Genetics/epigenetics of oral premalignancy: current status and future research

• Type: Another Publication in an International Scientific Journal
• Date: 2011

Authors

Lingen, MW (Author) Other; Pinto, A (Author) Other; Mendes, RA (Author) Other; Franchini, R (Author) Other; Czerninski, R (Author) Other; Tilakaratne, WM (Author) Other; Partridge, M (Author) Other; Peterson, DE (Author) Other; Woo, SB (Author) Other

Journal

Title: Oral Diseases

Vol. 17

Pages: 7-22

ISSN: 1354-523X

Publisher: Wiley-Blackwell

Indexing

ISI Web of Knowledge - 82 Citations

Scopus - 89 Citations

Other information

Authenticus ID: P-002-T2W

DOI: 10.1111/j.1601-0825.2011.01789.x

Abstract (EN): Squamous cell carcinoma (SCC) of the oral and oropharyngeal region is the sixth most common malignancy in the world today. Despite numerous advances in treatment, long-term survival from this disease remains poor. Early detection can decrease both morbidity and mortality associated with this neoplasm. However, screening for potentially malignant disease is typically confounded by difficulty in discriminating between reactive/inflammatory lesions vs those lesions that are premalignant in nature. Furthermore, the histologic diagnosis of dysplasia can be subjective and is thus prone to a considerable range of interpretation. Similarly, no definitive, validated criteria exist for predicting which dysplastic lesions are most likely to progress to cancer over time. Given this state of science, the presence of dysplasia can only be used to indicate that an oral lesion may have an increased risk of malignant transformation. Molecular biomarkers capable of identifying the subset of lesions likely to progress to cancer are required to eliminate this clinical diagnostic dilemma. The purpose of this review is to assess the current state of knowledge regarding genetic/epigenetic alterations observed in oral mucosal premalignancy. In addition, recommendations for future research studies directed at defining the predictive capacity of specific biomarkers in this modeling are presented.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 16