Cytotoxic activity of secondary metabolites derived from Artemisia annua L. towards cancer cells in comparison to its designated active constituent artemisinin.
Artemisia annua L (sweet wormwood, qinhao) has traditionally been used in Chinese medicine. The isolation of artemisinin from Artemisia annua and its worldwide accepted application in malaria therapy is one of the showcase success stories of phytomedicine during the past decades. Artemisinin-type compounds are also active towards other protozoal or viral diseases as well as cancer cells in vitro and in vivo. Nowadays, Artemisia annua tea is used as a self-reliant treatment in developing countries. The unsupervised use of Artemisia annua tea has been criticized to foster the development of artemisinin resistance in malaria and cancer due to insufficient artemisinin amounts in the plant as compared to standardized tablets with isolated artemisinin or semisynthetic artemisinin derivatives. However, artemisinin is not the only bioactive compound in Artemisia annua. In the present investigation, we analyzed different Artemisia annua extracts. Dichloromethane extracts were more cytotoxic (range of [IC.sub.50]: 1.8-14.4 [micro]g/ml) than methanol extracts towards Trypanosoma b. brucei (TC221 cells). The range of [IC.sub.50] values for HeLa cancer cells was 54.1-275.5 [micro]g/ml for dichloromethane extracts and 276.3-1540.8 [micro]g/ml for methanol extracts. Cancer and trypanosomal cells did not reveal cross-resistance among other compounds of Artemisia annua, namely the artemisinin-related artemisitene and arteanuine B as well as the unrelated compounds, scopoletin and 1,8-cineole. This indicates that cells resistant to one compound retained sensitivity to another one These results were also supported by microarray-based mRNA expression profiling showing that molecular determinants of sensitivity and resistance were different between artemisinin and the other phytochemicals investigated. [c] 2011 Elsevier GmbH. All rights reserved.
Artemisia annua L (sweet wormwood, qinghao) has traditionally been used in China for the treatment of fever and chills. Artemisinin has been identified as the anti-malarial principle of the plant, and artemisinin derivatives are nowadays established as anti-malarial drugs with activity towards otherwise drug-resistant Plasmodium infections. Though originally growing in Asia and Europe, the plant is cultivated in Africa and used as tea for the treatment of malaria. Artemisinin-type compounds are not only active towards malaria, but also towards a variety of other diseases such as infections with Schistosoma, Leishmania, Trypanosoma, a wide variety of viruses and human cancer cell lines in vitro and in vivo, and even plant crown gall tumors (Efferth et al. 2003, 2008; Efferth 2005, 2007, 2009; Dell'Eva et al. 2004; Ullrich et al. 2009; Nibret and Wink 2010).
Despite artemisinin's global application in malaria therapy is one of the showcase success stories of pharmacognosy during the past decades, there are still some contradictions which have not satisfactorily been addressed as yet. Artemisinin is not or hardly water soluble, but the traditional use in Chinese medicine is based on water preparations such as tea or decoction. Nowadays, Artemisia annua tea is used as a self-reliant treatment for malaria in developing countries (Mueller et al. 2000; de Ridder et al. 2008; RITAM Artemisia annua Task Force 2006). Especially the unsupervised use of Artemisia annua tea has been criticized. It has been argued that the use of suboptimal concentrations of artemisinin would facilitate the development of resistance (Jansen 2006). It is, however, a general biological phenomenon that medicinal plants contain rather many than single pharmacologically active phytochemical compounds. This is well-known and thoroughly discussed for many years as one of the advantages of phytotherapy (including traditional Chinese medicine) compared to classical Western medicine (Wink 2008). In Artemisia annua, more than 50 different phytochemicals have been recorded (Dr. Duke's Phytochemical and Ethnobotanical Databases: http://www.arsgrin.gov/cgi-bin/duke/farmacy2.pl). It can, hence, be hypothesized that the development of resistance, which is not recorded for the use of this plant in traditional Chinese medicine, might not take place. Rather the plant provides a sort of combination therapy which engraves or even prevents the development of resistance to single bioactive plant constituents. The bioactivity of other constituents of Artemisia annua apart from artemisinin has, however, not adequately been addressed as yet.
In an effort to evaluate, whether other constituents than artemisinin in Artemisia annua may also reveal cytotoxicity towards cancer cells we focused on two artemisinin-related compounds, arteanuine B and artemisitene, and two other compounds without structural similarity to artemisinin, scopoletin and 1,8-cineole, which are also present in this plant. First, we analyzed the inhibitory activity of these compounds towards human HeLa cervical cancer cells. To prove a broader bioactivity in addition to cytotoxicity towards cancer cells, the inhibitory action towards Trypanosoma has been investigated. As a second step, we analyzed cross-resistance profiles of these compounds in the NCI panel of cell lines derived from different tumor types. Microarray-based mRNA expression profiling and COMPARE analyses revealed that different sets of genes correlated with the ICso values for these compounds, indicating that the missing cross-resistance of arteanuine B, artemisitene, 1,8-cineole or scopoletin towards artemisinin may be based on different transcriptomic expression profiles determining sensitivity or resistance to these compounds.
Materials and methods
Artemisia annua was obtained from different sources to test the variability of different specimens. Artemisia annua specimen A was obtained from a pharmacy in Germany. The origin of this specimen was China, the harvest date is unknown. Artemisia annua specimen B was grown in Tansania/Bunda and was obtained from the non-governmental organisation, Anamed (pulverized leaves; harvest date: 2008). Further specimens were also provided by Anamed: specimen C (grown in Winnenden, Germany, screen leftovers and thin caulis, harvest date: 2007) and specimen D (Winnenden, chaff and thick caulis, harvest date: 2007). A further specimen was purchased on a medicinal plant market in Shanghai, China (specimen E; harvest date: 2005).
These plant samples were macerated in dichloromethane or methanol, and left on a shaker for two days. The extracts were filtered and evaporated to dryness under reduced pressure using Rotavapor as described (Nibret and Wink 2010).
Artemisinin was obtained from Sigma-Aldrich (Taufkirchen, Germany) and artesunate was purchased from Saokim Ltd. (Hanoi, Vietnam). Arteanuine B and artemisitene were obtained from the drug repository of the Developmental Therapeutics Program of the National Cancer Institute (NCI, Bethesda, MA, USA). Scopoletin and 1,8-cineole were purchased from Sigmal-Aldrich (Taufkirchen, Germany). The chemical structures of the compounds are depicted in Fig. 1.
Determination of plant constituents by GLC-MS
The analysis was carried out on a Hewlett-Packard gas chromatograph (GC 5890II, Hewlett PACKARD; Bad Homburg, Germany) equipped with OV-1 column (30m x 0.25mm x 0.25 [micro]m; Ohio Valleys, Ohio, USA). The capillary column was directly coupled to a quadrupole mass spectrometer (SSQ7000, Thermo-Finnigan, Bremen, Germany). The operation conditions were previously described (Nibret and Wink 2010).
TC221 Trypanosoma brucei brucei cells, the causative agent of Nagana epidemic, were grown in Baltz medium supplemented with 20% inactivated fetal bovine serum (FBS) and 0.001% ([beta]-mercaptoethanol as previously described (Baltz et al. 1985).
Human HeLa cervical carcinoma cells were cultured in DMEM complete medium supplemented with 10% inactivated FBS, 1% antibiotics (penicillin, streptomycin) and 1 % NEA. Cells were maintained in a humified atmosphere containing 5% [CO.sub.2] at 37[degrees].
The panel of human tumor cell lines of the Developmental Therapeutics Program of NCI consisted of leukemia, melanoma, non-small cell lung cancer, colon cancer, renal cancer, ovarian cancer cells, tumor cells of the central nervous system, prostate carcinoma, and breast cancer. Their origin and processing have previously been described (Alley et al. 1988). These cell lines were employed to determine the cytotoxicity of the isolated compounds and of topotecan, irinotecan and SN-38 as positive controls.
Sensitivity of TC221 and HeLa cells towards extracts and pure compounds was determined using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) cell viability assay (Mosmannl983). 1 x [10.sup.5] cells/ml were seeded in 96 well plates and cultured for 24 h. They were treated with 0-5 mg/ml of Artemisia annua extract 0-5 mg/ml pure compound for 24 h. Medium was exchanged with fresh medium containing 1 mg/ml MTT and incubated for 4 h. The formazan crystals were dissolved in 100 [um]l DMSO. The absorbance was measured at 570 nm with a Tecan Safire II Reader (Tecan, Mannedorf, Switzerland). All experiments were performed in triplicates and repeated three times. The viability results of TC221 cells were additionally confirmed by counting under the microscope. The results were expressed as percentage of the control set at 100%.
The cytotoxicity of phytochemical compounds towards the NCI cell line panel was evaluated by determining the [IC.sub.50] (concentration resulting in 50% inhibition) using a modification of the sulforhodamine B assay (SRB, Sigma, MI, USA; Monks et al. 1991).
The mRNA microarray hybridization of the NCI cell line panel has been described (Scherf et al. 2000; Amundson et al. 2008) and the date das been depositied at the NCI website (http://dtp.nci.nih.gov). For hierarchical cluster analysis, objects were classified by calculation of distances according to the closeness of between-individual distances by means of hierarchical cluster analysis. All objects were assembled into a cluster tree (dendrogram). The merging of objects with similar features leads to the formation of a cluster, where the length of the branch indicates the degree of relation. The distance of a subordinate cluster to a superior cluster represents a criterion for the closeness of clusters as well as for the affiliation of single objects to clusters. Thus, objects with tightly related features appear together, while the separation in the cluster tree increases with progressive dissimilarity. Previously, cluster models have been validated for gene expression profiling and for approaching molecular pharmacology of cancer(Efferthetal. 1997; Scherf et al. 2000). Hierarchical cluster analyses applying the WARD method were done with the WinSTAT program (Kalmia, Cambridge, MA, USA). Missing values were automatically omitted by the program, and the closeness of two joined objects was calculated by the number of data points they contained. In order to calculate dis tances between all variables included in the analysis, the program automatically standardizes the variables by transforming the data with a mean = 0 and a variance =1.
For COMPARE analysis, the mRNA expression values of genes of interest and [IC.sub.50] values for artemisinin, arteanuine B, artemisitene, scopoletin, and 1,8-cineole of the NCI cell lines were selected from the NCI database (http://dtp.nci.nih.gov). The mRNA expression has been determined by microarray analyses as reported (Scherf et al. 2000). COMPARE analyses were performed to produce rank-ordered lists of genes expressed in the NCI cell lines. The methodology has been described previously in detail (Wosikowski et al. 1997). Briefly, every gene of the NCI microarray database was ranked for similarity of its mRNA expression to the [IC.sub.50] values for the corresponding compound. To derive COMPARE rankings, a scale index of correlations coefficients (R-values) was created. In the standard COMPARE approach, greater mRNA expression in cell lines correlate with enhanced drug resistance, whereas in reverse COMPARE analyses greater mRNA expression in cell lines indicated drug sensitivity.
Pearson's correlation test was used to calculate significance values and rank correlation coefficients as relative measure for the linear dependency of two variables. This test was implemented into the WinSTAT Program (Kalmia).
[FIGURE 1 OMITTED]
Cytotoxicity of extracts and single constituents of Artemisia annua towards trypanosomes
Dichloromethane or methanol extracts of six different Artemisia annua samples of different origin have been tested for their activity to inhibit the growth of trypanosomes. All extracts inhibited trypanosomal growth in a dose-dependent manner, albeit at different efficacy (Fig. 2). The [IC.sub.50] values were calculated from the dose response curves (Table 1, Supplementary file). The dichloromethane extracts were more cytotoxic (range of [IC.sub.50]: 1.8-14.4 [um]g/ml) than the methanol extracts (range of IC50: 10.8-77.5 [um]g/ml).
Three phytochemicals have been included into the analysis, which have been described as constituents of Artemisia annua (Dr. Duke's Phytochemical and Ethnobotanical Databases; http://www.ars-grin.gov/cgi-bin/duke/farmacy2.pl), i.e. artemisinin, 1,8-cineole, and scopoletin. As shown in Fig. 3 and Table 1, Supplementary file, all compounds inhibited trypanosomal growth. Of them, 1,8-cineole was the most potent one with an IC50 value of 64.6 [um]g/ml. As control drug, the semisynthetic artemisinin-derivative artesunate was used. The [IC.sub.50] value of artesunate for trypanosomes was 2.3 [um]g/100 [um]l).
Table 1 Relative abundance of artemisinin, arteanuine B and scopoletin in dichloromethane and methanol extracts of different Artemisia annua specimens as measured by GLC-MS. Specimen Solvent Artemisinin Arteanuine B Scopole A MeOH 9.96% 9.96% 80.07% A [CH.sub.2][Cl.sub.2] 18.75% 39.20% 42.05% B MeOH 47.88% 0% 52.12% B [CH.sub.2][Cl.sub.2] 92.60% 0% 7.40% C MeOH 5.87% 0% 94.13% C [CH.sub.2][Cl.sub.2] 35.41% 6.6% 57.98% D MeOH 6.93% 0% 93.07% D [CH.sub.2][Cl.sub.2] 6.40% 0% 93.60% E MeOH 5032% 7.62% 42.05% E [CH.sub.2][Cl.sub.2] 59.75% 13.70% 26.55% [CH.sub.2][Cl.sub.2], dichloromethane; MeOH, methanol.
Cytotoxicity of single constituents and extracts of Artemisia annua towards HeLa cervical cancer cells
Furthermore, we tested the activity of the Artemisia extracts towards HeLa cells (Fig. 2). All extracts tended to be less active towards HeLa cells as compared to trypanosomes. Comparable to the results obtained for trypanosomes, dichloromethane extracts were more active towards HeLa cells than methanol extracts. The range of [IC.sub.50] values was 54.1-275.5 ([um]g/ml for dichloromethane extracts and 276.3-1540.8 [um]g/ml for methanol extracts.
The dose-response curves of individual terpenoids are shown in Fig. 3. The [IC.sub.50] values in Table 1, Supplementary file show that artemisinin was more cytotoxic than 1,8-cineoIe or scopoletin. Artesunate as control drug revealed the highest cytotoxicity.
In addition to extracts of Artemisia annua and its chemical constituents, we also tested established trypanosomal drugs as positive control. The [IC.sub.50] values for diminazene, DL-a- difluoromethylornithine, metronidazole, ornidazole, and suramin in TC221 cells were in a range of 0.9-18.8 [um]g/ml (Table 1, Supplementary file). Remarkably, the activity of dichloromethane extracts of Artemisia annua ([IC.sub.50] range: 1.8-14.4 [um]g/ml) was comparable to that of these established drugs. The activity of these try-panosomal drugs towards HeLa cancer cells was weak ([IC.sub.50] range: 170.6-1502.6 [um]g/ml).
A phytochemical investigation of the extracts by GLC-MS revealed artemisinin, arteanuine B, and scopoletin in all extracts (Table 1). Artemisitene and 1,8-cineole, both of which have been reported as components of Artemisia annua (http://www.ars-grin.gov/cgi-bin/duke/farmacy2.pl) were not detected in our samples.
Cytotoxicity of phytochemicals from Artemisia annua towards the NCI cell line panel
In addition to HeLa cervical carcinoma cells, we investigated the activity of artemisinin, arteanuine B, artemisitene 1,8-cineole, and scopoletin towards cell lines of different other tumor origin. The [IC.sub.50] values for artemisinin, 1,8-cineole and scopoletin as well as two additional compounds, which are also constituents of Artemisia annua (arteanuine B and artemisitene) have been determined over a dose range of [10.sup.-8]-[10.sup.-4] M in the NCI panel of tumor cell lines and deposited at the database of the NCI's Developmental Therapeutics Program (www.dtp.nci.nih.gov). The [log.sub.10] [IC.sub.50] mean values for these cell lines grouped according to their tumor type are shown in Table 2. Across all cell lines, artemisitene was the most cytotoxic compound, whereas artemisinin and scopoletin were less active. Arteanuine B and 1,8-cineole showed intermediate inhibitory activity. Interestingly, artemisitene and 1,8-cineole exhibited different activity profiles. Leukemia ceil lines were most sensitive towards arteanuine B and artemisitene, whereas breast cancer cell lines were most affected by 1,8-cineole. Renal cancer cells were most resistant towards arteanuine B and artemisitene, and ovarian cancer cells showed the lowest inhibition by 1,8-cineole (Table 2).
Table 2 50%.inhibition.concentration ([log.sub.10] [IC.sub.50]) values (M) for five phytochemicals of the NCI cell line panel grouped according to tumor types. The [log.sub.10] [IC.sub.50] values (mean [ + or - ] SEM were determined by the sulforhodamine assay. Artemisinin Scopoletin 1,8-CineoIe ArtemisiteneB All -4.059 ([+ -4.172 ([+ -4.937 ([+ -5.134 ([+ or tumors or -]0,013) or or -]0.061) -]0.036) -]0.037) Leukemia -4.243 ([+ -4.334 ([+ -4.646 ([+ -5.425 ([+ or or -]0.067) or or -]0.094) -]0.074) -]0.133) Breast -4.053 ([+ -3.928 ([+ -6.191 ([+ -5.164 ([+ or Ca or -]0.039) or -]0 or -]0) -]0.103) Colon Ca -4.019 ([+ -4.102 ([+ -4.656 ([+ -5,187([+ or or -]0.012) or -]0.098 or -]0.090) -]0.104) Melanoma -4.002 ([+ -4.077 ([+ -4.735 ([+ -5.275 ([+ or or -]0.002) or -]0.046 or -]0.146) -]0.084) Brain -4.026 ([+ -4.247 ([+ -4.656 ([+ -5.087 ([+ or tumors or -]0.026) or or -]0.159) -]0.146) -]0.129) Lung Ca -4.078 ([+ -4.209 ([+ -4.950 ([+ -4.904 ([+ or or -]0.030) or or -]0.122 -]0.069) -]0.089) Ovarian -4.060 ([+ -4.096 ([+ -4.370 ([+ -4.958 ([+ or ca or -]0.031) or or -]0.068 -]0.095) -]0.062) Renal Ca -4.028 ([+ -4.223 ([+ -5.025 ([+ -4.519 ([+ or or -]0.016) or or -]0.216) -]0.081) -]0.128) Arteanuine All -5.372 ([+ tumors or -]0.045) Leukemia -5.881 ([+ or -]0.090) Breast -5.564 ([+ Ca or -]0) Colon Ca -5.451 ([+ or -]0.109) Melanoma -5.425 ([+ or -]0.080) Brain -5.266 ([+ tumors or -]0.076) Lung Ca -5.227 ([+ or -]0.106) Ovarian -5.137 ([+ ca or -]0.136) Renal Ca -4.077 ([+ or -]0.055)
The [IC.sub.50] values of these cell lines were subjected to Pearson's correlation test to investigate, whether cell lines resistant to one phytochemical were also resistant to another compound. The rationale behind this approach was to test the cross-resistance profile of the cell lines. Although the relationships between artemisinin, arteanuine B and artemisitene revealed P-levels below 0.05. the correlation coefficients where rather weak (R-----0.6; Table 3). The [IC.sub.50] values for 1,8-cineole and scopoletin did not correlate with those for artemisinin. Although scopoletin cytotoxicity was associated with those of 1,8-cineole and artemisitene (P = 0.04), the correlation coefficients were weak (R > 0.03).
Table 3 Cross-resistance profile of the NCI cell line panel towards five phytochemicals from Artemisia annua as determined by correlating the IC5o values by Pearson's correlation test. Artemisinin Arteanuine Artemisitene B 1,8-Cineole P-Value -0.121 -0.152 0.232 R-Value 0.190 0.152 0.043 Scopoletin P-Value 0.070 -0.117 0.231 R-Value 0.305 0.215 0.042 Artemisitene P-Value 0330 0.347 R-Value 0.007 0.008 Arteanuine B P-Value 0.263 R-Value 0.025 Scopoletin 1,8-Cineole 0.229 0.045 Scopoletin Artemisitene Arteanuine B
As a control experiment, when the cross-resistance profiles of the well-known phytochemical and established anti-cancer drug, camptothecin and its derivatives (topotecan, irinotecan, and SN-38) were analyzed, significant relationships at sufficient high correlation coefficients were found (P < 0.05 and R > 0.6; Table 4), indicating pronounced cross-resistance among these drugs.
Table 4 Cross-resistance profile of the NCI cell line panel towards camptothecin, SN-38, irinotecan. and topotecan as control drugs. Camplothecin Topotecan Irinotecan SN-38 P-Value 0.718 0.746 0.594 R-Value 7.49 x 5.69 x 3.49 x [10.sup.-11] [10.sup.-12] [10.sup.-7] Irinotecan P- 0.698 0.682 Value R-Value 1.24 x 5.38 x [10.sup.-11] [10.sup.-11] Topotecan P-Value 0.855 R-Value 4.1713 x [10.sup.-21]'
Cluster analysis of [IC.sub.50] values of the NCI cell line panel for constituents of Artemisia annua
To mimic the activity of several compounds in the plant by a computational approach, we subjected the [IC.sub.50] values of artean-uine B, artemisitene, 1,8-cineole and scopoletin to hierarchical cluster analysis. The intention was to investigate whether or not clusters with high [IC.sub.50] values for these four phytochemicals also reveal a significant probability for high [IC.sub.50] values for artemisinin. If cell lines resistant to artemisinin were also resistant to the other compounds, these cell lines would cluster together in one of the dendrogram branches obtained. Vice versa, sensitive cell lines would cluster together in another branch of the dendrogram.
[FIGURE 3 OMITTED]
[FIGURE 4 OMITTED]
The dendrogram in Fig. 4A shows three distinct branches. Most importantly, none of them significantly correlated with the [IC.sub.50] values for artemisinin. To test whether these cluster branches contain cell lines with different sensitivity to arteanuine B, artemisitene, 1,8-cineole or scopoletin. The distribution of cell lines among the three dendrogram branches in Fig. 4A shows that clusters 1 and 2 contained cell lines resistant to arteanuine B, artemisitene, or scopoletin (Table 5). Cluster 3 contained cell lines sensitive to the three compounds. These relationships were statistically significant (Table 5, [x.sup.2] test). A significant relationship to 1,8-cineole was not observed in this dendrogram. Even if we subjected only the [IC.sub.50] values for the two artemisinin-related compounds, arteanuine B and artemisitene, to hierarchical cluster analysis, no significant retionship to [IC.sub.50] values for artemisinin was observed in the cluster tree (Fig. 4B), whereas the distribution of cell lines sensitive or resistant to arteanuine or artemisitene was statistically different (Table 5). Similarly, clustering of [IC.sub.50] values for 1,8-cineole and scopoletin did not result in a dendrogram, which separates cell lines according to their resistance or sensitivity towards artemisinin (Fig. 4C). However, significant relationships were obtained for 1,8-cineole and scopoletin (Table 5). As a control, we subjected the [IC.sub.50] values for topotecan, irinotecan and SN-38 to hierarchical cluster analysis. As expected, the dendrogram branches containing cell lines resistant to topotecan, irinotecan or SN-38 were also resistant to camptothecin with statistical significance (Fig. 4D). Vice versa, cell lines sensitive to topotecan, irinotecan or SN-38 were also sensitive to camptothecin.
Table 5 Separation of clusters of the NCI cell line panel obtained by hierarchical cluster analysis shown in Fig. 4 in comparison to phytochemical constituents of Artemisia annua. The [IC.sub.50] median values of each compound were used as cut-off values to define cell lines as being sensitive or resistant. n.s., not significant(p >0.05). Sensitive Resistant X2 test Clustering of all four phytochemicals Artemisinin Cluster 1 3 11 (n = 63) Cluster 2 10 18 Cluster 3 12 9 n.s. Arteanuine B Cluster 1 5 6 (n = 56) Cluster 2 5 20 Cluster 3 18 2 P=1.76xl0 5 Artemisitene Cluster 1 3 11 (n = 56) Cluster 2 17 10 Cluster 3 8 7 P= 0.040 1,8-Cineole Cluster 1 3 11 (n = 56) Cluster 2 16 10 Cluster 3 9 7 n.s. Scopoletin Cluster 1 0 14 (n-56) Cluster 2 16 11 Cluster 3 12 3 P= 0.001 Clustering of arteanuine B and artemisitence Artemisinin Cluster 1 5 9 (n-63) Cluster 2 13 23 Cluster 3 7 6 n.s. Arteanuine B Cluster 1 2 10 (n = 55) Cluster 2 13 17 Cluster 3 13 0 P=8.05x10-5 Artemisitene Cluster 1 0 14 (n = 54) Cluster 2 22 8 Cluster 3 5 5 P = 3.48xl0"5 Clustering of 1,8-cineole and scopoletin Artemisinin Cluster 1 9 15 (n-55) Cluster 2 0 5 Cluster 3 14 12 n.s. 1,8-Cineole Cluster 1 3 22 (n"56) Cluster 2 3 2 Cluster 3 22 4 P=1.3x 10"9 Scopoletin Cluster 1 5 19 (n-56) Cluster 2 5 0 Cluster 3 18 9 P=3.09xl0-' Control clustering of topotecan, irinotean and SN-38 Camptothecin Cluster 1 1 17 (n = 69) Cluster 2 11 17 Cluster 3 23 0 P = 4.36x10-9 Topotecan Cluster 1 1 17 (n = 69) Cluster 2 12 16 Cluster 3 23 0 P=6.40x10"y Irinotecan Cluster 1 2 16 (n = 69) Cluster 2 11 17 Cluster 3 23 0 P=2.38xl0"8 SN-38 Cluster 1 0 17 (n = 59) Cluster 2 10 12 Cluster 3 20 0 P=8.46x 10-9
mRNA microarray and COMPARE analyses
We further investigated the microarray-based transcriptome-wide mRNA expression by COMPARE analyses to test, whether sensitivity and resistance to the compounds were correlated with expression of similar or different sets of genes. First, standard COMPARE analyses were performed. Lowest [IC.sub.50] values) of cell lines were correlated with the lowest mRNA expression levels of genes. Then, a reverse COMPARE analysis was done which correlated lowest [IC.sub.50] values with the highest gene expression level. Genes with correlation coefficients of R > 0.6 (standard COMPARE) and R < -0.6 (reverse COMPARE) are listed in Table 6. Importantly, no genes appeared in association with more than one of the phytochemicals, indicating that different genes may determine cellular response to these phytochemicals and that the weak or missing cross-resistance was reflected at genetic level.
Chemoprofiling of different Artemisia species
As exemplarily shown for five phytochemicals from Artemisia annua, the cellular response towards these compounds was considerably different. Therefore, we attempted to establish a chemoprofile for different Artemisia species. We subjected the chemical compositions of 11 Artemisia species (Dr. Duke's Phytochemical and Ethnobotanical Databases: http://www.arsgrin.gov/cgi-bin/duke/farmacy2.pl) to hierarchical cluster analysis. A total number of 546 phytochernicals has been included into the analysis (Supplementary Table 2) They have been subjected to hierarchical cluster analysis. As shown in the dendrogram of Fig. 5, Artemisia annua clustered closely together with A abrotanum, A. cina, A maritima, A palens, and A vulgaris in one branch of the dendrogram, while A herba-alba, A absinthium, A capillaris, A. salsoloides, and A dracunculus were less closely clustered. This dendrogram demonstrates that the considerable divergence of chemical composition in the Artemisia species enables specific clustering and separation of the species.
[FIGURE 5 OMITTED]
Whether or not cancer cells and protozoans develop resistance towards artemisinin-type compounds is a long standing discussion in malaria therapy. In vitro, it was possible to generate Plasmodium strains with acquired resistance towards artemisinin (Walker et al., 2000). The relevance for the in vivo situation was unclear, since drug-resistant Plasmodium strains have worldwide not been detected for many years. It was only recently that artemisinin-resistant P. falciparum isolates emerged at the Thailand-Cambodian border (Witkowski et al. 2010). Resistance to high dose artesunate was associated with a quiescence mechanism involving overexpression of heat shock proteins and erythrocyte surface proteins and downregulation of cell cycle regulators and DNA biosynthesis proteins. A role of genetic polymorphisms in the pfmdr1 gene has been discussed (Pickard et al. 2003). Since drug resistance to novel and effective drugs belong to the major threats of chemotherapy, WHO recommended not to use artemisinins as monotherapy, but only in combination with other antimalarials. WHO also critically acknowledged the use of artemisinin in any other form than tablets or capsules, i.e. Artemisia annua tea (www.who.int/entity/medicines/publications/traditional/ArtemisiaStatement.pdf).
In this context, it is also important to address the question, whether or not arternisinin-type drugs induce resistance in cancer cells. While artemisinin cross-resistance can be tested in multidrug-resistant cell lines (Efferth et al. 2003), stable artemisinin-resistant cell line has not been described thus far. In the present investigation, we focused on phytochemicals in Artemisia annua in addition to artemisinin. While >50 compounds have been described in Artemisia annua (http://www.ars-grin.gov/cgi-bin/duke/farmacy2.pl), we exemplarily selected four compounds of interest, two artemisinin-type compounds (artemisitene and arteanuine B) and two unrelated ones (1,8-cineole, scopoletin). All of these compounds revealed cytotoxicity towards cancer and try-panosomal cells, but no cross-resistance of the NCI cell line panel was observed between artemisinin and these four phytochemicals. A general concept of drug resistance has been described by Goldie and Coldman (1985). Starting point of this seminal work were observations with bacterial strains which acquired resistance towards viruses by spontaneous mutations (Luria and Delbruck 1943). Goldie and Coldman and later on other groups developed mathematical models which explained drug resistance of tumors on the basis of spontaneous mutations of single cells. Upon drug treatment, such resistant cells have a survival advantage compared to the majority of non-mutated sensitive cells and overgrow the entire tumor cell population (Dy and Adjei 2008). Sublethal drug concentrations act as an evolutionary selection pressure for the development of resistant tumors. This can be prevented by the simultaneous treatment with a second drug. The assumption is that small subpopulations resistant to one drug are not resistant at the same time to a second drug. Therefore, they are killed by the second drug and development of resistance to the first drug is avoided. This is the basic principle of combination chemotherapy for tumors developed in the 1970s and 1980s and still well established in clinical oncology up to now. Transferring this concept to medicinal plants e.g. A annua provides a similar scenario: small subpopula-tions resistant to artemisinin do not survive when they are treated with 1,8-cineole. Hence, artemisinin resistance of the entire tumor cell population may be avoided. This point of view has not extensively been discussed so far in the field of phytotherapy. We have shown that artemisinin-resistant cell lines are not cross-resistant to other compounds of Artemisia annua such as 1,8-cineole. Therefore, when it is apparent that artemisinin-resistant subclones of a tumor can efficiently be killed by 1,8-cineole preventing the emergence of artemisinin-resistant tumors.
COMPARE ID GenBank Symbol coefficient Artemisinin - standard COMPARE 0.819 GC54762 AB023220 USP20 0.771 GC183783 NM005187 CBFA2T3 0.766 GC96878 U43185 STAT5 A 0.765 GC101502 Z22576 CD69 0.756 GC100401 X59834 GLUL 0.753 GC182328 NM003189 TALI 0.752 CC166288 AL590118 SERHL2 0.742 GC90143 M6358990 None 0.734 GC31019 AF054186 EEF1E1 0.734 GC33623 X07109 PRKCB1 0.733 GC165496 AL161952 None 0.727 GC182816 NM003888 ALDH1A2 0.725 GC183873 NM005320 HIST1H1D 0.723 GC187047 NM016520 C9orf78 0.72 GC36324 Z93241 None 0.711 GC81738 AJ245416 LSM2 0.71 GC191046 U08626 None 0.706 GC186656 NM015905 TRIM24 0.7 GC32454 M6358990 None 0.7 GC29282 Z82206 None 0.693 GC156430 AI335888 ATP9B 0.686 GC188575 NM020993 BCL7A 0.676 GC182953 NM004117 FKBP5 0.668 GC174612 BF056790 LOC91431 0.668 GC99087 W60897 ZNRD1 0.66 GC32262 AF001862 FYB Artemisinin - reverse COMPARE -0.63 GC11521 H29810 None -0.601 GC13148 H55766 None Artemisitene - standard COMPARE 0.712 GC31589 T89651 None 0.669 GC37806 D14530 RPS23 0.644 GC30164 AF054187 NACA 0.634 GC37651 Z25749 None 0.628 GC15116 N68924 None 0.628 GC148889 AA524093 FBX041 0.626 GC192507 Z98950 None 0.624 GC16228 W78173 None 0.62 GC34926 X79563 RPS21 0.62 GC38852 ABO19409 None 0.618 GC34785 AC004537 None 0.616 GC37574 S79522 RPS27A 0.612 GC30713 U68140 NVL 0.61 GC17766 W87741 MYC 0.608 GC37836 U59151 DKC1 0.605 GC36655 U14966 RPL5 0.604 GC36609 X80822 RPL18A 0.602 GC30254 AA044823 RPL27 Artemisitene - reverse COMPARE -0.653 GC182056 NM002844 PTPRK -0.627 GC18210 AA009800 GSTT2B -0.615 GC97127 U53204 PLEC1 -0.609 GC91265 N26926 GNA11 -0.601 GC31852 AF037339 CLPTM1 Arteanuine B - reverse COMPARE -0.619 GC60519 ZNF488 1,8-Cineole - standard COMPARE 0.646 GC147599 AF169689 PCDHA6 0.634 GC176788 BF792773 FIBCD1 0.627 GC167434 AV710838 BC02 0.615 GC97912 U91512 NINJ1 0.612 GC165127 AL136870 KIAA1787 0.612 GC167406 AV706915 MTHFD2L 0.602 GC98312 W23068 HSPB8 0.601 GC160320 AI831738 DDX59 1,8-Cineofe - reverse COMPARE -0.683 GC64100 AI375128 FSD2 Scopoletin - standard COMPARE 0.618 GC183972 NM005463 None 0.606 GC17951 AA001636 None COMPARE Name Function coefficient Artemisinin - standard COMPARE 0.819 Ubiquitin specific peptidase 20 Ubiquitin thiolesterase, peptidase 0.771 Core-binding factor, runt domain, Transcription a subunit 2; translocated to, 3 factor 0.766 Signal transducer and activator Signal transducer of transcription 5 and transcription factor 0.765 CD69 molecule Transmembrane receptor 0.756 Glutamate-ammonia ligase Glutamate ammonia (glutamine synthetase) ligase 0.753 T-cell acute lymphocytic leukemia Transcription 1 regulator 0.752 Serine hydrolase-like 2 Serine hydrolase 0.742 Not specified Unknown 0.734 Kukaryotic translation elongation Translation factor 1 epsilon 1 factor 0.734 Protein kinase C, [beta] 1 Calcium-activated protein kinase 0.733 Not specified Unknown 0.727 Aldehyde dehydrogenase 1 family, Oxidoreductase member A2 0.725 Histone cluster 1, H1d Involved in histone condensation 0.723 Chromosome 9 open reading frame Unknown 78 0.72 Not specified Unknown 0.711 LSM2 homologue, U6 small nuclear Protein kinase; RNA associated (S. cerevisiae) involved in pre-mRMA splicing 0.71 Not specified Unknown 0.706 Tripartite motif-containing 24 Transcription coactivator 0.7 Not specified Unknown 0.7 Not specified Unknown 0.693 ATPase, class II, type 9B ATPase 0.686 B-cell CLL/Iymphoma 7A Putative F-actin cross-linking protein 0.676 FK506-binding protein 5 FK506 binding 0.668 Prematurely terminated mRNA decay Zinc ion binding factor-like 0.668 Zinc ribbon domain containing 1 Transcription regulator 0.66 FYN-binding protein Adapter protein of (FYB-120/130) FYN and LCP2 signaling Artemisinin - reverse COMPARE -0.63 Not specified Unknown -0.601 Not specified Unknown Artemisitene - standard COMPARE 0.712 Transcribed locus, strongly Unknown similar to NP.775369.1 ribosomal protein L36A 0.669 Ribosomal protein S23 Structural constituent of ribosome 0.644 Nascent polypeptide-associated Binds nascent complex a subunit proteins emerging from ribosome 0.634 Not specified Unknown 0.628 Not specified Unknown 0.628 F-box protein 41 Component of ubiquitin ligase complex 0.626 Not specified Unknown 0.624 Not specified Unknown 0.62 Ribosomal protein S21 Structural constituent of ribosome 0.62 Not specified Unknown 0.618 Not specified Unknown 0.616 Ribosomal protein S27a Structural constituent of ribosome 0.612 Nuclear VCP-Iike Unknown 0.61 Avian myelocytomastosis viral Transcription (v-myc) oncogene homologue factor 0.608 Dyskeratosis congenita 1, Required for dyskerin ribosome biogenesis and telomere maintenance 0.605 Ribosomal protein L5 Structural constittient of ribosome 0.604 Ribosomal protein L18a Structural constituent of ribosome 0.602 Ribosomal protein L27 Structural constituent of ribosome Artemisitene - reverse COMPARE -0.653 Protein tyrosine phosphatase, Regulation of cell receptor type, K contact and adhesion -0.627 Glutathione S-transferase theta Detoxification of 2B electrophiles. Phase II enzyme -0.615 Plectin 1, intermediate filament Structural binding protein 500 kDa constituent of muscle -0.609 Guanine nucleotide binding Signal transducer protein (G protein), a 11 (Gq class) -0.601 Cleft lip and palate associated Cell transmembrane protein 1 differentiation Arteanuine B - reverse COMPARE -0.619 Zinc finger protein 488 Transcriptional repressor 1,8-Cineole - standard COMPARE 0.646 Protocadherin [alpha] 9 Cell adhesion 0.634 Fibrinogen C domain containing 1 Receptor binding activity 0.627 [beta] -Carotene oxygenase 2 Oxidoreductase 0.615 Ninjurin 1 Cell adhesion 0.612 KIAA1787 protein Unknown 0.612 MethyienetetrabydrofoJate Oxidoreductase dehyhdro-genase(NADP+-dependent) 2-like 0.602 Heat shock protein 22 kDa protein Chaperone 8 0.601 DEAD (Asp-Glu-Ala-Asp) box ATP-dependent polypeptide 59 helicase 1,8-Cineofe - reverse COMPARE -0.683 Fibronectin type HI and SPRY Unknown domain containing 2 Scopoletin - standard COMPARE 0.618 Not specified Unknown 0.606 Not specified Unknown information on gene functions was taken from the OMIM database, NCI, USA. (http://www.ncbi.nlm.nih.gov/Omim/) and from the GeneCard database of the Weizman Institute of Science, Rehovot, Israel http://bioinfo.weizmann.ac.il/cards/index.html).
Our in vitro model with single compounds tested towards a panel of cell lines does not reflect all complex interactions in herbal mixtures of compounds. The activity of a mixture of compounds is constituted by additive and synergistic compound interactions. Synergistic interactions need a common mechanism, e.g. a common target where they bind to or a common pathway they inhibit. From an evolutionary point of view, synergistic compound interactions are not likely formed by chance. They need a co-evolution under appropriate selection pressure. The biosynthesis of different phytochemicals in plants with different models of action (as illustrated by different gene expression profiled) does not necessarily require co-evolutionary conditions. It can, therefore, be speculated that additive compound interactions occur with higher probability than synergistic ones.
The missing cross-resistance of the NCI cell line panel to several phytochemicals of Artemisia annua speaks for a sustained activity of Artemisia annua extracts, even if cancer cells would resist the detrimental effects of one of these compounds. Whether this result can be transferred from the in vitro to the in vivo situation remains to be seen. In addition to cellular determinants of sensitivity and resistance, the response of living organisms towards cytotoxic compounds is influenced by other factors such as immune system, angiogenesis, pharmacokinetics, etc. A clinical study with a limited number of patients showed that Artemisia annua tea was capable to reduce the parasitic load of malaria patients, but that the recrudescence rates were high (Mueller et al. 2004). Artemisia annua tea is widely used outside the official health care systems by local people and non-governmental organizations in Africa. Therefore, clinical validation is still warranted to see whether the lack of pronounced cross-resistance profiles in vitro among the four phytochemicals and artemisinin may indicate that herbal Artemisia annua extracts reveal activity towards heterogenous cancer cell populations with different genetic background and response rates towards these natural products.
This point of view is also supported by the microarray-based mRNA expression profiles identified by COMPARE and hierarchical cluster analyses. These expression profiles did not only considerably differ between artemisinin and the structurally unrelated compounds 1,8-cineole and scopoletin, but also to the related arteanuine B and artemisitene. This indicates that the molecular determinants of sensitivity and resistance of these phytochemicals are not identical and that different signaling routes and genetic networks may be active in tumor cells upon treatment with artemisinin compared to the other natural products analyzed. This is also consistent with recent pharmacogenomic data obtained for artesunate, a semisynthetic derivative of artemisinin (Sertel et at 2010).
Among the various Artemisia annua extracts which have been analyzed in the present study, a considerable heterogeneity of inhibitory activity was observed. This heterogeneity was obvious among samples of different origin and points to an important aspect in phytotherapy in general. Differing bioactivities mirror biological variability between different plant individuals as well as differences in growth and cultivation conditions (soil composition, climate, harvest, processing and storage conditions). The differences observed in the present investigation clearly show the necessity for standardized cultivation conditions (e.g. by the rules of good agricultural practice, GAP, etc.).
In addition to heterogeneous bioactivities between different samples, we also found varying cytotoxicities of extracts from different parts of the plant obtained from the same plant sample. Most active were methanol extracts from leaves, while dichloromethane extracts from chaff and thick caulis revealed the weakest growth inhibitory activity. This is a well-known phenomenon in pharmacognosy and a specific terminology has been established characterizing the morphological structure of a plant, e.g. flos, fructus, semen kerb[R], folia, summhates, ramulus, stipes, caulis, lignum, cortex, radix, bulbus, rhizoma, and tuber drugs. Commonly, Artemisia annua is used as herbal drug (Herba Artemisiae annuae). The data found in our investigation showed that the leaves were more active than other parts of the plant. Hence, the leave drug (Folia Artemisiae annuae) is more recommendable. This is true for the cytotoxic activity towards both cancer cells and trypanosomal cells. Our data are in accord with previous results on the antitrypanosomal activity of artemisinins and Artemisia annua extracts (Mishina et al. 2007; Nibret and Wink 2010). Furthermore, we showed here that phytochemicals in addition to artemisinin such as 1,8-cineole and scopoletin also revealed activity against trypanosomal cells. Hence, the bioactivity of Artemisia annua is not solely due to artemisinin.
Another point that has to be critically discussed is that dichloromethane extracts were more cytotoxic than the corresponding methanol extracts. This indicates that phytochemicals solved in non-polar solvents such as dichloromethane are more cytotoxic and/or present in higher amounts than compounds that can be found in polar methanol extracts. Artemisinin as best known phytochemical of Artemisia annua cannot be solved in polar solvents such as methanol or water. This may raise doubts about the activity of tea preparations for unsupervised self-reliant treatments. Either the tea might be inactive or other compounds than artemisinin confer bioactivity of Artemisia annua tea. Another possibility is that tea preparation might contain solving mediators facilitating the solubility of artemisinin.
Finally, we applied hierarchical cluster analysis for chemical profiling of diverse Artemisia species. Phytochemical profiling has been used in the past to test the hypothesis that the phytochemical constitution of plants can be used for taxonomy of plants, although not all species have been analyzed to the same extent. While this approach seems attractive at first sight, its taxonomic value has been controversially discussed, because the phytochemical constitution can vary within the same species due to varying external stimuli and growth conditions (Wink 2003; Wink et al. 2010). In the present investigation, we found that artemisinin was only present in Artemisia annua, but not in other Artemisia species. Although our analysis was limited to only 11 Artemisia species, we can conclude that artemisinin is not a lead compound for the genus Artemisia. These results are consistent with other investigations showing that artemisinin is present in some, but not ail Artemisia species (Liersch et al. 1986; Luo et al. 1991; Tan et al. 1998; Erdemoglu et al. 2007; Nibret and Wink 2010). Furthermore, there was no other compound present in all Artemisia species analyzed, indicating that there may also be no other Artemisia-specific lead compound. Some natural products appeared in more than one Artemisia species, e.g. 1,8-cineole or scopoletin. These compounds have a wide distribution over many plant families.
In conclusion, the present study showed that there is no pronounced cross-resistance among different phytochemicals of Artemisia annua. This result obtained by cytotoxicity assays was confirmed by microarray-based mRNA expression profiles, which revealed individual pharmacogenomic signatures with no overlap of genes for each of the phytochemicals tested.
Appendix A. Supplementary data
Supplementary data associated with this article can be found, in the online version, at doi:10.l0l6/j.phymed.20l 1.06.008.
0944-7113/$ - see front matter [c] 2011 Elsevier GmbH. All rights reserved, doi: 10.1016/j.phymed.2011.06.008
* Corresponding author at: Department of Pharmaceutical Biology, Institute of Pharmacy and Biochemistry, University of Mainz, Staudinger Weg 5, 55128 Mainz, Germany, Tel.: +49 6131 392575; fax: +49 6131 3923752.
E-mail address: efferth[congruent to]uni-mainz.de (T. Efferth).
Alley, M.C., Scudiero, D.A., Monks, A., Hursey, M.L, Czerwinski, M.J., Fine, D.L, Abbott, B.J., Mayo.J.C., Shoemaker, R.H., Boyd, M.R., 1988. Feasibility of drug screening with panels of human tumor cell lines using a microculture tetrazolium assay. Cancer Res. 48,589-601.
Amundson, S.A., Do, K.T., Vinikoor, LC, Lee, R.A., Koch-Paiz, C.A., Ahn, J., Reimers, M., Chen, Y., Scudiero, D.A., Weinstein, J.N., Trent, J.M., Bittner, M.L, Meltzer, P.S., Fornace Jr., A.J., 2008. Integrating global gene expression and radiation survival parameters across the 60 cell lines of the National Cancer Institute Anticancer Drug Screen. Cancer Res. 68,415-424.
Baltz, T., Baltz, D.( Giroud, C, Crockett, J., 1985. Cultivation in a semi-defined medium of animal infective forms of Trypanosoma brucei, T. equiperdum, T. evansi, T. rhodiense and T. gambiense. EMBO J. 4,1273-1277.
Dell'Eva, R., Pfeffer, U., Vene, R., Anfosso, L, Forlani, A., Albini, A., Efferth, T., 2004. Inhibition of angiogenesis in vivo and growth of Kaposi's sarcoma xenograft tumors by the anti-malarial artesunate. Biochem. Pharmacol. 68, 2359-2366.
Dy, G.K., Adjei, A.A., 2008. Systemic cancer therapy: evolution over the last 60 years. Cancer 113(7 Suppl.), 1857-1887.
Efferth, T., Fabry, U., Osieka, R., 1997. Apoptosis and resistance to daunorubicin in human leukemic cells. Leukemia 11,1180-1186.
Efferth, T., Sauerbrey, A., Olbrich, A., Gebhart, E., Rauch, P., Weber, H.O., Hengstler, J.G., Halatsch, M.E., Volm, M., Tew, K.D., Ross, D.D., Funk, J.O., 2003. Molecular modes of action of artesunate in tumor cell lines. Mol. Pharmacol. 64, 382-394.
Efferth,T., 2005. Mechanistic perspectives for 1,2,4-trioxanes in anti-cancer therapy. Drug Resist. Updat. 8, 85-97.
Efferth,T., 2007. WillmarSchwabe Award 2006: antiplasmodial and antitumor activity of artemisinin - from bench to bedside. Planta Med. 73,299-309.
Efferth, T., Romero, M.R., Wolf, D.G., Stamminger, T.t Marin, J.J., Marschali, M., 2008. The antiviral activities of artemisinin and artesunate. Clin. Infect. Dis. 47, 804-811.
Efferth, T., 2009. Artemisinin - a versatile weapon from traditional Chinese medicine. In: Ramawat, K.G. (Ed.), Herbal Drugs: Ethnobotany to Modern Medicine. Springer, Berlin, Heidelberg, pp. 173-193.
Erdemoglu, N., Orhan, I., Kartal, M., Adigiizel, N., Bani, B., 2007. Determination of artemisinin in selected Artemisia L. species of Turkey by reversed phase HPLC. Rec. Nat. Prod. 1,2-3.
Goldie, J.H., Coldman, A.J., 1985. A model for tumor response to chemotherapy: an integration of the stem cell and somatic mutation hypotheses. Cancer Invest. 3 (6), 553-564.
Jansen, F.H., 2006. The herbal tea approach for artemisinin as a therapy for malaria? Trans. R. Soc. Trop. Med. Hyg. 100, 285-286.
Liersch, R., Soicke, H., Stehr, C, Ttillner, H.U., 1986. Formation of artemisinin in Artemisia annua during one vegetation period*,!. Planta Med. 52,387-390.
Luo, S.D., Ning, B.M., Hu, W.Y., Xie, J.L., 1991. Studies on peroxides of Artemisia lamcea. J. Nat. Prod. 54,573-575.
Luria, S.E., Delbriick, M., 1943. Mutations of bacteria from virus sensitivity to virus resistance. Genetics 28 (6), 491-511.
Mishina, Y.V., Krishna, S., Haynes, R.K., Meade, J.C, 2007. Artemisinins inhibit Trypanosoma cruzi and Trypanosoma brucei rhodesiense in vitro growth. Antimicrob. Agents Chemother. 51,1852-1854.
Monks, A., Scudiero, D., Skehan, P., Shoemaker, R., Paull, K., Vistica, D., Hose, C, Langley, J., Cronise, P., Vaigro-Wolff, A., 1991. Feasibility of a high-flux anticancer drug screen using a diverse panel of cultured human tumor cell lines, j. Natl. Cancer Inst. 83,757-766.
Mosmann,T., 1983. Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. J. Immunol. Methods 65,55-63.
Mueller, M.S., Karhagomba, I.B., Hirt, H.M., Wemakor, E., 2000. The potential of Artemisia annua L as a locally produced remedy for malaria in the tropics: agricultural, chemical and clinical aspects. J. Ethnopharmacol. 73,487-493.
Mueller, M.S., Runyambo, N., Wagner, I., Borrmann, S., Dietz, K., Heide, L, 2004. Randomized controlled trial of a traditional preparation of Artemisia annua L., (Annual Wormwood) in the treatment of malaria. Trans. R. Soc.Trop. Med. Hyg. 98,318-321.
Nibret, E., Wink, M., 2010. Volatile components of four Ethiopian Artemisia species extracts and their in vitro antitrypanosomal and cytotoxic activities. Phytomedicine 17, 369-374.
Pickard, A.L, Wongsrichanalai, C, Purfield, A., Kamwendo, D., Emery, K., Zalewski, C, Kawamoto, F., Miller, R.S., Meshnick, S.R., 2003. Resistance to antimalarials in Southeast Asia and genetic polymorphisms in pfmdr1. Antimicrob. Agents Chemother. 47,2418-2423.de Ridder, S., van der Kooy, F., Verpoorte, R., 2008. Artemisia annua as a self-reliant treatment for malaria in developing countries. J. Ethnopharmacol. 120,302-314.
RITAM Artemisia annua Task Force, Willcox, M., Falquet, J., Ferreira, J.F., Gilbert, B., Hsu, E., de Magalhes, P.M., Plaizier-Vercammen, J., Sharma, V.P., Wright, C.W., Yaode, W., 2006. Artemisia annua as a herbal tea for malaria. Afr. J. Tradit. Complement. Altern. Med. 4,121-123.
Scherf, U., Ross, D.T., Waltham, M., Smith, L.H., Lee.J.K.Tanabe, L, Kohn, K.W., Reinhold, W.C, Myers, T.G., Andrews, DT, Scudiero, DA, Eisen, M.B., Sausville, E.A., Pommier, Y., Botstein, D., Brown, P.O., Weinstein, J.N., 2000. A gene expression database for the molecular pharmacology of cancer. Nat. Genet. 24,236-244.
Sertel, S., Eichhorn, T., Simon, C.H., Plinkert, P.K.Johnson, S.W., Efferth, T., 2010. Pharmacogenomic identification of c-Myc/Max-regulated genes associated with cytotoxicity of artesunate towards human colon, ovarian and lung cancer cell lines. Molecules 15,2886-2910.
Tan, R.X., Zheng, W.F., Tang, H.Q., 1998. Biologically active substances from the genus Artemisia. Planta Med. 64,295-302.
Ullrich, CI., von Eitzen-Ritter, M., Jockel, A., Efferth, T., 2009. Prevention of plant crown gall tumor development by the anti-malarial artesunate of Artemisia annua. J. Cultivated Plants 61,31 -36.
Walker, D.J., Pitsch, J.L, Peng, M.M., Robinson, B.L, Peters, W., Bhisutthibhan, J., Meshnick, S.R., 2000. Mechanisms of artemisinin resistance in the rodent malaria pathogen Plasmodium yoelil. Antimicrob. Agents Chemother. 44,344-347.
Wink, M., 2003. Evolution of secondary metabolites from an ecological and molecular phylogenetic perspective. Phytochemistry 64,3-19.
Wink, M., 2008. Evolutionary advantage and molecular modes of action of multicomponent mixtures used in phytomedicine. Curr. Drug Metab. 9,996-1009.
Wink, M., Botschen, F., Gosmann, C, Schafer, H., Waterman, P.G., 2010. Chemotaxonomy seen from a phylogenetic perspective and evolution of secondary metabolism. In: Wink, M. (Ed.), Biochemistry of Plant Secondary Metabolism, vol. 40, second ed. Blackwell, Annual Plant Reviews.
Witkowski, B., Leli[union]vre, J., Barragan, M.J., Laurent, V., Su, X.Z., Berry, A., BenoitVical, F., 2010. Increased tolerance to artemisinin in Plasmodium falciparum is mediated by a quiescence mechanism. Antimicrob. Agents Chemother. 54, 1872-1877.
Wosikowski, K., Schuurhuis, D.Johnson, K., Paull, K.D., Myers, T.G., Weinstein, J.N., Bates, S.E., 1997. Identification of epidermal growth factor receptor and erbB2 pathway inhibitors by correlation with gene expression patterns. J. Natl. Cancer Inst. 89, 1505-1515.
Thomas Efferth (a), (*), Florian Herrmann (b), Ahmed Tahrani (b), Michael Wink (b)
a Department of Pharmaceutical Biology, Institute of Pharmacy and Biochemistry,University of Mainz, Mainz, Germany
b Department of Biology, Institute of Pharmacy and Molecular Biotechnology, Heidelberg University, Heidelberg, Germany
|Printer friendly Cite/link Email Feedback|
|Author:||Efferth, Thomas; Herrmann, Florian; Tahrani, Ahmed; Wink, Michael|
|Publication:||Phytomedicine: International Journal of Phytotherapy & Phytopharmacology|
|Date:||Aug 15, 2011|
|Previous Article:||The effects of rose hip (Rosa canina) on plasma antioxidative activity and C-reactive protein in patients with rheumatoid arthritis and normal...|
|Next Article:||Bioactive components from the tea polyphenols influence on endogenous antioxidant defense system and modulate inflammatory cytokines after total-body...|