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Original Articles
cDNA Microarray Analysis of Differential Gene Expression in Gastric Cancer Cells Sensitive and Resistant to 5-Fluorouracil and Cisplatin
Myung-Ju Ahn, Young-Do Yoo, Ki-Hwan Lee, Joon-Ik Ahn, Dong-Hyun Yu, Hye-Sook Lee, Ho-Suck Oh, Jung-Hye Choi, Yong-Sung Lee
Cancer Res Treat. 2005;37(1):54-62.   Published online February 28, 2005
DOI: https://doi.org/10.4143/crt.2005.37.1.54
AbstractAbstract PDFPubReaderePub
Purpose

Gastric cancer is one of the most prevalent cancers worldwide. 5-fluorouracil (5-FU) and cisplatin are the most commonly used drugs for the treatment of gastric cancer. However, a significant number of tumors often fail to respond to chemotherapy.

Materials and Methods

To better understand the molecular mechanisms underlying drug resistance in gastric cancer the gene expression in gastric cancer cells, which were either sensitive or resistant to 5-FU and cisplatin, were examined using cDNA microarray analysis. To confirm the differential gene expression, as determined using the microarray, semiquantitative RT-PCR was performed on a subset of differentially expressed cDNAs.

Results

69 and 45 genes, which were either up-regulated (9 and 22 genes) or down-regulated (60 and 25 genes), were identified in 5-FU- and cisplatin-resistant cells, respectively. Several genes, such as adaptor-related protein complex 1 and baculoviral IAP repeat-containing 3, were up-regulated in both drug-resistant cell types. Several genes, such as the ras homolog gene family, tropomyosin, tumor rejection antigen, protein disulfide isomerase-related protein, melanocortin 1 receptor, defensin, cyclophilin B, dual specificity phosphatase 8 and hepatocyte nuclear factor 3, were down-regulated in both drugresistant cell types.

Conclusion

These findings show that cDNA microarray analysis can be used to obtain gene expression profiles that reflect the effect of anticancer drugs on gastric cancer cells. Such data may lead to the assigning of signature expression profiles of drug-resistant tumors, which may help predict responses to drugs and assist in the design of tailored therapeutic regimens to overcome drug resistance.

Citations

Citations to this article as recorded by  
  • Molecular classification and prediction in gastric cancer
    Xiandong Lin, Yongzhong Zhao, Won-min Song, Bin Zhang
    Computational and Structural Biotechnology Journal.2015; 13: 448.     CrossRef
  • Identification of Differentially-Expressed Genes in Intestinal Gastric Cancer by Microarray Analysis
    Shizhu Zang, Ruifang Guo, Rui Xing, Liang Zhang, Wenmei Li, Min Zhao, Jingyuan Fang, Fulian Hu, Bin Kang, Yonghong Ren, Yonglong Zhuang, Siqi Liu, Rong Wang, Xianghong Li, Yingyan Yu, Jing Cheng, Youyong Lu
    Genomics, Proteomics & Bioinformatics.2014; 12(6): 276.     CrossRef
  • Protein disulfide isomerase in redox cell signaling and homeostasis
    Francisco R.M. Laurindo, Luciana A. Pescatore, Denise de Castro Fernandes
    Free Radical Biology and Medicine.2012; 52(9): 1954.     CrossRef
  • 10,203 View
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  • 3 Crossref
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Comparison of As2O3 and As4O6 in the Detection of SiHa Cervical Cancer Cell Growth Inhibition Pathway
Yong Wook Kim, Su Mi Bae, Keun Ho Lee, Joon Mo Lee, Sung Eun Namkoong, Insu P. Lee, Chong Kook Kim, Jeong-Sun Seo, Jeong-Im Sin, Yong-Wan Kim, Woong Shick Ahn
Cancer Res Treat. 2004;36(4):255-262.   Published online August 31, 2004
DOI: https://doi.org/10.4143/crt.2004.36.4.255
Retraction in: Cancer Res Treat 2007;39(1):47
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Review Article
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.

Citations

Citations to this article as recorded by  
  • Screening and identification of gene expression in large cohorts of clinical tissue samples unveils the major involvement of EZH2 and SOX2 in lung cancer
    Niharika, Ankan Roy, Ratan Sadhukhan, Samir Kumar Patra
    Cancer Genetics.2025; 290-291: 16.     CrossRef
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    Ali Hassan Nawaz, Phatthawin Setthaya, Chungang Feng
    Animals.2024; 14(15): 2215.     CrossRef
  • Evaluating the use of a 22-pathogen TaqMan array card for rapid diagnosis of respiratory pathogens in intensive care
    Nick K. Jones, Andrew Conway Morris, Martin D. Curran, Surendra Parmar, Olajumoke Sule, David A. Enoch, Sani H. Aliyu, Hongyi Zhang, Hamid Jalal, Vilas Navapurkar, Michael E. Murphy
    Journal of Medical Microbiology .2020; 69(7): 971.     CrossRef
  • DHPLC Analysis of Adenomatous Polyposis Coli (APC) Mutations Using Ready-to-Use APC Plates: Simple Detection of Multiple Base Pair Deletion Mutations
    Il-Jin Kim, Kun Kim, Hio Chung Kang, Sang-Geun Jang, Jae-Gahb Park
    Genetic Testing.2008; 12(2): 295.     CrossRef
  • Microarray Gene Expression Profiling for Predicting Complete Response to Preoperative Chemoradiotherapy in Patients with Advanced Rectal Cancer
    Il-Jin Kim, Seok-Byung Lim, Hio Chung Kang, Hee Jin Chang, Sun-A Ahn, Hye-Won Park, Sang-Geun Jang, Jae-Hyun Park, Dae Yong Kim, Kyung Hae Jung, Hyo Seong Choi, Seung-Yong Jeong, Dae Kyung Sohn, Duck-Woo Kim, Jae-Gahb Park
    Diseases of the Colon & Rectum.2007; 50(9): 1342.     CrossRef
  • Molecular Changes From Dysplastic Nodule to Hepatocellular Carcinoma Through Gene Expression Profiling *
    Suk Woo Nam, Jik Young Park, Adaikalavan Ramasamy, Shirish Shevade, Amirul Islam, Philip M. Long, Cheol Keun Park, Soo Eun Park, Su Young Kim, Sug Hyung Lee, Won Sang Park, Nam Jin Yoo, Edison T. Liu, Lance D. Miller, Jung Young Lee
    Hepatology.2005; 42(4): 809.     CrossRef
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  • 6 Crossref
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Original Articles
The Differential Gene Expression Profiles between Sensitive and Resistant Breast Cancer Cells to Adriamycin by cDNA Microarray
Myung-Ju Ahn, Ki-Hwan Lee, Joon-Ik Ahn, Dong-Hyun Yu, Hye-Sook Lee, Jung-Hye Choi, Joung Soon Jang, Jong Min Bae, Yong-Sung Lee
Cancer Res Treat. 2004;36(1):43-49.   Published online February 29, 2004
DOI: https://doi.org/10.4143/crt.2004.36.1.43
AbstractAbstract PDFPubReaderePub
Purpose

Adriamycin® is one of the most commonly used drugs in the treatment of breast cancer. This study was performed to understand the molecular mechanisms of drug resistance in breast cancer cells.

Materials and Methods

We have analyzed the MCF-7 breast cell line and its adriamycin-resistant variants, MCF-7/ADR using human 10 K element cDNA microarrays.

Results

We defined 68 genes that were up-regulated (14 genes) or down-regulated (54 genes) in adriamycin resistant breast cancer cells. Several genes, such as G protein-coupled receptor kinase 5, phospholipase A2, guanylate cyclase 1, vimentin, matrix metalloproteinase 1 are up-regulated in drug resistant cells. Several genes, such as interferon, alpha-inducible protein 27, forkhead box M1, mitogen-activated protein kinase 6, regulator of mitotic spindle assembly 1 and tumor necrosis factor superfamily are down-regulated in adriamycin resistant cells. The altered expression of genes observed in microarray was verified by RT-PCR.

Conclusion

These findings show that cDNA microarray analysis can be used to obtain gene expression profiles reflecting the effect of anticancer drugs on breast cancer cells. Such data may lead to the assigning of signature expression profiles of drug-resistant tumors which may help predict responses to drugs and assist in the design of tailored therapeutic regimens to overcome drug resistance.

Citations

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  • Fabrication of Mn-TPP/RGO Tailored Glassy Carbon Electrode for Doxorubicin Sensing
    Rafia Zafar, Syeda Aqsa Batool Bukhari, Habib Nasir
    ACS Omega.2024; 9(24): 25694.     CrossRef
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    Journal of the Iranian Chemical Society.2024; 21(10): 2623.     CrossRef
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    William Z. Suo, Bruce Citron
    Journal of Alzheimer's Disease.2022; 85(4): 1399.     CrossRef
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    Daniele R. Nogueira-Librelotto, Laís E. Scheeren, Letícia B. Macedo, M. Pilar Vinardell, Clarice M.B. Rolim
    Colloids and Surfaces B: Biointerfaces.2020; 190: 110897.     CrossRef
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    S. Deepa, B.E. Kumara Swamy, K. Vasantakumar Pai
    Sensors International.2020; 1: 100033.     CrossRef
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    Hilal Taymaz-Nikerel, Muhammed Erkan Karabekmez, Serpil Eraslan, Betül Kırdar
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    William Z. Suo
    Advances in Alzheimer's Disease.2013; 02(04): 148.     CrossRef
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    Ling Yao, Yan Zhang, Keying Chen, Xiaofang Hu, Lisa X. Xu, Irina V. Lebedeva
    PLoS ONE.2011; 6(9): e24684.     CrossRef
  • cDNA Microarray Analysis of Differential Gene Expression in Gastric Cancer Cells Sensitive and Resistant to 5-Fluorouracil and Cisplatin
    Myung-Ju Ahn, Young-Do Yoo, Ki-Hwan Lee, Joon-Ik Ahn, Dong-Hyun Yu, Hye-Sook Lee, Ho-Suck Oh, Jung-Hye Choi, Yong-Sung Lee
    Cancer Research and Treatment.2005; 37(1): 54.     CrossRef
  • 10,233 View
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  • 10 Crossref
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Expression Profiling of the Cellular Processes in Uterine Leiomyomas: Omic Approaches and IGF-2 Association with Leiomyosarcomas
Su Mi Bae, Yong-Wan Kim, Joon Mo Lee, Sung Eun Namkoong, Chong Kook Kim, Woong Shick Ahn
Cancer Res Treat. 2004;36(1):31-42.   Published online February 29, 2004
DOI: https://doi.org/10.4143/crt.2004.36.1.31
AbstractAbstract PDFPubReaderePub
Purpose

This study utilized both cDNA microarray and 2D protein gel electrophoresis technology to investigate the multiple interactions of the genes and proteins involved in the pathophysiology of uterine leiomyomas. Also, Gene Ontology (GO) analysis was used to systematically characterize the global expression profiles, which were found to correlate with the leiomyosarcomas.

Materials and Methods

The uterine leiomyoma biopsies were obtained from patients in the Department of Obstetrics and Gynecology, The Catholic University of Korea. Differentially expressed transcriptome and proteome, in 6 paired leiomyoma and normal myometrium, were profiled. The total RNAs from the leiomyoma and normal myometrium were labeled with Cy5 and Cy3. All specimens were punch-biopsy-obtained, and frozen in liquid nitrogen.

Results

Screening of up to 17,000 genes identified 71 that were either up-regulated or down-regulated (21 and 50, respectively). The gene expression profiles were classified into 420 mutually dependent functional sets, resulting in 611 cellular processes, according to the gene ontology. Also, the protein analysis, using 2D gel electrophoresis, identified 33 proteins (17 up-regulated and 16 down-regulated) with more than 500 total spots, which were classified into 302 cellular processes. O f these functional profilings, transcriptomes and proteoms down-regulations were shown in the cell adhesion, cell m otility, organogenesis, enzyme regulator, structural molecule activity and responses to external stimulus functional activities, which are supposed to play important roles in the pathophysiology. In contrast, up-regulation was only shown in the nucleic acid binding activity. The CDKN2A, ADH1A, DCX, IGF2, CRABP2 and KIF5C were found to increase the reliability of this study, and correlate with the leiomyosarcomas.

Conclusion

Potentially significant pathogenetic cellular processes showed that down-regulated functional profiling has an important impact on the discovery of the pathogenic pathways in leiomyomas and leiomyosarcomas. GO analysis can also overcome the complexity of the expression profiles of cDNA microarrays and 2D protein analyses, via a cellular process level approach. Thereby, a valuable prognostic candidate gene, with real relevance to disease-specific pathogenesis, can be found at cellular process levels.

Citations

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    María Cristina Carbajo-García, Elena Juarez-Barber, Marina Segura-Benítez, Amparo Faus, Alexandra Trelis, Javier Monleón, Greta Carmona-Antoñanzas, Antonio Pellicer, James M. Flanagan, Hortensia Ferrero
    Reproductive Biology and Endocrinology.2023;[Epub]     CrossRef
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    Tsai-Der Chuang, Jianjun Gao, Derek Quintanilla, Hayden McSwiggin, Drake Boos, Wei Yan, Omid Khorram
    International Journal of Molecular Sciences.2023; 24(4): 3742.     CrossRef
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    Zorawar Singh
    Journal of Cancer Research and Practice.2018; 5(1): 1.     CrossRef
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    Liping Xia, Yan Liu, Yan Fu, Shengyi Dongye, Dewei Wang
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    BLENDI URA, FEDERICA SCRIMIN, FABRIZIO ZANCONATI, GIORGIO ARRIGONI, LORENZO MONASTA, ANDREA ROMANO, RUBINA BANCO, MARINA ZWEYER, DANIELA MILANI, GIUSEPPE RICCI
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    Hoguen Kim
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  • 11 Crossref
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cDNA Microarray Experiment: Design Issues in Early Stage and the Need of Normalization
Byung Soo Kim, Sunho Lee, Sun Young Rha, Hyun Cheol Chung
Cancer Res Treat. 2003;35(6):533-540.   Published online December 31, 2003
DOI: https://doi.org/10.4143/crt.2003.35.6.533
AbstractAbstract PDF
PURPOSE
The cDNA microarray has become a useful tool for observing the expression of thousands of genes simultaneously. However, obtaining good quality microarray data is not easy due to the inherent noise at various stages of the experiment. Therefore, it is essential to understand the source of the variation in the microarray experiment and its size as an initial step of the data analyses. MATERIALS AND METHODS: The total RNA extracted from HT-1080 fibrosarcoma and normal rat tissues were hybridized to the cDNA microarrays with 0.5 K human and 5 K rat genes, respectively. A homotypic reaction and dye swap experiments were used to identify the sources of the variation. RESULTS: The relative fluorescent intensities of the microarray, if unnormalized, have a large variation, particularly in the lower intensity region. The distribution of the log intensity ratios also exhibit some departure from a band around zero, which is the distribution pattern expected when the majority of genes in the microarray are not regulated. Normalization of the log ratios is usually required as a means of preprocessing the data. We claim that a within-print tip group, an intensity-dependent normalization through a loess fit adjustment will be useful for this purpose, particularly in the initial stages of the microarray experiment. CONCLUSION: For proper data analysis, an understanding the source of the variation and preprocessing of data with a suitable normalization method will be important. It is important to have an interactive cooperation between a researcher and a statistician from the early stages of the study design and to the final stages of data analysis.

Citations

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  • Whole genome analysis for liver metastasis gene signatures in colorectal cancer
    Dong Hyuk Ki, Hei‐Cheul Jeung, Chan Hee Park, Seung Hee Kang, Gui Youn Lee, Won Suk Lee, Nam Kyu Kim, Hyun Chul Chung, Sun Young Rha
    International Journal of Cancer.2007; 121(9): 2005.     CrossRef
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cDNA Microarray Analysis of Gene Expression Profiles Associated with Cervical Cancer
Joo Hee Yoon, Joon Mo Lee, Sung Eun Namkoong, Su Mi Bae, Yong Wan Kim, Sei Jun Han, Young Lae Cho, Gye Hyun Nam, Chong Kook Kim, Jeong Sun Seo, Woong Shick Ahn
Cancer Res Treat. 2003;35(5):451-459.   Published online October 31, 2003
DOI: https://doi.org/10.4143/crt.2003.35.5.451
AbstractAbstract PDF
PURPOSE
The molecular pathology of cervical cancers associated with human papillomavirus infection is presently unclear. In an effort to clarify this issue, the gene expression profiles and pathogenic cellular processes of cervical cancer lesions were investigated. MATERIALS AND METHODS: Cervical cancer biopsies were obtained from patients at the Department of Obstetrics and Gynecology, The Catholic University of Korea. The disease status was assigned according to the International Federation of Gynecology and Obstetrics. The tissue samples of 11 patients (invasive cancer stage Ib- IIIa) were investigated by a cDNA microarray of 4, 700 genes, hierarchical clustering and the Gene Ontology (GO). Total RNA from cervical cancer and non-lesional tissues were labeled with Cy5 and Cy3. The HaCaT human epithelial keratinocyte cell line was used as a negative control cell. The stages of invasive cancer were Ib to IIIb. All specimens were obtained by punch-biopsies and frozen in liquid nitrogen until required. RESULTS: 74 genes, showing more than a 2 fold difference in their expressions, were identified in at least 8 of the 11 patients. Of these genes, 33 were up-regulated and 41 were down-regulated. The gene expression profiles were classified into 345 mutually dependent function sets, resulting in 611 cellular processes according to their GO. The GO analysis showed that cervical carcinogenesis underwent complete down-regulation of cell death, protein biosynthesis and nucleic acid metabolism. The genes related to nucleic acid binding and structural molecule activity were also significantly down-regulated. In contrast, significant up-regulation was shown in the skeletal development, immune response and extracellular activity. CONCLUSION: These data are suggestive of potentially significant pathogenetic cellular processes, and showed that the down-regulated functional profiling has an important impact on the discovery of pathogenic pathways in cervical carcinogenesis. GO analysis can also overcome the complexity of the expression profiles of the cDNA microarray via a cellular process level approach. Thereby, a valuable prognostic candidate gene, with real relevance to disease-specific pathogenesis, can be found at the cellular process levels.

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  • The Differential Gene Expression Profiles between Sensitive and Resistant Breast Cancer Cells to Adriamycin by cDNA Microarray
    Myung-Ju Ahn, Ki-Hwan Lee, Joon-Ik Ahn, Dong-Hyun Yu, Hye-Sook Lee, Jung-Hye Choi, Joung Soon Jang, Jong Min Bae, Yong-Sung Lee
    Cancer Research and Treatment.2004; 36(1): 43.     CrossRef
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Gene Expression Profiling of Non-Small Cell Lung Cancer
Mee Sook Roh, Hyuk Chan Kwon, Jin Sook Jeong, Dae Cheol Kim, Choon Hee Son, Soo Keol Lee, Phil Jo Choi, Jae Ik Lee, Ki Nam Lee, Hyo Jin Kim, Jin Han Yoon, Tae Ho Hwang
Cancer Res Treat. 2003;35(2):154-160.   Published online April 30, 2003
DOI: https://doi.org/10.4143/crt.2003.35.2.154
AbstractAbstract PDF
PURPOSE
cDNA microarray provided a powerful alternative, with an unprecedented view scope, in monitoring gene expression levels, and led to the discovery of regulatory pathways involved in complicated biological processes. This study was performed to gain better understanding of the molecular mechanisms underlying the carcinogenesis and progression of lung cancer. MATERIALS AND METHODS: Using a cDNA microarray, representing 4, 600 cDNA clusters, we studied the expression profiles in 10 non-small cell lung cancer (NSCLC) samples and the adjacent noncancerous lung tissues form the same patients. The alterations in the levels of gene expression were confirmed by reverse-transcription PCR in 10 randomly selected genes.
RESULTS
Genes that were differently expressed in the cancerous and noncancerous tissues were identified. One hundred and nine genes (of which 68 were known) and 69 cDNAs (of which 32 were known) were up- and down-regulated in>70% of the NSCLC samples, respectively. In the cancerous tissues, the genes related to the cell cycle, metabolism, cell structure and signal transduction, were mostly up-regulated. Furthermore, we identified a few putative tumor suppressor genes that had previously been proposed by other workers. CONCLUSIONS: These results provide, not only a new molecular basis for understanding the biological properties of NSCLC, but also useful resources for the future development of diagnostic markers and therapeutic targets for NSCLC.

Citations

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  • Expression of double‐stranded RNA‐activated protein kinase in small‐size peripheral adenocarcinoma of the lung
    Mee Sook Roh, Ju Young Kwak, Su Jin Kim, Hyun Wook Lee, Hyuk Chan Kwon, Tae Ho Hwang, Phil Jo Choi, Young Seoub Hong
    Pathology International.2005; 55(11): 688.     CrossRef
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