Dataset Information

Differential Expression of Gene Profiles in MRGX-treated Lung Cancer.

ABSTRACT:

Objectives

Modified regular ginseng extract (MRGX) has stronger anti-cancer activity-possessing gensenoside profiles.

Methods

To investigate changes in gene expression in the MRGX-treated lung cancer cells (A549), we examined genomic data with cDNA microarray results. After completing the gene-ontology-based analysis, we grouped the genes into up-and down-regulated profiles and into ontology-related regulated genes and proteins through their interaction network.

Results

One hundred nine proteins that were up- and down-regulated by MRGX were queried by using IPA. IL8, MMP7 and PLAUR and were found to play a major role in the anti-cancer activity in MRGX-treated lung cancer cells. These results were validated using a Western blot analysis and a semi-quantitative reverse transcription-polymerase chain reaction (RT-PCR) analysis.

Conclusions

Most MRGX-responsive genes are up-regulated transiently in A549 cells, but down-regulated in a sustained manner in lung cancer cells.

SUBMITTER: Kwon YK

PROVIDER: S-EPMC4331971 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Publications

Differential Expression of Gene Profiles in MRGX-treated Lung Cancer.

Kwon Yong-Kyun YK Lee Seung-Yeul SY Kang Hwan-Soo HS Sung Jung-Suk JS Cho Chong-Kwan CK Yoo Hwa-Seung HS Shin Seungjin S Choi Jong-Soon JS Lee Yeon-Weol YW Jang Ik-Soon IS

Journal of pharmacopuncture 20130901 3

<h4>Objectives</h4>Modified regular ginseng extract (MRGX) has stronger anti-cancer activity-possessing gensenoside profiles.<h4>Methods</h4>To investigate changes in gene expression in the MRGX-treated lung cancer cells (A549), we examined genomic data with cDNA microarray results. After completing the gene-ontology-based analysis, we grouped the genes into up-and down-regulated profiles and into ontology-related regulated genes and proteins through their interaction network.<h4>Results</h4>One ...[more]

PMID: 25780673

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Project description:BackgroundTherapies targeting the epidermal growth factor receptor (EGFR) result in a painful rash, the most common and debilitating toxicity among patients with non-small cell lung cancer (NSCLC) who take EGFR tyrosine kinase inhibitor (TKI) therapy; however, predicting the development and the severity of the rash is difficult.ObjectiveThe aim of this study was to examine how erlotinib-an EGFR TKI that NSCLC patients take to stop or slow tumor growth-altered the transcriptome of dermal fibroblasts.MethodsDermal fibroblasts (ATCC PCS-201-012) were seeded in cell culture flasks, grown under standard conditions, and transferred to cell culture dishes. Cells were treated once daily for 3 days with erlotinib 100 nM (n = 5), erlotinib 1 μM (n = 5), vehicle 1 μM (dimethyl sulfoxide) (n = 5), or no treatment (n = 5). Total RNA was extracted using a standard TRIzol method and hybridized using Affymetrix GeneChip Human Genome U133 Plus 2.0 arrays. Raw intensities generated from the arrays were normalized using a Robust Multiarray Average method and analyzed using analysis of variance in Limma R software. Differentially expressed genes were analyzed using Ingenuity Pathway Analysis to identify canonical or noncanonical signaling pathways enriched in this dataset.ResultsWe selected genes for investigation based on their potential role in wound healing (AQP3), rash development (CCL2), fibroblast activation (PALLD), cancer and cancer progression (GDF-15, SLC7A11, MMP12, and DIRAS3), and cell cycle control (CDC6). We were able to validate four of these genes by both Western blot analysis and quantitative polymerase chain reaction (MMP12, CCL2, CDC6, and SLC7A11).DiscussionIf found predictive of rash in future studies using patient samples, our findings may help to identify those at risk for severe rash so that (a) the dose of EGFR TKI therapy may be adjusted; (b) additional treatments for the rash can be developed; and/or (c) precise, patient-centered interventions can be developed so that patients with cancer can better self-manage their rash and adhere to EGFR TKI treatment.

Dataset Information

Differential Expression of Gene Profiles in MRGX-treated Lung Cancer.

Objectives

Methods

Results

Conclusions

Publications

Differential Expression of Gene Profiles in MRGX-treated Lung Cancer.

Similar Datasets

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