세미나 (주제 : Application of Bioinformatics for Cancer Epigenetics) 개최 안내
- bics
- 조회수1204
- 2018-04-19
Application of Bioinformatics for Cancer Epigenetics 라는 주제로 아래와 같이 공개 세미나를 개최하오니
구성원 여러분들의 많은 관심과 참석을 바랍니다.
○주제: Application of Bioinformatics for Cancer Epigenetics
○연설자: 최정현 박사 (국립해양생물자원관 국가해양생명자원센터 센터장)
○일시: 2018. 5. 3.(목) 16:00 ~ 18:00
○장소: 성균관대학교 자연과학캠퍼스 산학협력센터 85712호
[Abstract]
Human cancers exist as a highly complex system consisting of heterogeneous cell populations that exhibit diverse
molecular and phenotypic features. Cancer cells often evolve through a reiterative process of clonal expansion, genetic diversification,
clonal selection, and adaptation within tumor microenvironments. Clinically, the presence of a small percentage of drug-resistant or
tumor-initiating cells may ultimately determine the patient’s outcome and survival. The significant intratumoral heterogeneity represents
a formidable challenge to the discovery of effective cancer treatments, and therefore dissection of the tumor heterogeneity holds the key
to the development of more effective drugs to control cancer growth and metastasis. The overarching goal of this project is to develop
bioinformatics tools for dissecting the epigenetic heterogeneity of human cancer. Cancer genome sequencing has opened a new window
to investigate the evolution and genetic tumor heterogeneity in many malignancies. However, the number of mutated genes identified
in cancer is still limited, and many cancer driver genes are mutated at relatively low frequency in a number of cancers. On the other hand,
epigenetic differences are vast between tumor and normal tissues, as well as between patients, typically involving thou-sands of loci in
a particular genome. Several recent studies have revealed the coevolution of genetic and epige-netic aberrations and highlighted
the influential role of epigenetic hierarchy in tumor cell evolution. One of the innovative tools that can examine intratumoral epigenetic
heterogeneity is NOMe-seq (Nucleosome Occupancy and Methylome Sequencing) or MAPit-BGS (Methyltransferase Accessibility Protocol
for individual templates-Bisulfite Genome Sequencing), which allow simultaneously profiling chromatin accessibility and DNA methylation
on single molecules. NOMe-seq uses a GpC methyltransferase (M.CviPI) to methylate GpCs in nucleosome-depleted regions followed
by bisulfite sequencing that measures the de novo methylation of cytosines by M.CviPI. Since the methylation of GpCs and CpGs
represent chromatin accessibility and DNA methylation, respectively, NOMe-seq can footprint active (unmethylated and nucleosome-
depleted), repressed (unmethylated and nucleo-some-occupied), and silent (methylated and nucleosome-occupied) promoters.
Using deep sequencing and long paired-end sequencing, it is possible to detect the minority subpopulations of tumor cells that display
different chromatin and DNA methylation profiles from the bulk tumor population using NOMe-seq. In our preliminary study, we have
successfully sequenced and analyzed one wild type and 3 DNMT knockout HCT116 cell lines using NOMe-seq. Since normal tissues
surrounding the tumors complicate the analysis of the somatic tumor specific epigenetic alteration, we will use cancer-specific and normal
cell-specific signatures. For instance, tumor-infiltrating immune cells will have very different chromatin and DNA methylation patterns in
the promoters of immune responsive genes when compared to tumor cells and other normal epithelial or stromal cells. Therefore, these
immune cell-specific epigenetic signatures can be used to quantify the fraction of tumor infiltrating immune cells. Because NOMe-seq is
DNA-based analysis and normal cells are generally copy number neutral, we in fact can quantify the fraction of normal cell types based on
epigenetic signatures that represent the specific cell types. In addition, hypermethylation in certain tumor suppressor genes such as p16
(CDKN2A) is highly specific to tumor cells; this is supported by a vast amount of published literatures. Using these cancer-specific and
normal cell-specific epigenetic signatures, we will to develop a similar “Cancer Cell Fraction” (CCF) concept used in clonality analysis using
exome sequencing for analyzing NOMe-seq; clonal lineages will be identified by cluster-ing mutations exhibiting shared CCF. Despite
highly innovative technology of NOMe-seq, there are currently no appropriate bioinformatics programs and statistical approaches
that are suitable for this study.
[연설자 주요 약력]
- 국립해양생물자원관 국가해양생명자원센터, 센터장, 2016-현재
- 부산대학교 의료정보학교실, 겸임교수, 2015-현재
- 국립해양생물자원관 응용연구실, 실장, 2016
- 조지아 의과대학 생물통계학과/암센터, 조교수/부교수, 2011-2016
- 조지아 대학교 생물정보학원, 겸임교수, 2014-2016
- 인디애나 대학교 유전체 및 생물정보학센터, 연구원/부디렉터, 2005-2010
- 인디애나 대학교 정보대학, 포스닥, 2004-2005