Kwon Joong Na
Seoul National University · Medicine
About the Lab
Professor Kwon Joong Na's research lab specializes in cancer systems biology, focusing on the interplay between tumor metabolism, immune microenvironment, and clinical outcomes. The lab integrates multi-omics data—including transcriptomics, PET imaging, and single-cell RNA sequencing—to decode the molecular mechanisms underlying immune evasion and therapeutic resistance in solid tumors. Key research directions include constructing gene coexpression networks to identify prognostic biomarkers and developing machine learning-based models for risk stratification in lung and thyroid cancers. The lab also investigates metabolic reprogramming in the tumor microenvironment to inform immunotherapy and precision oncology strategies.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Although papillary thyroid cancer (PTC) is curable with excellent survival rate, patients with dedifferentiated PTC suffer the recurrence or death. As cancer immune escape plays a critical role in cancer progression, we aimed to investigate the relationship between differentiation and immune landscape of PTC and its implications for immunotherapy. Using The Cancer Genome Atlas data, we estimated the immune cell enrichment scores and overall immune infiltration, ImmuneScore, to characterize the i
The metabolic properties of tumor microenvironment (TME) are dynamically dysregulated to achieve immune escape and promote cancer cell survival. However, <i>in vivo</i> properties of glucose metabolism in cancer and immune cells are poorly understood and their clinical application to development of a biomarker reflecting immune functionality is still lacking. <b>Methods:</b> We analyzed RNA-seq and fluorodeoxyglucose (FDG) positron emission tomography profiles of 63 lung squamous cell carcinoma
The importance of <sup>18</sup>F-FDG PET in imaging head and neck squamous cell carcinoma (HNSCC) has grown in recent decades. Because PET has prognostic values, and provides functional and molecular information in HNSCC, the genetic and biologic backgrounds associated with PET parameters are of great interest. Here, as a systems biology approach, we aimed to investigate gene networks associated with tumor metabolism and their biologic function using RNA sequence and <sup>18</sup>F-FDG PET data.
Introduction: Tumor immune microenvironment (TIME) promotes immune escape, allowing for tumor progression and metastasis. In spite of the current evidence of the complicated role of immune cells in promoting or suppressing cancer progression, the heterogeneity of TIME according to the tumor site has been scarcely investigated. Here, we analyzed transcriptomic profiles of metastatic breast cancer to understand how TIME varies according to tumor sites. Methods: Two gene expression datasets from me
BACKGROUND: Robot-assisted minimally invasive esophagectomy (RAMIE) reduces postoperative respiratory complications and enables meticulous mediastinal lymphadenectomy. However, whether adding a robotic abdominal procedure to a robotic thoracic procedure can result in better outcomes is unclear. We examined outcomes after total-RAMIE (T-RAMIE) and compared them with the outcomes after hybrid-RAMIE (H-RAMIE). METHODS: Total of 227 patients who underwent robotic esophagectomy for esophageal cancer
Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma based on gene coexpression network. Using multiple microarray, gene coexpression network analysis was performed to identify survival-related networks. A deep learning based risk stratification model was constructed with representative genes of these n
OBJECTIVES: Thymectomy is the treatment of choice for thymomatous myasthenia gravis (MG) for both oncological and neurological aspects. However, only a few studies comprising small numbers of patients have investigated post-thymectomy neurological outcomes. We examined post-thymectomy long-term neurological outcomes and predictors of thymomatous MG using a multi-institutional database. METHODS: In total, 193 patients (47.3 ± 12.0 years; male:female = 90:103) with surgically resected thymomatous
Robotic thymectomy is widely accepted as a valuable treatment option for surgical resection of thymic epithelial tumor as minimally invasive surgery has shown better early clinical outcomes than open surgery. Technical advances in robotic surgery have expanded the indications for robotic thymectomy, and the technique can be used to perform complete resection of advanced thymic epithelial tumor requiring concomitant resection of adjacent structures. To ensure complete resection, a multi-disciplin
OBJECTIVE: To compare nutritional and postoperative outcomes between early oral feeding and late oral feeding with jejunostomy feeding support after esophagectomy. BACKGROUND: Esophagectomy is associated with substantial body weight loss and malnutrition, impacting the prognosis of esophageal cancer patients. Despite many studies on postesophagectomy nutritional support, optimal strategies remain elusive. This study investigates the impact of jejunostomy feeding with late oral feeding compared t
Patients with non-small cell lung cancer (NSCLC) at stage IV have typically been considered incurable. Nonetheless, there is growing evidence that certain patient groups with fewer metastases, or so-called oligometastatic disease, which may have a more indolent biological nature than widespread metastatic diseases, may survive longer if definitive local treatment is administered to all metastatic sites. According to several retrospective investigations, this subgroup had a better prognosis than
= .02), with similar specificity. Conclusion The CT-based DL model identified patients at high risk among those with clinical stage IA NSCLC who underwent segmentectomy, outperforming the JCOG criteria. © RSNA, 2024
Abstract The Coronavirus disease 2019 (COVID-19) has been spreading worldwide with rapidly increased number of deaths. Hyperinflammation mediated by dysregulated monocyte/macrophage function is considered to be the key factor that triggers severe illness in COVID-19. However, no specific targeting molecule has been identified for detecting or treating hyperinflammation related to dysregulated macrophages in severe COVID-19. In this study, previously published single-cell RNA-sequencing data of b
BACKGROUND: A close metabolic interaction between cancer and immune cells in the tumor microenvironment (TME) plays a pivotal role in cancer immunity. Herein, we have comprehensively investigated the glucose metabolic features of the TME at the single-cell level to discover feasible metabolic targets for the tumor immune status. METHODS: We examined expression levels of glucose transporters (GLUTs) in various cancer types using The Cancer Genome Atlas (TCGA) data and single-cell RNA-seq (scRNA-s
Research Areas
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