Correlating gene expression with chemical scaffolds of cytotoxic agents: ellipticines as substrates and inhibitors of MDR1

Anticancer Thiosemicarbazones: Chemical Properties, Interaction with Iron Metabolism, and Resistance Development

SIGNIFICANCE

During the past decades, thiosemicarbazones were clinically developed for a variety of diseases, including tuberculosis, viral infections, malaria, and cancer. With regard to malignant diseases, the class of α-N-heterocyclic thiosemicarbazones, and here especially 3-aminopyridine-2-carboxaldehyde thiosemicarbazone (Triapine), was intensively developed in multiple clinical phase I/II trials. Recent Advances: Very recently, two new derivatives, namely COTI-2 and di-2-pyridylketone 4-cyclohexyl-4-methyl-3-thiosemicarbazone (DpC) have entered phase I evaluation. Based on the strong metal-chelating/metal-interacting properties of thiosemicarbazones, interference with the cellular iron (and copper) homeostasis is assumed to play an important role in their biological activity.

CRITICAL ISSUES

In this review, we summarize and analyze the data on the interaction of (α-N-heterocyclic) thiosemicarbazones with iron, with the special aim of bridging the current knowledge on their mode of action from chemistry to (cell) biology. In addition, we highlight the difference to classical iron(III) chelators such as desferrioxamine (DFO), which are used for the treatment of iron overload.

FUTURE DIRECTIONS

We want to emphasize that thiosemicarbazones are not solely removing iron from the cells/organism. In contrast, they should be considered as iron-interacting drugs influencing diverse biological pathways in a complex and multi-faceted mode of action. Consequently, in addition to the discussion of physicochemical properties (e.g., complex stability, redox activity), this review contains an overview on the diversity of cellular thiosemicarbazone targets and drug resistance mechanisms.

Application of alkaloids in reversing multidrug resistance in human cancers

Multidrug resistance (MDR) in human cancer is one of greatest challenges in cancer therapy. Natural products, especially the alkaloids, exert reversed effects on MDR with low toxicity, by interacting with various targets. In this review article, we summarize the recent progress made in the research of the main alkaloids, including classification, function, mechanism, research status, and application in reversing MDR.

Overcoming chemoresistance in prostate cancer with Chinese medicine Tripterygium wilfordii via multiple mechanisms

A leading cause of cancer chemotherapy failure is chemoresistance, which often involves multiple mechanisms. Chinese medicines (CM) usually contain multiple components which could potentially target many mechanisms simultaneously and may offer an advantage over single compounds that target one mechanism at a time. The purpose of this study was to investigate the chemosensitizing effect (CE) of a specific CM, Tripterygium wilfordii (TW), on prostate cancer cells resistant to docetaxel (Dtx) and identify the potential mechanisms. The CE of TW (in combination with Dtx) was evaluated in two Dtx resistant prostate cancer cell lines (PC3-TxR and DU145-TxR) and the efficacy of the combination for resistant PC3-TxR tumor was investigated using a xenograft mouse model. For mechanistic study, the inhibitory effect of TW on P-glycoprotein activity was assessed. In addition, novel gene targets of TW were identified using DNA microarray and quantitative PCR. Results showed that TW induced a CE of 8 and >38 folds in PC3-TxR and DU145-TxR cells, respectively with Dtx IC50 reversed back to that of the sensitive parent cells. An optimum dose of TW+Dtx significantly retarded tumor growth in mice compared to TW or Dtx alone. TW inhibited P-glycoprotein activity and induced a significant gene expression changes in genes related to angiogenesis, cell cycle regulation and differentiation. Our in vitro and in vivo studies demonstrate that TW in combination with Dtx was able to overcome the chemoresistance and suppress resistant prostate tumor growth via multi-mechanisms.

An integrative analysis of small molecule transcriptional responses in the human malaria parasite Plasmodium falciparum

Background

Transcriptional responses to small molecules can provide insights into drug mode of action (MOA). The capacity of the human malaria parasite, Plasmodium falciparum, to respond specifically to transcriptional perturbations has been unclear based on past approaches. Here, we present the most extensive profiling to date of the parasite’s transcriptional responsiveness to thirty-one chemically and functionally diverse small molecules.

Methods

We exposed two laboratory strains of the human malaria parasite P. falciparum to brief treatments of thirty-one chemically and functionally diverse small molecules associated with biological effects across multiple pathways based on various levels of evidence. We investigated the impact of chemical composition and MOA on gene expression similarities that arise between perturbations by various compounds. To determine the target biological pathways for each small molecule, we developed a novel framework for encoding small molecule effects on a spectra of biological processes or GO functions that are enriched in the differentially expressed genes of a given small molecule perturbation.

Results

We find that small molecules associated with similar transcriptional responses contain similar chemical features, and/ or have a shared MOA. The approach also revealed complex relationships between drugs and biological pathways that are missed by most exisiting approaches. For example, the approach was able to partition small molecule responses into drug-specific effects versus non-specific effects.

Conclusions

Our work provides a new framework for linking transcriptional responses to drug MOA in P. falciparum and can be generalized for the same purpose in other organisms.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2165-1) contains supplementary material, which is available to authorized users.

Impact of terminal dimethylation on the resistance profile of α-N-heterocyclic thiosemicarbazones

Triapine is an α-N-heterocyclic thiosemicarbazone with promising anticancer activity against hematologic malignancies but widely ineffective against solid tumor types in clinical trials. The anticancer activity of thiosemicarbazones can be dramatically increased by terminal dimethylation. KP1089 is a gallium compound containing two terminal dimethylated thiosemicarbazone ligands. To gain insights on the vulnerability of this highly active terminal dimethylated thiosemicarbazone to drug resistance mechanisms, a new cell model with acquired resistance against the lead compound KP1089 was established. Subsequent genomic analyses (arrayCGH and FISH) revealed amplification of the ABCC1 gene on double minute chromosomal DNA in KP1089-resistant cells as well as overexpression of ABCC1 and ABCG2 on the protein level. KP1089 was further confirmed as a substrate of ABCC1 and ABCG2 but not of ABCB1 using a panel of ABC transporter-overexpressing cell models as well as ABC transporter inhibitors. Moreover, glutathione depletion strongly enhanced KP1089 activity, although no glutathione conjugate formation by glutathione-S-transferase was observed. Thus, a co-transport of KP1089 together with glutathione is suggested. Finally, a panel of thiosemicarbazone derivatives was tested on the new KP1089-resistant cell line. Notably, KP1089-resistant cells were not cross-resistant against thiosemicarbazones lacking terminal dimethylation (e.g. Triapine) which are less active than KP1089. This suggests that terminal dimethylation of thiosemicarbazones – linked with distinctly enhanced anticancer activity – leads to altered resistance profiles compared to classical thiosemicarbazones making this compound class of interest for further (pre)clinical evaluation.

HIGHLIGHTING RELATIONSHIPS BETWEEN HETEROGENEOUS BIOLOGICAL DATA THROUGH GRAPHICAL DISPLAYS BASED ON REGULARIZED CANONICAL CORRELATION ANALYSIS

Biological data produced by high throughput technologies are becoming more and more abundant and are arousing many statistical questions. This paper addresses one of them; when gene expression data are jointly observed with other variables with the purpose of highlighting significant relationships between gene expression and these other variables. One relevant statistical method to explore these relationships is Canonical Correlation Analysis (CCA). Unfortunately, in the context of postgenomic data, the number of variables (gene expressions) is usually greater than the number of units (samples) and CCA cannot be directly performed: a regularized version is required.

We applied regularized CCA on data sets from two different studies and show that its interpretation evidences both previously validated relationships and new hypothesis. From the first data sets (nutrigenomic study), we generated interesting hypothesis on the transcription factor pathways potentially linking hepatic fatty acids and gene expression. From the second data sets (pharmacogenomic study on the NCI-60 cancer cell line panel), we identified new ABC transporter candidate substrates which relevancy is illustrated by the concomitant identification of several known substrates.

In conclusion, the use of regularized CCA is likely to be relevant to a number and a variety of biological experiments involving the generation of high throughput data. We demonstrated here its ability to enhance the range of relevant conclusions that can be drawn from these relatively expensive experiments.

Mutagen structure and transcriptional response: induction of distinct transcriptional profiles in Salmonella TA100 by the drinking-water mutagen MX and its homologues

The relationship between chemical structure and biological activity has been examined for various compounds and endpoints for decades. To explore this question relative to global gene expression, we performed microarray analysis of Salmonella TA100 after treatment under conditions of mutagenesis by the drinking-water mutagen MX and two of its structural homologues, BA-1, and BA-4. Approximately 50% of the genes expressed differentially following MX treatment were unique to MX; the corresponding percentages for BA-1 and BA-4 were 91 and 80, respectively. Among these mutagens, there was no overlap of altered Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways or RegulonDB regulons. Among the 25 Comprehensive Microbial Resource functions altered by these mutagens, only four were altered by more than one mutagen. Thus, the three structural homologues produced distinctly different transcriptional profiles, with none having a single altered KEGG pathway in common. We tested whether structural similarity between a xenobiotic and endogenous metabolites could explain transcriptional changes. For the 830 intracellular metabolites in Salmonella that we examined, BA-1 had a high degree of structural similarity to 2-isopropylmaleate, which is the substrate for isopropylmalate isomerase. The transcription of the gene for this enzyme was suppressed twofold in BA-1-treated cells. Finally, the distinct transcriptional responses of the three structural homologues were not predicted by a set of phenotypic anchors, including mutagenic potency, cytotoxicity, mutation spectra, and physicochemical properties. Ultimately, explanations for varying transcriptional responses induced by compounds with similar structures await an improved understanding of the interactions between small molecules and the cellular machinery.

Identification of compounds selectively killing multidrug-resistant cancer cells

There is a great need for the development of novel chemotherapeutic agents that overcome the emergence of multidrug resistance (MDR) in cancer. We catalogued the National Cancer Institute's DTP drug repository in search of compounds showing increased toxicity in MDR cells. By comparing the sensitivity of parental cell lines with MDR derivatives, we identified 22 compounds possessing MDR-selective activity. Analysis of structural congeners led to the identification of 15 additional drugs showing increased toxicity in Pgp-expressing cells. Analysis of MDR-selective compounds led to the formulation of structure activity relationships and pharmacophore models. This data mining coupled with experimental data points to a possible mechanism of action linked to metal chelation. Taken together, the discovery of the MDR-selective compound set shows the robustness of the developing field of MDR-targeting therapy as a new strategy for resolving Pgp-mediated MDR.

Genetic variations and gene expression of transporters in drug disposition and response

BACKGROUND

The importance of transporters in drug disposition and response has led to increasing interest in genetic variations and expression differences of their genes.

OBJECTIVE

This review summarizes: i) genetic variations in transporters and associated drug response; and ii) a pharmacogenomic approach to correlate transporter expression and drug response.

METHODS

Several transporters in ATP-binding cassette family and solute carrier family are discussed.

CONCLUSION

The field of transporter pharmacogenomics is in its early stage. Transporter expression at mRNA levels could be more directly related to their functions and more practical to be assayed in high throughput. Correlating microarray expression of transporters with anticancer drug activity in the NCI-60 panel has provided an approach for identifying drug-transporter relationships and predicting drug response.

Ellipticine derivative NSC 338258 represents a potential new antineoplastic agent for the treatment of multiple myeloma

High-risk multiple myeloma can be correlated with amplification and overexpression of the cell cycle regulator CKS1B. Herein, we used the COMPARE algorithm to correlate high expression of CKS1B mRNA in the NCI-60 cell line panel with the concentration causing 50% growth inhibition (GI(50)) of >40,000 synthetic compounds. This led to the identification of NSC 338258 (EPED3), a highly stable, hydrophilic derivative of the plant alkaloid ellipticine. In vitro, this synthetic anticancer compound exhibits dramatic cytotoxic activity against myeloma cells grown in suspension or in coculture with stromal cells. EPED3-induced cell cycle arrest and an apoptotic progression that appear to be a consequence of the instantaneous effect of the drug on cytoplasmic organelles, particularly mitochondria. Disruption of mitochondria and cytoplasmic distribution of cytochrome c initiated the intracellular proteolytic cascade through the intrinsic apoptotic pathway. EPED3 is able to induce apoptosis in myeloma cells with de novo or acquired resistance to commonly administered antimyeloma agents. Collectively, our data suggest that EPED3 targets mitochondrial function to rapidly deplete chemical energy and initiate apoptosis in myeloma cells at nanomolar concentrations while leaving stromal cells unharmed.

Anticancer medicines in development: assessment of bioactivity profiles within the National Cancer Institute anticancer screening data

We present an analysis of current anticancer compounds that are in phase I, II, or III clinical trials and their structural analogues that have been screened in the National Cancer Institute (NCI) anticancer screening program. Bioactivity profiles, measured across the NCI 60 cell lines, were examined for a correspondence between the type of cancer proposed for clinical testing and selective sensitivity to appropriately matched tumor subpanels in the NCI screen. These results find strongest support for using the NCI anticancer screen to select analogue compounds with selective sensitivity to the leukemia, colon, central nervous system, melanoma, and ovarian panels, but not for renal, prostate, and breast panels. These results are extended to applications of two-dimensional structural features to further refine compound selections based on tumor panel sensitivity obtained from tumor screening results.

Cystine-glutamate transporter SLC7A11 mediates resistance to geldanamycin but not to 17-(allylamino)-17-demethoxygeldanamycin

The cystine-glutamate transporter SLC7A11 has been implicated in chemoresistance, by supplying cystine to the cell for glutathione maintenance. In the NCI-60 cell panel, SLC7A11 expression shows negative correlation with growth inhibitory potency of geldanamycin but not with its analog 17-(allylamino)-17-demethoxygeldanamycin (17-AAG), which differs in the C-17 substituent in that the the methoxy moiety of geldanamycin is replaced by an amino group. Structure and potency analysis classified 18 geldanamycin analogs into two subgroups, "17-O/H" (C-17 methoxy or unsubstituted) and "17-N" (C-17 amino), showing distinct SLC7A11 correlation. We used three 17-O/H analogs and four 17-N analogs to test the role of the 17-substituents in susceptibility to SLC7A11-mediated resistance. In A549 cells, which are resistant to geldanamycin and strongly express SLC7A11, inhibition of SLC7A11 by (S)-4-carboxyphenylglycine or small interfering RNA increased sensitivity to 17-O/H, but had no effect on 17-N analogs. Ectopic expression of SLC7A11 in HepG2 cells, which are sensitive to geldanamycin and express low SLC7A11, confers resistance to geldanamycin, but not to 17-AAG. Antioxidant N-acetylcysteine, a precursor for glutathione synthesis, completely suppressed cytotoxic effects of 17-O/H but had no effect on 17-N analogs, whereas the prooxidant ascorbic acid had the opposite effect. Compared with 17-AAG, geldanamycin led to significantly more intracellular reactive oxygen species (ROS) production, which was quenched by addition of N-acetylcysteine. We conclude that SLC7A11 confers resistance selectively to 17-O/H (e.g., geldanamycin) but not to 17-N (e.g., 17-AAG) analogs partly as a result of differential dependence on ROS for cytotoxicity. Distinct mechanisms could significantly affect antitumor response and organ toxicity of these compounds in vivo.

Pharmacogenetics/genomics of membrane transporters in cancer chemotherapy

Inter-individual variability in drug response and the emergence of adverse drug reactions are main causes of treatment failure in cancer therapy. Recently, membrane transporters have been recognized as an important determinant of drug disposition, thereby affecting chemosensitivity and -resistance. Genetic factors contribute to inter-individual variability in drug transport and targeting. Therefore, pharmacogenetic studies of membrane transporters can lead to new approaches for optimizing cancer therapy. This review discusses genetic variations in efflux transporters of the ATP-binding cassette (ABC) family such as ABCB1 (MDR1, P-glycoprotein), ABCC1 (MRP1), ABCC2 (MRP2) and ABCG2 (BCRP), and uptake transporters of the solute carrier (SLC) family such as SLC19A1 (RFC1) and SLCO1B1 (SLC21A6), and their relevance to cancer chemotherapy. Furthermore, a pharmacogenomic approach is outlined, which using correlations between the growth inhibitory potency of anticancer drugs and transporter gene expression in multiple human cancer cell lines, has shown promise for determining the relevant transporters for any given drugs and predicting anticancer drug response.

MicroRNA expression profiles for the NCI-60 cancer cell panel

Advances in the understanding of cancer cell biology and response to drug treatment have benefited from new molecular technologies and methods for integrating information from multiple sources. The NCI-60, a panel of 60 diverse human cancer cell lines, has been used by the National Cancer Institute to screen >100,000 chemical compounds and natural product extracts for anticancer activity. The NCI-60 has also been profiled for mRNA and protein expression, mutational status, chromosomal aberrations, and DNA copy number, generating an unparalleled public resource for integrated chemogenomic studies. Recently, microRNAs have been shown to target particular sets of mRNAs, thereby preventing translation or accelerating mRNA turnover. To complement the existing NCI-60 data sets, we have measured expression levels of microRNAs in the NCI-60 and incorporated the resulting data into the CellMiner program package for integrative analysis. Cell line groupings based on microRNA expression were generally consistent with tissue type and with cell line clustering based on mRNA expression. However, mRNA expression seemed to be somewhat more informative for discriminating among tissue types than was microRNA expression. In addition, we found that there does not seem to be a significant correlation between microRNA expression patterns and those of known target transcripts. Comparison of microRNA expression patterns and compound potency patterns showed significant correlations, suggesting that microRNAs may play a role in chemoresistance. Combined with gene expression and other biological data using multivariate analysis, microRNA expression profiles may provide a critical link for understanding mechanisms involved in chemosensitivity and chemoresistance.

Chemogenomic Analysis Identifies Geldanamycins as Substrates and Inhibitors of ABCB1

PURPOSE

A prerequisite for geldanamycin (GA, NSC122750) to targeting heat shock protein 90 and inhibiting tumor growth is sufficient intracellular drug accumulation. We hypothesized that membrane transporters on tumor cells determine at least in part the response to GA analogues.

MATERIALS AND METHODS

To facilitate a systematic study of chemosensitivity across a group of GA analogues with similar chemical structures, we correlated mRNA expression profiles of most known transporters with growth inhibitory potencies of compounds in 60 tumor cell lines (NCI-60). We subsequently validated the gene-drug correlations using cytotoxicity and transport assays.

RESULTS

Geldanamycin analogues displayed a range of negative correlations coefficients with ABCB1 (MDR1, or P-glycoprotein) expression. Suppressing ABCB1 in multidrug resistant cells (NCI/ADR-RES and K562/DOX) and ABCB1-transfected cells (BC19) increased sensitivity to GA analogues, as expected for substrates. Moreover, ABCB1-mediated efflux of daunorubicin in K562/DOX cells could be blocked markedly by GA analogues in a dose-dependent fashion. The IC(50) values (half-maximum inhibition of daunorubicin efflux) were 5.5, 7.3 and 12 muM for macbecin II (NSC330500), 17-AAG (NSC330507) and GA, respectively.

CONCLUSIONS

These observations demonstrate that GA analogues are substrates as well as inhibitors of ABCB1, suggesting that drug interactions between GA analogues and other agents that are ABCB1 substrates may occur via ABCB1 in normal or tumor cells.

Membrane transporters and channels in chemoresistance and -sensitivity of tumor cells

Membrane transporters play important roles in mediating chemosensitivity and -resistance of tumor cells. ABC transporters, such as ABCB1/MDR1, ABCC1/MRP1 and ABCG2/BCRP, are frequently associated with decreased cellular accumulation of anticancer drugs and multidrug resistance of tumors. SLC transporters, such as folate, nucleoside, and amino acid transporters, commonly increase chemosensitivity by mediating the cellular uptake of hydrophilic drugs. Ion channels and pumps variably affect sensitivity to anticancer therapy by modulating viability of tumor cells. A pharmacogenomic approach, using correlations between drug potency and transporter gene expression in multiple cancer cell lines, has shown promise for identifying potential drug-transporter relationships and predicting anticancer drug response, in an effort to optimize chemotherapy for individual patients.

Prediction of anticancer drug potency from expression of genes involved in growth factor signaling

PURPOSE

This study develops and evaluates a systematic approach to finding biomarker genes for predicting potency of anticancer drugs against tumor cells, focusing on gene families related to growth factor signaling.

METHODS

Cytotoxic potencies of 119 drugs against 60 neoplastic cell lines (NCI-60) were correlated with expression of 343 genes, including 90 growth factors and receptors, 63 metalloproteinases, and 92 ras-like GTPases as downstream signaling factors. Progressively more stringent criteria and predictive models aim at identifying the smallest subset of genes predictive of cytotoxic potency.

RESULTS

Comparing gene expression with drug potency across the NCI-60 yielded genes with negative and positive correlations (p < 0.001), indicative of a role in chemoresistance and chemosensitivity, respectively. Of 17 genes with multiple negative correlations, 8 are known chemoresistance factors, validating the approach. Negatively correlated genes clustered into two main groups with distinct expression profiles and drug correlations, represented by EGFR and ERBB2 (Her-2/Neu). Accordingly, no synergism was observed between EGFR and ERBB2 inhibitors. However, combinations with classical anticacer drugs were not correlated with EGFR and ERBB2 expression in four cell lines tested, suggesting complex interactions in combination treatments. Finally, a subset of only 13 genes was found to be sufficient for near optimal prediction of drug potency against the NCI-60.

CONCLUSIONS

Our approach using a small subset of genes reveals known and potential biomarkers in cancer chemotherapy, providing a strategy for genome-wide analysis.

Linking pathway gene expressions to the growth inhibition response from the National Cancer Institute's anticancer screen and drug mechanism of action

Novel strategies are proposed to quantitatively analyze and relate biological pathways to drug responses using gene expression and small-molecule growth inhibition data (GI(50)) derived from the National Cancer Institute's 60 cancer cells (NCI(60)). We have annotated groups of drug GI(50) responses with pathways defined by the Kyoto Encyclopedia of Genes and Genomes (KEGG) and BioCarta, and functional categories defined by Gene Ontology (GO), through correlations between pathway gene expression patterns and drug GI(50) profiles. Drug-gene-pathway relationships may then be utilized to find drug targets or target-specific drugs. Significantly correlated pathways and the gene products involved represent interesting targets for further exploration, whereas drugs that are significantly correlated with only certain pathways are more likely to be target specific. Separate pathway clustering finds that pathways engaged in the same biological process tend to have similar drug correlation patterns. The biological and statistical significances of our method are established by comparison to known small-molecule inhibitor-gene target relationships reported in the literature and by standard randomization procedures. The results of our pathway, gene expression and drug-induced growth inhibition associations, can serve as a basis for proposing testable hypotheses about potential anticancer drugs, their targets, and mechanisms of action.