Polymeric Micelles as Drug Delivery System: Recent Advances, Approaches, Applications and Patents.

Administering therapeutics through the oral route is a pervasive and widely approved medication administration approach. However, it has been found that many drugs show low systemic absorption when delivered through this route. Such limitations of oral drug delivery can be overcome by polymeric micelles acting as vehicles. As a result, they improve drug absorption by protecting loaded drug substances from the gastrointestinal system's hostile conditions, allowing controlled drug release at a specific site, extending the time spent in the gut through mucoadhesion, and inhibiting the efflux pump from reducing therapeutic agent accumulation. To promote good oral absorption of a weakly water-soluble medicinal drug, the loaded medicine should be protected from the hostile atmosphere of the GI tract. Polymeric micelles can be stacked with a broad assortment of ineffectively dissolvable medications, improving bioavailability. This review discusses the major mechanism, various types, advantages, and limitations for developing the polymeric micelle system and certain micellar drug delivery system applications. The primary goal of this review is to illustrate how polymeric micelles can be used to deliver poorly water-soluble medications.

Adult stem cell activity in naked mole rats for long-term tissue maintenance.

The naked mole rat (NMR), Heterocephalus glaber, the longest-living rodent, provides a unique opportunity to explore how evolution has shaped adult stem cell (ASC) activity and tissue function with increasing lifespan. Using cumulative BrdU labelling and a quantitative imaging approach to track intestinal ASCs (Lgr5+) in their native in vivo state, we find an expanded pool of Lgr5+ cells in NMRs, and these cells specifically at the crypt base (Lgr5+CBC) exhibit slower division rates compared to those in short-lived mice but have a similar turnover as human LGR5+CBC cells. Instead of entering quiescence (G0), NMR Lgr5+CBC cells reduce their division rates by prolonging arrest in the G1 and/or G2 phases of the cell cycle. Moreover, we also observe a higher proportion of differentiated cells in NMRs that confer enhanced protection and function to the intestinal mucosa which is able to detect any chemical imbalance in the luminal environment efficiently, triggering a robust pro-apoptotic, anti-proliferative response within the stem/progenitor cell zone.

Enrichment analysis of phenotypic data for drug repurposing in rare diseases.

Drug-induced Behavioral Signature Analysis (DBSA), is a machine learning (ML) method for in silico screening of compounds, inspired by analytical methods quantifying gene enrichment in genomic analyses. When applied to behavioral data it can identify drugs that can potentially reverse in vivo behavioral symptoms in animal models of human disease and suggest new hypotheses for drug discovery and repurposing. We present a proof-of-concept study aiming to assess Drug-induced Behavioral Signature Analysis (DBSA) as a systematic approach for drug discovery for rare disorders. We applied Drug-induced Behavioral Signature Analysis to high-content behavioral data obtained with SmartCube®, an automated in vivo phenotyping platform. The therapeutic potential of several dozen approved drugs was assessed for phenotypic reversal of the behavioral profile of a Huntington's Disease (HD) murine model, the Q175 heterozygous knock-in mice. The in silico Drug-induced Behavioral Signature Analysis predictions were enriched for drugs known to be effective in the symptomatic treatment of Huntington's Disease, including bupropion, modafinil, methylphenidate, and several SSRIs, as well as the atypical antidepressant tianeptine. To validate the method, we tested acute and chronic effects of tianeptine (20 mg/kg, i. p.) in vivo, using Q175 mice and wild type controls. In both experiments, tianeptine significantly rescued the behavioral phenotype assessed with the SmartCube® platform. Our target-agnostic method thus showed promise for identification of symptomatic relief treatments for rare disorders, providing an alternative method for hypothesis generation and drug discovery for disorders with huge disease burden and unmet medical needs.

Benefits of global mutant huntingtin lowering diminish over time in a Huntington's disease mouse model.

We have developed an inducible Huntington's disease (HD) mouse model that allows temporal control of whole-body allele-specific mutant huntingtin (mHtt) expression. We asked whether moderate global lowering of mHtt (~50%) was sufficient for long-term amelioration of HD-related deficits and, if so, whether early mHtt lowering (before measurable deficits) was required. Both early and late mHtt lowering delayed behavioral dysfunction and mHTT protein aggregation, as measured biochemically. However, long-term follow-up revealed that the benefits, in all mHtt-lowering groups, attenuated by 12 months of age. While early mHtt lowering attenuated cortical and striatal transcriptional dysregulation evaluated at 6 months of age, the benefits diminished by 12 months of age, and late mHtt lowering did not ameliorate striatal transcriptional dysregulation at 12 months of age. Only early mHtt lowering delayed the elevation in cerebrospinal fluid neurofilament light chain that we observed in our model starting at 9 months of age. As small-molecule HTT-lowering therapeutics progress to the clinic, our findings suggest that moderate mHtt lowering allows disease progression to continue, albeit at a slower rate, and could be relevant to the degree of mHTT lowering required to sustain long-term benefits in humans.

TOP2B Enzymatic Activity on Promoters and Introns Modulates Multiple Oncogenes in Human Gliomas.

PURPOSE: The epigenetic mechanisms involved in transcriptional regulation leading to malignant phenotype in gliomas remains poorly understood. Topoisomerase IIB (TOP2B), an enzyme that decoils and releases torsional forces in DNA, is overexpressed in a subset of gliomas. Therefore, we investigated its role in epigenetic regulation in these tumors. EXPERIMENTAL DESIGN: To investigate the role of TOP2B in epigenetic regulation in gliomas, we performed paired chromatin immunoprecipitation sequencing for TOP2B and RNA-sequencing analysis of glioma cell lines with and without TOP2B inhibition and in human glioma specimens. These experiments were complemented with assay for transposase-accessible chromatin using sequencing, gene silencing, and mouse xenograft experiments to investigate the function of TOP2B and its role in glioma phenotypes. RESULTS: We discovered that TOP2B modulates transcription of multiple oncogenes in human gliomas. TOP2B regulated transcription only at sites where it was enzymatically active, but not at all native binding sites. In particular, TOP2B activity localized in enhancers, promoters, and introns of PDGFRA and MYC, facilitating their expression. TOP2B levels and genomic localization was associated with PDGFRA and MYC expression across glioma specimens, which was not seen in nontumoral human brain tissue. In vivo, TOP2B knockdown of human glioma intracranial implants prolonged survival and downregulated PDGFRA. CONCLUSIONS: Our results indicate that TOP2B activity exerts a pleiotropic role in transcriptional regulation of oncogenes in a subset of gliomas promoting a proliferative phenotype.

Computational Analysis of Multidimensional Behavioral Alterations After Chronic Social Defeat Stress.

BACKGROUND: The study of depression in humans depends on animal models that attempt to mimic specific features of the human syndrome. Most studies focus on one or a few behavioral domains, with time and practical considerations prohibiting a comprehensive evaluation. Although machine learning has enabled unbiased analysis of behavior in animals, this has not yet been applied to animal models of psychiatric disease. METHODS: We performed chronic social defeat stress (CSDS) in mice and evaluated behavior with PsychoGenics' SmartCube, a high-throughput unbiased automated phenotyping platform that collects >2000 behavioral features based on machine learning. We evaluated group differences at several times post-CSDS and after administration of the antidepressant medication imipramine. RESULTS: SmartCube analysis after CSDS successfully separated control and defeated-susceptible mice, and defeated-resilient mice more resembled control mice. We observed a potentiation of CSDS effects over time. Treatment of susceptible mice with imipramine induced a 40.2% recovery of the defeated-susceptible phenotype as assessed by SmartCube. CONCLUSIONS: High-throughput analysis can simultaneously evaluate multiple behavioral alterations in an animal model for the study of depression, which provides a more unbiased and holistic approach to evaluating group differences after CSDS and perhaps can be applied to other mouse models of psychiatric disease.

N-quinoline-benzenesulfonamide derivatives exert potent anti-lymphoma effect by targeting NF-κB.

We previously identified the N-quinoline-benzenesulfonamide (NQBS) scaffold as a potent inhibitor of nuclear factor-κB (NF-κB) translocation. Now, we report the structure-activity relationship of compounds with the NQBS scaffold in models of diffuse large B-cell lymphoma (DLBCL). We identified CU-O42, CU-O47, and CU-O75 as NQBS analogs with the most potent cytotoxic activity in DLBCL lines. Their anti-lymphoma effect was mediated by NF-κB sequestration to the cytoplasm of DLBCL cells. Internal Coordinates Mechanics analysis suggested direct binding between CU-O75 and IκBα/p50/p65 which leads to the stabilization of the NF-κB trimer. A whole cellular thermal shift assay confirmed direct binding of the NQBS to IκBα, an inhibitory component of the IκBα/p50/p65 trimer. Lymphoma cell line sequencing revealed CU-O75 induced downregulation of NF-κB-dependent genes and DeMAND analysis identified IκBα as one of the top protein targets for CU-O75. CU-O42 was potent in inhibiting tumor growth in two mouse models of aggressive lymphomas.

Ribosomal protein S11 influences glioma response to TOP2 poisons.

Topoisomerase II poisons are one of the most common class of chemotherapeutics used in cancer. We and others had shown that a subset of glioblastomas, the most malignant of all primary brain tumors in adults, is responsive to TOP2 poisons. To identify genes that confer susceptibility to this drug in gliomas, we performed a genome-scale CRISPR knockout screen with etoposide. Genes involved in protein synthesis and DNA damage were implicated in etoposide susceptibility. To define potential biomarkers for TOP2 poisons, CRISPR hits were overlapped with genes whose expression correlates with susceptibility to this drug across glioma cell lines, revealing ribosomal protein subunit RPS11, 16, and 18 as putative biomarkers for response to TOP2 poisons. Loss of RPS11 led to resistance to etoposide and doxorubicin and impaired the induction of proapoptotic gene APAF1 following treatment. The expression of these ribosomal subunits was also associated with susceptibility to TOP2 poisons across cell lines from gliomas and multiple other cancers.

Experimental microdissection enables functional harmonisation of pancreatic cancer subtypes.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDA) has among the highest stromal fractions of any cancer and this has complicated attempts at expression-based molecular classification. The goal of this work is to profile purified samples of human PDA epithelium and stroma and examine their respective contributions to gene expression in bulk PDA samples. DESIGN: We used laser capture microdissection (LCM) and RNA sequencing to profile the expression of 60 matched pairs of human PDA malignant epithelium and stroma samples. We then used these data to train a computational model that allowed us to infer tissue composition and generate virtual compartment-specific expression profiles from bulk gene expression cohorts. RESULTS: Our analysis found significant variation in the tissue composition of pancreatic tumours from different public cohorts. Computational removal of stromal gene expression resulted in the reclassification of some tumours, reconciling functional differences between different cohorts. Furthermore, we established a novel classification signature from a total of 110 purified human PDA stroma samples, finding two groups that differ in the extracellular matrix-associated and immune-associated processes. Lastly, a systematic evaluation of cross-compartment subtypes spanning four patient cohorts indicated partial dependence between epithelial and stromal molecular subtypes. CONCLUSION: Our findings add clarity to the nature and number of molecular subtypes in PDA, expand our understanding of global transcriptional programmes in the stroma and harmonise the results of molecular subtyping efforts across independent cohorts.

Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis.

To understand drug combination effect, it is necessary to decipher the interactions between drug targets-many of which are signaling molecules. Previously, such signaling pathway models are largely based on the compilation of literature data from heterogeneous cellular contexts. Indeed, de novo reconstruction of signaling interactions from large-scale molecular profiling is still lagging, compared to similar efforts in transcriptional and protein-protein interaction networks. To address this challenge, we introduce a novel algorithm for the systematic inference of protein kinase pathways, and applied it to published mass spectrometry-based phosphotyrosine profile data from 250 lung adenocarcinoma (LUAD) samples. The resulting network includes 43 TKs and 415 inferred, LUAD-specific substrates, which were validated at >60% accuracy by SILAC assays, including "novel' substrates of the EGFR and c-MET TKs, which play a critical oncogenic role in lung cancer. This systematic, data-driven model supported drug response prediction on an individual sample basis, including accurate prediction and validation of synergistic EGFR and c-MET inhibitor activity in cells lacking mutations in either gene, thus contributing to current precision oncology efforts.

FGF-induced Pea3 transcription factors program the genetic landscape for cell fate determination.

FGF signaling is a potent inducer of lacrimal gland development in the eye, capable of transforming the corneal epithelium into glandular tissues. Here, we show that genetic ablation of the Pea3 family of transcription factors not only disrupted the ductal elongation and branching of the lacrimal gland, but also biased the lacrimal gland epithelium toward an epidermal cell fate. Analysis of high-throughput gene expression and chromatin immunoprecipitation data revealed that the Pea3 genes directly control both the positive and negative feedback loops of FGF signaling. Importantly, Pea3 genes are also required to suppress aberrant Notch signaling which, if gone unchecked, can compromise lacrimal gland development by preventing the expression of both Sox and Six family genes. These results demonstrate that Pea3 genes are key FGF early response transcriptional factors, programing the genetic landscape for cell fate determination.

The number of titrated microRNA species dictates ceRNA regulation.

microRNAs (miRNAs) play key roles in cancer, but their propensity to couple their targets as competing endogenous RNAs (ceRNAs) has only recently emerged. Multiple models have studied ceRNA regulation, but these models did not account for the effects of co-regulation by miRNAs with many targets. We modeled ceRNA and simulated its effects using established parameters for miRNA/mRNA interaction kinetics while accounting for co-regulation by multiple miRNAs with many targets. Our simulations suggested that co-regulation by many miRNA species is more likely to produce physiologically relevant context-independent couplings. To test this, we studied the overlap of inferred ceRNA networks from four tumor contexts-our proposed pan-cancer ceRNA interactome (PCI). PCI was composed of interactions between genes that were co-regulated by nearly three-times as many miRNAs as other inferred ceRNA interactions. Evidence from expression-profiling datasets suggested that PCI interactions are predictive of gene expression in 12 independent tumor- and non-tumor contexts. Biochemical assays confirmed ceRNA couplings for two PCI subnetworks, including oncogenes CCND1, HIF1A and HMGA2, and tumor suppressors PTEN, RB1 and TP53. Our results suggest that PCI is enriched for context-independent interactions that are coupled by many miRNA species and are more likely to be context independent.

Alx4 relays sequential FGF signaling to induce lacrimal gland morphogenesis.

The sequential use of signaling pathways is essential for the guidance of pluripotent progenitors into diverse cell fates. Here, we show that Shp2 exclusively mediates FGF but not PDGF signaling in the neural crest to control lacrimal gland development. In addition to preventing p53-independent apoptosis and promoting the migration of Sox10-expressing neural crests, Shp2 is also required for expression of the homeodomain transcription factor Alx4, which directly controls Fgf10 expression in the periocular mesenchyme that is necessary for lacrimal gland induction. We show that Alx4 binds an Fgf10 intronic element conserved in terrestrial but not aquatic animals, underlying the evolutionary emergence of the lacrimal gland system in response to an airy environment. Inactivation of ALX4/Alx4 causes lacrimal gland aplasia in both human and mouse. These results reveal a key role of Alx4 in mediating FGF-Shp2-FGF signaling in the neural crest for lacrimal gland development.

High-throughput validation of ceRNA regulatory networks.

BACKGROUND: MicroRNAs (miRNAs) play multiple roles in tumor biology. Interestingly, reports from multiple groups suggest that miRNA targets may be coupled through competitive stoichiometric sequestration. Specifically, computational models predicted and experimental assays confirmed that miRNA activity is dependent on miRNA target abundance, and consequently, changes in the abundance of some miRNA targets lead to changes to the regulation and abundance of their other targets. The resulting indirect regulatory influence between miRNA targets resembles competition and has been dubbed competitive endogenous RNA (ceRNA). Recent studies have questioned the physiological relevance of ceRNA interactions, our ability to accurately predict these interactions, and the number of genes that are impacted by ceRNA interactions in specific cellular contexts. RESULTS: To address these concerns, we reverse engineered ceRNA networks (ceRNETs) in breast and prostate adenocarcinomas using context-specific TCGA profiles, and tested whether ceRNA interactions can predict the effects of RNAi-mediated gene silencing perturbations in PC3 and MCF7 cells._ENREF_22 Our results, based on tests of thousands of inferred ceRNA interactions that are predicted to alter hundreds of cancer genes in each of the two tumor contexts, confirmed statistically significant effects for half of the predicted targets. CONCLUSIONS: Our results suggest that the expression of a significant fraction of cancer genes may be regulated by ceRNA interactions in each of the two tumor contexts.

Quantitative Tyrosine Phosphoproteomics of Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitor-treated Lung Adenocarcinoma Cells Reveals Potential Novel Biomarkers of Therapeutic Response.

Mutations in the Epidermal growth factor receptor (EGFR) kinase domain, such as the L858R missense mutation and deletions spanning the conserved sequence 747LREA750, are sensitive to tyrosine kinase inhibitors (TKIs). The gatekeeper site residue mutation, T790M accounts for around 60% of acquired resistance to EGFR TKIs. The first generation EGFR TKIs, erlotinib and gefitinib, and the second generation inhibitor, afatinib are FDA approved for initial treatment of EGFR mutated lung adenocarcinoma. The predominant biomarker of EGFR TKI responsiveness is the presence of EGFR TKI-sensitizing mutations. However, 30-40% of patients with EGFR mutations exhibit primary resistance to these TKIs, underscoring the unmet need of identifying additional biomarkers of treatment response. Here, we sought to characterize the dynamics of tyrosine phosphorylation upon EGFR TKI treatment of mutant EGFR-driven human lung adenocarcinoma cell lines with varying sensitivity to EGFR TKIs, erlotinib and afatinib. We employed stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative mass spectrometry to identify and quantify tyrosine phosphorylated peptides. The proportion of tyrosine phosphorylated sites that had reduced phosphorylation upon erlotinib or afatinib treatment correlated with the degree of TKI-sensitivity. Afatinib, an irreversible EGFR TKI, more effectively inhibited tyrosine phosphorylation of a majority of the substrates. The phosphosites with phosphorylation SILAC ratios that correlated with the TKI-sensitivity of the cell lines include sites on kinases, such as EGFR-Y1197 and MAPK7-Y221, and adaptor proteins, such as SHC1-Y349/350, ERRFI1-Y394, GAB1-Y689, STAT5A-Y694, DLG3-Y705, and DAPP1-Y139, suggesting these are potential biomarkers of TKI sensitivity. DAPP1, is a novel target of mutant EGFR signaling and Y-139 is the major site of DAPP1 tyrosine phosphorylation. We also uncovered several off-target effects of these TKIs, such as MST1R-Y1238/Y1239 and MET-Y1252/1253. This study provides unique insight into the TKI-mediated modulation of mutant EGFR signaling, which can be applied to the development of biomarkers of EGFR TKI response.

Bone morphogenetic protein and Notch signalling crosstalk in poor-prognosis, mesenchymal-subtype colorectal cancer.

The functional role of bone morphogenetic protein (BMP) signalling in colorectal cancer (CRC) is poorly defined, with contradictory results in cancer cell line models reflecting the inherent difficulties of assessing a signalling pathway that is context-dependent and subject to genetic constraints. By assessing the transcriptional response of a diploid human colonic epithelial cell line to BMP ligand stimulation, we generated a prognostic BMP signalling signature, which was applied to multiple CRC datasets to investigate BMP heterogeneity across CRC molecular subtypes. We linked BMP and Notch signalling pathway activity and function in human colonic epithelial cells, and normal and neoplastic tissue. BMP induced Notch through a γ-secretase-independent interaction, regulated by the SMAD proteins. In homeostasis, BMP/Notch co-localization was restricted to cells at the top of the intestinal crypt, with more widespread interaction in some human CRC samples. BMP signalling was downregulated in the majority of CRCs, but was conserved specifically in mesenchymal-subtype tumours, where it interacts with Notch to induce an epithelial-mesenchymal transition (EMT) phenotype. In intestinal homeostasis, BMP-Notch pathway crosstalk is restricted to differentiating cells through stringent pathway segregation. Conserved BMP activity and loss of signalling stringency in mesenchymal-subtype tumours promotes a synergistic BMP-Notch interaction, and this correlates with poor patient prognosis. BMP signalling heterogeneity across CRC subtypes and cell lines can account for previous experimental contradictions. Crosstalk between the BMP and Notch pathways will render mesenchymal-subtype CRC insensitive to γ-secretase inhibition unless BMP activation is concomitantly addressed. © 2017 The Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Synergistic antileukemic therapies in NOTCH1-induced T-ALL.

The Notch1 gene is a major oncogenic driver and therapeutic target in T-cell acute lymphoblastic leukemia (T-ALL). However, inhibition of NOTCH signaling with γ-secretase inhibitors (GSIs) has shown limited antileukemic activity in clinical trials. Here we performed an expression-based virtual screening to identify highly active antileukemic drugs that synergize with NOTCH1 inhibition in T-ALL. Among these, withaferin A demonstrated the strongest cytotoxic and GSI-synergistic antileukemic effects in vitro and in vivo. Mechanistically, network perturbation analyses showed eIF2A-phosphorylation-mediated inhibition of protein translation as a critical mediator of the antileukemic effects of withaferin A and its interaction with NOTCH1 inhibition. Overall, these results support a role for anti-NOTCH1 therapies and protein translation inhibitor combinations in the treatment of T-ALL.

Novel Hybrid Phenotype Revealed in Small Cell Lung Cancer by a Transcription Factor Network Model That Can Explain Tumor Heterogeneity.

Small cell lung cancer (SCLC) is a devastating disease due to its propensity for early invasion and refractory relapse after initial treatment response. Although these aggressive traits have been associated with phenotypic heterogeneity, our understanding of this association remains incomplete. To fill this knowledge gap, we inferred a set of 33 transcription factors (TF) associated with gene signatures of the known neuroendocrine/epithelial (NE) and non-neuroendocrine/mesenchymal-like (ML) SCLC phenotypes. The topology of this SCLC TF network was derived from prior knowledge and was simulated using Boolean modeling. These simulations predicted that the network settles into attractors, or TF expression patterns, that correlate with NE or ML phenotypes, suggesting that TF network dynamics underlie the emergence of heterogeneous SCLC phenotypes. However, several cell lines and patient tumor specimens failed to correlate with either the NE or ML attractors. By flow cytometry, single cells within these cell lines simultaneously expressed surface markers of both NE and ML differentiation, confirming the existence of a "hybrid" phenotype. Upon exposure to standard-of-care cytotoxic drugs or epigenetic modifiers, NE and ML cell populations converged toward the hybrid state, suggesting possible escape from treatment. Our findings indicate that SCLC phenotypic heterogeneity can be specified dynamically by attractor states of a master regulatory TF network. Thus, SCLC heterogeneity may be best understood as states within an epigenetic landscape. Understanding phenotypic transitions within this landscape may provide insights to clinical applications. Cancer Res; 77(5); 1063-74. ©2016 AACR.

Correction: Inferring Protein Modulation from Gene Expression Data Using Conditional Mutual Information.

[This corrects the article DOI: 10.1371/journal.pone.0109569.].