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FULLTEXT01.Pdf To identify novel oncogenes for the design of novel tools for diagnosis and treatment of cancer Master Degree Project in infection Biology 60 ECTS Spring term Year Selva Kumar Mandiramoorthy [email protected] 19930713-3513 Course responsible Diana Tilvek [email protected] School of Bio science University of skÖvde, Sweden Examiner Patric Nilsson [email protected] School of Bio-science University of skÖvde, Sweden Supervisor Annica K. B. Gad, Ph.D. Senior/ Leading Researcher (R4) [email protected] CQM- Madeira Chemistry Research Centre / Centro de Química da Madeira University of Madeira Campus da Penteada 9020-105 Funchal, PORTUGAL ABSTRACT Cancer is a disease caused by an uncontrolled cell growth that destroys the healthy tissue of the body. It is one of the deadliest diseases in the world that alters many cellular mechanisms and features. In this report, a list of 22 upregulated oncogenes is studied to identify the novel oncogene. The need to determine the novel oncogene is to develop the anti-cancer agent. To determine the novel oncogene, gene enrichment analysis (GEA) was performed. It is a method to identify classes of genes that are over-represented in the large set of genes to determine the phenotypes of the organisms. DAVID and PANTHER are the methods used to carry on this study as it has Gene Ontology (GO) embedded in it. The GEA uses fishers exact test to determine the enriched gene by the standard p-value of 0.05. To further study the oncogene Network Enrichment Analysis was performed with EVINET. We found that microtubule was significantly enriched in NEA. The genes significantly enriched for GO microtubule were studied. The significantly enriched microtubule in NEA might then be used as a target for anti- cancer agent and used to develop the drug in the future. POPULAR SCIENTIFIC ABSTRACT Cancer is a disease caused by an uncontrolled cell growth that destroys the healthy tissue of the body. Cancer composition alters many cellular mechanisms and functions. According to the World Health Organization (WHO), cancer is the second leading cause of death globally, and it is estimated to be about 9.6 million deaths in 2018. Cancer is caused mainly due to infections such as hepatitis and human papillomavirus (HPV) mostly in the middle – low-income countries. Cancer is a genetic disease that can affect any part of the body. The main feature of a tumor is that it can grow abnormal cells beyond the usual boundaries and then destroy the specific organ and spread to the other parts of the body in a process called metastasis. The ability of the abnormal cells to spread to the other organs is known as metastasizing cells. Gene Enrichment analysis it is a method to identify classes of genes and protein that are over- represented in the large set of genes by the user to define the phenotypes of the organisms. In this study, it is used because it helps to understand the direct interest to the understanding of the functional mechanism in a cell also specific pathway activated in a given data. GEA works on the statistical analysis it used basic Fisher exact test to provide the raw p-value and multiple hypotheses or FDR are calculated by Benjamini-Hochberg method or Bonferroni method. The technique used to perform this study is by DAVID and PANTHER. They are the online software tool for accomplishing this Enrichment Analysis. The technology works with human data as background collected in a group and stored in a database known as Gene Ontology (GO). The result from this study is provided in three distributions; Cellular Component, Biological Pathway, and Molecular Functions. Network Enrichment analysis was performed to determine the topological information and the network links between the gene-protein interaction. NEA performs the quick binomial test as described in methods and quantifies enrichment in each AGS (Altered Gene Set) FGS (Functional Gene Set) pair with some statistics: chi-squared score, z-score, p-value, q-value (the p-value Adjusted for false discovery rate). EVINET is an online tool used to perform the NEA. The result from this study gave the understanding of 22 upregulated genes. The significantly enriched genes are KIF18A, KIF14, KIF13B include known as kinesin protein family members. These genes are significantly enriched for the microtubule-based process. Microtubule is the significant component of the cytoskeleton. Microtubule is a tubular polymer that forms the structure and shape to the cytoplasm of eukaryotic cells and regulates cell adhesions. These are results helpful in constructing the anti-cancer agent. Microtubule is said to be a potent as it is essential in a cellular process, cell growth, cytokinesis, transport, and mobility in the cell used as the development of anti-cancer agent. LIST OF ABBREVIATIONS AGS – Altered Gene Set FGS – Functional Gene Set GSEA – Gene Set Enrichment Analysis. ICGC - International Cancer Genomics Consortium. TCGA - Cancer Genome Atlas. GO – Gene Ontology. NCBI - National Center for Biotechnology Information. PSA - prostate-specific antigen. IBD - Inflammatory Bowel Disease. DAVID - The Database for Annotation, Visualization, and Integrated Discovery. PANTHER - Protein Analysis Through Evolutionary Relationships. KEGG - Kyoto Encyclopedia of Genes and Genomes FAP - Familial Adenomatous Polyposis. HNPCC - hereditary nonpolyposis colorectal cancer. FDR – False Discovery Rate. PIP3- phosphatidylinositol-trisphosphate. HA- Hyaluronan Contents INTRODUCTION ................................................................................................................................... 1 Cancer.................................................................................................................................................. 1 Oncogenes ........................................................................................................................................... 1 Oncogene list ....................................................................................................................................... 1 Breast cancer ....................................................................................................................................... 1 Prostate cancer ..................................................................................................................................... 2 Colorectal cancer ................................................................................................................................. 2 Cancer in System Biology ................................................................................................................... 2 Gene Ontology .................................................................................................................................... 3 Gene Enrichment Analysis .................................................................................................................. 4 Network Enrichment Analysis (NEA)................................................................................................. 4 AIM ......................................................................................................................................................... 5 MATERIALS AND METHODS ............................................................................................................ 5 DAVID ................................................................................................................................................ 5 PANTHER .......................................................................................................................................... 5 Statistical analysis: .............................................................................................................................. 6 EVINET .............................................................................................................................................. 6 RESULTS ................................................................................................................................................ 7 Results from DAVID........................................................................................................................... 7 Results from PANTHER ..................................................................................................................... 9 Results from EVINET ....................................................................................................................... 13 Other Methods ................................................................................................................................... 14 DISCUSSION ....................................................................................................................................... 14 ETHICAL ASPECTS ............................................................................................................................ 17 CONCLUSION ..................................................................................................................................... 17 FUTURE WORK .................................................................................................................................. 17 ACKNOWLEDGMENT ....................................................................................................................... 18 REFERENCE .......................................................................................................................................
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