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Supplementary Table 1 from Batracylin (NSC 320846), a Dual Inhibitor of DNA Topoisomerases I and II Induces Histone γ-H2AX as a Biomarker of DNA Damage

To date, over 100 small-molecule oncology drugs have been approved by the FDA. Because of the inherent heterogeneity of tumors, these small molecules are often administered in combination to prevent emergence of resistant cell subpopulations. Therefore, new combination strategies to overcome drug resistance in patients with advanced cancer are needed. In this study, we performed a systematic evaluation of the therapeutic activity of over 5,000 pairs of FDA-approved cancer drugs against a panel of 60 well-characterized human tumor cell lines (NCI-60) to uncover combinations with greater than additive growth-inhibitory activity. Screening results were compiled into a database, termed the NCI-ALMANAC (A Large Matrix of Anti-Neoplastic Agent Combinations), publicly available at https://dtp.cancer.gov/ncialmanac. Subsequent in vivo experiments in mouse xenograft models of human cancer confirmed combinations with greater than single-agent efficacy. Concomitant detection of mechanistic biomarkers for these combinations in vivo supported the initiation of two phase I clinical trials at the NCI to evaluate clofarabine with bortezomib and nilotinib with paclitaxel in patients with advanced cancer. Consequently, the hypothesis-generating NCI-ALMANAC web-based resource has demonstrated value in identifying promising combinations of approved drugs with potent anticancer activity for further mechanistic study and translation to clinical trials. Cancer Res; 77(13); 3564–76. ©2017 AACR.

Background The National Cancer Institute drug pair screening effort against 60 well-characterized human tumor cell lines (NCI-60) presents an unprecedented resource for modeling combinational drug activity. Results We present a computational model for predicting cell line response to a subset of drug pairs in the NCI-ALMANAC database. Based on residual neural networks for encoding features as well as predicting tumor growth, our model explains 94% of the response variance. While our best result is achieved with a combination of molecular feature types (gene expression, microRNA and proteome), we show that most of the predictive power comes from drug descriptors. To further demonstrate value in detecting anticancer therapy, we rank the drug pairs for each cell line based on model predicted combination effect and recover 80% of the top pairs with enhanced activity. Conclusions We present promising results in applying deep learning to predicting combinational drug response. Our feature analysis indicates screening data involving more cell lines are needed for the models to make better use of molecular features.

Phosphorylated H2AX (γ-H2AX) is a sensitive marker for DNA double-strand breaks (DSBs), but the variability of H2AX expression in different cell and tissue types makes it difficult to interpret the meaning of the γ-H2AX level. Furthermore, the assays commonly used for γ-H2AX detection utilize laborious and low-throughput microscopy-based methods. We describe here an ELISA assay that measures both phosphorylated H2AX and total H2AX absolute amounts to determine the percentage of γ-H2AX, providing a normalized value representative of the amount of DNA damage. We demonstrate the utility of the assay to measure DSBs introduced by either ionizing radiation or DNA-damaging agents in cultured cells and in xenograft models. Furthermore, utilizing the NCI-60 cancer cell line panel, we show a correlation between the basal fraction of γ-H2AX and cellular mutation levels. This additional application highlights the ability of the assay to measure γ-H2AX levels in many extracts at once, making it possible to correlate findings with other cellular characteristics. Overall, the γ-H2AX ELISA represents a novel approach to quantifying DNA damage, which may lead to a better understanding of mutagenic pathways in cancer and provide a useful biomarker for monitoring the effectiveness of DNA-damaging anticancer agents.

The NCI-60 cell lines are the most frequently studied human tumor cell lines in cancer research. This panel has generated the most extensive cancer pharmacology database worldwide. In addition, these cell lines have been intensely investigated, providing a unique platform for hypothesis-driven research focused on enhancing our understanding of tumor biology. Here, we report a comprehensive analysis of coding variants in the NCI-60 panel of cell lines identified by whole exome sequencing, providing a list of possible cancer specific variants for the community. Furthermore, we identify pharmacogenomic correlations between specific variants in genes such as TP53, BRAF, ERBBs, and ATAD5 and anticancer agents such as nutlin, vemurafenib, erlotinib, and bleomycin showing one of many ways the data could be used to validate and generate novel hypotheses for further investigation. As new cancer genes are identified through large-scale sequencing studies, the data presented here for the NCI-60 will be an invaluable resource for identifying cell lines with mutations in such genes for hypothesis-driven research. To enhance the utility of the data for the greater research community, the genomic variants are freely available in different formats and from multiple sources including the CellMiner and Ingenuity websites. Cancer Res; 73(14); 4372–82. ©2013 AACR.

Flavoprotein-dependent reactive oxygen species (ROS) play a critical role in cytokine-mediated signal transduction in normal tissues and tumor cells. The flavoenzyme inhibitors diphenylene iodonium (DPI) and di-2-thienyliodonium (DTI) have been used to inhibit membrane-bound, flavoprotein-containing NADPH oxidases, including epithelial and leukocyte NADPH oxidases (Nox1-5 and Duox 1 and 2). Recent evidence suggests that DPI can decrease tumor cell proliferation; however, the molecular mechanisms involved remain poorly defined. To explore the mechanisms underlying DPI- and DTI-related tumor cell growth delay, we examined growth inhibition patterns produced by both agents in the NCI-60 tumor panel, and determined expression levels of Nox gene family members across these cell lines. Possible molecular targets were predicted using the COMPARE program. DPI was more potent than DTI (GI(50): 10nM versus 10μM); DPI and DTI exposure produced unique patterns of growth inhibition when evaluated against the small molecule anticancer database of the National Cancer Institute. Growth inhibition profiling of DPI revealed a modest positive correlation with Nox1 levels; novel mechanisms of DPI and DTI action, including alterations in Stat, Erk1/2, and Akt pathways, were inferred by correlation with NCI-60 Affymetrix(®) array data. Exposure of HT-29 colon cancer cells, which express Nox1, to DPI and DTI confirmed their inhibitory effects on steady state ROS levels, and demonstrated decreased Stat, Erk1/2, and Akt signaling mediated by IL-4, IL-6, IL-13, and IL-22, possibly due to a concomitant increase in tumor cell phosphatase activity. These findings suggest that DPI and DTI may act therapeutically by altering ROS-related signal transduction.

The rapid development of new therapeutic agents that target specific molecular pathways involved in tumour cell proliferation provides an unprecedented opportunity to achieve a much higher degree of biochemical specificity than previously possible with traditional chemotherapeutic anticancer agents. However, the lack of specificity of these established chemotherapeutic drugs allowed a relatively straightforward approach to their use in combination therapies. Developing a paradigm for combining new, molecularly targeted agents, on the other hand, is substantially more complex. The abundance of molecular data makes it possible, at least in theory, to predict how such agents might interact across crucial growth control networks. Initial strategies to examine molecularly targeted agent combinations have produced a small number of successes in the clinic. However, for most of these combination strategies, both in preclinical models and in patients, it is not clear whether the agents being combined actually hit their targets to induce growth inhibition. Here, we consider the initial approach of the US National Cancer Institute (NCI) to the evaluation of combinations of molecularly targeted anticancer agents in patients and provide a description of several new approaches that the NCI has initiated to improve the effectiveness of combination-targeted therapy for cancer.

Since the early 1990s the Developmental Therapeutics Program of the National Cancer Institute (NCI) has utilized a panel of 60 human tumor cell lines (NCI60) representing 9 tissue types to screen for potential new anticancer agents. To date, about 100,000 compounds and 50,000 natural product extracts have been screened. Early in this program it was discovered that the pattern of growth inhibition in these cell lines was similar for compounds of similar mechanism. The development of the COMPARE algorithm provided a means by which investigators, starting with a compound of interest, could identify other compounds whose pattern of growth inhibition was similar. With extensive molecular characterization of these cell lines, COMPARE and other user-defined algorithms have been used to link patterns of molecular expression and drug sensitivity. We describe here the results of screening current Food and Drug Administration (FDA)-approved anticancer agents in the NCI60 screen, with an emphasis on those agents that target signal transduction. We analyzed results from agents with mechanisms of action presumed to be similar; we also carried out a hierarchical clustering of all of these agents. The addition of data from recently approved anticancer agents will increase the utility of the NCI60 databases to the cancer research community. These data are freely accessible to the public on the DTP website (http://dtp.cancer.gov/). The FDA-approved anticancer agents are themselves available from the NCI as a plated set of compounds for research use. Mol Cancer Ther; 9(5); 1451–60. ©2010 AACR.

A large number of hormones and local agonists activating guanine-binding protein-coupled receptors (GPCR) play a major role in cancer progression. Here, we characterize the new imidazo-pyrazine derivative BIM-46174, which acts as a selective inhibitor of heterotrimeric G-protein complex. BIM-46174 prevents the heterotrimeric G-protein signaling linked to several GPCRs mediating (a) cyclic AMP generation (Gαs), (b) calcium release (Gαq), and (c) cancer cell invasion by Wnt-2 frizzled receptors and high-affinity neurotensin receptors (Gαo/i and Gαq). BIM-46174 inhibits the growth of a large panel of human cancer cell lines, including anticancer drug-resistant cells. Exposure of cancer cells to BIM-46174 leads to caspase-3-dependent apoptosis and poly(ADP-ribose) polymerase cleavage. National Cancer Institute COMPARE analysis for BIM-46174 supports its novel pharmacologic profile compared with 12,000 anticancer agents. The growth rate of human tumor xenografts in athymic mice is significantly reduced after administration of BIM-46174 combined with either cisplatin, farnesyltransferase inhibitor, or topoisomerase inhibitors. Our data validate the feasibility of targeting heterotrimeric G-protein functions downstream the GPCRs to improve anticancer chemotherapy. (Cancer Res 2006; 66(18): 9227-34)

Indenoisoquinolines are topoisomerase (Top) I inhibitors developed to overcome some of the limitations of camptothecins and expand their anticancer spectrum. Bis-1,3-{(5,6-dihydro-5,11-diketo-11H-indeno[1,2-c]isoquinoline)-6-propylamino}-propane bis(trifluoroacetate) (NSC 727357) is a novel dimeric indenoisoquinoline derivative with potent antiproliferative activity in the NCI-60 cell line panel, promising hollow fiber activity (score of 32) and activity against xenografts. Submicromolar concentrations of the bisindenoisoquinoline NSC 727357 induce Top1 cleavage complexes at specific sites in biochemical assays. At higher concentrations, inhibition of Top1 catalytic activity and DNA intercalation is observed. NSC 727357 also induces a limited number of Top2-DNA cleavage complexes. In contrast to the effect of other Top1 inhibitors, cells treated with the bisindenoisoquinoline NSC 727357 show an arrest of cell cycle progression in G(1) with no significant inhibition of DNA synthesis after a short exposure to the drug. Moreover, unlike camptothecin and the indenoisoquinoline MJ-III-65 (NSC 706744, 6-[3-(2-hydroxyethyl)aminopropyl]-5,6-dihydro-5,11-diketo-2,3-dimethoxy-(methylenedioxy)-11H-indeno[1,2-c]isoquinoline hydrochloride), the cytotoxicity of bisindenoisoquinoline NSC 727357 is only partially dependent on Top1 and p53, indicating that this drug has additional targets besides Top1 and Top2.

Tubulysin A (tubA) is a natural product isolated from a strain of myxobacteria that has been shown to depolymerize microtubules and induce mitotic arrest. The potential of tubA as an anticancer and antiangiogenic agent is explored in the present study. tubA shows potent antiproliferative activity in a panel of human cancer cell lines irrespective of their multidrug resistance properties. It induces apoptosis in cancer cells but not in normal cells and shows significant potential antiangiogenic properties in several in vitro assays. It is efficacious in initial animal studies using a hollow fibre assay with 12 different human tumour cell lines. This study suggests that both in vitro and preclinical profiles of tubA may translate into clinically useful anticancer properties.

Among the biologically active indolocarbazoles, rebeccamycin, a microbial metabolite produced by Saccharothrix aerocolonigenes, is a well-known topoisomerase (Topo) I poison. In the course of structure-activity relationship studies on rebeccamycin analogs, we have prepared a large number of indolocarbazole derivatives and have shown that, depending on the structural modifications, the cytotoxic effects may be, or not, directly correlated to DNA binding and Topo I inhibition. This suggests that if DNA binding and Topo I play a part in the biological activity of these compounds, other cellular targets might be involved. This paper reports the results of the antiproliferative activities (evaluated in the National Cancer Institute's in vitro panel of 60 tumor cell lines) and the results of a COMPARE analysis run with rebeccamycin derivatives to identify other potential biological targets for these compounds.

Transcript profiling, using microarray or other analogous technologies, to query on a large-scale the expression of genes in tumours or their derivative cell lines has numerous potential uses in oncology drug discovery and development. Characterisation of genes expressed in tumours may allow tumours to be separated into subsets defining subtypes that have a distinctive pathway utilisation. The molecular entities comprising the pathways which distinguish one disease subset from another then become potential candidate drug targets. Alternatively, gene expression patterns may be correlated with the degree of antiproliferative effect of candidate drug leads. This can reveal aspects of the drug's action that could serve to provide a further basis for benchmarking the generation of analogues or provide important information about pathways potentially modulated by the drug in achieving cytotoxicity. New information is emerging that the expression of drug transport-related molecules is a major variable that can be usefully explored using gene expression data, and the features promoting successful drug handling by the tumour cell may be an additional variable which can be illuminated by gene expression studies.

CD95 type I and II cells differ in their dependence on mitochondria to execute apoptosis, because antiapoptotic members of the Bcl-2 family render only type II cells resistant to death receptor-induced apoptosis. They can also be distinguished by a more efficient formation of the death-inducing signaling complex in type I cells. We have identified a soluble form of CD95 ligand (S2) that is cytotoxic to type II cells but does not kill type I cells. By testing 58 tumor cell lines of the National Cancer Institute's anticancer drug-screening panel for apoptosis sensitivity to S2 and performing death-inducing signaling complex analyses, we determined that half of the CD95-sensitive cells are type I and half are type II. Most of the type I cell lines fall into a distinct class of tumor cells expressing mesenchymal-like genes, whereas the type II cell lines preferentially express epithelium-like markers. This suggests that type I and II tumor cells represent different stages of carcinogenesis that resemble the epithelial–mesenchymal transition. We then screened the National Cancer Institute database of >42,000 compounds for reagents with patterns of growth inhibition that correlated with either type I or type II cell lines and found that actin-binding compounds selectively inhibited growth of type I cells, whereas tubulin-interacting compounds inhibited growth of type II cells. Our analysis reveals fundamental differences in programs of gene expression between type I and type II cells and could impact the way actin- and microtubule-disrupting antitumor agents are used in tumor therapy.

The influence of natural products upon drug discovery in general has been quite impressive; one only has to look at the number of clinically active drugs that are in use in cancer therapy to see how many either are natural products or have a natural pro-duct pharmacophore. What is now becoming quite apparent is that materials from natural sources are excellent probes (indicators) for cellular targets that when modulated, may well have a deleterious effect upon the cycling of a tumor cell through the conventional cell cycle. If the particular target is not expressed in normal cell cycling, then a directed "perturbation" of the tumor cell's cycle may well lead to a novel method of treatment for specific tumor types. In this review we have not attempted to be exhaustive but have given a current overview of how natural products from marine, microbial and plant sources have permitted in-depth analyses of various parts of the cell cycle under varying conditions with the ultimate aims of attempting to "control or perturb" the cycling of tumor cells in a fashion that permits their ultimate removal via cellular death, with a minimum of trauma to the host.

Epithelial-mesenchymal transition (EMT) is a critical process implicated in metastasis. Despite extensive research, the clinical significance of EMT remains unclear, and a quantitative evaluation of this process in human tumors has yet to be demonstrated. We previously reported a validated EMT immunofluorescence assay (EMT-IFA), that utilizes β-catenin as a tumor segmentation marker to delineate tumor tissue from surrounding stroma in FFPE tumor biopsies. The assay accurately quantifies individual expression and co-localization of E-cadherin (E) and vimentin (V) in tumor cells (Navas et al. NCI-EORTC 2015). We used this assay to measure changes in both the total number and the corresponding EMT phenotypes of tumor cells in xenograft tissues following treatment with various anticancer agents currently in clinical trials at the NCI. Daily treatment for 14 days with the multikinase inhibitor pazopanib caused significant tumor regression and delayed regrowth in the epithelial (E+) gastric cancer xenograft model MKN45, and the tumor cells remaining after treatment were significantly shifted toward a mesenchymal (V+) phenotype. In contrast, pazopanib (QDx15) had less anti-tumor efficacy in the mesenchymal gastric cancer xenograft model SNU5. In another instance, daily treatment of the MDA-MB-468 breast cancer xenograft model with the BCR-Abl kinase inhibitor nilotinib for 19 days did not demonstrate any significant anti-tumor efficacy or change in the predominance of the E+ phenotype, whereas a cycle of treatment with the anti-tubulin agent paclitaxel (Q3Dx4) led to MDA-MB-468 tumor regression and delayed tumor regrowth after completion of the treatment cycle. Furthermore, the combination of nilotinib with paclitaxel not only significantly diminished the total MDA-MB-468 tumor cell number compared to single-agent arms, but also effectively transformed the EMT phenotype of the tumor, with only a subset of cancer cells surviving by the last day of treatment, which were mostly CD44+CD133+ mesenchymal cells and potential cancer stem cells. The changes in EMT phenotype brought on by effective drug treatments occurred via preferential killing of cells with E+ phenotype, suggesting that V+ and V+E+ tumor cells may be more resistant to therapy. The EMT-IFA provides a much-needed analysis tool suitable for clinical investigation of the proposed role of EMT in tumor progression, metastasis, and acquired drug resistance, and is able to detect changes in EMT signature which may serve as early indicators of treatment efficacy and tumor resistance. Funded by NCI Contract No. HHSN261200800001E. Citation Format: Tony Navas, Melinda G. Hollingshead, Suzanne Borgel, John P. Carter, Angelena Millione, Brad A. Gouker, Donna Butcher, Susan Holbeck, Apurva K. Srivastava, Robert J. Kinders, Donald P. Bottaro, Shivaani Kumar, Alice Chen, James H. Doroshow, Ralph E. Parchment. A clinically validated multiplex immunofluorescence assay for the quantitative assessment of changes in EMT phenotypes in FFPE tumor tissues in response to cancer therapeutics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 845. doi:10.1158/1538-7445.AM2017-845

We profiled the expression of the 48 human nuclear receptors (NRs) by quantitative RT-PCR in 51 human cancer cell lines of the NCI60 collection derived from nine different tissues. NR mRNA expression accurately classified melanoma, colon, and renal cancers, whereas lung, breast, prostate, central nervous system, and leukemia cell lines exhibited heterogeneous receptor expression. Importantly, receptor mRNA levels faithfully predicted the growth-inhibitory qualities of receptor ligands in nonendocrine tumors. Correlation analysis using NR expression profiles and drug response information across the cell line panel uncovered a number of new potential receptor-drug interactions, suggesting that in these cases, individual receptor levels may predict response to chemotherapeutic interventions. Similarly, by cross-comparing receptor levels within our expression dataset and relating these profiles to existing microarray gene expression data, we defined interactions among receptors and between receptors and other genes that can now be mechanistically queried. This work supports the strategy of using NR expression profiling to classify various types of cancer, define NR-drug interactions and receptor-gene networks, predict cancer-drug sensitivity, and identify druggable targets that may be pharmacologically manipulated for potential therapeutic intervention.

ABCG2 is an ATP-binding cassette transporter that counts multiple anticancer compounds among its substrates and is believed to regulate oral bioavailability as well as serve a protective role in the blood-brain barrier, the maternal-fetal barrier, and hematopoietic stem cells. We sought to determine whether novel compounds that interact with the transporter could be identified through analysis of cytotoxicity profiles recorded in the NCI Anticancer Drug Screen database. A flow cytometric assay was used to measure ABCG2 function in the 60 cell lines and generate a molecular profile for COMPARE analysis. This strategy identified >70 compounds with Pearson correlation coefficients (PCCs) >0.4, where reduced drug sensitivity correlated with ABCG2 expression, as well as >120 compounds with PCCs < −0.4, indicating compounds to which ABCG2 expression conferred greater sensitivity. Despite identification of known single nucleotide polymorphisms in the ABCG2 gene in a number of the cell lines, omission of these lines from the COMPARE analysis did not affect PCCs. Available compounds were subjected to validation studies to confirm interaction with the transporter, including flow cytometry, [125I]IAAP binding, and cytotoxicity assays, and interaction was documented in 20 of the 27 compounds studied. Although known substrates of ABCG2 such as mitoxantrone or topotecan were not identified, we characterized three novel substrates—5-hydroxypicolinaldehyde thiosemicarbazone (NSC107392), (E)-N-(1-decylsulfanyl-3-hydroxypropan-2-yl)-3-(6-methyl-2,4-dioxo-1H-pyrimidin-5-yl)prop-2-enamide (NSC265473), and 1,2,3,4,7-pentahydroxy-1,3,4,4a,5,11b-hexahydro[1,3]dioxolo[4,5-j]phenanthridin-6(2H)-one [NSC349156 (pancratistatin)]—and four compounds that inhibited transporter function—2-[methyl(2-pyridin-2-ylethyl)-amino]fluoren-9-one hydroiodide (NSC24048), 5-amino-6-(7-amino-5,8-dihydro-6-methoxy-5,8-dioxo-2-quinolinyl)-4-(2-hydroxy-3,4-dimethoxyphenyl)-3-methyl-2-pyridinecarboxylic acid, methyl ester (NSC45384), (17β)-2,4-dibromo-estra-1,3,5(10)-triene-3,17-diol (NSC103054), and methyl N-(pyridine-4-carbonylamino)carbamodithioate (NSC636795). In summary, COMPARE analysis of the NCI drug screen database using the ABCG2 functional profile was able to identify novel substrates and transporter-interacting compounds.

Batracylin (8-aminoisoindolo [1,2-b]quinazolin-10(12H)-one; NSC320846) is an investigational clinical anticancer agent. Previous animal studies showed activity against solid tumors and Adriamycin-resistant leukemia. We initially sought to test the proposed Top2-mediated DNA cleavage activity of batracylin and identify potential biomarkers for activity. COMPARE analysis in the NCI-60 cell lines showed batracylin activity to be most closely related to the class of Top2 inhibitors. The 50% growth inhibition (GI50) value for batracylin in HT29 colon carcinoma cells was 10 μmol/L. DNA-protein cross-links, consistent with Top2 targeting, were measured by alkaline elution. DNA single-strand breaks were also detected and found to be protein associated. However, only a weak induction of DNA double-strand breaks was observed. Because batracylin induced almost exclusively DNA single-strand breaks, we tested batracylin as a Top1 inhibitor. Batracylin exhibited both Top1- and Top2α/β-mediated DNA cleavage in vitro and in cells. The phosphorylation of histone (γ-H2AX) was tested to measure the extent of DNA damage. Kinetics of γ-H2AX “foci” showed early activation with low μmol/L concentrations, thus presenting a useful early biomarker of DNA damage. The half-life of γ-H2AX signal reversal after drug removal was consistent with reversal of DNA-protein cross-links. The persistence of the DNA-protein complexes induced by batracylin was markedly longer than by etoposide or camptothecin. The phosphorylated DNA damage–responsive kinase, ataxia telangiectasia mutated, was also found activated at sites of γ-H2AX. The cell cycle checkpoint kinase, Chk2, was only weakly phosphorylated. Thus, batracylin is a dual Top1 and Top2 inhibitor and γ-H2AX could be considered a biomarker in the ongoing clinical trials. [Cancer Res 2007;67(20):9971–9]

Adenoviral vectors are commonly used for liver-directed gene therapy following systemic administration owing to their strong propensity for hepatocyte transduction. However, many disease applications would benefit from the delivery of adenoviruses to alternate tissues via this route. Research has thus focused on stripping the virus of native hepatic tropism in conjunction with modifying virus capsid proteins to incorporate novel tropism. Recently, the KO1S* adenovirus serotype 5 fiber mutant, devoid of both coxsackie and adenovirus receptor binding in the fiber knob domain and mutated at the putative heparan sulphate proteoglycan binding site in the fiber shaft, was shown to possess strikingly poor hepatic tropism in mice, rats, and non-human primates. Thus, it is an ideal candidate for retargeting strategies. We therefore assessed the ability of peptide-modified KO1S* fibers to retarget adenovirus. Peptide insertions were well tolerated and virions produced to high titers. However, expected retargeting at the level of transduction was not observed, despite cell-binding studies showing enhanced vector targeting at the cell surface. Cy3 labeling studies showed retarded trafficking of S*-containing fibers. Taken together, our data demonstrates that KO1S* mutant fibers are ineffective for cell retargeting strategies.

TPS2614 Background: We conducted a systematic combination drug screen across the NCI-60 cell line panel encompassing nearly all pairwise combinations of FDA-approved small-molecule cancer drugs ( >...

2559 Background: Gamma-H2AX (γH2AX) is a biomarker for DNA double-strand breaks and programmed cell death, but variable relative amounts of H2AX in different samples causes ambiguity in the meaning...

The facilitative glucose transporter Glut-1 is overexpressed and confers poor prognosis in a wide range of solid tumours. The peri-necrotic pattern of expression often seen in human tumour samples is linked with its transcriptional control in hypoxic conditions by hypoxia-inducible factor HIF-1 or through a reduced rate of oxidative phosphorylation. Hypoxia-regulated genes offer promise as novel therapeutic targets as a means of preventing the proliferation and eventual metastatic spread of tissue originating from residual chemically and radio resistant hypoxic cells that have survived treatment. Inhibiting the expression or functionality of Glut-1 may be a way of specifically targeting hypoxic cells within the tumour that depend upon a high rate of glucose uptake for anaerobic glycolysis. We used an array of formalin-fixed, paraffin-embedded samples of the NCI-60 panel of cell lines to carry out immunohistochemical detection of Glut-1 and to select possible candidate lead compounds by COMPARE analysis with agents from the NCI diversity screen, which may work via inhibition of Glut-1 or Glut-1-dependent processes. "Positive" COMPARE hits were mostly conjugated Pseudomonas toxins binding the epidermal growth factor receptor (EGFR). However, correlations with standard anticancer agents were virtually all negative, indicating a link between Glut-1 and chemoresistance. MTT proliferation assays carried out using stable, Glut-1 overexpressing cell lines generated from the bladder EJ138, human fibrosarcoma HT 1080 and the hepatoma wild type Hepa and HIF-1B-deficient c4 tumour cell lines revealed a cell line-dependent increase in chemoresistance to dacarbazine, vincristine and the bioreductive agent EO9 in Glut-1 overexpressing EJ138 relative to WT and empty vector controls. Metabolomic analysis ((31)P-MRS and (1)H MRS) carried out using cell lysates and xenografts generated from Glut-1 overexpressing Hepa and c4 cell lines showed higher glucose levels in Glut-1 overxpressing c4 relative to parental tumour extracts occurred in the absence of an increase in lactate levels, which were in turn significantly higher in the Glut-1 overexpressing Hepa xenografts. This implies that Glut-1 over-expression without a co-ordinate increase in HIF-1-regulated glycolytic enzymes increases glucose uptake but not the rate of glycolysis. Glut-1 overexpressing xenografts also showed higher levels of phosphodiester (PDE), which relates to the metabolite turnover of phospholipids and is involved in membrane lipid degradation, indicating a mechanism by which Glut-1 may increase cell turnover.

A collection of 60 cell lines derived from human tumors (NCI-60) has been widely explored as a tool for anticancer drug discovery. Here, we profiled the cell surface of the NCI-60 by high-throughput screening of a phage-displayed random peptide library and classified the cell lines according to the binding selectivity of 26,031 recovered tripeptide motifs. By analyzing selected cell-homing peptide motifs and their NCI-60 recognition patterns, we established that some of these motifs (a) are similar to domains of human proteins known as ligands for tumor cell receptors and (b) segregate among the NCI-60 in a pattern correlating with expression profiles of the corresponding receptors. We biochemically validated some of the motifs as mimic peptides of native ligands for the epidermal growth factor receptor. Our results indicate that ligand-directed profiling of tumor cell lines can select functional peptides from combinatorial libraries based on the expression of tumor cell surface molecules, which in turn could be exploited as “druggable” receptors in specific types of cancer. (Cancer Res 2006; 66(1): 34-40)

Purpose: According to some studies, susceptibility of cells to anticancer drug-induced apoptosis is markedly inhibited by targeted deletion of genes encoding apoptotic protease activating factor 1 (Apaf-1) or certain caspases. Information about levels of these polypeptides in common cancer cell types and any possible correlation with drug sensitivity in the absence of gene deletion is currently fragmentary. Experimental Design: Immunoblotting was used to estimate levels of Apaf-1 as well as procaspase-2, -3, -6, -7, -8, and -9 in the 60-cell-line panel used for drug screening by the National Cancer Institute. Sensitivity of the same lines to >80,000 compounds was determined with 48-hour sulforhodamine B binding assays. Additional 6-day assays were performed for selected agents. Results: Levels of Apaf-1 and procaspases varied widely. Apaf-1 and procaspase-9, which are implicated in caspase activation after treatment of cells with various anticancer drugs, were detectable in all of the cell lines, with levels of Apaf-1 ranging from ∼1 × 105 to 2 × 106 molecules per cell and procaspase-9 from ∼5 × 103 to ∼1.6 × 105 molecules per cell. Procaspase-8 levels ranged from 1.7 × 105 to 8 × 106 molecules per cell. Procaspase-3, a major effector caspase, varied from undetectable to ∼1.6 × 106 molecules per cell. Correlations between levels of these polypeptides and sensitivity to any of a variety of experimental or conventional antineoplastic agents in either 2-day or 6-day cytotoxicity assays were weak at best. Conclusions: With the exception of caspase-3, all of the components of the core cell-death machinery are expressed in all of the cell lines examined. Despite variations in expression, levels of any one component are not a major determinant of drug sensitivity in these cells in vitro.

A series of peptidic boronic acids that inhibit the activity of the proteasome were screened by the NCI for activity against a panel of 60 human tumor cell lines. Comparison to data from approx 80,000 other compounds demonstrated that these proteasome inhibitors exhibited a novel pattern of growth inhibition against these cell lines. The potency of these compounds in the cell line screen correlated well with activity against purified proteasomes, indicating that proteasome inhibition was likely causing the growth inhibition. Comparison of bortezomib (formerly known as PS-341) sensitivity to expression levels of thousand of molecular targets within the 60 cell line panel did not yield strong correlations with any single molecular target, consistent with the role of the proteasome in degradation of a multitude of proteins.

As oncology treatment moves toward personalized targeted therapeutic agents, the NCI-60 human tumor cell line panel is an ideal community-wide tool to further understanding of the disease and molecular targets of new agents. The panel includes cell lines from nine tumor types, and is extremely well characterized at the molecular level, enabling interrogation of patterns of growth inhibition by a set of targeted investigational oncology agents looking for characteristics of the cell lines that determine sensitivity. We have used a number of online tools to enable data analysis, including COMPARE (http://dtp.nci.nih.gov/compare/), which provided the identification of compounds and/or genes that have highly correlated response patterns for any selected ‘seed’ compound. These data enable comparisons between drug sensitivity profiles that lead to the elucidation of common mechanistic targets or pathways, associations with potential response biomarkers, the confirmation of mechanism of action or identification of novel mechanisms, and the uncovering of unexpected “off-target” activities. For example, using the allosteric Akt inhibitor MK-2206 as the seed compound, response patterns for the ATP-competitive Akt inhibitors PF-4173640 (0.84), GDC-0068 (0.80), AZD-5363 (0.83), GSK-690693 (0.67), and CCT-128930 (0.69) are highly correlated. In addition, examination of the response profile for vandetinib produced a set of highly correlative agents including the corresponding EGFR inhibitors sapatinib (0.81) and AEE-788 (0.83), as well as the recently FDA-approved BTK inhibitor, ibrutinib (0.72) and the SRC inhibitor, AZD-0530 (0.74). Not surprisingly, kinase profiling of these 5 agents (0.5 uM) showed >90% inhibition of EGFR in all cases. In a third example, the BRAF V600E mutated cell lines were found to be sensitive to the bcr-abl inhibitors bafetinib and rebastinib, similarly to vemurafenib. This association suggested BRAF inhibitory activity for the former agents, which was confirmed through kinase profiling. Moreover, the NCI-60 response pattern for the androgen receptor modulator AZD-3514 has a high correlation with the BET bromodomain inhibitors JQ-1 (0.77), I-Bet-151 (0.80), and I-Bet-762 (0.78), suggesting a commonality of target/pathway for these compounds. Further correlations, associations and hypotheses generated from interrogating the compound response patterns, gene expression profiles, mutations and other characteristics will be presented. Funded by NCI Contract No. HHSN261200800001E. Citation Format: Joel Morris, Mark Kunkel, Eric Polley, Susan Holbeck, Anne Monks, David Evans, Annamaria Rapisarda, Jerry Collins, Beverly Teicher. Interrogation of NCI-60 patterns of growth inhibition in conjunction with investigational oncology agents kinase profiling for the elucidation of mechanistic targets. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5475. doi:10.1158/1538-7445.AM2014-5475

We have acquired >400 investigational oncology agents, comprised primarily of targeted small molecules currently in clinical and/or preclinical anticancer studies. As oncology treatment moves toward personalized targeted therapeutic agents, the NCI-60 human tumor cell line panel is an ideal community-wide tool to further understanding of the disease targets of new agents. The panel includes cell lines from nine tumor types, and is extremely well characterized at the molecular level, with both in-house and crowd-sourced characterization, including exome sequence for mutations, SNPs, DNA methylation, metabolome, mRNA, microRNA, and protein expression. This molecular characterization dataset enables interrogation of patterns of growth inhibition by the investigational drug set looking for characteristics of the cell lines that determine sensitivity. More than 150,000 small molecules, including all (> 100) FDA-approved anticancer drugs and now our acquired set of 400 investigational oncology agents have been screened against the panel for their effects on cell growth. We have used a number of online tools to enable data analysis for this set, including COMPARE (http://dtp.nci.nih.gov/compare/), which provided for the identification of compounds and/or genes that have highly correlated response patterns for any selected ‘seed’ compound. This presentation provides the first public disclosure of the NCI-60 data for this set of novel, targeted, investigational oncology agents. We anticipate that these data will enable comparison between drug sensitivity profiles that could lead to the elucidation of common mechanistic targets or pathways, associations with potential response biomarkers, the confirmation of mechanism of action or identification of novel mechanisms, and the uncovering of unexpected "off-target" activities. For example, Akt, pI3K, PDK, and mTOR inhibitors, multiple agents targeting one signaling pathway, display strong correlations with one another. Using the allosteric Akt inhibitor MK-2206 as the seed compound, response patterns for the ATP-competitive Akt inhibitors PF-4173640 (0.84), GDC-0068 (0.80), AZD-5363 (0.83), GSK-690693 (0.67), and CCT-128930 (0.69) are highly correlative. Moreover, the NCI-60 response pattern for the androgen receptor modulator AZD-3514 has a 0.77 correlation with the BET bromodomain inhibitor JQ-1, suggesting a commonality of target/pathway for these compounds. Further correlations, associations and hypotheses generated from interrogating the compound response patterns, gene expression profiles, mutations and other characteristics will be presented. Funded by NCI Contract No. HHSN261200800001E. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):A102. Citation Format: Joel Morris, Mark Kunkel, Eric Polley, Susan Holbeck, Kazimierz Wrzeszczynski, Anne Monks, David Evans, Annamaria Rapisarda, Jerry Collins, Beverly A. Teicher. NCI-60 response profiles of >400 investigational oncology agents: A resource enabling drug and biomarker discovery. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr A102.

Acquired and constitutional genetic variations in cancers have a substantial influence on response to therapy. The NCI60 panel of cell lines provides a unique opportunity to investigate this problem. These 60 human tumor cell lines represent 9 cancer types, and are richly characterized as the result of many previous studies which have collected various biochemical and genomics data [1]. In addition, there exists a comprehensive dataset of sensitivity and resistance profiles of over 100,000 compounds with potential antineoplastic activity. However, characterization of coding region DNA sequence variants has been lacking. In this study, we sequenced the whole exomes of the NCI60 cell lines and identified single nucleotide variants and short insertions/deletions. Variants found by sequencing were in excellent agreement with variants previously identified by SNP analysis or targeted capillary sequencing. Even though most cell lines displayed similar mutation counts, cell lines with microsatellite instability displayed a hypermutator phenotype. In addition, observation from ti/tv ratio and nature of base changes revealed preservation of possible carcinogen specific DNA mutation signatures. Deleterious variants were identified at higher frequency in known cancer genes while TP53 mutations where the most frequent event among the NCI60. Finally, notable instances of correlation between gene/pathway mutations with sensitivity to certain drug/compounds was identified. For example, sensitivity to vemurafenib was highly correlated with BRAF mutation. This comprehensive dataset enhances the value of cell lines widely used as disease models in many laboratories by adding depth to the existing genomic data. Our analysis identifies a large number of genomic variants correlated with drug responsiveness, including a number of genes known to be targeted by specific agents as well as numerous candidates for future investigation. 1. Shankavaram, U.T., et al., CellMiner: a relational database and query tool for the NCI-60 cancer cell lines. BMC Genomics, 2009. 10: p. 277. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1879. doi:1538-7445.AM2012-1879

We recently discovered that amplification and overexpression of the CKS1B gene, which regulates the ubiquitination and proteasomal degradation of the cyclin-dependent kinase inhibitor p27Kip1, is linked to a poor prognosis in myeloma. We used the COMPARE algorithm (NCI, Developmental Therapeutics Program) to identify correlations between the expression of CKS1B in the NCI 60 cell line panel and the GI50 of nearly 50,000 anticancer compounds. This analysis revealed a strong correlation between CKS1B expression and the anticancer activity of Ellipticine and multiple derivatives of it. Ellipticine (5,11-Dimethyl-6H-Pyrido[4,3]Carbazole, MW=246.3), an alkaloid isolated from Apocyanaceae, is a topoisomerase II poison that induces topoisomerase II-dependent DNA cleavages. Previous studies have shown that the anti-neoplastic mechanism of Ellipticine is to form covalent DNA adducts mediated by human cytochromes P450. We obtained Ellipticine and twelve other CKS1B-correlated antineoplastic compounds from the NCI-DTP. In vitro analyses were carried out with 12 myeloma cell lines. Cell viability was detected using CellTiter-Glo Luminescent Assay (Promega, Co.). We found that one of the Ellipticine derivatives, NSC 338258 (EPED3) showed significant cell kill activity not observed with Ellipticine or the other compounds in all cell lines tested. In a dose response analysis of cell kill using 0.2, 0.02, and 0.002 uM EPED3, 12 out of 12 myeloma cell lines showed at least 50% reduction in cell viability within 24 hrs at 0.2 uM compared to no treatment controls. By 48 hours essentially all cell growth was inhibited. Only weak to moderate cell kill was noted at 0.02 and 0.002 uM at all time points tested. We next tested the activity of the topoisomerase II inhibitor VP-16-213 at the same concentrations and time periods and found only modest reduction of cell viability at day 5 at 0.2uM. Essentially no effect on cell viability was observed at 0.02 and 0.002 uM at any of the time points tested. We next tested whether EPED3 had a comparable anti-myeloma activity as Adriamycin at the same concentrations. Twelve myeloma cell lines were exposed to EPED3, VP-16-213, and Adriamycin at 0.2mM for a total of 5 days. Results of the mean relative luminescence showed that EPED3 promoted an immediate cell proliferation arrest within the first 24 hours of culture, with almost complete cell kill within 3 days. The other drugs were less effective with Adriamycin inducing a > 90% reduction only after 4 days and VP-16 a > 70% reduction at day 5. These data suggests that EPED3 may represent a potential new therapeutic for myeloma. Studies are currently underway to test the efficacy of EPED3 in our in-vivo SCID-Hu mouse model of primary myeloma and results of these studies will be presented.

Background Development of cancer therapeutics partially depends upon selection of appropriate animal models. Therefore, improvements to model selection are beneficial. Results Forty-nine human tumor xenografts at in vivo passages 1, 4 and 10 were subjected to cDNA microarray analysis yielding a dataset of 823 Affymetrix HG-U133 Plus 2.0 arrays. To illustrate mining strategies supporting therapeutic studies, transcript expression was determined: 1) relative to other models, 2) with successive in vivo passage, and 3) during the in vitro to in vivo transition. Ranking models according to relative transcript expression in vivo has the potential to improve initial model selection. For example, combining p53 tumor expression data with mutational status could guide selection of tumors for therapeutic studies of agents where p53 status purportedly affects efficacy (e.g., MK-1775). The utility of monitoring changes in gene expression with extended in vivo tumor passages was illustrated by focused studies of drug resistance mediators and receptor tyrosine kinases. Noteworthy observations included a significant decline in HCT-15 colon xenograft ABCB1 transporter expression and increased expression of the kinase KIT in A549 with serial passage. These trends predict sensitivity to agents such as paclitaxel (ABCB1 substrate) and imatinib (c-KIT inhibitor) would be altered with extended passage. Given that gene expression results indicated some models undergo profound changes with in vivo passage, a general metric of stability was generated so models could be ranked accordingly. Lastly, changes occurring during transition from in vitro to in vivo growth may have important consequences for therapeutic studies since targets identified in vitro could be over- or under-represented when tumor cells adapt to in vivo growth. A comprehensive list of mouse transcripts capable of cross-hybridizing with human probe sets on the HG-U133 Plus 2.0 array was generated. Removal of the murine artifacts followed by pairwise analysis of in vitro cells with respective passage 1 xenografts and GO analysis illustrates the complex interplay that each model has with the host microenvironment. Conclusions This study provides strategies to aid selection of xenograft models for therapeutic studies. These data highlight the dynamic nature of xenograft models and emphasize the importance of maintaining passage consistency throughout experiments. Electronic supplementary material The online version of this article (doi: 10.1186/1471-2164-15-393) contains supplementary material, which is available to authorized users.