Joo Sang Lee
Sungkyunkwan University · Biochemistry, Genetics and Molecular Biology
About the Lab
Professor Joo Sang Lee's research lab focuses on translational cancer genomics and systems biology, with a central emphasis on identifying and validating synthetic lethal interactions for targeted cancer therapy. The lab integrates multi-omics data, particularly from TCGA, to discover clinically relevant genetic vulnerabilities across diverse tumor types. A key direction involves developing data-driven frameworks—such as ISLE—to prioritize synthetic lethal interactions with high translational potential, bridging the gap between preclinical screening and clinical application. The lab also explores innovative diagnostic techniques, including modified cytological methods for intraoperative pathology, and investigates fundamental biological mechanisms, such as genome dynamics in gene regulation.
Research Overview
Research Output Trend
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Selected Papers
15That we know of, this is the first systematic evaluation of the different variables associated with anti-PD-1/PD-L1 therapy response across different tumor types. The findings suggest that the 3 key variables can explain most of the observed cross-cancer response variability, but their relative explanatory roles may vary in specific cancer types.
While synthetic lethality (SL) holds promise in developing effective cancer therapies, SL candidates found via experimental screens often have limited translational value. Here we present a data-driven approach, ISLE (identification of clinically relevant synthetic lethality), that mines TCGA cohort to identify the most likely clinically relevant SL interactions (cSLi) from a given candidate set of lab-screened SLi. We first validate ISLE via a benchmark of large-scale drug response screens and
BACKGROUND: Synthetic lethality (SL) denotes a genetic interaction between two genes whose co-inactivation is detrimental to cells. Because more than 25 years have passed since SL was proposed as a promising way to selectively target cancer vulnerabilities, it is timely to comprehensively assess its impact so far and discuss its future. METHODS: We systematically analyzed the literature and clinical trial data from the PubMed and Trialtrove databases to portray the preclinical and clinical lands
Modified agarose cell-block (CB) technique can be effectively used to have the CB embedded in the OCT compound for the preparation of frozen CB (F-CB) sections in the same way as in the preparation of frozen sections from cryoembedded fresh tissue samples for the intraoperative consultation. In this report, we demonstrate the amenability of F-CB sections to the diagnostic immunocytochemistry. The pelleted cytologic material was at first compactly embedded in ultralow-gelling temperature agarose
Abstract In the last decade, sequencing methods like Hi-C have made it clear the genome is intricately folded, and that this organization contributes significantly to the control of gene expression and thence cell fate and behavior. Single-cell DNA tracing microscopy and polymer physics-based simulations of genome folding have proposed these population-scale patterns arise from motor- driven, heterogeneous movement, rather than stable 3D genomic architecture, implying that motion, rather than st
In this paper we prove that regularly almost periodic is equivalent to nearly periodic for homeomorphisms on compact metric spaces and give an example to show that the above is false without the compactness assumption. We also prove that the following statement is equivalent to the Hilbert-Smith conjecture on compact 3-manifolds <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper M cubed"> <mml:semantics> <mml:mrow class="MJX-TeXAto
Abstract Recent studies have reported that CRISPR-Cas9 gene editing induces a p53 -dependent DNA damage response in primary cells, which may select for cells with oncogenic p53 mutations 11,12 . It is unclear whether these CRISPR-induced changes are applicable to different cell types, and whether CRISPR gene editing may select for other oncogenic mutations. Addressing these questions, we analyzed genome-wide CRISPR and RNAi screens to systematically chart the mutation selection potential of CRIS
Abstract Immune checkpoint therapy leads to durable clinical responses in many cancer patients, but fails in others. To improve the clinical response to immunotherapy, it is highly important to identify predictive biomarkers. While checkpoint genes’ expression levels, tumor neo-antigen load and microsatellite instability (MSI) have been associated with enhanced response to checkpoint immunotherapies, they yet provide only a modest predictive signal and hence there is a need to identify additiona
Herpes simplex virus type 1 (HSV-1) infection remains a major global health challenge, yet the mechanisms underlying strain-specific innate immune responses are poorly understood. Here, we show that distinct HSV-1 strains differentially activate the absent in melanoma 2 (AIM2) inflammasome. The HF strain robustly induces AIM2-dependent inflammasome activation, whereas the F and KOS strains elicit minimal responses despite comparable infection efficiency. We demonstrate that this difference is dr
Interactions between the peripheral nervous system and solid tumors influence cancer progression and treatment response. Defining the 3D tumor neural niche using spatial omics and AI technologies will identify new opportunities for targeted therapies to stop cancer progression.
Abstract Precision oncology has made significant advances in the last few years, mainly by targeting actionable mutations in cancer driver genes. However, the proportion of patients whose tumors can be targeted therapeutically remains limited. Recent studies have begun to explore the benefit of analyzing tumor transcriptomics data to guide patient treatment, raising the need for new approaches for systematically accomplishing that. Here we show that computationally derived genetic interactions c
Research Areas
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