전체 게놈 검색법을 이용한 몽골 고립 부족 Triglyceride 유전자자리에 관한 연구

학위논문 (석사)-- 서울대학교 대학원 : 의학과 생화학 전공, 2011.8. 서정선.Maste

Development and Validation of Tumor Immunogenicity Based Gene Signature for Skin Cancer Risk Stratification

Melanoma is one of the most aggressive types of skin cancer, with significant heterogeneity in overall survival. Currently, tumor-node-metastasis (TNM) staging is insufficient to provide accurate survival prediction and appropriate treatment decision making for several types of tumors, such as those in melanoma patients. Therefore, the identification of more reliable prognosis biomarkers is urgently essential. Recent studies have shown that low immune cells infiltration is significantly associated with unfavorable clinical outcome in melanoma patients. Here we constructed a prognostic-related gene signature for melanoma risk stratification by quantifying the levels of several cancer hallmarks and identify the Wnt/β-catenin activation pathway as a primary risk factor for low tumor immunity. A series of bioinformatics and statistical methods were combined and applied to construct a Wnt-immune-related prognosis gene signature. With this gene signature, we computed risk scores for individual patients that can predict overall survival. To evaluate the robustness of the result, we validated the signature in multiple independent GEO datasets. Finally, an overall survival-related nomogram was established based on the gene signature and clinicopathological features. The Wnt-immune-related prognostic risk score could better predict overall survival compared with standard clinicopathological features. Our results provide a comprehensive map of the oncogene-immune-related gene signature that can serve as valuable biomarkers for better clinical decision making

ENCODE: A Sourcebook of Epigenomes and Chromatin Language

Until recently, since the Human Genome Project, the general view has been that the majority of the human genome is composed of junk DNA and has little or no selective advantage to the organism. Now we know that this conclusion is an oversimplification. In April 2003, the National Human Genome Research Institute (NHGRI) launched an international research consortium called Encyclopedia of DNA Elements (ENCODE) to uncover non-coding functional elements in the human genome. The result of this project has identified a set of new DNA regulatory elements, based on novel relationships among chromatin accessibility, histone modifications, nucleosome positioning, DNA methylation, transcription, and the occupancy of sequence-specific factors. The project gives us new insights into the organization and regulation of the human genome and epigenome. Here, we sought to summarize particular aspects of the ENCODE project and highlight the features and data that have recently been released. At the end of this review, we have summarized a case study we conducted using the ENCODE epigenome data

Discovery of common Asian copy number variants using integrated high-resolution array CGH and massively parallel DNA sequencing

Copy number variants (CNVs) account for the majority of human genomic diversity in terms of base coverage. Here, we have developed and applied a new method to combine high-resolution array comparative genomic hybridization (CGH) data with whole-genome DNA sequencing data to obtain a comprehensive catalog of common CNVs in Asian individuals. The genomes of 30 individuals from three Asian populations (Korean, Chinese and Japanese) were interrogated with an ultra-high-resolution array CGH platform containing 24 million probes. Whole-genome sequencing data from a reference genome (NA10851, with 28.3x coverage) and two Asian genomes (AK1, with 27.8x coverage and AK2, with 32.0x coverage) were used to transform the relative copy number information obtained from array CGH experiments into absolute copy number values. We discovered 5,177 CNVs, of which 3,547 were putative Asian-specific CNVs. These common CNVs in Asian populations will be a useful resource for subsequent genetic studies in these populations, and the new method of calling absolute CNVs will be essential for applying CNV data to personalized medicine.Conrad DF, 2010, NATURE, V464, P704, DOI 10.1038/nature08516Kim JI, 2009, NATURE, V460, P1011, DOI 10.1038/nature08211Horowitz RE, 2008, NEW ENGL J MED, V359, P2393Shiffman D, 2008, PLOS ONE, V3, DOI 10.1371/journal.pone.0002895Kidd JM, 2008, NATURE, V453, P56, DOI 10.1038/nature06862Perry GH, 2008, AM J HUM GENET, V82, P685, DOI 10.1016/j.ajhg.2007.12.010Graham DSC, 2008, GENES IMMUN, V9, P93, DOI 10.1038/sj.gene.6364453Lohmueller KE, 2008, NATURE, V451, P994, DOI 10.1038/nature06611Korbel JO, 2007, SCIENCE, V318, P420, DOI 10.1126/science.1149504Hossain P, 2007, NEW ENGL J MED, V356, P213Larson MG, 2007, BMC MED GENET, V8, DOI 10.1186/1471-2350-8-S1-S5Redon R, 2006, NATURE, V444, P444, DOI 10.1038/nature05329Jee SH, 2006, NEW ENGL J MED, V355, P779Aitman TJ, 2006, NATURE, V439, P851, DOI 10.1038/nature04489Conrad DF, 2006, NAT GENET, V38, P75, DOI 10.1038/ng1697Wang YH, 2005, J LAB CLIN MED, V146, P321, DOI 10.1016/j.lab.2005.07.007Lindner I, 2005, MOL NUTR FOOD RES, V49, P972, DOI 10.1002/mnfr.200500087Tuzun E, 2005, NAT GENET, V37, P727, DOI 10.1038/ng1562Lee JW, 2005, ONCOGENE, V24, P1477, DOI 10.1038/sj.onc.1208304Iafrate AJ, 2004, NAT GENET, V36, P949, DOI 10.1038/ng1416Samuels Y, 2004, SCIENCE, V304, P554, DOI 10.1126/science.1096502Burchard EG, 2003, NEW ENGL J MED, V348, P1170COLIN Y, 1991, BLOOD, V78, P27474