Selenium nanoparticles decorated with polysaccharides from Sargassum fusiforme protects against 6-OHDA-induced neurotoxicity in PC12 cells and rat model of Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder and identifying disease-causing pathways and drugs that target them has remained challenging. Herein, selenium nanoparticles decorated with polysaccharides from Sargassum fusiforme (SFPS-SeNPs) were investigated on 6-OHDA-induced neurotoxicity in PC12 cells and rats. 6-OHDA can significantly increase neurotoxicity, oxidative stress and decrease the activity of superoxide dismutase (SOD) and glutathione peroxidase (GPx) both in vitro and vivo. In vitro, treatment with SFPS-SeNPs can significantly decrease 6-OHDA cytotoxicity, reactive oxygen species (ROS) production or malondialdehyde (MDA) levels, and cell apoptosis, significantly increased the activity of SOD and GPx. In vivo, 6-OHDA exposure could also decrease the expression of Nrf2 and OH-1, while treatment with SFPS-SeNPs (1 mg Se/kg) increased. SFPS-SeNPs can protect neurons from 6-OHDA-induced neurotoxicity by regulating apoptosis and Nrf2/ARE pathway. The present study demonstrated that SFPS-SeNPs is a good candidate for developing a new drug against neurodegenerative diseases such as PD.

Novel Multitarget ACE Inhibitory Peptides from Bovine Colostrum Immunoglobulin G: Cellular Transport, Efficacy in Regulating Endothelial Dysfunction, and Network Pharmacology Studies.

In this study, we used traditional laboratory methods, bioinformatics, and cellular models to screen novel ACE inhibitory (ACEI) peptides with strong ACEI activity, moderate absorption rates, and multiple targets from bovine colostrum immunoglobulin G (IgG). The purified fraction of the compound proteinase hydrolysate of IgG showed good ACEI activity. After nano-UPLC-MS/MS identification and in silico analysis, eight peptides were synthesized and verified. Among them, SFYPDY, TSFYPDY, FSWF, WYQQVPGSGL, and GVHTFP were identified as ACEI peptides, as they exhibited strong ACEI activity (with IC50 values of 104.7, 80.0, 121.2, 39.8, and 86.3 µM, respectively). They displayed good stability in an in vitro simulated gastrointestinal digestion assay. In a Caco-2 monolayer model, SFYPDY, FSWF, and WYQQVPGSGL exhibited better absorption rates and lower IC50 values than the other peptides and were thereby identified as novel ACEI peptides. Subsequently, in a H2O2-induced endothelial dysfunction (ED) model based on HUVECs, SFYPDY, FSWF, and WYQQVPGSGL regulated ED by reducing apoptosis and ROS accumulation while upregulating NOS3 mRNA expression. Network pharmacology analysis and RT-qPCR confirmed that they regulated multiple targets. Overall, our results suggest that SFYPDY, FSWF, and WYQQVPGSGL can serve as novel multitarget ACEI peptides.

A Bayesian approach to estimate MHC-peptide binding threshold.

Major histocompatibility complex (MHC)-peptide binding is a critical step in enabling a peptide to serve as an antigen for T-cell recognition. Accurate prediction of this binding can facilitate various applications in immunotherapy. While many existing methods offer good predictive power for the binding affinity of a peptide to a specific MHC, few models attempt to infer the binding threshold that distinguishes binding sequences. These models often rely on experience-based ad hoc criteria, such as 500 or 1000nM. However, different MHCs may have different binding thresholds. As such, there is a need for an automatic, data-driven method to determine an accurate binding threshold. In this study, we proposed a Bayesian model that jointly infers core locations (binding sites), the binding affinity and the binding threshold. Our model provided the posterior distribution of the binding threshold, enabling accurate determination of an appropriate threshold for each MHC. To evaluate the performance of our method under different scenarios, we conducted simulation studies with varying dominant levels of motif distributions and proportions of random sequences. These simulation studies showed desirable estimation accuracy and robustness of our model. Additionally, when applied to real data, our results outperformed commonly used thresholds.

IRF3-mediated lncRNA FTX promotes cell proliferation, migration, invasion and suppresses cell apoptosis in oral squamous cell carcinoma by up-regulating FCHSD2 via miR-708-5p.

In recent years, researches into the molecular mechanisms of oral squamous cell carcinoma (OSCC) have improved greatly but effective targeted therapies remain elusive. More and more evidence has referred to long non-coding RNAs (lncRNAs) as modulators of carcinomas development. As a novel lncRNA, five prime to Xist (FTX), as reported before, is overexpressed in a variety of cancers. In the present study, we sought to unclose the impacts of FTX and its molecular mechanism in OSCC. Related gene expression levels were disclosed by qRT-PCR and we found that FTX was notably overexpressed in OSCC. The biological functions of FTX in OSCC were measured by functional assays. The results displayed that depletion of FTX hinderedOSCC cell migratory, invasive and proliferative abilities, but promoted cell apoptotic levels. The relationship among interferon regulatory factor 3 (IRF3), FTX, microRNA-708-5p (miR-708-5p) and FCH and double SH3 domains 2 (FCHSD2) was determined by several mechanism assays, from which we discovered that FTX activated by IRF3 regulated FCHSD2 expression by sponging miR-708-5p. Rescue experiments showed that FTX motivated OSCC development by modulating miR-708-5p/FCHSD2 axis. In summary, FTX was an oncogene in OSCC and might provide new insights into OSCC treatment.

Exhaustive Cross-Linking Search with Protein Feedback.

Improving the sensitivity of protein-protein interaction detection and protein structure probing is a principal challenge in cross-linking mass spectrometry (XL-MS) data analysis. In this paper, we propose an exhaustive cross-linking search method with protein feedback (ECL-PF) for cleavable XL-MS data analysis. ECL-PF adopts an optimized α/ß mass detection scheme and establishes protein-peptide association during the identification of cross-linked peptides. Existing major scoring functions can all benefit from the ECL-PF workflow to a great extent. In comparisons using synthetic data sets and hybrid simulated data sets, ECL-PF achieved 3-fold higher sensitivity over standard techniques. In experiments using real data sets, it also identified 65.6% more cross-link spectrum matches and 48.7% more unique cross-links.

A Bayesian model for identifying cancer subtypes from paired methylation profiles.

Aberrant DNA methylation is the most common molecular lesion that is crucial for the occurrence and development of cancer, but has thus far been underappreciated as a clinical tool for cancer classification, diagnosis or as a guide for therapeutic decisions. Partly, this has been due to a lack of proven algorithms that can use methylation data to stratify patients into clinically relevant risk groups and subtypes that are of prognostic importance. Here, we proposed a novel Bayesian model to capture the methylation signatures of different subtypes from paired normal and tumor methylation array data. Application of our model to synthetic and empirical data showed high clustering accuracy, and was able to identify the possible epigenetic cause of a cancer subtype.

Potential anticancer activities of securinine and its molecular targets.

BACKGROUND: Securinine is an alkaloid identified from the roots and leaves of the shrub Flueggea suffruticosa (Pall.) Baill. The molecular structure of securinine consists of four rings, including three chiral centers. It has been suggested that securinine can be chemically synthesized from tyrosine and lysine. Securinine has long been used to treat central nervous system diseases. In recent years, more and more evidence shows that securinine also has anticancer activity, which has not been systematically discussed and analyzed. PURPOSE: This study aims to propose an overall framework to describe the molecular targets of securinine in different signal pathways, and discuss the current status and prospects of each pathway, so as to provide a theoretical basis for the development securinine as an effective anticancer drug. METHODS: The research databases on the anticancer activity of securinine from PubMed, Scopus, Web of Science and ScienceDirect to 2021 were systematically searched. This paper follows the Preferred Reporting Items and Meta-Analysis guidelines. RESULTS: Securinine has the ability to kill a variety of human cancer cells, including, leukemia as well as prostate, cervical, breast, lung, and colon cancer cells. It can regulate the signal pathways of phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin, Wnt and Janus kinase-signal transducer and activator of transcription, promote cancer cell apoptosis and autophagy, and inhibit cancer cell metastasis. Securinine also has the activity of inducing leukemia cell differentiation. CONCLUSION: Although there has been some experimental evidence indicating the anticancer effect of securinine and its possible pharmacology, in order to design more effective anticancer drugs, it is necessary to study the synergy of intracellular signaling pathways. More in vivo experiments and even clinical studies are needed, and the synergy between securinine and other drugs is also worth studying.

Sunitinib Reduced the Migration of Ectopic Endometrial Cells via p-VEGFR-PI3K-AKT-YBX1-Snail Signaling Pathway.

Endometriosis (EMs) is one of the most common gynecological diseases, lacking effective treatment. EMs are currently being treated with small molecule targeted therapy, which has resulted in a significant reduction in patient suffering. Our previous studies have shown that sunitinib plays an obvious role in migration. Consequently, the purpose of this study is to explore the molecular mechanism by which sunitinib suppressed the ectopic endometrial migration. The ectopic endometrial cells from patients were divided into two groups: the control group and the sunitinib group. Co-IP and protein spectrum assay were employed to filtrate differential proteins between two groups, and then, our study discovered a signaling pathway, p-VEGFR-PI3K-AKT-YBX1-Snail, in the cell of EMs. To confirm this signaling pathway, VEGF165 was added to the sunitinib group to upregulate the expression of VEGFR. Next, the expression of p-VEGFR, PI3K, AKT, YBX1, and snail was measured in the control group and sunitinib group (compared with the control group: p-VEGFR, PI3K, AKT, YBX1, and snail, ∗∗∗∗P < 0.0001) and the VEGFR+sunitinib group (compared with the sunitinib group: p-VEGFR, PI3K, AKT, and snail, ∗∗∗∗P < 0.0001; YBX1, ∗∗∗P < 0.001); finally, the outcome was as expected. In addition to in vitro experiments, we also conducted in vivo experiments in mice. In the EMs mouse model, we found sunitinib reduced the number of heterotopic foci (t = 11.16, ∗∗∗∗P < 0.0001) and inhibited the expression of p-VEGFR, YBX1, and snail by immunofluorescence. To sum up, sunitinib exactly reduced the migration of ectopic endometrial cells with the involvement of the p-VEGFR-PI3K-AKT-YBX1-Snail signaling pathway in both in vitro and in vivo experiments. This study suggests that sunitinib presents a potential targeted drug for EMs therapy.

miR-2682-3p antagonizes its host lncRNA-MIR137HG by interacting with the same target FUS to regulate the progression of gastric cancer.

BACKGROUND: The mechanism of long non-coding RNA MIR137HG in human gastric cancer (GC) is currently unknown. In the present study, we aimed to explore the function and mechanism of MIR137HG in gastric cancer. METHODS: The expression of lncRNA-MIR137HG in 69 gastric cancer samples and their paired surgical margin (SM) tissue samples were tested by QRT-PCR. UCSC was used to find the gene location relationship among MIR137HG and its embedded miRNAs. TargetScan was used to predict the targets of miR-2682-3p. Starbase was used to predict the candidate proteins that interacted with MIR137HG. Western blot, co-focus, and RIP assay were used to verify the direct interaction between MIR137HG and FUS (fused in sarcoma/translocated in liposarcoma, FUS/TLS), while dual-luciferase reporter assay was used to confirm the interaction between miR-2682-3p and FUS. Cell migration assays, colony formation, and xenografts assay were used to investigate the function of MIR137HG and miR-2682-3p to tumor growth and metastasis. Western blot assay was used to explore the downstream candidate protein of FUS. RESULTS: Data showed that MIR137HG expressed significantly higher in GC than in SM. MIR137HG promoted colony formation and migration in vitro and promoted tumor formation and metastasis in vivo. MIR137HG is distributed in both the nucleus and cytoplasm. It was co-located with FUS and could directly interact with FUS, which might interact with other proteins, such as MET(MET-proto-oncogene, receptor tyrosine kinase), RHOC(ras homolog family member), and CTNNB1(catenin beta1). These proteins may involve different signaling pathways to regulate gastric cancer progression. By contrast, the embedded miR-2682-3p could antagonize the series functions of its host lncRNA-MIR137HG by targeting FUS. CONCLUSIONS: lncRNA-MIR137HG promoted growth and metastasis in gastric cancer by interacting with FUS, while miR-2682-3p could inhibit the function of MIR137HG via the same target FUS.

Detection of Structural Variations and Fusion Genes in Breast Cancer Samples Using Third-Generation Sequencing.

Background: Structural variations (SVs) are common genetic alterations in the human genome that could cause different phenotypes and diseases, including cancer. However, the detection of structural variations using the second-generation sequencing was limited by its short read length, which restrained our understanding of structural variations. Methods: In this study, we developed a 28-gene panel for long-read sequencing and employed it to Oxford Nanopore Technologies and Pacific Biosciences platforms. We analyzed structural variations in the 28 breast cancer-related genes through long-read genomic and transcriptomic sequencing of tumor, para-tumor, and blood samples in 19 breast cancer patients. Results: Our results showed that some somatic SVs were recurring among the selected genes, though the majority of them occurred in the non-exonic region. We found evidence supporting the existence of hotspot regions for SVs, which extended our previous understanding that they exist only for single nucleotide variations. Conclusion: In conclusion, we employed long-read genomic and transcriptomic sequencing to identify SVs from breast cancer patients and proved that this approach holds great potential in clinical application.

Synthesis and evaluation of Grateloupia Livida polysaccharides-functionalized selenium nanoparticles.

Grateloupia Livida polysaccharides-functionalized selenium nanoparticles (GLP-SeNPs) have been successfully prepared in a simple redox system of sodium selenite and ascorbic acid. The size, morphology, structure, stability and thermal behavior were analyzed by various characterization methods. These results showed that, GLP-SeNPs (particle size of 115.54 nm) prepared in optimal synthesis conditions (temperature of 45 °C, reaction time of 3 h, GLP concentration of 1.0 mg/mL and ascorbic acid concentration of 0.04 M) obtained by orthogonal experiments were uniform spherical and could be stable for 30 days at 4 °C. GLP-SeNPs exhibited significant scavenging ability on DPPH, ABTS, hydroxyl radical and superoxide anion radical when compared to GLP and Na2SeO3. GLP-SeNPs showed selective cytotoxicity toward various human cancer cells, but not normal cells. Besides, GLP-SeNPs exhibited low oral acute toxicity. Taken together, GLP-SeNPs might be used as potential diet nutritional supplement or anticancer agent.

Asperuloside ameliorates lipopolysaccharide-induced primary human periodontal ligament cell injury by decreasing TLR4 expression and NF-κB activation.

OBJECTIVE: The mechanism underlying lipopolysaccharide (LPS)-induced primary human periodontal ligament (PDLC) cell injury is unclear. In this study, we focused on the therapeutic function of asperuloside (ASP) on LPS-induced cell injury. DESIGN: The study enrolled 41 participants, including 18 healthy controls and 23 CP patients. Western blotting was used to measure the expression of Toll-like receptor 4 (TLR4), phosphorylated p65 (p-p65) and cyclin D1. Enzyme-linked immunosorbent assays (ELISAs) were utilized to evaluate the protein levels of proinflammatory factors interleukin (IL)-1ß, IL-6, IL-8 and tumor necrosis factor alpha (TNF-α). MTT assays and 5-ethynyl-2'-deoxyuridine (EdU) staining were performed to investigate cell proliferation. Immunohistochemistry was used to detect TLR4 and p65 expression in gingival tissues. RESULTS AND CONCLUSIONS: Asperuloside ameliorates lipopolysaccharide-induced PDLC cell injury by decreasing TLR4 expression and NF-κB activation, while this protective effect of ASP was reversed by TLR4 overexpression.

Applications of genetic-epigenetic tissue mapping for plasma DNA in prenatal testing, transplantation and oncology.

We developed genetic-epigenetic tissue mapping (GETMap) to determine the tissue composition of plasma DNA carrying genetic variants not present in the constitutional genome through comparing their methylation profiles with relevant tissues. We validated this approach by showing that, in pregnant women, circulating DNA carrying fetal-specific alleles was entirely placenta-derived. In lung transplant recipients, we showed that, at 72 hr after transplantation, the lung contributed only a median of 17% to the plasma DNA carrying donor-specific alleles, and hematopoietic cells contributed a median of 78%. In hepatocellular cancer patients, the liver was identified as the predominant source of plasma DNA carrying tumor-specific mutations. In a pregnant woman with lymphoma, plasma DNA molecules carrying cancer mutations and fetal-specific alleles were accurately shown to be derived from the lymphocytes and placenta, respectively. Analysis of tissue origin for plasma DNA carrying genetic variants is potentially useful for noninvasive prenatal testing, transplantation monitoring, and cancer screening.

Preparation and antioxidant activity of selenium nanoparticles decorated by polysaccharides from Sargassum fusiforme.

In this study, the response surface method was employed to optimize the extraction conditions of the ultrasonic-assisted extraction of Sargassum fusiforme polysaccharides (SFPS). The effects of four independent variables (hot water extraction time, ultrasonic time, ultrasonic power, and material-to-liquid ratio) on the extraction rate of SFPS were tested. In addition, the SFPS functionalized nanoselenium (SFPS-SeNPs) was prepared by chemical reduction method, whose characterization and in vitro antioxidant activity were investigated. The results showed that the yield of the crude SFPS was 25.8% at the optimal conditions of material-to-liquid ratio 1:50 (w/v), ultrasonic power 200 W, ultrasonic time 15 min, and water bath time 130 min. A series of characterization experiments showed that the SFPS-SeNPs performed higher dispersion and stability than naked SeNPs. Furthermore, the in vitro antioxidant activity assay indicated that SFPS functioned as a modifier improved the free radical scavenging activity of SeNPs significantly. In conclusion, this study provided a method to extract SFPS as a carrier for SeNPs, and SFPS-SeNPs could not only improve the stability of SeNPs, but also exerted the biological activities of SFPS. PRACTICAL APPLICATION: This research provided new ideas for the application of SFPS and the development of nanoselenium preparation carriers.

Detect differentially methylated regions using non-homogeneous hidden Markov model for bisulfite sequencing data.

DNA methylation plays an important role in many biological processes and diseases. With the rise of the whole genome bisulfite sequencing technique, aberrant methylation patterns can now be detected by comparing paired normal and disease samples at the single nucleotide level. We develop a novel Bayesian method for detecting differentially methylated regions from paired bisulfite sequencing data, and implement it as a R package called BSDMR. Based on a non-homogeneous hidden Markov model, BSDMR provides a better modeling strategy for the spatial correlation between CpG sites and takes into consideration the relationship between methylation signals from normal and disease samples. Simulations show that BSDMR performs well even under low read depth and has a smaller false discovery rates than existing methods. We also apply BSDMR to the colon cancer data from Gene Expression Omnibus. The detected DMRs are well supported by existing biomedical literatures.

Sunitinib induces primary ectopic endometrial cell apoptosis through up-regulation of STAT1 in vitro.

BACKGROUND: Endometriosis (EMS) is a prevalent gynecological condition characterized by the growth of endometrial tissue outside the uterine cavity. This study aimed to clarify the targeted therapeutic effect of sunitinib in an endometriosis in vitro experiment. METHODS: Primary culture of ectopic endometrial cells and normal endometrial cells. Six tumor targeting drugs were selected to screen. MTT was used to determine the IC50, flow cytometry, and DAPI staining of the targeted drugs, in order to determine the apoptosis. The differential proteins after seeding were analyzed by protein spectrum, the correlation between the specific protein and cell apoptosis was determined by small molecule interference, and the expression of each related protein was detected by Western blot. Immunohistochemistry and ELISA were used to detect the expression of p-PDGFR and p-STAT1 in clinical samples, and the correlation between p-STAT1 expression and ectopic focal size was analyzed by SPSS 19. RESULTS: Through the drug screening, it was found that sunitinib has a significant inhibitory effect on ectopic endometrial cells. It was determined that the IC50 of sunitinib on ectopic stromal endometrial cells was 3.32 µM, while the IC50 on normal endometrium was 7.9 µM. Meanwhile, the flow cytometry and DAPI nuclear dye that took out sunitinib had an inhibition effect on the ectopic endometrium at a concentration of 4 µM. Protein spectrum analysis was conducted on ectopic intimal cells after sunitinib treatment, and it was found that STAT1 is specifically expressed in ectopic endometrial cells. In vitro, and through fludarabine interference, it was revealed that sunitinib specifically inhibited the phosphorylation site Tyr751 of PDGFR, while the expression of STAT1, p-STAT1, and caspase-3 was significantly upregulated, and the expression of STAT1 and p-STAT1 was positively correlated with the expression of caspase-3. Finally, the expression of p-PDGFR and p-STAT1 in ectopic foal tissues was both higher than that in normal endometrium, and p-STAT1 expression was positively with ectopic focal size. CONCLUSION: The in vitro experiments revealed that sunitinib could upregulate the expression of STAT1 by inhibiting the phosphorylation site Tyr751 of PDGFR, thereby specifically inducing the apoptosis of the primary heterotopic mesenchymal endometrium.

Discovering Cancer-Related miRNAs from miRNA-Target Interactions by Support Vector Machines.

MicroRNAs (miRNAs) have been shown to be closely related to cancer progression. Traditional methods for discovering cancer-related miRNAs mostly require significant marginal differential expression, but some cancer-related miRNAs may be non-differentially or only weakly differentially expressed. Such miRNAs are called dark matters miRNAs (DM-miRNAs) and are targeted through the Pearson correlation change on miRNA-target interactions (MTIs), but the efficiency of their method heavily relies on restrictive assumptions. In this paper, a novel method was developed to discover DM-miRNAs using support vector machine (SVM) based on not only the miRNA expression data but also the expression of its regulating target. The application of the new method in breast and kidney cancer datasets found, respectively, 9 and 24 potential DM-miRNAs that cannot be detected by previous methods. Eight and 15 of the newly discovered miRNAs have been found to be associated with breast and kidney cancers, respectively, in existing literature. These results indicate that our new method is more effective in discovering cancer-related miRNAs.

A Comprehensive Human Gastric Cancer Organoid Biobank Captures Tumor Subtype Heterogeneity and Enables Therapeutic Screening.

Gastric cancer displays marked molecular heterogeneity with aggressive behavior and treatment resistance. Therefore, good in vitro models that encompass unique subtypes are urgently needed for precision medicine development. Here, we have established a primary gastric cancer organoid (GCO) biobank that comprises normal, dysplastic, cancer, and lymph node metastases (n = 63) from 34 patients, including detailed whole-exome and transcriptome analysis. The cohort encompasses most known molecular subtypes (including EBV, MSI, intestinal/CIN, and diffuse/GS, with CLDN18-ARHGAP6 or CTNND1-ARHGAP26 fusions or RHOA mutations), capturing regional heterogeneity and subclonal architecture, while their morphology, transcriptome, and genomic profiles remain closely similar to in vivo tumors, even after long-term culture. Large-scale drug screening revealed sensitivity to unexpected drugs that were recently approved or in clinical trials, including Napabucasin, Abemaciclib, and the ATR inhibitor VE-822. Overall, this new GCO biobank, with linked genomic data, provides a useful resource for studying both cancer cell biology and precision cancer therapy.

Detect differentially methylated regions using non-homogeneous hidden Markov model for methylation array data.

MOTIVATION: DNA methylation is an important epigenetic mechanism in gene regulation and the detection of differentially methylated regions (DMRs) is enthralling for many disease studies. There are several aspects that we can improve over existing DMR detection methods: (i) methylation statuses of nearby CpG sites are highly correlated, but this fact has seldom been modelled rigorously due to the uneven spacing; (ii) it is practically important to be able to handle both paired and unpaired samples; and (iii) the capability to detect DMRs from a single pair of samples is demanded. RESULTS: We present DMRMark (DMR detection based on non-homogeneous hidden Markov model), a novel Bayesian framework for detecting DMRs from methylation array data. It combines the constrained Gaussian mixture model that incorporates the biological knowledge with the non-homogeneous hidden Markov model that models spatial correlation. Unlike existing methods, our DMR detection is achieved without predefined boundaries or decision windows. Furthermore, our method can detect DMRs from a single pair of samples and can also incorporate unpaired samples. Both simulation studies and real datasets from The Cancer Genome Atlas showed the significant improvement of DMRMark over other methods. AVAILABILITY AND IMPLEMENTATION: DMRMark is freely available as an R package at the CRAN R package repository. CONTACT: xfan@cuhk.edu.hk. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.