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Microarray expression profiles of angiogenesis-related genes predict tumor cell response to artemisinins

Abstract

Artemisinin (ARS) and its derivatives are used for the second-line therapy of malaria infections with Plasmodium falciparum and P. vivax. ARSs also reveal profound antitumor activity in vitro and in vivo. In the present investigation, we correlated the mRNA expression data of 89 angiogenesis-related genes obtained by microarray hybridization from the database of the US National Cancer Institute with the 50% growth inhibition concentration values for eight ARSs (ARS, arteether (ARE), artesunate (ART), artemisetene, arteanuine B, dihydroartemisinylester stereoisomers 1 and 2). The constitutive expression of 30 genes correlated significantly with the cellular response to ARSs. By means of hierarchical cluster analysis and cluster image mapping expression, profiles were identified that determined significantly the cellular response to ART, ARE, artemether and dihydroartemisinylester stereoisomer 1. We have exemplarily validated the microarray data of six out of these 30 genes by real-time RT-PCR in seven cell lines. The fact that sensitivity and resistance of tumor cells could be predicted by the mRNA expression of angiogenesis-related genes indicate that ARSs reveal their antitumor effects at least in part by inhibition of tumor angiogenesis. As many chemopreventive drugs exert antiangiogenic features, ARSs might also be chemopreventive in addition to their cytotoxic effects.

Introduction

Surgery, chemotherapy and radiotherapy have been the established treatment options for cancer during the past five decades. They aim to damage proliferating cells and to induce apoptotic cell death. Major drawbacks are the frequent development of resistance to chemotherapy and the severe side effects. Efforts to improve tumor therapy have led to the concept of molecular targeted chemotherapy leading to more selective mechanism-based approaches to minimize the disadvantages of established chemotherapy. Inhibitors of angiogenesis that block angiogenic signals have been developed, and antiangiogenic therapy strategies have raised considerable interest as valuable adjuncts to cytostatic and cytotoxic chemotherapy.1, 2 In the angiogenic process, the formation of new blood vessels from pre-existing ones is essential for the supply of tumors with oxygen and nutrients and for the spread of metastatic cells throughout the body.3 Angiogenesis is promoted by numerous factors including cytokines, VEGF, bFGF, PDGF, etc. It is negatively regulated by angiostatin, endostatin, thrombospondin, TIMPs and others. The factors that are produced in tumor cells as well as in surrounding stromal cells act in a balance to promote either proangiogenic or antiangiogenic processes.4

Artesunate (ART) is a semisynthetic derivative of the sesquiterpene artemisinin (ARS) extracted from the leaves of Artemisia annua L., which has been used in traditional Chinese medicine for the treatment of fever for more than 2000 years.5 Today, ART and the related compound, artemether (ARM), are used as second-line treatment for malaria infections with Plasmodium falciparum. These compounds are well-tolerated, and no major side effects are observed in patients.6, 7 The molecular mechanisms of action are not fully explored yet. Formation of carbon-centered free radicals has been suggested.5, 8, 9, 10, 11, 12 A recent meta-analysis revealed that ART-containing regimens substantially reduce treatment failure compared to standard antimalarial treatments.13 ART can significantly prolong the time span of antimalarial treatment efficacy.14

The observation that ART inhibits the growth of many transformed cell lines has led to the hypothesis that the drug can also be useful for the treatment of human neoplasia.15, 16, 17, 18, 19, 20, 21, 22, 23, 24 As shown by us and others,25, 26, 27, 28, 29, 30, 31, 32 ARSs reveal antiangiogenic features in vitro and in vivo. The molecular determinants of the antiangiogenic activity of ARSs are incompletely understood at present. For this reason, we compared the 50% growth inhibitory concentration (GI50) values for ARS as lead drug and seven ARS derivatives in 60 cell lines of the Developmental Therapeutics Program of the National Cancer Institute (NCI), with baseline mRNA microarray expression levels of 89 genes involved in tumor angiogenesis. The mRNA expression as determined by microarray analyses has been reported33 and deposited in the NCI's database (http://dtp.nci.nih.gov). The GI50 values for ART in 60 cell lines of the NCI have been described by us,17 while the GI50 values for the other ARSs have been deposited in the NCI's database. We subjected these data to Kendall's τ-test, hierarchical cluster analysis, and cluster image mapping to further characterize mRNA expression profiles of angiogenesis-related genes. This analysis correlated cellular responses of these tumor cell lines to ARSs. We have exemplarily validated the microarray data by real-time RT-PCR for 20 genes.

Materials and methods

Cell culture

The panel of 60 human tumor cell lines of the Developmental Therapeutics Program of the NCI of the USA consisted of leukemia (CCRF-CEM, HL-60, K-562, MOLT-4, RPMI-8226, SR), melanoma (LOX-IMVI, MALME-3M, M14, SK-MEL2, SK-MEL28, SK-MEL-5, UACC-257, UACC-62), non-small-cell lung cancer (A549, EKVX, HOP-62, HOP-92, NCI-H226, NCI-H23, NCI-H322M, NCI-460, NCI-H522), colon cancer (COLO205, HCC-2998, HCT-116, HCT-15, HT29, KM12, SW-620), renal cancer (786-0, A498, ACHN, CAKI-1, RXF-393, SN12C, TK-10, UO-31), ovarian cancer (IGROV1, OVCAR-3, OVCAR-4, OVCAR-5, OVCAR-8, SK-OV-3), cells, cells of tumors of the central nervous system (SF-268, SF-295, SF-539, SNB-19, SNB-75, U251), prostate carcinoma (PC-2, DU-145) and breast cancer (MCF-7, NCI/ADR-Res, MDA-MB-231, Hs578T, MDA-MB-435, MDA-N, BT-549, T-47D). Their origin and processing have been previously described.34

In vitro response to cytostatic drugs

The sulforhodamine B assay for the determination of drug sensitivity in these cell lines has been reported.35 The response of the 60 tumor cell lines to ART has been determined in a previous collaboration with the NCI.17 The GI50 values for ART as well as for other ARSs (ARS, arteether (ARE), artemether (ARM), artemisitene (ARTEMIS), arteanuine B (ARAB), dihydroartemisinyl ester stereoisomers 1 and 2 (ARTEST 1 and 2)) have been deposited in the database of the Developmental Therapeutics Program of the NCI (http://dtp.nci.nih.gov) (see Supplementary Table 1).

Real-time PCR

For real-time PCR validation, CCRF-CEM, DU-154, HL60, HS-578T, MCF-7, MDS-MB-231 and T47D cells were grown under identical conditions in RPMI medium supplemented with 0.5% L-glutamine and 10% fetal calf serum. Total RNA was extracted from the cells and reverse transcribed using T7-(dT)24 oligo primers and the Custom SuperScript Double-Stranded cDNA Synthesis Kit (Invitrogen, Irvine, CA, USA) following the instructions given by the provider. RT-PCR primers used are listed in Supplementary Table 2. Real-time PCR was performed on an I-Cycler (BioRad Hercules, CA, USA) using iQ Supermix (BioRad) supplemented with 10 nM fluorescein (BioRad) and 0.1 × Sybr-Green I (Sigma, Milan, Italy). Fifty cycles of 15″ at 95°C followed by 30″ at 60°C were performed. After amplification, melt curves were performed to monitor amplicon identity. Expression data were normalized on the housekeeping genes GAPDH, G6PD and RNA-polymerase II gene expression data obtained in parallel using the Bestkeeper software.36 Relative expression values were calculated using Qgene software.37 Three biological replicates were performed and each real-time PCR reaction was run with three technical replicates to calculate expression data.

Statistical analysis

The mRNA expression values for 60 cell lines of 89 genes, which according to a recent review by Peale and Gerritsen38 are related to angiogenesis were selected from the database of the NCI, Bethesda, MA, USA (http://dtp.nci.nih.gov) (the 89 genes are listed in supplementary Table 3). The mRNA expression has been determined by microarray analyses as reported.33 Hierarchical cluster analysis is an explorative statistical method which groups at first sight heterogeneous objects into clusters of homogeneous objects. Objects are classified by calculation of distances according to the closeness of between-individual distances. The applicability of hierarchical cluster analysis for microarray data has been demonstrated previously.33 Cluster analyses applying the complete-linkage method were performed by means of the WinSTAT program (Kalmia, Cambridge, MA, USA).

Kendall's τ-test was used to calculate significance values (P-values) and rank correlation coefficients (R-values) as a relative measure for the linear dependency of two variables. This test was implemented into the WinSTAT program. The χ2 test was used as implement of the WinSTAT program to proof bivariate frequency distributions for pairs of nominal scaled variables for dependencies.

Results

Hierarchical cluster analysis and cluster image mapping of microarray data

As a starting point to elucidate genes, which may be involved in the antiangiogenic pathway(s) activated by ARSs, we correlated the GI50 values for eight ARS derivatives with the baseline mRNA expression levels of 89 genes for the 60 NCI cell lines by means of Kendall's τ test. These genes were selected because of their involvement in angiogenesis.38 Only those genes whose mRNA expression correlated with a significance level of P<0.05 not only with GI50 values for ART but also to those of least three further ARS derivatives were further analyzed. This criterion was used to optimize the chance to identify genes that are involved in the anti-angiogenic effect of ARS derivatives. Of the 89 genes analyzed, 30 (two of which were represented with two different clones each) fulfilled this criterion. The P-values of the correlations between the mRNA expressions values and the GI50 values for eight ARS derivatives are shown in Table 1.

Table 1 Correlation of the IC50 values for artemisinin deriviatives to mRNA baseline expression of angiogenesis-related genes of 60 NCI cell lines by means of Kendall's τ test

Then, a hierarchical cluster analysis was performed and a cluster image map constructed using the microarray data of these 30 genes. The dendrogram on the right side of Figure 1 shows the 60 cell lines analyzed. Three major branches of the cluster tree can be separated from each other. We performed a second analysis and clustered these 30 genes (Figure 1, top). The cluster image map that was constructed from these two dendrograms shows that the distribution of mRNA expression values of the 30 genes was differentially clustered in six areas of the cluster image map (Figure 1).

Figure 1
figure1

Dendrograms and clustered image map obtained by hierarchical cluster analysis (complete linkage method). The dendrogram on the right shows the clustering of 60 cell lines and indicates the degrees of relatedness between cell lines. The dendrogram on the top shows the clustering of 30 genes (two of which were represented with two different clones each). The cluster image map corresponds to each mRNA expression value obtained by microarray analysis. The areas of the cluster image map that contribute to segregating the clusters are labeled (ai).

To validate the microarray data, we selected six of the 30 genes, which were most clearly differentially regulated in the 60 cell lines (THBS1, TGFB2, urokinase plasminogen activator (PLAU), AXL, CYR61, FGF2; Figure 1, squares a, d, g) and analyzed their baseline expression in three cell lines from square a (DU-154, HS-578T, MDA-MB-231), two from square d (MCF-7, T47D), and two from square g (CCRF-CEM, HL-60). In order to obtain a reliable normalization of values derived from different cell lines, we selected three house keeping genes (see also Materials and methods) that were expressed at particularly stable levels in the seven cell lines tested. Gene expression data were normalized on the mean value of the three house keeping genes. The mRNA expression values obtained by real-time RT-PCR correlated significantly with the values obtained by microarray analysis for all six genes analyzed at a significance level of P<0.05 (range 0.00533–0.04926). The correlation coefficient R ranges between 0.52381 and 0.80952 (Figure 2A). The overall correlation for all six genes was R=0.60918 at a significance level of P=1.01 × 10−8.

Figure 2
figure2

Validation of microarray data by real-time RT-PCR. (A) The six best discriminators were selected, and the relative expression levels measured by real-time RT-PCR were calculated as levels relative to the housekeeping genes GAPDH, G6PD and RPII in seven of the 60 NCI cell lines: HS-578T, MDA-MB-231, MCF7, T-47D (breast), DU-145 (prostate), HL60, CCRF-CEM (leukemia). Breast: Hs-578T (filled circle), MDA-MB 231 (filled square), MCF7 (filled triangle), T-47D (open square); prostate: DU-145 (open circle); leukemia: HL-60 (open triangle); CCRF-CEM (filled diamond). (B) Analysis of 20 genes contained in the discriminating panel in HS-578T, MDA-MB-231, MCF7, T-47D, DU-145 and HL60 cells. Data are reported as log2 ratio.

The analysis of 14 other genes that were randomly selected from the list of the 30 discriminatory genes confirmed the microarray expression data. Spearman's correlation analysis of the comparison of real-time PCR and microarray data for these 20 genes yielded a significant correlation (R=0.5433, P<0.0001; Figure 2B).

To analyze whether this expression profile contains relevant information, we correlated the GI50 values for the eight ARS derivatives with the distribution of the 60 cell lines in this dendrogram, which had been generated independently from this information. As can be seen in Table 2, cluster 1 of the dendrogram on the right side of Figure 1 contained mainly ART-resistant cell lines, whereas cluster 3 contained predominately ART-sensitive cell lines. Cluster 2 was of a mixed type. This pattern of distribution was statistically significant (P=0.0422, χ2 test), indicating that it is possible to predict sensitivity or resistance of cell lines to ART using the mRNA expression of the present set of angiogenesis-related genes. We also found correlations for ARE, ARM and ARTEST1 at a significance level of P<0.05 (P=0.018 and P=0.013, respectively) and correlations of borderline significance (0.05<P<0.1) for ARTEST2 and ARS. The GI50 values for ARAB and ARTEMIS did not correlate with the expression pattern identified by hierarchical cluster analysis (Table 2).

Table 2 Separation of clusters of 60 NCI cell lines obtained by hierarchical cluster analysis shown in Figure 1 in comparison to sensitivity to eight artemisinins

Discussion

During the past years, several antiangiogenic treatment strategies with specificity against certain target molecules have been developed, that is, small molecules and monoclonal antibodies inhibiting angiogenic molecules and their receptors.39 Although the present investigation points to the general importance of angiogenesis-related genes for the antitumor effects of ARSs, it is still not deducible, whether this drug class inhibits a single target protein or whether the antiangiogenic mode of action of ARSs is multifactorial.

Most likely, ARSs elicit a multifactorial response rather than being directed against a single target. We and others have described antiangiogenic effects of ARS in vitro and in vivo.25, 26, 27, 28, 29, 30, 31, 32 ART strongly reduced neovascularization of Matrigel plugs injected under the skin of mice when administered with the drinking water. No apoptotic effects on endothelial cells were observed.25 This prompted us to further investigate into the mechanisms of this antiangiogenic acitivity. We therefore investigated the role of 89 known angiogenesis-related genes38 for the response of tumor cells to ARS derivatives. As angiogenesis is regulated by a wide variety of positive and negative factors,40 microarray analyses might be more suited than single gene approaches. Mining the NCI database, we selected 89 genes known to be involved in angiogenesis and present on the microarrays used, in order to analyze their possible connection to ART-related antiangiogenic effects. The mRNA expression of 30 genes (two of which are represented with two different clones each) correlated significantly with the cytotoxicity of ART.

We validated the microarray data through extensive testing by real-time PCR. We observed a significant correlation of microarray and real-time PCR data. In general, the expression levels of the single genes in six cell lines analyzed were in concordance, although the level of expression was not confirmed for each gene in each cell line. It is known from similar studies that the two technologies of expression analysis deliver qualitatively comparable data, whereas for the assessment of the precise expression value, real-time PCR is better suited.

Our analysis identified angiogenesis-related genes that are differentially expressed in ART-sensitive and resistant cell lines. Sensitivity to the drug in terms of cell viability and growth and the angiogenic phenotype of the same cells are correlated. Resistance to the drug in terms of proliferation would thus extend to the antiangiogenic response of the cell in its microenvironment. It is therefore probable that these genes determine the antiangiogenic response of the cell lines when treated with ART. We and others have recently shown that many chemopreventive agents, among which 4-hydroxyphenyl-retinamide that also produces reactive oxygen species exert antiproliferative and antiangiogenic activities.41, 42 The panel of genes that correlate with the response to ART contains many fundamental angiogenic regulators, such as the vascular endothelial growth factors, which stimulate proliferation and migration of endothelial cells as fundamental step in vessel formation. Three human genes encode for vascular endothelial growth factors (VEGFA, VEGFB, VEGFC). Additional heterogeneity arises through alternative splicing of these genes.43 VEGF-A forms homodimers and interacts with its two major receptor tyrosine kinases FLT1 and KDR/FLK1. Thereby they control blood vessel formation in many tissues. VEGF-B acts as an endothelial cell growth factor.44 VEGF-C forms disulfide-linked dimers, activates both the FLT4 which is involved in lymphatic vessel development and KDR/FLK1, and stimulate the growth of endothelial cells.45, 46 In our investigation, VEGF-A expression correlated with GI50 values for ART, ARTEST1 and ARTEST3 and VEGF-B expression with ARTEST1 at a significance level of P<0.05 (data not shown). This indicates that VEGF-A and VEGF-B regulators might also play a role for the antiangiogenic effect of ARSs. As described above, we decided to include into the cluster analysis only those genes, whose mRNA expression correlated with GI50 values of at least four ARSs. Therefore, only VEGF-C was among the panel of the 30 genes used for cluster analysis. The antiangiogenic activity of ARS and ART has been investigated by different authors. ARS downregulated vascular endothelial growth factor (VEGF) expression, an effect that was reversed upon cotreatment with the free radical scavengers mannitol and vitamin E. This indicates that ARS may act in an antiangiogenic manner via reactive oxygen species generation.27 ART and dihydroARS reduced the expression of the two major VEGF receptors, Flt-1 and KDR/flk-1, as determined by immunohistochemistry in the chicken chorioallantoic membrane neovascularization model, in HUVEC, and in nude mice injected with human ovarian cancer HO-8910, respectively. The results of these authors and of the present investigation suggest that the antiangiogenic effect induced by ARSs might occur by induction of cellular apoptosis and inhibition of expression of VEGF receptors.28, 29, 31 In addition to ARSs, other sesquiterpene lactones, such as costunolide also inhibit the VEGFR KDR/Flk-1 signaling pathway.47 It merits further investigation to analyze, whether the correlations between gene expression and GI50 values for ARSs found in the present investigation are events downstream of the inhibition of the VEGF ligand/receptor system or whether other angiogenic regulators are also causative affected by these drugs.

The correlation of FGF2 expression and response to ARSs found in our analyses fits to reports of other authors, who found that extracts of various Chinese herbs show antiangiogenic properties.48 Isolated and chemically characterized compounds from traditional Chinese medicine, that is, erianin from Dendrobium chrysotoxum, have been described to display antiangiogenic activity by abrogation of fibroblast growth factor-induced neovascularisation.49 It is tempting to speculate that the materia medica of traditional Chinese medicine may represent a rich repertoire for novel inhibitors of tumor angiogenesis.

Our investigations with the NCI cell line panel point to hypoxia-inducible factor 1α (HIF1A), which is a promotor of angiogenesis by transcriptional activation of VEGF-A under hypoxic conditions. This is in accord with a report of Wartenberg et al.,27 who observed that ARS downregulates HIF1A. HIF1A is a regulator of neoangiogenesis in hypoxic tumor areas. Interestingly, in addition to sesquiterpenes of the ARS type, other sesquiterpenes, that is, torilin isolated from the fruits Torilis japonica (Umbelliferae), represents another angiogenesis inhibitor, which significantly downregulated the expression of hypoxia-inducible vascular endothelial growth factor and basic fibroblast growth factor-induced vessel formation.50 This indicates that sesquiterpenes might represent a novel class of angiogenesis inhibitors.

Using a microarray-based approach, we identified angiogenin (ANG)51 and the cysteine-rich angiogenic inducer 61 (CYR61)52 as determinants of cellular response to ARSs, both of which are potent mediators of new vessel formation. Furthermore, various metalloproteinases (MMP9, MMP11 and BMP1) and collagens (COL1A2, COL4A2 and COL18A1) also correlated with the cellular response to ARSs. Matrix metalloproteinases (MMP) and collagenases are lytic enzymes that degrade compounds of the extracellular matrix, a prerequisite of neovascularization. Our results with ARSs are in accord with those obtained with another compound derived from traditional Chinese medicine, curcumin, the active principle of turmeric (Curcuma longa). Synthetic derivatives of curcumin inhibited activator protein-1 transcription and tumor-induced angiogenesis by downregulation of the expression of MMP3 (stromelysin-1) and MMP-9 (gelatinase-B).53 Cucurmin and its derivatives act both in a chemopreventive as well as in a cytotoxic manner against tumors.54 Epigallocatechin gallate, the chemopreventive component of green tea, inhibits membrane-type 1 matrix metalloproteinase and tumor angiogenesis.55, 56

PLAU is responsible for the activation of plasminogen. Thrombospondin (THBS1) and Ephrin A2 represent endogenous angiogenesis inhibitors,57, 58 whose expression also correlated with cellular response to ARSs in our analysis. Genistein, another natural product with chemopreventive features, exhibited a dose-dependent inhibition of expression/excretion of vascular endothelial growth factor165, platelet-derived growth factor, tissue factor, PLAU, and matrix metalloprotease-2 and 9, respectively. On the other hand, there was an upregulation of angiogenesis inhibitors: plasminogen activator inhibitor-1, endostatin, angiostatin, and thrombospondin-1.59

ABCG1 gene, whose expression was also found to correlate with GI50 values for ARSs encodes an ATP-dependent transporter that is downregulated by the antiangiogenic antioxidants N-acetyl cysteine and (−)-epigallocatechin gallate.60 It is intriguing that many chemopreventive drugs exert antiangiogenic features as ARSs do. It is, therefore, worth hypothesizing that ARSs might also exert chemopreventive activity in addition to their cytotoxic effects.

The results of the present investigation with ARSs add further to our concept of angio-prevention61, 62 based on non-toxic drugs, which can be taken for extended periods, eventually for life-long treatments that are needed to control tumor or metastasis growth that would resume once the inhibition of angiogenesis is removed. It is unknown yet, whether ARS derivatives belong to this category, as its prolonged use has not been reported. However, given its efficacy against drug-resistant tumor cells17, 19 and the relation to antiangiogenesis, it appears to be well-suited for adjuvant therapy in combination with classical chemotherapy.

Duality of interest

None declared.

Abbreviations

ARAB:

arteanuine B

ARE:

arteether

ARM:

artemether

ARS:

artemisinin

ART:

artesunate

ARTEMIS:

artemisitene

ARTEST1/2:

dihydroartemisinyl ester stereoisomers 1/2

IC50:

inhibition concentration 50%

NCI:

National Cancer Institute

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Acknowledgements

The present work was supported by grants from CIPE-Regione Liguria, Associazione Italiana per la Ricerca sul Cancro (AIRC), Compagnia San Paolo di Torino, and MIUR-FIRB.

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Correspondence to A Albini.

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Supplementary Information accompanies the paper on The Pharmacogenomics Journal website http://www.nature.com/tpj)

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Anfosso, L., Efferth, T., Albini, A. et al. Microarray expression profiles of angiogenesis-related genes predict tumor cell response to artemisinins. Pharmacogenomics J 6, 269–278 (2006). https://doi.org/10.1038/sj.tpj.6500371

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Keywords

  • angiogenesis
  • cluster analysis
  • drug resistance
  • expression profiling
  • microarrays

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