Chang Hee Kim

Publications (5)19.48 Total impact

• Source

  Available from: Jeffrey E Green

  Article: miRNA signature associated with outcome of gastric cancer patients following chemotherapy.

  Chang Hee Kim, Hark K Kim, R Luke Rettig, Joseph Kim, Eunbyul T Lee, Olga Aprelikova, Il J Choi, David J Munroe, Jeffrey E Green
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  ABSTRACT: Identification of patients who likely will or will not benefit from cytotoxic chemotherapy through the use of biomarkers could greatly improve clinical management by better defining appropriate treatment options for patients. microRNAs may be potentially useful biomarkers that help guide individualized therapy for cancer because microRNA expression is dysregulated in cancer. In order to identify miRNA signatures for gastric cancer and for predicting clinical resistance to cisplatin/fluorouracil (CF) chemotherapy, a comprehensive miRNA microarray analysis was performed using endoscopic biopsy samples. Biopsy samples were collected prior to chemotherapy from 90 gastric cancer patients treated with CF and from 34 healthy volunteers. At the time of disease progression, post-treatment samples were additionally collected from 8 clinical responders. miRNA expression was determined using a custom-designed Agilent microarray. In order to identify a miRNA signature for chemotherapy resistance, we correlated miRNA expression levels with the time to progression (TTP) of disease after CF therapy. A miRNA signature distinguishing gastric cancer from normal stomach epithelium was identified. 30 miRNAs were significantly inversely correlated with TTP whereas 28 miRNAs were significantly positively correlated with TTP of 82 cancer patients (P<0.05). Prominent among the upregulated miRNAs associated with chemosensitivity were miRNAs known to regulate apoptosis, including let-7g, miR-342, miR-16, miR-181, miR-1, and miR-34. When this 58-miRNA predictor was applied to a separate set of pre- and post-treatment tumor samples from the 8 clinical responders, all of the 8 pre-treatment samples were correctly predicted as low-risk, whereas samples from the post-treatment tumors that developed chemoresistance were predicted to be in the high-risk category by the 58 miRNA signature, suggesting that selection for the expression of these miRNAs occurred as chemoresistance arose. We have identified 1) a miRNA expression signature that distinguishes gastric cancer from normal stomach epithelium from healthy volunteers, and 2) a chemoreresistance miRNA expression signature that is correlated with TTP after CF therapy. The chemoresistance miRNA expression signature includes several miRNAs previously shown to regulate apoptosis in vitro, and warrants further validation.
  BMC Medical Genomics 11/2011; 4:79. · 3.69 Impact Factor
• Article: Integrated miRNA and mRNA expression profiling of mouse mammary tumor models identifies miRNA signatures associated with mammary tumor lineage.

  Min Zhu, Ming Yi, Chang Hee Kim, Chuxia Deng, Yi Li, Daniel Medina, Robert M Stephens, Jeffrey E Green
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  ABSTRACT: MicroRNAs (miRNAs) are small, non-coding, endogenous RNAs involved in regulating gene expression and protein translation. miRNA expression profiling of human breast cancers has identified miRNAs related to the clinical diversity of the disease and potentially provides novel diagnostic and prognostic tools for breast cancer therapy. In order to further understand the associations between oncogenic drivers and miRNA expression in sub-types of breast cancer, we performed miRNA expression profiling on mammary tumors from eight well-characterized genetically engineered mouse (GEM) models of human breast cancer, including MMTV-H-Ras, -Her2/neu, -c-Myc, -PymT, -Wnt1 and C3(1)/SV40 T/t-antigen transgenic mice, BRCA1(fl/fl);p53(+/-);MMTV-cre knock-out mice and the p53(fl/fl);MMTV-cre transplant model. miRNA expression patterns classified mouse mammary tumors according to luminal or basal tumor subtypes. Many miRNAs found in luminal tumors are expressed during normal mammary development. miR-135b, miR-505 and miR-155 are expressed in both basal human and mouse mammary tumors and many basal-associated miRNAs have not been previously characterized. miRNAs associated with the initiating oncogenic event driving tumorigenesis were also identified. miR-10b, -148a, -150, -199a and -486 were only expressed in normal mammary epithelium and not tumors, suggesting that they may have tumor suppressor activities. Integrated miRNA and mRNA gene expression analyses greatly improved the identification of miRNA targets from potential targets identified in silico. This is the first large-scale miRNA gene expression study across a variety of relevant GEM models of human breast cancer demonstrating that miRNA expression is highly associated with mammary tumor lineage, differentiation and oncogenic pathways.
  Genome biology 08/2011; 12(8):R77. · 6.63 Impact Factor
• Source

  Available from: Jeffrey E Green

  Article: Distinctions in gastric cancer gene expression signatures derived from laser capture microdissection versus histologic macrodissection.

  Hark Kyun Kim, Joseph Kim, Susie Korolevich, Il Ju Choi, Chang Hee Kim, David J Munroe, Jeffrey E Green
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  ABSTRACT: Gastric cancer samples obtained by histologic macrodissection contain a relatively high stromal content that may significantly influence gene expression profiles. Differences between the gene expression signature derived from macrodissected gastric cancer samples and the signature obtained from isolated gastric cancer epithelial cells from the same biopsies using laser-capture microdissection (LCM) were evaluated for their potential experimental biases. RNA was isolated from frozen tissue samples of gastric cancer biopsies from 20 patients using both histologic macrodissection and LCM techniques. RNA from LCM was subject to an additional round of T7 RNA amplification. Expression profiling was performed using Affymetrix HG-U133A arrays. Genes identified in the expression signatures from each tissue processing method were compared to the set of genes contained within chromosomal regions found to harbor copy number aberrations in the tumor samples by array CGH and to proteins previously identified as being overexpressed in gastric cancer. Genes shown to have increased copy number in gastric cancer were also found to be overexpressed in samples obtained by macrodissection (LS P value < 10(-5)), but not in array data generated using microdissection. A set of 58 previously identified genes overexpressed in gastric cancer was also enriched in the gene signature identified by macrodissection (LS P < 10(-5)), but not in the signature identified by microdissection (LS P = 0.013). In contrast, 66 genes previously reported to be underexpressed in gastric cancer were enriched in the gene signature identified by microdissection (LS P < 10-5), but not in the signature identified by macrodissection (LS P = 0.89). The tumor sampling technique biases the microarray results. LCM may be a more sensitive collection and processing method for the identification of potential tumor suppressor gene candidates in gastric cancer using expression profiling.
  BMC Medical Genomics 06/2011; 4:48. · 3.69 Impact Factor
• Article: Identifying functional miRNA-mRNA regulatory modules with correspondence latent dirichlet allocation.

  Bing Liu, Lin Liu, Anna Tsykin, Gregory J Goodall, Jeffrey E Green, Min Zhu, Chang Hee Kim, Jiuyong Li
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  ABSTRACT: MOTIVATION: MicroRNAs (miRNAs) are small non-coding RNAs that cause mRNA degradation and translational inhibition. They are important regulators of development and cellular homeostasis through their control of diverse processes. Recently, great efforts have been made to elucidate their regulatory mechanism, but the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With more and more matched expression profiles of miRNAs and mRNAs having been made available, it is of great interest to utilize both expression profiles to discover the functional regulatory networks of miRNAs and their target mRNAs for potential biological processes that they may participate in. RESULTS: We present a probabilistic graphical model to discover functional miRNA regulatory modules at potential biological levels by integrating heterogeneous datasets, including expression profiles of miRNAs and mRNAs, with or without the prior target binding information. We applied this model to a mouse mammary dataset. It effectively captured several biological process specific modules involving miRNAs and their target mRNAs. Furthermore, without using prior target binding information, the identified miRNAs and mRNAs in each module show a large proportion of overlap with predicted miRNA target relationships, suggesting that expression profiles are crucial for both target identification and discovery of regulatory modules.
  Bioinformatics 10/2010; 26(24):3105-11. · 5.47 Impact Factor
• Article: Identifying functional miRNA-mRNA regulatory modules with correspondence latent dirichlet allocation.

  Bing Liu, Lin Liu, Anna Tsykin, Gregory J. Goodall, Jeffrey E. Green, Min Zhu, Chang-Hee Kim, Jiuyong Li
  Bioinformatics. 01/2010; 26:3105-3111.