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Review Articles
Applicability of Spatial Technology in Cancer Research
Sangjeong Ahn, Hye Seung Lee
Cancer Res Treat. 2024;56(2):343-356.   Published online January 30, 2024
DOI: https://doi.org/10.4143/crt.2023.1302
AbstractAbstract PDFPubReaderePub
This review explores spatial mapping technologies in cancer research, highlighting their crucial role in understanding the complexities of the tumor microenvironment (TME). The TME, which is an intricate ecosystem of diverse cell types, has a significant impact on tumor dynamics and treatment outcomes. This review closely examines cutting-edge spatial mapping technologies, categorizing them into capture-, imaging-, and antibody-based approaches. Each technology was scrutinized for its advantages and disadvantages, factoring in aspects such as spatial profiling area, multiplexing capabilities, and resolution. Additionally, we draw attention to the nuanced choices researchers face, with capture-based methods lending themselves to hypothesis generation, and imaging/antibody-based methods that fit neatly into hypothesis testing. Looking ahead, we anticipate a scenario in which multi-omics data are seamlessly integrated, artificial intelligence enhances data analysis, and spatiotemporal profiling opens up new dimensions.

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  • Navigating the landscape of plant proteomics
    Tian Sang, Zhen Zhang, Guting Liu, Pengcheng Wang
    Journal of Integrative Plant Biology.2025;[Epub]     CrossRef
  • Distinctive Phenotypic and Microenvironmental Characteristics of Neuroendocrine Carcinoma and Adenocarcinoma Components in Gastric Mixed Adenoneuroendocrine Carcinoma
    Yoonjin Kwak, Soo Kyung Nam, Yujun Park, Yun-Suhk Suh, Sang-Hoon Ahn, Seong-Ho Kong, Do Joong Park, Hyuk-Joon Lee, Hyung-Ho Kim, Han-Kwang Yang, Hye Seung Lee
    Modern Pathology.2024; 37(10): 100568.     CrossRef
  • Effector Function Characteristics of Exhausted CD8+ T-Cell in Microsatellite Stable and Unstable Gastric Cancer
    Dong-Seok Han, Yoonjin Kwak, Seungho Lee, Soo Kyung Nam, Seong-Ho Kong, Do Joong Park, Hyuk-Joon Lee, Nak-Jung Kwon, Hye Seung Lee, Han-Kwang Yang
    Cancer Research and Treatment.2024; 56(4): 1146.     CrossRef
  • Prognostic significance of CD8 and TCF1 double positive T cell subset in microsatellite unstable gastric cancer
    Juhyeong Park, Soo Kyung Nam, Yoonjin Kwak, Hyeon Jeong Oh, Seong-Ho Kong, Do Joong Park, Hyuk-Joon Lee, Han-Kwang Yang, Hye Seung Lee
    Scientific Reports.2024;[Epub]     CrossRef
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Biology of SNU Cell Lines
Ja-Lok Ku, Jae-Gahb Park
Cancer Res Treat. 2005;37(1):1-19.   Published online February 28, 2005
DOI: https://doi.org/10.4143/crt.2005.37.1.1
AbstractAbstract PDFPubReaderePub

SNU (Seoul National University) cell lines have been established from Korean cancer patients since 1982. Of these 109 cell lines have been characterized and reported, i.e., 17 colorectal carcinoma, 12 hepatocellular carcinoma, 11 gastric carcinoma, 12 uterine cervical carcinoma, 17 B-lymphoblastoid cell lines derived from cancer patients, 5 ovarian carcinoma, 3 malignant mixed Mllerian tumor, 6 laryngeal squamous cell carcinoma, 7 renal cell carcinoma, 9 brain tumor, 6 biliary tract, and 4 pancreatic carcinoma cell lines. These SNU cell lines have been distributed to biomedical researchers domestic and worldwide through the KCLB (Korean Cell Line Bank), and have proven to be of value in various scientific research fields. The characteristics of these cell lines have been reported in over 180 international journals by our laboratory and by many other researchers from 1987. In this paper, the cellular and molecular characteristics of SNU human cancer cell lines are summarized according to their genetic and epigenetic alterations and functional analysis.

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Citations to this article as recorded by  
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    Molecular Therapy - Oncolytics.2023; 31: 100734.     CrossRef
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    Gut.2022; 71(7): 1277.     CrossRef
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    Phytotherapy Research.2022; 36(6): 2449.     CrossRef
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    Cellular and Molecular Life Sciences.2022;[Epub]     CrossRef
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    Sun-Jin Boo, Mei Jing Piao, Kyoung Ah Kang, Ao Xuan Zhen, Pincha Devage Sameera Madushan Fernando, Herath Mudiyanselage Udari Lakmini Herath, Seung Joo Lee, Seung Eun Song, Jin Won Hyun
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    Cancer Immunology Research.2021; 9(10): 1158.     CrossRef
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  • Reduced Autophagy in 5-Fluorouracil Resistant Colon Cancer Cells
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  • AZD6738, A Novel Oral Inhibitor of ATR, Induces Synthetic Lethality with ATM Deficiency in Gastric Cancer Cells
    Ahrum Min, Seock-Ah Im, Hyemin Jang, Seongyeong Kim, Miso Lee, Debora Keunyoung Kim, Yaewon Yang, Hee-Jun Kim, Kyung-Hun Lee, Jin Won Kim, Tae-Yong Kim, Do-Youn Oh, Jeff Brown, Alan Lau, Mark J. O'Connor, Yung-Jue Bang
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  • Epithelial–mesenchymal transition confers resistance to selective FGFR inhibitors in SNU-16 gastric cancer cells
    Paulina Grygielewicz, Barbara Dymek, Anna Bujak, Pawel Gunerka, Aleksandra Stanczak, Monika Lamparska-Przybysz, Maciej Wieczorek, Karolina Dzwonek, Daria Zdzalik
    Gastric Cancer.2016; 19(1): 53.     CrossRef
  • Reduced cohesin destabilizes high-level gene amplification by disrupting pre-replication complex bindings in human cancers with chromosomal instability
    Jiyeon Yun, Sang-Hyun Song, Jee-Youn Kang, Jinah Park, Hwang-Phill Kim, Sae-Won Han, Tae-You Kim
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  • Aberrant Epigenetic Modifications of LPHN2 Function as a Potential Cisplatin-Specific Biomarker for Human Gastrointestinal Cancer
    Mi-Seong Jeon, Sang-Hyun Song, Jiyeon Yun, Jee-Youn Kang, Hwang-Phill Kim, Sae-Won Han, Tae-You Kim
    Cancer Research and Treatment.2016; 48(2): 676.     CrossRef
  • Carboxyl-Terminal Modulator Protein Positively Acts as an Oncogenic Driver in Head and Neck Squamous Cell Carcinoma via Regulating Akt phosphorylation
    Jae Won Chang, Seung-Nam Jung, Ju-Hee Kim, Geun-Ae Shim, Hee Sung Park, Lihua Liu, Jin Man Kim, Jongsun Park, Bon Seok Koo
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  • C-terminal truncated hepatitis B virus X protein promotes hepatocellular carcinogenesis through induction of cancer and stem cell-like properties
    Kai-Yu Ng, Stella Chai, Man Tong, Xin-Yuan Guan, Chi-Ho Lin, Yick-Pang Ching, Dan Xie, Alfred Sze-Lok Cheng, Stephanie Ma
    Oncotarget.2016; 7(17): 24005.     CrossRef
  • Bone morphogenetic protein-9 is a potent growth inhibitor of hepatocellular carcinoma and reduces the liver cancer stem cells population
    Jae Woo Jung, So-Mi Yoon, Subin Kim, Yun-Hui Jeon, Byung-Hak Yoon, Su-Geun Yang, Min Kyoung Kim, Senyon Choe, Mario Meng-Chiang Kuo
    Oncotarget.2016; 7(45): 73754.     CrossRef
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    Paola Francica, Lluís Nisa, Daniel M. Aebersold, Rupert Langer, Friedhelm Bladt, Andree Blaukat, Deborah Stroka, María Rodríguez Martínez, Yitzhak Zimmer, Michaela Medová
    Clinical Cancer Research.2016; 22(21): 5322.     CrossRef
  • Potential Role of CD133 Expression in the Susceptibility of Human Liver Cancer Stem-Like Cells to TRAIL
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    Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics.2016; 24(6): 495.     CrossRef
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    Eun Kyung Lee, Kyung‐A. Song, Ji‐Hye Chae, Kyoung‐Mee Kim, Seok‐Hyung Kim, Myung‐Soo Kang
    International Journal of Cancer.2015; 136(10): 2284.     CrossRef
  • Identification of Long-Range Epigenetic Silencing on Chromosome 15q25 and Its Clinical Implication in Gastric Cancer
    Jee-Youn Kang, Sang-Hyun Song, Jiyeon Yun, Mi-Seong Jeon, Yongjun Cha, Si-Hyun Lee, Hwang-Phill Kim, Eun-Goo Jeong, Sae-Won Han, Nam-Yun Cho, Myeong Cherl Kook, Gyeong Hoon Kang, Tae-You Kim
    The American Journal of Pathology.2015; 185(3): 666.     CrossRef
  • Targeting HIF1α Peri-operatively Increased Post-surgery Survival in a Tongue Cancer Animal Model
    Soon-Hyun Ahn, Joo Yeon Choi, Dong Wook Kim, Doh Young Lee, Eun-Hui Jeon, Woo-Jin Jeong, Jin Ho Paik
    Annals of Surgical Oncology.2015; 22(9): 3041.     CrossRef
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    International Journal of Cancer.2015; 137(7): 1598.     CrossRef
  • Evaluation of Lapatinib Powder-Entrapped Biodegradable Polymeric Microstructures Fabricated by X-Ray Lithography for a Targeted and Sustained Drug Delivery System
    Eun-Goo Jeong, Hyung Yoo, Byeonghwa Song, Hwang-Phill Kim, Sae-Won Han, Tae-You Kim, Dong-Il Cho
    Materials.2015; 8(2): 519.     CrossRef
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    Namgyu Lee, Jung-Hee Kwon, Young Bae Kim, Seong-Hoon Kim, Sung Jin Park, Weiguang Xu, Hoe-Yune Jung, Kyong-Tai Kim, Hee Jung Wang, Kwan Yong Choi
    Oncotarget.2015; 6(30): 30130.     CrossRef
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    Oncotarget.2015; 6(10): 8323.     CrossRef
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    Fung-Yu Huang, Danny Ka-Ho Wong, Wai-Kay Seto, Ching-Lung Lai, Man-Fung Yuen
    Oncotarget.2015; 6(33): 34941.     CrossRef
  • Novel fusion transcripts in human gastric cancer revealed by transcriptome analysis
    H-P Kim, G-A Cho, S-W Han, J-Y Shin, E-G Jeong, S-H Song, W-C Lee, K-H Lee, D Bang, J-S Seo, J-Il Kim, T-Y Kim
    Oncogene.2014; 33(47): 5434.     CrossRef
  • p21-Activated Kinase 4 (PAK4) as a Predictive Marker of Gemcitabine Sensitivity in Pancreatic Cancer Cell Lines
    Sung-Ung Moon, Jin Won Kim, Ji Hea Sung, Mi Hyun Kang, Se-Hyun Kim, Hyun Chang, Jeong-Ok Lee, Yu Jung Kim, Keun-Wook Lee, Jee Hyun Kim, Soo-Mee Bang, Jong Seok Lee
    Cancer Research and Treatment.2014; 47(3): 501.     CrossRef
  • Decreased Mitochondrial OGG1 Expression is Linked to Mitochondrial Defects and Delayed Hepatoma Cell Growth
    Young-Kyoung Lee, Hwang-Guem Youn, Hee-Jung Wang, Gyesoon Yoon
    Molecules and Cells.2013; 35(6): 489.     CrossRef
  • Anti-cancer effect of a quinoxaline derivative GK13 as a transglutaminase 2 inhibitor
    Seon-Hyeong Lee, Nayeon Kim, Se-Jin Kim, Jaewhan Song, Young-Dae Gong, Soo-Youl Kim
    Journal of Cancer Research and Clinical Oncology.2013; 139(8): 1279.     CrossRef
  • Large-scale profiling and identification of potential regulatory mechanisms for allelic gene expression in colorectal cancer cells
    Robin Dong-Woo Lee, Min-Young Song, Jong-Keuk Lee
    Gene.2013; 512(1): 16.     CrossRef
  • Claudin-1 induces epithelial–mesenchymal transition through activation of the c-Abl-ERK signaling pathway in human liver cells
    Y Suh, C-H Yoon, R-K Kim, E-J Lim, Y S Oh, S-G Hwang, S An, G Yoon, M C Gye, J-M Yi, M-J Kim, S-J Lee
    Oncogene.2013; 32(41): 4873.     CrossRef
  • p53 restoration can overcome cisplatin resistance through inhibition of Akt as well as induction of Bax
    CHAE WON KIM, JING NAN LU, SE-IL GO, JI HYUN JUNG, SANG MI YI, JAE-HOON JEONG, YOUNG-SOOL HAH, MYUNG SHIN HAN, JEONG WOO PARK, WON SUP LEE, YOUNG JOO MIN
    International Journal of Oncology.2013; 43(5): 1495.     CrossRef
  • RAD51C-Deficient Cancer Cells Are Highly Sensitive to the PARP Inhibitor Olaparib
    Ahrum Min, Seock-Ah Im, Young-Kwang Yoon, Sang-Hyun Song, Hyun-Jin Nam, Hyung-Seok Hur, Hwang-Phill Kim, Kyung-Hun Lee, Sae-Won Han, Do-Youn Oh, Tae-You Kim, Mark J. O'Connor, Woo-Ho Kim, Yung-Jue Bang
    Molecular Cancer Therapeutics.2013; 12(6): 865.     CrossRef
  • Antitumor Activity of Saracatinib (AZD0530), a c-Src/Abl Kinase Inhibitor, Alone or in Combination with Chemotherapeutic Agents in Gastric Cancer
    Hyun-Jin Nam, Seock-Ah Im, Do-Youn Oh, Paul Elvin, Hwang-Phill Kim, Young-Kwang Yoon, Ahrum Min, Sang-Hyun Song, Sae-Won Han, Tae-You Kim, Yung-Jue Bang
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Microarray Applications in Cancer Research
Il-Jin Kim, Hio Chung Kang, Jae-Gahb Park
Cancer Res Treat. 2004;36(4):207-213.   Published online August 31, 2004
DOI: https://doi.org/10.4143/crt.2004.36.4.207
AbstractAbstract PDFPubReaderePub

DNA microarray technology permits simultaneous analysis of thousands of DNA sequences for genomic research and diagnostics applications. Microarray technology represents the most recent and exciting advance in the application of hybridization-based technology for biological sciences analysis. This review focuses on the classification (oligonucleotide vs. cDNA) and application (mutation-genotyping vs. gene expression) of microarrays. Oligonucleotide microarrays can be used both in mutation-genotyping and gene expression analysis, while cDNA microarrays can only be used in gene expression analysis. We review microarray mutation analysis, including examining the use of three oligonucleotide microarrays developed in our laboratory to determine mutations in RET, β-catenin and K-ras genes. We also discuss the use of the Affymetrix GeneChip in mutation analysis. We review microarray gene expression analysis, including the classifying of such studies into four categories: class comparison, class prediction, class discovery and identification of biomarkers.

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