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Feichtinger Phd 2012.Pdf Bangor University DOCTOR OF PHILOSOPHY Development of bioinfirmatic analytical approach to identify novel human cancer testis gene candidates Feichtinger, Julia Award date: 2012 Awarding institution: Bangor University Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Download date: 04. Oct. 2021 Development of a Bioinformatic Analytical Approach to Identify Novel Human Cancer Testis Gene Candidates A thesis submitted to Bangor University in candidature for the degree of Doctor of Philosophy in Cancer Studies Julia Feichtinger North West Cancer Research Fund Institute, Bangor University, Bangor, Gwynedd LL57 2UW, UK December 2012 Summary The identification of tumour antigens (TAs) represents an ongoing challenge to the de- velopment of novel cancer diagnostic, prognostic and therapeutic strategies. A group of proteins, the cancer testis (CT) antigens are promising targets for such clinical ap- plications. Their encoding genes show expression restricted to the immunologically privileged testes but their expression is also found in cells with a cancerous phenotype. To facilitate and automate the identification of novel CT genes, bioinformatic analytical pipelines based on publicly available microarray and expressed sequence tag (EST) data were developed and implemented as web tools to support wider application. Human germline-associated datasets were generated and the developed screening pipelines were subsequently used to analyse these datasets, leading to the identification of a novel co- hort of meiosis-specific genes, the meiCT genes that exhibit the characteristics of CT genes and may have oncogenic features. In general, frequent germline gene expression found in cancer could reflect a soma-to-germline transformation occurring in human cells in the course of the development of cancer. The expression of germline-specific genes, in particular of meiotic genes, could lead to the production of proteins that cause oncogenic events and thus contribute to tumorigenesis and to the acquisition of tumour characteristics. i Contents Please note that chapters with * are presented as papers/manuscripts and thus do not follow regular numbering. The numbering for these sections is omitted. Acknowledgements xiii Declaration xv Abbreviations xix 1 Introduction 1 1.1 CancerandCancerTestisAntigens . 1 1.1.1Cancer................................... 1 1.1.2Carcinogenesis .............................. 1 1.1.3TumourAntigens............................. 3 1.1.4 CancerTestisAntigens. 5 1.2Meiosis...................................... 11 1.2.1 ThePrincipleofMeiosis . 11 1.2.2 MammalianGametogenesis . 12 1.2.3MeioticEntry............................... 15 1.2.4 MeioticRecombination. 16 1.2.5 TheSynaptonemalComplex . 18 1.2.6 Dependency of Pairing, Meiotic Recombination and Synapsis. 20 1.3CancerandGermCells............................. 21 1.4 MicroarrayMeta-analysis* . 23 Abstract..................................... Introduction................................... MicroarrayTechnologyandDataAnalysis . Meta-Analysis: TheAnalysisofAnalyses . VisualizationofComplexData. References .................................... iii Contents 1.5 ExpressedSequenceTagMeta-analysis . 59 1.5.1 ExpressedSequenceTagTechnology . 59 1.5.2 ExpressedSequenceTagDataAnalysis . 59 1.5.3 Expressed Sequence Tag Meta-analysis . 60 2 Aims and Objectives 67 3 Meta-analysis of Clinical Data Identifies a Novel Cohort of Highly Cancer-specific Marker Genes* 69 Abstract ....................................... Introduction ..................................... Results........................................ Discussion ...................................... MaterialsandMethods ............................... References ...................................... SupplementalMaterial ............................... 4 CancerMA: a Web-based Tool for Automatic Meta-analysis of Public Cancer Microarray Data* 91 Abstract ....................................... Introduction ..................................... MethodsandStructureofCancerMA . Discussion ...................................... Conclusion ...................................... References ...................................... SupplementalMaterial ............................... 5 CancerEST: a Web-based Tool for Automatic Meta-analysis of Public EST Data* 103 Abstract ....................................... Introduction ..................................... MethodsandStructureofCancerEST . .. UseofCanceEST .................................. Validation ...................................... Discussion ...................................... Conclusion ...................................... References ...................................... SupplementalMaterial ............................... iv Contents 6 Meta-analysis of Germline Gene Expression* 123 Abstract ....................................... Introduction ..................................... MaterialsandMethods ............................... Results........................................ Discussion ...................................... References ...................................... SupplementalMaterial ............................... 7 Overall Discussion 165 8 Conclusions 181 8.1ProjectAimI ..................................181 8.2ProjectAimII..................................182 9 Further Works 183 Appendices 185 References 233 v List of Tables Please note that chapters with * are presented as papers/manuscripts and thus do not follow regular numbering. The numbering for these tables is omitted. Chapter 1* A selection of internet repositories and search interfaces for microarray data . A selection of useful annotation tools for microarrays . .......... A selection of available meta-analysis tools . ........ vii List of Figures Please note that chapters with * are presented as papers/manuscripts and thus do not follow regular numbering. The numbering for these figures is omitted. Chapter 1* 1.1 The hallmarks of cancer proposed by Hanahan and Weinberg . 3 1.2 Scheme of spermatogenesis and expression of cancer testis (CT) genes in humangermcells ............................... 7 1.3 Epigenetic events regulating cancer testis (CT) gene expression. 9 1.4 Overview of the meiotic process during mammalian gametogenesis . 13 1.5 Timing of gametogenesis/meiosis in mammalian males and females. 14 1.6 Schematic composition of the seminiferous epithelium in the mammaliantestes............................... 15 1.7 Distinct pathways of meiotic recombination. 17 1.8 Schematic composition of the synaptonemal complex (SC) . 19 1.9 Assemblyofthesynaptonemalcomplex(SC) . 19 1.10 Temporal course of pairing, meiotic recombination and synaptonemal complex(SC)formation ........................... 20 ExampleForestplot ................................ Chapter 3* Examples of gene expression and protein production profiles for meiCT genes . Schematic flow diagram for the selection of candidate meiCT genes . Grid representation of gene expression profiles for the 33 meiCT genes identified Circos plot showing the meta-change in gene expression in relation to corresponding cancer types for the 25 meiCT genes . ... An example of a Forest plot for a meiCT gene, PRDM9 ............ Circos plot showing the meta-change in gene expression in relation to corresponding cancer types for the 21 genes with a testis-only expression profile ..................................... ix List of Figures Chapter 4* CancerMAworkflow ................................ Circos plots showing the meta-change in gene expression in relation to correspondingcancertypes. An example of a Forest plot showing the expression of gene CAV1 downregulatedinlungcancer . Circos plot showing the meta-change in gene expression in relation to correspondingcancertypes. Chapter 5* CancerESTworkflow ................................ Circos plot showing the gene expression in relation to the corresponding cancer types for the 39 testis-restricted genes . ..... An example of a bar chart showing the integrated expression profile of the MAGEA1 gene ................................ Chapter 6* Circos plot showing the gene expression in relation to the corresponding cancer types for the 43 human orthologues based on the EST meta-analysis Circos plot showing the meta-change in gene expression in relation to corresponding cancer types for the 41 human homologues based on the microarraymeta-analysis . Chapter 7 7.1 High-throughput expression profiling techniques in comparison with high-sensitivitymethods . 167 7.2 Examples of applications and workflows for both pipelines ........169 7.3 DataselectionprocessforCancerEST . 170 7.4 DataselectionprocessforCancerMA . 171 7.5 Visualisations of the results generated by CancerMA . 176 x Appendices AppendixA.......................................185 AppendixB.......................................189
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