Genome-wide mRNA and microRNA profiling of the NCI 60 cell-line screen and comparison of FdUMP[10] with fluorouracil, floxuridine, and topoisomerase 1 poisons

Enhanced Therapeutic Efficacy of the Nanoscale Fluoropyrimidine Polymer CF10 in a Rat Colorectal Cancer Liver Metastasis Model

Combination chemotherapy regimens that include fluoropyrimidine (FP) drugs, e.g., 5-fluorouracil (5-FU), are central to the treatment of colorectal cancer liver metastases (CRLMs), a major cause of cancer mortality. We tested a second-generation FP polymer, CF10, in a CC531/WAGRij syngeneic orthotopic rat model of liver metastasis to determine if CF10 improved response relative to 5-FU. CF10 displayed increased potency relative to 5-FU in CC531 rat colorectal cancer cells based on clonogenic assay results and caused increased apoptosis, as shown using a live/dead assay. The increased potency of CF10 to CC531 cells was associated with increased replication stress, as assessed by Western blot for biomarkers of ATR/Chk1 and ATM/Chk2 pathway activation. CF10 dosed to deliver equivalent FP content as an established dose of 5-FU in rats (50 mg/kg) did not cause weight loss in WAGRij rats even when combined with ethynyl uracil (EU), an inhibitor of dihydropyrimidine dehydrogenase, the enzyme primarily responsible for 5-FU degradation in the liver. In contrast, 5-FU caused significant weight loss that was exacerbated in combination with EU. Importantly, CF10 was significantly more effective than 5-FU at inhibiting tumor progression (~90% reduction) in the CC531/WAG/Rij CRLM model. Our results reveal strong potential for CF10 to be used for CRLM treatment.

Review of 5-FU resistance mechanisms in colorectal cancer: clinical significance of attenuated on-target effects

The emergence of chemoresistant disease during chemotherapy with 5-Fluorouracil-based (5-FU-based) regimens is an important factor in the mortality of metastatic CRC (mCRC). The causes of 5-FU resistance are multi-factorial, and besides DNA mismatch repair deficiency (MMR-D), there are no widely accepted criteria for determining which CRC patients are not likely to be responsive to 5-FU-based therapy. Thus, there is a need to systematically understand the mechanistic basis for 5-FU treatment failure and an urgent need to develop new approaches for circumventing the major causes of 5-FU resistance. In this manuscript, we review mechanisms of 5-FU resistance with an emphasis on: (1) altered anabolic metabolism limiting the formation of the primary active metabolite Fluorodeoxyuridylate (5-Fluoro-2'-deoxyuridine-5'-O-monophosphate; FdUMP); (2) elevated expression or activity of the primary enzymatic target thymidylate synthase (TS); and (3) dysregulated programmed cell death as important causes of 5-FU resistance. Importantly, these causes of 5-FU resistance can potentially be overcome through the use of next-generation fluoropyrimidine (FP) polymers (e.g., CF10) that display reduced dependence on anabolic metabolism and more potent TS inhibitory activity.

Potential Phytochemicals for Prevention of Familial Breast Cancer with BRCA Mutations

Breast cancer has remained a global challenge and the second leading cause of cancer mortality in women and family history. Hereditary factors are some of the major risk factors associated with breast cancer. Out of total breast cancer cases, 5-10% account only for familial breast cancer, and nearly 50% of all hereditary breast cancer are due to BRCA1/BRCA2 germline mutations. BRCA1/2 mutations play an important role not only in determining the clinical prognosis of breast cancer but also in the survival curves. Since this risk factor is known, a significant amount of the healthcare burden can be reduced by taking preventive measures among people with a known history of familial breast cancer. There is increasing evidence that phytochemicals of nutrients and supplements help in the prevention and cure of BRCA-related cancers by different mechanisms such as limiting DNA damage, altering estrogen metabolism, or upregulating expression of the normal BRCA allele, and ultimately enhancing DNA repair. This manuscript reviews different approaches used to identify potential phytochemicals to mitigate the risk of familial breast cancer with BRCA mutations. The findings of this review can be extended for the prevention and cure of any BRCAmutated cancer after proper experimental and clinical validation of the data.

Oligonucleotides Carrying Nucleoside Antimetabolites as Potential Prodrugs

BACKGROUND

Nucleoside and nucleobase antimetabolites are an important class of chemotherapeutic agents for the treatment of cancer as well as other diseases.

INTRODUCTION

In order to avoid undesirable side effects, several prodrug strategies have been developed. In the present review, we describe a relatively unknown strategy that consists of using oligonucleotides modified with nucleoside antimetabolites as prodrugs.

METHODS

The active nucleotides are generated by enzymatic degradation once incorporated into cells. This strategy has attracted large interest and is widely utilized at present due to the continuous developments made in therapeutic oligonucleotides and the recent advances in nanomaterials and nanomedicine.

RESULTS

A large research effort was made mainly in the improvement of the antiproliferative properties of nucleoside homopolymers, but recently, chemically modified aptamers, antisense oligonucleotides and/or siRNA carrying antiproliferative nucleotides have demonstrated a great potential due to the synergetic effect of both therapeutic entities. In addition, DNA nanostructures with interesting properties have been built to combine antimetabolites and enhancers of cellular uptake in the same scaffold. Finally, protein nanoparticles functionalized with receptor-binders and antiproliferative oligomers represent a new avenue for a more effective treatment in cancer therapy.

CONCLUSION

It is expected that oligonucleotides carrying nucleoside antimetabolites will be considered as potential drugs in the near future for biomedical applications.

Targeting O-GlcNAcylation to overcome resistance to anti-cancer therapies

In cancer cells, metabolic reprogramming is associated with an alteration of the O-GlcNAcylation homeostasis. This post-translational modification (PTM) that attaches O-GlcNAc moiety to intracellular proteins is dynamically and finely regulated by the O-GlcNAc Transferase (OGT) and the O-GlcNAcase (OGA). It is now established that O-GlcNAcylation participates in many features of cancer cells including a high rate of cell growth, invasion, and metastasis but little is known about its impact on the response to therapies. The purpose of this review is to highlight the role of O-GlcNAc protein modification in cancer resistance to therapies. We summarize the current knowledge about the crosstalk between O-GlcNAcylation and molecular mechanisms underlying tumor sensitivity/resistance to targeted therapies, chemotherapies, immunotherapy, and radiotherapy. We also discuss potential benefits and strategies of targeting O-GlcNAcylation to overcome cancer resistance.

MYC dosage compensation is mediated by miRNA-transcription factor interactions in aneuploid cancer

We hypothesize that dosage compensation of critical genes arises from systems-level properties for cancer cells to withstand the negative effects of aneuploidy. We identified several candidate genes in cancer multiomics data and developed a biocomputational platform to construct a mathematical model of their interaction network with micro-RNAs and transcription factors, where the property of dosage compensation emerged for MYC and was dependent on the kinetic parameters of its feedback interactions with three micro-RNAs. These circuits were experimentally validated using a genetic tug-of-war technique to overexpress an exogenous MYC, leading to overexpression of the three microRNAs involved and downregulation of endogenous MYC. In addition, MYC overexpression or inhibition of its compensating miRNAs led to dosage-dependent cytotoxicity in MYC-amplified colon cancer cells. Finally, we identified negative correlation of MYC dosage compensation with patient survival in TCGA breast cancer patients, highlighting the potential of this mechanism to prevent aneuploid cancer progression.

Differential Gene Set Enrichment Analysis: a statistical approach to quantify the relative enrichment of two gene sets

MOTIVATION

Gene Set Enrichment Analysis (GSEA) is an algorithm widely used to identify statistically enriched gene sets in transcriptomic data. However, GSEA cannot examine the enrichment of two gene sets or pathways relative to one another. Here we present Differential Gene Set Enrichment Analysis (DGSEA), an adaptation of GSEA that quantifies the relative enrichment of two gene sets.

RESULTS

After validating the method using synthetic data, we demonstrate that DGSEA accurately captures the hypoxia-induced coordinated upregulation of glycolysis and downregulation of oxidative phosphorylation. We also show that DGSEA is more predictive than GSEA of the metabolic state of cancer cell lines, including lactate secretion and intracellular concentrations of lactate and AMP. Finally, we demonstrate the application of DGSEA to generate hypotheses about differential metabolic pathway activity in cellular senescence. Together, these data demonstrate that DGSEA is a novel tool to examine the relative enrichment of gene sets in transcriptomic data.

AVAILABILITY AND IMPLEMENTATION

DGSEA software and tutorials are available at https://jamesjoly.github.io/DGSEA/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Parallel G-quadruplex Structures Increase Cellular Uptake and Cytotoxicity of 5-Fluoro-2'-deoxyuridine Oligomers in 5-Fluorouracil Resistant Cells

Fluoropyrimidines, such as 5-fluorouracil (5-FU) and related prodrugs have been considered first-line chemotherapy agents for the treatment of colorectal cancer. However, poor specificity and tumor cell resistance remain major limiting bottlenecks. G-quadruplexes, have been suggested as preferred nanostructures for enhancing cellular uptake mediated by G-quadruplex binding proteins which are abundant at the membranes of some tumor cells. In the current study, we propose a new strategy to deliver 5-fluoro-2′-deoxyuridine (5-FdU) monophosphate, the main active drug from 5-FU derivatives that may circumvent the cellular mechanisms of FU-resistant cancer cells. Two G-quadruplexes delivery systems containing four and six G-tetrads ((TG₄T) and (TG₆T)) linked to a FdU oligonucleotide were synthesized. Biophysical studies show that the G-quadruplex parallel structures are not affected by the incorporation of the 5 units of FdU at the 5’-end. Internalization studies confirmed the ability of such G-quadruplex nanostructures to facilitate the transport of the FdU pentamer and increase its cytotoxic effect relative to conventional FU drug in FU-resistant colorectal cancer cells. These results suggest that FdU oligomers linked to G-quadruplex parallel sequences may be a promising strategy to deliver fluoropyrimidines to cancer cells.

CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics

CellMiner Cross-Database (CellMinerCDB, discover.nci.nih.gov/cellminercdb) allows integration and analysis of molecular and pharmacological data within and across cancer cell line datasets from the National Cancer Institute (NCI), Broad Institute, Sanger/MGH and MD Anderson Cancer Center (MDACC). We present CellMinerCDB 1.2 with updates to datasets from NCI-60, Broad Cancer Cell Line Encyclopedia and Sanger/MGH, and the addition of new datasets, including NCI-ALMANAC drug combination, MDACC Cell Line Project proteomic, NCI-SCLC DNA copy number and methylation data, and Broad methylation, genetic dependency and metabolomic datasets. CellMinerCDB (v1.2) includes several improvements over the previously published version: (i) new and updated datasets; (ii) support for pattern comparisons and multivariate analyses across data sources; (iii) updated annotations with drug mechanism of action information and biologically relevant multigene signatures; (iv) analysis speedups via caching; (v) a new dataset download feature; (vi) improved visualization of subsets of multiple tissue types; (vii) breakdown of univariate associations by tissue type; and (viii) enhanced help information. The curation and common annotations (e.g. tissues of origin and identifiers) provided here across pharmacogenomic datasets increase the utility of the individual datasets to address multiple researcher question types, including data reproducibility, biomarker discovery and multivariate analysis of drug activity.

Molecular genomic features associated with in vitro response of the NCI-60 cancer cell line panel to natural products

Natural products remain a significant source of anticancer chemotherapeutics. The search for targeted drugs for cancer treatment includes consideration of natural products, which may provide new opportunities for antitumor cytotoxicity as single agents or in combination therapy. We examined the association of molecular genomic features in the well-characterized NCI-60 cancer cell line panel with in vitro response to treatment with 1302 small molecules which included natural products, semisynthetic natural product derivatives, and synthetic compounds based on a natural product pharmacophore from the Developmental Therapeutics Program of the US National Cancer Institute's database. These compounds were obtained from a variety of plant, marine, and microbial species. Molecular information utilized for the analysis included expression measures for 23059 annotated transcripts, lncRNAs, and miRNAs, and data on protein-changing single nucleotide variants in 211 cancer-related genes. We found associations of expression of multiple genes including SLFN11, CYP2J2, EPHX1, GPC1, ELF3, and MGMT involved in DNA damage repair, NOTCH family members, ABC and SLC transporters, and both mutations in tyrosine kinases and BRAF V600E with NCI-60 responses to specific categories of natural products. Hierarchical clustering identified groups of natural products, which correlated with a specific mechanism of action. Specifically, several natural product clusters were associated with SLFN11 gene expression, suggesting that potential action of these compounds may involve DNA damage. The associations between gene expression or genome alterations of functionally relevant genes with the response of cancer cells to natural products provide new information about potential mechanisms of action of these identified clusters of compounds with potentially similar biological effects. This information will assist in future drug discovery and in design of new targeted cancer chemotherapy agents.

A multiple genomic data fused SF2 prediction model, signature identification, and gene regulatory network inference for personalized radiotherapy

Radiotherapy is one of the most important cancer treatments, but its response varies greatly among individual patients. Therefore, the prediction of radiosensitivity, identification of potential signature genes, and inference of their regulatory networks are important for clinical and oncological reasons. Here, we proposed a novel multiple genomic fused partial least squares deep regression method to simultaneously analyze multi-genomic data. Using 60 National Cancer Institute cell lines as examples, we aimed to identify signature genes by optimizing the radiosensitivity prediction model and uncovering regulatory relationships. A total of 113 signature genes were selected from more than 20,000 genes. The root mean square error of the model was only 0.0025, which was much lower than previously published results, suggesting that our method can predict radiosensitivity with the highest accuracy. Additionally, our regulatory network analysis identified 24 highly important ‘hub’ genes. The data analysis workflow we propose provides a unified and computational framework to harness the full potential of large-scale integrated cancer genomic data for integrative signature discovery. Furthermore, the regression model, signature genes, and their regulatory network should provide a reliable quantitative reference for optimizing personalized treatment options, and may aid our understanding of cancer progress mechanisms.

Fluoropyrimidine Modulation of the Anti-Tumor Immune Response-Prospects for Improved Colorectal Cancer Treatment

Chemotherapy modulates the anti-tumor immune response and outcomes depend on the balance of favorable and unfavorable effects of drugs on anti-tumor immunity. 5-Florouracil (5-FU) is widely used in adjuvant chemotherapy regimens to treat colorectal cancer (CRC) and provides a survival benefit. However, survival remains poor for CRC patients with advanced and metastatic disease and immune checkpoint blockade therapy benefits only a sub-set of CRC patients. Here we discuss the effects of 5-FU-based chemotherapy regimens to the anti-tumor immune response. We consider how different aspects of 5-FU's multi-factorial mechanism differentially affect malignant and immune cell populations. We summarize recent studies with polymeric fluoropyrimidines (e.g., F10, CF10) that enhance DNA-directed effects and discuss how such approaches may be used to enhance the anti-tumor immune response and improve outcomes.

Lapatinib-induced annexin A6 upregulation as an adaptive response of triple-negative breast cancer cells to EGFR tyrosine kinase inhibitors

The epidermal growth factor receptor (EGFR) is a major oncogene in triple-negative breast cancer (TNBC), but the use of EGFR-targeted tyrosine kinase inhibitors (TKI) and therapeutic monoclonal antibodies is associated with poor response and acquired resistance. Understanding the basis for the acquired resistance to these drugs and identifying biomarkers to monitor the ensuing resistance remain a major challenge. We previously showed that reduced expression of annexin A6 (AnxA6), a calcium-dependent membrane-binding tumor suppressor, not only promoted the internalization and degradation of activated EGFR but also sensitized TNBC cells to EGFR-TKIs. Here, we demonstrate that prolong (>3 days) treatment of AnxA6-low TNBC cells with lapatinib led to AnxA6 upregulation and accumulation of cholesterol in late endosomes. Basal extracellular signal-regulated kinase 1 and 2 (ERK1/2) activation was EGFR independent and significantly higher in lapatinib-resistant MDA-MB-468 (LAP-R) cells. These cells were more sensitive to cholesterol depletion than untreated control cells. Inhibition of lapatinib-induced upregulation of AnxA6 by RNA interference (A6sh) or withdrawal lapatinib from LAP-R cells not only reversed the accumulation of cholesterol in late endosomes but also led to enrichment of plasma membranes with cholesterol, restored EGFR-dependent activation of ERK1/2 and sensitized the cells to lapatinib. These data suggest that lapatinib-induced AnxA6 expression and accumulation of cholesterol in late endosomes constitute an adaptive mechanism for EGFR-expressing TNBC cells to overcome prolong treatment with EGFR-targeted TKIs and can be exploited as an option to inhibit and/or monitor the frequently observed acquired resistance to these drugs.

Mining Drug-Target Associations in Cancer: Analysis of Gene Expression and Drug Activity Correlations

Cancer is a complex disease affecting millions of people worldwide, with over a hundred clinically approved drugs available. In order to improve therapy, treatment, and response, it is essential to draw better maps of the targets of cancer drugs and possible side interactors. This study presents a large-scale screening method to find associations of cancer drugs with human genes. The analysis is focused on the current collection of Food and Drug Administration (FDA)-approved drugs (which includes about one hundred chemicals). The approach integrates global gene-expression transcriptomic profiles with drug-activity profiles of a set of 60 human cell lines obtained for a collection of chemical compounds (small bioactive molecules). Using a standardized expression for each gene versus standardized activity for each drug, Pearson and Spearman correlations were calculated for all possible pairwise gene-drug combinations. These correlations were used to build a global bipartite network that includes 1007 gene-drug significant associations. The data are integrated into an open web-tool called GEDA (Gene Expression and Drug Activity) which includes a relational view of cancer drugs and genes, disclosing the putative indirect interactions found for FDA-approved drugs as well as the known targets of these drugs. The results also provide insight into the complex action of pharmaceuticals, presenting an alternative view to address predicted pleiotropic effects of the drugs.

Dysregulated Pyrimidine Biosynthesis Contributes to 5-FU Resistance in SCLC Patient-Derived Organoids but Response to a Novel Polymeric Fluoropyrimidine, CF10

Chemo-immunotherapy is central to the treatment of small cell lung cancer (SCLC). Despite modest progress made with the addition of immunotherapy, current cytotoxic regimens display minimal survival benefit and new treatments are needed. Thymidylate synthase (TS) is a well-validated anti-cancer drug target, but conventional TS inhibitors display limited clinical efficacy in refractory or recurrent SCLC. We performed RNA-Seq analysis to identify gene expression changes in SCLC biopsy samples to provide mechanistic insight into the potential utility of targeting pyrimidine biosynthesis to treat SCLC. We identified systematic dysregulation of pyrimidine biosynthesis, including elevated TYMS expression that likely contributes to the lack of efficacy for current TS inhibitors in SCLC. We also identified E2F1-3 upregulation in SCLC as a potential driver of TYMS expression that may contribute to tumor aggressiveness. To test if TS inhibition could be a viable strategy for SCLC treatment, we developed patient-derived organoids (PDOs) from human SCLC biopsy samples and used these to evaluate both conventional fluoropyrimidine drugs (e.g., 5-fluorouracil), platinum-based drugs, and CF10, a novel fluoropyrimidine polymer with enhanced TS inhibition activity. PDOs were relatively resistant to 5-FU and while moderately sensitive to the front-line agent cisplatin, were relatively more sensitive to CF10. Our studies demonstrate dysregulated pyrimidine biosynthesis contributes to drug resistance in SCLC and indicate that a novel approach to target these pathways may improve outcomes.

Entrapment of DNA topoisomerase-DNA complexes by nucleotide/nucleoside analogs

Topoisomerases are well-validated targets for cancer chemotherapy and DNA topoisomerase 1 (Top1) is the sole target of the camptothecin (CPT) class of anticancer drugs. Over the last 20 years, multiple studies have shown Top1 activity is modulated by non-native DNA structures and this can lead to trapping of Top1 cleavage complexes (Top1cc) and conversion to DNA double strand breaks. Among the perturbations to DNA structure that generate Top1cc are nucleoside analogs that are incorporated into genomic DNA during replication including cytarabine, gemcitabine, and 5-fluoro-2'-deoxyuridine (FdU). We review the literature summarizing the role of Top1cc in mediating the DNA damaging and cytotoxic activities of nucleoside analogs. We also summarize studies demonstrating distinct differences between Top1cc induced by nucleoside analogs and CPTs, particularly with regard to DNA repair. Collectively, these studies demonstrate that, while Top1 is a common target for both Top1 poisons such as CPT and nucleoside analogs such as FdU, these agents are not redundant. In recent years, studies have shown that Top1 poisons and nucleoside analogs together with other anti-cancer drugs such as cisplatin cause replication stress and the DNA repair pathways that modulate the cytotoxic activities of these compounds are being elucidated. We present an overview of this evolving literature, which has implications for how targeting of Top1 with nucleoside analogs can be used more effectively for cancer treatment.

Dissecting celastrol with machine learning to unveil dark pharmacology

By coalescing bespoke machine learning and bioinformatics analyses with cell-based assays, we unveil the pharmacology of celastrol. Celastrol is a direct modulator of the progesterone and cannabinoid receptors, and its effects correlate with the antiproliferative activity. We demonstrate how in silico methods may drive systems biology studies for natural products.

Characterizing the cellular attachment receptor for Langat virus

Tick-borne encephalitis infections have increased the last 30 years. The mortality associated to this viral infection is 0.5 to 30% with a risk of permanent neurological sequelae, however, no therapeutic is currently available. The first steps of virus-cell interaction, such as attachment and entry, are of importance to understand pathogenesis and tropism. Several molecules have been shown to interact with tick-borne encephalitis virus (TBEV) at the plasma membrane surface, yet, no studies have proven that these are specific entry receptors. In this study, we set out to characterize the cellular attachment receptor(s) for TBEV using the naturally attenuated member of the TBEV complex, Langat virus (LGTV), as a model. Inhibiting or cleaving different molecules from the surface of A549 cells, combined with inhibition assays using peptide extracts from high LGTV binding cells, revealed that LGTV attachment to host cells is dependent on plasma membrane proteins, but not on glycans or glycolipids, and suggested that LGTV might use different cellular attachment factors on different cell types. Based on this, we developed a transcriptomic approach to generate a list of candidate attachment and entry receptors. Our findings shed light on the first step of the flavivirus life-cycle and provide candidate receptors that might serve as a starting point for future functional studies to identify the specific attachment and/or entry receptor for LGTV and TBEV.

Thymineless Death by the Fluoropyrimidine Polymer F10 Involves Replication Fork Collapse and Is Enhanced by Chk1 Inhibition

We are developing the fluoropyrimidine polymer F10 to overcome limitations of 5-fluorouracil (5-FU) that result from inefficient metabolism to 5-fluoro-2′-deoxyuridine-5′-mono- and tri-phosphate, the deoxyribonucleotide metabolites that are responsible for 5-FU's anticancer activity. F10 is much more cytotoxic than 5-FU to colorectal cancer (CRC) cells; however, the mechanism of enhanced F10 cytotoxicity remains incompletely characterized. Using DNA fiber analysis, we establish that F10 decreases replication fork velocity and causes replication fork collapse, while 1000-fold excess of 5-FU is required to achieve similar endpoints. Treatment of HCT-116 cells with F10 results in Chk1 phosphorylation and activation of intra–S-phase checkpoint. Combining F10 with pharmacological inhibition of Chk1 with either PF-477736 or prexasertib in CRC cells enhanced DNA damage relative to single-agent treatment as assessed by γH2AX intensity and COMET assay. PF-477736 or prexasertib co-treatment also inhibited upregulation of Rad51 levels in response to F10, resulting in reduced homologous repair. siRNA knockdown of Chk1 also increased F10-induced DNA damage assessed and sensitized CRC cells to F10. However, Chk1 knockdown did not inhibit Rad51 upregulation by F10, indicating that the scaffolding activity of Chk1 imparts activity in DNA repair distinct from Chk1 enzymatic activity. Our results indicate that F10 is cytotoxic to CRC cells in part through DNA damage subsequent to replication fork collapse. F10 is ~1000-fold more potent than 5-FU at inducing replication-mediated DNA damage which correlates with the increased overall potency of F10 relative to 5-FU. F10 efficacy can be enhanced by pharmacological inhibition of Chk1.

Drug resistance related to aberrant glycosylation in colorectal cancer

Colorectal cancer (CRC) is the fourth leading cause of cancer-related deaths in the world. Drug resistance of tumour cells remains the main challenge toward curative treatments efficiency. Several epidemiologic studies link emergence and recurrence of this cancer to metabolic disorders. Glycosylation that modifies more than 80% of human proteins is one of the most widepread nutrient-sensitive post-translational modifications. Aberrant glycosylation participates in the development and progression of cancer. Thus, some of these glycan changes like carbohydrate antigen CA 19-9 (sialyl Lewis a, sLea) or those found on carcinoembryonic antigen (CEA) are already used as clinical biomarkers to detect and monitor CRC. The current review highlights emerging evidences accumulated mainly during the last decade that establish the role played by altered glycosylations in CRC drug resistance mechanisms that induce resistance to apoptosis and activation of signaling pathways, alter drug absorption and metabolism, and led to stemness acquisition. Knowledge in this field of investigation could aid to the development of better therapeutic approaches with new predictive biomarkers and targets tied in with adapted diet.

All-atom MD indicates ion-dependent behavior of therapeutic DNA polymer

Understanding the efficacy of and creating delivery mechanisms for therapeutic nucleic acids requires understanding structural and kinetic properties which allow these polymers to promote the death of cancerous cells. One molecule of interest is a 10 mer of FdUMP (5-fluoro-2'-deoxyuridine-5'-O-monophosphate) - also called F10. Here we investigate the structural and kinetic behavior of F10 in intracellular and extracellular solvent conditions along with non-biological conditions that may be efficacious in in vitro preparations of F10 delivery systems. From our all-atom molecular dynamics simulations totaling 80 microseconds, we predict that F10's phosphate groups form close-range interactions with calcium and zinc ions, with calcium having the highest affinity of the five ions investigated. We also predict that F10's interactions with magnesium, potassium and sodium are almost exclusively long-range interactions. In terms of intramolecular interactions, we find that F10 is least structured (in terms of hydrogen bonds among bases) in the 150 mM NaCl (extracellular-like solvent conditions) and most structured in 150 mM ZnCl2. Kinetically, we see that F10 is unstable in the presence of magnesium, sodium or potassium, finding stable kinetic traps in the presence of calcium or zinc.

All-Atom MD Predicts Magnesium-Induced Hairpin in Chemically Perturbed RNA Analog of F10 Therapeutic

Given their increasingly frequent usage, understanding the chemical and structural properties which allow therapeutic nucleic acids to promote the death of cancer cells is critical for medical advancement. One molecule of interest is a 10-mer of FdUMP (5-fluoro-2'-deoxyuridine-5'-O-monophosphate) also called F10. To investigate causes of structural stability, we have computationally restored the 2' oxygen on each ribose sugar of the phosphodiester backbone, creating FUMP[10]. Microsecond time-scale, all-atom, simulations of FUMP[10] in the presence of 150 mM MgCl₂ predict that the strand has a 45% probability of folding into a stable hairpin-like secondary structure. Analysis of 16 μs of data reveals phosphate interactions as likely contributors to the stability of this folded state. Comparison with polydT and polyU simulations predicts that FUMP[10]'s lowest order structures last for one to 2 orders of magnitude longer than similar nucleic acid strands. Here we provide a brief structural and conformational analysis of the predicted structures of FUMP[10], and suggest insights into its stability via comparison to F10, polydT, and polyU.

MutSα's Multi-Domain Allosteric Response to Three DNA Damage Types Revealed by Machine Learning

MutSα is a key component in the mismatch repair (MMR) pathway. This protein is responsible for initiating the signaling pathways for DNA repair or cell death. Herein we investigate this heterodimer's post-recognition, post-binding response to three types of DNA damage involving cytotoxic, anti-cancer agents-carboplatin, cisplatin, and FdU. Through a combination of supervised and unsupervised machine learning techniques along with more traditional structural and kinetic analysis applied to all-atom molecular dynamics (MD) calculations, we predict that MutSα has a distinct response to each of the three damage types. Via a binary classification tree (a supervised machine learning technique), we identify key hydrogen bond motifs unique to each type of damage and suggest residues for experimental mutation studies. Through a combination of a recently developed clustering (unsupervised learning) algorithm, RMSF calculations, PCA, and correlated motions we predict that each type of damage causes MutSα to explore a specific region of conformation space. Detailed analysis suggests a short range effect for carboplatin-primarily altering the structures and kinetics of residues within 10 angstroms of the damaged DNA-and distinct longer-range effects for cisplatin and FdU. In our simulations, we also observe that a key phenylalanine residue-known to stack with a mismatched or unmatched bases in MMR-stacks with the base complementary to the damaged base in 88.61% of MD frames containing carboplatinated DNA. Similarly, this Phe71 stacks with the base complementary to damage in 91.73% of frames with cisplatinated DNA. This residue, however, stacks with the damaged base itself in 62.18% of trajectory frames with FdU-substituted DNA and has no stacking interaction at all in 30.72% of these frames. Each drug investigated here induces a unique perturbation in the MutSα complex, indicating the possibility of a distinct signaling event and specific repair or death pathway (or set of pathways) for a given type of damage.

The NCI-60 Methylome and Its Integration into CellMiner

A unique resource for systems pharmacology and genomic studies is the NCI-60 cancer cell line panel, which provides data for the largest publicly available library of compounds with cytotoxic activity (∼21,000 compounds), including 108 FDA-approved and 70 clinical trial drugs as well as genomic data, including whole-exome sequencing, gene and miRNA transcripts, DNA copy number, and protein levels. Here, we provide the first readily usable genome-wide DNA methylation database for the NCI-60, including 485,577 probes from the Infinium HumanMethylation450k BeadChip array, which yielded DNA methylation signatures for 17,559 genes integrated into our open access CellMiner version 2.0 (https://discover.nci.nih.gov/cellminer). Among new insights, transcript versus DNA methylation correlations revealed the epithelial/mesenchymal gene functional category as being influenced most heavily by methylation. DNA methylation and copy number integration with transcript levels yielded an assessment of their relative influence for 15,798 genes, including tumor suppressor, mitochondrial, and mismatch repair genes. Four forms of molecular data were combined, providing rationale for microsatellite instability for 8 of the 9 cell lines in which it occurred. Individual cell line analyses showed global methylome patterns with overall methylation levels ranging from 17% to 84%. A six-gene model, including PARP1, EP300, KDM5C, SMARCB1, and UHRF1 matched this pattern. In addition, promoter methylation of two translationally relevant genes, Schlafen 11 (SLFN11) and methylguanine methyltransferase (MGMT), served as indicators of therapeutic resistance or susceptibility, respectively. Overall, our database provides a resource of pharmacologic data that can reinforce known therapeutic strategies and identify novel drugs and drug targets across multiple cancer types. Cancer Res; 77(3); 601-12. ©2016 AACR.

Uncovering Large-Scale Conformational Change in Molecular Dynamics without Prior Knowledge

As the length of molecular dynamics (MD) trajectories grows with increasing computational power, so does the importance of clustering methods for partitioning trajectories into conformational bins. Of the methods available, the vast majority require users to either have some a priori knowledge about the system to be clustered or to tune clustering parameters through trial and error. Here we present non-parametric uses of two modern clustering techniques suitable for first-pass investigation of an MD trajectory. Being non-parametric, these methods require neither prior knowledge nor parameter tuning. The first method, HDBSCAN, is fast-relative to other popular clustering methods-and is able to group unstructured or intrinsically disordered systems (such as intrinsically disordered proteins, or IDPs) into bins that represent global conformational shifts. HDBSCAN is also useful for determining the overall stability of a system-as it tends to group stable systems into one or two bins-and identifying transition events between metastable states. The second method, iMWK-Means, with explicit rescaling followed by K-Means, while slower than HDBSCAN, performs well with stable, structured systems such as folded proteins and is able to identify higher resolution details such as changes in relative position of secondary structural elements. Used in conjunction, these clustering methods allow a user to discern quickly and without prior knowledge the stability of a simulated system and identify both local and global conformational changes.

Non-coding RNA/microRNA-modulatory dietary factors and natural products for improved cancer therapy and prevention: Alkaloids, organosulfur compounds, aliphatic carboxylic acids and water-soluble vitamins

Non-coding small RNA molecules, the microRNAs (miRNAs), contribute decisively to the epigenetic regulation processes in cancer cells. Problematic pathogenic properties of cancer cells and the response of cancers towards anticancer drugs are highly influenced by miRNAs. Both increased drug activity and formation of tumor resistance are regulated by miRNAs. Further to this, the survival and proliferation of cancer cells and the formation of metastases is based on the modulated expression of certain miRNAs. In particular, drug-resistant cancer stem-like cells (CSCs) depend on the presence and absence of specific miRNAs. Fortunately, several small molecule natural compounds were discovered that target miRNAs involved in the modulation of tumor aggressiveness and drug resistance. This review gives an overview of the effects of a selection of naturally occurring small molecules (alkaloids, organosulfur compounds, aliphatic carboxylic acids and water-soluble vitamins) on miRNAs that are closely tangled with cancer diseases.

All-Atom Molecular Dynamics Reveals Mechanism of Zinc Complexation with Therapeutic F10

Advancing the use of therapeutic nucleic acids requires understanding the chemical and structural properties that allow these polymers to promote the death of malignant cells. Here we explore Zn²⁺ complexation by the fluoropyrimidine polymer F10, which has strong activities in multiple preclinical models of cancer. Delivery of fluoropyrimidine FdUMP in the 10-residue polymer F10 rather than the nucleobase (5-fluorouracil) allows consideration of metal ion binding effects on drug delivery. The differences in metal ion interactions with fluoropyrimidine compared to normal DNA results in conformation changes that affect protein binding, cell uptake, and codelivery of metals such as zinc, and the cytoxicity thereof. Microsecond-time-scale, all-atom simulations of F10 predict that zinc selectively stabilizes the polymer via interactions with backbone phosphate groups and suggest a mechanism of complexation for the zinc-base interactions shown in previous experimental work. The positive zinc ions are attracted to the negatively charged phosphate groups. Once the Zn²⁺ ions are near F10, they cause the base's N3 nitrogen to deprotonate. Subsequently, magnesium atoms displace zinc from their interactions with phosphate, freeing the zinc ions to interact with the FdU bases by forming weak interactions with the O4 oxygen and the fluorine attached to C5. These interactions of magnesium with phosphate groups and zinc with nucleobases agree with previous experimental results and are seen in MD simulations only when magnesium is introduced after N3 deprotonation, indicating a specific order of metal binding events. Additionally, we predict interactions between zinc and F10's O2 atoms, which were not previously observed. By comparison to 10mers of polyU and polydT, we also predict that the presence of fluorine increases the binding affinity of zinc to F10 relative to analogous strands of RNA and DNA consisting of only native nucleotides.

The applications of the novel polymeric fluoropyrimidine F10 in cancer treatment: current evidence

F10 is a novel polymeric fluoropyrimidine drug candidate with strong anticancer activity in multiple preclinical models. F10 has strong potential for impacting cancer treatment because it displays high cytotoxicity toward proliferating malignant cells with minimal systemic toxicities thus providing an improved therapeutic window relative to traditional fluoropyrimidine drugs, such as 5-fluorouracil. F10 has a unique mechanism that involves dual targeting of thymidylate synthase and Top1. In this review, the authors provide an overview of the studies that revealed the novel aspects of F10's cytotoxic mechanism and summarize results obtained in preclinical models of acute myeloid leukemia, acute lymphocytic leukemia, glioblastoma and prostate cancer that demonstrate the strong potential of F10 to improve treatment outcomes.

Visualizing ensembles in structural biology

Displaying a single representative conformation of a biopolymer rather than an ensemble of states mistakenly conveys a static nature rather than the actual dynamic personality of biopolymers. However, there are few apparent options due to the fixed nature of print media. Here we suggest a standardized methodology for visually indicating the distribution width, standard deviation and uncertainty of ensembles of states with little loss of the visual simplicity of displaying a single representative conformation. Of particular note is that the visualization method employed clearly distinguishes between isotropic and anisotropic motion of polymer subunits. We also apply this method to ligand binding, suggesting a way to indicate the expected error in many high throughput docking programs when visualizing the structural spread of the output. We provide several examples in the context of nucleic acids and proteins with particular insights gained via this method. Such examples include investigating a therapeutic polymer of FdUMP (5-fluoro-2-deoxyuridine-5-O-monophosphate) - a topoisomerase-1 (Top1), apoptosis-inducing poison - and nucleotide-binding proteins responsible for ATP hydrolysis from Bacillus subtilis. We also discuss how these methods can be extended to any macromolecular data set with an underlying distribution, including experimental data such as NMR structures.

Five-Membered Ring Peroxide Selectively Initiates Ferroptosis in Cancer Cells

A 1,2-dioxolane (FINO2) was identified as a lead compound from a screen of organic peroxides. FINO2 does not induce apoptosis, but instead initiates ferroptosis, an iron-dependent, oxidative cell death pathway. Few compounds are known to induce primarily ferroptosis. In contrast to the perceived instability of peroxides, FINO2 was found to be thermally stable to at least 150 °C. FINO2 was more potent in cancer cells than nonmalignant cells of the same type. One of the enantiomers was found to be more responsible for the observed activity.

An individualized prognostic signature for gastric cancer patients treated with 5-Fluorouracil-based chemotherapy and distinct multi-omics characteristics of prognostic groups

5-Fluorouracil (5-FU)-based chemotherapy is currently the first-line treatment for gastric cancer. In this study, using gene expression profiles for a panel of cell lines with drug sensitivity data and two cohorts of patients, we extracted a signature consisting of two gene pairs (KCNE2 and API5, KCNE2 and PRPF3) whose within-sample relative expression orderings (REOs) could robustly predict prognoses of gastric cancer patients treated with 5-FU-based chemotherapy. This REOs-based signature was insensitive to experimental batch effects and could be directly applied to samples measured by different laboratories. Taking this unique advantage of the REOs-based signature, we classified gastric cancer samples of The Cancer Genome Atlas (TCGA) into two prognostic groups with distinct transcriptional characteristics, circumventing the usage of confounded TCGA survival data. We further showed that the two prognostic groups displayed distinct copy number, gene mutation and DNA methylation landscapes using the TCGA multi-omics data. The results provided hints for understanding molecular mechanisms determining prognoses of gastric cancer patients treated with 5-FU-based chemotherapy.

Current dichotomy between traditional molecular biological and omic research in cancer biology and pharmacology

There is currently a split within the cancer research community between traditional molecular biological hypothesis-driven and the more recent “omic” forms or research. While the molecular biological approach employs the tried and true single alteration-single response formulations of experimentation, the omic employs broad-based assay or sample collection approaches that generate large volumes of data. How to integrate the benefits of these two approaches in an efficient and productive fashion remains an outstanding issue. Ideally, one would merge the understandability, exactness, simplicity, and testability of the molecular biological approach, with the larger amounts of data, simultaneous consideration of multiple alterations, consideration of genes both of known interest along with the novel, cross-sample comparisons among cell lines and patient samples, and consideration of directed questions while simultaneously gaining exposure to the novel provided by the omic approach. While at the current time integration of the two disciplines remains problematic, attempts to do so are ongoing, and will be necessary for the understanding of the large cell line screens including the Developmental Therapeutics Program’s NCI-60, the Broad Institute’s Cancer Cell Line Encyclopedia, and the Wellcome Trust Sanger Institute’s Cancer Genome Project, as well as the the Cancer Genome Atlas clinical samples project. Going forward there is significant benefit to be had from the integration of the molecular biological and the omic forms or research, with the desired goal being improved translational understanding and application.

Using CellMiner 1.6 for Systems Pharmacology and Genomic Analysis of the NCI-60

The NCI-60 cancer cell line panel provides a premier model for data integration, and systems pharmacology being the largest publicly available database of anticancer drug activity, genomic, molecular, and phenotypic data. It comprises gene expression (25,722 transcripts), microRNAs (360 miRNAs), whole-genome DNA copy number (23,413 genes), whole-exome sequencing (variants for 16,568 genes), protein levels (94 genes), and cytotoxic activity (20,861 compounds). Included are 158 FDA-approved drugs and 79 that are in clinical trials. To improve data accessibility to bioinformaticists and non-bioinformaticists alike, we have developed the CellMiner web-based tools. Here, we describe the newest CellMiner version, including integration of novel databases and tools associated with whole-exome sequencing and protein expression, and review the tools. Included are (i) "Cell line signature" for DNA, RNA, protein, and drugs; (ii) "Cross correlations" for up to 150 input genes, microRNAs, and compounds in a single query; (iii) "Pattern comparison" to identify connections among drugs, gene expression, genomic variants, microRNA, and protein expressions; (iv) "Genetic variation versus drug visualization" to identify potential new drug:gene DNA variant relationships; and (v) "Genetic variant summation" designed to provide a synopsis of mutational burden on any pathway or gene group for up to 150 genes. Together, these tools allow users to flexibly query the NCI-60 data for potential relationships between genomic, molecular, and pharmacologic parameters in a manner specific to the user's area of expertise. Examples for both gain- (RAS) and loss-of-function (PTEN) alterations are provided.

The cytotoxic and pro-apoptotic activities of the novel fluoropyrimidine F10 towards prostate cancer cells are enhanced by Zn(2+) -chelation and inhibiting the serine protease Omi/HtrA2

BACKGROUND

Intracellular Zn(2+) levels decrease during prostate cancer progression and agents that modulate intracellular Zn(2+) are cytotoxic to prostate cancer cells by an incompletely described mechanism. F10 is a new polymeric fluoropyrimidine drug-candidate that displays strong activity with minimal systemic toxicity in pre-clinical models of prostate cancer and other malignancies. The effects of exogenous Zn(2+) or Zn(2+) chelation for enhancing F10 cytotoxicity are investigated as is the role of Omi/HtrA2, a serine protease that promotes apoptosis in response to cellular stress.

METHODS

To test the hypothesis that the pro-apoptotic effects of F10 could be enhanced by modulating intracellular Zn(2+) we investigated cell-permeable and cell-impermeable Zn(2+) chelators and exogenous Zn(2+) and evaluated cell viability and apoptosis in cellular models of castration-resistant prostate cancer (CRPC; PC3, C4-2). The role of Omi/HtrA2 for modulating apoptosis was evaluated by pharmacological inhibition and Western blotting.

RESULTS

Exogenous Zn(2+) initially reduced prostate cancer cell viability but these effects were transitory and were ineffective at enhancing F10 cytotoxicity. The cell-permeable Zn(2+) -chelator tetrakis-(2-pyridylmethl) ethylenediamine (TPEN) induced apoptosis in prostate cancer cells and enhanced the pro-apoptotic effects of F10. The pro-apoptotic effects of Zn(2+) -chelation in combination with F10 treatment were enhanced by inhibiting Omi/HtrA2 implicating this serine protease as a novel target for prostate cancer treatment.

CONCLUSIONS

Zn(2+) -chelation enhances the pro-apoptotic effects of F10 and may be useful for enhancing the effectiveness of F10 for treatment of advanced prostate cancer. The serine protease Omi/HtrA2 modulates Zn(2+) -dependent apoptosis in prostate cancer cells and represents a new target for treatment of CRPC. Prostate 75:360-369, 2015. © 2014 Wiley Periodicals, Inc.

Using drug response data to identify molecular effectors, and molecular "omic" data to identify candidate drugs in cancer

The current convergence of molecular and pharmacological data provides unprecedented opportunities to gain insights into the relationships between the two types of data. Multiple forms of large-scale molecular data, including but not limited to gene and microRNA transcript expression, DNA somatic and germline variations from next-generation DNA and RNA sequencing, and DNA copy number from array comparative genomic hybridization are all potentially informative when one attempts to recognize the panoply of potentially influential events both for cancer progression and therapeutic outcome. Concurrently, there has also been a substantial expansion of the pharmacological data being accrued in a systematic fashion. For cancer cell lines, the National Cancer Institute cell line panel (NCI-60), the Cancer Cell Line Encyclopedia (CCLE), and the collaborative Genomics of Drug Sensitivity in Cancer (GDSC) databases all provide subsets of these forms of data. For the patient-derived data, The Cancer Genome Atlas (TCGA) provides analogous forms of genomic information along with treatment histories. Integration of these data in turn relies on the fields of statistics and statistical learning. Multiple algorithmic approaches may be chosen, depending on the data being considered, and the nature of the question being asked. Combining these algorithms with prior biological knowledge, the results of molecular biological studies, and the consideration of genes as pathways or functional groups provides both the challenge and the potential of the field. The ultimate goal is to provide a paradigm shift in the way that drugs are selected to provide a more targeted and efficacious outcome for the patient.

NCI-60 whole exome sequencing and pharmacological CellMiner analyses

Exome sequencing provides unprecedented insights into cancer biology and pharmacological response. Here we assess these two parameters for the NCI-60, which is among the richest genomic and pharmacological publicly available cancer cell line databases. Homozygous genetic variants that putatively affect protein function were identified in 1,199 genes (approximately 6% of all genes). Variants that are either enriched or depleted compared to non-cancerous genomes, and thus may be influential in cancer progression and differential drug response were identified for 2,546 genes. Potential gene knockouts are made available. Assessment of cell line response to 19,940 compounds, including 110 FDA-approved drugs, reveals ≈80-fold range in resistance versus sensitivity response across cell lines. 103,422 gene variants were significantly correlated with at least one compound (at p<0.0002). These include genes of known pharmacological importance such as IGF1R, BRAF, RAD52, MTOR, STAT2 and TSC2 as well as a large number of candidate genes such as NOM1, TLL2, and XDH. We introduce two new web-based CellMiner applications that enable exploration of variant-to-compound relationships for a broad range of researchers, especially those without bioinformatics support. The first tool, “Genetic variant versus drug visualization”, provides a visualization of significant correlations between drug activity-gene variant combinations. Examples are given for the known vemurafenib-BRAF, and novel ifosfamide-RAD52 pairings. The second, “Genetic variant summation” allows an assessment of cumulative genetic variations for up to 150 combined genes together; and is designed to identify the variant burden for molecular pathways or functional grouping of genes. An example of its use is provided for the EGFR-ERBB2 pathway gene variant data and the identification of correlated EGFR, ERBB2, MTOR, BRAF, MEK and ERK inhibitors. The new tools are implemented as an updated web-based CellMiner version, for which the present publication serves as a compendium.

F10 Inhibits Growth of PC3 Xenografts and Enhances the Effects of Radiation Therapy

Chemotherapy remains of limited use for the treatment of prostate cancer with only one drug, docetaxel, demonstrating a modest survival advantage for treatment of late-stage disease. Data from the NCI 60 cell line screen indicated that the castration-resistant prostate cancer cell lines PC3 and DU145 were more sensitive than average to the novel polymeric fluoropyrimidine (FP), F10, despite displaying less than average sensitivity to the widely-used FP, 5FU. Here, we show that F10 treatment of PC3 xenografts results in a significant survival advantage (treatment to control ratio (T/C) days = 18; p < 0.001; n = 16) relative to control mice treated with saline. F10 (40 mg/kg/dose) was administered via jugular vein catheterization 3-times per week for five weeks. This aggressive dosing regimen was completed with no drug-induced weight loss and with no evidence of toxicity. F10 was also shown to sensitize PC3 cells to radiation and F10 was also shown to be a potent radiosensitizer of PC3 xenografts in vivo with F10 in combination with radiation resulting in significantly greater regression of PC3 xenografts than radiation alone. The results indicate that F10 in this pre-clinical setting is an effective chemotherapeutic agent and possesses significant radiosensitizing properties.

Gene expression profiling of 49 human tumor xenografts from in vitro culture through multiple in vivo passages--strategies for data mining in support of therapeutic studies

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.

High resolution copy number variation data in the NCI-60 cancer cell lines from whole genome microarrays accessible through CellMiner

Array-based comparative genomic hybridization (aCGH) is a powerful technique for detecting gene copy number variation. It is generally considered to be robust and convenient since it measures DNA rather than RNA. In the current study, we combine copy number estimates from four different platforms (Agilent 44 K, NimbleGen 385 K, Affymetrix 500 K and Illumina Human1Mv1_C) to compute a reliable, high-resolution, easy to understand output for the measure of copy number changes in the 60 cancer cells of the NCI-DTP (the NCI-60). We then relate the results to gene expression. We explain how to access that database using our CellMiner web-tool and provide an example of the ease of comparison with transcript expression, whole exome sequencing, microRNA expression and response to 20,000 drugs and other chemical compounds. We then demonstrate how the data can be analyzed integratively with transcript expression data for the whole genome (26,065 genes). Comparison of copy number and expression levels shows an overall medium high correlation (median r = 0.247), with significantly higher correlations (median r = 0.408) for the known tumor suppressor genes. That observation is consistent with the hypothesis that gene loss is an important mechanism for tumor suppressor inactivation. An integrated analysis of concurrent DNA copy number and gene expression change is presented. Limiting attention to focal DNA gains or losses, we identify and reveal novel candidate tumor suppressors with matching alterations in transcript level.

Preventive cancer stem cell-based vaccination reduces liver metastasis development in a rat colon carcinoma syngeneic model

Cancer stem cells (CSCs) represent a minor population of self-renewing cancer cells that fuel tumor growth. As CSCs are generally spared by conventional treatments, this population is likely to be responsible for relapses that are observed in most cancers. In this work, we analyzed the preventive efficiency of a CSC-based vaccine on the development of liver metastasis from colon cancer in a syngeneic rat model. We isolated a CSC-enriched population from the rat PROb colon carcinoma cell line on the basis of the expression of the aldehyde dehydrogenase-1 (ALDH1) marker. Comparative analysis of vaccines containing lysates of PROb or ALDH(high) cells by mass spectrometry identifies four proteins specifically expressed in the CSC subpopulation. The expression of two of them (heat shock protein 27-kDa and aldose reductase) is already known to be associated with treatment resistance and poor prognosis in colon cancer. Preventive intraperitoneal administration of vaccines was then performed before the intrahepatic injection of PROb cancer cells. While no significant difference in tumor occurrence was observed between control and PROb-vaccinated groups, 50% of the CSC-based vaccinated animals became resistant to tumor development. In addition, CSC-based vaccination induced a 99.5% reduction in tumor volume compared to the control group. To our knowledge, this study constitutes the first work analyzing the potential of a CSC-based vaccination to prevent liver metastasis development. Our data demonstrate that a CSC-based vaccine reduces efficiently both tumor volume and occurrence in a rat colon carcinoma syngeneic model.

Selective anti-tumor activity of the novel fluoropyrimidine polymer F10 towards G48a orthotopic GBM tumors

F10 is a novel anti-tumor agent with minimal systemic toxicity in vivo and which displays strong cytotoxicity towards glioblastoma (GBM) cells in vitro. Here we investigate the cytotoxicity of F10 towards GBM cells and evaluate the anti-tumor activity of locally-administered F10 towards an orthotopic xenograft model of GBM. The effects of F10 on thymidylate synthase (TS) inhibition and Topoisomerase 1 (Top1) cleavage complex formation were evaluated using TS activity assays and in vivo complex of enzyme bioassays. Cytotoxicity of F10 towards normal brain was evaluated using cortices from embryonic (day 18) mice. F10 displays minimal penetrance of the blood–brain barrier and was delivered by intra-cerebral (i.c.) administration and prospective anti-tumor response towards luciferase-expressing G48a human GBM tumors in nude mice was evaluated using IVIS imaging. Histological examination of tumor and normal brain tissue was used to assess the selectivity of anti-tumor activity. F10 is cytotoxic towards G48a, SNB-19, and U-251 MG GBM cells through dual targeting of TS and Top1. F10 is not toxic to murine primary neuronal cultures. F10 is well-tolerated upon i.c. administration and induces significant regression of G48a tumors that is dose-dependent. Histological analysis from F10-treated mice revealed tumors were essentially completely eradicated in F10-treated mice while vehicle-treated mice displayed substantial infiltration into normal tissue. F10 displays strong efficacy for GBM treatment with minimal toxicity upon i.c. administration establishing F10 as a promising drug-candidate for treating GBM in human patients.

Direct quantification of mRNA and miRNA from cell lysates using reverse transcription real time PCR: a multidimensional analysis of the performance of reagents and workflows

Substantial efforts have been devoted to in vitro testing of candidate chemotherapeutics by profiling transcriptional changes across the collection of NCI-60 cell-lines. A work-flow with reagents that enable the direct quantification of RNA of different molecular sizes simultaneously in the same sample without laborious total RNA isolation will invariably increase the throughput and accuracy of the study. MicroRNAs (miRNAs) are known to regulate most cellular functions, acting post-transcriptionally by repressing numerous eukaryotic mRNAs. Recent findings on the remarkable stability of miRNA prompted us to investigate the feasibility of quantifying the expression levels of both mRNA and miRNA directly from cell lysates (cell-to-Ct). Multidimensional analyses of the expressions of mRNA and miRNA across seven NCI-60 cell lines and multiple reagents were conducted to assess the performances of these reagents and workflows for cell-to-Ct measurements using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Quantification of RNA species using lysates prepared from an in-house and one of the commercial reagents demonstrated comparable performance to those prepared by the more laborious and conventional method of using guanidinium-phenol-chloroform. Additionally, miRNA was found to be highly stable in the cell lysates when incubated at room temperature for prolonged period of time and subjected to multiple freeze-thaw cycles. In summary, this study demonstrated significant differences in pre-analytical performance of a variety of commercially available reagents and described a cost-effective reagent useful for rapid, scalable, and high-throughput workflow for the detection of mRNA and miRNA from the same biological sample.

MicroRNA-224 negatively regulates p21 expression during late neoplastic progression in inflammatory bowel disease

BACKGROUND

The development of colon cancer represents a major complication in patients with inflammatory bowel disease (IBD). The importance of microRNAs (miRs) in carcinogenesis is becoming clearer because miRs have been implicated in the regulation of cancer-related cellular processes to include apoptosis, differentiation, cell cycle progression, and immune function. In the current study, we sought to identify miR dysregulation specific to progression along the normal-inflammation-cancer axis in colonic specimens from patients with IBD.

METHODS

MiR microarrays and quantitative reverse transcription PCR were used to detect and confirm dysregulated miRs. Receiver operating characteristic curve analysis was applied to evaluate the potential use of miR-224 as a neoplastic disease marker in IBD. For miR-224 target messenger RNA (mRNA) identification, mRNA microarrays were employed in combination with bioinformatic analyses, Western blotting, and luciferase activity measurements.

RESULTS

We identified 30 miRs that were differentially expressed between chronically inflamed mucosae and cancers arising from IBD tissues. MiR-224 levels increased successively at each stage of IBD progression and accurately discriminated cancers from normal or chronically inflamed IBD tissues. Moreover, mRNA arrays combined with bioinformatic analyses suggested the participation of miR-224 in cell cycle regulation. Subsequently, cell cycle experiments indicated that miR-224 regulates the G1-S checkpoint. Finally, in silico prediction analyses, confirmed by Western blotting and luciferase assays, identified p21 as a specific direct mRNA target of miR-224.

CONCLUSIONS

These findings reveal miR dysregulation specific to IBD-associated colorectal carcinoma. MiR-224 is overexpressed in IBD cancers and targets p21, a key cell cycle regulator. Moreover, these results establish the participation of miR-224 in IBD carcinogenesis.

Replication-dependent irreversible topoisomerase 1 poisoning is responsible for FdUMP[10] anti-leukemic activity

Previous studies have indicated that 5-Fluoro-2'-deoxyuridine-5'-O-monophosphate 10mer (FdUMP[10]) displays strong antileukemic activity through the dual targeting of thymidylate synthase (TS) and DNA topoisomerase 1 (Top1). The present studies were undertaken to clarify the relationship between the induction of a thymineless state and the formation of Top1 cleavage complexes (Top1CC) for inducing cell death and to clarify the role of DNA replication for induction of lethal DNA double-strand breaks (DSBs) in FdUMP[10]-treated acute myeloid leukemia (AML) cells. Human promyelocytic (HL60) and AML (KG1a, Molm13, THP-1) cells were synchronized by serum starvation and treated with FdUMP[10] with thymidine (Thy) rescue. Cells were assayed for TS inhibition, DNA DSBs, Top1CC, and apoptosis to clarify the interrelationship of TS inhibition and Top1CC for cell death. FdUMP[10] induced a thymineless state in AML cells and exogenous Thy administered within the first 18 hours of treatment rescued FdUMP[10]-induced Top1CC formation, γH2AX phosphorylation, and apoptosis induction. Exogenous Thy was not effective after cells had committed to mitosis and undergone cell division in the presence of FdUMP[10]. FdUMP[10] treatment resulted in Chk1 activation, and Chk1 inhibition enhanced FdUMP[10]-induced DNA damage and apoptosis. Jnk-signaling was required for FdUMP[10]-induced apoptosis in promyelocytic HL60 cells and in THP1 cells, but was antiapoptotic in Molm13 and to a lesser extent KG1a AML cells. The results are consistent with FdUMP[10] inducing a thymineless state, leading to misincorporation of FdU into genomic DNA of proliferating cells. Top1CC form in cells upon re-entry into S-phase, resulting in DNA double-strand breaks, and initiating apoptotic signaling that can be either muted or enhanced by Jnk-signaling depending on cell type.

MicroRNAs: relevant tools for a colorectal surgeon?

Colorectal cancer is the third most common malignancy and cause of cancer-related deaths worldwide. Approximately half of the patients diagnosed with colorectal cancer ultimately die of the condition. Death from colorectal cancer can be prevented by early detection, but unfortunately presentation is often late, with a worse prognosis. Screening by fecal occult blood testing reduces disease-specific mortality, but there is a need for sensitive and specific noninvasive biomarkers to facilitate detecting the disease, staging it, and predicting the best therapeutic options. MicroRNAs (miRNAs) are short noncoding RNA sequences that have a crucial role in the regulation of gene expression. They have significant regulatory functions in basic cellular processes, such as cell differentiation, proliferation, and apoptosis. Evidence suggests that miRNAs may function as both tumor suppressors and oncogenes. The main mechanism for changes in the function of miRNAs in cancer cells is due to aberrant gene expression. Accurate discrimination of miRNA profiles between tumor and normal mucosa in colorectal cancer allows definition of specific expression patterns of miRNAs, giving good potential as diagnostic and therapeutic targets. MiRNAs expressed in colorectal cancers are also abundantly present and stable in stool and plasma samples. Their extraction from these three sources is feasible and reproducible. The ease and reliability of determining miRNA profiles in plasma or stool makes them potential molecular markers for colorectal cancer screening. This review summarizes the role miRNAs have in colorectal cancer, highlighting particularly the potential diagnostic, prognostic, and therapeutic implications in the future treatment of the disease.

Expression of microRNAs in the NCI-60 cancer cell-lines

The NCI-60 panel of 60 human cancer cell-lines of nine different tissues of origin has been extensively characterized in biological, molecular and pharmacological studies. Analyses of data from such studies have provided valuable information for understanding cellular processes and developing strategies for the diagnosis and treatment of cancer. Here, Affymetrix® GeneChip™ miRNA version 1 oligonucleotide microarrays were used to quantify 847 microRNAs to generate an expression dataset of 495 (58.4%) microRNAs that were identified as expressed in at least one cell-line of the NCI-60 panel. Accuracy of the microRNA measurements was partly confirmed by reverse transcription and polymerase chain reaction assays. Similar to that seen among the four existing NCI-60 microRNA datasets, the concordance of the new expression dataset with the other four was modest, with mean Pearson correlation coefficients of 0.37–0.54. In spite of this, comparable results with different datasets were noted in clustering of the cell-lines by their microRNA expression, differential expression of microRNAs by the lines’ tissue of origin, and correlation of specific microRNAs with the doubling-time of cells or their radiation sensitivity. Mutation status of the cell-lines for the TP53, PTEN and BRAF but not CDKN2A or KRAS cancer-related genes was found to be associated with changes in expression of specific microRNAs. The microRNA dataset generated here should be valuable to those working in the field of microRNAs as well as in integromic studies of the NCI-60 panel.