Procollagen C-Endopeptidase Enhancer 2 Secreted by Tonsil-Derived Mesenchymal Stem Cells Increases the Oxidative Burst of Promyelocytic HL-60 Cells

Integration of single-cell and bulk RNA sequencing data using machine learning identifies oxidative stress-related genes LUM and PCOLCE2 as potential biomarkers for heart failure

Oxidative stress (OS) is a pivotal mechanism driving the progression of cardiovascular diseases, particularly heart failure (HF). However, the comprehensive characterisation of OS-related genes in HF remains largely unexplored. In the present study, we analysed single-cell RNA sequencing datasets from the Gene Expression Omnibus and OS gene sets from GeneCards. We identified 167 OS-related genes potentially linked to HF by applying algorithms, such as AUCell, UCell, singscore, ssgsea, and AddModuleScore, combined with correlation analysis. Subsequently, we used feature selection algorithms, including least absolute shrinkage and selection operator, XGBoost, Boruta, random forest, gradient boosting machines, decision trees, and support vector machine recursive feature elimination, to identify lumican (LUM) and procollagen C-endopeptidase enhancer 2 (PCOLCE2) as key biomarker candidates with significant diagnostic potential. Bulk RNA-sequencing confirmed their elevated expression in patients with HF, highlighting their predictive utility. Single-cell analysis further revealed their upregulation primarily in fibroblasts, emphasising their cell-specific role in HF. To validate these findings, we developed a transverse aortic constriction-induced HF mouse model that showed enhanced cardiac OS activity and significant PCOLCE2 upregulation in the HF group. These results provide strong evidence of the involvement of OS-related mechanisms in HF. Herein, we propose a diagnostic strategy that provides novel insights into the molecular mechanisms underlying HF. However, further studies are required to validate its clinical utility and ensure its application in the diagnosis of HF.

Paeoniflorin Attenuates APAP-Induced Liver Injury via Intervening the Crosstalk Between Hepatocyte Pyroptosis and NETs

(1) Liver injury caused by an overdose of acetaminophen (APAP) represents a major public health concern. Paeoniflorin (PF) has been reported to have anti-inflammatory and liver-protective effects, but the underlying mechanisms remain unclear. This study aimed to investigate the effect of PF on the crosstalk between pyroptosis and NETs in AILI. (2) APAP-treated C57BL/6J mice were used to demonstrate the protective effect of PF on liver injury. HepG2 and dHL-60 cells were cultured to study the effects of PF on hepatocyte pyroptosis and neutrophil extracellular traps (NETs) in vitro. Moreover, cell co-culture experiments were performed, and mice were treated with a NETs-depleting agent and hepatocyte pyroptosis inhibitor to investigate the improvement of AILI induced by PF through regulating the crosstalk between hepatocyte pyroptosis and NETs. (3) PF significantly alleviated AILI. Additionally, PF inhibited the expression of pyroptosis-related proteins, high-mobility group box 1 (HMGB1), and NETs-associated proteins in vitro and in vivo. The co-culture experiments demonstrated that PF not only inhibited the NETs triggered by hepatocyte pyroptosis, but also suppressed the hepatocyte pyroptosis induced by NETs. In mice with depleted neutrophils, the level of hepatocyte pyroptosis notably decreased, indicating a diminished impact of PF. Similarly, NETs formation was reduced in mice receiving a pyroptosis inhibitor compared to the APAP group. Compared with DNase I alone, the reduction effect of PF combined with DNase I on serum ALT and AST levels decreased from 46.857% and 39.927% to 44.347% and 33.419%, respectively. Compared with DSF alone, PF combined with DSF reduced the ALT and AST levels from 46.857% and 39.927% to 45.347% and 36.419%, respectively. (4) PF demonstrated therapeutic effects on AILI. Its mechanism involves the regulation of the crosstalk between hepatocyte pyroptosis and NETs. This research substantiates the pharmacological promise of PF as a therapeutic intervention for acute AILI.

Identification of macrophage-related molecular subgroups and risk signature in colorectal cancer based on a bioinformatics analysis

Macrophages play a crucial role in tumor initiation and progression, while macrophage-associated gene signature in colorectal cancer (CRC) patients has not been investigated. Our study aimed to identify macrophage-related molecular subgroups and develop a macrophage-related risk model to predict CRC prognosis. The mRNA expression profile and clinical information of CRC patients were obtained from TCGA and GEO databases. CRC patients from TCGA were divided into high and low macrophage subgroups based on the median macrophage score. The ESTIMATE and CIBERSORT algorithms were used to assess immune cell infiltration between subgroups. GSVA and GSEA analyses were performed to investigate differences in enriched pathways between subgroups. Univariate and LASSO Cox regression were used to build a prognostic risk model, which was further validated in the GSE39582 dataset. A high macrophage score subgroup was associated with poor prognosis, highly activated immune-related pathways and an immune-active microenvironment. A total of 547 differentially expressed macrophage-related genes (DEMRGs) were identified, among which seven genes (including RIMKLB, UST, PCOLCE2, ZNF829, TMEM59L, CILP2, DTNA) were identified by COX regression analyses and used to build a risk score model. The risk model shows good predictive and diagnostic values for CRC patients in both TCGA and GSE39852 datasets. Furthermore, multivariate Cox regression analysis showed that the risk score was an independent risk factor for overall survival in CRC patients. Our findings provided a novel insight into macrophage heterogeneity and its immunological role in CRC. This risk score model may serve as an effective prognostic tool and contribute to personalised clinical management of CRC patients.

Multiomics analysis of platelet-rich plasma promoting biological performance of mesenchymal stem cells

Mesenchymal Stem Cells are ideal seed cells for tissue repair and cell therapy and have promising applications in regenerative medicine and tissue engineering. Using Platelet-Rich Plasma as an adjuvant to create and improve the microenvironment for Mesenchymal Stem Cells growth can enhance the biological properties of Mesenchymal Stem Cells and improve the efficacy of cell therapy. However, the mechanism by which Platelet-Rich Plasma improves the biological performance of Mesenchymal Stem Cells is still unknown. In this study, by examining the effects of Platelet-Rich Plasma on the biological performance of Mesenchymal Stem Cells, combined with multiomics analysis (Transcriptomics, Proteomics and Metabolomics) and related tests, we analyzed the specific pathways, related mechanisms and metabolic pathways of Platelet-Rich Plasma to improve the biological performance of Mesenchymal Stem Cells. In an in vitro cell culture system, the biological performance of Mesenchymal Stem Cells was significantly improved after replacing Foetal Bovine Serum with Platelet-Rich Plasma, and the genes (ESM1, PDGFB, CLEC7A, CCR1 and ITGA6 et al.) related to cell proliferation, adhesion, growth, migration and signal transduction were significantly upregulated. Platelet-Rich Plasma can enhance the secretion function of MSC exosomes, significantly upregulate many proteins related to tissue repair, immune regulation and anti-infection, and enhance the repair effect of exosomes on skin injury. After replacing Foetal Bovine Serum with Platelet-Rich Plasma, Mesenchymal Stem Cells underwent metabolic reprogramming, the metabolism of amino acids and fatty acids and various signaling pathways were changed, the anabolic pathways of various proteins were enhanced. These results provide a theoretical and technical reference for optimizing the Mesenchymal Stem Cells culture system, improving the biological characteristics and clinical application effects of Mesenchymal Stem Cells.

Characterization and verification of CAF-relevant prognostic gene signature to aid therapy in bladder cancer

Cancer-associated fibroblasts (CAFs) are significantly involved in determining the patient's prognosis and response to bladder cancer (BLCA) therapy. CAFs can induce epithelial-mesenchymal transformation (EMT) as well as complex interaction with immune cells. Hence, it is imperative to identify potential markers for enhancing our understanding of CAFs in BLCA progression and immune regulation. A variety of algorithms and analyses were employed in the study, leading to the development of a novel prognostic feature for CAFs-Stromal-EMT (CSE)-prognostic feature. This feature was constructed based on the genes MFAP5, PCOLCE2, and JUN. Furthermore, we revealed that patients with higher CSE risk scores responded to immunotherapy better compared to those with lower. Finally, we verified two CSE-related genes using in vitro experiments. Our results suggested that the CSE-prognostic feature could predict the prognosis and evaluate the response of patients to immune and chemotherapies. This would aid clinicians in designing treatment strategies for patients with BLCA.

Identification of PCPE-2 as the endogenous specific inhibitor of human BMP-1/tolloid-like proteinases

BMP-1/tolloid-like proteinases (BTPs) are major players in tissue morphogenesis, growth and repair. They act by promoting the deposition of structural extracellular matrix proteins and by controlling the activity of matricellular proteins and TGF-β superfamily growth factors. They have also been implicated in several pathological conditions such as fibrosis, cancer, metabolic disorders and bone diseases. Despite this broad range of pathophysiological functions, the putative existence of a specific endogenous inhibitor capable of controlling their activities could never be confirmed. Here, we show that procollagen C-proteinase enhancer-2 (PCPE-2), a protein previously reported to bind fibrillar collagens and to promote their BTP-dependent maturation, is primarily a potent and specific inhibitor of BTPs which can counteract their proteolytic activities through direct binding. PCPE-2 therefore differs from the cognate PCPE-1 protein and extends the possibilities to fine-tune BTP activities, both in physiological conditions and in therapeutic settings.

Special Issue on Differential Gene Expression and Coexpression

The most common approach in transcriptomics (RNA-seq and microarrays) is differential gene expression analysis (DGEA) [...].

Identification of key biomarkers based on the proliferation of secondary hyperparathyroidism by bioinformatics analysis and machine learning

Objective

Secondary hyperparathyroidism (SHPT) is a frequent complication of chronic kidney disease (CKD) associated with morbidity and mortality. This study aims to identify potential biomarkers that may be used to predict the progression of SHPT and to elucidate the molecular mechanisms of SHPT pathogenesis at the transcriptome level.

Methods

We analyzed differentially expressed genes (DEGs) between diffuse and nodular parathyroid hyperplasia of SHPT patients from the GSE75886 dataset, and then verified DEG levels with the GSE83421 data file of primary hyperparathyroidism (PHPT) patients. Candidate gene sets were selected by machine learning screens of differential genes and immune cell infiltration was explored with the CIBERSORT algorithm. RcisTarget was used to predict transcription factors, and Cytoscape was used to construct a lncRNA-miRNA-mRNA network to identify possible molecular mechanisms. Immunohistochemistry (IHC) staining and quantitative real-time polymerase chain reaction (qRT-PCR) were used to verify the expression of screened genes in parathyroid tissues of SHPT patients and animal models.

Results

A total of 614 DEGs in GSE75886 were obtained as candidate gene sets for further analysis. Five key genes (USP12, CIDEA, PCOLCE2, CAPZA1, and ACCN2) had significant expression differences between groups and were screened with the best ranking in the machine learning process. These genes were shown to be closely related to immune cell infiltration levels and play important roles in the immune microenvironment. Transcription factor ZBTB6 was identified as the master regulator, alongside multiple other transcription factors. Combined with qPCR and IHC assay of hyperplastic parathyroid tissues from SHPT patients and rats confirm differential expression of USP12, CIDEA, PCOLCE2, CAPZA1, and ACCN2, suggesting that they may play important roles in the proliferation and progression of SHPT.

Conclusion

USP12, CIDEA, PCOLCE2, CAPZA1, and ACCN2 have great potential both as biomarkers and as therapeutic targets in the proliferation of SHPT. These findings suggest novel potential targets and future directions for SHPT research.

Mitophagy and endoplasmic reticulum-phagy accelerated by a p62 ZZ ligand alleviates paracetamol-induced hepatotoxicity

BACKGROUND AND PURPOSE

Paracetamol (acetaminophen)-induced hepatotoxicity is the leading cause of drug-induced liver injury worldwide. Autophagy is a degradative process by which various cargoes are collected by the autophagic receptors such as p62/SQSTM1/Sequestosome-1 for lysosomal degradation. Here, we investigated the protective role of p62-dependent autophagy in paracetamol-induced liver injury.

EXPERIMENTAL APPROACH

Paracetamol-induced hepatotoxicity was induced by a single i.p. injection of paracetamol (500 mg·kg^-1 ) in C57/BL6 male mice. YTK-2205 (20 mg·kg^-1 ), a p62 agonist targeting ZZ domain, was co- or post-administered with paracetamol. Western blotting and immunocytochemistry were performed to explore the mechanism.

KEY RESULTS

N-terminal arginylation of the molecular chaperone calreticulin retro-translocated from the endoplasmic reticulum (ER) was induced in the livers undergoing paracetamol-induced hepatotoxicity, and YTK-2205 exhibited notable therapeutic efficacy in acute hepatotoxicity as assessed by the levels of serum alanine aminotransferase and hepatic necrosis. This efficacy was significantly attributed to accelerated degradation of ubiquitin (Ub) conjugates as well as damaged mitochondria (mitophagy) and endoplasmic reticulum (ER-phagy). In primary murine hepatocytes treated with paracetamol, YTK-2205 induced the co-localization of p62⁺ LC3⁺ phagophores to the sites of mitophagy and ER-phagy. A similar activity of YTK-2205 was observed with N-acetyl-p-benzoquinone imine, a putative toxic metabolite of paracetamol in Hep3B cells.

CONCLUSION AND IMPLICATIONS

Our results elucidated that p62-dependent autophagy plays a key role in the removal of cytotoxic materials such as damaged mitochondria in paracetamol-induced hepatotoxicity. Small molecule ligands to p62 may be developed into drugs to treat this pathological condition.

Meta-Analytic Comparison of Global RNA Transcriptomes of Acute and Chronic Myeloid Leukemia Cells Reveals Novel Gene Candidates Governing Myeloid Malignancies

Simple Summary

Despite advances in the understanding of genetic risk factors and molecular mechanisms underlying acute myeloid leukemia (AML) and chronic myeloid leukemia (CML), clinical outcomes of current therapies in terms of disease relapse and mortality rate pose a great economic and social burden. To overcome this, the identification of new molecular prognostic biomarkers and pharmacological targets is crucial. Recent studies have suggested that AML and CML may share common pathogenic mechanisms and cellular substrates. To this end, in the present study, global transcriptome profiles of AML and CML at the molecular and cellular level were directly compared using a combination of meta-analysis and modern statistics, and novel candidate genes and specific biological processes associated with the pathogenesis of AML and CML were characterized. Our study significantly improves our current understanding of myeloid leukemia and will help develop new therapeutic targets and biomarkers for disease progression, management and treatment response.

Abstract

Background: Acute myeloid leukemia (AML) and chronic myeloid leukemia (CML) represent a group of hematological malignancies characterized by the pathogenic clonal expansion of leukemic myeloid cells. The diagnosis and clinical outcome of AML and CML are complicated by genetic heterogeneity of disease; therefore, the identification of novel molecular biomarkers and pharmacological targets is of paramount importance. Methods: RNA-seq-based transcriptome data from a total of five studies were extracted from NCBI GEO repository and subjected to an in-depth bioinformatics analysis to identify differentially expressed genes (DEGs) between AML and CML. A systemic literature survey and functional gene ontology (GO) enrichment analysis were performed for the top 100 DEGs to identify novel candidate genes and biological processes associated with AML and CML. Results: LINC01554, PTMAP12, LOC644936, RPS27AP20 and FAM133CP were identified as novel risk genes for AML and CML. GO enrichment analysis showed that DEGs were significantly associated with pre-RNA splicing, reactive oxygen species and glycoprotein metabolism, the cellular endomembrane system, neutrophil migration and antimicrobial immune response. Conclusions: Our study revealed novel biomarkers and specific biological processes associated with AML and CML. Further studies are required to evaluate their value as molecular targets for managing and treating the myeloid malignancies.