CXCR4-Targeted Macrophage-Derived Biomimetic Hybrid Vesicle Nanoplatform for Enhanced Cancer Therapy through Codelivery of Manganese and Doxorubicin.

Immune-cell-derived membranes have garnered significant attention as innovative delivery modalities in cancer immunotherapy for their intrinsic immune-modulating functionalities and superior biocompatibilities. Integrating additional parental cell membranes or synthetic lipid vesicles into cellular vesicles can further potentiate their capacities to perform combinatorial pharmacological activities in activating antitumor immunity, thus providing insights into the potential of hybrid cellular vesicles as versatile delivery vehicles for cancer immunotherapy. Here, we have developed a macrophage-membrane-derived hybrid vesicle that has the dual functions of transporting immunotherapeutic drugs and shaping the polarization of tumor-associated macrophages for cancer immunotherapy. The platform combines M1 macrophage-membrane-derived vesicles with CXCR4-binding-peptide-conjugated liposomes loaded with manganese and doxorubicin. The hybrid nanovesicles exhibited remarkable macrophage-targeting capacity through the CXCR4-binding peptide, resulting in enhanced macrophage polarization to the antitumoral M1 phenotype characterized by proinflammatory cytokine release. The manganese/doxorubicin-loaded hybrid vesicles in the CXCR4-expressing tumor cells evoked potent cancer cytotoxicity, immunogenic cell death of tumor cells, and STING activation. Moreover, cotreatment with manganese and doxorubicin promoted dendritic cell maturation, enabling effective tumor growth inhibition. In murine models of CT26 colon carcinoma and 4T1 breast cancer, intravenous administration of the manganese/doxorubicin-loaded hybrid vesicles elicited robust tumor-suppressing activity at a low dosage without adverse systemic effects. Local administration of hybrid nanovesicles also induced an abscessive effect in a bilateral 4T1 tumor model. This study demonstrates a promising biomimetic manganese/doxorubicin-based hybrid nanovesicle platform for effective cancer immunotherapy tailored to the tumor microenvironment, which may offer an innovative approach to combinatorial immunotherapy.

Protein interaction networks in the vasculature prioritize genes and pathways underlying coronary artery disease.

Population-based association studies have identified many genetic risk loci for coronary artery disease (CAD), but it is often unclear how genes within these loci are linked to CAD. Here, we perform interaction proteomics for 11 CAD-risk genes to map their protein-protein interactions (PPIs) in human vascular cells and elucidate their roles in CAD. The resulting PPI networks contain interactions that are outside of known biology in the vasculature and are enriched for genes involved in immunity-related and arterial-wall-specific mechanisms. Several PPI networks derived from smooth muscle cells are significantly enriched for genetic variants associated with CAD and related vascular phenotypes. Furthermore, the networks identify 61 genes that are found in genetic loci associated with risk of CAD, prioritizing them as the causal candidates within these loci. These findings indicate that the PPI networks we have generated are a rich resource for guiding future research into the molecular pathogenesis of CAD.

Vaccines for immune tolerance against autoimmune disease.

The high prevalence and rising incidence of autoimmune diseases have become a prominent public health issue. Autoimmune disorders result from the immune system erroneously attacking the body's own healthy cells and tissues, causing persistent inflammation, tissue injury, and impaired organ function. Existing treatments primarily rely on broad immunosuppression, leaving patients vulnerable to infections and necessitating lifelong treatments. To address these unmet needs, an emerging frontier of vaccine development aims to restore immune equilibrium by inducing immune tolerance to autoantigens, offering a potential avenue for a cure rather than mere symptom management. We discuss this burgeoning field of vaccine development against inflammation and autoimmune diseases, with a focus on common autoimmune disorders, including multiple sclerosis, type 1 diabetes, rheumatoid arthritis, inflammatory bowel disease, and systemic lupus erythematosus. Vaccine-based strategies provide a new pathway for the future of autoimmune disease therapeutics, heralding a new era in the battle against inflammation and autoimmunity.

Using brain cell-type-specific protein interactomes to interpret neurodevelopmental genetic signals in schizophrenia.

Genetics have nominated many schizophrenia risk genes and identified convergent signals between schizophrenia and neurodevelopmental disorders. However, functional interpretation of the nominated genes in the relevant brain cell types is often lacking. We executed interaction proteomics for six schizophrenia risk genes that have also been implicated in neurodevelopment in human induced cortical neurons. The resulting protein network is enriched for common variant risk of schizophrenia in Europeans and East Asians, is down-regulated in layer 5/6 cortical neurons of individuals affected by schizophrenia, and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in individuals with schizophrenia and bipolar disorder. Our findings showcase brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and its related disorders.

Induction of T-helper-17-cell-mediated anti-tumour immunity by pathogen-mimicking polymer nanoparticles.

The effectivity of cancer immunotherapies is hindered by immunosuppressive tumour microenvironments that are poorly infiltrated by effector T cells and natural killer cells. In infection and autoimmune disease, the recruitment and activation of effector immune cells is coordinated by pro-inflammatory T helper 17 (TH17) cells. Here we show that pathogen-mimicking hollow nanoparticles displaying mannan (a polysaccharide that activates TH17 cells in microbial cell walls) limit the fraction of regulatory T cells and induce TH17-cell-mediated anti-tumour responses. The nanoparticles activate the pattern-recognition receptor Dectin-2 and Toll-like receptor 4 in dendritic cells, and promote the differentiation of CD4+ T cells into the TH17 phenotype. In mice, intra-tumoural administration of the nanoparticles decreased the fraction of regulatory T cells in the tumour while markedly increasing the fractions of TH17 cells (and the levels of TH17-cell-associated cytokines), CD8+ T cells, natural killer cells and M1-like macrophages. The anti-tumoural activity of the effector cells was amplified by an agonistic antibody against the co-stimulatory receptor OX40 in multiple mouse models. Nanomaterials that induce TH17-cell-mediated immune responses may have therapeutic potential.

The Effects of pH and Excipients on Exenatide Stability in Solution.

Exenatide, a glucagon-like peptide-1 receptor agonist, is the active pharmaceutical ingredient in Byetta® and Bydureon®, two type 2 diabetes drug products that have generics and multiple follow-up formulations currently in development. Even though exenatide is known to be chemically and physically unstable at pH 7.5, there lacks a systematic evaluation of the impact of pH and excipients on the peptide solution stability. In this study, we established analytical methods to measure the chemical and physical degradation of the peptide in solution. Exenatide remained relatively stable at pH 4.5 when incubated at 37 °C. At pH 5.5-6.5, degradation was driven by oxidation, while driven by deamidation at pH 7.5-8.5. Significant aggregation of exenatide at pH 7.5 and 8.5 was detected by size exclusion chromatography and dynamic light scattering. Each pH value greater than 4.5 exhibited unique profiles corresponding to a loss of α-helical content and an increase in unordered structures. The addition of sugars, including mannitol, sorbitol and sucrose, conferred small protective effects against peptide aggregation when incubating at pH 7.5 and 37 °C, as measured by size-exclusion chromatography and dynamic light scattering. The results of this study will be useful for investigators developing generic exenatide products, peptide analogs and novel exenatide drug delivery systems.

Genoppi is an open-source software for robust and standardized integration of proteomic and genetic data.

Combining genetic and cell-type-specific proteomic datasets can generate biological insights and therapeutic hypotheses, but a technical and statistical framework for such analyses is lacking. Here, we present an open-source computational tool called Genoppi (lagelab.org/genoppi) that enables robust, standardized, and intuitive integration of quantitative proteomic results with genetic data. We use Genoppi to analyze 16 cell-type-specific protein interaction datasets of four proteins (BCL2, TDP-43, MDM2, PTEN) involved in cancer and neurological disease. Through systematic quality control of the data and integration with published protein interactions, we show a general pattern of both cell-type-independent and cell-type-specific interactions across three cancer cell types and one human iPSC-derived neuronal cell type. Furthermore, through the integration of proteomic and genetic datasets in Genoppi, our results suggest that the neuron-specific interactions of these proteins are mediating their genetic involvement in neurodegenerative diseases. Importantly, our analyses suggest that human iPSC-derived neurons are a relevant model system for studying the involvement of BCL2 and TDP-43 in amyotrophic lateral sclerosis.

GeNets: a unified web platform for network-based genomic analyses.

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets.

Integrated Bayesian analysis of rare exonic variants to identify risk genes for schizophrenia and neurodevelopmental disorders.

BACKGROUND: Integrating rare variation from trio family and case-control studies has successfully implicated specific genes contributing to risk of neurodevelopmental disorders (NDDs) including autism spectrum disorders (ASD), intellectual disability (ID), developmental disorders (DDs), and epilepsy (EPI). For schizophrenia (SCZ), however, while sets of genes have been implicated through the study of rare variation, only two risk genes have been identified. METHODS: We used hierarchical Bayesian modeling of rare-variant genetic architecture to estimate mean effect sizes and risk-gene proportions, analyzing the largest available collection of whole exome sequence data for SCZ (1,077 trios, 6,699 cases, and 13,028 controls), and data for four NDDs (ASD, ID, DD, and EPI; total 10,792 trios, and 4,058 cases and controls). RESULTS: For SCZ, we estimate there are 1,551 risk genes. There are more risk genes and they have weaker effects than for NDDs. We provide power analyses to predict the number of risk-gene discoveries as more data become available. We confirm and augment prior risk gene and gene set enrichment results for SCZ and NDDs. In particular, we detected 98 new DD risk genes at FDR < 0.05. Correlations of risk-gene posterior probabilities are high across four NDDs (ρ>0.55), but low between SCZ and the NDDs (ρ<0.3). An in-depth analysis of 288 NDD genes shows there is highly significant protein-protein interaction (PPI) network connectivity, and functionally distinct PPI subnetworks based on pathway enrichment, single-cell RNA-seq cell types, and multi-region developmental brain RNA-seq. CONCLUSIONS: We have extended a pipeline used in ASD studies and applied it to infer rare genetic parameters for SCZ and four NDDs ( https://github.com/hoangtn/extTADA ). We find many new DD risk genes, supported by gene set enrichment and PPI network connectivity analyses. We find greater similarity among NDDs than between NDDs and SCZ. NDD gene subnetworks are implicated in postnatally expressed presynaptic and postsynaptic genes, and for transcriptional and post-transcriptional gene regulation in prenatal neural progenitor and stem cells.

Overlapping 16p13.11 deletion and gain of copies variations associated with childhood onset psychosis include genes with mechanistic implications for autism associated pathways: Two case reports.

Copy number variability at 16p13.11 has been associated with intellectual disability, autism, schizophrenia, epilepsy, and attention-deficit hyperactivity disorder. Adolescent/adult- onset psychosis has been reported in a subset of these cases. Here, we report on two children with CNVs in 16p13.11 that developed psychosis before the age of 7. The genotype and neuropsychiatric abnormalities of these patients highlight several overlapping genes that have possible mechanistic relevance to pathways previously implicated in Autism Spectrum Disorders, including the mTOR signaling and the ubiquitin-proteasome cascades. A careful screening of the 16p13.11 region is warranted in patients with childhood onset psychosis.

N100 Repetition Suppression Indexes Neuroplastic Defects in Clinical High Risk and Psychotic Youth.

Highly penetrant mutations leading to schizophrenia are enriched for genes coding for N-methyl-D-aspartate receptor signaling complex (NMDAR-SC), implicating plasticity defects in the disease's pathogenesis. The importance of plasticity in neurodevelopment implies a role for therapies that target these mechanisms in early life to prevent schizophrenia. Testing such therapies requires noninvasive methods that can assess engagement of target mechanisms. The auditory N100 is an obligatory cortical response whose amplitude decreases with tone repetition. This adaptation may index the health of plasticity mechanisms required for normal development. We exposed participants aged 5 to 17 years with psychosis (n = 22), at clinical high risk (CHR) for psychosis (n = 29), and healthy controls (n = 17) to an auditory tone repeated 450 times and measured N100 adaptation (mean amplitude during first 150 tones - mean amplitude during last 150 tones). N100 adaptation was reduced in CHR and psychosis, particularly among participants <13 years old. Initial N100 blunting partially accounted for differences. Decreased change in the N100 amplitude with tone repetition may be a useful marker of defects in neuroplastic mechanisms measurable early in life.

Early auditory processing evoked potentials (N100) show a continuum of blunting from clinical high risk to psychosis in a pediatric sample.

BACKGROUND: The N100 is a negative deflection in the surface EEG approximately 100 ms after an auditory signal. It has been shown to be reduced in individuals with schizophrenia and those at clinical high risk (CHR). N100 blunting may index neural network dysfunction underlying psychotic symptoms. This phenomenon has received little attention in pediatric populations. METHOD: This cross-sectional study compared the N100 response measured via the average EEG response at the left medial frontal position FC1 to 150 sinusoidal tones in participants ages 5 to 17 years with a CHR syndrome (n=29), a psychotic disorder (n=22), or healthy controls (n=17). RESULTS: Linear regression analyses that considered potential covariates (age, gender, handedness, family mental health history, medication usage) revealed decreasing N100 amplitude with increasing severity of psychotic symptomatology from healthy to CHR to psychotic level. CONCLUSIONS: Longitudinal assessment of the N100 in CHR children who do and do not develop psychosis will inform whether it predicts transition to psychosis and if its response to treatment predicts symptom change.