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Updated: Jun 13, 2026

A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies
Published on: September 23, 2014
Molecular analysis of oral squamous cell carcinoma: a tissue microarray study
M C Solomon1, S Carnelio, V Gudattu
1Department of Oral Pathology, Manipal College of Dental Science, Manipal University, Manipal, Karnataka 576 104, India.
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 mum thick sections were cut and immunostained for p53, Bcl-2 and E-cadherin.
Statistical 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.
