Metastatic genes targeted by an antioxidant in an established radiation- and estrogen-breast cancer model

  • Authors:
    • Gloria M. Calaf
    • Debasish Roy
  • View Affiliations

  • Published online on: September 14, 2017     https://doi.org/10.3892/ijo.2017.4125
  • Pages: 1590-1600
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Abstract

Breast cancer remains the second most common disease worldwide. Radiotherapy, alone or in combination with chemotherapy, is widely used after surgery as a treatment for cancer with proven therapeutic efficacy manifested by reduced incidence of loco-regional and distant recurrences. However, clinical evidence indicates that relapses occurring after radiotherapy are associated with increased metastatic potential and poor prognosis in the breast. Among the anticarcinogenic and antiproliferative agents, curcumin is a well-known major dietary natural yellow pigment derived from the rhizome of the herb Curcuma longa (Zingiberaceae). The aim of the present study was to analyze the differential expression of metastatic genes in radiation- and estrogen-induced breast cancer cell model and the effect of curcumin on such metastatic genes in breast carcinogenesis. Expression levels of TGF-α and TGFβ1 genes were upregulated in MCF-10F and downregulated in Tumor2 cell lines treated with curcumin. Expression levels of other genes such as caspase 9 and collagen 4 A2 were upregulated in both MCF-10F and Tumor2-treated cell lines. Integrin α5 and cathepsin B and D decreased its expression in Tumor2, whereas E-Cadherin, c-myc and CD44 expressions were only increased in MCF-10F. It can be concluded that metastatic genes can be affected by curcumin in cancer progression and such substance can be used in breast cancer patients with advanced disease without side-effects commonly observed with therapeutic drugs.

Introduction

Breast cancer remains the second most common cancer worldwide with nearly 1.7 million new cases in 2012 (1). In cancer treatment, radiotherapy, alone or in a combination with chemotherapy, is widely used after surgery with proven therapeutic efficacy manifested by reduced incidence of loco-regional and distant recurrences (24). However, clinical evidence indicates that relapses occurring after radiotherapy are associated with increased metastatic potential and poor prognosis in breast (5,6) and other tissues (7,8). This has also been confirmed experimentally in tumors growing within a previously irradiated mammary tissue that is more invasive and metastasized (911).

Metastasis is a complex, multistep biological process, involving a multitude of genes and biomolecules. Despite the successful therapeutic management of breast cancer to control primary tumor growth, metastatic disease remains the greatest clinical challenge in oncology, as there are still not very efficient methods to prevent relapses and check the breast cancer metastasis. The interactions between cancer cells and normal host cells contribute significantly to the metastatic cascade, and a wide range of signaling and stimulating biomolecules and genes are involved in this process. Various authors have showed that heterogeneous nature of breast carcinomas that are not only characterized on the basis of histopathological features but can also be subdivided based on metastases gene-expression analysis (1214).

Cancer metastases are responsible for the majority of cancer-related deaths. It usually arises from few cells in the primary tumor that acquire the ability to progress by sequential steps necessary to grow at a distant site (15,16). Some of these sequential steps include invasion through extracellular matrix, intravasation, survival in the circulation, extravasation into a distant site, and progressive growth at that site (16).

Although early-stage breast cancer is highly treatable, no effective treatment is available for metastatic breast cancer that follows surgery, radiation and chemotherapy for the primary tumor. In breast cancer, for example, metastasis affects the bone and the lung, and less frequently the liver, brain and adrenal medulla. Although, the genetic basis of these differential metastatic properties are poorly understood, acquisition of the ability to complete each step involved in metastasis is thought to be driven by the accumulation of genetic mutations. These rare mutations are acquired at relatively late stage of the disease during the evolution of the primary tumor (17,18). Among the anticarcinogenic and antiproliferative agents, curcumin [1,7-bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione;diferuloylmethane] is a well-known major dietary natural yellow pigment derived from the rhizome of the herb Curcuma longa (Zingiberaceae) (19). This phytochemical has also been shown to suppress the proliferation of numerous types of tumor cells (20,21). It has been previously shown to prevent the formation of many chemically-induced cancers including mammary cancer in mice (22,23). Metastatic development in human mammary epithelial carcinoma MCF-7 cells was also found to be inhibited by curcumin via the suppression of urokinase-type plasminogen activator by NF-κB signaling pathways (24). It is also a potent blocker of NF-κB activation induced by different inflammatory stimuli through inhibition of various cell cycle pathways, thus resulting in the suppression of NF-κB-dependent gene products that suppress apoptosis and mediate proliferation, invasion and angiogenesis (2528). The human multidrug-resistant breast cancer cell line (MCF-7/TH) has been shown to be several-fold more sensitive to curcumin than the mammary epithelial cell line (MCF-10A). Even though both cell lines accumulated a similar amount of curcumin, a significantly higher percentage of apoptotic cells was induced in breast cancer cells compared to a very low percentage of apoptosis in mammary epithelial cells (29). The synergistic mechanisms of combinatorial treatment using curcumin and mitomycin C (MMC) on the inhibition of tumor growth were also explored by differential gene expression profile, Gene Ontology (GO), Ingenuity Pathway Analysis (IPA) and Signal-Net network analysis (30).

The development of DNA microarray technology of genome-wide transcriptomic profiling, has provided new insight into the genetic basis of metastasis The human tumor metastasis GE Array represents ~84 genes related to metastasis and it was utilized to study the effect of curcumin on radiation-induced breast cell model (31,32). Genes selected for this array encode several classes of growth factor receptors, cell-matrix interaction molecules, metastasis-associated proteases and suppressors, oncogenes and various signal transduction molecules. The aim of the present study was to analyze the differential expression of metastatic genes in radiation- and estrogen-induced breast cancer cell model and the effect of curcumin on such metastatic genes reported previously in breast carcinogenesis.

Materials and methods

Breast cancer cell lines

An in vitro experimental breast cancer model (Alpha model) developed by exposure of the immortalized human breast epithelial cell line, MCF-10F to low doses of high LET (linear energy transfer) α particle radiation (150 keV/µm) and subsequent growth in the presence or absence of 17β-estradiol was used in the present study (31). The spontaneously immortalized breast epithelial cell line MCF-10F has a near diploid karyotype and is of luminal epithelial cell origin. These cells retain all the characteristics of normal epithelium in vitro, including anchorage-dependence, non-invasiveness and non-tumorigenicity in the nude mice. Cell lines were grown in DMEM/F-12 (1:1) medium supplemented with antibiotics [100 U/mI penicillin, 100 µg/ml streptomycin, 2.5 µg/ml amphotericin B (all from Life Technologies, Grand Island, NY, USA)], 10 µg/ml and 5% equine serum (Biofluids, Rockville, MD, USA), 0.5 µg/ml hydrocortisone (Sigma, St. Louis, MO, USA) and 0.02 µg/ml epidermal growth factor (Collaborative Research, Bedford, MA, USA) (33). This model consisted of human breast epithelial cells in different stages of transformation: i) a control cell line, MCF-10F; ii) a malignant and tumorigenic cell line named Alpha5; and iii) Tumor2 derived from cells originated from a tumor after injection of Alpha5 cell line in the nude mice. The MCF-10F cell line was exposed to double doses of 60 cGy of α particles and treated with estrogen before the two exposures, such cell line was called Alpha5. Tumor2 cell line was originated from this cell line after injection in the nude mice. Both cell lines were treated with curcumin (30 µM for 48 h). Phenotypic characteristics of these cell lines and their genetic alterations including differentially expressed genes were previously described (3136).

Isolation and purification of total RNA and mRNA

Total RNA was isolated from both the controls (MCF-10F) and Tumor2 cell lines and curcumin-treated cell lines using TRIzol reagent (Invitrogen Corp., Long Island, NY, USA). Each sample comprising 500 µg of total RNA was treated with 5 µl of DNAse I (10 U/µl) (Roche Pharm., Indianapolis, IN, USA) for 60 min at 37°C. Then, 10X Termination Mix (0.1 M EDTA, pH 8.0 and 1 mg/ml glycogen) (Clontech, Palo Alto, CA, USA) was used to stop the reaction. Each sample was then purified following established procedure (32,37). The amount of each purified RNA sample was first measured by a spectrophotometer and then electrophoresed on denaturing formaldehyde/agarose/ethidium bromide gel, to check its quality and purity from proteins and free nucleotides. Each sample of 500 µg of purified total RNA was then subjected to PolyA+ RNA analysis with the Oligotex mRNA Purification kit (Qiagen Inc., Valencia, CA, USA). PolyA+ RNA was then purified following established procedures (37).

Development of cDNA from mRNA

A sample of 0.5–1 µg of PolyA+ RNA was then used for First Strand cDNA Synthesis using the Advantage™ RT-for-PCR kit (Clontech) using oligo(dT) and random hexamer primers. Approximately 100 ng of the First Strand cDNA Synthesis product was used for carrying out RT-PCR reactions using gene specific primers as mentioned above. The PCR amplified products were then labeled using respective primers and Biotin-16-UTP as well as RT cocktail, as before, to generate the probes, and then used for cDNA hybridization analysis.

Protein expression by immunocytochemistry

Exponentially growing cells were plated on a glass chamber slide (Nunc Inc., Naperville, IL, USA), at a density of 1×104 cells/ml of medium, and allowed to grow until 70% confluence. Cells were fixed with buffered paraformaldehyde, incubated with 1% H2O2 in methanol to block endogenous peroxidase and washed with buffer solution, then covered with normal horse serum for 30 min, and then tested with mouse TGF-α (C-18; sc-1338), TGFβ1 (H-112; sc-7892), E-Cadherin (H-108; 7870) and cathepsin D (E-7; sc-13148) monoclonal antibodies (Santa Cruz Biotechnology, Inc., Santa Cruz, CA, USA) at 1:500 dilution overnight at 4°C; then incubated for 45 min with diluted biotinylated secondary antibody solution and Vectastin Elite ABC reagent (both from Vector Laboratories, Burlingame, CA, USA). The experiments were repeated 3 times in cells with similar passages in vitro.

cDNA expression array

GE Array Q Series Human Tumor Metastasis Array (SABiosciences/Qiagen, Bethesda, MD, USA) represents 84 genes known to be involved in metastasis. Each of these genes was amplified by polymerase chain reaction (PCR) with gene-specific primers to generate 200- to 600-bp products. Each PCR product (~100 ng) that was spotted in quadruplicate onto a positively charged membrane. Each GEArray Q series membrane was spotted with a negative control of pUC18 DNA, blanks and housekeeping genes, including β-actin, GAPDH, cyclophilin A and ribosomal protein L13A (32).

Synthesis of cDNA probes from mRNA

The purified mRNAs were used for the synthesis of cDNA probes with Biotin-16-dUTP (Roche Pharm.). Annealing mixture was prepared by mixing ~1.0–5.0 µg of mRNA with 3 µl of Buffer A (GE primer mix) (SABiosciences) and the final volume was adjusted to 10 µl. The mixture was then incubated in a preheated thermal cycler at 70°C for 3 min. Cooled to 42°C and kept at that temperature for 2 min. Then, 10 µl of RT cocktail was prepared by mixing 4 µl of 5X Buffer BN [for 50 µl 10X buffer, add 1 µl of 1 M DTT and 50 µl of 10X dNTP mix (5 mM dATP, dCTP, dGTP and 500 µM dTTP)], 2 µl of Biotin-16-UTP, 2 µl of RNase-free H2O, 1 µl of RNase inhibitor and 1 µl of MMLV reverse transcriptase (both from Promega Corp., Madison, WI, USA). RT cocktail was then warmed at 42°C for 1 min and slowly mixed with 10 µl of pre-warmed annealing mixture. The incubation continued at 42°C for 90 min, and then labeled cDNA probe was denatured by heating at 94°C for 5 min, and quickly chilled on ice. In each cell line tested, mRNA was isolated and purified from different passages, and cDNA probes were prepared from each of them and hybridized to the respective membranes. Experiments using the same mRNA preparation were repeated 3 times, and measurable, median-normalized expression values of each gene were compared to avoid false-positive signals (32).

Differential hybridization of cDNA expression array

Each array membrane was pre-wetted with 5 ml of de-ionized water and incubated at 60°C for 5 min. It was then replaced with 2 ml of pre-warm (60°C) GEAprehyb solution (GEAhyb solution with a heat-denatured sheared salmon sperm DNA at a final concentration of 100 µg/ml) (SABiosciences, Bethesda, MD) and gently mixed for a few seconds. Pre-hybridization was continued at 60°C for 1–2 h with continuous gentle agitation. Approximately 0.75 ml solution of GEAhyb was prepared by adding the entire volume of denatured cDNA probe onto GEAprehyb solution and kept at 60°C. Then, GEAprehyb solution was replaced by GEAhyb solution and hybridization continued overnight at 60°C with continuous gentle agitation. Subsequently, array membranes were washed twice in wash solution 1 (2X sodium chloride sodium citrate and 1% sodium dodecyl sulfate) at 60°C for 15 min each with gentle agitation and then twice with solution 2 (0.1X sodium chloride sodium citrate and 0.5% sodium dodecyl sulfate) at 60°C for 15 min each with gentle agitation. To assess the reproducibility of the hybridization array assays, pair-wise comparisons between array data sets for each cell line was tested by repeated hybridization and the mRNAs prepared in different lots were analyzed in scatter plots with multiple regressions (32,38). In each case, expression levels of 95% of the genes had repeated values that were within 2-fold (32).

Chemiluminescent detection of cDNA probes

After discarding the last wash, 2 ml of GEAblocking solution was added to each membrane and incubated for 40 min at room temperature with continuous agitation. Then, binding buffer was prepared by diluting alkaline phosphatase-conjugated streptavidin (AP) with 1X buffer F (SuperArray, Bethesda, MD, USA) in a 1:7,500 dilution. GEAblocking solution was replaced by 2 ml of binding buffer and incubated for 10 min with continuous but gentle agitation. Then, membrane was washed 4 times with 4 ml of 1X binding buffer F for 5 min in each washing and rinse twice with 3 ml of rinsing buffer G (SuperArray). The membrane was covered with 1.0 ml of CDP-Star chemiluminescent substrate and incubated at room temperature for 2–5 min. It was then exposed to X-ray film (Kodak BioMax MS Film; Kodak Corp., Rochester, NY, USA) with corresponding intensifying screen at room temperature for multiple exposures of 1–5 min.

Quantification of array hybridization

Quantification of hybridization signals on the expression array membranes was carried out by exposing the autoradiographic film in a densitometric scanner (model 300A; Molecular Dynamics, Sunnyvale, CA, USA). It was then estimated both with the ImageQuant (Molecular Dynamics) and ScanAlyze program (Eisen Lab). Volume quantification was performed by calculating the volume under the surface created by a 3-dimensional plot of pixel locations and pixel values as previously described (32,38). All raw signal intensities were corrected for background by subtracting the signal intensity of a negative control or blank. Results were also normalized to that of a housekeeping gene. These corrected, normalized signals can then be used to estimate the relative abundance of particular transcripts. To delineate the potential signal interference between adjacent strong hybridization signals, equal-sized ellipses were drawn around each signal area (hybridization spots) using software (ImageQuant/ScanAlyze) and was then separately scanned and compared with housekeeping genes so the chances of interference between adjacent strong hybridization signals were minimized. Normalization of the expression levels of different housekeeping genes from multiple autoradiographic exposures between different hybridization experiments were carried out by taking the average signals of each of the housekeeping genes. Data from high intensity spots were chosen for further use. Median background was subtracted, and signals that were <2.0-fold above background level were considered too low to accurately measure and were omitted from the analysis. Signals for each individual gene were also normalized to the geometric mean of the expression level of that gene across the set of membranes being compared. Mean signals were calculated from quadruplicate measurable spots, or whether 3 of the 4 spots were measurable. Then, the changed folds indicated whether a gene exhibited increased, decreased, or unchanged expression based on statistical criteria (38).

Western blot analysis

Differential expression of few genes after quantification by array were further confirmed by western blot analysis following usual procedures.

Results

The effect of curcumin on cell lines from a radiation-induced breast cell model was studied. Microarray technology allowed us to measure the relative expression of many genes in a single experiment. In the present study, two controls the MCF-10F and Tumor2 cell lines were treated with curcumin (MCF-10F+curcumin and Tumor2+curcumin). Table I shows the genes selected for this array that encode several classes of growth factor receptors, cell-cell, cell-matrix interaction molecules, metastasis-associated proteinase, protease inhibitors, signal transduction molecules oncogenes, metastasis, suppressors and other related genes. Fig. 1 corresponds to the membranes containing the genes found in this particular array as GE Array Q Series Human Tumor Metastasis Gene Array that was used.

Table I

GEArray Q series of human tumor metastasis gene array.

Table I

GEArray Q series of human tumor metastasis gene array.

Functional gene groupingGene symbols/names
Growth factors and receptorsCSF1 (csf-1), CSF1R (c-fms/MC-SF-R), FGF1 (a-FGF), FGF2 (b-FGF2), HGF (scatter factor), IGF2, NGFB, TGFA (TGF-α), TGFB1 (TGFβ1), VEGF, VEGFC
Cell-cell and cell-matrix interaction moleculesCAV1 (caveolin-1), CDH1 (cadherin-1/E-cadherin), COL4A2 [collagen α2 (IV)], ICAM5 (telencephalin), ITGA2-3, ITGA5-6, ITGA6, ITGB1, ITGB3, LAMB1 (laminin β1), LAMC1 (laminin β2), MICA (MUC-18), MUC1, NCAM1, PECAM1, VTN (vitronectin)
Metastasis-associated proteases:MMP1-3, MMP7-11, MMP13-16
Matrix metalloproteinasesCASP8-9, CST3 (cystatin C), CTSB (Cathepsin B),
OthersCTSD (cathepsin D), CTSL (cathepsin L), ELA2 (elastase), HPSE (heparanase), MGEA5 (meningioma hyaluronidase 5), PLAU (uPA), TMPRSS4
Protease inhibitorsSERPINB2 (PaI-2), SERPINB5 (maspin), SARPINE1 (PAI-1), THBS1-S2, TIMP1-P3
Signal transduction moleculesLIMK1 (Lim kinase), PLAUR (uPAR), PIK3C2B, RAC1
OncogenesERBB2 (c-erb-2/neu), ETS1-2 (c-ets-1-2), ETV4 (PEA3), FES, FOS (c-fos), HRAS (c-Ha-ras), MDM2, MYC (c-myc), RAF1, SRC (c-src)
Metastasis, suppressorsBRMS1 (BrMS1), CD44, DCC, KAI1, KISS1 (KiSS-1), MAP2K4 [mkk4 (JNKK1)], MTA1, NM23A (NM23), NME4, PTEN
Other related genesAPI5 (apoptosis inhibitor 5), ARHC (Rho C), EHM2, ENPP2 (autotaxin/ATX), MGAT3 and 5 (acetylglucosa-minyltransferase III and V), ODC1, PTGS2 (cox-2), S100A4 (mts-1), SNCG (BCSG1), SSP1 (osteopontin)

Results indicated that out of 84 genes, 16 were upregulated and 4 were downregulated by curcumin treatment in MCF-10F cell line, whereas, a total of 24 genes were altered with 11 upregulated and 13 downregulated by curcumin treatment in Tumor2 cell line. In both cases, alterations of Q ≥2.0 were taken into consideration whereas, ~20–25 genes also showed moderate alterations in their expression (Q <1.50) (data not shown). The remaining 30–35 genes showed no altered expression in either group of experiments.

Table II A and B show upregulated and downregulated metastatic genes found in MCF-10F control and treated with curcumin cell lines, respectively. Fig. 2 presents differentially expressed genes found in such array, where a comparison between MCF-10F and MCF-10F plus curcumin cell lines were analyzed. Table III A and B show regulated and downregulated metastatic genes found in Tumor2 cell line control and treated with curcumin cell lines. Fig. 3 presents differentially expressed genes found in such array, where a comparison between Tumor2 and Tumor2 plus curcumin cell lines were analyzed. Protein expression of growth factors such as TGF-α (Fig. 4A) was upregulated in MCF-10F cells treated with curcumin. However, it was downregulated in Tumor2 by this substance (Fig. 4B). Similar results were observed in TGFβ1 protein expression in Tumor2 cell lines treated with curcumin (Fig. 4C and D). Among other important genes, E-Cadherin protein expression was upregulated in MCF-10 cells by the effect of curcumin and no effect in the Tumor2 cell line as shown in Fig. 5A and B). However, cathepsin D protein expression was not affected by curcumin in the MCF-10F cell line and decreased such expression in the Tumor2 cell line as seen in Fig. 5C and D. The expression levels of few selected genes identified by cDNA microarray expression profiling were further validated by western blot analysis (Fig. 6).

Table II

Upregulated and downregulated metastatic genes in MCF-10F cell line treated with curcumin (30 µM).

Table II

Upregulated and downregulated metastatic genes in MCF-10F cell line treated with curcumin (30 µM).

A, Upregulated metastatic genes in MCF-10F cell line treated with curcumin (30 µM)
PositionUniGeneGeneBankSymbolDescriptionGene nameFold change
MCF-10FMCF-10F+cur
56Hs.90800D83646MMP16Matrix metalloproteinase 16 (membrane-inserted)MMP164.7 (↑)
86Hs.170009NM_003236TGFATransforming growth factor, αTGF-α4.6 (↑)
87Hs.1103X02812TGFB1Transforming growth factor, β1TGFβ14.5 (↑)
94Hs.73793M32977VEGFVascular endothelial growth factorVEGF3.9 (↑)
8Hs.194657Z13009CDH1Cadherin 1, type 1, E-cadherin (epithelial)E-Cadherin3.6 (↑)
49Hs.90598NM_000247MICAHomo sapiens MICA gene, allele MUC-18MUC-183.6 (↑)
64Hs.79070X00364MYCv-myc avian myelocytomatosis viral oncogene homologc-myc3.6 (↑)
95Hs.79141X94216VEGFCVascular endothelial growth factor-CVEGF-C3.4 (↑)
47Hs.121502NM_002410MGAT5cDNA encod N-acetylglucosamyltransferase-V (Homo sapiens)GnT-V3.1 (↑)
91Hs.325495NM_003255TIMP2Tissue inhibitor of metalloproteinase 2TIMP-22.8 (↑)
16Hs.211567NM_005215DCCDeleted in colorectal carcinomaDCC2.5 (↑)
71Hs.78146NM_000442PECAM1Homo sapiens platelet endothelial cell adhesion molecule (CD31 ag)CD312.3 (↑)
5Hs.100641U60521CASP9Caspase 9, apoptosis-related cysteine proteaseCaspase 9, Mch62.1 (↑)
9Hs.75617X05610COL4A2Collagen, type IV, α2Collagen 4 A22.0 (↑)
7Hs.169610M59040CD44CD44 antigen (homing function and Indian blood group systemCD442.0 (↑)
51Hs.2258NM_002425MMP10Matrix metalloproteinase 10Stromelysin 22.0 (↑)
B, Downregulated metastatic genes in MCF-10F cell line treated with curcumin (30 µM)
PositionUniGeneGeneBankSymbolDescriptionGene nameFold change
MCF-10FMCF-10F+cur
93Hs.63325NM_019894TMPRSS4Transmembrane protease, serine 4TMPRSS-45.3 (↓)
78Hs.85181X03484RAF1v-raf-1 murine leukemia viral oncogene homolog 1c-raf-14.7 (↓)
34Hs.265829M59911ITGA3Integrin, α3 (ag CD49C, α3 sub of VLA3 rec.)Integrin α34.0 (↓)
31Hs.151250U72671ICAM5Intercellular adhesion molecule 5, telencephalinICAM-53.4 (↓)
97–99N/AL08752PUC18PUC18 plasmid DNApUC181.01.0
100–102BlankBlankBlankBlank00.00.0
103–104Hs.169476M33197GAPDGlyceraldehyde-3- phosphate dehydrogenaseGAPDH1.01.0
105–108Hs.342389NM_021130PPIAHomo sapiens peptidylprolyl isomerase ACyclophilin A1.01.0
109–110Hs.119122NM_012423RPL13ARibosom. protein L13a (23 kDa highly basic protein)RPL13A1.01.0
111–112Hs.288061X00351ACTBβ-actinβ-actin1.01.0

Table III

Upregulated and downregulated metastatic genes: Tumor2 cell line treated with curcumin (30 µM).

Table III

Upregulated and downregulated metastatic genes: Tumor2 cell line treated with curcumin (30 µM).

A, Upregulated metastatic genes: Tumor2 cell line treated with curcumin (30 µM)
PositionUniGeneGeneBankSymbolDescriptionGene nameFold change
Tumor2Tumor2+cur
60Hs.73862NM_002424MMP8Matrix metalloproteinase 8 (neutrophil collagenase)MMP88.2 (↑)
9Hs.75617X05610COL4A2Collagen, type IV, α2Collagen 4 A27.0 (↑)
76Hs.196384NM_000963PTGS2Homo sapiens prostaglandin-endoperoxide synthase 2 (prostaglandin G/hsynthase and cyclooxygenase)Cox-24.3(↑)
75Hs.10712U96180PTENPhosphatase and tensin homolog (mut in multiple Adv cancers 1)PTEN3.2 (↑)
80Hs.75716J02685SERPINB2Human plasminogen activator inhibitorPAI-23.1(↑)
30Hs.37003NM_005343HRASv-Ha-ras Harvey rat sarcoma viral oncogene homologH-ras2.5 (↑)
36Hs.227730X53586ITGA6Integrin, α6 subunitIntegrin α62.5 (↑)
28Hs.809X57574HGFHepatocyte growth factor) (hepapoietin A; scatter factorScatter factor2.4 (↑)
24Hs.7636X52192FESProto-oncogene tyrosine-protein kinase fes/fpsc-fes2.3 (↑)
20Hs.323910m11730ERBB2v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 2erb-22.1 (↑)
5Hs.100641U60521CASP9Caspase 9, apoptosis-related cysteine proteaseCaspase 9, Mch62.1 (↑)
B, Downregulated metastatic genes: Tumor2 cell line treated with curcumin (30 µM)
PositionUniGeneGeneBankSymbolDescriptionGene nameFold change
Tumor2Tumor2+cur
86Hs.170009NM_003236TGFATransforming growth factor, αTGF-α7.0 (↓)
87Hs.1103X02812TGFB1Transforming growth factor, β1TGFβ16.9 (↓)
27Hs.25647V01512FOSHuman cellular oncogene c-fosc-fos6.3 (↓)
14Hs.343475M11233CTSDCathepsin D (lysosomal aspartyl protease)Cathepsin D5.4 (↓)
51Hs.2258NM_002425MMP10Matrix metalloproteinase 10Stromelysin 25.1 (↓)
83Hs.63236NM_003087SNCGSynuclein, γ (breast cancer-specific protein 1)BCSG14.7 (↓)
57Hs.111301J03210MMP2Matrix metalloproteinase 2 (gelatinase A, 72 kDa gelatinase)Gelatinase A4.5 (↓)
66Hs.2561X52599NGFBNerve growth factor, β polypeptideNGFβ3.5 (↓)
95Hs.79141X94216VEGFCVascular endothelial growth factor-CVEGF-C3.1 (↓)
13Hs.297939L16510CTSBCathepsin BCathepsin B3.0 (↓)
26Hs.284244NM_002006FGF2Fibroblast growth factor 2 (basic)β-FGF2.0 (↓)
35Hs.149609X06256ITGA5Integrin, α5 (fibronectin receptor, α polypeptid)Integrin α52.0 (↓)
77Hs.173737NM_006908RAC1Ras-rel C3 bot. toxin subs. 1 (rho family, small GTP bind prot.)Rac12.0 (↓)
97–99N/AL08752PUC18PUC18 Plasmid DNApUC181.01.0
100–102BlankBlankBlankBlank00.00.0
103–104Hs.169476M33197GAPD Glyceraldehyde-3-phosphate dehydrogenaseGAPDH1.01.0
105–108Hs.342389NM_021130PPIAHomo sapiens peptidylprolyl isomerase ACyclophilin A1.01.0
109–110Hs.119122NM_012423RPL13ARibosom protein L13a (23 kDa highly basic protein)RPL13A1.01.0
111–112Hs.288061X00351ACTBβ-actinβ-actin1.01.0

Discussion

Microarray technology allows us to measure the relative expression of thousands of genes in a single experiment. Advancement in microarray technology and gene expression databases provide a new opportunity for identifying the mode of action and targets for various genes involved in breast cancer metastatic cascade. As breast cancer is one of the most common and complex types of cancer, which frequently progress towards metastasis, microarray technique is ideal to study the genes associated with this process.

The aim of the present study was to investigate the effect of antiproliferative compound curcumin in a radiation-induced breast cancer model on genes involved in breast cancer metastasis. In the present study, the two controls MCF-10F and Tumor2 cell lines, were used and both were treated with 30 mM curcumin as MCF-10F+curcumin and Tumor2+curcumin cell lines.

Various genes related to metastasis were differentially altered in the human metastasis gene array after cell lines were treated with curcumin. Thus, curcumin showed upregulation of TGF-α expression in MCF-10F cell line but downregulated in Tumor2 cell line. This result is consistent with the role of TGF-α during brain metastases where estrogen was found to promote colonization of triple-negative breast cancer cells by upregulation of TGF-α mRNA and protein levels via astrocytes mediated paracrine mechanism which activated EGFR in brain metastatic cells (39). Similar results were obtained when TGFβ1 expression was analyzed. Various curcuminoids are known to block TGFβ1 signaling in human breast cancer cells and limit osteolysis in a murine model of breast cancer bone metastasis which is corroborated with these findings (40).

Results also indicated that another important gene, the vascular endothelial growth factor-C (VEGF-C) altered the expression since it was upregulated in MCF-10F cell line and downregulated in Tumor2 cell line in presence of curcumin. In a xenograft model of triple-negative breast cancer in mice, a lower expression of VEGFR2/3 and inhibition of angiogenesis was noted in presence of curcumin. Curcumin is known to inhibit VEGF-C induced lymphangiogenesis in a matrigel assay in mice, which is fully consistent with the result obtained in curcumin treated Tumor2 cell line (41,42). Flow cytometry and western blot analysis showed that curcumin and its derivatives induced cell cycle arrest at G0/G1 phase in MCF-7 cells by entering early phase of apoptosis via mitochondrial pathway, as evidenced by the activation of caspase 3 and 9, which led to elevation of intracellular ROS, a decrease in Bcl-2 and PARP and as well as an increase in Bax expression (43).

Other genes as caspase 9 and collagen 4 A2 were upregulated in both MCF-10F and Tumor2 groups. Angiogenesis is a crucial step in the growth and metastasis of cancers and the role of curcumin to act as an angiogenesis inhibitor by modulating collagen-like protease activity during endothelial morphogenesis and in few other systems are already established (44).

Several integrins (e.g., integrin α3, α5 and α6) showed differential expression in both cell lines. The downregulation of integrin-mediated signal transduction by curcumin treatment in Tumor2 cell line strongly indicated the potential role of curcumin as an inhibitor of tumor cell invasion and metastasis (45). Integrins are usually cell surface markers to detect various cancer stem cell activities. Differential gene alterations of different types of integrins were noted in the analysis of the present results. It has been reported that cancer stem cells resist conventional cancer therapies and are likely to play a major role in cancer relapse by upregulating the surface markers such as integrins that leads to metastasis (46).

Other important genes usually altered in cancer progression of breast were cathepsin B and E, members of papain family of cysteine proteases normally present in the lysosome. They can be translocated and are able to degrade components of the extracellular matrix. It is interesting to note that curcumin lower protein expression of both these genes in Tumor2 cell lines. It has been shown that an example of substrate for cathepsin B is E-Cadherin, which is involved in adherens junctions, where the downregulation of E-Cadherin in cancer is directly linked to invasion and metastasis (47,48). E-Cadherin expression was only upregulated in the MCF-10F, but not in the Tumor2 cell lines by the effect of curcumin. It is notable that such gene is related to epithelium mesenchymal transition, corroborating the epithelial phenotype that characterized E-Cadherin in such process (49).

It is concluded that metastatic genes can be affected by curcumin in cancer progression therefore it is interesting to determine that this substance can be used in breast cancer patients with advanced disease without side-effects usually induced by therapeutic drugs. Due to complex structure involving multiple functional groups, the exact mechanism and site of action of curcumin on breast cancer cells is difficult to determine and needs to be further studied.

Abbreviations:

IR

ionizing radiation

HBEC

human breast epithelial cell

LET

linear energy transfer

Acknowledgments

In the present study, the technical support of Guiliana Rojas, Georgina Vargas Marchant and Leodán A Crispin is greatly appreciated. The present study was supported by grant support FONDECYT #1120006b (to G.M.C.) and Universidad de Tarapaca-Ministerio de Educación (MINEDUC); COBI Innovation-HCC (Title-V) (to D.R.).

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Calaf GM and Calaf GM: Metastatic genes targeted by an antioxidant in an established radiation- and estrogen-breast cancer model. Int J Oncol 51: 1590-1600, 2017
APA
Calaf, G.M., & Calaf, G.M. (2017). Metastatic genes targeted by an antioxidant in an established radiation- and estrogen-breast cancer model. International Journal of Oncology, 51, 1590-1600. https://doi.org/10.3892/ijo.2017.4125
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Calaf, G. M., Roy, D."Metastatic genes targeted by an antioxidant in an established radiation- and estrogen-breast cancer model". International Journal of Oncology 51.5 (2017): 1590-1600.
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Calaf, G. M., Roy, D."Metastatic genes targeted by an antioxidant in an established radiation- and estrogen-breast cancer model". International Journal of Oncology 51, no. 5 (2017): 1590-1600. https://doi.org/10.3892/ijo.2017.4125