<records>
<record>
<language>eng</language>
<publisher>Excellent Publishers</publisher>
<journalTitle>
International Journal of Current Microbiology and Applied Sciences (IJCMAS) CODEN(USA)-IJCMO9
</journalTitle>
<issn>2319-7692</issn>
<eissn>2319-7706</eissn>
<publicationDate>2015-01-10</publicationDate>
<volume>5</volume>
<issue>1</issue>
<startPage>209</startPage>
<endPage>220</endPage>
<documentType>article</documentType>
<title language="eng">
Oral Cancer Biomarkers - as Powerful Diagnostic and Prognostic Tools 
</title>

<authors>
<author>
<name>	Palak Ahuja</name>
<affiliationId>1</affiliationId>
</author>

</authors>

<affiliationsList>
<affiliationName affiliationId="1">
Department of Biotechnology, Faculty of Science, Jamia Hamdard, New Delhi-110062, India
</affiliationName>


</affiliationsList>

<abstract language="eng">
<p>
Oral cancer, a complex multistage process, is predominant in the Southeast
Asian countries, owing to increased consumption of smokeless tobacco, tobacco, alcohol and Human papilloma virus type 16 infection. Oral cancers
tends to advance from the non-healing pre-malignant lesions, namely, leukoplakia, erythroplakia and oral sub-mucous fibrosis. However, the
major challenge encountered is to predict which pre-cancerous lesion might
transform into oral carcinoma, indicating the importance of protein based
molecular markers or biomarkers. Several biomarkers, with diagnostic, prognostic and therapeutic value for oral carcinogenesis have been identified
till date and this review focuses on the current understanding of the potential
OSCC biomarkers, such as Endothelin 1, salivary transferrin, zinc finger
protein 510, microRNA: miR-31 as well as cytokine biomarkers, including
</p>
</abstract>

<fullTextUrl format="pdf">
http://www.ijcmas.com/vol-5-1/Palak%20Ahuja.pdf
</fullTextUrl>
<keywords language="eng">
<keyword>Oral cancer
</keyword>
</keywords>
<keywords language="eng">
<keyword>  OSCC</keyword>
</keywords>
<keywords language="eng">
<keyword>Premalignant
lesion
</keyword>
</keywords>
<keywords language="eng">
<keyword>Biomarkers
</keyword>
</keywords>
<keywords language="eng">
<keyword>cytokines
</keyword>
</keywords>
</record>
</records>