Abstract
Background : An intriguing aspect of Oral Squamous Cell Carcinomas (OSCC) is its behavioral disparity. Among patients who present with the similar clinicopathological features, some have a better prognosis than others. Identification of molecular alterations responsible for this may contribute to a greater understanding of tumor behavior. Tissue microarray (TMA) approach is a high throughput technology that enables analysis of multiple molecular targets simultaneously without causing any morphological alteration to tissue specimens. Aim and Objective : To assess the tumor behavior based on the expression of p53, Bcl-2 and E-cadherin using TMA technology. Settings and Design : This was a case series analysis using tissue microarray technology. Materials and Methods : Formalin-fixed Paraffin-embedded (FFPE) tissue blocks of histological proven cases of OSCC (n = 30) were retrieved from the department archives. Tissue microarray blocks were constructed; 4 m thick sections were cut and immunostained for p53, Bcl-2 and E-cadherin. Stastistical Analysis : Mean (SD) was used to summarize age, frequencies with percentages was used to summarize categorical variable and Chi-square test was used to find association between histopathology evaluation and expression of Bcl-2, p53, E-cadherin. Results and Conclusion : Bcl-2 was the most frequently expressed biomarker. The expression of Bcl-2 was inversely related to the degree of differentiation (P = 0.005). The follow-up data showed that 63.6% of the cases that were positive for both Bcl-2 and E-cadherin were disease-free following treatment. Tissue microarray technology is a promising way to analyse multiple biomarkers simultaneously. The molecular data obtained from TMA will enhance diagnosis, provide better prognostication and will improve cancer treatment for individual patients.
| Original language | English |
|---|---|
| Pages (from-to) | 166-172 |
| Number of pages | 7 |
| Journal | Indian Journal of Cancer |
| Volume | 47 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 01-04-2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Oncology
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