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J Carcinog. 2018 Dec 31;17:7. doi: 10.4103/jcar.JCar_17_18. eCollection 2018.

Molecular pathways of oral cancer that predict prognosis and survival: A systematic review.

Author information

1
Department of Oral Pathology and Microbiology, Faculty of Dental Sciences, Ramaiah University of Applied Sciences, Bengaluru, Karnataka, India.
2
Department of Maxillofacial Surgery and Diagnostic Sciences, College of Dentistry, Jazan University, Jazan, Saudi Arabia.
3
College of Dental Medicine, Roseman University of Health Sciences, South Jordan, Utah, USA.
4
Department of Oral and Maxillofacial Surgery, Faculty of Dental Sciences, Ramaiah University of Applied Sciences, Bengaluru, Karnataka, India.

Abstract

Several genes and pathways associated with oral squamous cell carcinoma (OSCC) are significant in terms of early detection and prognosis. The objective of this literature review is to evaluate the current research on molecular pathways and genes involved in oral cancer. Articles on the genes involved in oral cancer pathways were evaluated to identify potential biomarkers that can predict survival. In total, 36 articles were retrieved from internet databases, including EBSCO Host, Google Scholar, PubMed, and Science Direct, using the keywords "biomarker of oral cancer," "pathways of oral cancer," "genes involved in oral cancer," and "oral cancer pathways." A total of 36 studies related to OSCC were chosen. Most of the studies used cell lines, while others used archival tissues, few studies followed up the cases. Three major interlinked pathways found were the nuclear factor kappa B (NF-kB), PI3K-AKT, and Wnt pathways. The commonly mutated genes were cyclin D1 (CCND1), Rb, p53, FLJ10540, and TC21. The NF-kB, PI3K-AKT, and Wnt pathways are most frequently involved in the molecular pathogenesis of oral cancer. However, the CCND1, Rb, p53, FLJ10540, and TC21 genes were found to be more accurate in determining patients' overall survival. Polymerase chain reaction, immunohistochemistry, and immunoblotting were the commonly used detection methods.

KEYWORDS:

Biomarkers; molecular pathways; prognosis; survival; targeted therapy

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