Identification of a combined biomarker for malignant transformation in oral submucous fibrosis

Shadavlonjid Bazarsad, Xianglan Zhang, Ki Yeol Kim, Rasika Illeperuma, Ruwan D. Jayasinghe, Wanninayake M. Tilakaratne, Jin Kim

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Background: Oral submucous fibrosis (OSF) is a chronic progressive disease of the oral cavity that is considered a common potentially malignant disorder in South Asia. Areca nut chewing is the main etiological factor, but its carcinogenic mechanism has yet to be proven. The purpose of this study was to identify the useful biomarkers in predicting high-risk patients with OSF. Methods: Thirty-six cases of OSF and six cases of normal oral mucosa (NOM) were used for this study. Immunohistochemical staining was performed for Ki67, cyclin D1, p16, p53, β-catenin, c-Jun, c-Met, and insulin-like growth factor II mRNA-binding protein 3 (IMP3). The expression patterns of NOM served as guidelines for the scoring system. Results: The expression of Ki67, cyclin D1, c-Met, IMP3, and β-catenin showed a significant difference between OSF and NOM samples. The combined biomarkers of Ki67 and p16 showed significantly different expression between the transformation and non-transformation groups. With discriminant analysis, we proposed a noble formula and cutoff value for predicting high-risk patients with OSF. Conclusion: The notable biomarkers in our present study were Ki67 and p16 showing significantly different expression levels between the transformation and non-transformation groups. With the identification of high-risk patients with OSF, we can expect to develop more intensive treatment modalities, leading to the reduction in cancer transformation rate from OSF.

Original languageEnglish
Pages (from-to)431-438
Number of pages8
JournalJournal of Oral Pathology and Medicine
Volume46
Issue number6
DOIs
Publication statusPublished - 2017 Jul 1

Fingerprint

Oral Submucous Fibrosis
Biomarkers
Mouth Mucosa
Catenins
Cyclin D1
Carrier Proteins
Areca
Messenger RNA
Nuts
Insulin-Like Growth Factor II
Mastication
Discriminant Analysis
Mouth
Chronic Disease
Guidelines
Staining and Labeling

All Science Journal Classification (ASJC) codes

  • Pathology and Forensic Medicine
  • Oral Surgery
  • Otorhinolaryngology
  • Cancer Research
  • Periodontics

Cite this

Bazarsad, S., Zhang, X., Kim, K. Y., Illeperuma, R., Jayasinghe, R. D., Tilakaratne, W. M., & Kim, J. (2017). Identification of a combined biomarker for malignant transformation in oral submucous fibrosis. Journal of Oral Pathology and Medicine, 46(6), 431-438. https://doi.org/10.1111/jop.12483
Bazarsad, Shadavlonjid ; Zhang, Xianglan ; Kim, Ki Yeol ; Illeperuma, Rasika ; Jayasinghe, Ruwan D. ; Tilakaratne, Wanninayake M. ; Kim, Jin. / Identification of a combined biomarker for malignant transformation in oral submucous fibrosis. In: Journal of Oral Pathology and Medicine. 2017 ; Vol. 46, No. 6. pp. 431-438.
@article{105097ce291a49fca6874c08a9c69c09,
title = "Identification of a combined biomarker for malignant transformation in oral submucous fibrosis",
abstract = "Background: Oral submucous fibrosis (OSF) is a chronic progressive disease of the oral cavity that is considered a common potentially malignant disorder in South Asia. Areca nut chewing is the main etiological factor, but its carcinogenic mechanism has yet to be proven. The purpose of this study was to identify the useful biomarkers in predicting high-risk patients with OSF. Methods: Thirty-six cases of OSF and six cases of normal oral mucosa (NOM) were used for this study. Immunohistochemical staining was performed for Ki67, cyclin D1, p16, p53, β-catenin, c-Jun, c-Met, and insulin-like growth factor II mRNA-binding protein 3 (IMP3). The expression patterns of NOM served as guidelines for the scoring system. Results: The expression of Ki67, cyclin D1, c-Met, IMP3, and β-catenin showed a significant difference between OSF and NOM samples. The combined biomarkers of Ki67 and p16 showed significantly different expression between the transformation and non-transformation groups. With discriminant analysis, we proposed a noble formula and cutoff value for predicting high-risk patients with OSF. Conclusion: The notable biomarkers in our present study were Ki67 and p16 showing significantly different expression levels between the transformation and non-transformation groups. With the identification of high-risk patients with OSF, we can expect to develop more intensive treatment modalities, leading to the reduction in cancer transformation rate from OSF.",
author = "Shadavlonjid Bazarsad and Xianglan Zhang and Kim, {Ki Yeol} and Rasika Illeperuma and Jayasinghe, {Ruwan D.} and Tilakaratne, {Wanninayake M.} and Jin Kim",
year = "2017",
month = "7",
day = "1",
doi = "10.1111/jop.12483",
language = "English",
volume = "46",
pages = "431--438",
journal = "Journal of Oral Pathology and Medicine",
issn = "0904-2512",
publisher = "Wiley-Blackwell",
number = "6",

}

Bazarsad, S, Zhang, X, Kim, KY, Illeperuma, R, Jayasinghe, RD, Tilakaratne, WM & Kim, J 2017, 'Identification of a combined biomarker for malignant transformation in oral submucous fibrosis', Journal of Oral Pathology and Medicine, vol. 46, no. 6, pp. 431-438. https://doi.org/10.1111/jop.12483

Identification of a combined biomarker for malignant transformation in oral submucous fibrosis. / Bazarsad, Shadavlonjid; Zhang, Xianglan; Kim, Ki Yeol; Illeperuma, Rasika; Jayasinghe, Ruwan D.; Tilakaratne, Wanninayake M.; Kim, Jin.

In: Journal of Oral Pathology and Medicine, Vol. 46, No. 6, 01.07.2017, p. 431-438.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Identification of a combined biomarker for malignant transformation in oral submucous fibrosis

AU - Bazarsad, Shadavlonjid

AU - Zhang, Xianglan

AU - Kim, Ki Yeol

AU - Illeperuma, Rasika

AU - Jayasinghe, Ruwan D.

AU - Tilakaratne, Wanninayake M.

AU - Kim, Jin

PY - 2017/7/1

Y1 - 2017/7/1

N2 - Background: Oral submucous fibrosis (OSF) is a chronic progressive disease of the oral cavity that is considered a common potentially malignant disorder in South Asia. Areca nut chewing is the main etiological factor, but its carcinogenic mechanism has yet to be proven. The purpose of this study was to identify the useful biomarkers in predicting high-risk patients with OSF. Methods: Thirty-six cases of OSF and six cases of normal oral mucosa (NOM) were used for this study. Immunohistochemical staining was performed for Ki67, cyclin D1, p16, p53, β-catenin, c-Jun, c-Met, and insulin-like growth factor II mRNA-binding protein 3 (IMP3). The expression patterns of NOM served as guidelines for the scoring system. Results: The expression of Ki67, cyclin D1, c-Met, IMP3, and β-catenin showed a significant difference between OSF and NOM samples. The combined biomarkers of Ki67 and p16 showed significantly different expression between the transformation and non-transformation groups. With discriminant analysis, we proposed a noble formula and cutoff value for predicting high-risk patients with OSF. Conclusion: The notable biomarkers in our present study were Ki67 and p16 showing significantly different expression levels between the transformation and non-transformation groups. With the identification of high-risk patients with OSF, we can expect to develop more intensive treatment modalities, leading to the reduction in cancer transformation rate from OSF.

AB - Background: Oral submucous fibrosis (OSF) is a chronic progressive disease of the oral cavity that is considered a common potentially malignant disorder in South Asia. Areca nut chewing is the main etiological factor, but its carcinogenic mechanism has yet to be proven. The purpose of this study was to identify the useful biomarkers in predicting high-risk patients with OSF. Methods: Thirty-six cases of OSF and six cases of normal oral mucosa (NOM) were used for this study. Immunohistochemical staining was performed for Ki67, cyclin D1, p16, p53, β-catenin, c-Jun, c-Met, and insulin-like growth factor II mRNA-binding protein 3 (IMP3). The expression patterns of NOM served as guidelines for the scoring system. Results: The expression of Ki67, cyclin D1, c-Met, IMP3, and β-catenin showed a significant difference between OSF and NOM samples. The combined biomarkers of Ki67 and p16 showed significantly different expression between the transformation and non-transformation groups. With discriminant analysis, we proposed a noble formula and cutoff value for predicting high-risk patients with OSF. Conclusion: The notable biomarkers in our present study were Ki67 and p16 showing significantly different expression levels between the transformation and non-transformation groups. With the identification of high-risk patients with OSF, we can expect to develop more intensive treatment modalities, leading to the reduction in cancer transformation rate from OSF.

UR - http://www.scopus.com/inward/record.url?scp=84982804408&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84982804408&partnerID=8YFLogxK

U2 - 10.1111/jop.12483

DO - 10.1111/jop.12483

M3 - Article

VL - 46

SP - 431

EP - 438

JO - Journal of Oral Pathology and Medicine

JF - Journal of Oral Pathology and Medicine

SN - 0904-2512

IS - 6

ER -

Bazarsad S, Zhang X, Kim KY, Illeperuma R, Jayasinghe RD, Tilakaratne WM et al. Identification of a combined biomarker for malignant transformation in oral submucous fibrosis. Journal of Oral Pathology and Medicine. 2017 Jul 1;46(6):431-438. https://doi.org/10.1111/jop.12483