Laboratory of Cancer Genomics, GSMSE, KAIST

Building #N26 (CHIPS Center) 3F,  Daejeon 34141, Korea

Ph:+82-42-350-4267; F:+82-42-350-4240

Copyright 2017 Julab. All rights reserved.

last update: Apr. 10. 2017

Academic interests

As an independent scientist, I started my laboratory at KAIST, from Nov. 2015. My expertise is cancer genomics, which aims to understand somatic mutations and their functional consequences in human cancers. Now, I am interested in understanding the mutational processes operative in human somatic cells at variant time points across the life history of human cells, from fertilized-egg to advanced and very late stage of cancer cells (1).

Graduate School of Medical Science and Engineering at KAIST (http://gsmse.kaist.ac.kr) has a unique and specialized PhD training program for distinguished medical doctors and biologists in South Korea to perform cutting-edge biomedical research. We are in very good position to perform both the basic medical research for understanding the basic disease mechanisms and translational medical research for bringing genome technologies to promote enhancements in cancer diagnosis and therapies.

Here, I introduce major directions of my research for a few years to come.

1. Understanding the genetic etiology of uncommon and undiagnosed cancers

For the last a couple of years, international cancer genome consortia (i.e. ICGC and TCGA) have extensively revealed genomic mutations in many human cancers. However, many rare cancer types are still left unexplored by genome technologies (2). In South Korea, approximately 20% of all cancer cases are classified as “uncommon or undiagnosed”. These patients are disadvantaged because their diseases are frequently neglected from the development of therapeutic agents and clinical trials. Usually, the patients are treated by empirical treatments, such as cytotoxic agents, without any specific supporting evidence for their cancer. Therefore, it is necessary to shift our focus of cancer genome research from common into these rare tumor types.


As soon as I started my laboratory in KAIST, I constructed a translational research pipeline with clinicians in Korea. (We are always open to collaboration research! Please contact us if you are interested in.) Here, we intend to collect all the uncommon and undiagnosed cancer cases, which are to be used for derivation of cancer cell-lines and for analyses of cancer genomes and transcriptomes. Our efforts will definitely enable us to understand the pathophysiology of these cancers at a molecular level. Furthermore, at least in some fortunate cases, clinically actionable targets will be identified. From 2016, we started to sequence some undiagnosed cases in clinic. From two tumor case, we identified an oncogenic fusion between NUT and BRD3 genes (PMID:28203693). This allowed us to diagnose the case as NUT midline carcinoma and to suggest the best treatment option (BRD-inhibitor) for the patient. In addition, we revealed that complex genome rearrangement mechanisms, i.e. chromoplexy, are underlying for the fusion genes. These cases directly shows that our translational research would be very productive for the next few years.

2. Understanding tumor heterogeneity using organoid deep sequencing and single-cell RNA imaging

Cancer evolves by continuous acquisition of somatic mutations and natural selection resulting in the emergence of intra-tumor heterogeneity (3). Heterogeneity among intra-tumor clones enhances the fitness of the tumor and allows it to grow under the challenges of new or altered environments. The Darwinian concept of clone evolution explains how growing genetic complexity among the tumor cell population induces tumor metastasis and resistance to medical intervention. Until recently, however, the theoretical model of Darwinian tumor evolution has not been fully scrutinized due to technical limitations. For example, single cell technologies are immature with sub-optimal accuracy. Multi-regional bulk sequencing with bioinformatic reconstruction lacks clonal resolution. By integration of cutting edge technologies, i.e. organoids, genome sequencing, and high resolution imaging, we intend to understand the spatial landscape of intra-tumor heterogeneity at single-cell resolution.

 

3. Understanding cell dynamics in human early embryogenesis by cellular lineage tracing using somatic mutations

 

The human individual consists of ~30 trillion somatic cells. The beginning of our lives is a single cell, or fertilized-egg. Human early embryogenesis, from one cell to blastocyst stage, is a very complex and tightly controlled process and is fundamental to understand the formation of human bodies. However, the early embryonic stage of humans is mostly unexplored, partly due to ethical issues and/or technical limitations. In other words, we do not understand the pattern of cell divisions, the relative contribution of each blastomere to adult tissues, and whether overall the embryo-formation process is deterministic or stochastic.

Using adult blood sequencing data, we sought somatic mutations that occurred during human early embryogenesis (PMID:28329761). This study provided us an insight that ~3 somatic substitution mutations accumulate in every cell division from the very early embryogenesis. These mutations are then maintained in all of the descendants of the cell. Therefore, the cell lineage can be differentiated from the others. I intend to use this to reconstruct the exact family tree of somatic cells by extensive sequencing of clonal lines established from an individual. This will provide an insight into how cell fates were determined in early human embryogenesis. The proof-of-concept of this study was introduced in mice in small scale (4), but not yet applied to humans systematically. 

As described above, using genome sequencing technologies and through international collaboration, we will expand our research field and will perform innovative and challenging studies which I believe are all essential to understand basic biological mechanisms underlying neoplastic diseases and human early embryogenesis.