- Research article
- Open Access
Transcriptomic dissection of tongue squamous cell carcinoma
- Hui Ye†1,
- Tianwei Yu†2,
- Stephane Temam3, 4,
- Barry L Ziober5,
- Jianguang Wang6,
- Joel L Schwartz7, 8,
- Li Mao3,
- David T Wong9 and
- Xiaofeng Zhou1, 8, 10Email author
© Ye et al; licensee BioMed Central Ltd. 2008
Received: 15 August 2007
Accepted: 06 February 2008
Published: 06 February 2008
The head and neck/oral squamous cell carcinoma (HNOSCC) is a diverse group of cancers, which develop from many different anatomic sites and are associated with different risk factors and genetic characteristics. The oral tongue squamous cell carcinoma (OTSCC) is one of the most common types of HNOSCC. It is significantly more aggressive than other forms of HNOSCC, in terms of local invasion and spread. In this study, we aim to identify specific transcriptomic signatures that associated with OTSCC.
Genome-wide transcriptomic profiles were obtained for 53 primary OTSCCs and 22 matching normal tissues. Genes that exhibit statistically significant differences in expression between OTSCCs and normal were identified. These include up-regulated genes (MMP1, MMP10, MMP3, MMP12, PTHLH, INHBA, LAMC2, IL8, KRT17, COL1A2, IFI6, ISG15, PLAU, GREM1, MMP9, IFI44, CXCL1), and down-regulated genes (KRT4, MAL, CRNN, SCEL, CRISP3, SPINK5, CLCA4, ADH1B, P11, TGM3, RHCG, PPP1R3C, CEACAM7, HPGD, CFD, ABCA8, CLU, CYP3A5). The expressional difference of IL8 and MMP9 were further validated by real-time quantitative RT-PCR and immunohistochemistry. The Gene Ontology analysis suggested a number of altered biological processes in OTSCCs, including enhancements in phosphate transport, collagen catabolism, I-kappaB kinase/NF-kappaB signaling cascade, extracellular matrix organization and biogenesis, chemotaxis, as well as suppressions of superoxide release, hydrogen peroxide metabolism, cellular response to hydrogen peroxide, keratinization, and keratinocyte differentiation in OTSCCs.
In summary, our study provided a transcriptomic signature for OTSCC that may lead to a diagnosis or screen tool and provide the foundation for further functional validation of these specific candidate genes for OTSCC.
Head and neck/oral squamous cell carcinoma (HNOSCC) is a complex disease arising in various organs, including oral cavity, tongue, pharynx, and larynx. Tumors from these different sites have distinct clinical presentations and clinical outcomes, and are associated with different risk factors  and genetic characteristics . In this study, we focused on the oral tongue squamous cell carcinomas (OTSCC), one of the most common sites for HNOSCCs. The incidence of OTSCC is actually increasing in young and middle age groups [3–5]. OTSCC is significantly more aggressive than other forms of HNOSCCs, with a propensity for rapid local invasion and spread .
Cancer cells harbor genetic alterations which are translated into unique expression patterns. These patterns may segregate cancer cells from normal tissue of the same origin and serve as a molecular biomarker. Moreover, expression pattern changes may occur far earlier than clinical disease detection. The identification of such patterns has significant translational values for early detection and diagnosis, as well as for identifying novel therapeutic targets. While several recent studies have attempted to identify expression patterns for HNOSCCs [7–10], to our knowledge, no study has been devoted to identify the unique expression pattern for OTSCC. In this study, we aim to identify the specific transcriptomic/expression patterns that associated with OTSCC.
Results and discussion
Signature gene sets for OTSCC
Upregulated genes in OTSCC
matrix metalloproteinase 1
matrix metalloproteinase 10
matrix metalloproteinase 3
matrix metallopeptidase 12
parathyroid hormone-like hormone
inhibin, beta A
laminin, gamma 2
collagen, type I, alpha 2
interferon, alpha-inducible protein 6
ISG15 ubiquitin-like modifier
plasminogen activator, urokinase
matrix metallopeptidase 9
interferon-induced protein 44
chemokine (C-X-C motif) ligand 1
Downregulated genes in OTSCC
mal, T-cell differentiation protein
cysteine-rich secretory protein 3
serine protease inhibitor, Kazal type 5
chloride channel, calcium activated, family member 4
alcohol dehydrogenase IB (class I), beta polypeptide
26 serine protease
Rhesus blood group, C glycoprotein
protein phosphatase 1, regulatory (inhibitor) subunit 3C
carcinoembryonic antigen-related cell adhesion molecule 7
hydroxyprostaglandin dehydrogenase 15-(NAD)
D component of complement (adipsin)
ATP-binding cassette, sub-family A (ABC1), member 8
cytochrome P450, family 3, subfamily A, polypeptide 5
In this study, we identified and validated several interesting potential biomarkers for OTSCC diagnosis. One interesting observation is that 5 members of the Matrix Metalloproteinase (MMP) family (MMP1 MMP3, MMP9, MMP10, and MMP12) are among the genes that most significantly upregulated, which may contribute to the aggressive nature of the OTSCC. MMPs are a large family of proteinases which remodel extracellular matrix (ECM) components and play a significant role in tumor development, survival, invasion and metastasis [11–13]. Several members of the MMP family have been considered to be important biomarkers for diagnosis and prognosis as well as potential therapeutic targets for many types of cancers, including HNOSCC . Our recent study suggested that up regulation of the MMP9 gene is associated with advanced OTSCC and has predictive value for the identification of lymph node metastasis . Here, our data further suggested that MMP9 is one of the biomarkers for the detection of OTSCC. We also observed 2 chemokines (IL8 and CXCL1) to be among the most significantly upregulated genes in OTSCC. The increase in the protein and mRNA of IL8 gene has been suggested as a biomarker for the early detection of oral cancer [16, 17]. Our data provided independent validation for this biomarker at the disease tissue level, and suggested that the increase of IL8 molecules (mRNA and protein) is due at least in part to the increased expression of gene in the disease tissues. CXCL1, also known as growth-regulated oncogene 1 (Gro-1), is vital for the survival, progression and invasion of several cancer types [18, 19], including oral cancer . Our results here further confirmed the importance of CXCL1 in the tumorgenesis of tongue cancer. Other interesting observations include the up-regulation of KRT17 (associated with invasion and proliferation) and down-regulation of KRT4 (which is associated with squamous cell differentiation), suggesting the potentially distinct roles of KRT genes in tongue SCC development and progression. In addition to those identified biomarkers, our results will also serve as a valuable reference data set for future development and validation of biomarkers for detection, diagnosis and prognosis of tongue cancer.
Our analysis demonstrated that OTSCC can be identified based on the gene expression signature. This finding should provide a foundation for the creation of a specific screen tool for OTSCC. One of the major factors accounting for the poor outcome of OTSCC patients is that a great proportion of oral cancers are diagnosed at advanced stages. Patients diagnosed at an early stage of the disease typically have a better chance for cure and functional outcome. Early detection of tongue cancer lesion will greatly improve patient survival and the quality of life. Current clinical diagnosis and histopathologic examinations are usually based on biopsied material, which requires invasive procedures and surgical techniques. The emerging technology of saliva-based diagnosis may provide an alternative strategy for early diagnosis and screening of the subjects at risk . The markers identified here may be suitable for the saliva-based early diagnosis and screening strategy [17, 21]. Additional validation studies will be needed to fully explore this possibility.
Selected biological processes that altered in OTSCCs *
% Change **
Positive regulation of chemotaxis
Extracellular matrix organization and biogenesis
Positive regulation of I-kappaB kinase/NF-kappaB cascade
Hydrogen peroxide metabolism
Response to hydrogen peroxide
Among the identified alteration in biological activities in OTSCC, the most significantly enhanced are related to the extracellular matrix remodeling (GO:0030574, GO:0030198), I-kappaB kinase/NF-kappaB cascade (GO:0043123) and chemotaxis (GO:0050921), which are known to be related to tumorgenesis and progression of the cancer. One interesting observation is the enhancement in phosphate transport (GO:0006817) in OTSCC. This may be related directly to the enhanced metabolic activity and energy consumption rate in OTSCCs. It has also been suggested that phosphate can act as a signaling molecule on the extracellular signal-regulated kinase (ERK1/2)  and adenylate cyclase/cAMP signaling pathways , and ultimately affect cell growth. However, the precise role of enhanced phosphate transport in tumorgenesis is largely unclear. The significantly suppressed biological activities, such as superoxide release (GO:0042554), hydrogen peroxide metabolism (GO:0042743), and response to hydrogen peroxide (GO:0042542) are all appeared to be related to the cellular redox state. The effects of redox state in malignancies are somewhat contradictory. In theory, reducing the oxidative stress may prevent DNA degeneration and therefore prevent the development of cancer. However, doing so may also offer increased growth potential to tumor cells and protect them from excess of reactive oxygen species (ROS), which would otherwise lead to apoptosis or necrosis. At the center of this apparent controversy is superoxide dismutase 2 (SOD2), which has been considered as one of the most important antioxidant enzymes. The role of SODs in carcinogenesis has been widely studied but is still rather ambiguous. While the majority of in vitro studies have reported a protective role of SOD2 against tumor progression in cancer cell lines [26–30], including oral cancer cell lines , the in vivo studies indicate more complicated roles. Increased SOD2 levels have been observed from esophageal, gastric, brain astrocytic and colorectal carcinomas, and often associated with metastasis and poor prognosis [32–40]. The status of SOD2 in breast cancer is not clear, with some studies showing an increase , while others showing a decrease in SOD2 level . Reduction in SOD2 level has been observed in prostatic carcinomas [43, 44]. Our microarray results indicated a significant increase in expression of SOD2 gene (probset: 215223_s_at; fold change = 2.37; p value = 0.00014; and probeset: 216841_s_at; fold change = 2.24; p value = 0.000197) in OTSCC. These findings are in agreement with the recent observation in oral cancer . Additional studies will be needed to fully understand the role(s) of redox state and SOD2 in OTSCC.
Expression values of genes that constitute the collagen catabolism (GO:0030574) and positive regulation of chemotaxis (GO:0050921) processes in OTSCC.
The HNOSCCs are a diverse group of cancers, that develop from many different anatomic sites and are associated with different risk factors  and genetic characteristics . This is the first high-resolution genomic profiling study to our knowledge that has focused on identifying unique expression patterns for tongue cancer (OTSCC). OTSCC is one of the most common types of HNOSCC, and is significantly more aggressive than other forms of HNOSCCs, with a propensity for rapid local invasion and spread . Recent epidemiological studies suggested that the incidence of OTSCC is actually increasing in young and middle age groups [3–5]. In this study, we utilized a relatively large sample size (53 OTSCCs and 22 normal matching samples), which enabled us to capture a precise picture of the genome-wide expression pattern for this disease. It is possible that the genomic portrait of HNOSCC originating from different anatomic sites may be different. More studies will be needed to address this important question.
In summary, we identified the unique expression pattern for OTSCC. Several interesting candidate genes associated with OTSCC were identified. The Gene Ontology analysis indicated that several biological processes and cellular functions are consistently altered in OTSCC. Our results demonstrate the feasibility of utilizing biomarkers discovered by global expression profiling analyses for the detection and diagnosis of OTSCC. In addition, we also provided a valuable reference dataset for future identification and validation of biomarkers for detection, diagnosis and prognosis of OTSCC.
Clinical Characterization of the OTSCC Patients*
OTSCC (n = 53)
Normal (n = 22)
Pathological T Stage
Stage 4 (%)
Stage 3 (%)
Stage 2 (%)
Stage 1 (%)
Pathological N Stage
Stage 2 (%)
Stage 1 (%)
Stage 0 (%)
Tumor procurement, RNA extraction and microarray hybridization
The OTSCC tissues and their matching normal samples were obtained for this study. These tissues were snap frozen. Cancer tissues containing more than 80% tumor cells based on haematoxylin and eosin (H&E) staining and pathological examination were identified and selectively microdissected by a trained pathologist. The total RNA was isolated using RNeasy Mini kit (Qiagen), and quantified by the RiboGreen RNA Quantitation Reagent (Molecular Probes). A total of 150–200 ng of purified total RNA was amplified by a modified T7 RNA amplification protocol as described previously [15, 17]. The Enzo BioArray High Yield RNA Transcript Labeling System (Enzo) was used for labeling the sample prior to hybridization. The biotinylated cRNA (IVT product) was purified using the RNeasy kit (Qiagen). The quantity and purity of the biotinylated cRNA was determined by spectrophotometry and an aliquot of the sample was checked by gel electrophoresis. The samples were hybridized to the Affymetrix Human Genome U133 Plus 2.0 GeneChip arrays according to the Affymetrix protocols. The arrays were scanned with a GeneChip Scanner 3000. The scanned array images were processed with GeneChip Operating software (GCOS), and the CEL files were extracted for further analysis.
Array data analysis and gene ontology analysis
In the model, the random effect α ij is the laboratory effect, and β i is the first-order cancer effect, which is our major focus in the identification of cancer-associated genes. After obtaining the estimates and the p-values of the β i 's of each probeset, we corrected the p-values for false discovery rate (FDR) . We selected genes at the FDR level of 0.01, and with cancer effect size > 1 (> 2 fold change between cancer and normal samples). Functional analysis of the differentially expressed genes was carried out using the GOstats package in Bioconductor  based on the Gene Ontology Consortium database .
The mRNA levels of interleukin-8 (IL8) and matrix metalloproteinases 9 (MMP9) in OTSCCs and normal tissues were further validated using qRT-PCR as previously described [15, 17]. The RNA was converted to first strand cDNA using MuLV reverse transcriptase (Applied Biosystems) and the quantitative PCR was performed using iQ SYBR Green Supermix (Bio-Rad) in a BIO-RAD iCycler iQ real-time PCR detection system. The primer sets specific for IL8 (Forward: 5'-GAGGGTTGTGGAGAAGTTTTTG-3', Reverse: 5'-CTGGCATCTTCACTGATTCTTG-3') and for MMP9 (Forward: 5'-GCACGACGTCTTCCAGTACC-3', Reverse: 5'-TCAACTCACTCCGGGAACTC-3') were used. All reactions were performed in triplicate. The melting curve analyses were performed to ensure the specificity of the qRT-PCR reactions. The data analysis was performed using the 2-deltadelta Ct method described previously , where beta-actin was used as reference gene. The qRT-PCR based gene expression values between two groups were compared by the nonparametric Wilcoxon test.
The expression of IL8 and MMP9 in OTSCCs were further examined using immunohistochemistry tests as previously described . In brief, the OTSCC tissues were processed, embedded, and sectioned at 5 μm. Tissue sections were stained using monoclonal antibody to IL8 (MAB208) (R & D Systems) and MMP9 (ab51203) (Abcam, Inc) and detected using peroxidase-antiperoxidase and diaminebenzadine (DAB) with a Discovery XT automated instrument (Ventana Medical Systems, Inc).
This work was supported in part by NIH PHS grants K22 DE014847, RO3 DE016569, and RO3 CA114688 (to X. Zhou), R01 DE015970 (to D. Wong), P01 CA106451 Project 3 (to L. Mao), and a Foundation de France grant (to S. Temam). We thank Drs. O'Donnell and Muschel at Children's Hospital of Philadelphia and Dr Dermody at University of Medicine and Dentistry of New Jersey for sharing their microarray datasets with us. We thank Mr. Hui Zhou and Ms. Nisa Pungpravat for their excellent technical assistance, and Ms. Katherine Long for editorial assistance.
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