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Year : 2014  |  Volume : 1  |  Issue : 1  |  Page : 2

Quantitative proteomic analysis of different stages of rat lingual carcinogenesis

1 Vaidya Laboratory, TMC Advanced Centre for Treatment, Research and Education in Cancer, Kharghar Navi-Mumbai, India
2 Institute of Bioinformatics, International Technology Park Limited, Whitefield, Bengaluru, Karnataka, India
3 Asian Institute of Oncology, Department of Pathology, S L Raheja Hospital, Mahim, Mumbai, Maharashtra, India
4 Department of Oral and Maxillofacial Pathology, Ragas Dental College and Hospital, Chennai, Tamil Nadu, India
5 McKusick Nathans Institute of Genetic Medicine; Department of Biological Chemistry; Department of Oncology; Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
6 Animal House facility, TMC Advanced Centre for Treatment, Research and Education in Cancer, Kharghar Navi Mumbai, India

Date of Submission22-Jan-2014
Date of Acceptance07-Mar-2014
Date of Web Publication09-May-2014

Correspondence Address:
Milind Murlidhar Vaidya
Vaidya Laboratory, TMC Advanced Centre for Treatment, Research and Education in Cancer, Kharghar Navi-Mumbai, India

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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/2393-8633.132172

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Background: In India, oral squamous cell carcinoma (OSCC) is the single largest group of malignancies in males. Early diagnosis of cancer is difficult because of the lack of specific symptoms and/or biomarkers for early disease. Animal models provide an opportunity to study development and progression of cancers. Materials and Methods: In this study, we have explored the 4-nitroquinoline 1-oxide (4NQO)-induced tongue cancer model in Sprague Dawley rats. We compared the protein expression profiles of normal tissues with different stages of rat tongue cancer using isobaric tags for relative and absolute quantitation (iTRAQ)-liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics strategy. We validated some known and novel proteins by immunohistochemistry (IHC) and real-time polymerase chain reaction (PCR). Results: We observed hyperplasia, papillomas, and carcinomas after 120, 160, and 200 days treatment of 4NQO, respectively. LC-MS/MS analysis resulted in identification of 2223 proteins. Of these, 415 proteins were found to be differentially expressed in tumors, 333 proteins in papilloma and 109 proteins in hyperplasia. We have found alterations in several previously reported as well as novel proteins during rat tongue carcinogenesis. We validated known molecules such as vimentin, fascin, periostin, transglutaminase 3 by IHC and cornulin by real-time PCR on rat tissues. We also validated tenascin N, a novel protein by IHC on rat as well as in human tongue tissues. Conclusion: To the best of our knowledge, this is the first in-depth differential proteomics study carried out using an experimental rat model of OSCC. Proteomic alterations observed in this study provide insights into carcinogenesis process and may serve as a valuable resource for oral cancer biomarker discovery.

Keywords: Chemical carcinogenesis, isobaric tags for relative and absolute quantitation, mass spectrometry, oral cancer, rat model

How to cite this article:
Soni BL, Marimuthu A, Pawar H, Sawant SS, Borges A, Kannan R, Pandey A, Ingle AD, Harsha HC, Vaidya MM. Quantitative proteomic analysis of different stages of rat lingual carcinogenesis. Clin Commun Oncol 2014;1:2

How to cite this URL:
Soni BL, Marimuthu A, Pawar H, Sawant SS, Borges A, Kannan R, Pandey A, Ingle AD, Harsha HC, Vaidya MM. Quantitative proteomic analysis of different stages of rat lingual carcinogenesis. Clin Commun Oncol [serial online] 2014 [cited 2017 Mar 26];1:2. Available from:

  Introduction Top

Oral squamous cell carcinoma (OSCC) is the sixth largest group of malignancies globally and represents one of the leading causes of mortality. [1] It remains a major cancer in the Indian subcontinent, comprising >40% of all cancer cases. The most commonly involved sites of tumor development in the Indian population are buccal mucosa and tongue. [2] The major risk factors for oral cancer include chewing tobacco either alone or with substances such as betel nut and alcohol. Precancerous lesions like leukoplakia and submucous fibrosis are also quite prevalent in India due to these habits. [3] The malignant transformation of oral leukoplakia has been proposed to range from 15%-18%, respectively. [3],[4] Despite advances in treatment and therapeutic modalities, the 5 year survival rate of OSCC has not changed much in the last few decades. The possible reasons for poor survival rates are late detection and local recurrence/regional lymph node metastasis.

In patients, the molecular analysis of multiple stages of carcinogenesis is hampered by the unavailability of biopsies of all the stages of oral carcinogenesis (e.g., normal, premalignant, dysplastic, and malignant lesions). However, animal models of carcinogenesis allow the reproducible isolation of all stages, including normal tissues, which are then amenable to pathological, genetic, and biochemical analyses. [5] We chose the 4-nitroquinoline 1-oxide (4NQO)-induced rat model of carcinogenesis as our model for studies related to oral carcinogenesis because it mimics molecular and pathological changes observed in patients. [5],[6]

Proteomics has grown as powerful tool for biomarker discovery in various cancers. [7],[8] A few proteomics studies on human samples have been conducted to dissect the molecular events, which lead to development of OSCC from leukoplakia. [9],[10] Isobaric tags for relative and absolute quantitation (iTRAQ)-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) is one of the useful quantitative approaches in proteomics to identify the differences between protein expression profiles of normal and diseased samples. [8]

In this study, we utilized 4NQO-induced rat model for tongue cancer because it recapitulates all the histological grades of human lingual carcinogenesis. [6],[11] We obtained hyperplasia, papilloma, and carcinoma stages after 120, 160, and 200 days treatment of 4NQO, respectively. An iTRAQ-based differential proteomic analysis was carried out by labeling tryptic peptides derived from protein samples isolated from different stages of rat lingual carcinogenesis followed by LC-MS/MS analysis. This resulted in identification of 2223 total proteins. Of these, 415 proteins were found to be differentially expressed SCC as compared with normal tissues. Among these, 109 proteins were differentially expressed in hyperplasia, while 333 proteins were differentially expressed in papillomas as compared with normal tissues. We validated some known molecules, including vimentin (Vim), fascin (Fscn1), and periostin (Postn) by immunohistochemistry (IHC). We also validated a novel protein, tenascin N (Tnn) in both rat and human tissues by IHC.

Thus, to the best of our knowledge, this is the first in-depth differential proteomics study on rat model of tongue carcinogenesis, which led to the identification of several known as well as novel molecules as candidate biomarkers for lingual carcinogenesis. Our studies demonstrate the utility of this model in the study of oral carcinogenesis and as tool for early biomarker discovery of tongue cancer.

  Materials and Methods Top

Animal model for tongue cancer

All animal experiments were approved by the Institutional Animal Ethics Committee. 5-6 weeks old male Sprague Dawley Rats were used to induce oral tongue cancer. Animals were randomized and grouped in three groups: Untreated group (n = 36), acetone (vehicle) treated (n = 36), and 4NQO treated (n = 48). Each group was further sub divided into three sub-groups and treated for 120, 160, and 200 days, respectively. For 4NQO treatment animals were distributed into three groups (12 animals for 120 and 160 days while 24 animals for 200 days). 4NQO was dissolved in acetone and finally given to the animals at 30 ppm concentration in normal drinking water[Figure 1]a. After each time point of treatment, animals were fed with normal drinking water for another 15 days to get the stable changes. Animals were sacrificed by CO 2 inhalation followed by cervical dislocation. Detail distribution of 4NQO treated animals with their corresponding lesions on the tongue is given in [Table 1].
Figure 1: Rat lingual carcinogenesis model. (a) Protocol for lingual carcinogenesis, 5-6 weeks old Sprague Dawley male rats were taken and treated with 30 ppm of 4NQO in drinking water for 120, 160, and 200 days, respectively (b) Morphological alterations after 4-nitroquinoline 1-oxide (4NQO) treatment. (c) Photomicrograph of Hematoxylin and Eosin staining of different stages of rat lingual carcinogenesis (×100)

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Table 1: Incidence of histopathological lesions in tongue of 4NQO treated rat for the development of oral carcinogenesis model

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Gross lesions were seen on the base of the dorsal tongue of rat [Figure 1]b. Histopathological observations were made by an experienced pathologist using hematoxylin and eosin stained slides [Figure 1]c.

Protein extraction and pooling of samples

Approximately 30 mg of epithelial tissue from the rat tongue was pulverized in liquid nitrogen by mortar and pestle. The powdered tissue was reconstituted in 0.5% sodium dodecyl sulfate and sonicated using ultrsonicator on ice. Each sonication cycle was of 20s of pulsing at 50% output with intermittent gap of 45s; this cycle was repeated 3 times. Subsequently, the cell lysate was centrifuged at 14,000 rpm for 10 min at 40°C. Supernatant was transferred into fresh eppendorf tube and total protein content was measured using Lowry's method. [12] 100 μg of protein was pooled from each group normal (n = 10), hyperplasia (n = 5), papilloma (n = 5), and tumor (n = 5). Cell lysate were stored at −80°C until further use.

Protein digestion and isobaric tags for relative and absolute quantitation labeling

100 μg of total protein from each pool representing control, hyperplasia, papilloma, and carcinoma was used for iTRAQ labeling. Labeling was carried out as per manufacturer's instructions. Briefly, proteins were subjected to reduction using 2 ul of tris-(2-corboxyethyl) phosphine at 60°C for 1 h and alkylated with cystein blocking reagent, methyl methanethiosulfonate for 10 min at room temperature. They were then digested with sequencing grade trypsin (Promega, Madison, WI) (1:20) at 37°C for 16 h. The peptide digest from each sample type was subjected to iTRAQ labeling. Normal, hyperplasia, papilloma, and carcinoma samples were labeled with iTRAQ reagents yielding reporter ions of m/z 114, 115, 116, and 117 respectively. Labeled samples were then pooled and subjected to strong cationic exchange chromatography.

Strong cation exchange fractionation

Pooled samples were diluted with solvent A (10 mM of KH 2 PO 4, 20% acetonitrile, pH 2.8). The diluted samples were acidified by adding phosphoric acid to reduce the pH to 2.8. Acidified sample was loaded on to strong cation exchange chromatography column (polyLC Inc.) at a flow rate of 250 ul/min followed by washing for 20 min. The peptides were fractionated using a 30 min gradient from 8% solvent B (350 mM KCl, 10 mM KH 2 PO 4, and 20% Acetonitrile pH 2.8) to 50% solvent B, to a total of 23 fractions. Subsequently, the peptides were cleaned up using C18 zip tips. Prior to LC-MS/MS analysis, the peptide fractions were dried and stored at −20°C.

Liquid chromatography-tandem mass spectrometry analysis

Liquid chromatography-tandem mass spectrometry analysis of the iTRAQ labeled peptides was carried out using LTQ-Orbitrap Velos mass spectrometer interfaced with Agilent's 1200 Series nanoflow LC system. The chromatographic capillary columns used were packed with Magic C18 AQ (Michrom Bioresources, 5 μm particle size, pore size 100 Ε) reversed phase material in 100% acetonitrile at a pressure of 1000 psi. The peptides were first loaded on to a trap column (75 × 2 cm) at a flow rate of 5 μl/min followed by separation on an analytical column (75 × 10 cm) at a flow rate of 300 nl/min. The peptides were then eluted using a linear gradient of 7-30% solvent B (90% acetonitrile, 0.1% formic acid) over 50 min. MS analysis was performed in a data dependent manner with full scans acquired using Orbitrap mass analyzer at a mass resolution of 60,000 at 400 m/z. For each cycle, 20 most intense precursor ions from a survey scan were selected for MS/MS and detected at a mass resolution of 15,000 at m/z 400. The fragmentation was carried out using higher-energy collision dissociation with 40% normalized collision energy. The ions selected for fragmentation were dynamically excluded for 30s. The automatic gain control for full fourier transformed MS (FT MS) was set to 1 million ions and for FT MS/MS was set to 0.1 million ions with a maximum time of accumulation of 750 ms and 100 ms, respectively. For accurate mass measurements, the lock mass option was enabled. Internal calibration was enabled using the polydimethylcyclosiloxane (m/z, 445.12) ion.

Data analysis

The raw files obtained from LC-MS/MS analysis were processed using Proteome Discoverer (Version software (Thermo Fisher Scientific, USA). MS/MS searches were carried out against NCBI RefSeq 49 rat protein database (n = 25,317) using sequest and mascot search algorithms. Oxidation of methionine, iTRAQ 4-plex modification at peptide N-terminus and lysine (K) were selected as variable modifications and methylthio of cysteine as a fixed modification. MS and MS/MS tolerance were set to 20 ppm and 0.1 Da, respectively. One missed cleavage was allowed. False discovery rate (FDR) was calculated using a decoy database. Peptide spectrum matches at 1% FDR were used for protein identification and quantitation. Relative quantification of peptides was done on the basis of relative intensity of reporter ions (115, 116, and 117 for hyperplasia, papilloma and carcinoma respectively) with respect to normal (114 for vehicle control). Protein ratios were calculated as the median of all the peptide ratios corresponding to respective proteins. A fold change of >2 was considered as upregulated while <0.5 was considered as downregulated.

Collection of human oral tumors and premalignant tissues

The tongue tumor tissues (n = 34) were collected from Tata Memorial Hospital, Mumbai, India at the time of surgery. In 14 of the cases, the adjoining histologically normal tissue was also collected. 10 paraffin embedded blocks of the biopsies collected from leukoplakia of tongue were obtained from Ragas Dental College, Chennai, India and Nair Dental Hospital, Mumbai, India. This study was approved by the Human Ethics Committees of the respective Institutional Review Boards. Informed consent was obtained from the patients before enrolling them in this study.


Formalin-fixed, paraffin-embedded, 5 μm thick rat and human tissue sections were mounted on poly-l-lysine coated glass slides. Sections were de-paraffinized with xylene and incubated with 3% hydrogen peroxide in methanol for 30 min in dark to quench the endogenous peroxidase activity of the tissues. After blocking with horse serum for 1 h at 37°C in humidified chamber, sections were incubated with primary antibodies, Vim (Sigma V 6630, mouse monoclonal, dilution 1:400), periostin (Postn) (Santacruz, sc 49,480, rabbit polyclonal, dilution 1:10), Fscn1 (Pierce, MA1-20,912, mouse monoclonal dilution 1:100), Transglutaminase 3 (Tgm3) (Santacruz, sc-101,366, mouse monoclonal dilution 1:8,000), and tenascin N (Tnn) (Sigma, HPA-026,764 Rabbit polyclonal, dilution 1:100 [for both rat and human samples]) overnight at 4°C. Detection was done using Vectastain ABC system (Vector Laboratories, CA). Diaminobenzidine was used as the chromogen and slides were counterstained with Mayor's hematoxylin.

Ribonucleic acid isolation and quantitative real-time-polymerase chain reaction

To validate our proteomics data, we also performed quantitative real-time-polymerase chain reaction (qRT-PCR) analysis. Total cellular ribonucleic acid (RNA) was extracted from the tissue by Tri-reagent (Sigma-Aldrich, USA) as per manufacturer's protocol. RNA was estimated by measuring absorbance at 260 nm and 280 nm using nanodrop (ND-1000 Spectrophotometer, Wilmington, USA). cDNA synthesis was carried out as per the manufacturer's protocol (Fermentas, Thermo Scientific, Waltham, MA) and the obtained cDNA was used as template for qRT-PCR. Master Mix SYBR Green (Applied Biosystems, Bedford, MA) was used with 5nM of forward and reverse primers [Table 2]. Real-time quantitative PCR was performed with the ABI PRISM7700 Sequence Detection System. Beta actin gene was used as endogenous control. All amplifications were done in triplicate. Results are expressed as relative gene expression using the 2-ΔCt method. [13]
Table 2: Primer sequences used in qRT‑PCR

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  Results and Discussion Top

Experimental animal models have proved to be an important tool to study tumor progression. [6] In this study, Sprague Dawley rats were treated with 30 ppm of 4NQO in drinking water and sacrificed after different time points [Figure 1]c. 4NQO is potent carcinogen and widely used in studies understanding the experimental oral carcinogenesis. It is metabolically converted in to its active form 4 hydroxyaminoquinoline-1-oxide (4HAQO) by enzyme NADH: 4NQO nitroreductase and NAD (P) H: Quinone reductase. This activated molecule 4HAQO preferably binds to guanine residues and forms a DNA adduct. These adducts mimic ultraviolet-induced pyrimidine dimer formation. It has been proposed that the carcinogenesis process induced by 4NQO shows similar molecular alterations as in human carcinogenesis. [6],[11] [Figure 1]b shows gross morphological alterations on the posterior dorsal of the tongue. The histopathological analysis of posterior dorsal tongue epithelium revealed no alterations in vehicle and untreated groups . However, treatment with 4NQO for 120 days resulted in the hyperplasia with hyperkeratosis while 160 days treatment resulted in the papillary growth of the squamous epithelium with increased hyperkeratosis. 200 days treatment resulted in well-differentiated SCC with marked disorganized and infiltrative growth of squamous cells [Figure 1]c and [Table 1]. The majority of lesions were at the dorsum of posterior tongue. One possible reason for this site specificity could be higher activity/expression of enzyme 4NQO reductase at the base of the tongue. [14]

Proteomics is a promising approach for identification of markers for early detection of cancers. It has been successfully employed in studies of various tumor tissues and body fluids. [8],[15] Studies on oral cancer patients to investigate possible biomarkers for early diagnosis/prognosis have been reported. [4],[8] Pawar et al. carried out tissue proteomics on esophageal squamous cell carcinoma for novel biomarkers discovery, while Bijian et al. have used serum proteomics approach to discover serum biomarkers for OSCC. [8],[15] Since our goal was to study sequential changes during oral carcinogenesis, we collected only tissue samples and therefore we carried out only tissue proteomics. The proteomics strategy employed in our study is shown in [Figure 2].
Figure 2: Work flow for quantitative tissue proteomics using isobaric tags for relative and absolute quantitation (iTRAQ) labeling and validation of biomarkers for tongue squamous cell carcinoma. For iTRAQ labeling, Proteins were isolated from 10 normals, 5 hyperplasia, 5 papilloma, and 5 tumor tissues, respectively. Proteins were subjected to trypsin digestion followed by iTRAQ labeling of peptides. Posts labeling the peptides were pooled and fractionated using strong cation exchange chromatography, followed by liquid chromatography tandem mass spectrometry/mass spectrometry on Orbitrap Velos mass spectrometer. Data were searched using Mascot and SEQEST search engines. Some of the over expressed proteins (e.g., Tnn) were validated using immunohistochemistry

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Isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry analysis

We employed iTRAQ based quantitative proteomics to analyze differences in protein expression profiles at different stages of tongue carcinogenesis as described under material and method section. A list of proteins with identified peptides is given in the Supplementary Tables S1 and S2, respectively.

Quantitative analysis of mass spectrometry data

We identified a number of differentially expressed proteins at different stages of rat lingual carcinogenesis when compared with normal vehicle treated control. We identified a total of 2223 proteins of which 415 proteins were found to be differentially expressed in tumors when compared to normal tissues. Of these 415 proteins, 194 proteins were upregulated while 221 proteins were downregulated in premalignant and malignant lesions. [Table 3] describes the details of differentially expressed proteins at each stage.
Table 3: List of differentially expressed proteins during different stages of rat lingual carcinogenesis. Proteins showing differential expression >2‑fold were reported as upregulated while proteins showing differential expression <2‑fold were reported as downregulated

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Bioinformatics analysis of the data

Bioinformatics analysis was carried out to classify proteins based on subcellular localization and biological function. We carried out classification based on Gene Ontology annotations. The distribution of proteins identified in our study based on subcellular localization and biological process is provided in [Figure 3]a and b, respectively. All proteins identified in the current iTRAQ-based analysis of rat lingual carcinogenesis were categorized on the basis of primary subcellular locations [Figure 3]a, which resulted in 1835 proteins (83%) being localized to one of the subcellular compartments. In addition, proteins were classified on the basis of biological processes (e.g., cell signaling and communication). This resulted in the identification of 1786 proteins (80%), which were grouped into one of biological processes [Figure 3]b. The majority of the grouped proteins play a role in cellular metabolism, protein synthesis, degradation, and transport.
Figure 3: Classification of proteins by gene ontology based on their cellular localization and biological process. Panel (a) - Distribution of proteins based on their cellular localization using gene ontology classifier. Panel (b) - Distribution of proteins based on their biological processes using gene ontology classifier

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Some of these differentially expressed proteins have already been identified in human OSCC while we have detected some novel proteins, which have not been reported previously. Here, we have validated some of the known candidate proteins whose differential expression in human oral carcinomas has been previously reported. These include Vim, Fscn1, Tgm3, Postn and cornulin (Crnn).

Known upregulated proteins identified in rat lingual carcinogenesis


Vimentin is type III intermediate filament protein, which is ubiquitously expressed in mesenchymal cells. This protein not only has important role in the epithelial-mesenchymal transition of epithelial cells, but also has major role in the tumor microenvironment remodeling to facilitate the tumor cell metastasis. [16] In our proteomics study on experimental model, we have observed the sequential increase in Vim expression [Figure 4]a. We noted a 2-fold upregulation of Vim in tumor as compared with normal tissues. IHC data [Figure 5]a revealed that Vim expression was not detectable in normal epithelial tissues, but hyperplastic tissues demonstrated weak staining in cytoplasm and suprabasal layers. We noticed increased suprabasal and cytoplasmic expression of Vim in papillomas and carcinomas as compared with normal tissues [Figure 5]a. It has been shown that Vim expression begins in epithelial layers of variety of human cancers including head and neck, [17] prostate, [18] and breast cancers. [19] Recent study from our lab has shown aberrant Vim expression in precancerous lesions and SCC of oral mucosa. [20] Chaw et al. 2012 have proposed that aberrant expression of Vim may be used as a potential marker for malignant transformation in OSCC. [21]
Figure 4: Mass spectrometry/mass spectrometry (MS/MS) spectra from representative differentially regulated known and novel proteins identified in this study. The inset shows the reporter ions used for quantitation. MS/MS spectra of peptide from representative differentially expressed proteins identified in this study. (a) Vimentin, (b) fascin, (c) Periostin, (d) transglutaminase 3, (e) cornulin and (f) tenascin N

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Figure 5: Validation of known proteins by Immunohistochemistry using specific antibodies. Representative photomicrographs showing immunohistochemical labeling of: (a) Vimentin, (b) Fascin, (c) Periostin, and (d) transglutaminase 3 at different stages of rat lingual carcinogenesis (magnification ×200)

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Fascin is an actin-bundling protein that is found in membrane ruffles, microspikes, and stress fibers. [22] It is found to be associated with tumor cell invasion and metastasis in various types of cancers including OSCC. [23],[24] Our proteomics study suggests it's sequential upregulation during the process of carcinogenesis and upregulation to 3-fold in tumor as compared with normal tissues [Figure 4]b. IHC studies on rat tongue at different stages revealed that Fscn1 expression was not detectable in the vehicle treated group while weak cytoplasmic staining was observed in the basal layer of hyperplastic tissues. Furthermore, strong cytoplasmic, and suprabasal staining was seen in papilloma and carcinoma tissues respectively [Figure 5]b. Similar observations were made by Shimamura et al. in human oral dysplasia, who proposed that Fscn1 overexpression in dysplastic tissue drives tumor formation. [25]


Periostin is a matricellular protein and also reported as osteoblast-specific factor 2. [26] It is also referred as a stroma-associated protein and plays an important role in tumor development and is upregulated in a wide variety of cancers including head and neck. [27],[28] Proteomics data demonstrated its sequential upregulation during rat tongue carcinogenesis and a 3.7-fold upregulation in tumors as compared with normal [Figure 4]c. Immunohistochemical analysis of Postn showed that Postn was not detectable in epithelial layers of normal and hyperplastic tissues while papillomatous lesions and tumor tissues showed Postn expression only in the stromal region [Figure 5]c. A study by Kyutoku et al. demonstrated that it plays a pivotal role in tumor progression and metastasis of murine breast cancer and proposed that this molecule can be potential drug target against breast cancer. [29] Together, these findings along with our result of progressive expression of Postn in 4NQO-induced rat tongue tumors demonstrate its potential candidature for early diagnostic and prognostic marker for tongue tumors.

Known downregulated proteins identified in rat lingual carcinogenesis

Transglutaminase 3

Transglutaminases are a family of calcium-dependent acyl-transfer enzymes that are widely expressed in mammalian cells. [30] Tgm3 enzyme is required for the cross-linking of the structural protein Trichohyalin and the keratin intermediate filaments to form a rigid structure within the inner root sheath cells. [31] Marked suppression of Tgm3 is associated with various cancers like head and neck squamous cell carcinoma. [32] We obtained sequential downregulation of Tgm3 in our proteomics study and noted a ~6-fold downregulation in tumor as compared with normal [Figure 4]d. Validation by IHC indicates its strong cytoplasmic and suprabasal expression in normal tongue tissues. While, its cytoplasmic expression was sequentially downregulated during the process of tumorogenesis [Figure 5]d. Ohkura et al., 2005 demonstrated that Tgm3 is downregulated in OSCC and proposed that the lack of TGM-3 expression may also facilitate survival in OSCC cells. [33]


Cornulin is a recently identified protein also known as chromosome one open reading frame 10 (C1orf10). [34] It has conserved S100 EF-hand calcium binding motif and is highly expressed in esophagus. It also has a glutamine rich repeats at its C-terminal region which are frequently crossed linked by TGM proteins in differentiated layers of epithelia, and forms barriers protecting regenerative basal layer from exposure to environmental agents. [35] It has been observed that forced expression of Crnn leads G1/S cell cycle arrest and a downregulation of cyclin D1 in OSCC. [36] It is considered as late differentiation marker of skin. [37] Due to unavailability of specific antibody for Crnn against rat, we validated our results of proteomics analysis using real-time quantitative PCR. Our proteomics and real-time data demonstrated marked and sequential downregulation of this protein [Figure 4]e and its messenger RNA (mRNA) in hyperplasia and papillomas and it was undetectable in tumors [Supplementary Figure 1] [Additional file 1]. Proteomics data revealed it's 14-fold downregulation in tumor as compared to normal. Real-time data revealed that Crnn downregulation is an early event in carcinogenesis. This indicates that Crnn might act as strong tumor suppressor. [35] Our data correlates with findings of Schaaij-Visser et al. in that Crnn expression was downregulated in mucosal epithelium at high risk of malignant transformation, when compared with normal oral mucosa. [38,39]

Overall, we were able to validate differential expression of many known proteins during different stages of rat lingual carcinogenesis, whose differential expression has been shown in human system. Our data underlines the importance of this model system for development of biomarkers. As stated earlier, we have also detected some of novel proteins whose differential expression in lingual carcinogenesis has not been documented in patients. A partial list of novel upregulated and downregulated proteins is given in [Table 4] and [Table 5], respectively. Further, we have validated one novel upregulated protein in both rat and human systems. We have taken histologically normal (tissue 2 cm away from the tumor, n = 14), leukoplakia (n = 10) and tongue tumors (n = 32) for validation of novel over expressed protein.
Table 4: Partial list of novel upregulated proteins in rat lingual carcinogenesis

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Table 5: Partial list of novel downregulated proteins in rat lingual carcinogenesis

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Validation of tenascin N, a novel protein in rat and human tongue tumerogenesis

Tenascin N

Tenascin is a high molecular weight extracellular matrix glycoprotein. Its expression was detected during embryogenesis, wound healing and neoplastic processes. [52] Tnn is novel member of tenascin family and is expressed in brain, kidney and spleen and more so in the adult than in the developing mouse. [53] Our rat proteomics data demonstrated that Tnn was sequentially upregulated across the stages of rat lingual carcinogenesis and found to be upregulated by 2.5-fold in tumors as compared with normal tissues [Figure 4]f. To validate our proteomics results, we performed IHC on rat tissues [Figure 6]a. Tnn expression was not seen in the vehicle treated rat tissues (control groups) while hyperplasia tissues showed weak cytoplasmic staining in keratinized layer of epithelium. Tnn expression was also confined to keratinized layer in papillomas and carcinomas. Carcinomas showed higher expression of Tnn as compared to papillomas and hyperplastic tissues. We further validated Tnn expression in human tongue tissues [Figure 6]b. Immunohistochemical staining on human tissues revealed strong basal layer and cytoplasmic expression of Tnn in normal tissues (12/14) while upregulation was noticed in leukoplakia (9/10) in all layers. In human tongue tumors (27/32) Tnn was expressed in keratinized tumor cells, while its basal cell expression was weak [Figure 6]b. Strong cytoplasmic staining was detected in tumor cells. Intriguingly, Tnn was predominantly seen in keratinizing cells of the tumor tissues and basal layer shows very weak expression. The significance of this finding is unclear.
Figure 6: Validation of tenascin N (Tnn) by immunohistochemistry using specific antibody. (a) Representative photomicrographs showing immunohistochemical detection labeling of Tnn during rat lingual carcinogenesis (×200). (b) Representative photomicrographs showing immunohistochemical detection of Tnn in human normal, leukoplakia and tumor of tongue tissues. Arrows indicate the weak expression of Tnn in basal layer (black) of tumor while increased expression of tenascin N in differentiated layers (blue) (×200)

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  Conclusions and Future Perspective Top

This is the most extensive quantitative proteomic study in rat model of 4NQO-induced oral carcinogenesis carried out until date. We successfully validated several known proteins like Vim, Fscn1, Tgm3, Postn and Crnn, and a novel molecule, Tnn, based on our proteomics findings. Using this model, we are able to show sequential alterations in expression pattern during rat tongue carcinogenesis. Furthermore, we are also able to extrapolate our rat model data to human system indicating the fact that this model has potential to be used for biomarker discovery in human oral cancer. We plan to take up validation of novel proteins on a large scale on human tissues. Therefore, we are in the process of collecting SCC of tongue samples at different stages that is, from T1 to T4. We are also in the process of collecting more leukoplakia of tongue samples. Our ultimate aim is to carry out sequential analysis, so as to establish these proteins as predictive markers for human oral cancer.

  References Top

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  Authors Top

Bihari Lal Soni: TMC-Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Kharghar, Navi-Mumbai, Maharashtra, India.

Dr. Arivusudar Marimuthu: Institute of Bioinformatics, Discoverer building, International Technology Park Limited (ITPL), Whitefield, Bengaluru, Karnataka, India.

Harsh Pawar: Institute of Bioinformatics, Discoverer building, International Technology Park Limited (ITPL), Whitefield, Bangalore, Karnataka, India. Dr. Anita Borges: Asian Institute of Oncology, S L Raheja Hospital, Mahim, Mumbai, Maharastra, India.

Ranganathan Kannan: Department of Oral and Maxillofacial Pathology, Ragas Dental College and Hospital, Chennai, Tamil Nadu, India.

Dr. Arvind D. Ingle: TMC-Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Kharghar, Navi-Mumbai, Maharashtra, India.

Dr. Hindahally Chandregowda Harsha: Institute of Bioinformatics, Discoverer building, International Technology Park Limited (ITPL), Whitefield, Bangalore, Karnataka, India.

Dr. Akhilesh Pandey: McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA, Department of Biological Chemistry, Department of Oncology, and Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Sharada S. Sawant: TMC-Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Kharghar Navi-Mumbai, Maharashtra, India.

Dr. Milind Murlidhar Vaidya: TMC-Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Kharghar, Navi-Mumbai, Maharashtra, India.


  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


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