Impact of the physical-chemical properties of poly(lactic acid)-poly(ethylene glycol) polymeric nanoparticles on biodistribution.

Nanoparticle (NP) formulations are inherently polydisperse making their structural characterization and justification of specifications complex. It is essential, however, to gain an understanding of the physico-chemical properties that drive performance in vivo. To elucidate these properties, drug-containing poly(lactic acid) (PLA)-poly(ethylene glycol) (PEG) block polymeric NP formulations (or PNPs) were sub-divided into discrete size fractions and analyzed using a combination of advanced techniques, namely cryogenic transmission electron microscopy, small-angle neutron and X-ray scattering, nuclear magnetic resonance, and hard-energy X-ray photoelectron spectroscopy. Together, these techniques revealed a uniquely detailed picture of PNP size, surface structure, internal molecular architecture and the preferred site(s) of incorporation of the hydrophobic drug, AZD5991, properties which cannot be accessed via conventional characterization methodologies. Within the PNP size distribution, it was shown that the smallest PNPs contained significantly less drug than their larger sized counterparts, reducing overall drug loading, while PNP molecular architecture was critical in understanding the nature of in vitro drug release. The effect of PNP size and structure on drug biodistribution was determined by administrating selected PNP size fractions to mice, with the smaller sized NP fractions increasing the total drug-plasma concentration area under the curve and reducing drug concentrations in liver and spleen, due to greater avoidance of the reticuloendothelial system. In contrast, administration of unfractionated PNPs, containing a large population of NPs with extremely low drug load, did not significantly impact the drug's pharmacokinetic behavior - a significant result for nanomedicine development where a uniform formulation is usually an important driver. We also demonstrate how, in this study, it is not practicable to validate the bioanalytical methodology for drug released in vivo due to the NP formulation properties, a process which is applicable for most small molecule-releasing nanomedicines. In conclusion, this work details a strategy for determining the effect of formulation variability on in vivo performance, thereby informing the translation of PNPs, and other NPs, from the laboratory to the clinic.

The Next-Generation Oral Selective Estrogen Receptor Degrader Camizestrant (AZD9833) Suppresses ER+ Breast Cancer Growth and Overcomes Endocrine and CDK4/6 Inhibitor Resistance.

Oral selective estrogen receptor degraders (SERD) could become the backbone of endocrine therapy (ET) for estrogen receptor-positive (ER+) breast cancer, as they achieve greater inhibition of ER-driven cancers than current ETs and overcome key resistance mechanisms. In this study, we evaluated the preclinical pharmacology and efficacy of the next-generation oral SERD camizestrant (AZD9833) and assessed ER-co-targeting strategies by combining camizestrant with CDK4/6 inhibitors (CDK4/6i) and PI3K/AKT/mTOR-targeted therapy in models of progression on CDK4/6i and/or ET. Camizestrant demonstrated robust and selective ER degradation, modulated ER-regulated gene expression, and induced complete ER antagonism and significant antiproliferation activity in ESR1 wild-type (ESR1wt) and mutant (ESR1m) breast cancer cell lines and patient-derived xenograft (PDX) models. Camizestrant also delivered strong antitumor activity in fulvestrant-resistant ESR1wt and ESR1m PDX models. Evaluation of camizestrant in combination with CDK4/6i (palbociclib or abemaciclib) in CDK4/6-naive and -resistant models, as well as in combination with PI3Kαi (alpelisib), mTORi (everolimus), or AKTi (capivasertib), indicated that camizestrant was active with CDK4/6i or PI3K/AKT/mTORi and that antitumor activity was further increased by the triple combination. The response was observed independently of PI3K pathway mutation status. Overall, camizestrant shows strong and broad antitumor activity in ER+ breast cancer as a monotherapy and when combined with CDK4/6i and PI3K/AKT/mTORi. SIGNIFICANCE: Camizestrant, a next-generation oral SERD, shows promise in preclinical models of ER+ breast cancer alone and in combination with CDK4/6 and PI3K/AKT/mTOR inhibitors to address endocrine resistance, a current barrier to treatment.

Optimal experimental design for efficient toxicity testing in microphysiological systems: A bone marrow application.

Introduction: Microphysiological systems (MPS; organ-on-a-chip) aim to recapitulate the 3D organ microenvironment and improve clinical predictivity relative to previous approaches. Though MPS studies provide great promise to explore treatment options in a multifactorial manner, they are often very complex. It is therefore important to assess and manage technical confounding factors, to maximise power, efficiency and scalability. Methods: As an illustration of how MPS studies can benefit from a systematic evaluation of confounders, we developed an experimental design approach for a bone marrow (BM) MPS and tested it for a specified context of use, the assessment of lineage-specific toxicity. Results: We demonstrated the accuracy of our multicolour flow cytometry set-up to determine cell type and maturity, and the viability of a "repeated measures" design where we sample from chips repeatedly for increased scalability and robustness. Importantly, we demonstrated an optimal way to arrange technical confounders. Accounting for these confounders in a mixed-model analysis pipeline increased power, which meant that the expected lineage-specific toxicities following treatment with olaparib or carboplatin were detected earlier and at lower doses. Furthermore, we performed a sample size analysis to estimate the appropriate number of replicates required for different effect sizes. This experimental design-based approach will generalise to other MPS set-ups. Discussion: This design of experiments approach has established a groundwork for a reliable and reproducible in vitro analysis of BM toxicity in a MPS, and the lineage-specific toxicity data demonstrate the utility of this model for BM toxicity assessment. Toxicity data demonstrate the utility of this model for BM toxicity assessment.

Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion tools.

Capture Hi-C is widely used to obtain high-resolution profiles of chromosomal interactions involving, at least on one end, regions of interest such as gene promoters. Signal detection in Capture Hi-C data is challenging and cannot be adequately accomplished with tools developed for other chromosome conformation capture methods, including standard Hi-C. Capture Hi-C Analysis of Genomic Organization (CHiCAGO) is a computational pipeline developed specifically for Capture Hi-C analysis. It implements a statistical model accounting for biological and technical background components, as well as bespoke normalization and multiple testing procedures for this data type. Here we provide a step-by-step guide to the CHiCAGO workflow that is aimed at users with basic experience of the command line and R. We also describe more advanced strategies for tuning the key parameters for custom experiments and provide guidance on data preprocessing and downstream analysis using companion tools. In a typical experiment, CHiCAGO takes ~2-3 h to run, although pre- and postprocessing steps may take much longer.

Radiopotentiation Profiling of Multiple Inhibitors of the DNA Damage Response for Early Clinical Development.

Radiotherapy is an effective anticancer treatment, but combinations with targeted agents that maximize efficacy while sparing normal tissue are needed. Here, we assess the radiopotentiation profiles of DNA damage response inhibitors (DDRi) olaparib (PARP1/2), ceralasertib (ATR), adavosertib (WEE1), AZD0156 (ATM), and KU-60648 (DNA-PK). We performed a radiotherapy combination screen and assessed how drug concentration and cellular DDR deficiencies influence the radiopotentiation ability of DDRi. We pre-selected six lung cancer cell lines with different genetic/signaling aberrations (including mutations in TP53 and ATM) and assessed multiple concentrations of DDRi in combination with a fixed radiotherapy dose by clonogenic assay. The effective concentration of DDRi in radiotherapy combinations is lower than that required for single-agent efficacy. This has the potential to be exploited further in the context of DDR deficiencies to increase therapeutic index and we demonstrate that low concentrations of AZD0156 preferentially sensitized p53-deficient cells. Moreover, testing multiple concentrations of DDRi in radiotherapy combinations indicated that olaparib, ceralasertib, and adavosertib have a desirable safety profile showing moderate increases in radiotherapy dose enhancement with increasing inhibitor concentration. Small increases in concentration of AZD0156 and particularly KU-60648, however, result in steep increases in dose enhancement. Radiopotentiation profiling can inform on effective drug doses required for radiosensitization in relation to biomarkers, providing an opportunity to increase therapeutic index. Moreover, multiple concentration testing demonstrates a relationship between drug concentration and radiotherapy effect that provides valuable insights that, with future in vivo validation, can guide dose-escalation strategies in clinical trials.

The global and promoter-centric 3D genome organization temporally resolved during a circadian cycle.

BACKGROUND: Circadian gene expression is essential for organisms to adjust their physiology and anticipate daily changes in the environment. The molecular mechanisms controlling circadian gene transcription are still under investigation. In particular, how chromatin conformation at different genomic scales and regulatory elements impact rhythmic gene expression has been poorly characterized. RESULTS: Here we measure changes in the spatial chromatin conformation in mouse liver using genome-wide and promoter-capture Hi-C alongside daily oscillations in gene transcription. We find topologically associating domains harboring circadian genes that switch assignments between the transcriptionally active and inactive compartment at different hours of the day, while their boundaries stably maintain their structure over time. To study chromatin contacts of promoters at high resolution over time, we apply promoter capture Hi-C. We find circadian gene promoters displayed a maximal number of chromatin contacts at the time of their peak transcriptional output. Furthermore, circadian genes, as well as contacted and transcribed regulatory elements, reach maximal expression at the same timepoints. Anchor sites of circadian gene promoter loops are enriched in DNA binding sites for liver nuclear receptors and other transcription factors, some exclusively present in either rhythmic or stable contacts. Finally, by comparing the interaction profiles between core clock and output circadian genes, we show that core clock interactomes are more dynamic compared to output circadian genes. CONCLUSION: Our results identify chromatin conformation dynamics at different scales that parallel oscillatory gene expression and characterize the repertoire of regulatory elements that control circadian gene transcription through rhythmic or stable chromatin configurations.

High-Throughput Mechanism of Inhibition.

Enzymes represent a significant proportion of the druggable genome and constitute a rich source of drug targets. Delivery of a successful program for developing a modulator of enzyme activity requires an understanding of the enzyme's mechanism and the mode of interaction of compounds. This allows an understanding of how physiological conditions in disease-relevant cells will affect inhibitor potency. As a result, there is increasing interest in evaluating hit compounds from high-throughput screens to determine their mode of interaction with the target. This work revisits the common inhibition modalities and illustrates the impact of substrate concentration relative to Km upon the pattern of changes in IC50 that are expected for increasing substrate concentration. It proposes a new, high-throughput approach for assessing mode of inhibition, incorporating analyses based on a minimal descriptive model, to deliver a workflow that allows rapid and earlier compound classification immediately after high-throughput screening.

AZD7648 is a potent and selective DNA-PK inhibitor that enhances radiation, chemotherapy and olaparib activity.

DNA-dependent protein kinase (DNA-PK) is a critical player in the DNA damage response (DDR) and instrumental in the non-homologous end-joining pathway (NHEJ) used to detect and repair DNA double-strand breaks (DSBs). We demonstrate that the potent and highly selective DNA-PK inhibitor, AZD7648, is an efficient sensitizer of radiation- and doxorubicin-induced DNA damage, with combinations in xenograft and patient-derived xenograft (PDX) models inducing sustained regressions. Using ATM-deficient cells, we demonstrate that AZD7648, in combination with the PARP inhibitor olaparib, increases genomic instability, resulting in cell growth inhibition and apoptosis. AZD7648 enhanced olaparib efficacy across a range of doses and schedules in xenograft and PDX models, enabling sustained tumour regression and providing a clear rationale for its clinical investigation. Through its differentiated mechanism of action as an NHEJ inhibitor, AZD7648 complements the current armamentarium of DDR-targeted agents and has potential in combination with these agents to achieve deeper responses to current therapies.

Single-cell study of neural stem cells derived from human iPSCs reveals distinct progenitor populations with neurogenic and gliogenic potential.

We used single-cell RNA sequencing (seq) on several human induced pluripotent stem (iPS) cell-derived neural stem cell (NSC) lines and one fetal brain-derived NSC line to study inherent cell type heterogeneity at proliferating neural stem cell stage and uncovered predisposed presence of neurogenic and gliogenic progenitors. We observed heterogeneity in neurogenic progenitors that differed between the iPS cell-derived NSC lines and the fetal-derived NSC line, and we also observed differences in spontaneous differentiation potential for inhibitory and excitatory neurons between the iPS cell-derived NSC lines and the fetal-derived NSC line. In addition, using a recently published glia patterning protocol we enriched for gliogenic progenitors and generated glial cells from an iPS cell-derived NSC line.

RNA proximity sequencing reveals the spatial organization of the transcriptome in the nucleus.

The global, three-dimensional organization of RNA molecules in the nucleus is difficult to determine using existing methods. Here we introduce Proximity RNA-seq, which identifies colocalization preferences for pairs or groups of nascent and fully transcribed RNAs in the nucleus. Proximity RNA-seq is based on massive-throughput RNA barcoding of subnuclear particles in water-in-oil emulsion droplets, followed by cDNA sequencing. Our results show RNAs of varying tissue-specificity of expression, speed of RNA polymerase elongation and extent of alternative splicing positioned at varying distances from nucleoli. The simultaneous detection of multiple RNAs in proximity to each other distinguishes RNA-dense from sparse compartments. Application of Proximity RNA-seq will facilitate study of the spatial organization of transcripts in the nucleus, including non-coding RNAs, and its functional relevance.

Chicdiff: a computational pipeline for detecting differential chromosomal interactions in Capture Hi-C data.

SUMMARY: Capture Hi-C is a powerful approach for detecting chromosomal interactions involving, at least on one end, DNA regions of interest, such as gene promoters. We present Chicdiff, an R package for robust detection of differential interactions in Capture Hi-C data. Chicdiff enhances a state-of-the-art differential testing approach for count data with bespoke normalization and multiple testing procedures that account for specific statistical properties of Capture Hi-C. We validate Chicdiff on published Promoter Capture Hi-C data in human Monocytes and CD4+ T cells, identifying multitudes of cell type-specific interactions, and confirming the overall positive association between promoter interactions and gene expression. AVAILABILITY AND IMPLEMENTATION: Chicdiff is implemented as an R package that is publicly available at https://github.com/RegulatoryGenomicsGroup/chicdiff. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrated in vitro models for hepatic safety and metabolism: evaluation of a human Liver-Chip and liver spheroid.

Drug-induced liver injury remains a frequent reason for drug withdrawal. Accordingly, more predictive and translational models are required to assess human hepatotoxicity risk. This study presents a comprehensive evaluation of two promising models to assess mechanistic hepatotoxicity, microengineered Organ-Chips and 3D hepatic spheroids, which have enhanced liver phenotype, metabolic activity and stability in culture not attainable with conventional 2D models. Sensitivity of the models to two hepatotoxins, acetaminophen (APAP) and fialuridine (FIAU), was assessed across a range of cytotoxicity biomarkers (ATP, albumin, miR-122, α-GST) as well as their metabolic functionality by quantifying APAP, FIAU and CYP probe substrate metabolites. APAP and FIAU produced dose- and time-dependent increases in miR-122 and α-GST release as well as decreases in albumin secretion in both Liver-Chips and hepatic spheroids. Metabolic turnover of CYP probe substrates, APAP and FIAU, was maintained over the 10-day exposure period at concentrations where no cytotoxicity was detected and APAP turnover decreased at concentrations where cytotoxicity was detected. With APAP, the most sensitive biomarkers were albumin in the Liver-Chips (EC50 5.6 mM, day 1) and miR-122 and ATP in the liver spheroids (14-fold and EC50 2.9 mM, respectively, day 3). With FIAU, the most sensitive biomarkers were albumin in the Liver-Chip (EC50 126 µM) and miR-122 (15-fold) in the liver spheroids, both on day 7. In conclusion, both models exhibited integrated toxicity and metabolism, and broadly similar sensitivity to the hepatotoxicants at relevant clinical concentrations, demonstrating the utility of these models for improved hepatotoxicity risk assessment.

Optimizing the design of population-based patient-derived tumor xenograft studies to better predict clinical response.

The high attrition rate of preclinical agents entering oncology clinical trials has been associated with poor understanding of the heterogeneous patient response, arising from limitations in the preclinical pipeline with cancer models. Patient-derived tumor xenograft (PDX) models have been shown to better recapitulate the patient drug response. However, the platform of evidence generated to support clinical development in a drug discovery project typically employs a limited number of models, which may not accurately predict the response at a population level. Population PDX studies, large-scale screens of PDX models, have been proposed as a strategy to model the patient inter-tumor heterogeneity. Here, we present a freely available interactive tool that explores the design of a population PDX study and how it impacts the sensitivity and false-positive rate experienced. We discuss the reflection process needed to optimize the design for the therapeutic landscape being studied and manage the risk of false-negative and false-positive outcomes that the sponsor is willing to take. The tool has been made freely available to allow the optimal design to be determined for each drug-disease area. This will allow researchers to improve their understanding of treatment efficacy in the presence of genetic variability before taking a drug to clinic. In addition, the tool serves to refine the number of animals to be used for population-based PDX studies, ensuring researchers meet their ethical obligation when performing animal research.

Long-Range Enhancer Interactions Are Prevalent in Mouse Embryonic Stem Cells and Are Reorganized upon Pluripotent State Transition.

Transcriptional enhancers, including super-enhancers (SEs), form physical interactions with promoters to regulate cell-type-specific gene expression. SEs are characterized by high transcription factor occupancy and large domains of active chromatin, and they are commonly assigned to target promoters using computational predictions. How promoter-SE interactions change upon cell state transitions, and whether transcription factors maintain SE interactions, have not been reported. Here, we used promoter-capture Hi-C to identify promoters that interact with SEs in mouse embryonic stem cells (ESCs). We found that SEs form complex, spatial networks in which individual SEs contact multiple promoters, and a rewiring of promoter-SE interactions occurs between pluripotent states. We also show that long-range promoter-SE interactions are more prevalent in ESCs than in epiblast stem cells (EpiSCs) or Nanog-deficient ESCs. We conclude that SEs form cell-type-specific interaction networks that are partly dependent on core transcription factors, thereby providing insights into the gene regulatory organization of pluripotent cells.

Chromosome contacts in activated T cells identify autoimmune disease candidate genes.

BACKGROUND: Autoimmune disease-associated variants are preferentially found in regulatory regions in immune cells, particularly CD4+ T cells. Linking such regulatory regions to gene promoters in disease-relevant cell contexts facilitates identification of candidate disease genes. RESULTS: Within 4 h, activation of CD4+ T cells invokes changes in histone modifications and enhancer RNA transcription that correspond to altered expression of the interacting genes identified by promoter capture Hi-C. By integrating promoter capture Hi-C data with genetic associations for five autoimmune diseases, we prioritised 245 candidate genes with a median distance from peak signal to prioritised gene of 153 kb. Just under half (108/245) prioritised genes related to activation-sensitive interactions. This included IL2RA, where allele-specific expression analyses were consistent with its interaction-mediated regulation, illustrating the utility of the approach. CONCLUSIONS: Our systematic experimental framework offers an alternative approach to candidate causal gene identification for variants with cell state-specific functional effects, with achievable sample sizes.

Lineage-specific dynamic and pre-established enhancer-promoter contacts cooperate in terminal differentiation.

Chromosome conformation is an important feature of metazoan gene regulation; however, enhancer-promoter contact remodeling during cellular differentiation remains poorly understood. To address this, genome-wide promoter capture Hi-C (CHi-C) was performed during epidermal differentiation. Two classes of enhancer-promoter contacts associated with differentiation-induced genes were identified. The first class ('gained') increased in contact strength during differentiation in concert with enhancer acquisition of the H3K27ac activation mark. The second class ('stable') were pre-established in undifferentiated cells, with enhancers constitutively marked by H3K27ac. The stable class was associated with the canonical conformation regulator cohesin, whereas the gained class was not, implying distinct mechanisms of contact formation and regulation. Analysis of stable enhancers identified a new, essential role for a constitutively expressed, lineage-restricted ETS-family transcription factor, EHF, in epidermal differentiation. Furthermore, neither class of contacts was observed in pluripotent cells, suggesting that lineage-specific chromatin structure is established in tissue progenitor cells and is further remodeled in terminal differentiation.

Platelet function is modified by common sequence variation in megakaryocyte super enhancers.

Linking non-coding genetic variants associated with the risk of diseases or disease-relevant traits to target genes is a crucial step to realize GWAS potential in the introduction of precision medicine. Here we set out to determine the mechanisms underpinning variant association with platelet quantitative traits using cell type-matched epigenomic data and promoter long-range interactions. We identify potential regulatory functions for 423 of 565 (75%) non-coding variants associated with platelet traits and we demonstrate, through ex vivo and proof of principle genome editing validation, that variants in super enhancers play an important role in controlling archetypical platelet functions.

Dynamic Rewiring of Promoter-Anchored Chromatin Loops during Adipocyte Differentiation.

Interactions between transcriptional promoters and their distal regulatory elements play an important role in transcriptional regulation; however, the extent to which these interactions are subject to rapid modulations in response to signals is unknown. Here, we use promoter capture Hi-C to demonstrate a rapid reorganization of promoter-anchored chromatin loops within 4 hr after inducing differentiation of 3T3-L1 preadipocytes. The establishment of new promoter-enhancer loops is tightly coupled to activation of poised (histone H3 lysine 4 mono- and dimethylated) enhancers, as evidenced by the acquisition of histone H3 lysine 27 acetylation and the binding of MED1, SMC1, and P300 proteins to these regions, as well as to activation of target genes. Intriguingly, formation of loops connecting activated enhancers and promoters is also associated with extensive recruitment of corepressors such as NCoR and HDACs, indicating that this class of coregulators may play a previously unrecognized role during enhancer activation.

Global reorganisation of cis-regulatory units upon lineage commitment of human embryonic stem cells.

Long-range cis-regulatory elements such as enhancers coordinate cell-specific transcriptional programmes by engaging in DNA looping interactions with target promoters. Deciphering the interplay between the promoter connectivity and activity of cis-regulatory elements during lineage commitment is crucial for understanding developmental transcriptional control. Here, we use Promoter Capture Hi-C to generate a high-resolution atlas of chromosomal interactions involving ~22,000 gene promoters in human pluripotent and lineage-committed cells, identifying putative target genes for known and predicted enhancer elements. We reveal extensive dynamics of cis-regulatory contacts upon lineage commitment, including the acquisition and loss of promoter interactions. This spatial rewiring occurs preferentially with predicted changes in the activity of cis-regulatory elements and is associated with changes in target gene expression. Our results provide a global and integrated view of promoter interactome dynamics during lineage commitment of human pluripotent cells.

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters.

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.