Cell Cycle Analysis and Relevance for Single-Cell Gating in Mass Cytometry

MiR-17-5p-engineered sEVs Encapsulated in GelMA Hydrogel Facilitated Diabetic Wound Healing by Targeting PTEN and p21

Delayed wound healing is a major complication of diabetes, and is associated with impaired cellular functions. Current treatments are unsatisfactory. Based on the previous reports on microRNA expression in small extracellular vesicles (sEVs), miR-17-5p-engineered sEVs (sEVs17-OE) and encapsulated them in gelatin methacryloyl (GelMA) hydrogel for diabetic wounds treatment are fabricated. SEVs17-OE are successfully fabricated with a 16-fold increase in miR-17-5p expression. SEVs17-OE inhibited senescence and promoted the proliferation, migration, and tube formation of high glucose-induced human umbilical vein endothelial cells (HG-HUVECs). Additionally, sEVs17-OE also performs a promotive effect on high glucose-induced human dermal fibroblasts (HG-HDFs). Mechanism analysis showed the expressions of p21 and phosphatase and tensin homolog (PTEN), as the target genes of miR-17-5p, are downregulated significantly by sEVs17-OE. Accordingly, the downstream genes and pathways of p21 and PTEN, are activated. Next, sEVs17-OE are loaded in GelMA hydrogel to fabricate a novel bioactive wound dressing and to evaluate their effects on diabetic wound healing. Gel-sEVs17-OE effectively accelerated wound healing by promoting angiogenesis and collagen deposition. The cellular mechanism may be associated with local cell proliferation. Therefore, a novel bioactive wound dressing by loading sEVs17-OE in GelMA hydrogel, offering an option for chronic wound management is successfully fabricated.

Curcumin induces ferroptosis and apoptosis in osteosarcoma cells by regulating Nrf2/GPX4 signaling pathway

Curcumin, an antitumor agent, has been shown to inhibit cell growth and metastasis in osteosarcoma. However, there is no evidence of curcumin and its regulation of cell ferroptosis and nuclear factor E2-related factor 2 (Nrf2)/glutathione peroxidase 4 (GPX4) signaling pathways in osteosarcoma. This study aimed to investigate the effects of curcumin on osteosarcoma both in vitro and in vivo. To explore the effects and mechanisms of curcumin on osteosarcoma, cells (MNNG/HOS and MG-63) and xenograft mice models were established. Cell viability, cell apoptosis rate, cycle distribution, cell migration, cell invasion, reactive oxygen species, malonaldehyde and glutathione abilities, and protein levels were detected by cell counting kit-8, flow cytometry, wound healing, transwell assay, respectively. Nrf2 and GPX4 expressions were detected using an immunofluorescence assay. Nrf2/GPX4-related protein levels were detected using western blotting. The results showed that curcumin effectively decreased cell viability and increased apoptosis rate. Meanwhile, curcumin inhibited tumor volume in the xenograft model, and Nrf2/GPX4-related protein levels were also altered. Interestingly, the effects of curcumin were reversed by liproxstatin-1 (an effective inhibitor of ferroptosis) and bardoxolone-methyl (an effective activator of Nrf2). Our results indicate that curcumin has therapeutic effects on osteosarcoma cells and a xenograft model by regulating the expression of the Nrf2/GPX4 signaling pathway.

To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.

VEGF Expression in Umbilical Cord MSC Depends on the Patient's Health, the Week of Pregnancy in Which the Delivery Took Place, and the Body Weight of the Newborn - Preliminary Report

Introduction

Cells collected from Wharton's jelly are a rich source of mesenchymal stem cells. They can be easily obtained and grown using the adhesive method. They produce many types of proteins, including VEGF. Their role is to participate in angiogenesis, vasodilation, stimulation of cells to migrate, and chemotactic activity. The aim of this study was to evaluate expression of genes from the vascular endothelial growth factor family: VEGFA, VEGFB and VEGFC in MSC and the analysis of dependence of the expression of the studied genes on clinical factors related to the course of pregnancy and childbirth, and health of mother and child.

Material and Methods

The research material was an umbilical cord obtained from 40 patients hospitalized in the Department of Obstetrics and Pathology of Pregnancy of the Independent Public Clinical Hospital No.1 in Lublin. The age of the women was 21-46, all gave birth by cesarean section. Some of the patients suffered from hypertension and hypothyroidism. Material collected from patients immediately after delivery was subjected to enzymatic digestion with type I collagenase. The isolated cells were then cultured in adherent conditions, and then gene expression was assessed using qPCR and the immunophenotype of the cells was assessed cytometrically.

Results

Conducted studies have shown significant differences in expression of VEGF family genes depending on clinical condition of mother and child. Significant differences in VEGF-family gene expression level in umbilical cord MSC collected from women with hypothyroidism, hypertension, time of labor and birth weight of the baby were shown.

Conclusion

Probably due to hypoxia (caused, for example, by hypothyroidism or hypertension), the MSCs found in the umbilical cord may react with an increased expression of VEGF and a compensatory increase in the amount of secreted factor, the aim of which is, i.a., vasodilation and increase of blood supply to the fetus through the umbilical vessels.

Matrine injection inhibits pancreatic cancer growth via modulating carbonic anhydrases- a network pharmacology-based study with in vitro validation

ETHNOPHARMACOLOGICAL RELEVANCE

Matrine injection is a complex mixture of plant bioactive substances extracted from Sophora flavescens Aiton and Smilax glabra Roxb. Since its approval by the Chinese Food and Drug Administration (CFDA) in 1995, Matrine injection has been clinically used as a complementary and alternative treatment for various cancers; however, the underlying mechanism of pancreatic cancer treatment is yet to be elucidated.

AIM OF THE STUDY

The present study explores the potential mechanism of matrine injection on pancreatic cancer through network pharmacology technique and in vitro experimental validation.

MATERIALS AND METHODS

Genes differentially expressed in pancreatic cancer were obtained from the Gene Expression Omnibus (GEO) database (GSE101448). The potential active components of matrine injection were selected following a literature search, and target prediction was performed by the SwissTarget Prediction database. Overlapping genes associated with survival were screened by the Gene Expression Profiling Interactive Analysis (GEPIA) database. In vitro experimental validation was performed with cell counting kit-8 (CCK-8) assay, apoptosis detection, cell cycle analysis, immunoblotting, and co-immunoprecipitation of the identified proteins.

RESULTS

One thousand seven hundred genes differentially expressed among pancreatic tumor and non-tumor tissues were screened out. Sixteen active components and 226 predicted target genes were identified in matrine injection. A total of 25 potential target genes of matrine injection for the treatment of pancreatic cancer were obtained. Among them, the prognostic target genes carbonic anhydrase 9 (CA9) and carbonic anhydrase 12 (CA12) based on the GEPIA database are differently expressed in tumors compared to adjacent normal tissue. In vitro experiments, the results of CCK-8 assay, apoptosis and cell cycle analysis, immunoblotting, and co-immunoprecipitation showed that matrine injection inhibited Capan-1 and Mia paca-2 proliferation, arrested the cell cycle at the S phase, and induced apoptosis through up-regulated CA12 and down-regulated CA9.

CONCLUSIONS

In this study, bioinformatics and network pharmacology were applied to explore the treatment mechanism on pancreatic cancer with matrine injection. This study demonstrated that matrine injection inhibited proliferation, arrested the cell cycle, and induced apoptosis of pancreatic cancer cells. The mechanism may be related to the induction of CA12 over-expression, and CA9 reduced expression. As novel targets for pancreatic cancer treatment, Carbonic anhydrases require further study.

Flow Cytometry and Cell Cycle Analysis: An Overview

Cell cycle analysis is one of the earliest applications in flow cytometry and continues to be highly used to this day. Since the first reported method of Feulgen-DNA staining, cell cycle analysis has continued to grow and mature. With the recent advances in DNA dyes, understanding of additional cell cycle phase markers, and new technologies, cell cycle analysis continues to be a dynamic field within the flow cytometry community. This chapter will give an overview of the current state of cell cycle analysis by flow cytometry.

A flow cytometric journey into cell cycle analysis

Cell cycle involves a series of changes that lead to cell growth and division. Cell cycle analysis is crucial to understand cellular responses to changing environmental conditions. Since its inception, flow cytometry has been particularly useful for cell cycle analysis at single cell level due to its speed and precision. Previously, flow cytometric cell cycle analysis relied solely on the measurement of cellular DNA content. Later, methods were developed for multiparametric analysis. This review explains the journey of flow cytometry to understand different molecular and cellular events underlying cell cycle using various protocols. Recent advances in the field that overcome the shortcomings of traditional flow cytometry and expand its scope for cell cycle studies are also discussed.

Multiplexed single-cell analysis of organoid signaling networks

Organoids are biomimetic tissue models comprising multiple cell types and cell states. Post-translational modification (PTM) signaling networks control cellular phenotypes and are frequently dysregulated in diseases such as cancer. Although signaling networks vary across cell types, there are limited techniques to study cell type-specific PTMs in heterocellular organoids. Here, we present a multiplexed mass cytometry (MC) protocol for single-cell analysis of PTM signaling and cell states in organoids and organoids co-cultured with fibroblasts and leukocytes. We describe how thiol-reactive organoid barcoding in situ (TOBis) enables 35-plex and 126-plex single-cell comparison of organoid cultures and provide a cytometry by time of flight (CyTOF) signaling analysis pipeline (CyGNAL) for computing cell type-specific PTM signaling networks. The TOBis MC protocol takes ~3 d from organoid fixation to data acquisition and can generate single-cell data for >40 antibodies from millions of cells across 126 organoid cultures in a single MC run.

Analyzing high-dimensional cytometry data using FlowSOM

The dimensionality of cytometry data has strongly increased in the last decade, and in many situations the traditional manual downstream analysis becomes insufficient. The field is therefore slowly moving toward more automated approaches, and in this paper we describe the protocol for analyzing high-dimensional cytometry data using FlowSOM, a clustering and visualization algorithm based on a self-organizing map. FlowSOM is used to distinguish cell populations from cytometry data in an unsupervised way and can help to gain deeper insights in fields such as immunology and oncology. Since the original FlowSOM publication (2015), we have validated the tool on a wide variety of datasets, and to write this protocol, we made use of this experience to improve the user-friendliness of the package (e.g., comprehensive functions replacing commonly required scripts). Where the original paper focused mainly on the algorithm description, this protocol offers user guidelines on how to implement the procedure, detailed parameter descriptions and troubleshooting recommendations. The protocol provides clearly annotated R code, and is therefore relevant for all scientists interested in computational high-dimensional analyses without requiring a strong bioinformatics background. We demonstrate the complete workflow, starting from data preparation (such as compensation, transformation and quality control), including detailed discussion of the different FlowSOM parameters and visualization options, and concluding with how the results can be further used to answer biological questions, such as statistical comparison between groups of interest. An average FlowSOM analysis takes 1-3 h to complete, though quality issues can increase this time considerably.

Data processing workflow for large-scale immune monitoring studies by mass cytometry

Mass cytometry is a powerful tool for deep immune monitoring studies. To ensure maximal data quality, a careful experimental and analytical design is required. However even in well-controlled experiments variability caused by either operator or instrument can introduce artifacts that need to be corrected or removed from the data. Here we present a data processing pipeline which ensures the minimization of experimental artifacts and batch effects, while improving data quality. Data preprocessing and quality controls are carried out using an R pipeline and packages like CATALYST for bead-normalization and debarcoding, flowAI and flowCut for signal anomaly cleaning, AOF for files quality control, flowClean and flowDensity for gating, CytoNorm for batch normalization and FlowSOM and UMAP for data exploration. As proper experimental design is key in obtaining good quality events, we also include the sample processing protocol used to generate the data. Both, analysis and experimental pipelines are easy to scale-up, thus the workflow presented here is particularly suitable for large-scale, multicenter, multibatch and retrospective studies.

Mass spectrometry techniques for imaging and detection of metallodrugs

Undoubtedly, metallomic approaches based on mass spectrometry have evolved into essential tools supporting the drug development of novel metal-based anticancer drugs. This article will comment on the state-of-the-art instrumentation and highlight some of the recent analytical advances beyond routine, especially focusing on the latest developments in inductively coupled plasma-mass spectrometry (ICP-MS). Mass spectrometry-based bioimaging and single-cell methods will be presented, paving the way to exciting investigations of metal-based anticancer drugs in heterogeneous and structurally, as well as functionally complex solid tumor tissues.

Mechanisms of Allergen Immunotherapy in Allergic Rhinitis

PURPOSE OF REVIEW

Allergic rhinitis (AR) is a chronic inflammatory immunoglobulin (Ig) E-mediated disease of the nasal mucosa that can be triggered by the inhalation of seasonal or perennial allergens. Typical symptoms include sneezing, rhinorrhea, nasal itching, nasal congestion and symptoms of allergic conjunctivitis. AR affects a quarter of the population in the United States of America and Europe.

RECENT FINDINGS

AR has been shown to reduce work productivity in 36-59% of the patients with 20% reporting deteriorated job attendance. Moreover, 42% of children with AR report reduced at-school productivity and lower grades. Most importantly, AR impacts the patient's quality of life, due to sleep deprivation. However, a proportion of patients fails to respond to conventional medication and opts for the allergen immunotherapy (AIT), which currently is the only disease-modifying therapeutic option. AIT can be administered by either subcutaneous (SCIT) or sublingual (SLIT) route. Both routes of administration are safe, effective, and can lead to tolerance lasting years after treatment cessation. Both innate and adaptive immune responses that contribute to allergic inflammation are suppressed by AIT. Innate responses are ameliorated by reducing local mast cell, basophil, eosinophil, and circulating group 2 innate lymphoid cell frequencies which is accompanied by decreased basophil sensitivity. Induction of allergen-specific blocking antibodies, immunosuppressive cytokines, and regulatory T and B cell phenotypes are key pro-tolerogenic adaptive immune responses.

CONCLUSION

A comprehensive understanding of these mechanisms is necessary for optimal selection of AIT-responsive patients and monitoring treatment efficacy. Moreover, it could inspire novel and more efficient AIT approaches.