The lignan, (-)-sesamin reveals cytotoxicity toward cancer cells: pharmacogenomic determination of genes associated with sensitivity or resistance.
(-)-Sesamin is a lignan present in sesam oil and a number of medicinal plants. It exerts various pharmacological effects, such as prevention of hyperlipidemia, hypertension, and carcinogenesis. Moreover, (-)-sesamin has chemopreventive and anticancer activity in vitro and in vivo. Multidrug resistance (MDR) of tumors leads to fatal treatment outcome in many patients and novel drugs able to kill multidrugresistant cells are urgently needed. P-glycoprotein (MDR1/ABCB1) is the best known ATP- binding cassette (ABC) drug transporter mediating MDR. ABCB5 is a close relative to ABCBI, which also mediates MDR. We found that the mRNA expressions of ABCBI and ABCB5 were not related to the 50% inhibition concentrations ([IC.sub.50]) for (-)-sesamin in a panel of 55 cell lines of the National Cancer Institute, USA. Furthermore, (-)-sesamin inhibited ABCB1- or ABCB5-overexpressing cells with similar efficacy than their drug-sensitive parental counterparts. In addition to ABC transporter- mediated MDR, we attempted to identify other molecular determinants of (-)-sesamin resistance. For this reason, we performed COMPARE and hierarchical cluster analyses of the transcriptome-wide microarray-based mRNA expression of the NCI cell panel. Twenty-three genes were identified, whose mRNA expression correlated with the 1C50 values for (-)-sesamin. These genes code for proteins of different biological functions, i.e. ribosomal proteins, components of the mitochondrial respiratory chain, proteins involved in RNA metabolism, protein biosynthesis, or glucose and fatty acid metabolism. Subjecting this set of genes to cluster analysis showed that the cell lines were assembled in the resulting dendrogram according to their responsiveness to (-)-sesamin. In conclusion, (-)-sesamin is not involved in MDR mediated by ABCBI or ABCB5 and may be valuable to bypass chemoresistance of refractory tumors. The microarray expression profile, which predicted sensitivity or resistance of tumor cells to (-)-sesamin consisted of genes, which do not belong to the classical resistance mechanisms to established anticancer drugs.
Sesamin is a major lipid-soluble lignan in the oil of Sesamum indicum and other sesam species, such as the Sudanese S. radiatum and S. angustifolium (Kamal-Eldin et al., 1991). It can also be found in other plants, such as flaxseed (Linum utisatissimum) (Truan et al., 2012), the stem bark of Acanthopanax senticosus (Hibasami et al., 2000), Hyptis tomentosa (Kingston et al., 1979), Machilus thunbergii (Lee et al., 2004), Aiouea trinervis (Garcez et al., 2005), Peperomia pellucida (Xu et al., 2006), Achillea clavennae (Trifunovic et al., 2006), Knema glauca (Rangkaew et al., 2009), Cinnamomum kotoense (Wang et al., 2010), leaves of Homalomena wendlandii (Sanchez et al., 2012), Zanthoxylum ailanthoides (Cao et al., 2013), Acronychia pedunculata (Kozaki et al., 2013). Sesam oil is commonly used as fat-reducing dietary oil, because of its cholesterol and triglyceride-reducing properties (Kamal-Eldin et al., 2011). In addition to prevention of hyperlipidemia, sesamin has more pharmacological effects, such as prevention of hypertension and carcinogenesis (Kamal-Eldin et al., 2011).
(-)-Sesamin exerts cytotoxic activity toward cancer cells and induces apoptosis in vitro (Deng et al., 2013; Hibasami et al., 2000; Miyahara et al., 2000; Wang et al., 2010; Yokota et al., 2007). Remarkably, an anticancer effect of sesamin has also been reported in athymic mice transplanted with human MCF-7 breast cancer cells (Truan et al., 2012). Furthermore, the dietary supplementation of sesamin on 7,12-dimethylbenz[a]anthracene (DMBA)-induced breast carcinogenesis led to a significantly reduced appearance of breast cancers compared to mice not supplemented with sesamin (Flirose et al., 1992).
These anticancer effects of (-)-sesamin in vivo are remarkable, since sesamin is metabolized in animals and men to enterolactones (Liu et al., 2006; Penalvo et al., 2005), indicating that the anticancer and chemopreventive effects are not inhibited by metabolization.
This opens the possibility, as to whether (-)-sesamin in addition to its chemopreventive function as dietary supplement might serve as lead compound for cancer drug development. Novel cancer drugs are urgently needed, because of high side effects of anticancer drugs and the development of drug resistance. A major challenge in cancer treatment is the development of multidrug resistance, i.e. cross-resistance toward many different drugs at the same time, a phenomenon which dramatically reduces the chances for successful cancer chemotherapy and ultimately the cure of cancer patients.
A well-known cause of multidrug resistance is the ATP-binding cassette (ABC) transporter P-glycoprotein (MDR1/ABCB1), which expels cytotoxic drugs at the expense of ATP hydrolysis. The ABC transporter family is considered as one of the largest protein families in biology (Dassa and Bouige, 2001). P-glycoprotein is able to transport cytotoxic drugs as well as amphiphilic, neutral or cationic molecules. Besides its expression in many tumor types (Efferth and Osieka, 1993) P-glycoprotein is normally found in the liver, kidney, colon, small intestine and blood-brain barrier, where absorption, distribution, metabolism and excretion of various drugs take place (Childs and Ling, 1994; Cordon-Cardo et al., 1990). Anticancer drugs that are transported by P-glycoprotein are structurally and functionally unrelated such as Vinca alkaloids (vinblastine, vincristine), taxanes (e.g. paclitaxel and docetaxel), epipodophyllotoxins (e.g. teneposide, etoposide) and anthracyclines (e.g. doxorubicin, daunorubicin) (Efferth, 2001; Gillet et al., 2007; Gottesman et al., 2002), other drug substrates of P-Glycoprotein include calcium channel blockers (verapamil), antiarrhythmics (quinidine), steroids (dexamethasone), anti-parasitics (ivermectin), and few antidepressants and antiepileptic drugs (Ford et al., 1996; Schinkel and Jonker, 2003). Consequently, P-glycoprotein considered as one of the most important drug transporters in pharmacology.
Recently, another member of the B-subfamily of human ABC transporters came into the focus, ABCB5. This efflux transporter also extrudes multiple drugs out of cancer cells, although the profile of transported anticancer drugs seems not be fully characterized as yet (Buckley et al., 1995; Chen et al., 2009; Frank et al., 2005; Kawanobe et al., 2012; Luo et al., 2012; Yang et al., 2012). ABCB5 is involved in melanin transport during melanogenesis and is highly expressed in melanoma (Chen et al., 2009). Since its expression is not restricted to melanoma and many other tumor types also express ABCB5 (Cheung et al., 2011; Grimm et al., 2012; Wilson et al., 2011; Yang et al., 2012), the contribution of ABCB5 to clinical multidrug resistance still needs to be established.
The aim of the present investigation was, firstly, to investigate whether or not tumor cells specifically over-expressing ABCB1- and ABCB5-type P-glycoproteins are cross-resistant to (-)-sesamin. In addition to ABC transporter-mediated drug resistance, we were secondly interested to identify other molecular determinants of (-)-sesamin resistance. For this reason, we performed COMPARE and hierarchical cluster analyses of the transcriptome-wide microarray-based mRNA expression of cell lines of the Developmental Therapeutics Program (DTP) of the National Cancer Institute (NCI), USA.
Material and methods
CCRF-CEM and CEM/ADR5000 cells: The maintenance of the cells and the generation of the CEM/ADR5000 subline have been reported (Kimmig et al., 1990). CEM/ADR5000 cells specifically overexpress P-glycoprotein (MDR1/ABCB1), but not other ABC transporters (Efferth et al., 2003; Gillet et al., 2004). The cross-resistance profile of CEM/ADR5000 cells has been reported (Efferth et al., 2008).
HEK293 wild type and FIEK293/ABCB5 transfectant cell lines: The generation and maintenance of HEK293 cells transfected with a cDNA for ABCB5 has been reported (Kawanobe et al., 2012). Non-transfected HEK293 cells have been used as control. The resistance of HEK293/ABCB5 transfectants to anthracyclines and taxanes has been described (Kawanobe et al., 2012).
NCI cell lines: The origin and processing of the cell lines of the Developmental Therapeutics Program (DTP) of the National Cancer Institute (NCI), USA, have been previously described in detail (Alley et al., 1988). The panel consisted of 60 cell lines derived from leukemia, colon cancer, breast cancer, ovarian cancer, lung cancer, prostate cancer, CNS tumors, melanoma, and kidney cancer. Fifty-five cell lines have been tested for their (-)-sesamin sensitivity.
Resazurin assay: Resazurin assay based on reduction of the indicator dye, resazurin, to the highly fluorescent resorufin by viable cells (O'Brien et al., 2000). Non-viable cells lose their ability to reduce resazurin dye, consequently no excitation signal appear. The procedure has been previously described in detail (Kuete et al., 2012).
Sulforhodamine assay: The cytotoxicity of (-)-sesamin has been determined by the sulforhodamine assay. A detailed protocol of this assay has been reported elsewhere (Rubinstein et al., 1990).
COMPARE analysis is internet-based algorithm for transcriptome-wide search of correlations between gene expressions and drug response of the NCI cell line panel (http://dtp.nci.nih.gov). The COMPARE method is based on Pearson's rank correlation test (Pauli et al., 1989). We performed COMPARE analyses of the [IC.sub.50] values for (-)-sesamin and the microarray-based transcriptome-wide mRNA expression levels in the NCI cell line panel. Standard and reverse COMPARE were performed to determine the resistance and sensitive candidates genes respectively, according to their expressions, in which cell lines that were most inhibited by (-)-sesamin (lowest [IC.sub.50] values) were correlated with the lowest mRNA expression levels of genes (resistance genes) while the most inhibited cell lines were correlated with the highest gene expression (sensitivity genes). To obtain COMPARE rankings, a scale index of correlation coefficients (R-values) has been generated.
We performed agglomerative hierarchical cluster analysis (WARD method) using the WinSTAT program (Kalmia Inc., Cambridge, MA) to cluster the mRNA expression of genes identified by COMPARE analysis. Each individual cluster is merged with another depending on closeness of their features, which is depicted as cluster tree or dendrogram. In order to calculate distances of all variables included in the analysis, the program automatically standardizes the variables by transforming the data with a mean = 0 and a variance = 1.
Pearson's correlation test was used to calculate significance values and rank correlation coefficients as a relative measure for the linear dependency of two variables. The [chi square]-test was performed using the WinSTAT program (Kalmia Inc., Cambridge, MA) to proof bivariate frequency distributions for pairs of nominal scaled variables for dependencies.
Cytotoxicity of (-)-sesamin to cancer cells
Among the entire panel of 55 cell lines, the [log.sub.10][IC.sub.50] values were in a range from -8.0 M (CAK1 cells) to -4.0 M (several cell lines). If the [log.sub.10][IC.sub.50] values were grouped according to the tumor origin of the cell lines, it can be seen that on average leukemia and melanoma cell lines were most sensitive toward (-)-sesamin, while brain tumor and ovarian cancer cell lines were most resistant. Cell lines of all other tumor types were of intermediate sensitivity (Fig-1)?
Sensitivity of (-)-sesamin in multidrug-resistant cells overexpressing ABCB1 or ABCB5
It is worth speculating that the varying sensitivities of the cell lines are due to differences in the expression of genes determining the response of tumor cells to cytotoxic compounds. As P-glycoprotein (MDR1/ABCB1) is a major determinant of cellular responsiveness toward anticancer drugs, we correlated the [log.sub.10] [IC.sub.50] values for (-)-sesamin of the NCI cell lines with different parameters of P-glycoprotein. We used the mRNA expression (as determined by RT-PCR or microarray hybridization) of the P-glycoprotein-encoding MDR1/ABCB1 gene as well as the accumulation rates of rhodamine 123 (R123) in the cell lines. R123 is a P-glycoprotein substrate and the flow cytometric determination of R123 uptake can serve as functional assay for P-glycoprotein activity. As shown in Table 1, none of these parameters revealed significant correlations with the [log.sub.10] [IC.sub.50] values for (-)-sesamin, indicating that the cellular sensitivity of (-)-sesamin was not related to the expression of MDR1/ABCB1 or the activity of P-glycoprotein. For comparison, the established anticancer drug doxorubicin was used as positive control. Doxorubicin is a well-known substrate of P-glycoprotein. As expected, the [log.sub.10] [IC.sub.50] values for doxorubicin significantly correlated with all P-glycoprotein/MDR1/ABCB1 parameters (Table 1).
To corroborate this correlation analysis, we tested the sensitivity of (-)-sesamin in the drug-sensitive, wild type CCRF-CEM cell line and its P-glycoprotein/MDR1/ABCB1-overexpressing subline, CEM/ADR5000. Indeed, CEM/ADR5000 cells were not cross-resistant to (-)-sesamin, indicating that (-)-sesamin is not a substrate of P-glycoprotein (Fig. 2A). In this context, the chemical structure of (-)-sesamin may play a role: the compound contains only two methyldioxol-groups, but no phenolic OH-groups. This may prevent degradation by metabolic processes. P-glycoprotein is a phase III protein in the pharmacokinetic metabolism and (-)-sesamin may not be able to bind to P-glycoprotein.
Furthermore, we were interested, whether or not the novel ABC transporter subfamily B member, ABCB5, is a determinant of resistance toward (-)-sesamin. The [log.sub.10] [IC.sub.50] values for mitox- antrone as positive control showed significant correlations to the mRNA expression of ABCB5 either measured by RT-PCR and microarray-hybridization (Table 2). In contrast, no correlation of [log.sub.10] [IC.sub.50] values for (-)-sesamin was found to mRNA expression as determined by RT-PCR and an inverse correlation to the mRNA expression measured by microarray hybridization (Table 2). Both cases do not show that increasing ABCB5 expression is associated with increasing resistance to (-)-sesamin. Thus, there was no clue for a role of ABCB5 for (-)-sesamin resistance.
As confirmatory experiment, we used F1EK293/ABCB5 cells, which were transfected with a cDNA for ABCB5 and wild type HEK293 cells to treat them with (-)-sesamin. ABCB5-transfectant cells were not resistant to (-)-sesamin compared to non-transfected wild type cells (Fig. 2B). verifying the results obtained by the correlation analysis of the NCI cell line panel.
COMPARE and cluster analyses of microarray data
From the experiments with ABCB1 and ABCB5, it is apparent that both efflux pumps to not mediate resistance to (-)-sesamin. However, Fig. 1 clearly shows that cell lines from different tumor types reveal different sensitivities, meaning that there should exist indeed cellular factors determining the sensitivity or resistance of tumor cells to this compound. As a screening strategy to identify possible candidate genes relevant for cellular responsiveness to (-)-sesamin, we mined the transcriptome-wide mRNA expression of the NCI cell lines in the NCI database and correlated the mRNA expression values to the [log.sub.10] [IC.sub.50] values for (-)-sesamin. This is a bioinformatic gene-hunting approach to find novel putative molecular determinants of resistance to (-)-sesamin. We performed a transcriptome-wide COMPARE analysis to generate a ranking list of genes, whose mRNA expression directly or inversely correlate with the [log.sub.10] [IC.sub.50] values for (-)-sesamin of all NCI cell lines. Only correlations with correlation coefficients of R > 0.5 (direct correlations) or R < -0.5 (inverse correlations) were listed in (Table 3). The proteins encoded by these genes have diverse biological functions such as catalytic activity in metabolism pathways or components of the mitochondrial respiratory chain, ribosome constituents or proteins involved in transcriptional or translational regulation, etc.
The mRNA expression values for the genes listed in Table 3 of all NCI cell lines were subsequently subjected to hierarchical cluster analysis, in order to find out, whether groups or clusters of cell lines can be identified with similar behavior after exposure to (-)-sesamin. The dendrogram of this cluster analysis showed three main branches in the cluster tree (Fig. 3).
Afterwards, the [IC.sub.50] values for (-)-sesamin, which were not included in the cluster analysis were assigned to the corresponding position of the cell lines in the cluster tree. The distribution cell lines being either sensitive or resistant to (-)-sesamin is shown in Table 4. This distribution among the three clusters was significantly different from each other (P = 1.05 x [10.sup.-6]). Cluster 1 contained solely cell lines resistant to (-)-sesamin, whereas cluster 3 contained only sensitive ones. Cluster 2 was of a mixed type. The median value of the [log.sub.10] [IC.sub.50] values was used as cutoff value to define cell lines as being sensitive or resistant to (-)-sesamin.
Cytotoxicity of other lignans toward tumor cells
The considerable cytotoxicity of (-)-sesamin raises the question about the activity of lignans in general against cancer cells. Therefore, we screened the NCI database for other lignans. We identified 14 further compounds in addition to (-)-sesamin. The mean values of the individual [IC.sub.50] values of all cell lines of the NCI panel for all of these lignans have been plotted in Fig. 4. These mean [IC.sub.50] values were in a range of 1.34 x [10.sup.-8] M (deoxypodophyllotoxin) to 7.54 x [10.sup.-5] M (neolignan from Clerodendron inerme) (Fig. 4).
Relevance of ABCB1 and ABCB5 for (-)-sesamin
In a search for cellular and molecular determinants of responsiveness of tumor cells to (-)-sesamin, we investigated the role of the multidrug transporter, P-glycoprotein (MDR1/ABCB1). It was pleasing that the expression and function of P-glycoprotein did not correlate with the [IC.sub.50] values for (-)-sesamin of the NCI cell line panel and that this results could be verified by a pair of P-glycoprotein-expressing and non-expressing cell lines (CCRF/CEM and CEM/ADR5000). Thus, P-glycoprotein does not confer resistance to (-)-sesamin and (-)-sesamin may not be a substrate of this efflux transporter, although CEM/ADR5000 cells are resistant to many different established anticancer drugs (anthracyclines, Vinca alkaloids, epipodophyllotoxins, tananes and others) (Efferth et al., 2008). This implies that (-)-sesamin might be used in cancer therapy to kill refractory, P-glycoprotein positive tumors, which are not responsive anymore to established cancer drugs. Hence, (-)-sesamin is able to bypass P-glycoprotein-mediated multidrug resistance.
In addition to our investigation, Nabekura et al. (2008) observed that (-)-sesamin was able to increase doxorubicin accumulation in cancer cells by inhibition of P-glycoprotein's efflux function. Taken together the results of our analysis and the data of Nabekura and colleagues, (-)-sesamin might be a valuable component for combination therapy regimen to improve the eradication of cancer cells either by bypassing multidrug resistance or inhibition the P-glycoprotein-mediated efflux of standard anticancer drugs (Nabekura et al., 2008).
In a comparable manner to P-glycoproteinIMDR1/ABCB1, cross-resistance of ABCB5-expressing tumor cells to (-)-sesamin was neither observed in the NCI cell lines nor in HEK293/ABCB5 transfectant cells. This is a remarkable result, since ABCB5 attracted attention not only as close relative to ABCB1, but also because of its expression in cancer stem-like cells (Gazzaniga et al., 2010; Grimm et al., 2012). These cells are frequently resistant to chemo- and radiotherapy (Efferth, 2012). Furthermore, HEK293/ABCB5 cells have been described to exert resistance toward doxorubicin, paclitaxel, and docetaxel (Kawanobe et al., 2012). Therefore, the fact that HEK293/ABCB5 transfectants did not reveal cross-resistance toward (-)-sesamin implies that (-)-sesamin might be also suitable to treat therapy-resistant cancer stem-like cells.
Microarray-based determination of genes associated with (-)-sesamin resistance
Since ABCB1 and ABCB5 were not involved in resistance toward (-)-sesamin, we performed a microarray-based transcriptome-wide screening of genes by means of COMPARE analysis, whose mRNA expression correlated with the [log.sub.10][IC.sub.50] values for (- )sesamin. This approach enables to find putative candidate genes associated with sensitivity or resistance to cytotoxic compounds (Evans et al., 2008; Fagan et al., 2012; Luzina and Popov, 2012; Wosikowski et al., 2000). Genes from diverse biological groups were found, indicating that (-)-sesamin may act by multiple pathways against cancer cells. Multifactorial activities are a typical feature of natural compounds (Efferth and Koch, 2011), and seem also to apply for (-)-sesamin. We found genes, whose gene products are either ribosomal proteins (RPL1, RPL6, EPL30, RPS17) or proteins involved in transcriptional or post-translational regulation (MEF2D, NARS2; PATZ1, TTL), in RNA metabolism (PABPC1), or in protein biosynthesis (SLC6A17). Also genes encoding proteins associated with the mitochondrial respiratory chain (UQCRB, NDUFB9) or involved in glucose and fatty acid metabolism (PDK4) were found.
Almost 70 proteins are known that bind to the rRNA in the small and large ribosomal subunits and an increasing number of these proteins are described to have extraribosomal functions (Wool, 1996; Wool et al., 1995). One of these functions relates to response of tumor cells to chemotherapy. Ribosomal proteins such as RPL4, RPL5, RPL13, RPL23, RPS28 have been reported to be over-expressed in multidrug resistant cells (Bertram et al., 1998; Hu et al., 2000; Johnsson et al., 2000; Shi et al., 2004). Interestingly, RPL6 which also appeared in our COMPARE analysis confers multidrug resistance (Du et al., 2005). In light of these data, it is worth speculating that the genes encoding ribosomal proteins identified in the present investigation might represent also resistance factors for (-)-sesamin.
The identification of genes encoding proteins necessary for RNA metabolism, protein biosynthesis and other transcriptional or posttranslational processes speaks for an interaction of (-)-sesamin with growth regulatory processes. The proliferative activity of tumors is an important determinant of drug resistance (Efferth et al., 2008) and may also be relevant for (-)-sesamin.
Furthermore, components of the mitochondrial respiratory chain appeared in our COMPARE analysis. Since the mitochondrial respiratory chain is linked with resistance to anticancer drugs (Jia et al., 1997; Oliva et al., 2010; Roesch et al., 2013), it can be imagined that this mechanism is also relevant for (-)-sesamin. Hints for an involvement of glucose and fatty acid metabolism by the PDI<4 gene are not only conceivable with the well-known role of (-)sesamin in the regulation hyperlipidemia, but also in the context of cancer. Both fatty acid and glucose metabolism are altered in cancer cells and contribute to aggressiveness and therapy resistance of tumors (Butler et al., 2013; Jang et al., 2013). A role for (-)-sesamin responsiveness of cancer cells can, therefore, be suggested.
The potential relevance of all these genes for sensitivity and resistance of the NCI cell line panel against (-)-sesamin was further emphasized by cluster analysis. Remarkably, the mRNA expression values of the genes identified by COMPARE analysis alone were sufficient to generate an ordering of cell lines in the dendrogram, which predicted whether a tumor cell line was sensitive or resistant to (-)-sesamin. The prediction of drug resistance by mRNA expression profiles relates to an intense discussion in clinical oncology and several commercial microarray platforms are available to test drug sensitivity in clinical tumors (Walther and Sklar, 2011).
The concept of personalized medicine in clinical oncology is to determine responsiveness of tumors before chemotherapy to optimize therapy protocols with the most active drugs for each individual patient (Efferth, 2010; Volm et al., 2004). The definition of an expression profile which correlated to cellular response toward (-)-sesamin indicates that the concept of prediction of chemosensitivity may also be applied to cytotoxic natural compounds.
Cytotoxicity toward other lignans toward tumor cells
A comparison of the cytotoxicity of (-)-sesamin with those of other lignans deposited in the NCI database showed that lignans represent an interesting class of chemicals with activity toward cancer cells. Beside well-established anticancer drugs such as etoposide and temposide, highly cytotoxic phytochemicals such as podophyllotoxin were included in this panel of compounds. Podophyllotoxin from Podophyllum peltatum is too toxic for cancer treatment, but served as lead compound for the semi-synthetic derivatives, etoposide and temposide which belong to the standard armatory of chemotherapeutics in clinical oncology.
It can be speculated that compounds revealing comparably high cytotoxicity than podophyllotoxin such as deoxypodophyllotoxin or austrobailignan-1 might also be too toxic for use in cancer therapy. The cytotoxicity of (-)-sesamin was intermediately to weak in this panel of lignans. This result can be taken as a hint that (-)-sesamin may be a promising candidate for cancer drug development.
Received 9 November 2013
Received in revised form 29 November 2013
Accepted 11 January 2014
Conflict of interest
We declare that there is no conflict of interest.
We are grateful to the Sudanese Government for providing a stipend to M.S.
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Mohamed Saeed (a), Hassan Khalid (b), Yoshikazu Sugimoto (c), Thomas Efferth (a), *
(a) Department of Pharmaceutical Biology, Institute of Pharmacy and Biochemistry, Johannes Gutenberg University, Mainz, Germany
(b) The Medicinal and Aromatic Plants Research Institute (MAPRI), National Centre for Research, Khartoum, Sudan
(c) Division of Chemotherapy, Faculty of Pharmacy, Keio University, Tokyo, Japan
* Corresponding author at: Department of Pharmaceutical Biology, Institute of Pharmacy and Biochemistry, Johannes Gutenberg University, Staudinger Weg 5, 55128 Mainz, Germany. Tel.:+49 6131 3925751; fax: +49 6131 23752.
E-mail address: firstname.lastname@example.org (T. Efferth).
Table 1 Correlation of [log.sub.10] [IC.sub.50] values for (-)-sesamin and doxorubicin to gain of the chromosomal locus of the MDR1-ABCB1 gene (7q21), expression of MDR1-ABCB1 mRNA by RT-PCR, and P-glycoprotein function (cellular rhodamine 123 accumulation) in the NCI tumor cell lines. Doxorubicin was used as positive control, as it is a well-known substrate of P-glycoprotein. The data for doxorubicin have been previously published (Kuete and Efferth, 2013) and are shown here only for comparison. The analysis was performed by means of Pearson's rank correlation test. (-)-Sesamin Chromosomal Correlation coefficient (R) * locus 7q21 Statistical significance (P) ** MDR1/ABCB1 mRNA Correlation coefficient (R) * (RT-PCR) Statistical significance (P) ** MDR1/ABCB1 mRNA Correlation coefficient (R) * (microarray) Statistical significance (P) ** Rhodamine 123 Correlation coefficient (R) * accumulation Statistical significance (P) ** Doxorubicin Chromosomal 0.513 locus 7q21 3.05 x [10.sup.-5] MDR1/ABCB1 mRNA 0.379 (RT-PCR) 0.003 MDR1/ABCB1 mRNA 0.560 (microarray) 1.68 x [10.sup.-6] Rhodamine 123 0.454 accumulation 1.50 x [10.sup.-4] * R<0.30. ** P>0.05. Table 2 Correlation of [log.sub.10] [IC.sub.50] values for (-)-sesamin and mRNA expression of ABCB5 (as measured by RT-PCR or microarray hybridization) in the NCI tumor ceil lines. The analysis was performed by means of Pearson's rank correlation test. (-)-Sesamin ABCB5 mRNA Correlation coefficient (R) * (RT-PCR) Statistical significance (P) ** ABCB5 mRNA Correlation coefficient (R) -0.333 (microarray) Statistical significance (P) 0.006 Mitoxantrone ABCB5 mRNA Correlation coefficient (R) 0.300 (RT-PCR) Statistical significance (P) 0.010 ABCB5 mRNA Correlation coefficient (R) 0.353 (microarray) Statistical significance (P) 0.003 * R<0.30. ** P>0.05. Table 3 Correlation of constitutive mRNA expression of genes identified by COMPARE analysis with logio IC50 values for (-)-sesamin of the NCI tumor cell lines. COMPARE Experimental GenBank Gene symbol coefficient ID accession 0.535 GC75008 A1806403 Unknown 0.511 GC50495 AA811257 Unknown 0.502 GC43879 AA417187 Unknown -0.529 GC29848 T79616 UQCRB -0.524 GC190792 T54159 STARD5 -0.521 GC173005 BE350882 DLL3 -0.513 GC184302 NM_005920 MEF2D -0.513 GC34930 X69391 RPL6 -0.512 GC34929 Z48501 PABPCl -0.51 GC159789 AI807017 PATZ1 -0.508 GC48488 AA702175 TTL -0.507 GC34935 M17886 RPLP1 -0.504 GC27310 X51420 TYRPl -0.503 GC73073 AI758901 ESCOl -0.503 GC78899 A1928869 NDUFB9 -0.502 GC89236 L37112 AVPR1B -0.501 GC78878 AI928491 PDK4 -0.501 GC156397 A1333058 SLC6A17 COMPARE Name coefficient 0.535 Transcribed locus 0.511 Unknown 0.502 Unknown -0.529 Ubiquinol-cytochrome c reductase binding protein -0.524 StAR-related lipid transfer (START) domain containing -0.521 Delta-like 3 (Drosophila) -0.513 Myocyte enhancer factor 2D -0.513 Ribosomal protein L6 -0.512 Poly(A) binding protein, cytoplasmic 1 -0.51 POZ(BTB)and AT hook containing zinc finger 1 -0.508 Tubulin tyrosine ligase -0.507 Ribosomal protein, large. P1 -0.504 Tyrosinase-related protein 1 -0.503 Establishment of cohesion 1 homologue 1 (S. cerevisiae) -0.503 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 9, 22 kDa -0.502 Arginine vasopressin receptor IB -0.501 Pyruvate dehydrogenase kinase, isozyme 4 -0.501 Solute carrier family 6, member 17 COMPARE Function coefficient 0.535 Not available 0.511 Not available 0.502 Not available -0.529 Component of mitochondrial respiratory chain (complex III or cytochrome b-cl complex) -0.524 Intracellular sterol transport -0.521 Inhibits primary neurogenesis -0.513 Transcriptional activator for growth factor- and stress-induced genes -0.513 Ribosome constituent -0.512 RNA metabolism (pre-mRNA splicing) -0.51 Transcriptional repressor -0.508 Post-translational tyrosinylation of alpha-tubulin -0.507 Elongation step of protein synthesis -0.504 Oxidation of 5,6dihydroxyindole-2-carboxylic acid (DHICA) into indole-5,6quinone-2-carboxylic acid -0.503 Establishment of sister chromatid cohesion and coupling to DNA replication process -0.503 Accessory subunit of the mitochondrial membrane respiratory chain NADH dehydrogenase (complex I) -0.502 Receptor for arginine vasopressin -0.501 Serine/threonine kinase regulating glucose and fatty acid metabolism -0.501 Sodium-dependent vesicular amino acid transporter Positive correlation coefficients indicate direct correlations negative ones indicate inverse correlations. Only correlations of R>0.5 and R</0.5 were taken into account. Information on gene functions was taken from the OM1M 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.htm). Table 4 Separation of clusters of NCI tumor cell lines obtained by hierarchical cluster analysis shown in Fig.3 in comparison to drug sensitivity. Partition (a) Cluster 1 Cluster 2 Cluster 3 Sensitive [less than or 0 17 12 equal to] 4.16M Resistant >-4.16 M 15 13 0 [chi square]-test: P = 1.05 x [10.sup.-6]. (a) The median log,0 IC50 value (-4.16M) for (-)-sesamin was used as cut-off to separate tumor cell lines as being "sensitive" or "resistant".