Loss of Cadherin-11 in pancreatic ductal adenocarcinoma alters tumor-immune microenvironment.

Pancreatic ductal adenocarcinoma (PDAC) is one of the top five deadliest forms of cancer with very few treatment options. The 5-year survival rate for PDAC is 10% following diagnosis. Cadherin 11 (Cdh11), a cell-to-cell adhesion molecule, has been suggested to promote tumor growth and immunosuppression in PDAC, and Cdh11 inhibition significantly extended survival in mice with PDAC. However, the mechanisms by which Cdh11 deficiency influences PDAC progression and anti-tumor immune responses have yet to be fully elucidated. To investigate Cdh11-deficiency induced changes in PDAC tumor microenvironment (TME), we crossed p48-Cre; LSL-KrasG12D/+; LSL-Trp53R172H/+ (KPC) mice with Cdh11+/- mice and performed single-cell RNA sequencing (scRNA-seq) of the non-immune (CD45-) and immune (CD45+) compartment of KPC tumor-bearing Cdh11 proficient (KPC-Cdh11+/+) and Cdh11 deficient (KPC-Cdh11+/-) mice. Our analysis showed that Cdh11 is expressed primarily in cancer-associated fibroblasts (CAFs) and at low levels in epithelial cells undergoing epithelial-to-mesenchymal transition (EMT). Cdh11 deficiency altered the molecular profile of CAFs, leading to a decrease in the expression of myofibroblast markers such as Acta2 and Tagln and cytokines such as Il6, Il33 and Midkine (Mdk). We also observed a significant decrease in the presence of monocytes/macrophages and neutrophils in KPC-Cdh11+/- tumors while the proportion of T cells was increased. Additionally, myeloid lineage cells from Cdh11-deficient tumors had reduced expression of immunosuppressive cytokines that have previously been shown to play a role in immune suppression. In summary, our data suggests that Cdh11 deficiency significantly alters the fibroblast and immune microenvironments and contributes to the reduction of immunosuppressive cytokines, leading to an increase in anti-tumor immunity and enhanced survival.

ES-Screen: A Novel Electrostatics-Driven Method for Drug Discovery Virtual Screening.

Electrostatic interactions drive biomolecular interactions and associations. Computational modeling of electrostatics in biomolecular systems, such as protein-ligand, protein-protein, and protein-DNA, has provided atomistic insights into the binding process. In drug discovery, finding biologically plausible ligand-protein target interactions is challenging as current virtual screening and adjuvant techniques such as docking methods do not provide optimal treatment of electrostatic interactions. This study describes a novel electrostatics-driven virtual screening method called 'ES-Screen' that performs well across diverse protein target systems. ES-Screen provides a unique treatment of electrostatic interaction energies independent of total electrostatic free energy, typically employed by current software. Importantly, ES-Screen uses initial ligand pose input obtained from a receptor-based pharmacophore, thus independent of molecular docking. ES-Screen integrates individual polar and nonpolar replacement energies, which are the energy costs of replacing the cognate ligand for a target with a query ligand from the screening. This uniquely optimizes thermodynamic stability in electrostatic and nonpolar interactions relative to an experimentally determined stable binding state. ES-Screen also integrates chemometrics through shape and other physicochemical properties to prioritize query ligands with the greatest physicochemical similarities to the cognate ligand. The applicability of ES-Screen is demonstrated with in vitro experiments by identifying novel targets for many drugs. The present version includes a combination of many other descriptor components that, in a future version, will be purely based on electrostatics. Therefore, ES-Screen is a first-in-class unique electrostatics-driven virtual screening method with a unique implementation of replacement electrostatic interaction energies with broad applicability in drug discovery.

Loss of RARRES1 function Promotes Follicular Lymphomagenesis and Inhibits B cell Differentiation in Mice.

Retinoic acid receptor responder 1 (RARRES1) is among the most commonly methylated loci in multiple cancers. RARRES1 regulates mitochondrial and fatty acid metabolism, stem cell differentiation, and survival of immortalized cell lines in vitro. Here, we created constitutive Rarres1 knockout (Rarres1-/-) mouse models to study RARRES1 function in vivo. Rarres1-/- embryonic fibroblasts regulated tubulin glutamylation, cell metabolism, and survival, recapitulating RARRES1 function in immortalized cell lines. In two mouse strains, loss of Rarres1 led to a markedly increased dose-dependent incidence of follicular lymphoma (FL). Prior to lymphoma formation, Rarres1-/- B cells have compromised activation, maturation, differentiation into antibody-secreting plasma cells, and cell cycle progression. Rarres1 ablation increased B cell survival and led to activation of the unfolded protein response (UPR) and heat shock response (HSR). Rarres1 deficiency had differential effects on cellular metabolism, with increased bioenergetic capacity in fibroblasts, and minor effects on bioenergetics and metabolism in B cells. These findings reveal that RARRES1 is a bona fide tumor suppressor in vivo and the deletion in mice promotes cell survival, and reduces B cell differentiation with B cell autonomous and non-autonomous functions.

A novel chemo-phenotypic method identifies mixtures of salpn, vitamin D3, and pesticides involved in the development of colorectal and pancreatic cancer.

Environmental chemical (EC) exposures and our interactions with them has significantly increased in the recent decades. Toxicity associated biological characterization of these chemicals is challenging and inefficient, even with available high-throughput technologies. In this report, we describe a novel computational method for characterizing toxicity, associated biological perturbations and disease outcome, called the Chemo-Phenotypic Based Toxicity Measurement (CPTM). CPTM is used to quantify the EC "toxicity score" (Zts), which serves as a holistic metric of potential toxicity and disease outcome. CPTM quantitative toxicity is the measure of chemical features, biological phenotypic effects, and toxicokinetic properties of the ECs. For proof-of-concept, we subject ECs obtained from the Environmental Protection Agency's (EPA) database to the CPTM. We validated the CPTM toxicity predictions by correlating 'Zts' scores with known toxicity effects. We also confirmed the CPTM predictions with in-vitro, and in-vivo experiments. In in-vitro and zebrafish models, we showed that, mixtures of the motor oil and food additive 'Salpn' with endogenous nuclear receptor ligands such as Vitamin D3, dysregulated the nuclear receptors and key transcription pathways involved in Colorectal Cancer. Further, in a human patient derived cell organoid model, we found that a mixture of the widely used pesticides 'Tetramethrin' and 'Fenpropathrin' significantly impacts the population of patient derived pancreatic cancer cells and 3D organoid models to support rapid PDAC disease progression. The CPTM method is, to our knowledge, the first comprehensive toxico-physicochemical, and phenotypic bionetwork-based platform for efficient high-throughput screening of environmental chemical toxicity, mechanisms of action, and connection to disease outcomes.

Cadherin 11 Promotes Immunosuppression and Extracellular Matrix Deposition to Support Growth of Pancreatic Tumors and Resistance to Gemcitabine in Mice.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinomas (PDACs) are characterized by fibrosis and an abundance of cancer-associated fibroblasts (CAFs). We investigated strategies to disrupt interactions among CAFs, the immune system, and cancer cells, focusing on adhesion molecule CDH11, which has been associated with other fibrotic disorders and is expressed by activated fibroblasts. METHODS: We compared levels of CDH11 messenger RNA in human pancreatitis and pancreatic cancer tissues and cells with normal pancreas, and measured levels of CDH11 protein in human and mouse pancreatic lesions and normal tissues. We crossed p48-Cre;LSL-KrasG12D/+;LSL-Trp53R172H/+ (KPC) mice with CDH11-knockout mice and measured survival times of offspring. Pancreata were collected and analyzed by histology, immunohistochemistry, and (single-cell) RNA sequencing; RNA and proteins were identified by imaging mass cytometry. Some mice were given injections of PD1 antibody or gemcitabine and survival was monitored. Pancreatic cancer cells from KPC mice were subcutaneously injected into Cdh11+/+ and Cdh11-/- mice and tumor growth was monitored. Pancreatic cancer cells (mT3) from KPC mice (C57BL/6), were subcutaneously injected into Cdh11+/+ (C57BL/6J) mice and mice were given injections of antibody against CDH11, gemcitabine, or small molecule inhibitor of CDH11 (SD133) and tumor growth was monitored. RESULTS: Levels of CDH11 messenger RNA and protein were significantly higher in CAFs than in pancreatic cancer epithelial cells, human or mouse pancreatic cancer cell lines, or immune cells. KPC/Cdh11+/- and KPC/Cdh11-/- mice survived significantly longer than KPC/Cdh11+/+ mice. Markers of stromal activation entirely surrounded pancreatic intraepithelial neoplasias in KPC/Cdh11+/+ mice and incompletely in KPC/Cdh11+/- and KPC/Cdh11-/- mice, whose lesions also contained fewer FOXP3+ cells in the tumor center. Compared with pancreatic tumors in KPC/Cdh11+/+ mice, tumors of KPC/Cdh11+/- mice had increased markers of antigen processing and presentation; more lymphocytes and associated cytokines; decreased extracellular matrix components; and reductions in markers and cytokines associated with immunosuppression. Administration of the PD1 antibody did not prolong survival of KPC mice with 0, 1, or 2 alleles of Cdh11. Gemcitabine extended survival of KPC/Cdh11+/- and KPC/Cdh11-/- mice only or reduced subcutaneous tumor growth in mT3 engrafted Cdh11+/+ mice when given in combination with the CDH11 antibody. A small molecule inhibitor of CDH11 reduced growth of pre-established mT3 subcutaneous tumors only if T and B cells were present in mice. CONCLUSIONS: Knockout or inhibition of CDH11, which is expressed by CAFs in the pancreatic tumor stroma, reduces growth of pancreatic tumors, increases their response to gemcitabine, and significantly extends survival of mice. CDH11 promotes immunosuppression and extracellular matrix deposition, and might be developed as a therapeutic target for pancreatic cancer.

Single-Cell Transcriptomic Analysis of Tumor-Derived Fibroblasts and Normal Tissue-Resident Fibroblasts Reveals Fibroblast Heterogeneity in Breast Cancer.

Cancer-associated fibroblasts (CAFs) are a prominent stromal cell type in solid tumors and molecules secreted by CAFs play an important role in tumor progression and metastasis. CAFs coexist as heterogeneous populations with potentially different biological functions. Although CAFs are a major component of the breast cancer stroma, molecular and phenotypic heterogeneity of CAFs in breast cancer is poorly understood. In this study, we investigated CAF heterogeneity in triple-negative breast cancer (TNBC) using a syngeneic mouse model, BALB/c-derived 4T1 mammary tumors. Using single-cell RNA sequencing (scRNA-seq), we identified six CAF subpopulations in 4T1 tumors including: 1) myofibroblastic CAFs, enriched for α-smooth muscle actin and several other contractile proteins; 2) 'inflammatory' CAFs with elevated expression of inflammatory cytokines; and 3) a CAF subpopulation expressing major histocompatibility complex (MHC) class II proteins that are generally expressed in antigen-presenting cells. Comparison of 4T1-derived CAFs to CAFs from pancreatic cancer revealed that these three CAF subpopulations exist in both tumor types. Interestingly, cells with inflammatory and MHC class II-expressing CAF profiles were also detected in normal breast/pancreas tissue, suggesting that these phenotypes are not tumor microenvironment-induced. This work enhances our understanding of CAF heterogeneity, and specifically targeting these CAF subpopulations could be an effective therapeutic approach for treating highly aggressive TNBCs.

Curation of the Pancreatic Ductal Adenocarcinoma Subset of the Cancer Genome Atlas Is Essential for Accurate Conclusions about Survival-Related Molecular Mechanisms.

Purpose: Publicly available databases, for example, The Cancer Genome Atlas (TCGA), containing clinical and molecular data from many patients are useful in validating the contribution of particular genes to disease mechanisms and in forming novel hypotheses relating to clinical outcomes.Experimental Design: The impact of key drivers of cancer progression can be assessed by segregating a patient cohort by certain molecular features and constructing survival plots using the associated clinical data. However, conclusions drawn from this straightforward analysis are highly dependent on the quality and source of tissue samples, as demonstrated through the pancreatic ductal adenocarcinoma (PDAC) subset of TCGA.Results: Analyses of the PDAC-TCGA database, which contains mainly resectable cancer samples from patients in stage IIB, reveal a difference from widely known historic median and 5-year survival rates of PDAC. A similar discrepancy was observed in lung, stomach, and liver cancer subsets of TCGA. The whole transcriptome expression patterns of PDAC-TCGA revealed a cluster of samples derived from neuroendocrine tumors, which have a distinctive biology and better disease prognosis than PDAC. Furthermore, PDAC-TCGA contains numerous pseudo-normal samples, as well as those that arose from tumors not classified as PDAC.Conclusions: Inclusion of misclassified samples in the bioinformatic analyses distorts the association of molecular biomarkers with clinical outcomes, altering multiple published conclusions used to support and motivate experimental research. Hence, the stringent scrutiny of type and origin of samples included in the bioinformatic analyses by researchers, databases, and web-tool developers is of crucial importance for generating accurate conclusions. Clin Cancer Res; 24(16); 3813-9. ©2018 AACR.

Differential prioritization of therapies to subtypes of triple negative breast cancer using a systems medicine method.

Triple negative breast cancer (TNBC) is a group of cancers whose heterogeneity and shortage of effective drug therapies has prompted efforts to divide these cancers into molecular subtypes. Our computational platform, entitled GenEx-TNBC, applies concepts in systems biology and polypharmacology to prioritize thousands of approved and experimental drugs for therapeutic potential against each molecular subtype of TNBC. Using patient-based and cell line-based gene expression data, we constructed networks to describe the biological perturbation associated with each TNBC subtype at multiple levels of biological action. These networks were analyzed for statistical coincidence with drug action networks stemming from known drug-protein targets, while accounting for the direction of disease modulation for coinciding entities. GenEx-TNBC successfully designated drugs, and drug classes, that were previously shown to be broadly effective or subtype-specific against TNBC, as well as novel agents. We further performed biological validation of the platform by testing the relative sensitivities of three cell lines, representing three distinct TNBC subtypes, to several small molecules according to the degree of predicted biological coincidence with each subtype. GenEx-TNBC is the first computational platform to associate drugs to diseases based on inverse relationships with multi-scale disease mechanisms mapped from global gene expression of a disease. This method may be useful for directing current efforts in preclinical drug development surrounding TNBC, and may offer insights into the targetable mechanisms of each TNBC subtype.

Metabolomic and Lipidomic Profiling Identifies The Role of the RNA Editing Pathway in Endometrial Carcinogenesis.

Endometrial cancer (EC) remains the most common malignancy of the genital tract among women in developed countries. Although much research has been performed at genomic, transcriptomic and proteomic level, there is still a significant gap in the metabolomic studies of EC. In order to gain insights into altered metabolic pathways in the onset and progression of EC carcinogenesis, we used high resolution mass spectrometry to characterize the metabolomic and lipidomic profile of 39 human EC and 17 healthy endometrial tissue samples. Several pathways including lipids, Kynurenine pathway, endocannabinoids signaling pathway and the RNA editing pathway were found to be dysregulated in EC. The dysregulation of the RNA editing pathway was further investigated in an independent set of 183 human EC tissues and matched controls, using orthogonal approaches. We found that ADAR2 is overexpressed in EC and that the increase in expression positively correlates with the aggressiveness of the tumor. Furthermore, silencing of ADAR2 in three EC cell lines resulted in a decreased proliferation rate, increased apoptosis, and reduced migration capabilities in vitro. Taken together, our results suggest that ADAR2 functions as an oncogene in endometrial carcinogenesis and could be a potential target for improving EC treatment strategies.

Drug Metabolism in Preclinical Drug Development: A Survey of the Discovery Process, Toxicology, and Computational Tools.

BACKGROUND: While establishing efficacy in translational models and humans through clinically-relevant endpoints for disease is of great interest, assessing the potential toxicity of a putative therapeutic drug is critical. Toxicological assessments in the pre-clinical discovery phase help to avoid future failure in the clinical phases of drug development. Many in vitro assays exist to aid in modular toxicological assessment, such as hepatotoxicity and genotoxicity. While these methods have provided tremendous insight into human toxicity by investigational new drugs, they are expensive, require substantial resources, and do not account for pharmacogenomics as well as critical ADME properties. Computational tools can fill this niche in toxicology if in silico models are accurate in relating drug molecular properties to toxicological endpoints as well as reliable in predicting important drug-target interactions that mediate known adverse events or adverse outcome pathways (AOPs). METHODS: We undertook an unstructured search of multiple bibliographic databases for peer-reviewed literature regarding computational methods in predictive toxicology for in silico drug discovery. As this review paper is meant to serve as a survey of available methods for the interested reader, no focused criteria were applied. Literature chosen was based on the writers' expertise and intent in communicating important aspects of in silico toxicology to the interested reader. CONCLUSION: This review provides a purview of computational methods of pre-clinical toxicologic assessments for novel small molecule drugs that may be of use for novice and experienced investigators as well as academic and commercial drug discovery entities.

The repurposed anthelmintic mebendazole in combination with trametinib suppresses refractory NRASQ61K melanoma.

Structure-based drug repositioning in addition to random chemical screening is now a viable route to rapid drug development. Proteochemometric computational methods coupled with kinase assays showed that mebendazole (MBZ) binds and inhibits kinases important in cancer, especially both BRAFWT and BRAFV600E. We find that MBZ synergizes with the MEK inhibitor trametinib to inhibit growth of BRAFWT-NRASQ61K melanoma cells in culture and in xenografts, and markedly decreased MEK and ERK phosphorylation. Reverse Phase Protein Array (RPPA) and immunoblot analyses show that both trametinib and MBZ inhibit the MAPK pathway, and cluster analysis revealed a protein cluster showing strong MBZ+trametinib - inhibited phosphorylation of MEK and ERK within 10 minutes, and its direct and indirect downstream targets related to stress response and translation, including ElK1 and RSKs within 30 minutes. Downstream ERK targets for cell cycle, including cMYC, were down-regulated, consistent with S- phase suppression by MBZ+trametinib, while apoptosis markers, including cleaved caspase-3, cleaved PARP and a sub-G1 population, were all increased with time. These data suggest that MBZ, a well-tolerated off-patent approved drug, should be considered as a therapeutic option in combination with trametinib, for patients with NRASQ61mut or other non-V600E BRAF mutant melanomas.

MSD-MAP: A Network-Based Systems Biology Platform for Predicting Disease-Metabolite Links.

BACKGROUND: Cancer-associated metabolites result from cell-wide mechanisms of dysregulation. The field of metabolomics has sought to identify these aberrant metabolites as disease biomarkers, clues to understanding disease mechanisms, or even as therapeutic agents. OBJECTIVE: This study was undertaken to reliably predict metabolites associated with colorectal, esophageal, and prostate cancers. Metabolite and disease biological action networks were compared in a computational platform called MSD-MAP (Multi Scale Disease-Metabolite Association Platform). METHODS: Using differential gene expression analysis with patient-based RNAseq data from The Cancer Genome Atlas, genes up- or down-regulated in cancer compared to normal tissue were identified. Relational databases were used to map biological entities including pathways, functions, and interacting proteins, to those differential disease genes. Similar relational maps were built for metabolites, stemming from known and in silico predicted metabolite-protein associations. The hypergeometric test was used to find statistically significant relationships between disease and metabolite biological signatures at each tier, and metabolites were assessed for multi-scale association with each cancer. Metabolite networks were also directly associated with various other diseases using a disease functional perturbation database. RESULTS: Our platform recapitulated metabolite-disease links that have been empirically verified in the scientific literature, with network-based mapping of jointly-associated biological activity also matching known disease mechanisms. This was true for colorectal, esophageal, and prostate cancers, using metabolite action networks stemming from both predicted and known functional protein associations. CONCLUSION: By employing systems biology concepts, MSD-MAP reliably predicted known cancermetabolite links, and may serve as a predictive tool to streamline conventional metabolomic profiling methodologies.

A role for the vitamin D pathway in non-intestinal lesions in genetic and carcinogen models of colorectal cancer and in familial adenomatous polyposis.

Vitamin D is implicated in the etiology of cancers of the gastrointestinal tract, usually characterized by alteration in the APC/ß-catenin/TCF tumor suppressor pathway. The vitamin D receptor (VDR) is also implicated in cardiovascular and skin diseases as well as in immunity. Activated VDR can indirectly alter ß-catenin nuclear localization and directly suppress ß-catenin/TCF mediated transcriptional activity. We treated VDR null mice with the carcinogen azoxymethane (AOM) and generated mice bearing a mutated APC (hypomorph) on a VDR null background (Apc1638N/+Vdr-/-). VDR null mice do not develop GI or extra-colonic tumors but loss of VDR decreased intestinal tumor latency and increased progression to adenocarcinoma in both models. AOM treatment of VDR null mice also caused squamous cell carcinoma of the anus. Although levels and distribution of total or activated ß-catenin in the epithelial component of tumors were unaffected by loss of VDR, ß-catenin dependent cyclin D1 expression was affected suggesting a direct VDR effect on ß-catenin co-activator activity. Extra-colonic mucosa manifestations in Apc1638N/+Vdr-/- animals included increased nuclear ß-catenin in submucosal stromal cells, spleno- and cardiomegaly and large epidermoid cysts characteristic of the FAP variant, Gardner's syndrome. Consistent with this, SNPs in the VDR, vitamin D binding protein and CYP24 as well as mutations in APC distal to codon 850 were strongly associated with Gardners syndrome in a cohort of 457 FAP patients, This work suggests that alterations in the vitamin D/VDR axis are important in Gardner's syndrome, as well as in the etiology of anal cancer.

DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing.

BACKGROUND: The targeting of disease-related proteins is important for drug discovery, and yet target-based discovery has not been fruitful. Contextualizing overall biological processes is critical to formulating successful drug-disease hypotheses. Network pharmacology helps to overcome target-based bottlenecks through systems biology analytics, such as protein-protein interaction (PPI) networks and pathway regulation. RESULTS: We present a systems polypharmacology platform entitled DrugGenEx-Net (DGE-NET). DGE-NET predicts empirical drug-target (DT) interactions, integrates interaction pairs into a multi-tiered network analysis, and ultimately predicts disease-specific drug polypharmacology through systems-based gene expression analysis. Incorporation of established biological network annotations for protein target-disease, -signaling pathway, -molecular function, and protein-protein interactions enhances predicted DT effects on disease pathophysiology. Over 50 drug-disease and 100 drug-pathway predictions are validated. For example, the predicted systems pharmacology of the cholesterol-lowering agent ezetimibe corroborates its potential carcinogenicity. When disease-specific gene expression analysis is integrated, DGE-NET prioritizes known therapeutics/experimental drugs as well as their contra-indications. Proof-of-concept is established for immune-related rheumatoid arthritis and inflammatory bowel disease, as well as neuro-degenerative Alzheimer's and Parkinson's diseases. CONCLUSIONS: DGE-NET is a novel computational method that predicting drug therapeutic and counter-therapeutic indications by uniquely integrating systems pharmacology with gene expression analysis. DGE-NET correctly predicts various drug-disease indications by linking the biological activity of drugs and diseases at multiple tiers of biological action, and is therefore a useful approach to identifying drug candidates for re-purposing.

Harnessing Polypharmacology with Computer-Aided Drug Design and Systems Biology.

The ascent of polypharmacology in drug development has many implications for disease therapy, most notably in the efforts of drug discovery, drug repositioning, precision medicine and combination therapy. The single- target approach to drug development has encountered difficulties in predicting drugs that are both clinically efficacious and avoid toxicity. By contrast, polypharmacology offers the possibility of a controlled distribution of effects on a biological system. This review addresses possibilities and bottlenecks in the efficient computational application of polypharmacology. The two major areas we address are the discovery and prediction of multiple protein targets using the tools of computer-aided drug design, and the use of these protein targets in predicting therapeutic potential in the context of biological networks. The successful application of polypharmacology to systems biology and pharmacology has the potential to markedly accelerate the pace of development of novel therapies for multiple diseases, and has implications for the intellectual property landscape, likely requiring targeted changes in patent law.

RepurposeVS: A Drug Repurposing-Focused Computational Method for Accurate Drug-Target Signature Predictions.

We describe here RepurposeVS for the reliable prediction of drug-target signatures using X-ray protein crystal structures. RepurposeVS is a virtual screening method that incorporates docking, drug-centric and protein-centric 2D/3D fingerprints with a rigorous mathematical normalization procedure to account for the variability in units and provide high-resolution contextual information for drug-target binding. Validity was confirmed by the following: (1) providing the greatest enrichment of known drug binders for multiple protein targets in virtual screening experiments, (2) determining that similarly shaped protein target pockets are predicted to bind drugs of similar 3D shapes when RepurposeVS is applied to 2,335 human protein targets, and (3) determining true biological associations in vitro for mebendazole (MBZ) across many predicted kinase targets for potential cancer repurposing. Since RepurposeVS is a drug repurposing-focused method, benchmarking was conducted on a set of 3,671 FDA approved and experimental drugs rather than the Database of Useful Decoys (DUDE) so as to streamline downstream repurposing experiments. We further apply RepurposeVS to explore the overall potential drug repurposing space for currently approved drugs. RepurposeVS is not computationally intensive and increases performance accuracy, thus serving as an efficient and powerful in silico tool to predict drug-target associations in drug repurposing.

ßII-Spectrin (SPTBN1) suppresses progression of hepatocellular carcinoma and Wnt signaling by regulation of Wnt inhibitor kallistatin.

UNLABELLED: ßII-Spectrin (SPTBN1) is an adapter protein for Smad3/Smad4 complex formation during transforming growth factor beta (TGF-ß) signal transduction. Forty percent of SPTBN1(+/-) mice spontaneously develop hepatocellular carcinoma (HCC), and most cases of human HCC have significant reductions in SPTBN1 expression. In this study, we investigated the possible mechanisms by which loss of SPTBN1 may contribute to tumorigenesis. Livers of SPTBN1(+/-) mice, compared to wild-type mouse livers, display a significant increase in epithelial cell adhesion molecule-positive (EpCAM(+)) cells and overall EpCAM expression. Inhibition of SPTBN1 in human HCC cell lines increased the expression of stem cell markers EpCAM, Claudin7, and Oct4, as well as decreased E-cadherin expression and increased expression of vimentin and c-Myc, suggesting reversion of these cells to a less differentiated state. HCC cells with decreased SPTBN1 also demonstrate increased sphere formation, xenograft tumor development, and invasion. Here we investigate possible mechanisms by which SPTBN1 may influence the stem cell traits and aggressive behavior of HCC cell lines. We found that HCC cells with decreased SPTBN1 express much less of the Wnt inhibitor kallistatin and exhibit decreased ß-catenin phosphorylation and increased ß-catenin nuclear localization, indicating Wnt signaling activation. Restoration of kallistatin expression in these cells reversed the observed Wnt activation. CONCLUSION: SPTBN1 expression in human HCC tissues is positively correlated with E-cadherin and kallistatin levels, and decreased SPTBN1 and kallistatin gene expression is associated with decreased relapse-free survival. Our data suggest that loss of SPTBN1 activates Wnt signaling, which promotes acquisition of stem cell-like features, and ultimately contributes to malignant tumor progression.

Cooperation between BRCA1 and vitamin D is critical for histone acetylation of the p21waf1 promoter and growth inhibition of breast cancer cells and cancer stem-like cells.

Carriers of germline mutations in the BRCA1 gene have a significant increased lifetime risk for being diagnosed with breast cancer. The incomplete penetrance of BRCA1 suggests that environmental and/or genetic factors modify the risk and incidence among mutation carriers. Nutrition and particular micronutrients play a central role in modifying the phenotypic expression of a given genotype by regulating chromatin structure and gene expression. The active form of vitamin D, 1α,25-dihydroxyvitamin D3, is a potent inhibitor of breast cancer growth. Here we report that two non-calcemic analogues of 1α,25-dihydroxyvitamin D3, seocalcitol (EB1089) and QW-1624F2-2, collaborate with BRCA1 in mediating growth inhibition of breast cancer cells and breast cancer stem-like cells. EB1089 induces a G1/S phase growth arrest that coincides with induction of p21waf1 expression only in BRCA1-expressing cells. A complete knockdown of BRCA1 or p21waf1 renders the cells unresponsive to EB1089. Furthermore, we show that in the presence of ligand, BRCA1 associates with vitamin D receptor (VDR) and the complex co-occupies vitamin D responsive elements (VDRE) at the CDKN1A (p21waf1) promoter and enhances acetylation of histone H3 and H4 at these sites. Thus, BRCA1 expression is critical for mediating the biological impact of vitamin D3 in breast tumor cells.

Big data: the next frontier for innovation in therapeutics and healthcare.

Advancements in genomics and personalized medicine not only effect healthcare delivery from patient and provider standpoints, but also reshape biomedical discovery. We are in the era of the '-omics', wherein an individual's genome, transcriptome, proteome and metabolome can be scrutinized to the finest resolution to paint a personalized biochemical fingerprint that enables tailored treatments, prognoses, risk factors, etc. Digitization of this information parlays into 'big data' informatics-driven evidence-based medical practice. While individualized patient management is a key beneficiary of next-generation medical informatics, this data also harbors a wealth of novel therapeutic discoveries waiting to be uncovered. 'Big data' informatics allows for networks-driven systems pharmacodynamics whereby drug information can be coupled to cellular- and organ-level physiology for determining whole-body outcomes. Patient '-omics' data can be integrated for ontology-based data-mining for the discovery of new biological associations and drug targets. Here we highlight the potential of 'big data' informatics for clinical pharmacology.

Cadherin-11 in poor prognosis malignancies and rheumatoid arthritis: common target, common therapies.

Cadherin-11 (CDH11), associated with epithelial to mesenchymal transformation in development, poor prognosis malignancies and cancer stem cells, is also a major therapeutic target in rheumatoid arthritis (RA). CDH11 expressing basal-like breast carcinomas and other CDH11 expressing malignancies exhibit poor prognosis. We show that CDH11 is increased early in breast cancer and ductal carcinoma in-situ. CDH11 knockdown and antibodies effective in RA slowed the growth of basal-like breast tumors and decreased proliferation and colony formation of breast, glioblastoma and prostate cancer cells. The repurposed arthritis drug celecoxib, which binds to CDH11, and other small molecules designed to bind CDH11 without inhibiting COX-2 preferentially affect the growth of CDH11 positive cancer cells in vitro and in animals. These data suggest that CDH11 is important for malignant progression, and is a therapeutic target in arthritis and cancer with the potential for rapid clinical translation.