Bioinformatic%20Analysis%20for%20the%20Validation%20of%20Novel%20Biomarkers%20for%20Cancer%20Diagnosis%20and%20Drug%20Sensitivity
Abstract

Background: The genetic control of tumour progression presents the opportunity for bioinformatics and gene expression data to be used as a basis for tumour grading. The development of a genetic signature based on microarray data allows for the development of personalised chemotherapeutic regimes. Method: ONCOMINE was utilised to create a genetic signature for ovarian serous adenocarcinoma and to compare the expression of genes between normal ovarian and cancerous cells. Ingenuity Pathways Analysis was also utilised to develop molecular pathways and observe interactions with exogenous molecules. Results: The gene signature demonstrated 98.6% predictive capability for the differentiation between borderline ovarian serous neoplasm and ovarian serous adenocarcinoma. The data demonstrated that many genes were related to angiogenesis. Thymidylate synthase, GLUT-3 and HSP90AA1 were related to tanespimycin sensitivity (p=0.005). Conclusions: Genetic profiling with the gene signature demonstrated potential for clinical use. The use of tanespimycin alongside overexpression of thymidylate synthase, GLUT-3 and HSP90AA1 is a novel consideration for ovarian cancer treatment.

How to Cite
Lockwood L. A. (2015) “Bioinformatic Analysis for the Validation of Novel Biomarkers for Cancer Diagnosis and Drug Sensitivity”, Fields: journal of Huddersfield student research. 1(1). doi: https://doi.org/10.5920/fields.2015.115

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Laura Anne Rebecca Lockwood
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