scholarly journals Gene expression changes associated with malignant transformation of oral potentially malignant disorders

2020 ◽  
Author(s):  
Hans P. Sathasivam ◽  
John Casement ◽  
Timothy Bates ◽  
Philip Sloan ◽  
Peter Thomson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Malignant Transformation ◽  
Oral Potentially Malignant Disorders ◽  
Potentially Malignant Disorders ◽  
Potentially Malignant

scholarly journals DNA Methylation Patterns in Saliva of Tobacco users with High-Risk Oral Potentially Malignant Disorders

2021 ◽  
pp. 129-137
Author(s):  
Mimansha Patel ◽  
Madhuri Nitin Gawande ◽  
Minal Shashikant Chaudhary ◽  
Alka Harish Hande
Keyword(s):  
Dna Methylation ◽  
High Risk ◽  
Malignant Transformation ◽  
Promoter Methylation ◽  
Genomic Dna ◽  
Premalignant Lesions ◽  
Oral Potentially Malignant Disorders ◽  
Potentially Malignant Disorders ◽  
Potentially Malignant ◽  
Methylation Patterns

Background: “Oral Potentially Malignant Disorder (OPMD)” is a well-known symptom that, if untreated, can be carcinogenic. It includes leukoplakia, erythroplakia or erythroleukoplakia. One of the typical premalignant lesions of the oral cavity is “oral leukoplakias (OLs),” which frequently precedes “OSCCs.”OLs with dysplastic characteristics are considered to be at a higher risk of “malignant transformation.” So, early diagnosis of "oral squamous cell carcinomas (OSCCs)" is desperately required to enhance patient prognosis and quality of life (QOL).As a result, we examined the distinctive promoter methylation presence in high-risk OLs. Objectives: To detect, compare & correlate “DNA methylation” patterns in normal individuals, tobacco users without disease and tobacco users with the disease. Methodology: With the participants' full consent, 48 saliva samples were obtained and prepared. DNA isolation, restriction digestion of genomic DNA, extraction of restriction enzyme digested genomic DNA, Polymerase Chain Reaction (PCR), and Agarose Gel Electrophoresis (AGE) were all carried out. Expected results: This study will help us to assess the use of Saliva as an aid to identifying both high and low risk “Oral Potentially Malignant Disorders.” Conclusion: Peculiar promoter methylation of various genes was related to a high possibility of malignant transformation in OLs.

scholarly journals The role of interventional surgery in oral potentially malignant disorders

2014 ◽  
Vol 5 (2) ◽  
pp. 84-89 ◽  
Author(s):  
Peter Thomson
Keyword(s):  
Malignant Transformation ◽  
Scientific Literature ◽  
Squamous Carcinoma ◽  
Oral Potentially Malignant Disorders ◽  
Management Guidelines ◽  
Increased Risk ◽  
Potentially Malignant Disorders ◽  
Potentially Malignant ◽  
Rising Incidence

Oral potentially malignant disorders are mucosal diseases with a significantly increased risk of squamous carcinoma development – a lethal and deforming disease with rising incidence, especially in young people. Despite the ability to recognise pre-cancer disorders in patients, clinicians remain unable to predict individual mucosal lesion behaviour or quantify the risk of malignant transformation. No clear management guidelines exist and the available scientific literature is unable to answer the fundamental question: does early diagnosis and interventional management treat pre-cancer effectively and prevent malignant transformation?

Prognostic biomarkers for malignant transformation of oral potentially malignant disorders: a scoping review protocol

2020 ◽  
Vol 18 (6) ◽  
pp. 1349-1357 ◽  
Author(s):  
Fernanda Weber Mello ◽  
Gilberto Melo ◽  
Eliete Neves da Silva Guerra ◽  
Saman Warnakulasuriya ◽  
Cathie Garnis ◽  
...  
Keyword(s):  
Malignant Transformation ◽  
Scoping Review ◽  
Prognostic Biomarkers ◽  
Oral Potentially Malignant Disorders ◽  
Potentially Malignant Disorders ◽  
Potentially Malignant ◽  
Review Protocol

scholarly journals Deep Learning Predicts the Malignant-Transformation-Free Survival of Oral Potentially Malignant Disorders

Cancers ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 6054
Author(s):  
John Adeoye ◽  
Mohamad Koohi-Moghadam ◽  
Anthony Wing Ip Lo ◽  
Raymond King-Yin Tsang ◽  
Velda Ling Yu Chow ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Malignant Transformation ◽  
Cross Validation ◽  
Machine Intelligence ◽  
Oral Leukoplakia ◽  
Time To Event ◽  
Oral Potentially Malignant Disorders ◽  
Oral Lichenoid Lesions ◽  
Potentially Malignant Disorders ◽  
Potentially Malignant

Machine-intelligence platforms for the prediction of the probability of malignant transformation of oral potentially malignant disorders are required as adjunctive decision-making platforms in contemporary clinical practice. This study utilized time-to-event learning models to predict malignant transformation in oral leukoplakia and oral lichenoid lesions. A total of 1098 patients with oral white lesions from two institutions were included in this study. In all, 26 features available from electronic health records were used to train four learning algorithms—Cox-Time, DeepHit, DeepSurv, random survival forest (RSF)—and one standard statistical method—Cox proportional hazards model. Discriminatory performance, calibration of survival estimates, and model stability were assessed using a concordance index (c-index), integrated Brier score (IBS), and standard deviation of the averaged c-index and IBS following training cross-validation. This study found that DeepSurv (c-index: 0.95, IBS: 0.04) and RSF (c-index: 0.91, IBS: 0.03) were the two outperforming models based on discrimination and calibration following internal validation. However, DeepSurv was more stable than RSF upon cross-validation. External validation confirmed the utility of DeepSurv for discrimination (c-index—0.82 vs. 0.73) and RSF for individual survival estimates (0.18 vs. 0.03). We deployed the DeepSurv model to encourage incipient application in clinical practice. Overall, time-to-event models are successful in predicting the malignant transformation of oral leukoplakia and oral lichenoid lesions.

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