An information-intensive approach to the molecular pharmacology of cancer

A comprehensive transcriptional portrait of human cancer cell lines

Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic responses. Although substantial effort has been made to define the genomic constitution of cancer cell line panels, the transcriptome remains understudied. Here we describe RNA sequencing and single-nucleotide polymorphism (SNP) array analysis of 675 human cancer cell lines. We report comprehensive analyses of transcriptome features including gene expression, mutations, gene fusions and expression of non-human sequences. Of the 2,200 gene fusions catalogued, 1,435 consist of genes not previously found in fusions, providing many leads for further investigation. We combine multiple genome and transcriptome features in a pathway-based approach to enhance prediction of response to targeted therapeutics. Our results provide a valuable resource for studies that use cancer cell lines.

InCHlib - interactive cluster heatmap for web applications

BACKGROUND

Hierarchical clustering is an exploratory data analysis method that reveals the groups (clusters) of similar objects. The result of the hierarchical clustering is a tree structure called dendrogram that shows the arrangement of individual clusters. To investigate the row/column hierarchical cluster structure of a data matrix, a visualization tool called 'cluster heatmap' is commonly employed. In the cluster heatmap, the data matrix is displayed as a heatmap, a 2-dimensional array in which the colour of each element corresponds to its value. The rows/columns of the matrix are ordered such that similar rows/columns are near each other. The ordering is given by the dendrogram which is displayed on the side of the heatmap.

RESULTS

We developed InCHlib (Interactive Cluster Heatmap Library), a highly interactive and lightweight JavaScript library for cluster heatmap visualization and exploration. InCHlib enables the user to select individual or clustered heatmap rows, to zoom in and out of clusters or to flexibly modify heatmap appearance. The cluster heatmap can be augmented with additional metadata displayed in a different colour scale. In addition, to further enhance the visualization, the cluster heatmap can be interconnected with external data sources or analysis tools. Data clustering and the preparation of the input file for InCHlib is facilitated by the Python utility script inchlib_clust.

CONCLUSIONS

The cluster heatmap is one of the most popular visualizations of large chemical and biomedical data sets originating, e.g., in high-throughput screening, genomics or transcriptomics experiments. The presented JavaScript library InCHlib is a client-side solution for cluster heatmap exploration. InCHlib can be easily deployed into any modern web application and configured to cooperate with external tools and data sources. Though InCHlib is primarily intended for the analysis of chemical or biological data, it is a versatile tool which application domain is not limited to the life sciences only.

Global and phylogenetic distribution of quorum sensing signals, acyl homoserine lactones, in the family of Vibrionaceae

Bacterial quorum sensing (QS) and the corresponding signals, acyl homoserine lactones (AHLs), were first described for a luminescent Vibrio species. Since then, detailed knowledge has been gained on the functional level of QS; however, the abundance of AHLs in the family of Vibrionaceae in the environment has remained unclear. Three hundred and one Vibrionaceae strains were collected on a global research cruise and the prevalence and profile of AHL signals in this global collection were determined. AHLs were detected in 32 of the 301 strains using Agrobacterium tumefaciens and Chromobacterium violaceum reporter strains. Ethyl acetate extracts of the cultures were analysed by ultra-high performance liquid chromatography-high resolution mass spectrometry (MS) with automated tandem MS confirmation for AHLs. N-(3-hydroxy-hexanoyl) (OH-C6) and N-(3-hydroxy-decanoyl) (OH-C10) homoserine lactones were the most common AHLs found in 17 and 12 strains, respectively. Several strains produced a diversity of different AHLs, including N-heptanoyl (C7) HL. AHL-producing Vibrionaceae were found in polar, temperate and tropical waters. The AHL profiles correlated with strain phylogeny based on gene sequence homology, however not with geographical location. In conclusion, a wide range of AHL signals are produced by a number of clades in the Vibrionaceae family and these results will allow future investigations of inter- and intra-species interactions within this cosmopolitan family of marine bacteria.

The opportunities of mining historical and collective data in drug discovery

Vast amounts of bioactivity data have been generated for small molecules across public and corporate domains. Biological signatures, either derived from systematic profiling efforts or from existing historical assay data, have been successfully employed for small molecule mechanism-of-action elucidation, drug repositioning, hit expansion and screening subset design. This article reviews different types of biological descriptors and applications, and we demonstrate how biological data can outlive the original purpose or project for which it was generated. By comparing 150 HTS campaigns run at Novartis over the past decade on the basis of their active and inactive chemical matter, we highlight the opportunities and challenges associated with cross-project learning in drug discovery.

Synthesis and anticancer activity of quinopimaric and maleopimaric acids’ derivatives

A series of quinopimaric and maleopimaric acids’ derivatives modified in the E-ring, at the carbonyl- and carboxyl-groups were synthesized and their in vitro cytotoxic activity was evaluated at the National Cancer Institute, USA. Methyl esters of dihydroquinopimaric, 1a,4a-dehydroquinopimaric, 2,3-epoxyquinopimaric, 1-ethylenketal-dihydroquinopimaric, 1-ethylenketal-4-hydroxyiminodihydroquinopimaric acids displayed an activity on renal cancer, leukemia, colon cancer and breast cancer cell lines in concentration 10(−5) M. Methyl 1,4-dihydroxyiminodihydroquinopimarate showed both a potent and broad spectrum of cytotoxic activity against NSC lung cancer, colon cancer, breast cancer, renal cancer and leukemia and revealed in vivo antineoplastic activity towards mouse solid transplantable mammary carcinoma Ca755 and colon adenocarcinoma AKATOL. The information about antineoplastic activity of the studied quinopimaric and maleopimaric acids’ derivatives will be used for hit to lead optimization in these chemical series.

Synthesis and in vitro antitumor activity of a novel series of 2-pyrazoline derivatives bearing the 4-aryloxy-7-chloroquinoline fragment

A new series of NH-pyrazoline derivatives 6 was synthesized by cyclocondensation reaction of novel [(7-chloroquinolin-4-yl)oxy]chalcones 5 with hydrazine hydrate. The treatment of pyrazolines 6 with acetic anhydride or formic acid yielded the N-acetyl- or N-formylpyrazoline derivatives 7–8, respectively. These novel 2-pyrazoline derivatives 6–8 were evaluated by the U.S. National Cancer Institute (NCI). Compounds 7b,d,f and 8c,f showed remarkable antitumor activity against 58 cancer cell lines, with the most important GI₅₀ values from in vitro assays ranging from 0.48 to 1.66 μM. The 2-pyrazoline derivatives bearing the 4-aryloxy-7-chloroquinoline fragment are thus considered to be useful leads for the rational design of new antitumor agents.

Prediction of individual response to anticancer therapy: historical and future perspectives

Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.

Genome sequencing and analysis of Mangalica, a fatty local pig of Hungary

BACKGROUND

Mangalicas are fatty type local/rare pig breeds with an increasing presence in the niche pork market in Hungary and in other countries. To explore their genetic resources, we have analysed data from next-generation sequencing of an individual male from each of three Mangalica breeds along with a local male Duroc pig. Structural variations, such as SNPs, INDELs and CNVs, were identified and particular genes with SNP variations were analysed with special emphasis on functions related to fat metabolism in pigs.

RESULTS

More than 60 Gb of sequence data were generated for each of the sequenced individuals, resulting in 11× to 19× autosomal median coverage. After stringent filtering, around six million SNPs, of which approximately 10% are novel compared to the dbSNP138 database, were identified in each animal. Several hundred thousands of INDELs and about 1,000 CNV gains were also identified. The functional annotation of genes with exonic, non-synonymous SNPs, which are common in all three Mangalicas but are absent in either the reference genome or the sequenced Duroc of this study, highlighted 52 genes in lipid metabolism processes. Further analysis revealed that 41 of these genes are associated with lipid metabolic or regulatory pathways, 49 are in fat-metabolism and fatness-phenotype QTLs and, with the exception of ACACA, ANKRD23, GM2A, KIT, MOGAT2, MTTP, FASN, SGMS1, SLC27A6 and RETSAT, have not previously been associated with fat-related phenotypes.

CONCLUSIONS

Genome analysis of Mangalica breeds revealed that local/rare breeds could be a rich source of sequence variations not present in cosmopolitan/industrial breeds. The identified Mangalica variations may, therefore, be a very useful resource for future studies of agronomically important traits in pigs.

NCI in vitro and in silico anticancer screen, cell cycle pertubation and apoptosis-inducing potential of new acylated, benzylidene and isopropylidene derivatives of andrographolide

Andrographolide (AGP) is the main bioactive constituent isolated from the traditional medicinal, Andrographis paniculata which contributes towards its various biological activities, including anticancer property. In this study, a series of new AGP derivatives were semi-synthesised and screened against the NCI in vitro 60 cell lines. From the screening results, we had identified SRS07 as the most potent AGP derivative, against breast and colon cancer cell lines. Subsequently, SRS07 was tested for its capability to induce cell cycle arrest and apoptosis in MCF-7 and HCT116 cancer cells. SRS07 effectively induced G1 cell cycle arrest in both cell lines and ultimately apoptosis by inducing DNA fragmentation in HCT116 cells. The apoptotic cell death induced by SRS07 was confirmed via FITC Annexin-V double staining. Western blot analysis of SRS07-treated HCT116 cells revealed that the compound induced apoptosis be activating caspase 8 which in turn cleaved Bid to t-Bid to initiate cell death cascade. Prediction of the possible mode of action of SRS07 by utilising NCI COMPARE analysis failed to reveal a distinct mechanism category. Hence, it is speculated that SRS07 possesses novel mechanism of action. In conclusion, SRS07 demonstrated superior in vitro anticancer profiles and emerged as a potential lead anticancer candidate.

Profiling the kinome for drug discovery

The human kinome is made up of 518 distinctive serine/threonine and tyrosine kinases, which are key components of virtually every mammalian signal transduction pathway. Consequently, kinases provide a compelling target family for the development of small molecule inhibitors, which could be used as tools to delineate the mechanism of action for biological processes and potentially be used as therapeutics to treat human diseases such as cancer. A myriad of recent technological advances have accelerated our understanding of kinome function, its relationship to tumorigenic development, and have contributed to the progression of small molecule kinase inhibitors into the clinic. Essential to the continued growth of the field are informatics tools that can assist in interpreting disparate and voluminous data sets and correctly guide decision making processes. These advances are expected to have a dramatic impact on kinase drug development and clinical diagnoses and treatment in the near future.:

Ron receptor-dependent gene regulation of Kupffer cells during endotoxemia

BACKGROUND

Ron receptor tyrosine kinase signaling in macrophages, including Kupffer cells and alveolar macrophages, suppresses endotoxin-induced proinflammatory cytokine/chemokine production. Further, we have also identified genes from Ron replete and Ron deplete livers that were differentially expressed during the progression of liver inflammation associated with acute liver failure in mice by microarray analyses. While important genes and signaling pathways have been identified downstream of Ron signaling during progression of inflammation by this approach, the precise role that Ron receptor plays in regulating the transcriptional landscape in macrophages, and particular in isolated Kupffer cells, has still not been investigated.

METHODS

Kupffer cells were isolated from wild-type (TK+/+) and Ron tyrosine kinase deficient (TK-/-) mice. Ex vivo, the cells were treated with lipopolysaccharide (LPS) in the presence or absence of the Ron ligand, hepatocyte growth factor-like protein (HGFL). Microarray and qRT-PCR analyses were utilized to identify alterations in gene expression between genotypes.

RESULTS

Microarray analyses identified genes expressed differentially in TK+/+ and TK-/- Kupffer cells basally as well as after HGFL and LPS treatment. Interestingly, our studies identified Mefv, a gene that codes for the anti-inflammatory protein pyrin, as an HGFL-stimulated Ron-dependent gene. Moreover, lipocalin 2, a proinflammatory gene, which is induced by LPS, was significantly suppressed by HGFL treatment. Microarray results were validated by qRT-PCR studies on Kupffer cells treated with LPS and HGFL.

CONCLUSION

The studies herein suggest a novel mechanism whereby HGFL-induced Ron receptor activation promotes the expression of anti-inflammatory genes while inhibiting genes involved in inflammation with a net effect of diminished inflammation in macrophages.

In silico modeling predicts drug sensitivity of patient-derived cancer cells

BACKGROUND

Glioblastoma (GBM) is an aggressive disease associated with poor survival. It is essential to account for the complexity of GBM biology to improve diagnostic and therapeutic strategies. This complexity is best represented by the increasing amounts of profiling ("omics") data available due to advances in biotechnology. The challenge of integrating these vast genomic and proteomic data can be addressed by a comprehensive systems modeling approach.

METHODS

Here, we present an in silico model, where we simulate GBM tumor cells using genomic profiling data. We use this in silico tumor model to predict responses of cancer cells to targeted drugs. Initially, we probed the results from a recent hypothesis-independent, empirical study by Garnett and co-workers that analyzed the sensitivity of hundreds of profiled cancer cell lines to 130 different anticancer agents. We then used the tumor model to predict sensitivity of patient-derived GBM cell lines to different targeted therapeutic agents.

RESULTS

Among the drug-mutation associations reported in the Garnett study, our in silico model accurately predicted ~85% of the associations. While testing the model in a prospective manner using simulations of patient-derived GBM cell lines, we compared our simulation predictions with experimental data using the same cells in vitro. This analysis yielded a ~75% agreement of in silico drug sensitivity with in vitro experimental findings.

CONCLUSIONS

These results demonstrate a strong predictability of our simulation approach using the in silico tumor model presented here. Our ultimate goal is to use this model to stratify patients for clinical trials. By accurately predicting responses of cancer cells to targeted agents a priori, this in silico tumor model provides an innovative approach to personalizing therapy and promises to improve clinical management of cancer.

Estrogen receptor α and aryl hydrocarbon receptor independent growth inhibitory effects of aminoflavone in breast cancer cells

Background

Numerous studies have implicated the aryl hydrocarbon receptor (AhR) as a potential therapeutic target for several human diseases, including estrogen receptor alpha (ERα) positive breast cancer. Aminoflavone (AF), an activator of AhR signaling, is currently undergoing clinical evaluation for the treatment of solid tumors. Of particular interest is the potential treatment of triple negative breast cancers (TNBC), which are typically more aggressive and characterized by poorer outcomes. Here, we examined AF’s effects on two TNBC cell lines and the role of AhR signaling in AF sensitivity in these model cell lines.

Methods

AF sensitivity in MDA-MB-468 and Cal51 was examined using cell counting assays to determine growth inhibition (GI₅₀) values. Luciferase assays and qPCR of AhR target genes cytochrome P450 (CYP) 1A1 and 1B1 were used to confirm AF-mediated AhR signaling. The requirement of endogenous levels of AhR and AhR signaling for AF sensitivity was examined in MDA-MB-468 and Cal51 cells stably harboring inducible shRNA for AhR. The mechanism of AF-mediated growth inhibition was explored using flow cytometry for markers of DNA damage and apoptosis, cell cycle analysis, and β-galactosidase staining for senescence. Luciferase data was analyzed using Student’s T test. Three-parameter nonlinear regression was performed for cell counting assays.

Results

Here, we report that ERα-negative TNBC cell lines MDA-MB-468 and Cal51 are sensitive to AF. Further, we presented evidence suggesting that neither endogenous AhR expression levels nor downstream induction of AhR target genes CYP1A1 and CYP1B1 is required for AF-mediated growth inhibition in these cells. Between these two ERα negative cell lines, we showed that the mechanism of AF action differs slightly. Low dose AF mediated DNA damage, S-phase arrest and apoptosis in MDA-MB-468 cells, while it resulted in DNA damage, S-phase arrest and cellular senescence in Cal51 cells.

Conclusions

Overall, this work provides evidence against the simplified view of AF sensitivity, and suggests that AF could mediate growth inhibitory effects in ERα-positive and negative breast cancer cells, as well as cells with impaired AhR expression and signaling. While AF could have therapeutic effects on broader subtypes of breast cancer, the mechanism of cytotoxicity is complex, and likely, cell line- and tumor-specific.

Selection on synonymous codons in mammalian rhodopsins: a possible role in optimizing translational processes

Background

Synonymous codon usage can affect many cellular processes, particularly those associated with translation such as polypeptide elongation and folding, mRNA degradation/stability, and splicing. Highly expressed genes are thought to experience stronger selection pressures on synonymous codons. This should result in codon usage bias even in species with relatively low effective population sizes, like mammals, where synonymous site selection is thought to be weak. Here we use phylogenetic codon-based likelihood models to explore patterns of codon usage bias in a dataset of 18 mammalian rhodopsin sequences, the protein mediating the first step in vision in the eye, and one of the most highly expressed genes in vertebrates. We use these patterns to infer selection pressures on key translational mechanisms including polypeptide elongation, protein folding, mRNA stability, and splicing.

Results

Overall, patterns of selection in mammalian rhodopsin appear to be correlated with post-transcriptional and translational processes. We found significant evidence for selection at synonymous sites using phylogenetic mutation-selection likelihood models, with C-ending codons found to have the highest relative fitness, and to be significantly more abundant at conserved sites. In general, these codons corresponded with the most abundant tRNAs in mammals. We found significant differences in codon usage bias between rhodopsin loops versus helices, though there was no significant difference in mean synonymous substitution rate between these motifs. We also found a significantly higher proportion of GC-ending codons at paired sites in rhodopsin mRNA secondary structure, and significantly lower synonymous mutation rates in putative exonic splicing enhancer (ESE) regions than in non-ESE regions.

Conclusions

By focusing on a single highly expressed gene we both distinguish synonymous codon selection from mutational effects and analytically explore underlying functional mechanisms. Our results suggest that codon bias in mammalian rhodopsin arises from selection to optimally balance high overall translational speed, accuracy, and proper protein folding, especially in structurally complicated regions. Selection at synonymous sites may also be contributing to mRNA stability and splicing efficiency at exonic-splicing-enhancer (ESE) regions. Our results highlight the importance of investigating highly expressed genes in a broader phylogenetic context in order to better understand the evolution of synonymous substitutions.

A compensatory role of NF-κB to p53 in response to 5-FU-based chemotherapy for gastric cancer cell lines

Despite of remarkable improvement of postoperative 5-FU–based adjuvant chemotherapy, the relapse rate of gastric cancer patients who undergo curative resection followed by the adjuvant chemotherapy remains substantial. Therefore, it is important to identify prediction markers for the chemotherapeutic efficacy of 5-FU. We recently identified NF-κB as a candidate relapse prediction biomarker in gastric cancer. To evaluate the biological significance of NF-κB in the context of 5-FU–based chemotherapy, we analyzed the NF-κB-dependent biological response upon 5-FU treatment in gastric cancer cell lines. Seven genes induced by 5-FU treatment in an NF-κB-dependent manner were identified, five of which are known p53 targets. Knockdown of RELA, which encodes the p65 subunit of NF-κB, decreased both p53 and p53 target protein levels. In contrast, NF-κB was not affected by TP53 knockdown. We also demonstrated that cell lines bearing Pro/Pro homozygosity in codon72 of p53 exon4, which is important for NF-κB binding to p53, are more resistant to 5-FU than those with Arg/Arg homozygosity. We conclude that NF-κB plays an important role in the response to 5-FU treatment in gastric cancer cell lines, with a possible compensatory function of p53. These results suggest that NF-κB is a potential 5-FU-chemosensitivity prediction marker that may reflect 5-FU-induced stress-response pathways, including p53.

Gadd45 in stress signaling, cell cycle control, and apoptosis

The first identified Gadd45 gene, Gadd45a, encodes a ubiquitously expressed protein that is often induced by DNA damage and other stress signals associated with growth arrest and apoptosis. This protein and the other two members of this small gene family, Gadd45b and Gadd45g, have been implicated in a variety of the responses to cell injury including cell cycle checkpoints, apoptosis, and DNA repair. In vivo, many of the prominent roles for the Gadd45 proteins are associated with signaling mediated by p38 mitogen-activated protein kinases (MAPK). Gadd45 proteins can contribute to p38 activation either by activation of upstream kinase(s) or by direct interaction. In vivo, there are important tissue and cell-type-specific differences in the roles for Gadd45 in MAPK signaling. In addition to being p53-regulated, Gadd45a has been found to contribute to p53 activation via p38. Like other stress and signaling proteins, Gadd45 proteins show complex regulation and numerous effectors.

Connecting Small Molecules with Similar Assay Performance Profiles Leads to New Biological Hypotheses

High-throughput screening allows rapid identification of new candidate compounds for biological probe or drug development. Here, we describe a principled method to generate "assay performance profiles" for individual compounds that can serve as a basis for similarity searches and cluster analyses. Our method overcomes three challenges associated with generating robust assay performance profiles: (1) we transform data, allowing us to build profiles from assays having diverse dynamic ranges and variability; (2) we apply appropriate mathematical principles to handle missing data; and (3) we mitigate the fact that loss-of-signal assay measurements may not distinguish between multiple mechanisms that can lead to certain phenotypes (e.g., cell death). Our method connected compounds with similar mechanisms of action, enabling prediction of new targets and mechanisms both for known bioactives and for compounds emerging from new screens. Furthermore, we used Bayesian modeling of promiscuous compounds to distinguish between broadly bioactive and narrowly bioactive compound communities. Several examples illustrate the utility of our method to support mechanism-of-action studies in probe development and target identification projects.

A thermogenic secondary sexual character in male sea lamprey

Secondary sexual characters in animals are exaggerated ornaments or weapons for intrasexual competition. Unexpectedly, we found that a male secondary sexual character in sea lamprey (Petromyzon marinus) is a thermogenic adipose tissue that instantly increases its heat production during sexual encounters. This secondary sexual character, developed in front of the anterior dorsal fin of mature males, is a swollen dorsal ridge known as the 'rope' tissue. It contains nerve bundles, multivacuolar adipocytes and interstitial cells packed with small lipid droplets and mitochondria with dense and highly organized cristae. The fatty acid composition of the rope tissue is rich in unsaturated fatty acids. The cytochrome c oxidase activity is high but the ATP concentration is very low in the mitochondria of the rope tissue compared with those of the gill and muscle tissues. The rope tissue temperature immediately rose up to 0.3°C when the male encountered a conspecific. Mature males generated more heat in the rope and muscle tissues when presented with a mature female than when presented with a male (paired t-test, P<0.05). On average, the rope generated 0.027±0.013 W cm(-3) more heat than the muscle in 10 min. Transcriptome analyses revealed that genes involved in fat cell differentiation are upregulated whereas those involved in oxidative-phosphorylation-coupled ATP synthesis are downregulated in the rope tissue compared with the gill and muscle tissues. Sexually mature male sea lamprey possess the only known thermogenic secondary sexual character that shows differential heat generation toward individual conspecifics.

Cytolethal distending toxin B as a cell-killing component of tumor-targeted anthrax toxin fusion proteins

Cytolethal distending toxin (Cdt) is produced by Gram-negative bacteria of several species. It is composed of three subunits, CdtA, CdtB, and CdtC, with CdtB being the catalytic subunit. We fused CdtB from Haemophilus ducreyi to the N-terminal 255 amino acids of Bacillus anthracis toxin lethal factor (LFn) to design a novel, potentially potent antitumor drug. As a result of this fusion, CdtB was transported into the cytosol of targeted cells via the efficient delivery mechanism of anthrax toxin. The fusion protein efficiently killed various human tumor cell lines by first inducing a complete cell cycle arrest in the G2/M phase, followed by induction of apoptosis. The fusion protein showed very low toxicity in mouse experiments and impressive antitumor effects in a Lewis Lung carcinoma model, with a 90% cure rate. This study demonstrates that efficient drug delivery by a modified anthrax toxin system combined with the enzymatic activity of CdtB has great potential as anticancer treatment and should be considered for the development of novel anticancer drugs.

Multidimensional profiling in the investigation of small-molecule-induced cell death

Numerous morphological variations of cell death have been described. These processes depend on a complex and overlapping cellular signaling network, making molecular definition of the pathways challenging. This review describes one solution to this problem for small-molecule-induced death, the creation of high-dimensionality profiles for compounds that can be used to define and compare pathways. Such profiles have been assembled from gene expression measurements, protein quantification, chemical-genetic interactions, chemical combination interactions, cancer cell line sensitivity profiling, quantitative imaging, and modulatory profiling. We discuss the advantages and limitations of these techniques in the study of cell death.

Employing heat maps to mine associations in structured routine care data

OBJECTIVE

Mining the electronic medical record (EMR) has the potential to deliver new medical knowledge about causal effects, which are hidden in statistical associations between different patient attributes. It is our goal to detect such causal mechanisms within current research projects which include e.g. the detection of determinants of imminent ICU readmission. An iterative statistical approach to examine each set of considered attribute pairs delivers potential answers but is difficult to interpret. Therefore, we aimed to improve the interpretation of the resulting matrices by the use of heat maps. We propose strategies to adapt heat maps for the search for associations and causal effects within routine EMR data.

METHODS

Heat maps visualize tabulated metric datasets as grid-like choropleth maps, and thus present measures of association between numerous attribute pairs clearly arranged. Basic assumptions about plausible exposures and outcomes are used to allocate distinct attribute sets to both matrix dimensions. The image then avoids certain redundant graphical elements and provides a clearer picture of the supposed associations. Specific color schemes have been chosen to incorporate preexisting information about similarities between attributes. The use of measures of association as a clustering input has been taken as a trigger to apply transformations which ensure that distance metrics always assume finite values and treat positive and negative associations in the same way. To evaluate the general capability of the approach, we conducted analyses of simulated datasets and assessed diagnostic and procedural codes in a large routine care dataset.

RESULTS

Simulation results demonstrate that the proposed clustering procedure rearranges attributes similar to simulated statistical associations. Thus, heat maps are an excellent tool to indicate whether associations concern the same attributes or different ones, and whether affected attribute sets conform to any preexisting relationship between attributes. The dendrograms help in deciding if contiguous sequences of attributes effectively correspond to homogeneous attribute associations. The exemplary analysis of a routine care dataset revealed patterns of associations that follow plausible medical constellations for several diseases and the associated medical procedures and activities. Cases with breast cancer (ICD C50), for example, appeared to be associated with radiation therapy (8-52). In cross check, approximately 60 percent of the attribute pairs in this dataset showed a strong negative association, which can be explained by diseases treated in a medical specialty which routinely does not perform the respective procedures in these cases. The corresponding diagram clearly reflects these relationships in the shape of coherent subareas.

CONCLUSION

We could demonstrate that heat maps of measures of association are effective for the visualization of patterns in routine care EMRs. The adjustable method for the assignment of attributes to image dimensions permits a balance between the display of ample information and a favorable level of graphical complexity. The scope of the search can be adapted by the use of pre-existing assumptions about plausible effects to select exposure and outcome attributes. Thus, the proposed method promises to simplify the detection of undiscovered causal effects within routine EMR data.

Oxadiazoles as privileged motifs for promising anticancer leads: recent advances and future prospects

Taking into account the rising trend of the incidence of cancers of various organs, effective therapies are urgently needed to control human malignancies. The rapid emergence of hundreds of new agents that modulate an ever-growing list of cancer-specific molecular targets offers tremendous hope for cancer patients. However, almost all of the chemotherapy drugs currently on the market cause serious side effects. Based on these facts, the design of new chemical entities as anticancer agents requires the simulation of a suitable bioactive pharmacophore. The pharmacophore not only should have the required potency but must also be safer on normal cell lines than on tumor cells. In this perspective, oxadiazole scaffolds with well-defined anticancer activity profile have fueled intense academic and industrial research in recent years. This paper is intended to highlight the recent advances along with current developments as well as future outlooks for the design of novel and efficacious anticancer agents based on oxadiazole motifs.

Next-generation NAMPT inhibitors identified by sequential high-throughput phenotypic chemical and functional genomic screens

Phenotypic high-throughput chemical screens allow for discovery of small molecules that modulate complex phenotypes and provide lead compounds for novel therapies; however, identification of the mechanistically relevant targets remains a major experimental challenge. We report the application of sequential unbiased high-throughput chemical and ultracomplex small hairpin RNA (shRNA) screens to identify a distinctive class of inhibitors that target nicotinamide phosphoribosyl transferase (NAMPT), a rate-limiting enzyme in the biosynthesis of nicotinamide adenine dinucleotide, a crucial cofactor in many biochemical processes. The lead compound STF-118804 is a highly specific NAMPT inhibitor, improves survival in an orthotopic xenotransplant model of high-risk acute lymphoblastic leukemia, and targets leukemia stem cells. Tandem high-throughput screening using chemical and ultracomplex shRNA libraries, therefore, provides a rapid chemical genetics approach for seamless progression from small-molecule lead identification to target discovery and validation.

Engineered reversal of drug resistance in cancer cells--metastases suppressor factors as change agents

Building molecular correlates of drug resistance in cancer and exploiting them for therapeutic intervention remains a pressing clinical need. To identify factors that impact drug resistance herein we built a model that couples inherent cell-based response toward drugs with transcriptomes of resistant/sensitive cells. To test this model, we focused on a group of genes called metastasis suppressor genes (MSGs) that influence aggressiveness and metastatic potential of cancers. Interestingly, modeling of 84 000 drug response transcriptome combinations predicted multiple MSGs to be associated with resistance of different cell types and drugs. As a case study, on inducing MSG levels in a drug resistant breast cancer line resistance to anticancer drugs caerulomycin, camptothecin and topotecan decreased by more than 50–60%, in both culture conditions and also in tumors generated in mice, in contrast to control un-induced cells. To our knowledge, this is the first demonstration of engineered reversal of drug resistance in cancer cells based on a model that exploits inherent cellular response profiles.

Capturing drug responses by quantitative promoter activity profiling

Quantitative analysis of cellular responses to drugs is of major interest in pharmaceutical research. Microarray technologies have been widely used for monitoring genome-wide expression changes. However, this approach has several limitations in terms of coverage of targeted RNAs, sensitivity, and quantitativeness, which are crucial for accurate monitoring of cellular responses. In this article, we report an application of genome-wide and quantitative profiling of cellular responses to drugs. We monitored promoter activities in MCF-7 cells by Cap Analysis of Gene Expression using a single-molecule sequencer. We identified a distinct set of promoters affected even by subtle inhibition of the Ras-ERK and phosphatidylinositol-3-kinase-Akt signal-transduction pathways. Furthermore, we succeeded in explaining the majority of promoter responses to inhibition of the upstream epidermal growth factor receptor kinase quantitatively based on the promoter profiles upon inhibition of the two individual downstream signaling pathways. Our results demonstrate unexplored utility of highly quantitative promoter activity profiling in drug research.

A two-hybrid approach to identify inhibitors of the RAS-RAF interaction

MCP compounds were developed with the idea to inhibit RAS/RAF interaction. They were identified by carrying out high-throughput screens of chemical compounds for their ability to inhibit RAS/RAF interaction in the yeast two-hybrid assay. A number of compounds including MCP1, MCP53, and MCP110 were identified as active compounds. Their inhibition of the RAS signaling was demonstrated by examining RAF and MEK activities, phosphorylation of ERK as well as characterizing their effects on events downstream of RAF. Direct evidence for the inhibition of RAS/RAF interaction was obtained by carrying out co-IP experiments. MCP compounds inhibit proliferation of a wide range of human cancer cell lines. Combination studies with other drugs showed that MCP compounds synergize with MAPK pathway inhibitors as well as with microtubule-targeting chemotherapeutics. In particular, a strong synergy with paclitaxel was observed. Efficacy to inhibit tumor formation was demonstrated using mouse xenograft models. Combination of MCP110 and paclitaxel was particularly effective in inhibiting tumor growth in a mouse xenograft model of colorectal carcinoma.

Antiangiogenic activity and pharmacogenomics of medicinal plants from traditional korean medicine

Aim. In the present study, we investigated the antiangiogenic properties of 59 plants used in traditional Korean medicine. Selected phytochemicals were investigated in more detail for their modes of action. Methods. A modified chicken-chorioallantoic-membrane (CAM) assay using quail eggs was applied to test for antiangiogenic effects of plant extracts. A molecular docking in silico approached the binding of plant constituents to the vascular endothelial growth factor receptors 1 and 2 (VEGFR1, VEGFR2). Microarray-based mRNA expression profiling was employed to correlate the 50% inhibition concentrations (IC₅₀) of a panel of 60 NCI cell lines to these phytochemicals. Results. Extracts from Acer mono leaves, Reynoutria sachalniensis fruits, Cinnamomum japonicum stems, Eurya japonica leaves, Adenophora racemosa whole plant, Caryopteris incana leaves-stems, and Schisandra chinensis stems inhibited angiogenesis more than 50% in quail eggs. Selected phytochemicals from Korean plants were analyzed in more detail using microarray-based mRNA expression profiles and molecular docking to VEGFR1 and VEGFR2. These results indicate multifactorial modes of action of these natural products. Conclusion. The antiangiogenic activity of plants used in traditional Korean medicine implicates their possible application for diseases where inhibition of blood vessel formation is desired, for example, cancer, macular degeneration, diabetic retinopathy and others.

Synthesis, antiproliferative and anti-inflammatory activities of some novel 6-aryl-2-(p-(methanesulfonyl)phenyl)-4,5-dihydropyridazi-3(2H)-ones

Sixteen new 6-aryl-2-(p-(methanesulfonyl)phenyl)-4,5-dihydropyridazi-3(2H)-ones (2a-p) were synthesized and tested for in vitro anticancer and in vivo anti-inflammatory activities. Eleven (2b, 2d, 2e-j and 2m-p) of the obtained compounds were screened for their antiproliferative activity towards 60 human cancer cell lines by the National Cancer Institute (USA). Compound 2f showed remarkable activity with GI50 less than 1 μM on 36 human tumor cell lines and has been referred to Biological Evaluation Committee (NCI) for advance study. Compound 2g also displayed promising antiproliferative activity against 20 different cell lines with GI50 less than 1 μM. Compounds 2k and 2n were found to have a comparable anti-inflammatory activity to that of standard drug etoricoxib in carrageenan-induced rat hind paw edema model at 5 h.

Synthesis of novel analogs of 2-pyrazoline obtained from [(7-chloroquinolin-4-yl)amino]chalcones and hydrazine as potential antitumor and antimalarial agents

A new series of N-acetyl and N-formyl-pyrazoline derivatives 6 and 7-8 were synthesized by cyclocondensation reaction of [(7-chloroquinolin-4-yl)amino]chalcones with hydrazine hydrate in acetic acid and hydrazine hydrate in formic acid respectively. These compounds were evaluated in vitro as antitumor and as antimalarial agents. Compounds 7b and 8b-e showed remarkable antitumor activity against cancer cell lines, with the most important GI50 values ranging from 0.13 to 0.99 μM. The best antimalarial response was observed for compound 7a with an inhibition percentage of 50.8% for Plasmodium falciparum, a hemolytic capacity of 3.2% and an IC50 of 14.1 μg/mL.

Assessing triclosan-induced ecological and trans-generational effects in natural phytoplankton communities: a trait-based field method

We exposed replicated phytoplankton communities confined in semi-permeable membrane-based mesocosms to 0, 0.1, 1 and 10 μg L(-1) triclosan (TCS) and placed them back in their original environment to investigate the occurrence of trans-generational responses at individual, population and community levels. TCS diffused out of mesocosms with a half-life of less than 8 h, so that only the parental generation was directly stressed. At the beginning of the experiment and after 7 days (approximately 2 generations) we analysed responses in the phytoplankton using scanning flow-cytometry. We acquired information on several individually expressed phenotypic traits, such as size, biovolume, pigment fluorescence and packaging, for thousands of individuals per replicated population and derived population and community aggregated traits. We found significant changes in community functioning (increased productivity in terms of biovolume and total fluorescence), with maximal effects at 1 μg L(-1) TCS. We detected significant and dose-dependent responses on population traits, such as changes in abundance for several populations, increased average size and fluorescence of cells, and strong changes in within-population trait mean and variance (suggesting micro-evolutionary effects). We applied the Price equation approach to partition community effects (changes in biovolume or fluorescence) in their physiological and ecological components, and quantified the residual component (including also evolutionary responses). Our results suggested that evolutionary or inheritable phenotypic plasticity responses may represent a significant component of the total observed change following exposure and over relatively small temporal scales.

Molecular approaches towards development of purified natural products and their structurally known derivatives as efficient anti-cancer drugs: current trends

Several natural products and their derivatives, either in purified or structurally identified form, exhibit immense pharmacological and biological properties, some of them showing considerable anticancer potential. Although the molecular mechanisms of action of some of these products are yet to be elucidated, extensive research in this area continues to generate new data that are clinically exploitable. Recent advancement in molecular biology, high throughput screening, biomarker identifications, target selection and genomic approaches have enabled us to understand salient interactions of natural products and their derivatives with cancer cells vis-à-vis normal cells. In this review we highlight the recent approaches and application of innovative technologies made to improve quality as well as efficiency of structurally identified natural products and their derivatives, particularly in small molecular forms capable of being used in "targeted therapies" in oncology. These products preferentially involve multiple mechanistic pathways and overcome chemo-resistance in tumor types with cumulative action. We also mention briefly a few physico-chemical features that compare natural products with drugs in recent natural product discovery approaches. We further report here a few purified natural products as examples that provide molecular interventions in cancer therapeutics to give the reader a glimpse of the current trends of approach for discovering useful anticancer drugs.

The UCSC Interaction Browser: multidimensional data views in pathway context

High-throughput data sets such as genome-wide protein–protein interactions, protein–DNA interactions and gene expression data have been published for several model systems, especially for human cancer samples. The University of California, Santa Cruz (UCSC) Interaction Browser (http://sysbio.soe.ucsc.edu/nets) is an online tool for biologists to view high-throughput data sets simultaneously for the analysis of functional relationships between biological entities. Users can access several public interaction networks and functional genomics data sets through the portal as well as upload their own networks and data sets for analysis. Users can navigate through correlative relationships for focused sets of genes belonging to biological pathways using a standard web browser. Using a new visual modality called the CircleMap, multiple ‘omics’ data sets can be viewed simultaneously within the context of curated, predicted, directed and undirected regulatory interactions. The Interaction Browser provides an integrative viewing of biological networks based on the consensus of many observations about genes and their products, which may provide new insights about normal and disease processes not obvious from any isolated data set.

Synthesis and biological evaluation of 4-arylphthalazones bearing benzenesulfonamide as anti-inflammatory and anti-cancer agents

Nine 4-arylphthalazones bearing benzenesulfonamide (2a-i) were synthesized by the condensation of the appropriate 2-aroylbenzoic acid (1a-i) and 4-hydrazinobenzenesulfonamide in ethanol. The structures of these compounds were elucidated by elemental analysis, IR, ¹H NMR, ¹³C NMR, and MS spectroscopy. Two compounds, 2b and 2i, showed significant anti-inflammatory activity comparable to that of the standard drug celecoxib in the carrageenan-induced rat paw edema model. These compounds (2b and 2i) had selective inhibitory activity towards the COX-2 enzyme. Compound 2b had a better selectivity ratio (COX-1/COX-2) compared to that of celecoxib and can be used as a novel template for the design of selective COX-2 inhibitors. Compounds 2d and 2i were screened for their antiproliferative activity toward 60 human cancer cell lines by the National Cancer Institute (USA). The compounds 2d and 2i displayed mild activity toward the renal cancer cell line UO-31.

Abstract 5132: Interactively exploring patterns in TCGA data: a web-based compendium of ‘next-generation’ clustered heat maps

Each of the 5 TCGA marker paper published in Nature to date has included at least one clustered heat map (CHM). We introduced CHMs in the early 1990’s for pharmacogenomic analysis (1) and later for integrated visualization of genomic, transcriptomic, proteomic, pharmacological, and functional data (1). As the ubiquitous first-order way of visualizing omic data, CHMs have appeared in many thousands of publications (3–9), including those from TCGA. We have elsewhere summarized their limitations (10).

One such limitation is that CHMs are generally static images. We therefore initiated the next-generation CHM (NG-CHM) project, using an image-tiling technology similar to that in Google Maps for navigation and extreme drill-down without loss of resolution. Once the CHM has been zoomed sufficiently, labels (e.g., gene, protein, or drug names) appear on the image's axes. Clicking on a label produces a menu of link-outs (e.g., to GeneCards, Google, PubMed). For gene vs. gene maps, each pixel can represent a color-coded Pearson correlation coefficient. Clicking on the pixel pulls up the corresponding data scattergram, bootstrap statistics, literature references, or pathway relationships. Strong usability features include floating windows, flexible search tools, cluster selection tools, customizable re-coloring of the CHM, and high-quality PDF's suitable for publication. NG-CHMs are a major resource for exploratory analysis and visualization in multiple projects of TCGA and other large-scale molecular profiling programs. Explore interactive versions for TCGA breast, colorectal, lung squamous, and glioblastoma data at http://bioinformatics.mdanderson.org/main/TCGA/NGCHM.

Supported in part by NCI Grant No. U24CA143883, by a gift from the Mary K. Chapman Foundation, and by a grant from the Michael and Susan Dell Foundation honoring Lorraine Dell.

Citation Format: John N. Weinstein, David W. Kane, Rehan Akbani, Deepti Dodda, Lam Nguyen, Michael C. Ryan, Chris Wakefield, Bradley M. Broom. Interactively exploring patterns in TCGA data: a web-based compendium of ‘next-generation’ clustered heat maps. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5132. doi:10.1158/1538-7445.AM2013-5132

Synthesis of 1,2,3-Triazole Derivatives and Evaluation of their Anticancer Activity

Anticancer screening of several 1,2,3-triazoles with heterocyclic fragments has been performed. The 1,2,3-triazole derivatives were synthesized from available starting materials according to convenient synthetic procedures. The antitumor activity of the synthesized compounds was tested in vitro by the National Cancer Institute in NCI60 cell lines. It was observed that some compounds showed slight anticancer activity. One of them possessed a moderate activity against melanoma, colon, and breast cancer. Standard COMPARE analysis was performed at the GI₅₀ level.

Treatment of stage IIIb/IV non-small cell lung cancer with Pemetrexed plus Oxaliplatin after failure of Erlotinib as second-line treatment

To determine the efficacy and toxicity of Pemetrexed plus Oxaliplatin in patients suffering from stage IIIb or IV lung adenocarcinoma and being treated with Erlotinib as second-line treatment, a total of 45 patients were randomly divided into two groups. One group was treated with 500 mg/m² Pemetrexed plus 100 mg/m² Oxaliplatin, and the other was treated with 500 mg/m² Pemetrexed plus 75 mg/m² Cisplatin. All drugs were administered on day one of a 21-day cycle. In the Oxaliplatin group, 3 patients (13.6 %) experienced partial response (PR), 9 patients (41.0 %) showed stable disease (SD), and 10 patients (45.5 %) had progressive disease (PD). In the Cisplatin group, 2 patients (8.7 %) experienced PR, 7 patients (30.4 %) showed SD, and 14 patients (60.9 %) had PD. The PFS of the Oxaliplatin group and the Cisplatin group was 4.45 months (95 % CI 4.10–4.80) and 3.96 months (95 % CI 3.68–4.24) (P = 0.03), respectively. The median overall survival (OS) was 10.8 months (95 % CI 10.2–11.5) and 10.7 months (95 % CI 10.2–11.3) (P = 0.72), respectively. There was no statistically significant difference in the occurrence rate of grades 3 and 4 myelotoxicity between the two groups. However, there was a significant difference in the occurrence rate of grades 3 and 4 gastrointestinal reactions and peripheral neurotoxicity between the two groups (P < 0.05). A regime combining Pemetrexed and Oxaliplatin was marginally effective and well tolerated in patients with stage IIIb or IV lung adenocarcinoma who have received Erlotinib as second-line treatment.

Target identification and mechanism of action in chemical biology and drug discovery

Target-identification and mechanism-of-action studies have important roles in small-molecule probe and drug discovery. Biological and technological advances have resulted in the increasing use of cell-based assays to discover new biologically active small molecules. Such studies allow small-molecule action to be tested in a more disease-relevant setting at the outset, but they require follow-up studies to determine the precise protein target or targets responsible for the observed phenotype. Target identification can be approached by direct biochemical methods, genetic interactions or computational inference. In many cases, however, combinations of approaches may be required to fully characterize on-target and off-target effects and to understand mechanisms of small-molecule action.

Targeting MYCN in neuroblastoma by BET bromodomain inhibition

Bromodomain inhibition comprises a promising therapeutic strategy in cancer, particularly for hematologic malignancies. To date, however, genomic biomarkers to direct clinical translation have been lacking. We conducted a cell-based screen of genetically defined cancer cell lines using a prototypical inhibitor of BET bromodomains. Integration of genetic features with chemosensitivity data revealed a robust correlation between MYCN amplification and sensitivity to bromodomain inhibition. We characterized the mechanistic and translational significance of this finding in neuroblastoma, a childhood cancer with frequent amplification of MYCN. Genome-wide expression analysis showed downregulation of the MYCN transcriptional program accompanied by suppression of MYCN transcription. Functionally, bromodomain-mediated inhibition of MYCN impaired growth and induced apoptosis in neuroblastoma. BRD4 knockdown phenocopied these effects, establishing BET bromodomains as transcriptional regulators of MYCN. BET inhibition conferred a significant survival advantage in 3 in vivo neuroblastoma models, providing a compelling rationale for developing BET bromodomain inhibitors in patients with neuroblastoma.

Target identification for small bioactive molecules: finding the needle in the haystack

Identification and confirmation of bioactive small-molecule targets is a crucial, often decisive step both in academic and pharmaceutical research. Through the development and availability of several new experimental techniques, target identification is, in principle, feasible, and the number of successful examples steadily grows. However, a generic methodology that can successfully be applied in the majority of the cases has not yet been established. Herein we summarize current methods for target identification of small molecules, primarily for a chemistry audience but also the biological community, for example, the chemist or biologist attempting to identify the target of a given bioactive compound. We describe the most frequently employed experimental approaches for target identification and provide several representative examples illustrating the state-of-the-art. Among the techniques currently available, protein affinity isolation using suitable small-molecule probes (pulldown) and subsequent mass spectrometric analysis of the isolated proteins appears to be most powerful and most frequently applied. To provide guidance for rapid entry into the field and based on our own experience we propose a typical workflow for target identification, which centers on the application of chemical proteomics as the key step to generate hypotheses for potential target proteins.

Induced pluripotent stem cells in cardiovascular drug discovery

The unexpected discovery that somatic cells can be reprogrammed to a pluripotent state yielding induced pluripotent stem cells has made it possible to produce cardiovascular cells exhibiting inherited traits and disorders. Use of these cells in high throughput analyses should broaden our insight into fundamental disease mechanisms and provide many benefits for patients, including new therapeutics and individually tailored therapies. Here we review recent progress in generating induced pluripotent stem cell-based models of cardiovascular disease and their multiple applications in drug development.