Microarray Analysis of Tumor Suppressor Proteins p53 and p63: Their Role in Tumor Cell Dynamics

Oluwafemi Shittu Bakare ^1*, Akinrinmisi Michael Ayomide ¹, Olajuyigbe Olakunle Julius ¹

Microarray analysis advances cancer research by enabling high-throughput gene expression profiling, uncovering biomarkers, and guiding personalized medicine.

Abstract

Background: Microarray technology has become essential in cancer research, providing insights into gene expression patterns and regulatory networks governed by key transcription factors. This review focuses on using microarray technology to elucidate genes regulated by tumor suppressor proteins p53 and p63. These proteins maintain genomic stability, regulate the cell cycle, and induce programmed cell death. Dysregulation of p53 and p63 is common in various cancers, highlighting their significance in cancer biology. Methods: Microarray technology enables high-throughput analysis of thousands of genes simultaneously. Researchers compare gene expression profiles in cancer cells and tissues with functional p53 and p63 against those with impaired function. This comparative analysis identifies numerous downstream target genes and pathways influenced by these transcription factors. Results: Microarray studies have revealed a wide array of genes regulated by p53 and p63, involved in DNA repair, apoptosis, cell cycle control, and epithelial differentiation. These findings enhance our understanding of molecular mechanisms driving cancer initiation, progression, and therapeutic resistance. Additionally, microarray technology enables the stratification of cancer subtypes based on distinct gene expression signatures associated with p53 and p63 status, offering insights into patient prognosis, treatment responses, and personalized therapeutic strategies. Conclusion: Microarray technology has significantly advanced our knowledge of gene regulatory networks orchestrated by p53 and p63 in cancer. Despite limitations like data interpretation and cross-hybridization, advancements in bioinformatics and complementary technologies are improving study accuracy and reliability, promising better cancer diagnostics, prognostics, and targeted therapies.

Keywords: Cell cycle, Genomics, Transcription factors, Epithelial differentiation, Gene expression.

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