Patient-derived organoids for personalized gallbladder cancer modelling and drug screening

BACKGROUND

Gallbladder carcinoma (GBC) is a relatively rare but highly aggressive cancer with late clinical detection and a poor prognosis. However, the lack of models with features consistent with human gallbladder tumours has hindered progress in pathogenic mechanisms and therapies.

METHODS

We established organoid lines derived from human GBC as well as normal gallbladder and benign gallbladder adenoma (GBA) tissues. The histopathology signatures of organoid cultures were identified by H&E staining, immunohistochemistry and immunofluorescence. The genetic and transcriptional features of organoids were analysed by whole-exome sequencing and RNA sequencing. A set of compounds targeting the most active signalling pathways in GBCs were screened for their ability to suppress GBC organoids. The antitumour effects of candidate compounds, CUDC-101 and CUDC-907, were evaluated in vitro and in vivo.

RESULTS

The established organoids were cultured stably for more than 6 months and closely recapitulated the histopathology, genetic and transcriptional features, and intratumour heterogeneity of the primary tissues at the single-cell level. Notably, expression profiling analysis of the organoids revealed a set of genes that varied across the three subtypes and thus may participate in the malignant progression of gallbladder diseases. More importantly, we found that the dual PI3K/HDAC inhibitor CUDC-907 significantly restrained the growth of various GBC organoids with minimal toxicity to normal gallbladder organoids.

CONCLUSIONS

Patient-derived organoids are potentially a useful platform to explore molecular pathogenesis of gallbladder tumours and discover personalized drugs.

Comparison of Drug Inhibitory Effects ([Formula: see text]) in Monolayer and Spheroid Cultures

Traditionally, the monolayer (two-dimensional) cell cultures are used for initial evaluation of the effectiveness of anticancer drugs. In particular, these experiments provide the [Formula: see text] curves that determine drug concentration that can inhibit growth of a tumor colony by half when compared to the cells grown with no exposure to the drug. Low [Formula: see text] value means that the drug is effective at low concentrations, and thus will show lower systemic toxicity when administered to the patient. However, in these experiments cells are grown in a monolayer, all well exposed to the drug, while in vivo tumors expand as three-dimensional multicellular masses, where inner cells have a limited access to the drug. Therefore, we performed computational studies to compare the [Formula: see text] curves for cells grown as a two-dimensional monolayer and a cross section through a three-dimensional spheroid. Our results identified conditions (drug diffusivity, drug action mechanisms and cell proliferation capabilities) under which these [Formula: see text] curves differ significantly. This will help experimentalists to better determine drug dosage for future in vivo experiments and clinical trials.

CLC-Pred: A freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds

In silico methods of phenotypic screening are necessary to reduce the time and cost of the experimental in vivo screening of anticancer agents through dozens of millions of natural and synthetic chemical compounds. We used the previously developed PASS (Prediction of Activity Spectra for Substances) algorithm to create and validate the classification SAR models for predicting the cytotoxicity of chemicals against different types of human cell lines using ChEMBL experimental data. A training set from 59,882 structures of compounds was created based on the experimental data (IG50, IC50, and % inhibition values) from ChEMBL. The average accuracy of prediction (AUC) calculated by leave-one-out and a 20-fold cross-validation procedure during the training was 0.930 and 0.927 for 278 cancer cell lines, respectively, and 0.948 and 0.947 for cytotoxicity prediction for 27 normal cell lines, respectively. Using the given SAR models, we developed a freely available web-service for cell-line cytotoxicity profile prediction (CLC-Pred: Cell-Line Cytotoxicity Predictor) based on the following structural formula: http://way2drug.com/Cell-line/.

Large-scale integration of heterogeneous pharmacogenomic data for identifying drug mechanism of action

A variety of large-scale pharmacogenomic data, such as perturbation experiments and sensitivity profiles, enable the systematical identification of drug mechanism of actions (MoAs), which is a crucial task in the era of precision medicine. However, integrating these complementary pharmacogenomic datasets is inherently challenging due to the wild heterogeneity, high-dimensionality and noisy nature of these datasets. In this work, we develop Mania, a novel method for the scalable integration of large-scale pharmacogenomic data. Mania first constructs a drug-drug similarity network through integrating multiple heterogeneous data sources, including drug sensitivity, drug chemical structure, and perturbation assays. It then learns a compact vector representation for each drug to simultaneously encode its structural and pharmacogenomic properties. Extensive experiments demonstrate that Mania achieves substantially improved performance in both MoAs and targets prediction, compared to predictions based on individual data sources as well as a state-of-the-art integrative method. Moreover, Mania identifies drugs that target frequently mutated cancer genes, which provides novel insights into drug repurposing.

MicroC(3): an ex vivo microfluidic cis-coculture assay to test chemosensitivity and resistance of patient multiple myeloma cells

Chemosensitivity and resistance assays (CSRAs) aim to direct therapies based upon ex vivo responses of patient tumor cells to chemotherapeutic drugs. However, successful CSRAs are yet to be developed. Here, we exposed primary CD138(+) multiple myeloma (MM) cells to bortezomib, a clinical proteasome inhibitor, in microfluidic-cis-coculture (MicroC(3)) incorporating the patient's own CD138(-) tumor-companion mononuclear cells to integrate some of the patients' own tumor microenvironment components in the CSRA design. Statistical clustering techniques segregated MicroC(3) responses into two groups which correctly identified all seventeen patients as either clinically responsive or non-responsive to bortezomib-containing therapies. In contrast, when the same patient MM samples were analyzed in the absence of the CD138(-) cells (monoculture), the tumor cell responses did not segregate into clinical response clusters. Thus, MicroC(3) identified bortezomib-therapy MM patient responses making it a viable CSRA candidate toward enabling personalized therapy.

Stepwise group sparse regression (SGSR): gene-set-based pharmacogenomic predictive models with stepwise selection of functional priors

Complex mechanisms involving genomic aberrations in numerous proteins and pathways are believed to be a key cause of many diseases such as cancer. With recent advances in genomics, elucidating the molecular basis of cancer at a patient level is now feasible, and has led to personalized treatment strategies whereby a patient is treated according to his or her genomic profile. However, there is growing recognition that existing treatment modalities are overly simplistic, and do not fully account for the deep genomic complexity associated with sensitivity or resistance to cancer therapies. To overcome these limitations, large-scale pharmacogenomic screens of cancer cell lines--in conjunction with modern statistical learning approaches--have been used to explore the genetic underpinnings of drug response. While these analyses have demonstrated the ability to infer genetic predictors of compound sensitivity, to date most modeling approaches have been data-driven, i.e. they do not explicitly incorporate domain-specific knowledge (priors) in the process of learning a model. While a purely data-driven approach offers an unbiased perspective of the data--and may yield unexpected or novel insights--this strategy introduces challenges for both model interpretability and accuracy. In this study, we propose a novel prior-incorporated sparse regression model in which the choice of informative predictor sets is carried out by knowledge-driven priors (gene sets) in a stepwise fashion. Under regularization in a linear regression model, our algorithm is able to incorporate prior biological knowledge across the predictive variables thereby improving the interpretability of the final model with no loss--and often an improvement--in predictive performance. We evaluate the performance of our algorithm compared to well-known regularization methods such as LASSO, Ridge and Elastic net regression in the Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (Sanger) pharmacogenomics datasets, demonstrating that incorporation of the biological priors selected by our model confers improved predictability and interpretability, despite much fewer predictors, over existing state-of-the-art methods.

TGI-Simulator: a visual tool to support the preclinical phase of the drug discovery process by assessing in silico the effect of an anticancer drug

This paper presents TGI-Simulator, a software tool designed to show, through a 2-D graphical animation, the simulated time effect of an anticancer drug on a tumor mass by exploiting the well-known Tumor Growth Inhibition (TGI) model published by Simeoni et al. [1]. Simeoni TGI model is a mathematical model routinely used by pharma companies and researchers during the drug development process. The application is based on a Java graphical user interface (GUI) including a self installing differential equation solver implemented in Matlab together with an optimization algorithm that performs model identification via Weighted Least Squares (WLS). However, it can graphically show also the simulation results obtained within other scientific software tools, if they are preventively stored into a suitable ASCII file. The tool would be a valid support also for researchers with no specific skills in scientific calculations and in pharmacokinetic and pharmacodynamic modeling but daily involved in pharma companies drug development processes at different levels. The availability of a movie with a temporal varying 2-D iconographic representation is an original instrument to communicate results and learn Simeoni TGI model and its potential application in preclinical studies.

In vitro cytotoxic activity of Aesculus indica against breast adenocarcinoma cell line (MCF-7) and phytochemical analysis

Aesculus indica (Linn.) (Sapindaceae) is an ethanobotanically important plant specie traditionally used against rheumatism, skin and vein complaints. Cytotoxic potential of Aesculus indica crude leaf extract and its fractions was investigated against MCF-7 cell line. Crude extract of Aesculus indica was prepared in methanol by maceration technique. Crude extract was fractionated into four organic and one aqueous fraction on polarity basis. MTT assay was used to evaluate the reduction of viability of MCF-7 breast cancer cell line. Cell viability was inhibited by Aesculus indica crude extract in a dose dependent manner ranging from 34.2% at 10 μg/ml to 94% at 500μg/ml. Activity was found in an ascending order from hexane showing 29.8% inhibition to aqueous fraction indicating maximum inhibition, 60%. Phytochemical analysis of crude and fractionated extracts revealed presence of flavonoids, saponins, coumarins and tannins upto varying degrees. Methanol and aqueous fraction of methanol extract of Aesculus indica can be good source of cytotoxic compounds.

Methods and goals for the use of in vitro and in vivo chemosensitivity testing

Sensitive, specific, and accurate methods to assay chemosensitivity are needed to (1) screen new therapeutic agents, (2) identify patterns of chemosensitivity for different tumor types, (3) establish patterns of cross-resistance and sensitivity in treatment of naïve and relapsing tumors, (4) identify genomic and proteomic profiles associated with sensitivity, (5) correlate in vitro response with preclinical in vivo effects and clinical outcomes for a particular therapeutic agent, and (6) tailor chemotherapy regimens to individual patients. Various methods are available to achieve these end points, including several in vitro clonogenic and proliferation assays, cell metabolic activity assays, molecular assays to monitor expression of markers for responsiveness, drug resistance, and for induction of apoptosis, in vivo tumor growth and survival assays in metastatic and orthotopic models, and in vivo imaging assays. The advantages and disadvantages of the specific assays are discussed. A summary of research questions related to chemosensitivity testing is also included.

Discovery and characterization of inhibitors of human palmitoyl acyltransferases

The covalent attachment of palmitate to specific proteins by the action of palmitoyl acyltransferases (PAT) plays critical roles in the biological activities of several oncoproteins. Two PAT activities are expressed by human cells: type 1 PATs that modify the farnesyl-dependent palmitoylation motif found in H- and N-Ras, and type 2 PATs that modify the myristoyl-dependent palmitoylation motif found in the Src family of tyrosine kinases. We have previously shown that the type 1 PAT HIP14 causes cellular transformation. In the current study, we show that mRNA encoding HIP14 is up-regulated in a number of types of human tumors. To assess the potential of HIP14 and other PATs as targets for new anticancer drugs, we developed three cell-based assays suitable for high-throughput screening to identify inhibitors of these enzymes. Using these screens, five chemotypes, with activity toward either type 1 or type 2 PAT activity, were identified. The activity of the hits were confirmed using assays that quantify the in vitro inhibition of PAT activity, as well as a cell-based assay that determines the abilities of the compounds to prevent the localization of palmitoylated green fluorescent proteins to the plasma membrane. Representative compounds from each chemotype showed broad antiproliferative activity toward a panel of human tumor cell lines and inhibited the growth of tumors in vivo. Together, these data show that PATs, and HIP14 in particular, are interesting new targets for anticancer compounds, and that small molecules with such activity can be identified by high-throughput screening.

Anticancer drug clustering in lung cancer based on gene expression profiles and sensitivity database

background

The effect of current therapies in improving the survival of lung cancer patients remains far from satisfactory. It is consequently desirable to find more appropriate therapeutic opportunities based on informed insights. A molecular pharmacological analysis was undertaken to design an improved chemotherapeutic strategy for advanced lung cancer.

Methods

We related the cytotoxic activity of each of commonly used anti-cancer agents (docetaxel, paclitaxel, gemcitabine, vinorelbine, 5-FU, SN38, cisplatin (CDDP), and carboplatin (CBDCA)) to corresponding expression pattern in each of the cell lines using a modified NCI program.

Results

We performed gene expression analysis in lung cancer cell lines using cDNA filter and high-density oligonucleotide arrays. We also examined the sensitivity of these cell lines to these drugs via MTT assay. To obtain our reproducible gene-drug sensitivity correlation data, we separately analyzed two sets of lung cancer cell lines, namely 10 and 19. In our gene-drug correlation analyses, gemcitabine consistently belonged to an isolated cluster in a reproducible fashion. On the other hand, docetaxel, paclitaxel, 5-FU, SN-38, CBDCA and CDDP were gathered together into one large cluster.

Conclusion

These results suggest that chemotherapy regimens including gemcitabine should be evaluated in second-line chemotherapy in cases where the first-line chemotherapy did not include this drug. Gene expression-drug sensitivity correlations, as provided by the NCI program, may yield improved therapeutic options for treatment of specific tumor types.

Early Identification of False Positives in High-Throughput Screening for Activators of p53-DNA Interaction

Naturally occurring mutant forms of p53 are deficient for specific DNA binding. However, their specific DNA binding can be reactivated. The search for small molecules that reactivate latent p53 is considered to be a cornerstone in cancer therapy. The authors describe a new homogeneous fluorescent assay approach for the characterization of binding affinities of human wild-type latent and activated p53 using DNA*spec(26), with and without the addition of the antibody PAb421, respectively, and fluorescence correlation spectroscopy (FCS)/2-dimensional fluorescence-intensity distribution analysis anisotropy as the detection methods. FCS was compared with 2D-FIDA anisotropy, and a very good correlation of the results with both readouts was observed (KDs for nonspecific DNA binding of 24.4 ± 3.5 nM with 2D-FIDA anisotropy and of 29.5 ± 5.5 nM with FCS). The presence of poly(dI-dC) led to a 10-fold increase of binding affinity (KD of 3.3 ± 0.5 nM in the presence of PAb421). 2D-FIDA anisotropy was demonstrated to be the most accurate readout; hence, this detection technology was selected for a 25,000 compound member high-throughput screening (HTS) campaign. The hits obtained were qualified using a novel data evaluation algorithm that identifies false positives and moreover assesses the validity of true hits in the presence of the deteriorating artifact. This process step is of utmost importance for decreasing the attrition in fluorescence-based HTS.

Learning a predictive model for growth inhibition from the NCI DTP human tumor cell line screening data: does gene expression make a difference?

We address the problem of learning a predictive model for growth inhibition from the NCI DTP human tumor cell line screening data. Extending the classical Quantitative Structure Activity Relationship paradigm, we investigate whether including gene expression data leads to a statistically significant improvement of prediction quality. Our analysis shows that the straightforward approach of including individual gene expression as features does not necessarily improve, but on the contrary, may degrade performance significantly. When gene expression information is aggregated, for instance by features representing the correlation with reference cell lines, performance can be improved significantly. Further improvements may be expected if the learning task is structured by grouping features and instances.

Estimation of cancer drug potencies and relative potencies from in vitro data

A method is proposed for the estimation of drug or toxicity potencies using in vitro data. A typical experiment in cancer research is presented where cells from a tumor-derived cell line were deposited as fixed volumes in 12-well cell culture plates. After waiting for 72 hours (for further growth), the wells were exposed to different concentrations of a drug and, at the end of the experiment, the numbers of surviving cells were counted. In this article, the "standard model" is extended to take explicit account of the error structure generated by the two experimental stages, namely, the cell deposition stage (and growth, prior to challenging by drug) and the cell counting stage (by hemacytometer) that are fundamental to the design but have usually been ignored in the modeling process. A simulation study illustrates substantial gains in efficiency in the estimation of the median effective dose.

Are syngeneic mouse tumor models still valuable experimental models in the field of anti-cancer drug discovery?

To establish the pharmacological profile of a molecule with anti-cancer potential, it seems essential to add an in vivo approach to the first pharmacological experiments carried out in vitro. The present study aims to characterize the degree of sensitivity of seven syngeneic models (two leukemias and five solid tumors) to eleven molecules which have proven to be clinically reliable. We also used some of these models to investigate whether the molecular effects on the extent of growth in a subcutaneously grafted experimental model correlate with the effects of the same drug on the survival of the animals so grafted. Our data show that all the molecules demonstrated significant anti-tumor activities in two mouse leukemia models (with some discrepancies between the two). Two lymphoma models displayed weaker chemosensitivity profiles than the two leukemia models from which they were developed. Two other models, namely the MXT-HS mammary carcinoma and the B16 melanoma, appeared to be rather chemoresistant. However, a direct relationship was evident between the drug-induced decrease in the tumor growth rate and the increase observed in the survival periods of the MXT tumor-bearing mice. This relationship was also observed in the L1210_LYM lymphoma, though to a lesser extent, and was completely absent from the B16 melanoma model. Finally, our data indicated that we had developed a pair of metastasizing, as opposed to non-metastasizing, lymphoma and mammary carcinoma models. In conclusion, the present study shows that syngeneic mouse tumor models can be used as valuable in vivo experimental models for the screening of potential anti-cancer agents.

(+)-discodermolide: a marine natural product against cancer

(+)-Discodermolide was isolated in 1990 by Gunasekera et al. from the deep-water Caribbean sponge Discodermia dissoluta. It attacks cancer cells in a similar way to the successful cancer drug Taxol® that has become the best-selling anticancer drug in history. Taxol is also the first natural product described that stabilizes the microtubules involved in many aspects of cellular biology and that represent an important target of anticancer chemotherapeutics. However, (+)-discodermolide appears to be far more potent than Taxol® against tumors that have developed multiple-drug resistance, with an IC₅₀ in the low nanomolar range. Due to these excellent results, this natural product was licensed to Novartis Pharmaceutical Corporation in early 1998. The present review covers the history, biological activity, total synthesis, and synthetic analogs of (+)-discodermolide.

A functional genomic study on NCI's anticancer drug screen

Pharmacogenomics requires massive computer exploration on heterogeneous databases. COMPARE, the gateway to the NCI's anticancer drug screen database, allows users to correlate drug-sensitivity profiles with a functional genomic database. However, most drugs of known molecular mechanism turn out to be uncorrelated with their molecular-target gene expression. Based on a novel statistical concept, liquid association, we develop an on-line system to identify candidate genes that intervene, confound and weaken the drug-gene correlation. The system takes queries and returns button-clickable tables of functionally associated genes for rerouting to knowledgebases such as Locus Link, OMIM and PubMed. We report results that link methotrexate resistance to DNA component biosynthesis, and taxol sensitivity to genes associated with human immunodeficiency virus infection. The drug-sensitivity database can be synergistically coanalyzed with gene expression data to study proteins of poorly understood physiological roles. When applied to the human prion, a cellular context embroidered with the gene expression network of Alzheimer disease is revealed.

Proteomic profiling of the NCI-60 cancer cell lines using new high-density reverse-phase lysate microarrays

Because most potential molecular markers and targets are proteins, proteomic profiling is expected to yield more direct answers to functional and pharmacological questions than does transcriptional profiling. To aid in such studies, we have developed a protocol for making reverse-phase protein lysate microarrays with larger numbers of spots than previously feasible. Our first application of these arrays was to profiling of the 60 human cancer cell lines (NCI-60) used by the National Cancer Institute to screen compounds for anticancer activity. Each glass slide microarray included 648 lysate spots representing the NCI-60 cell lines plus controls, each at 10 two-fold serial dilutions to provide a wide dynamic range. Mouse monoclonal antibodies and the catalyzed signal amplification system were used for immunoquantitation. The signal levels from the >30,000 data points for our first 52 antibodies were analyzed by using p-scan and a quantitative dose interpolation method. Clustered image maps revealed biologically interpretable patterns of protein expression. Among the principal early findings from these arrays were two promising pathological markers for distinguishing colon from ovarian adenocarcinomas. When we compared the patterns of protein expression with those we had obtained for the same genes at the mRNA level by using both cDNA and oligonucleotide arrays, a striking regularity appeared: cell-structure-related proteins almost invariably showed a high correlation between mRNA and protein levels across the NCI-60 cell lines, whereas non-cell-structure-related proteins showed poor correlation.

Luminescence applications for chemotherapeutic drug development

The application of in vitro and in vivo ATP bioluminescence systems as an integrated approach for preclinical research and development of new chemotherapeutic drugs is described. This approach includes both (a) the in vitro tumor response assay (TRA) system that utilizes new technologies for cell culture and ATP measurement of clinical specimens and (b) the use of human tumor cell lines transfected with Photinus pyralis luciferase (luc) gene for both in vitro and in vivo studies. Dried reagent microplates for TRA culture and counting procedures are described for a two-stage TRA method, which can be used to evaluate drug sensitivity and resistance of cells from clinical specimens after initial drug exposure in vitro. The use of dried reagent counting plates for screening and testing of agents against tumor cell lines is described, as well as an alternative method for screening and testing chemotherapeutic drugs in vitro with luc-transfected human tumor cell lines. The potential application of luc-transfected reporter cell lines for in vivo studies of drug activity with photon imaging for analysis is discussed.

Photocarcinogenesis: measuring the reproducibility of a biologic response to ultraviolet radiation exposure in mice

New drugs undergo safety evaluations of many types. For some drugs, a photocarcinogenesis study forms one of the elements in the overall toxicology package. Photocarcinogenesis studies are designed to evaluate a drug's ability to modify the growth and development of ultraviolet radiation (UVR)-induced skin tumors in albino hairless mice. "Exposure control" groups in such studies receive the UVR, either alone, or in combination with the "vehicle" or carrier associated with each study. This report presents skin tumor data from control groups compiled from nine consecutive studies conducted at this testing facility. The endpoints evaluated included median tumor onset, mortality-free prevalence and tumor yield. "Historical control data" are considered essential for designing, monitoring, interpreting and evaluating studies of a given type. In addition, a compilation of such control data can illustrate trends or provide measures of reproducibility more reliably than can individual studies. This data set shows how clearly the UVR-induced skin tumor onset time is dependent on UVR dose, how skin tumors develop sooner in female mice than in male mice at a low UVR exposure dose, and that topical administration of certain vehicle formulations can enhance photocarcinogenesis.

In vitro screening for antitumour activity of Clinopodium vulgare L. (Lamiaceae) extracts

Aqueous extract of Clinopodium vulgare L. showed strong antitumour activity when tested in vitro on A2058 (human metastatic melanoma), HEp-2 (epidermoid carcinoma, larynx, human) and L5178Y (mouse lymphoma) cell lines-6 h after treatment disintegration of the nuclei and cell lysis started. Applied at a concentration of 80 microg/ml it reduced the cell survival to 1.0, 5.6 and 6.6%, respectively. The concentrations of aqueous extract inhibiting the growth of A2058, HEp-2 and L5178Y cells by 50% (IC50 values) were calculated to be 20, 10 and 17.8 microg/ml respectively. Two groups of active substances were detected: the first one, probably combining glycosides, influenced adhesion, while the second one caused massive cell vacuolisation. The chloroform extract, which contained ursolic acid and gentriacontan had also cytotoxic, however a little bit weaker effect. All changes observed were irreversible.

Anticancer drug delivery systems: multi-loaded N4-acyl poly(ethylene glycol) prodrugs of ara-C. II. Efficacy in ascites and solid tumors

The synthesis of branched PEG (40,000) acids has been achieved using aspartic acid (Asp) and AspAsp dendrons. Complete conjugation of these dendritic acids with cytosine arabinoside (ara-C) was achieved by the use of spacers that allowed a greater separation of the branches to accommodate several large ara-C molecules in proximity to each other. The tetrameric and octameric PEG-ara-C amide prodrugs were much more effective in the treatment of solid and ascites tumors compared to the native drug. The greater loading of the PEG backbone appears to have achieved a minimum threshold concentration for the therapeutic delivery of ara-C.

Synthesis and tumoricidal activity evaluation of new morin and quercetin sulfonic derivatives

Flavonoids are a group of naturally occurring compounds with interesting medical properties, such as antiinflammatory, antiallergic, antiviral, antibacterial and antitumor activities. In our experiments we were trying to examine the tumoricidal activity of newly synthesized derivatives of two flavonoids: 3,5,7,2',4'-pentahydroxyflavone (morin) and 3,5,7,3',4'-pentahydroxyflavone (quercetin). These derivatives were: natrium salt of morin-5'-sulfonic acid (NaMSA), natrium salt of quercetin-5'-sulfonic acid (NaQSA), complex of Mg2+ with quercetin-5'-sulfonic acid (QSA), complex of iron(II) with QSA. The antitumor activity of these agents was tested in vitro on two cell lines: L1210--murine lymphocytic leukaemia and P-815--murine mastocytoma. Our experiments showed that sulfonic derivatives of these two flavonoids were less potent than the original agents in their cytostatic and cytotoxic activities. However, their solubility in water was greater than that of the original agents and higher culture medium concentration of these derivatives was obtained. The results indicate that the ability of flavonoids to act tumoricidally is reciprocally correlated with their lipophilicity.

Antitumor activity of milk kefir and soy milk kefir in tumor-bearing mice

The effects of oral administration of milk and soy milk kefirs on tumor growth in tumor-bearing mice and the mucosal immunoglobulin A response in mice were studied. Oral administration of milk and soy milk kefirs to mice inoculated with sarcoma 180 tumor cells resulted in 64.8% and 70.9% inhibition of tumor growth, respectively, compared with controls. In addition, oral administration of the two kefir types induced apoptotic tumor cell lysis. Total immunoglobulin A levels for tissue extracts from the wall of the small intestine were also significantly higher for mice fed a milk kefir or a soy milk kefir regimen for 30 days. These results suggest that milk and soy milk kefirs may be considered among the more promising food components in terms of cancer prevention and enhancement of mucosal resistance to gastrointestinal infection.

Anti-tumor-promoting activity of the diterpene from Excoecaria agallocha. II

Eight new diterpenoids (1-8) have been isolated from the wood of Excoecaria agallocha (Euphorbiaceae) and their inhibitory effects on the induction of Epstein-Barr virus early antigen (EBV-EA) in Raji cells were examined to search for potent anti-tumor-promoters from natural resources. Of these compounds, the secolabdane-type diterpenoid, compound 7 exhibited a remarkable inhibitory effect on EBV-EA induction, and a significant anti-tumor-promoting effect in the mouse two-stage carcinogenesis test using 7,12-dimethylbenz[a]anthracene and 12-O-tetradecanovl-phorbol-13-acetate.

Development of distamycin-related DNA binding anticancer drugs

The relatively low therapeutic index of the clinically used alkylating agents is probably related to the fact that these compounds cause DNA damage in a relatively unspecific manner, mainly involving guanine-cytosine rich stretches of DNA present in virtually all genes, therefore inducing unselective growth inhibition and death, both in neoplastic and in highly proliferative normal tissues. These considerations explain why in the last twenty years there has been an increasing interest in the identification of compounds which can target DNA with a much higher degree of sequence specificity than that of conventional alkylators. Minor groove binders (MGBs) are one of the most widely studied class of alkylating agents characterised by a high level of sequence specificity. The prototype of this class of drugs is distamycin A which is an antiviral compound able to interact, non-covalently, in theminor groove of DNA in A-T rich regions. It is not cytotoxic against tumour cells and thus has been used as a carrier for targeting cytotoxic alkylating moieties in theminor groove of DNA. The benzoyl mustard derivative of distamycin A, tallimustine, was found to be able to alkylate the N(3) of adenine in theminor groove of DNA only in the target hexamer 5'-TTTTGA or 5'-TTTTAA. Tallimustine was investigated in the clinic and was not successful because it causes severe bone marrow toxicity. The screening of other distamycin derivatives, which maintain antitumour activity and exhibit much lower toxicity against human bone marrow cells than tallimustine led to the identification of brostallicin (PNU-166196) which is currently under early clinical investigation. Although MGBs which bind DNA in A-T rich regions have not fulfilled the expectations, it is too early to draw definitive conclusions on this class of compounds. The peculiar bone-marrow toxicity observed in the clinic both with tallimustine or with CC-1065 derivatives is not necessarily a feature of all MGBs, as indicated by recent evidence obtained with brostallicin and other structurally unrelated MGBs (e.g., ET-743).

Mining and visualizing large anticancer drug discovery databases

In order to find more effective anticancer drugs, the U.S. National Cancer Institute (NCI) screens a large number of compounds in vitro against 60 human cancer cell lines from different organs of origin. About 70,000 compounds have been tested in the program since 1990, and each tested compound can be characterized by a vector (i.e., "fingerprint") of 60 anticancer activity, or -[log(GI50)], values. GI50 is the concentration required to inhibit cell growth by 50% compared with untreated controls. Although cell growth inhibitory activity for a single cell line is not very informative, activity patterns across the 60 cell lines can provide incisive information on the mechanisms of action of screened compounds and also on molecular targets and modulators of activity within the cancer cells. Various statistical and artificial intelligence methods, including principal component analysis, hierarchical cluster analysis, stepwise linear regression, multidimensional scaling, neural network modeling, and genetic function approximation, among others, can be used to analyze this large activity database. Mining the database can provide useful information: (a) for the development of anticancer drugs; (b) for a better understanding of the molecular pharmacology of cancer; and (c) for improvement of the drug discovery process.

The DiSC assay. A cost-effective guide to treatment for chronic lymphocytic leukemia?

The differential staining cytotoxicity (DiSC) assay involves in vitro drug panel testing against patient tumor cells to identify optimal therapy. This observational study investigated whether DiSC assay guided treatment could improve outcome in patients with chronic lymphocytic leukemia. A cohort of 178 patients were categorized either as sensitive to drugs in vitro and receiving a sensitive drug in vivo, sensitive in vitro but not treated with a sensitive drug, or having disease resistant to all drugs tested in vitro. Response and survival for these patient categories were compared using multivariate regression techniques. Patients receiving a sensitive drug, compared with those who though having sensitivity did not, had a higher remission rate (odds ratio, 6.5; 95% CI, 2.91-14.53) and reduced death rate (hazard ratio, 0.29; 95% CI, 0.16-0.53). Having adjusted for all known confounding factors, the results suggest that in vitro drug sensitivity is an important independent prognostic variable to include in future trials, and that the DiSC assay may be a cost-effective use of health resources: the estimated incremental cost-effectiveness was 1,470 Pounds per life-year gained. A randomized controlled trial is required to confirm the benefit and estimate reliably the potential impact of assay-guided choice of therapy.

[The targetted delivery of antitumor preparations by using protein vectors]

The prospects of the endocytosis-mediated targeted delivery of antitumor drugs to the target cells by means of vector proteins, such as nerve growth factor (NGF), epidermal growth factor (EGF), and the oncofetal protein alpha-fetoprotein (AFP), are discussed. The high selectivity and efficiency of antitumor effects of synthetic covalent EGF- and AFP-conjugates with chemical agents (antitumor antibiotics) and antisense oligonucleotides are compared with individual biologically active compounds in in vitro and in vivo animal studies. The molecular mechanisms of action of the above conjugates have been studied. Evidence is given for the fact that it is expedient to use them to overcome multidrug resistance in the clinical setting. The findings are the first important step in designing novel target antitumor drugs based on biologically active vector proteins showing their effects by receptor-mediated endocytosis.

[The determination of individual sensitivity to 5-fluorouracil in patients with malignant tumors in different locations]

Possible determination of individual chemosensitivity of tumors to 5-fluorouracil was investigated using new original data and suggestions that lymphocytes of the tumor carrier have an ability to assimilate chemical drugs. Such an ability is likely due to the fact that 5-fluorouracil as an antimetabolite converted its action by inclusion of lymphocytes to the nucleic acid metabolism. The relation between the phenomenon and the chemotherapy efficacy is possibly realized through two mechanisms. One of them is the direct cytotoxic action of chemical drugs on lymphocyte tumor-associated clones resulting in impairment of the tumor growth control. The other is possible participation of lymphocytes in transport of chemical drugs to the tumor tissue. The in vitro model for estimation of tumor carrier chemosensitivity by the level of the nucleic acid metabolism reflects the impact of the immune system on realization of the antitumor effect of chemical drugs.

The effect of paclitaxel on the radiosensitivity of gynecological tumor cells

BACKGROUND

Paclitaxel, a natural product from Taxus brevifolia, is a microtubule stabilizing agent, which has been shown to block different cells in the G2/M phase of the cell cycle and consequently, to modulate their radioresponsiveness. Our aim was to test the cytotoxic and radiosensitizing potential of paclitaxel, with respect to different gynecological tumors with varying radiosensitivities.

MATERIAL AND METHOD

We performed clonogenic assays and flow cytometry on 2 cell lines, MCF-7 (breast) and CaSki (cervix) cells, and on 2 primary ovarian tumor samples (OC-I and OC-II). The cells were irradiated with 200 kV X-rays, radiation doses of up to 8 Gy were applied either as single doses or in 2 Gy fractions. Paclitaxel concentrations varied from 0.07 to 700 nM, incubation times varied from 3 to 120 h.

RESULTS

Paclitaxel alone changed the cell cycle distribution of the cells tested and was cytotoxic in a time and concentration dependent manner. When combined with radiation, most schedules resulted in additive effects of the combined treatments. However, for MCF-7 cells, when 7 nM paclitaxel, applied 24 h before irradiation, were combined with fractionated irradiation a supra-additive effect with a SER of 1.2 was found. For CaSki cells, under comparable conditions the SER was 1.13 but the effects were not statistically significant.

CONCLUSION

Under specific conditions, paclitaxel exerted a weak radiosensitizing effect on breast and cervical carcinoma cells. A therapeutic gain may be possible on the basis of an optimal paclitaxel/radiation scheduling.

Combination of computerized morphonuclear and multivariate analyses to characterize in vitro the antineoplastic effect of alkylating agents

The influence of 13 anticancer alkylating agents on cell proliferation, cell cycle parameters, and morphonuclear characteristics was monitored in vitro on three neoplastic cell lines. This monitoring was carried out by means of the digital cell image analysis of Feulgen-stained nuclei. This computer-assisted microscope analysis of chromatin texture made it possible to assess 15 morphonuclear parameters. These 15 parameters were submitted to multivariate analyses, that is, principal-components analyses followed by the canonical transformation of the data. The 13 alkylating agents included four nitrogen mustards (chlormethine, chlorambucil, melphalan, and cyclophosphamide), two nitrosoureas (carmustine and lomustine), two platinum analogues (cisplatine and carboplatine), two ethyleneimine derivatives (thiotepa and investigational PE1001), one antibiotic (mitomycin C), one alkylsulfonate (busulfan), and one triazene (dacarbazine). The mouse MXT mammary and the human J82 and T24 bladder tumor cell lines were used in this study. The results show that these alkylating agents induced specific modifications to the chromatin pattern according to the subclass to which they belong. In other words, the multivariate statistical analyses of the 15 parameters made it possible to identify, at least partly, distinct subclasses of alkylating agents according to their mechanisms of action. As a validation of the methodology, the results also show that most of the alkylating agents induced an increase in the percentage of cells in the G2 phase, while some sometimes induced an increase in the percentage of cells in the S phase of the cell cycle.

TCA-100 tumour chemosensitivity assay: differences in sensitivity between cultured tumour cell lines and clinical studies

The BATLE LE TCA-100 tumour chemosensitivity assay has been used to evaluate chemotherapeutic drug sensitivity of cultured tumour cell lines. Studies were performed using test drug concentrations calibrated to discriminate sensitivity and resistance of clinical specimens. Strong sensitivity which appeared to be inconsistent with clinical experience was detected for some drugs and cell lines. Findings of strong sensitivity were consistent with basic differences between sensitivity testing cultured cell lines and clinical specimens. Results with cell lines frequently may not apply directly to clinical applications. Characterization of differences between cell lines and clinical specimens may assist in application of cell line findings to clinical trials.

Discrimination techniques applied to the NCI in vitro anti-tumour drug screen: predicting biochemical mechanism of action

The National Cancer Institute currently tests approximately 400 compounds per week against a panel of human tumour cell lines in order to identify potential anti-cancer drugs. We describe several approaches, based on these in vitro data, to the problem of identifying the primary biochemical mechanism of action of a compound. Using linear and non-parametric discriminant procedures and cross-validation, we find that accurate identification of the mechanism of action is achieved for approximately 90 per cent of a diverse collection of 141 known compounds, representing six different mechanistic categories. We demonstrate that two-dimensional graphical displays of the compounds in terms of the initial three principal components (of the original data) result in suggestive visual clustering according to mechanism of action. Finally, we compare the classification accuracy of the statistical discrimination procedures with the accuracy obtained from a neural network approach and, for our example, we find that the results obtained from the various approaches are similar.

Statistical analysis of animal cancer chemoprevention experiments

We explore the use of a statistical model proposed by Kokoska (1987, Biometrics 43, 525-534) for the analysis of animal cancer chemoprevention experiments. We show, using an example, that the results derived from the method can be sensitive to the parametric forms of the distributions that are assumed, particularly to the distribution of the number of tumors per animal. We propose goodness-of-fit tests to aid in the choice of the distributions.

Exploratory data analytic techniques to evaluate anticancer agents screened in a cell culture panel

Information theory is used to provide a measure of selectivity, i.e., the degree to which a drug has preferential toxicity or growth inhibition for one or a few cell lines from a large panel. The selectivity measure is intended to complement a measure of differential growth inhibition in evaluating the drug development potential of a new compound. Also, a similarity measure obtained from information theory is used to classify drugs according to their pattern of responses on the panel. Some structure-activity relations emerge. This work is applied to 176 agents selected to be tested by the National Cancer Institute in about 50 cell lines.

Analysis of multiple tumor data from a rodent carcinogenicity experiment

Rodent tumorigenicity experiments are conducted to determine the safety of substances for human exposure. The carcinogenicity of a substance is generally determined by statistical tests that compare the effects of treatment on the rate of tumor development at several body sites. The statistical analysis of such studies often includes hypothesis testing of the dose effect at each of the sites. However, the multiplicity of the significance tests may cause an excess overall false positive rate. In consideration of this problem, recent interest has focused on developing methods to test simultaneously for the treatment effect at multiple sites. In this paper, we propose a test that is based on the count of tumor-bearing sites. The test is appropriate regardless of tumor lethality or of treatment-related differences in the underlying mortality. Simulations are given which compare the performance of the proposed test to several other tests including a Bonferroni adjustment of site-specific tests, and the test is illustrated using the data from the large ED01 experiment.