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

Identification of selective cytotoxic and synthetic lethal drug responses in triple negative breast cancer cells

Background

Triple negative breast cancer (TNBC) is a highly heterogeneous and aggressive type of cancer that lacks effective targeted therapy. Despite detailed molecular profiling, no targeted therapy has been established. Hence, with the aim of gaining deeper understanding of the functional differences of TNBC subtypes and how that may relate to potential novel therapeutic strategies, we studied comprehensive anticancer-agent responses among a panel of TNBC cell lines.

Method

The responses of 301 approved and investigational oncology compounds were measured in 16 TNBC cell lines applying a functional profiling approach. To go beyond the standard drug viability effect profiling, which has been used in most chemosensitivity studies, we utilized a multiplexed readout for both cell viability and cytotoxicity, allowing us to differentiate between cytostatic and cytotoxic responses.

Results

Our approach revealed that most single-agent anti-cancer compounds that showed activity for the viability readout had no or little cytotoxic effects. Major compound classes that exhibited this type of response included anti-mitotics, mTOR, CDK, and metabolic inhibitors, as well as many agents selectively inhibiting oncogene-activated pathways. However, within the broad viability-acting classes of compounds, there were often subsets of cell lines that responded by cell death, suggesting that these cells are particularly vulnerable to the tested substance. In those cases we could identify differential levels of protein markers associated with cytotoxic responses. For example, PAI-1, MAPK phosphatase and Notch-3 levels associated with cytotoxic responses to mitotic and proteasome inhibitors, suggesting that these might serve as markers of response also in clinical settings. Furthermore, the cytotoxicity readout highlighted selective synergistic and synthetic lethal drug combinations that were missed by the cell viability readouts. For instance, the MEK inhibitor trametinib synergized with PARP inhibitors. Similarly, combination of two non-cytotoxic compounds, the rapamycin analog everolimus and an ATP-competitive mTOR inhibitor dactolisib, showed synthetic lethality in several mTOR-addicted cell lines.

Conclusions

Taken together, by studying the combination of cytotoxic and cytostatic drug responses, we identified a deeper spectrum of cellular responses both to single agents and combinations that may be highly relevant for identifying precision medicine approaches in TNBC as well as in other types of cancers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12943-016-0517-3) contains supplementary material, which is available to authorized users.

Measuring circadian clock function in human cells

Circadian clocks are present in most cells and are essential for maintenance of daily rhythms in physiology, mood, and cognition. Thus, not only neurons of the central circadian pacemaker but also many other peripheral tissues possess the same functional and self-sustained circadian clocks. Surprisingly, however, their properties vary widely within the human population. In recent years, this clock variance has been studied extensively both in health and in disease using robust lentivirus-based reporter technologies to probe circadian function in human peripheral cells as proxies for those in neurologically and physiologically relevant but inaccessible tissues. The same procedures can be used to investigate other conserved signal transduction cascades affecting multiple aspects of human physiology, behavior, and disease. Accessing gene expression variation within human populations via these powerful in vitro cell-based technologies could provide important insights into basic phenotypic diversity or to better interpret patterns of gene expression variation in disease.

miR-22 inhibits osteosarcoma cell proliferation and migration by targeting HMGB1 and inhibiting HMGB1-mediated autophagy

Acquisition of drug-resistant phenotypes is often associated with chemotherapy in osteosarcoma. Studies show that high-mobility group box 1 (HMGB1) plays an important role in facilitating autophagy and promotes drug resistance in osteosarcoma cells. In this study, we determined the targeting role of miR-22 to HMGB1 and the regulation of miR-22 on the HMGB1-mediated cell autophagy and on the cell proliferation, migration, and invasion of osteosarcoma cells. Results demonstrated that miR-22 well paired with the 3'-UTR of HMGB1 downregulated the HMGB1 expression and blocked the HMGB1-mediated autophagy during chemotherapy in osteosarcoma cells in vitro. Further study showed that the blockage of autophagy by miR-22 inhibited the osteosarcoma cell proliferation, migration, and invasion. In summary, this study implied the negative regulation of miR-22 on the HMGB1-mediated autophagy in osteosarcoma cells.

Therapeutic target database update 2014: a resource for targeted therapeutics

Here we describe an update of the Therapeutic Target Database (http://bidd.nus.edu.sg/group/ttd/ttd.asp) for better serving the bench-to-clinic communities and for enabling more convenient data access, processing and exchange. Extensive efforts from the research, industry, clinical, regulatory and management communities have been collectively directed at the discovery, investigation, application, monitoring and management of targeted therapeutics. Increasing efforts have been directed at the development of stratified and personalized medicines. These efforts may be facilitated by the knowledge of the efficacy targets and biomarkers of targeted therapeutics. Therefore, we added search tools for using the International Classification of Disease ICD-10-CM and ICD-9-CM codes to retrieve the target, biomarker and drug information (currently enabling the search of almost 900 targets, 1800 biomarkers and 6000 drugs related to 900 disease conditions). We added information of almost 1800 biomarkers for 300 disease conditions and 200 drug scaffolds for 700 drugs. We significantly expanded Therapeutic Target Database data contents to cover >2300 targets (388 successful and 461 clinical trial targets), 20 600 drugs (2003 approved and 3147 clinical trial drugs), 20 000 multitarget agents against almost 400 target-pairs and the activity data of 1400 agents against 300 cell lines.

Analysis of bypass signaling in EGFR pathway and profiling of bypass genes for predicting response to anticancer EGFR tyrosine kinase inhibitors

Some drugs, such as anticancer EGFR tyrosine kinase inhibitors, elicit markedly different clinical response rates due to differences in drug bypass signaling as well as genetic variations of drug target and downstream drug-resistant genes. The profiles of these bypass signaling are expected to be useful for improved drug response prediction, which have not been systematically explored previously. In this work, we searched and analyzed 16 literature-reported EGFR tyrosine kinase inhibitor bypass signaling routes in the EGFR pathway, which include 5 compensatory routes of EGFR transactivation by another receptor, and 11 alternative routes activated by another receptor. These 16 routes are reportedly regulated by 11 bypass genes. Their expression profiles together with the mutational, amplification and expression profiles of EGFR and 4 downstream drug-resistant genes, were used as new sets of biomarkers for identifying 53 NSCLC cell-lines sensitive or resistant to EGFR tyrosine kinase inhibitors gefitinib, erlotinib and lapatinib. The collective profiles of all 16 genes distinguish sensitive and resistant cell-lines are better than those of individual genes and the combined EGFR and downstream drug resistant genes, and their derived cell-line response rates are consistent with the reported clinical response rates of the three drugs. The usefulness of cell-line data for drug response studies was further analyzed by comparing the expression profiles of EGFR and bypass genes in NSCLC cell-lines and patient samples, and by using a machine learning feature selection method for selecting drug response biomarkers. Our study suggested that the profiles of drug bypass signaling are highly useful for improved drug response prediction.

Prediction of drug efficacy for cancer treatment based on comparative analysis of chemosensitivity and gene expression data

The NCI60 database is the largest available collection of compounds with measured anti-cancer activity. The strengths and limitations for using the NCI60 database as a source of new anti-cancer agents are explored and discussed in relation to previous studies. We selected a sub-set of 2333 compounds with reliable experimental half maximum growth inhibitions (GI(50)) values for 30 cell lines from the NCI60 data set and evaluated their growth inhibitory effect (chemosensitivity) with respect to tissue of origin. This was done by identifying natural clusters in the chemosensitivity data set and in a data set of expression profiles of 1901 genes for the corresponding tumor cell lines. Five clusters were identified based on the gene expression data using self-organizing maps (SOM), comprising leukemia, melanoma, ovarian and prostate, basal breast, and luminal breast cancer cells, respectively. The strong difference in gene expression between basal and luminal breast cancer cells was reflected clearly in the chemosensitivity data. Although most compounds in the data set were of low potency, high efficacy compounds that showed specificity with respect to tissue of origin could be found. Furthermore, eight potential topoisomerase II inhibitors were identified using a structural similarity search. Finally, a set of genes with expression profiles that were significantly correlated with anti-cancer drug activity was identified. Our study demonstrates that the combined data sets, which provide comprehensive information on drug activity and gene expression profiles of tumor cell lines studied, are useful for identifying potential new active compounds.

MicroRNA-375 and MicroRNA-221: Potential Noncoding RNAs Associated with Antiproliferative Activity of Benzyl Isothiocyanate in Pancreatic Cancer

The deregulated presence or absence of microRNAs (miRNAs) might play an important role in molecular pathways leading to neoplastic transformation. At present, it is also thought that the approaches to interfere miRNA functions should be helpful for developing novel therapeutic opportunities for human cancer. In this study, we provide evidence that the anticancer agent benzyl isothiocyanate (BITC) has the ability to modulate the level of miRNAs such as miR-221 and miR-375, known to be abnormally expressed in pancreatic cancer patients. Interestingly, ectopic expression of miR-375 or the enforced silencing of miR-221 in cultured pancreatic cancer cells attenuates cell viability and sensitizes antiproliferative action of BITC. We also show that the expression of putative tumor suppressor miR-375 is more abundant in nonpathological mice pancreata than those with Kras(G12D)-driven pancreatic intraepithelial neoplasia (PanIN). To the contrary, the expression of oncogenic miR-221 is significantly elevated in the mouse pancreas with PanIN lesions. Although miR-375 has been shown to be aberrantly expressed in pancreatic cancer patients, there has not been a comprehensive study to investigate the molecular pathways targeted by this miRNA in pancreatic cancer cells. Further analysis by gene expression microarray revealed that IGFBP5 and CAV-1, potential biomarkers of pancreatic cancer, were significantly downregulated in cells transfected with miR-375. Correlatively, elevated expression of IGFBP5 and CAV-1 was evident in the mouse pancreas with preneoplastic lesions in which the expression of miR-375 wanes. Taken together, our findings suggest that anticancer agent BITC might target the expression of miR-221 and miR-375 to switch hyperproliferative pancreatic cancer cells to a hypoproliferative state.

Alterations of microRNAs in cisplatin-resistant human non-small cell lung cancer cells (A549/DDP)

ABSTRACT MicroRNAs (miRNAs) are a class of small, noncoding RNAs that posttranscriptionally regulate genes expression and play crucial roles in diverse biological processes, such as development, differentiation, apoptosis, and proliferation. Accumulating evidence suggests that miRNAs may play a role in chemoresistance and may be involved in the modulation of some drug resistance-related pathways in cancer cells. Here, the authors investigated the possible role of miRNAs in the development of drug resistance in lung cancer cell line. The results showed that 14 miRNAs were presented significantly (>2-fold), including up-regulation of 9 miRNAs and down-regulation of 5 miRNAs in A549/DDP cell line, compared with the parental A549 cell line. Up-regulation of miR-138 increased the sensitivity of A549/DDP cells to cisplatin in in vitro drug sensitivity assay, and increased apoptosis assessed by flow cytometry. The authors also found that excision repair cross-complementation group 1 (ERCC1) was negatively regulated by miR-138 and that down-regulation of ERCC1 at the protein level largely correlated with elevated levels of miR-138 in A549/DDP cells. Taken together, these findings suggest that miR-138 could play an important role in the development of cisplatin resistance in non-small cell lung cancer (NSCLC).

The use of genomic information to optimize cancer chemotherapy

The field of pharmacogenomics is focused on the characterization of genetic factors contributing to the response of patients to pharmacological interventions. Drug response and toxicity are complex traits; therefore the effects are likely influenced by multiple genes. The investigation of the genetic basis of drug response has evolved from a focus on single genes to relevant pathways to the entire genome. Preclinical (cell-based models) and clinical genome-wide association studies (GWAS) in oncology provide an unprecedented opportunity for a comprehensive and unbiased assessment of the heritable factors associated with drug response. The primary challenge with attempting to identify pharmacogenomic markers from clinical studies is that they require a homogeneous population of patients treated with the same dosage regimen and minimal confounding variables. Therefore, the development of cell-based models for pharmacogenomic marker identification has utility for the field since performing these types of studies in humans is difficult and costly. This review intends to provide a current report on the status of genomic studies in oncology, the methods for discovery, and implications for patient care. We present a perspective and summary of the challenges and opportunities in translating heritable genomic discoveries to patients.

Gene expression profiling of drug-resistant small cell lung cancer cells by combining microRNA and cDNA expression analysis

MicroRNAs (miRNAs) are now known to play important roles in the regulation of gene expression for developmental timing, cell proliferation and apoptosis. Therefore, it is likely that they also modulate sensitivity and resistance to anti-cancer drugs. To better understand the molecular mechanisms of multidrug resistance in SCLC and identify novel molecular markers, we evaluated the expression of 856 miRNAs and approximately 22,000 genes using miRNA microarray and cDNA microarray in cellular models of SCLC which were widely used as sensitive (NCI-H69) and resistant cell lines (NCI-H69AR) to chemotherapy. We also analysed the correlations between miRNA and mRNA expression patterns. Further studies were tested to determine whether the differentially expressed miRNAs were involved in multidrug resistance in SCLC. Our results showed that 61 miRNAs are presented significantly (>3-fold) including up-regulation of 24 miRNAs and down-regulation of 37 miRNAs. Among these miRNAs, 48 of 61 differentially expressed miRNAs were firstly reported to be closely associated with drug resistance and 37.7% (24/61) of miRNA genes were organised as 10 clusters in total 61 significantly expressed miRNAs. We also found that only 27 of 69 miRNAs were significantly correlated with 604 of 21,522 70 mRNA transcripts by MAS database. The sensitivity to anti-cancer drugs Cisplatin, Etoposide and Doxorubicin greatly increased or reduced following transfection of the drug-resistant H69AR cells with the mimics or antagomirs of miR-134, miR-379 and miR-495, respectively. miR-134 increases the cell survival by inducing G1 arrest in H69AR cells. MRP1/ABCC1 is negatively regulated by miR-134 and down-regulation of MRP1/ABCC1 at the protein level largely correlates with elevated levels of miR-134 in H69AR cells. Our results support for the first time a substantial role for miRNAs in multidrug resistance in SCLC. miR-134 could be a causal factor of the down-regulation of MRP1/ABCC1 in H69AR cells. These findings provide valuable information for potential utility of these miRNAs as specific diagnostic biomarkers and novel therapeutic approaches for drug resistance of SCLC.

Pharmacogenomic discovery using cell-based models

Quantitative variation in response to drugs in human populations is multifactorial; genetic factors probably contribute to a significant extent. Identification of the genetic contribution to drug response typically comes from clinical observations and use of classic genetic tools. These clinical studies are limited by our inability to control environmental factors in vivo and the difficulty of manipulating the in vivo system to evaluate biological changes. Recent progress in dissecting genetic contribution to natural variation in drug response through the use of cell lines has been made and is the focus of this review. A general overview of current cell-based models used in pharmacogenomic discovery and validation is included. Discussion includes the current approach to translate findings generated from these cell-based models into the clinical arena and the use of cell lines for functional studies. Specific emphasis is given to recent advances emerging from cell line panels, including the International HapMap Project and the NCI60 cell panel. These panels provide a key resource of publicly available genotypic, expression, and phenotypic data while allowing researchers to generate their own data related to drug treatment to identify genetic variation of interest. Interindividual and interpopulation differences can be evaluated because human lymphoblastoid cell lines are available from major world populations of European, African, Chinese, and Japanese ancestry. The primary focus is recent progress in the pharmacogenomic discovery area through ex vivo models.

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.

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.

5-Aza-2'-deoxycytidine and depsipeptide synergistically induce expression of BIK (BCL2-interacting killer)

DNA methylation and histone acetylation are main epigenetic events regulating gene expression, serving as anticancer drug targets. A combination of the DNA methyltransferase inhibitor 5-aza-2'-deoxycytidine with the histone deacetylase inhibitor depsipeptide synergistically induces apoptosis. To characterize genes involved in this process, we measured expression of 376 apoptosis-related genes with microarrays after treatment with the two inhibitors alone or in combination. The pro-apoptotic BIK (Bcl2-interacting killer) was the only gene synergistically upregulated in all four cancer cell lines tested (A549, PC-3, TK-10, and UO-31). BIK induction was confirmed by RT-PCR and Western blots. Histone acetylation of the BIK promoter region increased with depsipeptide treatment but was not further affected by 5-aza-2'-deoxycytidine. In summary, synergistic upregulation of pro-apoptotic BIK-previously shown to suppress tumor growth-appears to play a critical role in anticancer effects of 5-aza-2'-deoxycytidine plus depsipeptide.

Protein therapeutics: new applications for pharmacogenetics

Pharmacogenetic studies have traditionally focused on genes involved in processes that affect the pharmacokinetics of small-molecule drugs, such as drug metabolism. However, attention is shifting to the effects of genetic variations in drug targets and associated pathway components on drug responses. We describe how these variations are important for understanding differences in responses to the growing number of protein therapeutics that are entering clinical practice. Pharmacogenetic studies of these drugs are surveyed, and issues important to the success of such endeavours are discussed. As novel protein therapeutics are introduced, we anticipate that the use of pharmacogenetics will assume a key role in their development and clinical application.