Abstract
Microarray technology (Human OneArray microarray, phylanxbiotech.com) was used to compare gene expression profiles of non-invasive MCF-7 and invasive MDA-MB-231 breast cancer cells exposed to dioscin (DS), a steroidal saponin isolated from the roots of wild yam, (Dioscorea villosa). Initially the differential expression of genes (DEG) was identified which was followed by pathway enrichment analysis (PEA). Of the genes queried on OneArray, we identified 4641 DEG changed between MCF-7 and MDA-MB-231 cells (vehicle-treated) with cut-off log2 |fold change|≧1. Among these genes, 2439 genes were upregulated and 2002 were downregulated. DS exposure (2.30 μM, 72 h) to these cells identified 801 (MCF-7) and 96 (MDA-MB-231) DEG that showed significant difference when compared with the untreated cells (p<0.05). Within these gene sets, DS was able to upregulate 395 genes and downregulate 406 genes in MCF-7 and upregulate 36 and downregulate 60 genes in MDA-MB-231 cells. Further comparison of DEG between MCF-7 and MDA-MB-231 cells exposed to DS identified 3626 DEG of which 1700 were upregulated and 1926 were down-regulated. Regarding to PEA, 12 canonical pathways were significantly altered between these two cell lines. However, there was no alteration in any of these pathways in MCF-7 cells, while in MDA-MB-231 cells only MAPK pathway showed significant alteration. When PEA comparison was made on DS exposed cells, it was observed that only 2 pathways were significantly affected. Further, we identified the shared DEG, which were targeted by DS and overlapped in both MCF-7 and MDA-MB-231 cells, by intersection analysis (Venn diagram). We found that 7 DEG were overlapped of which six are reported in the database. This data highlight the diverse gene networks and pathways in MCF-7 and MDA-MB-231 human breast cancer cell lines treated with dioscin.
Specification Table
| Subject area | Biology |
| More specific subject area | Breast Cancer |
| Type of data | Table, Figure |
| How data was acquired | Microarray analysis; data were done by Phalanx Biotech Group using Human OneArray (array version HOA 6.1) which contains 31,741 mRNA probes that can detect 20, 672 genes in human genome. |
| Data format | Analyzed |
| Experimental factors | Both MCF-7 and MDA-MB-231cells (~500×103 cells) were treated with DS (2.30 µM) for three days followed by RNA extraction and analysis. |
| Experimental features | MCF-7 and MDA-MB-231 cells were cultured in phenol red free DMEM-F12 (1:1) medium supplemented with 10% dextran charcoal treated fetal bovine serum, 50 U/mL penicillin and 50 µg/mL streptomycin as Pen-Strep and 2 mM of l-glutamine at 37 °C in a humidified atmosphere of 95% air and 5% CO2. The cells (~500×103 cells) were allowed to attach in the 25 cm3 culture flasks in 6 mL volume and after 24 h the cultures were treated with DS (2. 30 µM) for three days. |
| Data source location | N/A |
| Data accessibility | Data is within this article and available at the NCBI database via GEO series accession numbers GEO: GSE79465; GEO: GPL 19137; GEO:GSM2095708; GEO:GSM2095709; GEO:GSM2095710 |
Value of the data
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May stimulate further research on the utility of DS as a preventive agent of metastatic breast cancer.
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May facilitate new therapies to target specific genes that are associated with metastatic breast cancer.
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Genes participating in MAPK signaling pathways are the probable targets of breast cancer metastasis.
1. Data
Table 1 showed data on the global gene expression profile in MCF-7 and MDA-MB-231 cell lines treated with vehicle (DMSO) or DS in vitro. Table 2, Table 3, Table 4 showed gene ontology analysis based on molecular functions (Table 2), biological processes (Table 3), and cellular components (Table 4). Various canonical pathways, which were significantly altered between the cell lines (vehicle-treated) or after DS treatment, were presented in Table 5. The genes that were overlapped between these two cell lines (MCF-7 and MDA-MB-231) after DS treatment were listed in Table 6 and in a Venn diagram format in Fig. 1.
Table 1.
Number of differentially expressed genes in MCF-7 and MDA-MB-231 cells.
| Comparison | Up-regulated (number) | Down-regulated (number) | |
|---|---|---|---|
| 1 | MCF-7C/MDA-MB-231C | 2439 | 2002 |
| 2 | MCF-7C/MCF-7T | 395 | 406 |
| 3 | MDA-MB-231C/MDA-MB-231T | 36 | 60 |
| 4 | MCF-7T/MDA-MB-231T | 1700 | 1926 |
Table 2.
Gene ontology analysis based on molecular functions.
| Gene set name | Number of genes in the gene set | Number of genes overlap |
|||
|---|---|---|---|---|---|
| MCF-7 (T/C) | MDA-MB-231 (T/C) | MCF-7 (C)/ MDA-MB-231 (C) | MCF-7 (T)/MDA-MB-231 (T) | ||
| Magnesium ion binding | 452 | 38⁎ | – | 125⁎ | 97 |
| Cytokine activity | 195 | – | 8⁎ | – | – |
| Enzyme binding | 523 | 38 | – | 141⁎ | 109 |
| Actin binding | 326 | 23 | – | 95⁎ | 76 |
| Cytoskeletal protein binding | 504 | – | – | 135⁎ | 102 |
| Purine ribonucleotide binding | 1836 | 95 | – | 410⁎ | 306 |
| Ribonucleotide binding | 1836 | 95 | – | 410⁎ | – |
| Purine nucleotide binding | 1918 | 96 | – | 424⁎ | 323 |
| Nucleotide binding | 2245 | 110 | – | 485⁎ | – |
| Adenyl ribonucleotide binding | 1497 | 81 | – | 332⁎ | – |
| ATP binding | 1477 | 81 | 328⁎ | 251 | |
| Protein domain specific binding | 331 | – | – | 89⁎ | – |
| Nucleoside binding | 1612 | 84 | – | 353⁎ | 278 |
| Purine nucleoside binding | 1601 | 83 | – | 350⁎ | 273 |
| Adenyl nucleotide binding | 1577 | 82 | – | 345⁎ | 270 |
| Transcription factor binding | 513 | 29 | – | 127⁎ | – |
| Enzyme activator activity | 335 | 21 | – | 88⁎ | 62 |
The asterisk indicates q<0.05 [3].
Table 3.
Gene ontology analysis based on biological process.
| Gene set name | Number of genes in the gene set | Number of genes in overlap |
|||
|---|---|---|---|---|---|
| MCF-7 (T/C) | MDA-MB-231 (T/C) | MCF-7 (C)/ MDA-MB-231 (C) | MCF-7 (T)/MDA-MB-231 (T) | ||
| Protein complex biogenesis | 505 | 47⁎ | – | 129⁎ | – |
| Protein complex assembly | 505 | 47⁎ | – | 129⁎ | – |
| Macromolecular complex assembly | 665 | 55⁎ | – | – | – |
| Macromolecular complex subunit organization | 710 | 56⁎ | – | 165 | – |
| Protein oligomerization | 174 | 20⁎ | – | 50 | – |
| Protein amino acid phosphorylation | 667 | 47⁎ | – | 156 | – |
| Protein heterooligomerization | 52 | 10⁎ | – | 17 | – |
| Negative regulation of cell proliferation | 361 | 22 | 10⁎ | 81 | 86⁎ |
| Cell cycle | 776 | 46 | – | 210⁎ | – |
| Regulation of cell death | 815 | 52 | 11 | 205⁎ | 165⁎ |
| Regulation of apoptosis | 804 | 52 | 11 | 202⁎ | 163⁎ |
| Induction of programmed cell death | 321 | 21 | – | 94⁎ | 73⁎ |
| Regulation of programmed cell death | 812 | 52 | 11 | 202⁎ | 163⁎ |
| Induction of apoptosis | 320 | 21 | – | 93⁎ | 72⁎ |
| Positive regulation of cell death | 435 | 27 | – | 119⁎ | 95⁎ |
| Cell cycle process | 565 | 34 | – | 147⁎ | – |
| Regulation of binding | 153 | 78 | 4 | 52⁎ | 42⁎ |
| Positive regulation of Programmed cell death | 433 | 27 | – | 117⁎ | 94⁎ |
| Positive regulation of apoptosis | 430 | 27 | – | 116⁎ | 93⁎ |
| Cell death | 719 | 47 | 8 | 176⁎ | 146⁎ |
| Mitotic cell cycle | 370 | – | – | 100⁎ | – |
| Cell division | 295 | – | – | 83⁎ | – |
| Death | 724 | 47 | 8 | 176⁎ | – |
| Programmed cell death | 611 | 40 | 8 | 152⁎ | – |
| Apoptosis | 602 | 38 | 8 | 150⁎ | – |
| Regulation of DNA binding | 121 | – | 4 | 41⁎ | 35⁎ |
| Regulation of cell proliferation | 787 | 48 | 12 | 182 | 183⁎ |
| Positive regulation of cell proliferation | 414 | 29 | – | – | 97⁎ |
| Cell proliferation | 436 | 28 | – | 110 | 99⁎ |
| Neuron differentiation | 438 | – | – | – | 98⁎ |
| Death | 724 | 47 | 8 | – | 146⁎ |
| Regulation of locomotion | 192 | 15 | – | 56 | 50⁎ |
| Cell migration | 276 | – | 5 | 69 | 66⁎ |
| Regulation of cell motion | 193 | 16 | – | 56 | 50⁎ |
| Blood vessel development | 245 | – | – | 64 | 60⁎ |
| Neuron projection development | 256 | – | – | – | 62⁎ |
| Vasculature development | 251 | – | – | 64 | 61⁎ |
| Cell projection organization | 368 | – | – | 91 | 82⁎ |
| Regulation of cellular component size | 271 | – | 6 | 66 | 64⁎ |
| Transmembrane receptor protein serine/threonine kinase signaling pathway | 103 | 12 | – | 35 | 31⁎ |
| Regulation of cell migration | 169 | 14 | – | 51 | 44⁎ |
| Hemopoietic or lymphoid organ development | 260 | – | – | 60 | 61⁎ |
| Positive regulation of developmental process | 278 | 18 | 6 | 72 | 64⁎ |
| Axon guidance | 107 | – | – | – | 31⁎ |
| Hemopoiesis | 236 | – | – | – | 56⁎ |
| Positive regulation of locomotion | 98 | 12 | – | 32 | 29⁎ |
| Locomotory behavior | 274 | – | – | 63⁎ | |
| Response to vitamin | 66 | – | – | 22⁎ | |
The asterisk indicates q<0.05 [3].
Table 4.
Gene ontology analysis based on cellular component.
| Gene set name | Number of genes in the gene set | Number of genes in overlap |
|||
|---|---|---|---|---|---|
| MCF-7 (T/C) | MDA-MB-231 (T/C) | MCF-7 (C)/ MDA-MB-231 (C) | MCF-7 (T)/MDA-MB-231 (T) | ||
| Membrane-enclosed Lumen | 1856 | 111⁎ | – | 397⁎ | – |
| Organelle lumen | 1820 | 108⁎ | – | 391⁎ | 300 |
| Intracellular organelle Lumen | 1779 | 106⁎ | – | 382⁎ | 291 |
| Nuclear lumen | 1450 | 91⁎ | – | 312⁎ | 243 |
| Nucleoplasm | 882 | 62⁎ | – | 186 | – |
| Intracellular Non-membrane-bounded Organelle | 2596 | 134⁎ | – | – | – |
| Non-membrane-bounded Organelle | 2596 | 134⁎ | – | – | – |
| Cytosol | 1330 | 74⁎ | – | 285⁎ | – |
| Cytoskeleton | 1381 | 74⁎ | – | – | – |
| Nuclear matrix | 56 | 9⁎ | – | – | – |
| Nuclear periphery | 61 | 9⁎ | – | – | – |
| Extracellular space | 685 | – | 12⁎ | – | |
| Extracellular region part | 960 | – | 14⁎ | – | – |
| Lytic vacuole | 211 | 17 | – | 71⁎ | 56⁎ |
| Lysosome | 211 | – | – | 71⁎ | 56⁎ |
| Vacuole | 252 | 18 | – | 79⁎ | 62⁎ |
| Basolateral plasma Membrane | 203 | 14 | – | 64⁎ | – |
| Non-membrane-bounded Organelle | 2596 | 134 | – | 543⁎ | – |
| Intracellular Non-membrane-bounded Organelle | 2596 | 134 | – | 543⁎ | 413⁎ |
| Anchoring junction | 172 | 14 | – | 52⁎ | 46⁎ |
| Adherens junction | 155 | – | – | 48⁎ | 41⁎ |
| Golgi apparatus | 872 | – | – | 197⁎ | 150 |
| Mitochondrion | 1087 | 56 | – | 239⁎ | – |
| Cell fraction | 1083 | – | – | 237⁎ | 209⁎ |
| Nucleolus | 698 | – | – | 107⁎ | 129 |
| Cell leading edge | 138 | – | – | 41⁎ | 37⁎ |
| Extracellular matrix | 345 | – | 5 | – | 78⁎ |
| Insoluble fraction | 839 | – | – | – | 159⁎ |
The asterisk indicates q<0.05 [3].
Table 5.
Gene set enrichment analysis based on the canonical pathway.
| Gene set name | Number of genes in the gene set | Number of genes in overlap |
|||
|---|---|---|---|---|---|
| MCF-7 (T/C) | MDA-MB-231 (T/C) | MCF-7 (C)/ MDA-MB-231 (C) | MCF-7 (T)/MDA-MB-231 (T) | ||
| MAPK signaling pathway | 267 | – | 7⁎ | 70 | 56 |
| Pathways in cancer | 328 | 27 | – | 99⁎ | 76⁎ |
| Apoptosis | 87 | – | – | 34⁎ | 23 |
| Lysosome | 117 | – | – | 41⁎ | 37⁎ |
| VEGF signaling pathway | 75 | – | – | 29⁎ | – |
| Focal adhesion | 201 | – | – | 60⁎ | – |
| Prostate cancer | 89 | – | – | 32⁎ | – |
| mTOR signaling pathway | 52 | – | – | 21⁎ | – |
| Pancreatic cancer | 72 | – | – | 26⁎ | – |
| Colorectal cancer | 84 | – | – | 29⁎ | – |
| Renal cell carcinoma | 70 | – | – | 25⁎ | – |
| Regulation of actin cytoskeleton | 215 | 16 | – | 59⁎ | – |
| Small cell lung cancer | 84 | – | – | 28⁎ | – |
The asterisk indicates q<0.05 [3].
Table 6.
List of genes overlapped between the two cell lines.
| Gene symbol | Description of the gene | Log2 (ratio) |
|||
|---|---|---|---|---|---|
| MDA-MB-231C/MCF-7C | MCF-7T/MCF-7C | MDA-MB-231T/MDA-MB-231C | MDA-MB-231T/MCF-7T | ||
| ERRFI1 | ERBB receptor feedback inhibitor 1 | 0.01 | 1.33 | 1.06 | −0.35 |
| MMP1 | Matrix metallopeptidase 1 (interstitial collagenase) | 1.59 | 2.70 | 2.09 | 0.96 |
| SOD2 | Superoxide dismutase 2, mitochondrial | 2.54 | 1.04 | 1.08 | 2.61 |
| IL24 | Interleukin 24 | −0.93 | 1.44 | 2.86 | 0.37 |
| PTRF | Polymerase I and transcript release factor | −1.54 | −2.35 | −1.03 | −0.23 |
| ALKBH5 | AlkB, alkylation repair homolog 5 (E. coli) | −0.70 | −1.36 | −1.01 | −0.40 |
Fig. 1.
Venn diagram of the overlap among DEGs of MCF-7 and MDA-MB-231 cells exposed to DS (2.30 µM, 72 h). The MCF-7 and MDA-MB-231 cells shared seven genes of which six genes were found in the data base.
2. Experimental design, materials and methods
2.1. Cell culture, DS treatment, and extraction of nucleic acids
The detailed procedure of cell culture, treatment with DS, and the isolation of RNA have been described in our previous study [1]. In brief, human breast adenocarcinoma, MCF-7 (ER+) and MDA-MB-231 (ER−) cells were maintained in phenol red free DMEM-F12 (1:1) medium supplemented with 10% dextran charcoal treated fetal bovine serum, 50 U/mL penicillin and 50 µg/mL streptomycin and 2 mM of l-glutamine. The cells (~500×103 cells) were allowed to attach in the 25 cm3 culture flasks in 6 mL volume for 24 h before treating with DS (2.30 µM) for three days. After complete removal of the media, the cells were trypsinized, resuspended in the medium, and washed twice with PBS. RNA extraction was made by Trizol reagent as described previously [1]. Briefly, Trizol reagent (Invitrogen, Carlsberg, CA) was used to lyse the cells. Chloroform was added to the lysate for phase separation. The clean aqueous phase (RNA) was transferred to a clean 1.5 ml Eppendorf tube and RNA was precipitated by 2-propanol. After a quick wash in 75% ethanol, the extracted RNA was dissolved in nuclease-free water. The samples (extracted RNA) were further treated with DNase I (Promega, Madison, WI), to remove DNA contamination, if any. Finally, the concentration of RNA was determined by NanoDrop 2000c (Thermo Fisher Scientific, Waltham, MA) and the samples were stored at −80 °C until sending to Phalanx Biotech Group for microarray analysis.
2.2. Microarray analysis
Microarray analysis was carried out by Phalanx Biotech Group using OneArray (array version HOA 6.1) which contains 31,741 mRNA probes that can detect 20, 672 genes in human genome. In brief, the purity of the extracted RNA was checked using NanoDrop ND-1000. The Pass criteria for absorbance ratios are established as A260/A280≥1.8 and A260/A230≥1.5. RIN values are ascertained using Agilent RNA 6000 Nano assay to determine RNA integrity. Pass criteria for RIN value is established at >6. Genomic DNA (gDNA) contamination was evaluated by gel electrophoresis. Any RNA that did not meet these criteria was excluded from the analysis.
Target preparation was performed using an Eberwine-based amplification method with Amino Allyl MessageAmp II aRNA Amplification Kit (Ambion, AM1753) to generate amino-allyl antisense RNA (aa-aRNA). Labeled aRNA coupled with NHS-CyDye (Cy5) was prepared and purified prior to hybridization. Purified coupled aRNA was quantified using NanoDrop ND-1000; pass criteria for CyDye incorporation efficiency at >15 dye molecular/1000 nt. All the raw data are available in NCBI׳s gene expression Omnibus and are accessible through GEO series accession number GSE79465 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE79465).
2.3. Gene expression data analysis
Global scaling normalization (scatter plot, histogram and volcano plot, principal component analysis) was carried out, and the fold changes (cut-off (log2 |fold change|≧1)) were calculated based on the relative signal intensities (scanned by Agilent 0.1 XDR protocol). A filtering step was performed using Rosetta error model [2] which allowed for determination of the statistical significance of every pair wise gene between different groups. The default multiple testing corrections used was Benjamini and Hochberg [3] false discovery rate with a q value cutoff <0.05. The testing correction was the least stringent of all corrections and provided a good balance between the discovery of statistically significant genes and the limitation of false positive occurrences by removing all gene spots with a q value >0.05 in all conditions. This procedure narrowed the list of genes to those significantly affected by DS treatment. Gene annotation was based on two data bases: NCBI ref seq release 57.ensembl release 70 cDNA sequences and homo_sapiens_core_70_37. Finally the pathway enrichment analysis (PEA) was utilized to group and display genes with similar expression profiles. The online tool Database for Annotation, Visualization, and Integrated Discovery (DAVID) [4] was used for PEA. The selected KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways with an adjusted EASE (Expression Analysis Systematic Explore) score p value ≤0.05 and count >2. Data gained by this technique may help to understand more on in vitro studies of botanical natural products used in breast cancer treatment. The pathway analysis was used to examine functional correlations within the cell lines and different treatment groups. Data sets containing gene identifiers and corresponding expression values were uploaded into the application. Each gene identifier was mapped to its corresponding gene object in the KEGG pathway map with an adjusted EASE (Expression Analysis Systematic Explore) score p value ≤0.05 and count >2. Networks were “named” on the most common functional group(s) present in the database. Canonical pathway analysis (GeneGo maps) as evaluated acknowledged function-specific genes significantly present within the network [5].
Acknowledgments
This study was partially supported by the United States Department of Agriculture Research Specific Cooperative agreement No. 58-6408-1-603-04.
Footnotes
Transparency document associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.dib.2016.05.040.
Appendix A. Transparency document
Supplementary material
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