CellSTAR: a comprehensive resource for single-cell transcriptomic annotation.

Large-scale studies of single-cell sequencing and biological experiments have successfully revealed expression patterns that distinguish different cell types in tissues, emphasizing the importance of studying cellular heterogeneity and accurately annotating cell types. Analysis of gene expression profiles in these experiments provides two essential types of data for cell type annotation: annotated references and canonical markers. In this study, the first comprehensive database of single-cell transcriptomic annotation resource (CellSTAR) was thus developed. It is unique in (a) offering the comprehensive expertly annotated reference data for annotating hundreds of cell types for the first time and (b) enabling the collective consideration of reference data and marker genes by incorporating tens of thousands of markers. Given its unique features, CellSTAR is expected to attract broad research interests from the technological innovations in single-cell transcriptomics, the studies of cellular heterogeneity & dynamics, and so on. It is now publicly accessible without any login requirement at: https://idrblab.org/cellstar.

TheMarker: a comprehensive database of therapeutic biomarkers.

Distinct from the traditional diagnostic/prognostic biomarker (adopted as the indicator of disease state/process), the therapeutic biomarker (ThMAR) has emerged to be very crucial in the clinical development and clinical practice of all therapies. There are five types of ThMAR that have been found to play indispensable roles in various stages of drug discovery, such as: Pharmacodynamic Biomarker essential for guaranteeing the pharmacological effects of a therapy, Safety Biomarker critical for assessing the extent or likelihood of therapy-induced toxicity, Monitoring Biomarker indispensable for guiding clinical management by serially measuring patients' status, Predictive Biomarker crucial for maximizing the clinical outcome of a therapy for specific individuals, and Surrogate Endpoint fundamental for accelerating the approval of a therapy. However, these data of ThMARs has not been comprehensively described by any of the existing databases. Herein, a database, named 'TheMarker', was therefore constructed to (a) systematically offer all five types of ThMAR used at different stages of drug development, (b) comprehensively describe ThMAR information for the largest number of drugs among available databases, (c) extensively cover the widest disease classes by not just focusing on anticancer therapies. These data in TheMarker are expected to have great implication and significant impact on drug discovery and clinical practice, and it is freely accessible without any login requirement at: https://idrblab.org/themarker.

Strategy for Identifying a Robust Metabolomic Signature Reveals the Altered Lipid Metabolism in Pituitary Adenoma.

Despite the well-established connection between systematic metabolic abnormalities and the pathophysiology of pituitary adenoma (PA), current metabolomic studies have reported an extremely limited number of metabolites associated with PA. Moreover, there was very little consistency in the identified metabolite signatures, resulting in a lack of robust metabolic biomarkers for the diagnosis and treatment of PA. Herein, we performed a global untargeted plasma metabolomic profiling on PA and identified a highly robust metabolomic signature based on a strategy. Specifically, this strategy is unique in (1) integrating repeated random sampling and a consensus evaluation-based feature selection algorithm and (2) evaluating the consistency of metabolomic signatures among different sample groups. This strategy demonstrated superior robustness and stronger discriminative ability compared with that of other feature selection methods including Student's t-test, partial least-squares-discriminant analysis, support vector machine recursive feature elimination, and random forest recursive feature elimination. More importantly, a highly robust metabolomic signature comprising 45 PA-specific differential metabolites was identified. Moreover, metabolite set enrichment analysis of these potential metabolic biomarkers revealed altered lipid metabolism in PA. In conclusion, our findings contribute to a better understanding of the metabolic changes in PA and may have implications for the development of diagnostic and therapeutic approaches targeting lipid metabolism in PA. We believe that the proposed strategy serves as a valuable tool for screening robust, discriminating metabolic features in the field of metabolomics.

POSREG: proteomic signature discovered by simultaneously optimizing its reproducibility and generalizability.

Mass spectrometry-based proteomic technique has become indispensable in current exploration of complex and dynamic biological processes. Instrument development has largely ensured the effective production of proteomic data, which necessitates commensurate advances in statistical framework to discover the optimal proteomic signature. Current framework mainly emphasizes the generalizability of the identified signature in predicting the independent data but neglects the reproducibility among signatures identified from independently repeated trials on different sub-dataset. These problems seriously restricted the wide application of the proteomic technique in molecular biology and other related directions. Thus, it is crucial to enable the generalizable and reproducible discovery of the proteomic signature with the subsequent indication of phenotype association. However, no such tool has been developed and available yet. Herein, an online tool, POSREG, was therefore constructed to identify the optimal signature for a set of proteomic data. It works by (i) identifying the proteomic signature of good reproducibility and aggregating them to ensemble feature ranking by ensemble learning, (ii) assessing the generalizability of ensemble feature ranking to acquire the optimal signature and (iii) indicating the phenotype association of discovered signature. POSREG is unique in its capacity of discovering the proteomic signature by simultaneously optimizing its reproducibility and generalizability. It is now accessible free of charge without any registration or login requirement at https://idrblab.org/posreg/.

RNA-RNA interactions between SARS-CoV-2 and host benefit viral development and evolution during COVID-19 infection.

Some studies reported that genomic RNA of SARS-CoV-2 can absorb a few host miRNAs that regulate immune-related genes and then deprive their function. In this perspective, we conjecture that the absorption of the SARS-CoV-2 genome to host miRNAs is not a coincidence, which may be an indispensable approach leading to viral survival and development in host. In our study, we collected five datasets of miRNAs that were predicted to interact with the genome of SARS-CoV-2. The targets of these miRNAs in the five groups were consistently enriched immune-related pathways and virus-infectious diseases. Interestingly, the five datasets shared no one miRNA but their targets shared 168 genes. The signaling pathway enrichment of 168 shared targets implied an unbalanced immune response that the most of interleukin signaling pathways and none of the interferon signaling pathways were significantly different. Protein-protein interaction (PPI) network using the shared targets showed that PPI pairs, including IL6-IL6R, were related to the process of SARS-CoV-2 infection and pathogenesis. In addition, we found that SARS-CoV-2 absorption to host miRNA could benefit two popular mutant strains for more infectivity and pathogenicity. Conclusively, our results suggest that genomic RNA absorption to host miRNAs may be a vital approach by which SARS-CoV-2 disturbs the host immune system and infects host cells.

Biological activities of drug inactive ingredients.

In a drug formulation (DFM), the major components by mass are not Active Pharmaceutical Ingredient (API) but rather Drug Inactive Ingredients (DIGs). DIGs can reach much higher concentrations than that achieved by API, which raises great concerns about their clinical toxicities. Therefore, the biological activities of DIG on physiologically relevant target are widely demanded by both clinical investigation and pharmaceutical industry. However, such activity data are not available in any existing pharmaceutical knowledge base, and their potentials in predicting the DIG-target interaction have not been evaluated yet. In this study, the comprehensive assessment and analysis on the biological activities of DIGs were therefore conducted. First, the largest number of DIGs and DFMs were systematically curated and confirmed based on all drugs approved by US Food and Drug Administration. Second, comprehensive activities for both DIGs and DFMs were provided for the first time to pharmaceutical community. Third, the biological targets of each DIG and formulation were fully referenced to available databases that described their pharmaceutical/biological characteristics. Finally, a variety of popular artificial intelligence techniques were used to assess the predictive potential of DIGs' activity data, which was the first evaluation on the possibility to predict DIG's activity. As the activities of DIGs are critical for current pharmaceutical studies, this work is expected to have significant implications for the future practice of drug discovery and precision medicine.

RNAenrich: a web server for non-coding RNA enrichment.

MOTIVATION: With the rapid advances of RNA sequencing and microarray technologies in non-coding RNA (ncRNA) research, functional tools that perform enrichment analysis for ncRNAs are needed. On the one hand, because of the rapidly growing interest in circRNAs, snoRNAs, and piRNAs, it is essential to develop tools for enrichment analysis for these newly emerged ncRNAs. On the other hand, due to the key role of ncRNAs' interacting target in the determination of their function, the interactions between ncRNA and its corresponding target should be fully considered in functional enrichment. Based on the ncRNA-mRNA/protein-function strategy, some tools have been developed to functionally analyze a single type of ncRNA (the majority focuses on miRNA); in addition, some tools adopt predicted target data and lead to only low-confidence results. RESULTS: Herein, an online tool named RNAenrich was developed to enable the comprehensive and accurate enrichment analysis of ncRNAs. It is unique in (i) realizing the enrichment analysis for various RNA types in humans and mice, such as miRNA, lncRNA, circRNA, snoRNA, piRNA, and mRNA; (ii) extending the analysis by introducing millions of experimentally validated data of RNA-target interactions as a built-in database; and (iii) providing a comprehensive interacting network among various ncRNAs and targets to facilitate the mechanistic study of ncRNA function. Importantly, RNAenrich led to a more comprehensive and accurate enrichment analysis in a COVID-19-related miRNA case, which was largely attributed to its coverage of comprehensive ncRNA-target interactions. AVAILABILITY AND IMPLEMENTATION: RNAenrich is now freely accessible at https://idrblab.org/rnaenr/.

MOINER: A Novel Multiomics Early Integration Framework for Biomedical Classification and Biomarker Discovery.

In the context of precision medicine, multiomics data integration provides a comprehensive understanding of underlying biological processes and is critical for disease diagnosis and biomarker discovery. One commonly used integration method is early integration through concatenation of multiple dimensionally reduced omics matrices due to its simplicity and ease of implementation. However, this approach is seriously limited by information loss and lack of latent feature interaction. Herein, a novel multiomics early integration framework (MOINER) based on information enhancement and image representation learning is thus presented to address the challenges. MOINER employs the self-attention mechanism to capture the intrinsic correlations of omics-features, which make it significantly outperform the existing state-of-the-art methods for multiomics data integration. Moreover, visualizing the attention embedding and identifying potential biomarkers offer interpretable insights into the prediction results. All source codes and model for MOINER are freely available https://github.com/idrblab/MOINER.

VARIDT 2.0: structural variability of drug transporter.

The structural variability data of drug transporter (DT) are key for research on precision medicine and rational drug use. However, these valuable data are not sufficiently covered by the available databases. In this study, a major update of VARIDT (a database previously constructed to provide DTs' variability data) was thus described. First, the experimentally resolved structures of all DTs reported in the original VARIDT were discovered from PubMed and Protein Data Bank. Second, the structural variability data of each DT were collected by literature review, which included: (a) mutation-induced spatial variations in folded state, (b) difference among DT structures of human and model organisms, (c) outward/inward-facing DT conformations and (d) xenobiotics-driven alterations in the 3D complexes. Third, for those DTs without experimentally resolved structural variabilities, homology modeling was further applied as well-established protocol to enrich such valuable data. As a result, 145 mutation-induced spatial variations of 42 DTs, 1622 inter-species structures originating from 292 DTs, 118 outward/inward-facing conformations belonging to 59 DTs, and 822 xenobiotics-regulated structures in complex with 57 DTs were updated to VARIDT (https://idrblab.org/varidt/ and http://varidt.idrblab.net/). All in all, the newly collected structural variabilities will be indispensable for explaining drug sensitivity/selectivity, bridging preclinical research with clinical trial, revealing the mechanism underlying drug-drug interaction, and so on.

Multifunctional Nanoassembly for MRI-Trackable Dendritic Cell Dependent and Independent Photoimmunotherapy.

Immunotherapy has emerged as a triumph in the treatment of malignant cancers. Nevertheless, current immunotherapeutics are insufficient in addressing tumors characterized by tumor cells' inadequate antigenicity and the tumor microenvironment's low immunogenicity (TME). Herein, we developed a novel multifunctional nanoassembly termed FMMC through the self-assembly of indoleamine 2,3-dioxygenase 1 (IDO-1) inhibitor 1-methyl-tryptophan prodrug (FM), Ce6, and ionic manganese (Mn2+) via noncovalent interactions. The laser-ignited FMMC treatment could induce effective immunogenic cell death and activate the STING/MHC-I signaling pathway, thus deeply sculpting the tumor-intrinsic antigenicity to achieve dendritic cell (DC)-dependent and -independent T cell responses against tumors. Meanwhile, by inhibiting IDO-1, FMMC could lead to immunosuppressive TME reversion to an immunoactivated one. FMMC-based phototherapy led to the up-regulation of programmed death-ligand 1 (PD-L1), enhancing the sensitivity of tumors to anti-PD-1 therapy. Furthermore, the incorporation of Mn2+ into FMMC resulted in an augmented longitudinal relaxivity and enhanced the MRI for monitoring the growth of primary tumors and lung metastases. Collectively, the superior reprogramming performance of immunosuppressive tumor cells and TME, combined with excellent anticancer efficacy and MRI capability, made FMMC a promising immune nanosculptor for cancer theranostics.

Apoptotic Vesicles of MSCs: The Natural Therapeutic Agents and Bio-Vehicles for Targeting Drug Delivery.

Mesenchymal stem cell (MSC)-based therapies are increasingly recognized as promising cellular therapeutics and show the ability to treat various diseases. However, the underlying mechanism is not fully elucidated. Some recent studies have shown an unexpected result whereby MSCs undergo rapid apoptosis following administration but still exert therapeutic effects in some disease treatments. Such a therapeutic mechanism is believed to associate with the released apoptotic vesicles from apoptotic MSCs (MSC-ApoVs). This finding inspires a novel therapeutic strategy for using MSC-ApoVs for disease treatment. The present review aims to summarize the biogenesis, physiological functions, therapeutic potentials, and related mechanisms of apoptotic vesicles in MSC-based therapy. In addition, the potential applications of MSC-ApoVs as natural therapeutic agents and natural drug delivery vehicles are proposed and highlighted. The present review is hoped to provide a general understanding of MSC-ApoVs in disease treatment and inspire potential applications in targeted drug delivery.

An Enzymatic Antibiotic Adjuvant Modulates the Infectious Microenvironment to Overcome Antimicrobial Resistance of Pathogens.

The emergence and evolution of antimicrobial resistance (AMR) pose a significant challenge to the current arsenal to fight infection. Antibiotic adjuvants represent an appealing tactic for tackling the AMR of pathogens, however, their practical applications are greatly constrained by the harsh infectious microenvironment. Herein, it is found that silver nanoclusters (Ag NCs) can possess tunable enzymatic activities to modulate infectious microenvironments. Based on this finding, an enzymatic nanoadjuvant (EnzNA) self-assembled from Ag NCs, which is inert under neutral physiological conditions but can readily disassemble into isolated Ag NCs exhibiting biofilm destructive oxidase-mimetic activity in the acidic biofilm microenvironment, is developed. Once internalized into the neutral cytoplasm of bacteria, Ag NCs switch to reveal the thiol oxidase-mimetic activity to suppress ribosomal biogenesis for AMR reversal and evolution inhibition of pathogens. Consequently, EnzNAs revitalize various existing antibiotics against methicillin-resistant Staphylococcus aureus, and potentiate the antibiotic efficacy against biofilm-mediated skin infection and lethal lung infection in mice. These findings highlight the capability of enzyme-mimetic nanomaterials to modulate the infectious microenvironment and potentiate antibiotics, providing a paradigm shift for anti-infection therapy.

Advanced Therapies for Traumatic Central Nervous System Injury: Delivery Strategy Reinforced Efficient Microglial Manipulation.

Traumatic central nervous system (CNS) injuries, including spinal cord injury and traumatic brain injury, are challenging enemies of human health. Microglia, the main component of the innate immune system in CNS, can be activated postinjury and are key participants in the pathological procedure and development of CNS trauma. Activated microglia can be typically classified into pro-inflammatory (M1) and anti-inflammatory (M2) phenotypes. Reducing M1 polarization while promoting M2 polarization is thought to be promising for CNS injury treatment. However, obstacles such as the low permeability of the blood-brain barrier and short retention time in circulation limit the therapeutic outcomes of administrated drugs, and rational delivery strategies are necessary for efficient microglial regulation. To this end, proper administration methods and delivery systems like nano/microcarriers and scaffolds are investigated to augment the therapeutic effects of drugs, while some of these delivery systems have self-efficacies in microglial manipulation. Besides, systems based on cell and cell-derived exosomes also show impressive effects, and some underlying targeting mechanisms of these delivery systems have been discovered. In this review, we introduce the roles of microglia play in traumatic CNS injuries, discuss the potential targets for the polarization regulation of microglial phenotype, and summarize recent studies and clinical trials about delivery strategies on enhancing the effect of microglial regulation and therapeutic outcome, as well as targeting mechanisms post CNS trauma.

Recent Advances of Using Exosomes as Diagnostic Markers and Targeting Carriers for Cardiovascular Disease.

Cardiovascular diseases (CVDs) are the leading cause of human death worldwide. Exosomes act as endogenous biological vectors; they possess advantages of low immunogenicity and low safety risks, also providing tissue selectivity, including the inherent targeting the to heart. Therefore, exosomes not only have been applied as biomarkers for diagnosis and therapeutic outcome confirmation but also showed potential as drug carriers for cardiovascular targeting delivery. This review aims to summarize the progress and challenges of exosomes as novel biomarkers, especially many novel exosomal noncoding RNAs (ncRNAs), and also provides an overview of the improved targeting functions of exosomes by unique engineered approaches, the latest developed administration methods, and the therapeutic effects of exosomes used as the biocarriers of medications for cardiovascular disease treatment. Also, the possible therapeutic mechanisms and the potentials for transferring exosomes to the clinic for CVD treatment are discussed. The advances, in vivo and in vitro applications, modifications, mechanisms, and challenges summarized in this review will provide a general understanding of this promising strategy for CVD treatment.

INTEDE: interactome of drug-metabolizing enzymes.

Drug-metabolizing enzymes (DMEs) are critical determinant of drug safety and efficacy, and the interactome of DMEs has attracted extensive attention. There are 3 major interaction types in an interactome: microbiome-DME interaction (MICBIO), xenobiotics-DME interaction (XEOTIC) and host protein-DME interaction (HOSPPI). The interaction data of each type are essential for drug metabolism, and the collective consideration of multiple types has implication for the future practice of precision medicine. However, no database was designed to systematically provide the data of all types of DME interactions. Here, a database of the Interactome of Drug-Metabolizing Enzymes (INTEDE) was therefore constructed to offer these interaction data. First, 1047 unique DMEs (448 host and 599 microbial) were confirmed, for the first time, using their metabolizing drugs. Second, for these newly confirmed DMEs, all types of their interactions (3359 MICBIOs between 225 microbial species and 185 DMEs; 47 778 XEOTICs between 4150 xenobiotics and 501 DMEs; 7849 HOSPPIs between 565 human proteins and 566 DMEs) were comprehensively collected and then provided, which enabled the crosstalk analysis among multiple types. Because of the huge amount of accumulated data, the INTEDE made it possible to generalize key features for revealing disease etiology and optimizing clinical treatment. INTEDE is freely accessible at: https://idrblab.org/intede/.

An antioxidative sophora exosome-encapsulated hydrogel promotes spinal cord repair by regulating oxidative stress microenvironment.

Spinal cord injury (SCI) is a severe traumatic disease because of its complications and multi-organ dysfunction. After the injury, the disruption of microenvironment homeostasis in the lesion demolishes the surrounding healthy tissues via various pathways. The microenvironment regulation is beneficial for neural and functional recovery. Sustained release, cellular uptake, and long-term retention of therapeutic molecules at the impaired sites are important for continuous microenvironment improvement. In our study, a local-implantation system was constructed for SCI treatment by encapsulating exosomes derived from Flos Sophorae Immaturus (so-exos) in a polydopamine-modified hydrogel (pDA-Gel). So-exos are used as nanoscale natural vehicles of rutin, a flavonoid phytochemical that is effective in microenvironment improvement and nerve regeneration. Our study showed that the pDA-Gel-encapsulated so-exos allowed rapid improvement of the impaired motor function and alleviation of urination dysfunction by modulating the spinal inflammatory and oxidative conditions, thus illustrating a potential SCI treatment through a combinational delivery of so-exos.

Discovery of (2-phenylthiazol-4-yl)urea derivatives that induce neuronal differentiation from mesenchymal stem cells.

The success of stem cells therapy to treat neurodegenerative diseases is currently restricted by the lack of suitable stem cells. Mesenchymal stem cells (MSCs) have demonstrated several advantages as seed-cells for the stem cells therapy. In particular, the low immunogenicity and multiple lineages differentiation capability enables the possibility of using MSCs to treat neurodegenerative diseases. However, a more potent neuronal differentiation capacity of MSCs is required during a success treatment against neurodegenerative diseases. Bioengineering using small molecules to boost the neuronal differentiation of MSCs has been proposed as a promising strategy. Herein, we developed a new series of (2-phenylthiazol-4-yl)urea derivatives and one of them, 18g were observed to successfully promote neuronal differentiation of MSCs after culturing MSCs with 18g for 4 days. In addition, neither significant cytotoxicity nor cell cycle altering were found after the incubation. Interestingly, the osteogenic differentiation potential of MSCs was not affected after 18g treatment. The present study provides a promising small molecule to boost the innate neuronal differentiation capacity of MSCs with no serious detrimental effects.

Engineering of small-molecule lipidic prodrugs as novel nanomedicines for enhanced drug delivery.

A widely established prodrug strategy can effectively optimize the unappealing properties of therapeutic agents in cancer treatment. Among them, lipidic prodrugs extremely uplift the physicochemical properties, site-specificity, and antitumor activities of therapeutic agents while reducing systemic toxicity. Although great perspectives have been summarized in the progress of prodrug-based nanoplatforms, no attention has been paid to emphasizing the rational design of small-molecule lipidic prodrugs (SLPs). With the aim of outlining the prospect of the SLPs approach, the review will first provide an overview of conjugation strategies that are amenable to SLPs fabrication. Then, the rational design of SLPs in response to the physiological barriers of chemotherapeutic agents is highlighted. Finally, their biomedical applications are also emphasized with special functions, followed by a brief introduction of the promising opportunities and potential challenges of SLPs-based drug delivery systems (DDSs) in clinical application.

Upregulation of hsa_circ_0000977 participates in esophageal squamous cancer progression by sponging miR-874-3p.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of the most common clinical malignancies of the digestive system, characterized by high mortality but not evident early symptoms. Molecular markers for diagnostic and outcome prediction are urgently needed. Circular RNAs might play essential roles in the progression of ESCC. METHODS: Hsa_circ_0000977 was identified using circRNA microarrays and qRT-PCR. The diagnostic value of hsa_circ_0000977 was calculated. We also examined in vitro cell functions in ECA109 and TE12 ESCC cells to determine the effect of hsa_circ_0000977. A dual-luciferase reporter vector validated the binding of hsa_circ_0000977 to miR-874-3p. RESULTS: The top 10 significantly upregulated circRNAs from microarray assays were hsa_circ_0000977, hsa_circ_0006220, hsa_circ_0043278, hsa_circ_0000691, hsa_circ_0000288, hsa_circ_0000367, hsa_circ_0021647, hsa_circ_0006440, hsa_circRNA_405571 and hsa_circRNA_100790, while the top 10 significantly downregulated circRNAs were hsa_circ_0008389, hsa_circ_0089763, hsa_circ_0089762, hsa_circ_0000102, hsa_circ_0001714, hsa_circ_0089761, hsa_circ_0007326, hsa_circ_0001549, hsa_circ_0005133 and hsa_circRNA_405965. Hsa_circ_0000977 was significantly upregulated in ESCC (p < 0.01) and had diagnostic value in ESCC. The hsa_circ_0000977 expression level was related to the pT stage and numbers of lymph nodes in ESCC patients. Elevated hsa_circ_0000977 promoted cell proliferation, migration and inhibited apoptosis in ESCC cells. Hsa_circ_0000977 might function as a micro-RNA sponge to competitively bind miR-874-3p. CONCLUSION: Disordered hsa_circ_0000977 expression can promote carcinogenesis in ESCC and might serve as a diagnostic biomarker to evaluate the occurrence and development of esophageal cancer.

Glutathione-Responsive Magnetic Nanoparticles for Highly Sensitive Diagnosis of Liver Metastases.

Liver metastasis (LM) occurs in various cancers, and its early and accurate diagnosis is of great importance. However, the detection of small LMs is still a great challenge because of the subtle differences between normal liver tissue and small metastases. Herein, we prepare glutathione (GSH)-responsive hyaluronic acid-coated iron oxide nanoparticles (HIONPs) for highly sensitive diagnosis of LMs through a facile one-pot method. HIONPs greatly enhance the signal of MRI in tumor metastases as T1 contrast agent (CA), whereas they substantially decrease the signal of liver as T2 CA as they aggregate into clusters upon the high GSH in liver. Consequently, MRI contrasted by HIONPs clearly distinguishes metastatic tumors (bright) from surrounding liver tissues (dark). HIONPs with superior LM contrasting capability and facile synthesis are very promising for clinical translation and indicate a new strategy to develop an ultrasensitive MRI CA for LM diagnosis that exploits high GSH level in the liver.