Global Expression-Based Classification of Lymph Node Metastasis and Extracapsular Spread of Oral Tongue Squamous Cell Carcinoma (original) (raw)
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PLOS ONE, 2016
Oral Tongue Squamous cell carcinoma (OTSCC), the most frequently affected oral cancer sub-site, is associated with a poor therapeutic outcome and survival despite aggressive multi-modality management. Till date, there are no established biomarkers to indicate prognosis and outcome in patients presenting with tongue cancer. There is an urgent need for reliable molecular prognostic factors to enable identification of patients with high risk of recurrence and treatment failure in OTSCC management. In the current study, we present the meta-analysis of OTSCC microarray based gene expression profiles, deriving a comprehensive molecular portrait of tongue cancer biology, showing the relevant genes and pathways which can be pursued further to derive novel, tailored therapeutics as well as for prognostication. We have studied 5 gene expression profiling data sets available on exclusively oral tongue subsite comprising of sample size; n = 190, consisting of 111 tumors and 79 normals. The meta-analysis results showed 2405 genes differentially regulated comparing OTSCC tumor and normal. The top up regulated genes were found to be involved in Extracellular matrix degradation (ECM) and Epithelial to mesenchymal transition (EMT) pathways. The top down regulated genes were found to be involved in detoxication pathways. We validated the results in clinical samples (n = 206), comprising of histologically normals (n = 10), prospective (n = 29) and retrospective (n = 167) OTSCC by evaluating MMP9 and E-cadherin gene expression by qPCR and immunohistochemistry. Consistent with meta-analysis results, MMP9 mRNA expression was significantly up regulated in OTSCC primary tumors compared to normals. MMP9 protein over expression was found to be a significant predictor of poor prognosis, disease recurrence and poor Disease Free Survival (DFS) in OTSCC patients. Analysis by univariate and multivariate Cox proportional hazard model showed patients with loss of E-cadherin expression in OTSCC tumors having a PLOS ONE |
Four-gene expression model predictive of lymph node metastases in oral squamous cell carcinoma
Acta Oncologica, 2012
Background. Previous knowledge of cervical lymph node compromise may be crucial to choose the best treatment strategy in oral squamous cell carcinoma (OSCC). Here we propose a set four genes, whose mRNA expression in the primary tumor predicts nodal status in OSCC, excluding tongue. Material and methods. We identifi ed differentially expressed genes in OSCC with and without compromised lymph nodes using Differential Display RT-PCR. Known genes were chosen to be validated by means of Northern blotting or real time RT-PCR (qRT-PCR). Thereafter we constructed a Nodal Index (NI) using discriminant analysis in a learning set of 35 patients, which was further validated in a second independent group of 20 patients. Results. Of the 63 differentially expressed known genes identifi ed comparing three lymph node positive (pN ϩ) and three negative (pN0) primary tumors, 23 were analyzed by Northern analysis or RT-PCR in 49 primary tumors. Six genes confi rmed as differentially expressed were used to construct a NI, as the best set predictive of lymph nodal status, with the fi nal result including four genes. The NI was able to correctly classify 32 of 35 patients comprising the learning group (88.6%; p ϭ 0.009). Casein kinase 1alpha1 and scavenger receptor class B, member 2 were found to be up regulated in pN ϩ group in contrast to small proline-rich protein 2B and Ras-GTPase activating protein SH3 domainbinding protein 2 which were upregulated in the pN0 group. We validated further our NI in an independent set of 20 primary tumors, 11 of them pN0 and nine pN ϩ with an accuracy of 80.0% (p ϭ 0.012). Conclusions. The NI was an independent predictor of compromised lymph nodes, taking into the consideration tumor size and histological grade. The genes identifi ed here that integrate our " Nodal Index " model are predictive of lymph node metastasis in OSCC.
Journal of Clinical Oncology, 2012
Current assessment of lymph node metastasis in patients with head and neck squamous cell carcinoma is not accurate enough to prevent overtreatment. The aim of this study was validation of a gene expression signature for distinguishing metastasizing (Nϩ) from nonmetastasizing (N0) squamous cell carcinoma of the oral cavity (OSCC) and oropharynx (OPSCC) in a large multicenter cohort, using a diagnostic DNA microarray in a Clinical Laboratory Improvement Amendments/ International Organization for Standardization-approved laboratory.
Cancer Science, 2007
An accurate assessment of the cervical lymph node metastasis status in oral cavity cancer not only helps predict the prognosis of patients, but also helps surgeons to perform the appropriate treatment. We investigated the utilization of microarray technology focusing on the differences in gene expression profiles between primary tumors of oral squamous cell carcinoma that had metastasized to cervical lymph nodes and those that had not metastasized in the hope of finding new biomarkers to serve for diagnosis and treatment of oral cavity cancer. To design this experiment, we prepared two groups: the learning case group with 30 patients and the test case group with 13 patients. All tissue samples were performed using laser captured microdissection to yield cancer cells, and RNA was isolated from purified cancer cells. To identify a predictive gene expression signature, the different gene expressions between the two groups with and without metastasis in the learning case (n = 30) were analyzed, and the 85 genes expressed differentially were selected. Subsequently, to construct a more accurate prediction model, we further selected the genes with a high power for prediction from the 85 genes using the AdaBoost algorithm. The eight candidate genes, DCTD, IL-15, THBD, GSDML, SH3GL3, PTHLH, RP5-1022P6 and C9orf46, were selected to achieve the minimum error rate. Quantitative reverse transcription-polymerase chain reaction was carried out to validate the selected genes. From these statistical methods, the prediction model was constructed including the eight genes and this model was evaluated by using the test case group. The results in 12 of 13 cases (∼ ∼ ∼ ∼92.3%) were predicted correctly. (Cancer Sci 2007; 98: 740-746)
Oncotarget, 2017
Objectives: To establish a prognostic signature for locally advanced tongue squamous cell carcinoma (TSCC) patients treated with surgery. Results: In the discovery study, unsupervised hierarchical clustering analysis identified two clusters which differentiated the Kaplan-Meier curves of RFS [median RFS, 111 days vs. not reached; log-rank test, P = 0.023]. The 30 genes identified were combined into a dichotomous PI. In the validation cohort, classification according to the PI was associated with RFS [median RFS, 754 days vs. not reached; log-rank test, P = 0.026 in GSE31056] and DSS [median DSS, 540 days vs. not reached; log-rank test, P = 0.046 in GSE42743 and 443 days vs. not reached; P < 0.001 in GSE41613]. Among genes, positive immunohistochemical staining of cytokeratin 4 was associated with favorable prognostic values for RFS (hazard ratio (HR), 0.591, P = 0.045) and DSS (HR, 0.333, P = 0.004). Materials and methods: We conducted gene expression profiling of 26 clinicopathologically homogeneous advanced TSCC tissue samples using cDNA microarray as a discovery study. Candidate genes were screened using clustering analysis and univariate Cox regression analysis for relapse-free survival (RFS). These were combined into a prognostic index (PI), which was validated using three public microarray datasets of tongue and oral cancer (123 patients). Some genes identified in discovery were immunohistochemically examined for protein expression in another 127 TSCC patients. Conclusion: We identified robust molecular markers that showed significant associations with prognosis in TSCC patients. Gene expression profiling data were successfully converted to protein expression profiling data.
Radiotherapy and Oncology, 2011
Current assessment of lymph node metastasis in patients with head and neck squamous cell carcinoma is not accurate enough to prevent overtreatment. The aim of this study was validation of a gene expression signature for distinguishing metastasizing (Nϩ) from nonmetastasizing (N0) squamous cell carcinoma of the oral cavity (OSCC) and oropharynx (OPSCC) in a large multicenter cohort, using a diagnostic DNA microarray in a Clinical Laboratory Improvement Amendments/ International Organization for Standardization-approved laboratory.
Cancer Genomics - Proteomics, 2019
Background/Aim: In metastatic head and neck squamous cell carcinoma (HNSCC) the metastatic tumor does not always keep the same gene expression profile as the parental tumor, which may influence the course of the disease. The aim of this study was to compare the expression of genes implicated in HNSCC carcinogenesis between the primary tumor and the corresponding lymph node metastasis. Materials and Methods: Eighteen HNSCC, their corresponding node metastases and non-neoplastic tissues were studied by RT-qPCR for the expression of EGFR, VEGF, claudin7, maspin, survivin and SCCA. The levels of expression were correlated with histological characteristics and patients' prognosis. Results: All genes except for survivin displayed different expression in node metastasis compared to the primary tumor. The expression of EGFR, survivin, maspin, and claudin7 in node metastasis and SSCA in the primary tumor affected the prognosis. SCCA expression is associated with the expression of claudin7 and maspin. P16-positive tumors expressed low levels of VEGF and SCCA, while keratinizing tumors over-expressed VEGF. Conclusion: Differential gene expression levels in node metastases compared to the primary tumor is linked to the prognosis of HNSCC patients. The histological/immunohisto-chemical characteristics of the tumor are associated with these genes expression changes.
BMC Cancer, 2009
Background The present study is aimed at identifying potential candidate genes as prognostic markers in human oral tongue squamous cell carcinoma (SCC) by large scale gene expression profiling. Methods The gene expression profile of patients (n=37) with oral tongue SCC were analyzed using Affymetrix HG_U95Av2 high-density oligonucleotide arrays. Patients (n=20) from which there were available tumor and matched normal mucosa were grouped into stage (early vs. late) and nodal disease (node positive vs. node negative) subgroups and genes differentially expressed in tumor vs. normal and between the subgroups were identified. Three genes, GLUT3, HSAL2, and PACE4, were selected for their potential biological significance in a larger cohort of 49 patients via quantitative real-time RT-PCR. Results Hierarchical clustering analyses failed to show significant segregation of patients. In patients (n=20) with available tumor and matched normal mucosa, 77 genes were found to be differentially expressed (PMMP-1 encoding interstitial collagenase showed the highest level of increase (average: 34.18 folds). Using the criterion of two-fold or greater as overexpression, 30.6%, 24.5% and 26.5% of patients showed high levels of GLUT3, HSAL2 and PACE4, respectively. Univariate analyses demonstrated that GLUT3 over-expression correlated with depth of invasion (PHSAL2 was positively associated with depth of invasion (P=0.015) and advanced T stage (P=0.047). In survival studies, only GLUT3 showed a prognostic value with disease-free (P=0.049), relapse-free (P=0.002) and overall survival (P=0.003). PACE4 mRNA expression failed to show correlation with any of the relevant parameters. Conclusion The characterization of genes identified to be significant predictors of prognosis by oligonucleotide microarray and further validation by real-time RT-PCR offers a powerful strategy for identification of novel targets for prognostication and treatment of oral tongue carcinoma.