, S100 calcium-binding protein A9, p21-ARC, stathmin, and enolase. Several of these proteins regulate cellular proliferation, differentiation, and apoptosis, and their function may directly relate to the pathogenesis of cancer in these patients. These findings revealed potential biomarkers that may contribute to the pathogenesis of laryngeal carcinoma, and that may be suitable as targets for novel therapeutic and/or diagnostic modalities. However, because of the small sample size, these findings cannot be generalized for all laryngeal carcinoma cases, but they provided a scientific basis for further proteomic analyses of laryngeal cancer samples. The identification of nasopharyngeal carcinoma biomarkers was observed in Cheng et al’s study.71 After protein separation by 2D gel electrophoresis and MS identification, the expression levels of stathmin, 14-3-3r, and annexin I in the 2 types of tissues were confirmed and related to differentiation degree and/or metastatic potential of the nasopharyngeal cell lines. Significant stathmin up-regulation and down-regulation of 14-3-3r and annexin I were observed in nasopharyngeal carcinoma versus normal nasopharyngeal epithelial tissue, and
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Ig gamma-3 chain C regioni Complement component C4ai Ig kappa chain C regioni Chromiumi HSP 70j sICAM1j SAAj
Cytokeratinsf Intermediate filament proteinsf YWHAZg hnRNPKg Fibrinogen a-chain fragmenth
Annexin I Annexin A1c Heat shock protein 27c Lamin A/Cc Interleukin 1 receptor antagonistc Serine proteinase inhibitor clade B5c Stathmin 1b,c,d,e Superoxide dismutase 2c Stratifine S100 calcium-binding protein A9e P21-ARCe Enolasee 14-3-3rb
a,b
Potential Biomarker Epithelial differentiation and growth regulation Ca2þ-dependent phospholipid-binding proteins Immune response protein Nuclear stability, chromatin structure, and gene expression protein Immune response protein Protease Cell motility, migration, and microtubule dynamics protein Enzyme p53-regulated inhibitor of G2/M progression 14-3-3 sigma Cell cycle regulator protein Actin related protein Phosphopyruvate dehydratase enzyme Cellular differentiation proteins in epithelial tumors and transcription of c-myc oncogene protein inhibition Cytoskeletal proteins Cytoskeletal proteins Mediate signal transduction protein Heterogeneous nuclear ribonucleoprotein K Cellular adhesion, proliferation, and migration of protein during carcinogenesis Immune response protein Immune response protein Immune response protein Trace element Immune response protein Intercellular adhesion molecule Acute-phase protein
Biochemistry Function
Nano-LC ESI MS/MSþmascot identification MALDI ToF/ToFþCID and LIFT acquired MS/MS Nano-LC ESI MS/MSþmascot identification ICP-MS 2DEþMALDI ToF MS 2DEþMALDI ToF MS 2DEþMALDI ToF MS
Tandem MSþbioinformatic analysis Tandem MSþbioinformatic analysis LCþtandem MS LCþtandem MS MALDI ToF/ToFþmascot identification
DIGEþMS/2DEþMS 2DEþMALDI ToF MS 2DEþMALDI ToF MS 2DEþMALDI ToF MS 2DEþMALDI ToF MS 2DEþMALDI ToF MS 2DEþMALDI ToF MS 2DEþMALDI ToF MS 2DEþMS 2DEþMS 2DEþMS 2DEþMS 2DEþMS
Technology Used
HNSCC indicates head and neck squamous cell carcinoma; DIGE, differential in-gel electrophoresis; MS, mass spectrometry; 2DE, 2-dimensional electrophoresis; MALDI, matrix-assisted laser desorption/ ionization; ToF, time of flight; LC, liquid chromatography; Ig, immunoglobulin; ESI, electrospray ionization; CID, collision-induced dissociation; ICP, inductively coupled plasma; LIFT, laser-induced fragmentation tandem. a Zhou 200262; b Cheng 200871; c Koike 200563; d Kouzu 200664; e Sewell 200744; f Patel 200872; g Ralhan 200973; h Cheng 200545; i Gomes 201079; j Liao 2008.80
Serum
Plasma
Tissue
Sample
Table 1. Potential HNSCC Diagnostic Biomarkers
Head and Neck Cancer and Biomarkers/Rezende et al
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significant down-regulation of 14-3-3r and annexin I was also observed in lymph node metastasis versus primary nasopharyngeal carcinoma. In addition, stathmin upregulation and down-regulation of 14-3-3r and annexin I were significantly correlated with poor histological differentiation, advanced clinical stage, and recurrence, whereas down-regulation of 14-3-3r and annexin I was also significantly correlated with lymph node and distant metastasis. Survival curves showed that patients with stathmin up-regulation and down-regulation of 14-3-3r and annexin I had a poor prognosis. These data suggest that these proteins are potential biomarkers for the differentiation and prognosis of nasopharyngeal carcinoma. By using a different form of HNSCC sample, Patel et al described the utility of a novel proteomics platform for the global detection of expressed proteins in formalinfixed paraffin-embedded tissue.72 This approach enabled identification of a large number of molecules, including cytokeratins and intermediate filament proteins, differentiation markers, proteins involved in stem cell maintenance, signal transduction, and cell cycle regulation, growth and angiogenic factors, matrix-degrading proteases, and proteins with tumor suppressive and oncogenic potential. The ability to correlate protein expression profiles with histopathologic classification of disease may allow the development of novel biomarkers of diagnostic and prognostic value and may help identify novel targets for therapeutic intervention in HNSCC. By using online liquid chromatography and tandem MS, Ralhan et al compared isobaric mass tags (iTRAQ)labeled oral dysplasias and normal tissues against pooled normal control.73 Three best-performing biomarkers were identified by iTRAQ analysis and verified by immunohistochemistry: stratifin, YWHAZ, and hnRNPK. These biomarkers pointed to some key regulatory proteins that link inflammation and development of epithelial dysplasia in oral premalignant lesions, because they discriminate dysplasias from normal tissues. Pathway analysis revealed direct interactions between all 3 biomarkers and their involvement in 2 major networks involved in inflammation, signaling, proliferation, regulation of gene expression, and cancer. Tissue microarray and 2D differential in-gel electrophoresis were used to evaluate HNSCC for differences in protein expression between oral cavity, oropharynx, larynx, and hypopharynx subsites. For the tissue array study, the chosen proteins were cyclin D1, p53 Rb, and p14, and for the 2D differential in-gel electrophoresis, total protein was extracted. The authors did not find sig-
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nificant differences in protein expression between different subsites and proposed that the observed heterogeneity may reflect divergent etiologic pathways irrespective of subsite.74 Patel et al used imaging MS with chemical inkjet printing, revealing differential protein expression in human OSCC.75 The analysis of the resulting protein profiles reveals spectral features at 4500 and 8360 Da that strongly correlate with the SCC region of the tongue. The feature selection of this study was only performed on a single patient, and then the selected peaks were tested on a further 3 patients, which gives some confidence in these diagnostic peaks. However, the identity of these 2 proteins is still unknown. According to the authors, these studies needed to be extended to a larger sample set that includes premalignant lesions, and over a longer period, but it demonstrated that this MS profiling technique produced reproducible, informative chemical images for clinical pathology. Plasma and Serum Biomarker Studies In addition to tumor tissues, plasma and serum from patients could be alternative sources for the study of differential expression, especially for proteomic approaches. Cheng et al observed the high specificity and sensitivity of the fibrinogen a-chain fragment in oral cancer plasma, suggesting that it may be a clinically useful tumor marker.45 In this study, the fibrinogen fragment presented higher sensitivity (100%) and specificity (97%) for cancer than the other markers detected, by MALDI ToF/ToF followed by Mascot identification. Previous studies in animal models have shown that inhibition of fibrinogen strongly diminishes the development of metastatic lung cancer, further demonstrating the important role of fibrinogen in sustaining invasion and survival of tumor cells.76 In the series of coagulation markers tested, only the fibrinogen a-chain was significantly increased in gastric cancer, and it was correlated with tumor TNM stages.77 Similarly, the fibrinogen a-chain peptide has been found to be significantly increased in melanoma.78 Our group in a previous study analyzed plasmas of patients with laryngeal cancer and of healthy smokers by 2D gel electrophoresis and MS. Few differences were found between cancer and control patients. However, 3 spots gathered between platelet count increment 7.3 and 7.6 with different molecular masses appeared exclusively in cancer profiles. From 10 spots identified, 6 correspond to immune system components, including the 3 differential ones: Ig gamma-3 chain C region, complement
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Table 2. Potential HNSCC Physiology Biomarkers
Function
Regulated Protein
Technology Used
Hypoxiaa Tumor transitionb Early events Normal to dysplasia Pro-oncogenesc
IjB kinase b
2DEþpowerblot Multiplex tissue immunoblotting
MMP-9 activationd Tissue differentiation degree/metastatic potentiale
CK-4, CK-14, annexin 1 Cox-2, P53 Transcription factors Nuclear receptors Enzymes TNF-a Cathepsin D
MALDI ToF MS
2DEþMS 2DEþMS
HNSCC indicates head and neck squamous cell carcinoma; 2DE, 2-dimensional electrophoresis; MALDI, matrix-assisted laser desorption/ionization; ToF, time of flight; MS, mass spectrometry; MMP, matrix metalloproteinase; TNF, tumor necrosis factor. a Chen 200481; b Chung 200684; c Koehn 200885; d Hohberger 200886; e Cheng 2008.88
component C4a, and Ig kappa chain C region. Because tobacco is the main cause of laryngeal cancer, and it contains various carcinogenic components, including metallic elements, the presence of these elements was studied. Several trace elements in the identified proteins were determined by inductively coupled plasma MS, where chromium was increased in all proteins analyzed from patients with cancer. Our results reinforce the importance of the immune response as a target in the understanding and treatment of laryngeal cancer and the possibility that chromium is important in the carcinogenic progress.79 In a similar way, serum biomarkers were also used for HNSCC diagnosis. Liao et al analyzed serum proteome for profiling protein markers associated with carcinogenesis and lymph node metastasis in nasopharyngeal carcinoma.80 By 2D image analysis, MALDI ToF MS identification, and enzyme-linked immunosorbent assay validation, 3 proteins were selected. The overexpression of HSP70, sICAM-1, and SAA was observed in nasopharyngeal carcinoma patients and may be of great underlying significance in the clinical detection and management of this kind of cancer. In summary, analysis of the resultant protein profile may have greater utility in early diagnosis by selecting a combination of protein alterations rather than by focusing on specific tumor markers, which may vary between individual patients. HNC Physiology Biomarker Studies The proteomic findings in HNC are not limited to discovering diagnostic biomarkers but also include discovering targets for tumor-specific therapeutic modalities (Table 2). Chen et al identified the hypoxia-regulated proteins in HNC by proteomic and tissue array profiling.81
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Hypoxia is a major determinant of local, regional, and distant failure after anticancer therapy.82 At the molecular level, hypoxia selects tumors with an increased malignant phenotype,83 resulting in resistance to apoptosis and greater propensity for distant metastases. In this way, the identification of hypoxia markers may influence the choice of therapeutic modality. By using 2D gel electrophoresis and powerBlot (antibody-based array), they identified a group of 20 proteins. The majority of these proteins, such as IjB kinase b, MKK3b, highly expressed in cancer, density-regulated protein 1, P150, nuclear transport factor 2, binder of ARL2, paxillin, and transcription termination factor I have not been previously reported to be hypoxia inducible. A strong correlation between IjB kinase b protein expression and tumor oxygenation was observed. They found that IjB kinase b is induced by hypoxia and plays an important role in mediating cell survival under hypoxic stress. In human HNSCC, expression of this protein appeared to be a good indicator of tumor hypoxia and may represent a novel anticancer therapeutic target.81 Studying the normal to tumor transition of esophageal SCC, Chung et al quantified the change in 7 proteins in this tissue transition using multiplex tissue immunoblotting.84 Their data suggest that decreased expression of pan-cytokeratin (CK)-4, CK-14, and annexin 1 are early events. In contrast, the modest increase observed in cyclooxygenase-2 and p53 protein expression with progression from normal to dysplasia suggests that these markers may be most informative in more advanced neoplasia. The increase in cysteine (secreted protein acidic and rich in cysteine) even in stroma underlying dysplasia, as well as the potential to measure the protein in serum, makes it a potential biomarker of early disease. These findings suggest that changes in protein
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expression can be detected during the transition to dysplasia and may be useful biomarkers. Koehn et al analyzed by 2D gel electrophoresis, followed by MALDI ToF MS, subcellular fractions from OSCC and corresponding control samples, enriched in mitochondrial and cytosolic proteins, as well as blood from the tumor.85 They identified 350 different gene products, 20 proteins with deranged levels in the cancer samples, of which 16 were up-regulated. Eight of the up-regulated proteins are associated with gene products involved in the pathways of proto-oncogenes p53, MYC, and MYCN, which are transcription factors, nuclear receptors, or enzymes or have other functions. These results indicated that proteomic analysis is a powerful tool in systems biology for the elucidation of the complexity of expression profiles in cellular processes. Elucidating factors responsible for oral cancer progression at the late preneoplasia/invasion interface were investigated by Hohberger et al, who examined the integral role of matrix metalloproteinase (MMP) activation at this interface.86 These MMPs allow degradation of the extracellular matrix on secretion.87 In keratinocytes and other cells, they have been associated with tissue remodeling processes, including embryogenesis, tumor invasion and metastasis, wound healing, and inflammatory processes.87 The authors believe that inflammation may be a key factor in oral cancer progression in late preneoplasia, and that the inflammation-associated transcription factor, nuclear factor-jB, may be the principal regulator of these processes. In this study, they discovered that the MMP-9 promoter was significantly stimulated by phorbol myristate acetate and tumor necrosis factor (TNF)-a on luciferase reporter gene assays. Furthermore, functional MMP-9 promoter activation was accompanied by significant increases in MMP-9 gene expression. Functional activation of the MMP-9 protein was simulated by TNF-a and phorbol myristate acetate on a fluorescent enzyme-linked immunosorbent serologic assay. Finally, they observed that MMP-9 is the third most significant protein in saliva of oral cavity cancer patients over normal controls. These results suggest that TNF-a has the capacity to provide stimulation of events related to early invasion of oral cavity cancer.86 Trying to identify biomarkers for differentiation and prognosis of nasopharyngeal carcinoma by proteomic analysis, Cheng et al analyzed proteins from pooled microdissected nasopharyngeal carcinoma and normal nasopharyngeal epithelial tissues.88 Thirty-six differential proteins between the nasopharyngeal carcinoma and normal nasopharyngeal epithelial tissues were identified.
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The expression level of cathepsin D in the 2 types of tissues was confirmed by Western blotting and related to differentiation degree and metastatic potential of the nasopharyngeal carcinoma cell lines. Down-regulated cathepsin D expression by small interfering RNA significantly decreased the in vitro invasive ability of cancer cells. Significant cathepsin D down-regulation was observed in nasopharyngeal carcinoma versus normal nasopharyngeal epithelial tissues, whereas significant cathepsin D up-regulation was observed in lymph node metastasis versus primary nasopharyngeal carcinoma. In addition, cathepsin D down-regulation was significantly correlated with poor histological differentiation, whereas cathepsin D up-regulation was significantly correlated with advanced clinical stage, recurrence, and lymph node and distant metastasis. Furthermore, survival curves showed that patients with cathepsin D up-regulation had a poor prognosis. These findings could have clinical value in distinguishing histological grades, predicting the prognosis of nasopharyngeal cancer, and identifying nasopharyngeal cancer patients who are at high risk of metastasis and recurrence. Conclusive Remarks and Future Directions Proteomics, together with genomics, is well on the way to molecular characterization of the different tumor types and to detecting diagnostic and novel therapeutic targets for disease treatment. In addition, functional proteomics methods have also been developed to study the intracellular signaling pathways that underlie the development of cancers, which could therefore significantly contribute to the efficient performance of the entire discovery process. Potential areas for improvement of this approach to HNSCC will arise from studies that include high-risk groups as well as the analysis of serum proteomic profiles before, during, and after definitive treatment of HNSCC to determine whether this technique can be equally useful for monitoring patients for persistent or recurrent disease. In addition, because prognosis and treatment are influenced by early cancer diagnosis, the determination of a cancer biomarker at a proteome level allows this evaluation to be faster.
CONFLICT OF INTEREST DISCLOSURES Supported by Universidade Catolica de Brasilia (UCB), Conselho Nacional de Desenvolvimento Cientı´fico e Technolo´gico (CNPq), Coordenac¸a˜o de Aperfeic¸oamento de Pessoal de Nı´vel Superior (CAPES), Fundac¸a˜o de Amparo a Pesquisa de Minas Gerais (FAPEMIG), and Fundac¸a˜o de Amparo do Distrito Federal (FAPDF).
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REFERENCES 1. Rossini AR, Hashimoto CL, Iriya K, Zerbini C, Baba ER, Moraes-Filho JP. Dietary habits, ethanol and tobacco consumption as predictive factors in the development of esophageal carcinoma in patients with head and neck neoplasms. Dis Esophagus. 2008;21:316-321. 2. Argiris A, Karamouzis MV, Raben D, Ferris RL. Head and neck cancer. Lancet. 2008;371:1695-1709. 3. Iwadate Y. Clinical proteomics in cancer research-promises and limitations of current 2-dimensional gel electrophoresis. Curr Med Chem. 2008;15:2393-2400. 4. Liu ET. Functional genomics of cancer. Curr Opin Genet Dev. 2008;18:251-256. 5. Titcomb CP Jr. High incidence of nasopharyngeal carcinoma in Asia. J Insur Med. 2001;33:235-238. 6. Lippman SM, Sudbo J, Hong WK. Oral cancer prevention and the evolution of molecular-targeted drug development. J Clin Oncol. 2005;23:346-356. 7. Parkin DM, Bray F, Ferlay J, Pisani P. Global cancer statistics, 2002. CA Cancer J Clin. 2005;55:74-108. 8. Annertz K, Anderson H, Biorklund A, et al. Incidence and survival of squamous cell carcinoma of the tongue in Scandinavia, with special reference to young adults. Int J Cancer. 2002;101:95-99. 9. Scully C, Field JK, Tanzawa H. Genetic aberrations in oral or head and neck squamous cell carcinoma (SCCHN): 1. Carcinogen metabolism, DNA repair and cell cycle control. Oral Oncol. 2000;36:256-263. 10. Harris CC. Chemical and physical carcinogenesis: advances and perspectives for the 1990s. Cancer Res. 1991;51:5023s5044s. 11. Lieber CS. Cytochrome P-4502E1: its physiological and pathological role. Physiol Rev. 1997;77:517-544. 12. Vondracek M, Xi Z, Larsson P, et al. Cytochrome P450 expression and related metabolism in human buccal mucosa. Carcinogenesis. 2001;22:481-488. 13. Kriek E, Rojas M, Alexandrov K, Bartsch H. Polycyclic aromatic hydrocarbon-DNA adducts in humans: relevance as biomarkers for exposure and cancer risk. Mutat Res. 1998; 400:215-231. 14. Kawajiri K, Fujii-Kuriyama Y. P450 and human cancer. Jpn J Cancer Res. 1991;82:1325-1335. 15. Jaber MA, Porter SR, Scully C, Gilthorpe MS, Bedi R. The role of alcohol in non-smokers and tobacco in non-drinkers in the aetiology of oral epithelial dysplasia. Int J Cancer. 1998;77:333-336. 16. Schlecht NF, Franco EL, Pintos J, et al. Interaction between tobacco and alcohol consumption and the risk of cancers of the upper aero-digestive tract in Brazil. Am J Epidemiol. 1999;150:1129-1137. 17. Hsu H, Lacey DL, Dunstan CR, et al. Tumor necrosis factor receptor family member RANK mediates osteoclast differentiation and activation induced by osteoprotegerin ligand. Proc Natl Acad Sci U S A. 1999;96:3540-3545. 18. Day GL, Blot WJ, Shore RE, et al. Second cancers following oral and pharyngeal cancers: role of tobacco and alcohol. J Natl Cancer Inst. 1994;86:131-137. 19. Hahn M, Hagedorn G, Kuhlisch E, Schackert HK, Eckelt U. Genetic polymorphisms of drug-metabolizing enzymes and susceptibility to oral cavity cancer. Oral Oncol. 2002; 38:486-490. 20. Bondy ML, Spitz MR, Halabi S, et al. Association between family history of cancer and mutagen sensitivity in upper
Cancer
November 1, 2010
21. 22. 23. 24. 25. 26.
27. 28.
29. 30. 31.
32.
33.
34. 35. 36.
37.
38.
aerodigestive tract cancer patients. Cancer Epidemiol Biomarkers Prev. 1993;2:103-106. Tran N, Rose BR, O’Brien CJ. Role of human papillomavirus in the etiology of head and neck cancer. Head Neck. 2007;29:64-70. Negri E, Franceschi S, Bosetti C, et al. Selected micronutrients and oral and pharyngeal cancer. Int J Cancer. 2000; 86:122-127. Yang CS. Research on esophageal cancer in China: a review. Cancer Res. 1980;40:2633-2644. Mehrotra R, Yadav S. Oral squamous cell carcinoma: etiology, pathogenesis and prognostic value of genomic alterations. Indian J Cancer. 2006;43:60-66. Weinberg RA. Tumor suppressor genes. Science. 1991;254: 1138-1146. Grandis JR, Tweardy DJ. Elevated levels of transforming growth factor alpha and epidermal growth factor receptor messenger RNA are early markers of carcinogenesis in head and neck cancer. Cancer Res. 1993;53:3579-3584. Karamouzis MV, Grandis JR, Argiris A. Therapies directed against epidermal growth factor receptor in aerodigestive carcinomas. JAMA. 2007;298:70-82. Kato Y, Tapping RI, Huang S, Watson MH, Ulevitch RJ, Lee JD. Bmk1/Erk5 is required for cell proliferation induced by epidermal growth factor. Nature. 1998;395:713716. Owens DM, Keyse SM. Differential regulation of MAP kinase signalling by dual-specificity protein phosphatases. Oncogene. 2007;26:3203-3213. Ferrara N. VEGF as a therapeutic target in cancer. Oncology. 2005;69(suppl 3):11-16. Sunny L, Yeole BB, Hakama M, et al. Oral cancers in Mumbai, India: a fifteen years perspective with respect to incidence trend and cumulative risk. Asian Pac J Cancer Prev. 2004;5:294-300. Kuss I, Hathaway B, Ferris RL, Gooding W, Whiteside TL. Decreased absolute counts of T lymphocyte subsets and their relation to disease in squamous cell carcinoma of the head and neck. Clin Cancer Res. 2004;10:3755-3762. Lopez-Albaitero A, Nayak JV, Ogino T, et al. Role of antigen-processing machinery in the in vitro resistance of squamous cell carcinoma of the head and neck cells to recognition by CTL. J Immunol. 2006;176:3402-3409. Mehrotra R, Varricchio F, Husain SR, Puri RK. Head and neck cancers, but not benign lesions, express interleukin-4 receptors in situ. Oncol Rep. 1998;5:45-48. Mehrotra R. Interleukin 13 is secreted by human head and neck tumours and does not modulate their growth in vitro. Indian J Exp Biol. 1998;36:805-807. Bose A, Ghosh D, Pal S, Mukherjee KK, Biswas J, Baral R. Interferon alpha2b augments suppressed immune functions in tobacco-related head and neck squamous cell carcinoma patients by modulating cytokine signaling. Oral Oncol. 2006;42:161-171. Chae SC, Li CS, Kim KM, et al. Identification of polymorphisms in human interleukin-27 and their association with asthma in a Korean population. J Hum Genet. 2007; 52:355-361. Hu JC, Coffin RS, Davis CJ, et al. A phase I study of OncoVEXGM-CSF, a second-generation oncolytic herpes simplex virus expressing granulocyte macrophage colony-stimulating factor. Clin Cancer Res. 2006;12: 6737-6747.
4923
Review Article 39. Wasinger VC, Cordwell SJ, Cerpa-Poljak A, et al. Progress with gene-product mapping of the Mollicutes: Mycoplasma genitalium. Electrophoresis. 1995;16:1090-1094. 40. Charlwood J, Skehel JM, Camilleri P. Analysis of N-linked oligosaccharides released from glycoproteins separated by 2dimensional gel electrophoresis. Anal Biochem. 2000;284:4959. 41. Rudert F. Genomics and proteomics tools for the clinic. Curr Opin Mol Ther. 2000;2:633-642. 42. Celis JE, Gromov P. 2D protein electrophoresis: can it be perfected? Curr Opin Biotechnol. 1999;10:16-21. 43. Unlu M, Morgan ME, Minden JS. Difference gel electrophoresis: a single gel method for detecting changes in protein extracts. Electrophoresis. 1997;18:2071-2077. 44. Sewell DA, Yuan CX, Robertson E. Proteomic signatures in laryngeal squamous cell carcinoma. ORL J Otorhinolaryngol Relat Spec. 2007;69:77-84. 45. Cheng AJ, Chen LC, Chien KY, et al. Oral cancer plasma tumor marker identified with bead-based affinity-fractionated proteomic technology. Clin Chem. 2005;51:22362244. 46. Chapman K. The ProteinChip Biomarker System from Ciphergen Biosystems: a novel proteomics platform for rapid biomarker discovery and validation. Biochem Soc Trans. 2002; 30:82-87. 47. Conrads TP, Zhou M, Petricoin EF III, Liotta L, Veenstra TD. Cancer diagnosis using proteomic patterns. Expert Rev Mol Diagn. 2003;3:411-420. 48. Schraml P, Kononen J, Bubendorf L, et al. Tissue microarrays for gene amplification surveys in many different tumor types. Clin Cancer Res. 1999;5:1966-1975. 49. Camp RL, Charette LA, Rimm DL. Validation of tissue microarray technology in breast carcinoma. Lab Invest. 2000;80:1943-1949. 50. Rosenzweig CN, Zhang Z, Sun X, et al. Predicting prostate cancer biochemical recurrence using a panel of serum proteomic biomarkers. J Urol. 2009;181:1407-1414. 51. Hanrieder J, Wetterhall M, Enblad P, Hillered L, Bergquist J. Temporally resolved differential proteomic analysis of human ventricular CSF for monitoring traumatic brain injury biomarker candidates. J Neurosci Methods. 2009;177:469-478. 52. Wang QT, Li YZ, Liang YF, et al. Construction of a multiple myeloma diagnostic model by magnetic bead-based MALDI-ToF mass spectrometry of serum and pattern recognition software. Anat Rec (Hoboken). 2009;292:604-610. 53. Mannello F, Medda V, Tonti GA. Protein profile analysis of the breast microenvironment to differentiate healthy women from breast cancer patients. Expert Rev Proteomics. 2009;6:43-60. 54. Tian M, Cui YZ, Song GH, et al. Proteomic analysis identifies MMP-9, DJ-1 and A1BG as overexpressed proteins in pancreatic juice from pancreatic ductal adenocarcinoma patients. BMC Cancer. 2008;8:241. 55. Streckfus CF, Dubinsky WP. Proteomic analysis of saliva for cancer diagnosis. Expert Rev Proteomics. 2007;4:329-332. 56. Soler-Garcia AA, Johnson D, Hathout Y, Ray PE. Ironrelated proteins: candidate urine biomarkers in childhood HIV-associated renal diseases. Clin J Am Soc Nephrol. 2009;4:763771. 57. Deininger SO, Ebert MP, Futterer A, Gerhard M, Rocken C. MALDI imaging combined with hierarchical clustering as a new tool for the interpretation of complex human cancers. J Proteome Res. 2008;7:5230-5236.
4924
58. Walch A, Rauser S, Deininger SO, Hofler H. MALDI imaging mass spectrometry for direct tissue analysis: a new frontier for molecular histology. Histochem Cell Biol. 2008;130:421-434. 59. Gleich LL, Li YQ, Wang X, Stambrook PJ, Gluckman JL. Variable genetic alterations and survival in head and neck cancer. Arch Otolaryngol Head Neck Surg. 1999;125:949-952. 60. Wadsworth JT, Somers KD, Cazares LH, et al. Serum protein profiles to identify head and neck cancer. Clin Cancer Res. 2004;10:1625-1632. 61. Gourin CG, Xia ZS, Han Y, et al. Serum protein profile analysis in patients with head and neck squamous cell carcinoma. Arch Otolaryngol Head Neck Surg. 2006;132:390397. 62. Zhou G, Li H, DeCamp D, et al. 2D differential in-gel electrophoresis for the identification of esophageal scans cell cancer-specific protein markers. Mol Cell Proteomics. 2002;1:117-124. 63. Koike H, Uzawa K, Nakashima D, et al. Identification of differentially expressed proteins in oral squamous cell carcinoma using a global proteomic approach. Int J Oncol. 2005; 27:59-67. 64. Kouzu Y, Uzawa K, Koike H, et al. Overexpression of stathmin in oral squamous-cell carcinoma: correlation with tumour progression and poor prognosis. Br J Cancer. 2006; 94:717-723. 65. Hanash SM, Strahler JR, Kuick R, Chu EH, Nichols D. Identification of a polypeptide associated with the malignant phenotype in acute leukemia. J Biol Chem. 1988;263: 12813-12815. 66. Friedrich B, Gronberg H, Landstrom M, Gullberg M, Bergh A. Differentiation-stage specific expression of oncoprotein 18 in human and rat prostatic adenocarcinoma. Prostate. 1995;27:102-109. 67. Price DK, Ball JR, Bahrani-Mostafavi Z, et al. The phosphoprotein Op18/stathmin is differentially expressed in ovarian cancer. Cancer Invest. 2000;18:722-730. 68. Takahashi M, Yang XJ, Lavery TT, et al. Gene expression profiling of favorable histology Wilms tumors and its correlation with clinical features. Cancer Res. 2002;62:6598-6605. 69. Bieche I, Lachkar S, Becette V, et al. Overexpression of the stathmin gene in a subset of human breast cancer. Br J Cancer. 1998;78:701-709. 70. Nakashima D, Uzawa K, Kasamatsu A, et al. Protein expression profiling identifies maspin and stathmin as potential biomarkers of adenoid cystic carcinoma of the salivary glands. Int J Cancer. 2006;118:704-713. 71. Cheng AL, Huang WG, Chen ZC, et al. Identification of novel nasopharyngeal carcinoma biomarkers by laser capture microdissection and proteomic analysis. Clin Cancer Res. 2008; 14:435-445. 72. Patel V, Hood BL, Molinolo AA, et al. Proteomic analysis of laser-captured paraffin-embedded tissues: a molecular portrait of head and neck cancer progression. Clin Cancer Res. 2008;14:1002-1014. 73. Ralhan R, Desouza LV, Matta A, et al. iTRAQ-multidimensional liquid chromatography and tandem mass spectrometry-based identification of potential biomarkers of oral epithelial dysplasia and novel networks between inflammation and premalignancy. J Proteome Res. 2009;8:300-309. 74. Weinberger PM, Merkley M, Lee JR, et al. Use of combination proteomic analysis to demonstrate molecular similarity of head and neck squamous cell carcinoma arising from
Cancer
November 1, 2010
Head and Neck Cancer and Biomarkers/Rezende et al
75.
76.
77. 78. 79.
80.
81.
different subsites. Arch Otolaryngol Head Neck Surg. 2009;135:694-703. Patel SA, Barnes A, Loftus N, et al. Imaging mass spectrometry using chemical inkjet printing reveals differential protein expression in human oral squamous cell carcinoma. Analyst. 2009;134:301-307. Palumbo JS, Talmage KE, Liu H, La Jeunesse CM, Witte DP, Degen JL. Plasminogen supports tumor growth through a fibrinogen-dependent mechanism linked to vascular patency. Blood. 2003;102:2819-2827. Abbasciano V, Tassinari D, Sartori S, et al. Usefulness of coagulation markers in staging of gastric cancer. Cancer Detect Prev. 1995;19:331-336. Bottasso B, Mari D, Coppola R, Santoro N, Vaglini M, Mannucci PM. Hypercoagulability and hyperfibrinolysis in patients with melanoma. Thromb Res. 1996;81:345-352. Gomes CP, Freire MS, Pires BR, et al. Comparative proteomical and metalloproteomical analyses of human plasma from patients with laryngeal cancer. Cancer Immunol Immunother. 2010;59:173-181. Liao Q, Zhao L, Chen X, Deng Y, Ding Y. Serum proteome analysis for profiling protein markers associated with carcinogenesis and lymph node metastasis in nasopharyngeal carcinoma. Clin Exp Metastasis. 2008;25:465-476. Chen Y, Shi G, Xia W, et al. Identification of hypoxia-regulated proteins in head and neck cancer by proteomic and tissue array profiling. Cancer Res. 2004;64:7302-7310.
Cancer
November 1, 2010
82. Brizel DM, Dodge RK, Clough RW, Dewhirst MW. Oxygenation of head and neck cancer: changes during radiotherapy and impact on treatment outcome. Radiother Oncol. 1999;53:113-117. 83. Subarsky P, Hill RP. The hypoxic tumour microenvironment and metastatic progression. Clin Exp Metastasis. 2003;20: 237-250. 84. Chung JY, Braunschweig T, Hu N, et al. A multiplex tissue immunoblotting assay for proteomic profiling: a pilot study of the normal to tumor transition of esophageal squamous cell carcinoma. Cancer Epidemiol Biomarkers Prev. 2006;15: 1403-1408. 85. Koehn J, Krapfenbauer K, Huber S, et al. Potential involvement of MYC- and p53-related pathways in tumorigenesis in human oral squamous cell carcinoma revealed by proteomic analysis. J Proteome Res. 2008;7:3818-3829. 86. Hohberger L, Wuertz BR, Xie H, Griffin T, Ondrey F. TNF-alpha drives matrix metalloproteinase-9 in squamous oral carcinogenesis. Laryngoscope. 2008;118:1395-1399. 87. Werb Z, Vu TH, Rinkenberger JL, Coussens LM. Matrixdegrading proteases and angiogenesis during development and tumor formation. APMIS. 1999;107:11-18. 88. Cheng AL, Huang WG, Chen ZC, et al. Identificating cathepsin D as a biomarker for differentiation and prognosis of nasopharyngeal carcinoma by laser capture microdissection and proteomic analysis. J Proteome Res. 2008;7:24152426.
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