scholarly journals SOX2 Expression Is an Independent Predictor of Oral Cancer Progression

2019 ◽  
Vol 8 (10) ◽  
pp. 1744 ◽  
Author(s):  
Juan C. de Vicente ◽  
Paula Donate-Pérez del Molino ◽  
Juan P. Rodrigo ◽  
Eva Allonca ◽  
Francisco Hermida-Prado ◽  
...  
Keyword(s):  
Oral Cancer ◽  
Cancer Risk ◽  
Cancer Progression ◽  
Independent Predictor ◽  
Epithelial Dysplasia ◽  
Oral Epithelial Dysplasia ◽  
Sox2 Expression ◽  
Oral Cancer Risk ◽  
Oral Epithelial ◽  
Risk Of Cancer

Potentially malignant oral lesions, mainly leukoplakia, are common. Malignant transformation varies widely, even in the absence of histological features such as dysplasia. Hence, there is a need for novel biomarker-based systems to more accurately predict the risk of cancer progression. The pluripotency transcription factor SOX2 is frequently overexpressed in cancers, including oral squamous cell carcinoma (OSCC), thereby providing a link between malignancy and stemness. This study investigates the clinical relevance of SOX2 protein expression in early stages of oral carcinogenesis as a cancer risk biomarker, and also its impact on prognosis and disease outcome at late stages of OSCC progression. SOX2 expression was evaluated by immunohistochemistry in 55 patients with oral epithelial dysplasia, and in 125 patients with OSCC, and correlated with clinicopathological data and outcomes. Nuclear SOX2 expression was detected in four (7%) cases of oral epithelial dysplasia, using a cut-off of 10% stained nuclei, and in 16 (29%) cases when any positive nuclei was evaluated. Univariate analysis showed that SOX2 expression and histopathological grading were significantly associated with oral cancer risk; and both were found to be significant independent predictors in the multivariate analysis. Nuclear SOX2 expression was also found in 49 (39%) OSCC cases, was more frequent in early tumor stages and N0 cases, and was associated with a better survival. In conclusion, SOX2 expression emerges as an independent predictor of oral cancer risk in patients with oral leukoplakia. These findings underscore the relevant role of SOX2 in early oral tumorigenesis rather than in tumor progression.

scholarly journals Can Immunohistochemistry Serve as an Alternative to Subjective Histopathological Diagnosis of Oral Epithelial Dysplasia?

2013 ◽  
Vol 5 ◽  
pp. BIC.S12951 ◽  
Author(s):  
Ahmad A. AbdulMajeed ◽  
Camile S. Farah
Keyword(s):  
Gene Expression ◽  
Oral Cancer ◽  
Cancer Progression ◽  
Current Knowledge ◽  
Epithelial Dysplasia ◽  
Histopathological Diagnosis ◽  
Hallmarks Of Cancer ◽  
Oral Epithelial Dysplasia ◽  
Oral Epithelial ◽  
Review Current

Many attempts have been made to identify objective molecular biomarkers to diagnose and prognosticate oral epithelial dysplasia (OED) because histopathological interpretation is subjective and lacks sensitivity. The majority of these efforts describe changes in gene expression at protein level in OED as determined by immunohistochemistry (IHC). However, the literature on these putative markers of oral cancer progression is vast and varied. The main purpose of this article is to review current knowledge on biomarkers of protein expression for OED by IHC approaches. We further discuss these findings in terms of the proposed essential hallmarks of cancer cells to better understand their role in oral oncogenesis.

scholarly journals Non-Invasive Diagnostic System Based on Light for Detecting Early-Stage Oral Cancer and High-Risk Precancerous Lesions—Potential for Dentistry

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3185
Author(s):  
Seiko Tatehara ◽  
Kazuhito Satomura
Keyword(s):  
Oral Cancer ◽  
Aminolevulinic Acid ◽  
Early Stage ◽  
Diagnostic Methods ◽  
Epithelial Dysplasia ◽  
Benign Lesions ◽  
Oral Health Promotion ◽  
Oral Epithelial Dysplasia ◽  
Non Invasive ◽  
Oral Epithelial

Oral health promotion and examinations have contributed to the early detection of oral cancer and oral potentially malignant disorders, leading to the adaptation of minimally invasive therapies and subsequent improvements in the prognosis/maintenance of the quality of life after treatments. However, the accurate detection of early-stage oral cancer and oral epithelial dysplasia is particularly difficult for conventional oral examinations because these lesions sometimes resemble benign lesions or healthy oral mucosa tissues. Although oral biopsy has been considered the gold standard for accurate diagnosis, it is deemed invasive for patients. For this reason, most clinicians are looking forward to the development of non-invasive diagnostic technologies to detect and distinguish between cancerous and benign lesions. To date, several non-invasive adjunctive fluorescence-based detection systems have improved the accuracy of the detection and diagnosis of oral mucosal lesions. Autofluorescence-based systems can detect lesions as a loss of autofluorescence through irradiation with blue-violet lights. Photodynamic diagnosis using 5-aminolevulinic acid (ALA-PDD) shows the presence of very early oral cancers and oral epithelial dysplasia as a red fluorescent area. In this article, currently used fluorescence-based diagnostic methods are introduced and discussed from a clinical point of view.

scholarly journals Sociodemographic risk indicators for depressive symptoms among persons with oral cancer or oral epithelial dysplasia

2005 ◽  
Vol 63 (4) ◽  
pp. 513-520 ◽  
Author(s):  
Susan Reisine ◽  
Douglas E. Morse ◽  
Walter J. Psoter ◽  
Ellen Eisenberg ◽  
Donald Cohen ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Oral Cancer ◽  
Epithelial Dysplasia ◽  
Risk Indicators ◽  
Oral Epithelial Dysplasia ◽  
Sociodemographic Risk ◽  
Oral Epithelial

scholarly journals Oral Cancer Discrimination and Novel Oral Epithelial Dysplasia Stratification Using FTIR Imaging and Machine Learning

Diagnostics ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2133
Author(s):  
Rong Wang ◽  
Aparna Naidu ◽  
Yong Wang
Keyword(s):  
Machine Learning ◽  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Oral Cancer ◽  
Epithelial Dysplasia ◽  
Support Vector ◽  
Epithelial Tissue ◽  
Ftir Imaging ◽  
Oral Epithelial Dysplasia ◽  
Oral Epithelial

The Fourier transform infrared (FTIR) imaging technique was used in a transmission model for the evaluation of twelve oral hyperkeratosis (HK), eleven oral epithelial dysplasia (OED), and eleven oral squamous cell carcinoma (OSCC) biopsy samples in the fingerprint region of 1800–950 cm−1. A series of 100 µm × 100 µm FTIR imaging areas were defined in each sample section in reference to the hematoxylin and eosin staining image of an adjacent section of the same sample. After outlier removal, signal preprocessing, and cluster analysis, a representative spectrum was generated for only the epithelial tissue in each area. Two representative spectra were selected from each sample to reflect intra-sample heterogeneity, which resulted in a total of 68 representative spectra from 34 samples for further analysis. Exploratory analyses using Principal component analysis and hierarchical cluster analysis showed good separation between the HK and OSCC spectra and overlaps of OED spectra with either HK or OSCC spectra. Three machine learning discriminant models based on partial least squares discriminant analysis (PLSDA), support vector machines discriminant analysis (SVMDA), and extreme gradient boosting discriminant analysis (XGBDA) were trained using 46 representative spectra from 12 HK and 11 OSCC samples. The PLSDA model achieved 100% sensitivity and 100% specificity, while both SVM and XGBDA models generated 95% sensitivity and 96% specificity, respectively. The PLSDA discriminant model was further used to classify the 11 OED samples into HK-grade (6), OSCC-grade (4), or borderline case (1) based on their FTIR spectral similarity to either HK or OSCC cases, providing a potential risk stratification strategy for the precancerous OED samples. The results of the current study support the application of the FTIR-machine learning technique in early oral cancer detection.

scholarly journals Impact of SRY-Box Transcription Factor 11 Gene Polymorphisms on Oral Cancer Risk and Clinicopathologic Characteristics

2020 ◽  
Vol 21 (12) ◽  
pp. 4468
Author(s):  
Chia-Ming Yeh ◽  
Chiao-Wen Lin ◽  
Hsueh-Ju Lu ◽  
Chun-Yi Chuang ◽  
Chia-Hsuan Chou ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Oral Cancer ◽  
Cancer Risk ◽  
Cancer Progression ◽  
The Cancer Genome Atlas ◽  
Betel Quid ◽  
High Morbidity ◽  
Clinicopathologic Characteristics ◽  
Betel Quid Chewing ◽  
Oral Cancer Risk

Oral cancer is among the most common cancers worldwide and has become a major global health problem because of its relatively high morbidity and mortality rates. The sex-determining region on the Y-chromosome-related high-mobility-group box (SOX) transcription factor 11 (SOX11) plays a key role in human development and differentiation and is frequently increased in various human cancers. However, the clinical significance of SOX11 polymorphisms in oral cancer and their association with oral cancer risk are unclear. In this study, we included 1196 patients with oral cancer and 1200 controls. Real-time polymerase chain reaction was applied to analyze three SOX11 single-nucleotide polymorphisms (rs77996007, rs66465560, and rs68114586). Our results shown that SOX11 polymorphisms carriers with betel quid chewing were found to have an 8.38- to 9.23-fold risk to have oral cancer compared to SOX11 wild-type carriers without betel quid chewing. Furthermore, oral cancer patients who carried SOX11 rs77996007 “TC + CC” variants were significantly associated with large tumor size (AOR, 1.324; 95% CI, 1.047–1.674; p = 0.019). Moreover, a database analysis using the Cancer Genome Atlas suggested that SOX11 mRNA expression was high during the tumor development process. In conclusion, our results suggest that SOX11 rs77996007 is involved in oral cancer progression and clinical characteristics.

scholarly journals Similar Effect of P16 Hydroxymethylation and True Methylation on Prediction of Malignant Transformation of Oral Epithelial Dysplasia: A Prospective Study

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 211s-211s
Author(s):  
H. Liu ◽  
Z. Liu ◽  
X. Liu ◽  
S. Xu ◽  
L. Wang ◽  
...  
Keyword(s):  
Malignant Transformation ◽  
Cancer Progression ◽  
Odds Ratio ◽  
Progression Free Survival ◽  
Epithelial Dysplasia ◽  
Progression Rate ◽  
Double Blind ◽  
Oral Epithelial Dysplasia ◽  
Oral Epithelial

Background: Total P16 methylation (P16M), including P16 hydroxymethylation (P16H) and true-P16M, correlates with malignant transformation of oral epithelial dysplasia (OED). Both true-P16M and P16H are early events in carcinogenesis. Aim: The aim of this study is to prospectively determine if discrimination of true-P16M from P16H similarly is necessary for prediction of cancer development from OEDs. Methods: Patients (n = 265) with mild or moderate OED were recruited into the double-blind 2-center cohort. Total-P16M and P16H were analyzed using the 115-bp MethyLight, TET-assistant bisulfite (TAB) methylation-specific PCR (MSP), and TAB-sequencing. Total-P16M-positive and P16H-negative samples were defined as true-P16M-positive. Progression of OEDs was monitored for a minimum 24 months follow-up period. Results: P16H was detected in 23 of 73 (31.5%) total-P16M-positive OEDs. Follow-up information was obtained from 247 patients with an ultimate compliance of 93.2%. OED-derived squamous cell carcinomas were observed in 13.0% (32/247) patients during the follow-up (median, 41.0 months). The cancer progression rate for total-P16M-positive patients was significantly increased when compared with total-P16M-negative patients (23.3% vs 8.6%; adjusted odds ratio = 2.67 [95% CI: 1.19-5.99]). However, the cancer progression rate was similar between P16H- and true-P16M-positive OEDs (26.1% [6/23] vs 22.0% [11/50]; odds ratio = 0.80 [95% CI: 0.22-2.92]). The progression-free survival was also similar for these patients. Conclusion: P16H and true-P16M are similar biomarkers for determining malignant potential of OEDs. Discrimination of P16H from true-P16M, at least in OED, may be not necessary in clinical applications.

Sign in / Sign up

Export Citation Format

Share Document