Differential Expression of Gene Profiles in MRGX-treated Lung Cancer
Differential Expression of Gene Profiles in MRGX-treated Lung Cancer
Journal of Pharmacopuncture. 2013. Jul, 16(3): 30-38
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  • Received : June 15, 2013
  • Accepted : June 18, 2013
  • Published : July 30, 2013
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About the Authors
Yong-Kyun Kwon
East-West Cancer Center, Daejeon University College of Oriental Medicine, Daejeon, Korea
Seung-Yeul Lee
Division of Life Science, Korea Basic Science Institute, Daejeon, Korea
Hwan-Soo Kang
Department of Life Science, Dongguk University, Seoul, Korea
Jung-Suk Sung
Department of Life Science, Dongguk University, Seoul, Korea
Chong-Kwan Cho
East-West Cancer Center, Daejeon University College of Oriental Medicine, Daejeon, Korea
Hwa-Seung Yoo
East-West Cancer Center, Daejeon University College of Oriental Medicine, Daejeon, Korea
Seungjin Shin
Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA
Jong-Soon Choi
Division of Life Science, Korea Basic Science Institute, Daejeon, Korea
Yeon-Weol Lee
East-West Cancer Center, Daejeon University College of Oriental Medicine, Daejeon, Korea
Ik-Soon Jang
Division of Life Science, Korea Basic Science Institute, Daejeon, Korea

Modified regular ginseng extract (MRGX) has stronger anti-cancer activity-possessing gensenoside profiles.
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.
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.
Most MRGX-responsive genes are up-regulated transiently in A549 cells, but down-regulated in a sustained manner in lung cancer cells.
1. Introduction
Ginseng has been most widely used as herbal medicine in Eastern Asian countries, including Korea, China, and Japan. Ginseng is a species of a perennial plant belonging to the genus Panax in the family Araliaceae , and the ginseng species are only found in the northern hemisphere from Siberia to Vietnam. In general, Asian ginseng ( Panax ginseng ) and American ginseng ( Panax quinquefolius ) are most well-characterized, and these ginseng ginsenosides have been quantitatively and qualitatively characterized by ginsenoside profiling [ 1 ]. In particular, P. ginseng contains more than thirty pharmacologically-valuable ginsenosides [ 2 ]. Among them, ginsenosides such as Rg3, Rh2, Rb2, Compound K, and Rf2 are known to possess anti-cancer activities against colorectal cancer, colon cancer, hepatoma and breast cancer [ 3 - 6 ]. The ginsenosides exhibit anti-cancer activity by directly inhibiting cancer cell growth and metastasis in vivo and in vitro [ 7 ].The major ginsenosides, such as Rb1, Rb2 and Rg1, induce apoptosis of lung cancer via an extrinsic apoptotic pathway [ 8 ]. These results suggest that specific ginsenosides play critical roles in the inhibition of cancer cell proliferation.
Lung cancer, comprising of a majority of non-small-cell lung carcinomas (NSCLCs) of up to 85%, is the second leading cause of cancer death worldwide [ 9 ]. Thus, lung cancer is still considered as an extremely lethal cancer [ 10 ]. Surgical and combined therapies have contributed to reducing the mortality and the morbidity of lung cancer over last several decades; however, these therapies have limitations. Thus, complementary and alternative therapies with herbal medicine have recently been introduced in the Western medical society. However, few studies have reported on the anti-cancer activity of regular ginseng extract on a molecular biological level.
In this study, we prepared a modified regular ginseng extract (MRGX) that reinforced some gensenosides from regular ginseng butanol-extract (GBX) by using treatments with enzymes such as laminarinase and pectinase for stronger anti-cancer effect. The assessments of the gene expression profiles in human lung cancer samples by using cDNA microarray technology showed that some genes were down-regulated while others were up-regulated during the MRGX-treatment process. Because gene expression might change during the lung cancer cell death process, such studies should use specific components and not serum that contains a mixture of gensenosides.
2. Materials and Methods
- 2.1. Preparation of MRGX extract
The root of regular ginseng (4 yr old) was purchased from the National Agricultural Cooperative Foundation in Chuncheongnam-do, Korea. A total of 20 g of pulverized ginseng root powder was suspended in 380 ml of distilled water and then sterilized at 121℃ for 15 min. The ginseng butanol extract (GBX) contained compounds with specific anti-lung cancer activity. We used GBX as a control of regular ginseng. In addition, the suspension was treated with an aliquot of filter-sterilized commercial enzymes (laminarinase: 100 mg, pectinase: 100 mg) with equimolar ratio (1:1, specific activity unit); the mixture was then incubated at 40℃ for 2 days and evaporated to dryness at 60℃. These enzymes-modified ginseng powders were suspended in 400 ml of 80% (v/v) methanol. The suspension was treated in an ultrasound bath for 5 min and filtered through Whatman No. 2 filter paper. The filtrates were combined and evaporated to dryness at 50℃. The extract was diluted to a concentration of 10% (w/v) in 70% ethanol. In the present study, the finally-obtained sample was called the modified regular ginseng extract (MRGX).
- 2.2. Cell culture
Human lung cancer (A549) cells were obtained from American Type Culture Collection (Rockville, MD). Cell lines were grown in DMEM (Dulbecco Modified Eagle’s Medium, Sigma, USA) supplemented with 10% (v/v) FBS (Fetal Bovine Serum, GIBCO, NY) and 1% (w/v) penicillin- streptomycin (GIBCO, NY). The cells were incubated at 37℃ with 5% (v/v) CO 2 for 24 h. The density of A549 cells was adjusted to 5 × 10 3 cells/well in a 96-well plate. After a 24-h incubation, the cells were treated with MRGX at 50 ug/ml concentrations. The appropriate dose was determined by evaluating the cytotoxicity of MRGX for 24 h. To the cell solution, 10 ul of cell-counting kit-8 solution (Dojindo, Japan) was added for 1 h. Cell viability was determined by using a microplate reader (Sunrise, Tecan, Switzerland) to measuring the absorbance at 450 nm.
- 2.3. Microarray analysis
For the microarray analysis of the MRGX-treated lung cancer cells, a human twin 44K cDNA chip was used for the transcription profiling analysis. Total RNA was extracted from vehicle- or MRGX-treated lung cancer cells, and cDNA probes were prepared by using reverse transcription of 50 mg of RNA in the presence of aminoallyl-dUTP, followed by coupling with Cy3 dye (vehicle) or Cy5 dye (MRGX-treated). The mixed Cy3- and Cy5-labeled RNA from lung cancer cells (A549) was hybridized with one side of the Twin Chip TM Human 44K (Genocheck, Seoul, Korea), and that from MRGX-treated cells was hybridized with the other side of the chip.
Fluorescent images were quantified and normalized, as described previously [ 11 ]. This experiment was repeated four times. Genes were considered to be differentially expressed when the global M value, log2 (R/G), exceeded |1.0| (twofold) with a P -value < 0.05 after a significance analysis of the microarray (SAM). A student’s t -test was applied to assess the statistical significance of the differential expression of any gene between young and senescent HDFs (Human Dermal Fibroblasts) at each time point after MRGX treatment. To analyze the biological significance of the changes, we searched the gene ontology clone annotation ( and categorized the array data into specific gene groups. To verify the microarray data, we analyzed the total RNA extracted from cells by using a semi-quantitative reverse-transcription polymerase chain reaction (RT-PCR) and 2% agarose gel electrophoresis.
- 2.4. Ontology-related network analysis
To study the biological functions of ontology-relate regulated genes and proteins through their interaction network, we conducted a bioinformatic protein network analysis by using an ingenuity pathways analysis (IPA, http:// ). The IPA identifies the protein interaction network on the basis of a regularly-updated “Ingenuity Pathways Knowledge-base.” The updatable database containing millions of individual protein-protein relationships was retrieved from the biological literature. Network generation was optimized to include as many proteins from the inputted expression profile as possible and aimed at the production of highly-connected networks.
- 2.5. Semi-quantitative RT-PCR confirmation
Total RNA was extracted from young and senescent cells by using an acid guanidinium thiocyanate phenol-chloroform extraction-based method. To compare the relative amounts of mRNA in young and senescent cells, we performed a semi-quantitative RT-PCR. A series of mixtures was prepared by mixing RNA from young and senescent cells as indicated, so that each mixture had the same total amount of RNA (2 μg) in a constant volume (12 μl). The RT reaction was carried out in a final volume of 20 μl by using Superscript II reverse transcriptase according to the manufacturer’s protocol, and 4 μl of the final RT product mix was then PCR amplified. The primer sets used were 5’-ATCTGGCAACCCTAGTCTGC-3’ and 5’-GTGCTTCCACATGTCCTCAC- 3’ for IL8, 5’-GACATCATGATTGGCTTTGC- 3’ and 5’-TCCTCATCGAAGTGAGCATC-3’ for MMP7 and 5’-GTGAGGAAGCCCAAGCTACT-3’ and 5’-ATGTCCAAGGTGGCTTCTTC-3’ for PLAUR.
- 2.6. Western blot analysis
Expression levels of signaling proteins were examined by using Western blot analyses. In brief, 30 μg of denatured protein were run using 12% polyacrylamide gel electrophoresis and then transferred onto a nitrocellulose membrane. The transferred nitrocellulose membrane was stained with Ponceau S to position the proteins. The blotted membrane was blocked for 1 h with 5% (w/v) skimmed milk in TTBS (Tween-20 and Tris-buffered saline), followed by incubation with a dilution of primary antibodies (Cell Signal, Boston, USA), including interleukin-8 (IL-8), matrix metallopeptidase 7 (MMP7) and plasminogen activator, urokinase receptor (PLAUR), at room temperature for 2 h or at 4℃ overnight. The membrane was washed three times for 5 min with 0.1% (v/v) TTBS before incubation with horseradish peroxidase (HRP)-conjugated goat anti-mouse IgG or HRP-conjugated rabbit anti-goat IgG with a 1:2000 dilution in TBS containing 5% (w/v) skimmed milk at room temperature for 1 h. The membrane was rinsed three times with TBS-0.1% (v/v) Tween-20 for 5 min. The Pierce ® ECL system (Thermo Scientific, San Jose, CA) was used to develop the proteins on an X-ray film (Kodak, Seoul, Korea). The expression levels of proteins were quantitatively analyzed with GAPDH as an internal control.
3. Result
- 3.1. Analysis of MRGX related gene expression in lung cancer cells
To analyze the MRGX-related gene expression in lung cancer cells, we used a cDNA microarray analysis approach. Microarray data were filtered and combined using gene symbols; then, network analyses were performed. The clustered microarray data showed that groups of genes in lung cancer and MRGX-treated lung cancer cells were regulated differently by 50 mM of MRGX. Genes with at least one global M |1.0| are shown in Table 1 and 2 . A total of 109 were ultimately identified and categorized in terms of their cellular functions by using gene ontology and IPA annotation: The Venn-diagram for migration (45%), metabolism (45%), and cell death and survival (10%) are shown in Fig 1 The relative abundances of the regulated genes between lung and MRGX-treated lung cancer cells determined by using a semi-quantitative analysis, as described previously [ 12 ], are listed in Table 1 . Based on the criterion of a fold change > 1.0, 80 were up-regulated (Fig. 1A) whereas 29 were down-regulated in MRGX-treated lung cancer cells (Fig 1 B) compared to lung cancer.
- 3.2. Network analysis based on Gene Ontology analysis
To explore key MRGX-related proteins in the gene ontology analysis of gene functions, we used IPA to query 109 proteins belonging to the proteins up- and down-regulated by MRGX, resulting in a distinct interconnected network of 21 proteins (Fig 2 ). There were quantitative and qualitative alterations in MRGX-treated lung cancer cells between the regulation groups. Among them, interleukin 8 (IL8) was identified as the center of the MRGX-related protein network in lung cancer cells. IL-8 is a lung giant-cell carcinoma-derived chemotactic protein that binds CXCR1 and CXCR2 [ 13 ]. In the present study, IL-8 is one of critical chemo-attractants responsible for leukocyte recruitment, cancer proliferation, and angiogenesis, and the potential mechanism of IL-8 production from human non-small-cell lung cancer was investigated [ 14 ]. IL-8 was decreased dramatically in the MRGX-treated lung cancer cells. The protein-protein network analysis suggests that IL-8 is a major protein that interacts with multiple proteins and that it is directly or indirectly down-regulated or up-regulated in MRGX-treat lung cancer cells. IL-8-linked proteins include chemokine (C-X-C motif) ligand 2 (CXCl2), MMP7 and PLAUR. PLAUR plays a key role in lung cancer [ 15 ]. However, the detailed mechanism has not been studied in lung cancer. Herein, the level of IL-8 in the MRGX-treated lung-cancer cells was 1.9-fold down-regulated while PLAUR was up-regulated. The accumulation of PLAUR has been associated with lung cancer therapy.
Up-regulated gene list
Genbank Accession ID Gene Symbol Protein Name Fold Change
NM_001159699FHL1four and a half LIM domains 12.158241
NM_001184717TIPARPTCDD-inducible poly (ADP-ribose) polymerase1.982939
NM_000612IGF2insulin-like growth factor 2 somatomedin A1.871624
NM_002203ITGA2integrin alpha 2 (CD49B alpha 2 subunit of VLA-2 receptor)1.83122
NM_002526NT5E5'-nucleotidase ecto (CD73)1.808669
NM_032141NSRP1nuclear speckle splicing regulatory protein 11.734883
NM_000104CYP1B1cytochrome P450, family 1, subfamily B, polypeptide 11.694663
NM_000104UBASH3Bubiquitin associated and SH3 domain containing B1.555049
NM_003822NR5A2nuclear receptor subfamily 5, group A, member 21.503484
NM_000104CYP1B1cytochrome P450, family 1, subfamily B, polypeptide 11.493132
NM_005891ACAT2acetyl-CoA acetyltransferase 21.490562
NM_004487GOLGB1golgin B11.477885
NM_005633SOS1son of sevenless homolog 11.463831
NM_004454ETV5ets variant 51.445291
NM_001137550LRRFIP1leucine rich repeat (in FLII) interacting protein 11.410612
NM_004925AQP3aquaporin 3 (Gill blood group)1.374904
NM_001173463KIF21Akinesin family member 21A1.363929
NM_001105244PTPRMprotein tyrosine phosphatase, receptor type, M1.351404
NM_002483CEACAM6carcinoembryonic antigen-related cell adhesion molecule 61.34875
NM_022118RBM26RNA binding motif protein 261.333552
NM_003861DCAF5DDB1 and CUL4 associated factor 51.315943
NM_001023587ABCC5ATP-binding cassette, sub-family C (CFTR/MRP), member 51.313605
NM_003344UBE2Hubiquitin-conjugating enzyme E2H1.287242
NM_001174087NCOA3nuclear receptor coactivator 31.286065
NM_001946DUSP6dual specificity phosphatase 61.253699
NM_003870IQGAP1IQ motif containing GTPase activating protein 11.250989
NM_001193455NSUN2NOP2/Sun RNA methyltransferase family, member 21.24729
NM_001025356ANO6anoctamin 61.2465
NM_021925C2orf43chromosome 2 open reading frame 431.242904
NM_001098272HMGCS13-hydroxy-3-methylglutaryl-CoA synthase 1 (soluble)1.210537
NM_005063SCDstearoyl-CoA desaturase (delta-9-desaturase)1.201598
NM_014331SLC7A11solute carrier family 7 (anionic amino acid transporter light chain) member 111.186217
NM_001146276NCEH1neutral cholesterol ester hydrolase 11.185191
NM_000693ALDH1A3aldehyde dehydrogenase 1 family, member A31.183801
NM_004100EYA4eyes absent homolog 41.172664
NM_001032281TFPItissue factor pathway inhibitor1.171704
NM_001008938CKAP5cytoskeleton associated protein 51.171153
NM_001142568BBXbobby sox homolog1.168988
NM_001113239HIPK2homeodomain interacting protein kinase 21.164367
NM_016284CNOT1CCR4-NOT transcription complex, subunit 11.162079
NM_004775B4GALT6UDP-Gal:betaGlcNAc beta 1,4- galactosyltransferase, polypeptide 61.160644
NM_014646LPIN2lipin 21.14518
NM_172037RDH10retinol dehydrogenase 10 (all-trans)1.144987
NM_001005376PLAURplasminogen activator, urokinase receptor1.13818
NM_001077181CDC14Bcell division cycle 14B1.135517
NM_001083592ROR1receptor tyrosine kinase-like orphan receptor 11.135517
NM_007350PHLDA1pleckstrin homology-like domain, family A, member 11.131633
NM_020738KIDINS220kinase D-interacting substrate, 220kDa1.11258
NM_017694MFSD6major facilitator superfamily domain containing 61.110798
NM_031897CACNG6calcium channel, voltage-dependent, gamma subunit 61.094036
NM_001130107KLC1kinesin light chain 11.093194
NM_001174159SH2D4ASH2 domain containing 4A1.081308
NM_012090MACF1microtubule-actin crosslinking factor 11.078294
NM_001025081MBPmyelin basic protein1.077327
NM_001001894TTC3tetratricopeptide repeat domain 31.068548
NM_001190438NCOR1nuclear receptor corepressor 11.068334
NM_001077484SLC38A1solute carrier family 38, member 11.066673
NM_014827ZC3H11Azinc finger CCCH-type containing 11A1.058277
NM_015554GLCEglucuronic acid epimerase1.051527
NM_012197RABGAP1RAB GTPase activating protein 11.04982
NM_015635GAPVD1GTPase activating protein and VPS9 domains 11.048175
NM_152641ARID2AT rich interactive domain 21.044772
NM_203365RAPH1Ras association (RalGDS/AF-6) and pleckstrin homology domains 11.041108
NM_145693LPIN1lipin 11.039824
NM_004462FDFT1farnesyl-diphosphate farnesyltransferase 11.03898
NM_024817THSD4thrombospondin, type I, domain containing 41.038791
NM_001002860BTBD7BTB (POZ) domain containing 71.038677
NM_001081550THOC2THO complex 21.035132
NM_001128626SPIRE1spire homolog 11.026552
NM_001197030ANKHD1ankyrin repeat and KH domain containing 11.023268
NM_001142614EHBP1EH domain binding protein 11.02271
NM_014689DOCK10dedicator of cytokinesis 101.013887
NM_004462FDFT1farnesyl-diphosphate farnesyltransferase 11.012972
NM_015491PNISRPNN-interacting serine/arginine-rich protein1.012695
NM_004864GDF15growth differentiation factor 151.008396
NM_001031685TP53BP2tumor protein p53 binding protein, 21.004355
NM_016653ZAKsterile alpha motif and leucine zipper containing kinase AZK1.001137
Down-regulated gene list
Genbank Accession ID Gene Symbol Protein Name Fold Change
NM_000585IL15interleukin 15-1.00511
NM_006763BTG2BTG family, member 2-1.01812
NM_005195CEBPDCCAAT/enhancer binding protein (C/EBP), delta-1.02364
NM_001166599FAM122Bfamily with sequence similarity 122B-1.02554
NM_152603ZNF567zinc finger protein 567-1.02634
NM_000366TPM1tropomyosin 1 (alpha)-1.03063
NM_001416EIF4A1eukaryotic translation initiation factor 4A1-1.03982
NM_001008405BCAP29B-cell receptor-associated protein 29-1.05437
NM_001145275ZFYzinc finger protein, Y-linked-1.06241
NM_152487TMEM56transmembrane protein 56-1.0712
NM_002423MMP7matrix metallopeptidase 7 (matrilysin, uterine)-1.07991
NM_000598IGFBP3insulin-like growth factor binding protein 3-1.08553
NM_004617TM4SF4transmembrane 4 L six family member 4-1.09854
NM_006761YWHAEtyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, epsilon polypeptide-1.11487
NM_014696GPRIN2G protein regulated inducer of neurite outgrowth 2-1.13021
NM_020374C12orf4chromosome 12 open reading frame 4-1.19108
NM_001143668AMIGO2adhesion molecule with Ig-like domain 2-1.20343
NM_144643SCLT1sodium channel and clathrin linker 1-1.2175
NM_003821RIPK2receptor-interacting serine-threonine kinase 2-1.3159
NM_002522NPTX1neuronal pentraxin I-1.36692
NM_006528TFPI2tissue factor pathway inhibitor 2-1.45019
NM_005949MT1Fmetallothionein 1F-1.45041
NM_001511CXCL1chemokine (C-X-C motif) ligand 1-1.74981
NM_000584IL8interleukin 8-1.94821
NM_002090CXCL3chemokine (C-X-C motif) ligand 3-2.2981
NM_002089CXCL2chemokine (C-X-C motif) ligand 2-2.38018
AY227436DSP1drug-sensitive protein 1-6.3106
AB014766DERP12dermal papilla derived protein 12-6.74444
PPT Slide
Lager Image
Venn diagram of a 2-fold changed gene based on cellular function using gene ontology. Venn diagrams show (A) genes up-regulated in MRGX-treated lung cancer cells by migration, metabolism, and cell death and survival in the microarray analysis, and (B) genes down-regulated in the microarray analysis.
4. Discussion
Microarray analyses may result in biased data, and inconsistent results are often obtained when different methods are used. Therefore, the data need to be validated with a specific method. Because we measured gene expression, we wanted to validate our screening results with conventional methods such as RT-PCR and Western blots. We selected genes from each of the two up- and down-regulated group of genes for validation by using semi-quantitative RT-PCR and Western blot analyses. Four genes were selected based on their high fold-change (a large number) in the analysis and the availability of commercial antibodies. IL- 8, MMP7and PLAUR are examples of up- and down-regulated genes. The mRNA levels of IL-8 and MMP7 were decreased in the MRGX-treated lung cancer cells, and the protein levels of IL-8 and MMP7 also decreased. The semi-quantitative PCR and Western blot results showed that PLAUR was increased (Fig 3 ).
5. Conclusion
In conclusion, most MRGX-responsive genes are up-regulated transiently in A549 cells, but are down-regulated in a sustained manner in lung cancer cells. These genes might be involved in the altered MRGX responsiveness observed during the cancer migration and metabolism processes. The roles of these genes in MRGX responses, including the cell cycle and cell growth, should be evaluated in further studies by modulating their expressions.
PPT Slide
Lager Image
Network analysis based on a gene ontology analysis. Two-fold changed total proteins regulated by MRGX were queried by IPA, resulting in a distinct interconnected network of 21 proteins.
PPT Slide
Lager Image
Validation of microarray analysis results by using Western blot and RT-PCR analyses. Expressions of IL8 and MMP were examined by using a Western blot analysis with an anti-IL8 and MMP7 antibody (left panel) and by using a RT-PCR analysis (right panel). Expression of PLAUR was examined as described above. Beta-actin protein was used as a loading control for Western blot, and GAPDH was used as a normalization control forsemi-quantitative PCR.
This work was supported by a National Research Foundation of Korea grant funded by the Korean Government’s Ministry of Education, Science, and Technology (MEST, 2013, University-Institute Cooperation program). In addition, it was financially supported by a Korea Basic Science Institute NAP (Natonal Agenda Projecy) grant (T32780).
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