Sang-Jung Ahn
Korea University · Medicine
About the Lab
Professor Sang-Jung Ahn's research lab specializes in gastrointestinal oncology and molecular pathology, with a focus on understanding the molecular mechanisms underlying gastric carcinogenesis, intratumoral heterogeneity, and tumor progression. The lab employs advanced pathological techniques such as immunohistochemistry, in situ hybridization, and endoscopic ultrasonography-guided biopsy to improve diagnostic accuracy and guide personalized treatment strategies. Key research directions include molecular subtyping of gastric cancer, early detection of malignant transformation, and characterization of subepithelial tumors, particularly schwannomas and gastrointestinal stromal tumors.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Gastric cancers have recently been classified into several types on the basis of molecular characterization, and the new taxonomy has shown to have clinical relevance. However, the technology required for thorough molecular classification is complicated and expensive, currently preventing widespread use. We aimed to reproduce the results of molecular classification using only simple techniques, that is, immunohistochemical analysis and in situ hybridization. We classified a cohort of 349 success
Intratumoral heterogeneity of HER2 expression is common in gastric cancers and pose a challenge for identifying patients who would benefit from anti-HER2 therapy. The aim of this study is to compare HER2 expression in biopsy and resection specimens of gastric carcinoma by immunohistochemistry (IHC) and to find the ideal number of biopsy tumor fragments that can accurately predict HER2 overexpression in the corresponding surgically resected specimen. The HER2 IHC results of 702 paired biopsy and
Several recurrent mutations and epigenetic changes have been identified in advanced gastric cancer, but the genetic alterations associated with early gastric carcinogenesis and malignant transformation remain unclear. We investigated the genomic and transcriptomic landscape of adenomas with low-grade dysplasia (LGD) and high-grade dysplasia (HGD), and intestinal-type early gastric cancer (EGC). The results were validated in an independent cohort that included EGCs directly adjacent to adenoma (E
As treatment decisions for patients with gastric subepithelial tumors (SETs) largely depend on the histopathologic diagnosis, noninvasive and effective tissue acquisition methods are definitely required for proper management of gastric SETs. Recently, a new endoscopic ultrasonography-guided fine needle biopsy (EUS-FNB) device with ProCore reverse bevel technology was developed. We aimed to elucidate the feasibility and diagnostic yield of EUS-FNB with this new core biopsy needle device in patien
BACKGROUND/AIMS: Gastric schwannomas are rare benign mesenchymal tumors that are difficult to differentiate from other mesenchymal tumors with malignant potential, such as gastrointestinal stromal tumors. This study aimed to evaluate the characteristic findings of gastric schwannomas via endoscopic ultrasonography (EUS). METHODS: We retrospectively reviewed the EUS findings of 27 gastric schwannoma cases that underwent surgical excision at Pusan National University Hospital during 2007 to 2014.
AIM: To predict the rate of lymph node (LN) metastasis in diffuse- and mixed-type early gastric cancers (EGC) for guidelines of the treatment. METHODS: We reviewed 550 cases of EGC with diffuse- and mixed-type histology. We investigated the clinicopathological factors and histopathological components that influence the probability of LN metastasis, including sex, age, site, gross type, presence of ulceration, tumour size, depth of invasion, perineural invasion, lymphovascular invasion, and LN me
Lymphovascular invasion (LVI) is one of the most important prognostic factors in gastric cancer as it indicates a higher likelihood of lymph node metastasis and poorer overall outcome for the patient. Despite its importance, the detection of LVI(+) in histopathology specimens of gastric cancer can be a challenging task for pathologists as invasion can be subtle and difficult to discern. Herein, we propose a deep learning-based LVI(+) detection method using H&E-stained whole-slide images. The Con
CONTEXT: -The diagnosis of gastric epithelial lesions is difficult in clinical practice, even with the recent developments and advances in endoscopic modalities, owing to the diverse morphologic features of the lesions, lack of standardized diagnostic criteria, and the high intraobserver and interobserver variabilities in the nonneoplastic (regenerative)-neoplastic spectrum. OBJECTIVE: -To provide an overview of the current concepts and unresolved issues surrounding the diagnosis of diseases in
BACKGROUND: Naked cuticle Drosophila 1 (NKD1) has been related to non-small cell lung cancer in that decreased NKD1 levels have been associated with both poor prognosis and increased invasive quality. METHODS: Forty cases of lung adenocarcinoma staged as Tis or T1a were selected. Cases were subclassified into adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and small adenocarcinoma (SAD). Immunohistochemical studies for NKD1 were performed. RESULTS: Forty samples comprised
BACKGROUND: The presence of squamous epithelium in the stomach is only occasionally encountered and is associated with prolonged mucosal injury. Squamous metaplasia in patients with cancer is relatively rare and only four cases have been reported in the stomach, all of which have been associated with squamous cell carcinomas. We present the first case of exuberant squamous metaplasia in a patient with gastric adenocarcinoma of the cardia. CASE PRESENTATION: A 56-year-old woman presented with epi
Perineural invasion (PNI) is a well-established independent prognostic factor for poor outcomes in colorectal cancer (CRC). However, PNI detection in CRC is a cumbersome and time-consuming process, with low inter-and intra-rater agreement. In this study, a deep-learning-based approach was proposed for detecting PNI using histopathological images. We collected 530 regions of histology from 77 whole-slide images (PNI, 100 regions; non-PNI, 430 regions) for training. The proposed hybrid model consi
In this study, we identified long non-coding RNAs (lncRNAs) associated with DNA methylation in lung adenocarcinoma (LUAD) using clinical and methylation/expression data from 184 qualified LUAD tissue samples and 21 normal lung-tissue samples from The Cancer Genome Atlas (TCGA). We identified 1865 differentially expressed genes that correlated negatively with the methylation profiles of normal lung tissues, never-smoker LUAD tissues and smoker LUAD tissues, while 1079 differentially expressed lnc
Research Areas
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