N6-methyladenine DNA Modification in Glioblastoma.

Genetic drivers of cancer can be dysregulated through epigenetic modifications of DNA. Although the critical role of DNA 5-methylcytosine (5mC) in the regulation of transcription is recognized, the functions of other non-canonical DNA modifications remain obscure. Here, we report the identification of novel N6-methyladenine (N6-mA) DNA modifications in human tissues and implicate this epigenetic mark in human disease, specifically the highly malignant brain cancer glioblastoma. Glioblastoma markedly upregulated N6-mA levels, which co-localized with heterochromatic histone modifications, predominantly H3K9me3. N6-mA levels were dynamically regulated by the DNA demethylase ALKBH1, depletion of which led to transcriptional silencing of oncogenic pathways through decreasing chromatin accessibility. Targeting the N6-mA regulator ALKBH1 in patient-derived human glioblastoma models inhibited tumor cell proliferation and extended the survival of tumor-bearing mice, supporting this novel DNA modification as a potential therapeutic target for glioblastoma. Collectively, our results uncover a novel epigenetic node in cancer through the DNA modification N6-mA.

Glioblastoma stem cells generate vascular pericytes to support vessel function and tumor growth.

Glioblastomas (GBMs) are highly vascular and lethal brain tumors that display cellular hierarchies containing self-renewing tumorigenic glioma stem cells (GSCs). Because GSCs often reside in perivascular niches and may undergo mesenchymal differentiation, we interrogated GSC potential to generate vascular pericytes. Here, we show that GSCs give rise to pericytes to support vessel function and tumor growth. In vivo cell lineage tracing with constitutive and lineage-specific fluorescent reporters demonstrated that GSCs generate the majority of vascular pericytes. Selective elimination of GSC-derived pericytes disrupts the neovasculature and potently inhibits tumor growth. Analysis of human GBM specimens showed that most pericytes are derived from neoplastic cells. GSCs are recruited toward endothelial cells via the SDF-1/CXCR4 axis and are induced to become pericytes predominantly by transforming growth factor ß. Thus, GSCs contribute to vascular pericytes that may actively remodel perivascular niches. Therapeutic targeting of GSC-derived pericytes may effectively block tumor progression and improve antiangiogenic therapy.

USP33 deubiquitinates and stabilizes HIF-2alpha to promote hypoxia response in glioma stem cells.

Hypoxia regulates tumor angiogenesis, metabolism, and therapeutic response in malignant cancers including glioblastoma, the most lethal primary brain tumor. The regulation of HIF transcriptional factors by the ubiquitin-proteasome system is critical in the hypoxia response, but hypoxia-inducible deubiquitinases that counteract the ubiquitination remain poorly defined. While the activation of ERK1/2 also plays an important role in hypoxia response, the relationship between ERK1/2 activation and HIF regulation remains elusive. Here, we identified USP33 as essential deubiquitinase that stabilizes HIF-2alpha protein in an ERK1/2-dependent manner to promote hypoxia response in cancer cells. USP33 is preferentially induced in glioma stem cells by hypoxia and interacts with HIF-2alpha, leading to its stabilization through deubiquitination. The activation of ERK1/2 upon hypoxia promoted HIF-2alpha phosphorylation, enhancing its interaction with USP33. Silencing of USP33 disrupted glioma stem cells maintenance, reduced tumor vascularization, and inhibited glioblastoma growth. Our findings highlight USP33 as an essential regulator of hypoxia response in cancer stem cells, indicating a novel potential therapeutic target for brain tumor treatment.

A dual role of human tRNA methyltransferase hTrmt13 in regulating translation and transcription.

Since numerous RNAs and RBPs prevalently localize to active chromatin regions, many RNA-binding proteins (RBPs) may be potential transcriptional regulators. RBPs are generally thought to regulate transcription via noncoding RNAs. Here, we describe a distinct, dual mechanism of transcriptional regulation by the previously uncharacterized tRNA-modifying enzyme, hTrmt13. On one hand, hTrmt13 acts in the cytoplasm to catalyze 2'-O-methylation of tRNAs, thus regulating translation in a manner depending on its tRNA-modification activity. On the other hand, nucleus-localized hTrmt13 directly binds DNA as a transcriptional co-activator of key epithelial-mesenchymal transition factors, thereby promoting cell migration independent of tRNA-modification activity. These dual functions of hTrmt13 are mutually exclusive, as it can bind either DNA or tRNA through its CHHC zinc finger domain. Finally, we find that hTrmt13 expression is tightly associated with poor prognosis and survival in diverse cancer patients. Our discovery of the noncatalytic roles of an RNA-modifying enzyme provides a new perspective for understanding epitranscriptomic regulation.

Novel immunomodulatory properties of adenosine analogs promote their antiviral activity against SARS-CoV-2.

The COVID-19 pandemic reminded us of the urgent need for new antivirals to control emerging infectious diseases and potential future pandemics. Immunotherapy has revolutionized oncology and could complement the use of antivirals, but its application to infectious diseases remains largely unexplored. Nucleoside analogs are a class of agents widely used as antiviral and anti-neoplastic drugs. Their antiviral activity is generally based on interference with viral nucleic acid replication or transcription. Based on our previous work and computer modeling, we hypothesize that antiviral adenosine analogs, like remdesivir, have previously unrecognized immunomodulatory properties which contribute to their therapeutic activity. In the case of remdesivir, we here show that these properties are due to its metabolite, GS-441524, acting as an Adenosine A2A Receptor antagonist. Our findings support a new rationale for the design of next-generation antiviral agents with dual - immunomodulatory and intrinsic - antiviral properties. These compounds could represent game-changing therapies to control emerging viral diseases and future pandemics.

Understanding the Neural Mechanisms of General Anesthesia from Interaction with Sleep-Wake State: A Decade of Discovery.

The development of cutting-edge techniques to study specific brain regions and neural circuits that regulate sleep-wake brain states and general anesthesia (GA), has increased our understanding of these states that exhibit similar neurophysiologic traits. This review summarizes current knowledge focusing on cell subtypes and neural circuits that control wakefulness, rapid eye movement (REM) sleep, non-REM sleep, and GA. We also review novel insights into their interactions and raise unresolved questions and challenges in this field. Comparisons of the overlapping neural substrates of sleep-wake and GA regulation will help us to understand sleep-wake transitions and how anesthetics cause reversible loss of consciousness. SIGNIFICANCE STATEMENT: General anesthesia (GA), sharing numerous neurophysiologic traits with the process of natural sleep, is administered to millions of surgical patients annually. In the past decade, studies exploring the neural mechanisms underlying sleep-wake and GA have advanced our understanding of their interactions and how anesthetics cause reversible loss of consciousness. Pharmacotherapies targeting the neural substrates associated with sleep-wake and GA regulations have significance for clinical practice in GA and sleep medicine.

Interpretable artificial intelligence model for accurate identification of medical conditions using immune repertoire.

Underlying medical conditions, such as cancer, kidney disease and heart failure, are associated with a higher risk for severe COVID-19. Accurate classification of COVID-19 patients with underlying medical conditions is critical for personalized treatment decision and prognosis estimation. In this study, we propose an interpretable artificial intelligence model termed VDJMiner to mine the underlying medical conditions and predict the prognosis of COVID-19 patients according to their immune repertoires. In a cohort of more than 1400 COVID-19 patients, VDJMiner accurately identifies multiple underlying medical conditions, including cancers, chronic kidney disease, autoimmune disease, diabetes, congestive heart failure, coronary artery disease, asthma and chronic obstructive pulmonary disease, with an average area under the receiver operating characteristic curve (AUC) of 0.961. Meanwhile, in this same cohort, VDJMiner achieves an AUC of 0.922 in predicting severe COVID-19. Moreover, VDJMiner achieves an accuracy of 0.857 in predicting the response of COVID-19 patients to tocilizumab treatment on the leave-one-out test. Additionally, VDJMiner interpretively mines and scores V(D)J gene segments of the T-cell receptors that are associated with the disease. The identified associations between single-cell V(D)J gene segments and COVID-19 are highly consistent with previous studies. The source code of VDJMiner is publicly accessible at https://github.com/TencentAILabHealthcare/VDJMiner. The web server of VDJMiner is available at https://gene.ai.tencent.com/VDJMiner/.

The palmitoylation machinery is a spatially organizing system for peripheral membrane proteins.

Reversible S-palmitoylation of cysteine residues critically controls transient membrane tethering of peripheral membrane proteins. Little is known about how the palmitoylation machinery governs their defined localization and function. We monitored the spatially resolved reaction dynamics and substrate specificity of the core mammalian palmitoylation machinery using semisynthetic substrates. Palmitoylation is detectable only on the Golgi, whereas depalmitoylation occurs everywhere in the cell. The reactions are not stereoselective and lack any primary consensus sequence, demonstrating that substrate specificity is not essential for de-/repalmitoylation. Both palmitate attachment and removal require seconds to accomplish. This reaction topography and rapid kinetics allows the continuous redirection of mislocalized proteins via the post-Golgi sorting apparatus. Unidirectional secretion ensures the maintenance of a proper steady-state protein distribution between the Golgi and the plasma membrane, which are continuous with endosomes. This generic spatially organizing system differs from conventional receptor-mediated targeting mechanisms and efficiently counteracts entropy-driven redistribution of palmitoylated peripheral membrane proteins over all membranes.

High Breakthrough Pressure in Hydrogels Enabled Ultrastable Treatment of Hypersaline Wastewaters.

Surface effects of low-surface-tension contaminants accumulating at the evaporation surface easily induce wetting in membrane distillation, especially in hypersaline scenarios. Herein, we propose a novel strategy to eliminate the surface effect and redistribute contaminants at the evaporation interface simply by incorporating a layer of hydrogel. The as-fabricated composite membrane exhibits remarkable stability, even when exposed to solution with salt concentration of 5 M and surfactant concentration of 8 mM. Breakthrough pressure of the membrane reaches 20 bar in the presence of surfactants, surpassing commercial hydrophobic membranes by one to two magnitudes. Density functional theory and molecular dynamics simulations reveal the important role of the hydrogel-surfactant interaction in suppressing the surface effect. As a proof of concept, we demonstrate the membrane in stably processing synthetic wastewater containing 144 mg L-1 surfactants, 1 g L-1 mineral oils, and 192 g L-1 NaCl, showing its potential in addressing challenges of hypersaline water treatment.

KLHL21 suppresses gastric tumourigenesis via maintaining STAT3 signalling equilibrium in stomach homoeostasis.

OBJECTIVE: Precancerous metaplasia transition to dysplasia poses a risk for subsequent intestinal-type gastric adenocarcinoma. However, the molecular basis underlying the transformation from metaplastic to cancerous cells remains poorly understood. DESIGN: An integrated analysis of genes associated with metaplasia, dysplasia was conducted, verified and characterised in the gastric tissues of patients by single-cell RNA sequencing and immunostaining. Multiple mouse models, including homozygous conditional knockout Klhl21-floxed mice, were generated to investigate the role of Klhl21 deletion in stemness, DNA damage and tumour formation. Mass-spectrometry-based proteomics and ribosome sequencing were used to elucidate the underlying molecular mechanisms. RESULTS: Kelch-like protein 21 (KLHL21) expression progressively decreased in metaplasia, dysplasia and cancer. Genetic deletion of Klhl21 enhances the rapid proliferation of Mist1+ cells and their descendant cells. Klhl21 loss during metaplasia facilitates the recruitment of damaged cells into the cell cycle via STAT3 signalling. Increased STAT3 activity was confirmed in cancer cells lacking KLHL21, boosting self-renewal and tumourigenicity. Mechanistically, the loss of KLHL21 promotes PIK3CB mRNA translation by stabilising the PABPC1-eIF4G complex, subsequently causing STAT3 activation. Pharmacological STAT3 inhibition by TTI-101 elicited anticancer effects, effectively impeding the transition from metaplasia to dysplasia. In patients with gastric cancer, low levels of KLHL21 had a shorter survival rate and a worse response to adjuvant chemotherapy. CONCLUSIONS: Our findings highlighted that KLHL21 loss triggers STAT3 reactivation through PABPC1-mediated PIK3CB translational activation, and targeting STAT3 can reverse preneoplastic metaplasia in KLHL21-deficient stomachs.

Comparative phylogenetic analysis of the mediator complex subunit in asparagus bean (Vigna unguiculata ssp. sesquipedialis) and its expression profile under cold stress.

BACKGROUND: The mediator complex subunits (MED) constitutes a multiprotein complex, with each subunit intricately involved in crucial aspects of plant growth, development, and responses to stress. Nevertheless, scant reports pertain to the VunMED gene within the context of asparagus bean (Vigna unguiculata ssp. sesquipedialis). Establishing the identification and exploring the responsiveness of VunMED to cold stress forms a robust foundation for the cultivation of cold-tolerant asparagus bean cultivars. RESULTS: Within this study, a comprehensive genome-wide identification of VunMED genes was executed in the asparagus bean cultivar 'Ningjiang3', resulting in the discovery of 36 distinct VunMED genes. A phylogenetic analysis encompassing 232 MED genes from diverse species, including Arabidopsis, tomatoes, soybeans, mung beans, cowpeas, and asparagus beans, underscored the highly conserved nature of MED gene sequences. Throughout evolutionary processes, each VunMED gene underwent purification and neutral selection, with the exception of VunMED19a. Notably, VunMED9/10b/12/13/17/23 exhibited structural variations discernible across four cowpea species. Divergent patterns of temporal and spatial expression were evident among VunMED genes, with a prominent role attributed to most genes during early fruit development. Additionally, an analysis of promoter cis-acting elements was performed, followed by qRT-PCR assessments on roots, stems, and leaves to gauge relative expression after exposure to cold stress and subsequent recovery. Both treatments induced transcriptional alterations in VunMED genes, with particularly pronounced effects observed in root-based genes following cold stress. Elucidating the interrelationships between subunits involved a preliminary understanding facilitated by correlation and principal component analyses. CONCLUSIONS: This study elucidates the pivotal contribution of VunMED genes to the growth, development, and response to cold stress in asparagus beans. Furthermore, it offers a valuable point of reference regarding the individual roles of MED subunits.

The dysfunction of CD8+ T cells triggered by endometriotic stromal cells promotes the immune survival of endometriosis.

Endometriosis is defined as an oestrogen-dependent and inflammatory gynaecological disease of which the pathogenesis remains unclear. This study aimed to investigate the cellular heterogeneity and reveal the effect of CD8+ T cells on the progress of endometriosis. Three ovarian endometriosis patients were collected, and single-cell RNA sequencing (scRNA-seq) progressed and delineated the cellular landscape of endometriosis containing five cell clusters. The endometrial cells (EMCs) were the major component, of which the mesenchymal cells were preponderant and characterized with increased inflammation and oestrogen synthesis in endometriosis. The proportion of T cells, mainly CD8+ T cells rather than CD4+, was reduced in endometriotic lesions, and the cytokines and cytotoxicity of ectopic T cells were depressed. CD8+ T cells depressed the proliferation of ESCs through inhibiting CDK1/CCNB1 pathway to arrest the cell cycle and triggered inflammation through activating STAT1 pathway. Correspondingly, the coculture with ESCs resulted in the dysfunction of CD8+ T cells through upregulating STAT1/PDCD1 pathway and glycolysis-promoted metabolism reprogramming. The endometriotic lesions were larger in nude mouse models with T-cell deficiency than the normal mouse models. The inhibition of T cells via CD90.2 or CD8A antibody increased the endometriotic lesions in mouse models, and the supplement of T cells to nude mouse models diminished the lesion sizes. In conclusion, this study revealed the global cellular variation of endometriosis among which the cellular count and physiology of EMCs and T cells were significantly changed. The depressed cytotoxicity and aberrant metabolism of CD8+ T cells were induced by ESCs with the activation of STAT1/PDCD1 pathway resulting in immune survival to promote endometriosis.

Sparsentan ameliorates glomerular hypercellularity and inflammatory-gene networks induced by IgA1-IgG immune complexes in a mouse model of IgA nephropathy.

IgA nephropathy (IgAN) is characterized by glomerular deposition of immune complexes (ICs) consisting of IgA1 with O-glycans deficient in galactose (Gd-IgA1) and Gd-IgA1-specific IgG autoantibodies. These ICs induce kidney injury, and in the absence of disease-specific therapy, up to 40% of patients with IgAN progress to kidney failure. IgA1 with its clustered O-glycans is unique to humans, which hampered development of small-animal models of IgAN. Here, we used a model wherein engineered ICs (EICs) formed from human Gd-IgA1 and recombinant human IgG autoantibody are injected into nude mice to induce glomerular injury mimicking human IgAN. In this model, we assessed the protective effects of sparsentan, a single-molecule dual endothelin angiotensin receptor antagonist (DEARA) versus vehicle on EIC-induced glomerular proliferation and dysregulation of gene expression in the kidney. Oral administration of sparsentan (60 or 120 mg/kg daily) to mice intravenously injected with EIC attenuated the EIC-induced glomerular hypercellularity. Furthermore, analysis of changes in the whole kidney transcriptome revealed that key inflammatory and proliferative biological genes and pathways that are upregulated in this EIC model of IgAN were markedly reduced by sparsentan, including complement genes, integrin components, members of the mitogen-activated protein kinase family, and Fc receptor elements. Partial overlap between mouse and human differentially expressed genes in IgAN further supported the translational aspect of the immune and inflammatory components from our transcriptional findings. In conclusion, our data indicate that in the mouse model of IgAN, sparsentan targets immune and inflammatory processes leading to protection from mesangial hypercellularity.NEW & NOTEWORTHY The mechanisms by which deposited IgA1 immune complexes cause kidney injury during early phases of IgA nephropathy are poorly understood. We used an animal model we recently developed that involves IgA1-IgG immune complex injections and determined pathways related to the induced mesangioproliferative changes. Treatment with sparsentan, a dual inhibitor of endothelin type A and angiotensin II type 1 receptors, ameliorated the induced mesangioproliferative changes and the associated alterations in the expression of inflammatory genes and networks.

Age-related decline in melatonin contributes to enhanced osteoclastogenesis via disruption of redox homeostasis.

BACKGROUND: Increased oxidative stress contributes to enhanced osteoclastogenesis and age-related bone loss. Melatonin (MT) is an endogenous antioxidant and declines with aging. However, it was unclear whether the decline of MT was involved in the enhanced osteoclastogenesis during the aging process. METHODS: The plasma level of MT, oxidative stress status, bone mass, the number of bone marrow-derived monocytes (BMMs) and its osteoclastogenesis were analyzed in young (3-month old) and old (18-month old) mice (n = 6 per group). In vitro, BMMs isolated from aged mice were treated with or without MT, followed by detecting the change of osteoclastogenesis and intracellular reactive oxygen species (ROS) level. Furthermore, old mice were treated with MT for 2 months to investigate the therapeutic effect. RESULTS: The plasma level of MT was markedly lower in aged mice compared with young mice. Age-related decline in MT was accompanied by enhanced oxidative stress, osteoclastogenic potential and bone loss. MT intervention significantly suppressed the receptor activator of nuclear factor-κB ligand (RANKL)-induced osteoclastogenesis, decreased intracellular ROS and enhanced antioxidant capacity of BMMs from aged mice. MT supplementation significantly attenuated oxidative stress, osteoclastogenesis, bone loss and deterioration of bone microstructure in aged mice. CONCLUSIONS: These results suggest that age-related decline of MT enhanced osteoclastogenesis via disruption of redox homeostasis. MT may serve as a key regulator in osteoclastogenesis and bone homeostasis, thereby highlighting its potential as a preventive agent for age-related bone loss.

A graph neural network model to estimate cell-wise metabolic flux using single-cell RNA-seq data.

The metabolic heterogeneity and metabolic interplay between cells are known as significant contributors to disease treatment resistance. However, with the lack of a mature high-throughput single-cell metabolomics technology, we are yet to establish systematic understanding of the intra-tissue metabolic heterogeneity and cooperative mechanisms. To mitigate this knowledge gap, we developed a novel computational method, namely, single-cell flux estimation analysis (scFEA), to infer the cell-wise fluxome from single-cell RNA-sequencing (scRNA-seq) data. scFEA is empowered by a systematically reconstructed human metabolic map as a factor graph, a novel probabilistic model to leverage the flux balance constraints on scRNA-seq data, and a novel graph neural network-based optimization solver. The intricate information cascade from transcriptome to metabolome was captured using multilayer neural networks to capitulate the nonlinear dependency between enzymatic gene expressions and reaction rates. We experimentally validated scFEA by generating an scRNA-seq data set with matched metabolomics data on cells of perturbed oxygen and genetic conditions. Application of scFEA on this data set showed the consistency between predicted flux and the observed variation of metabolite abundance in the matched metabolomics data. We also applied scFEA on five publicly available scRNA-seq and spatial transcriptomics data sets and identified context- and cell group-specific metabolic variations. The cell-wise fluxome predicted by scFEA empowers a series of downstream analyses including identification of metabolic modules or cell groups that share common metabolic variations, sensitivity evaluation of enzymes with regards to their impact on the whole metabolic flux, and inference of cell-tissue and cell-cell metabolic communications.

Prediction of biomarker-disease associations based on graph attention network and text representation.

MOTIVATION: The associations between biomarkers and human diseases play a key role in understanding complex pathology and developing targeted therapies. Wet lab experiments for biomarker discovery are costly, laborious and time-consuming. Computational prediction methods can be used to greatly expedite the identification of candidate biomarkers. RESULTS: Here, we present a novel computational model named GTGenie for predicting the biomarker-disease associations based on graph and text features. In GTGenie, a graph attention network is utilized to characterize diverse similarities of biomarkers and diseases from heterogeneous information resources. Meanwhile, a pretrained BERT-based model is applied to learn the text-based representation of biomarker-disease relation from biomedical literature. The captured graph and text features are then integrated in a bimodal fusion network to model the hybrid entity representation. Finally, inductive matrix completion is adopted to infer the missing entries for reconstructing relation matrix, with which the unknown biomarker-disease associations are predicted. Experimental results on HMDD, HMDAD and LncRNADisease data sets showed that GTGenie can obtain competitive prediction performance with other state-of-the-art methods. AVAILABILITY: The source code of GTGenie and the test data are available at: https://github.com/Wolverinerine/GTGenie.

MIX-TPI: a flexible prediction framework for TCR-pMHC interactions based on multimodal representations.

MOTIVATION: The interactions between T-cell receptors (TCR) and peptide-major histocompatibility complex (pMHC) are essential for the adaptive immune system. However, identifying these interactions can be challenging due to the limited availability of experimental data, sequence data heterogeneity, and high experimental validation costs. RESULTS: To address this issue, we develop a novel computational framework, named MIX-TPI, to predict TCR-pMHC interactions using amino acid sequences and physicochemical properties. Based on convolutional neural networks, MIX-TPI incorporates sequence-based and physicochemical-based extractors to refine the representations of TCR-pMHC interactions. Each modality is projected into modality-invariant and modality-specific representations to capture the uniformity and diversities between different features. A self-attention fusion layer is then adopted to form the classification module. Experimental results demonstrate the effectiveness of MIX-TPI in comparison with other state-of-the-art methods. MIX-TPI also shows good generalization capability on mutual exclusive evaluation datasets and a paired TCR dataset. AVAILABILITY AND IMPLEMENTATION: The source code of MIX-TPI and the test data are available at: https://github.com/Wolverinerine/MIX-TPI.

Bay41-4109-induced aberrant polymers of hepatitis b capsid proteins are removed via STUB1-promoted p62-mediated macroautophagy.

The hepatitis B virus (HBV) core protein (HBc) functions in multiple steps of the viral life cycle. Heteroaryldihydropyrimidine compounds (HAPs) such as Bay41-4109 are capsid protein allosteric modulators that accelerate HBc degradation and inhibit the virion secretion of HBV, specifically by misleading HBc assembly into aberrant non-capsid polymers. However, the subsequent cellular fates of these HAP-induced aberrant non-capsid polymers are not well understood. Here, we discovered that that the chaperone-binding E3 ubiquitin ligase protein STUB1 is required for the removal of Bay41-4109-induced aberrant non-capsid polymers from HepAD38 cells. Specifically, STUB1 recruits BAG3 to transport Bay41-4109-induced aberrant non-capsid polymers to the perinuclear region of cells, thereby initiating p62-mediated macroautophagy and lysosomal degradation. We also demonstrate that elevating the STUB1 level enhances the inhibitory effect of Bay41-4109 on the production of HBeAg and HBV virions in HepAD38 cells, in HBV-infected HepG2-NTCP cells, and in HBV transgenic mice. STUB1 overexpression also facilitates the inhibition of Bay41-4109 on the cccDNA formation in de novo infection of HBV. Understanding these molecular details paves the way for applying HAPs as a potentially curative regimen (or a component of a combination treatment) for eradicating HBV from hepatocytes of chronic infection patients.

Updated epithelial barrier dysfunction in chronic rhinosinusitis: Targeting pathophysiology and treatment response of tight junctions.

Tight junction (TJ) proteins establish a physical barrier between epithelial cells, playing a crucial role in maintaining tissue homeostasis by safeguarding host tissues against pathogens, allergens, antigens, irritants, etc. Recently, an increasing number of studies have demonstrated that abnormal expression of TJs plays an essential role in the development and progression of inflammatory airway diseases, including chronic obstructive pulmonary disease, asthma, allergic rhinitis, and chronic rhinosinusitis (CRS) with or without nasal polyps. Among them, CRS with nasal polyps is a prevalent chronic inflammatory disease that affects the nasal cavity and paranasal sinuses, leading to a poor prognosis and significantly impacting patients' quality of life. Its pathogenesis primarily involves dysfunction of the nasal epithelial barrier, impaired mucociliary clearance, disordered immune response, and excessive tissue remodeling. Numerous studies have elucidated the pivotal role of TJs in both the pathogenesis and response to traditional therapies in CRS. We therefore to review and discuss potential factors contributing to impair and repair of TJs in the nasal epithelium based on their structure, function, and formation process.

Metabolic subtypes and immune landscapes in esophageal squamous cell carcinoma: prognostic implications and potential for personalized therapies.

BACKGROUND: This study aimed to identify metabolic subtypes in ESCA, explore their relationship with immune landscapes, and establish a metabolic index for accurate prognosis assessment. METHODS: Clinical, SNP, and RNA-seq data were collected from 80 ESCA patients from the TCGA database and RNA-seq data from the GSE19417 dataset. Metabolic genes associated with overall survival (OS) and progression-free survival (PFS) were selected, and k-means clustering was performed. Immune-related pathways, immune infiltration, and response to immunotherapy were predicted using bioinformatic algorithms. Weighted gene co-expression network analysis (WGCNA) was conducted to identify metabolic genes associated with co-expression modules. Lastly, cell culture and functional analysis were performed using patient tissue samples and ESCA cell lines to verify the identified genes and their roles. RESULTS: Molecular subtypes were identified based on the expression profiles of metabolic genes, and univariate survival analysis revealed 163 metabolic genes associated with ESCA prognosis. Consensus clustering analysis classified ESCA samples into three distinct subtypes, with MC1 showing the poorest prognosis and MC3 having the best prognosis. The subtypes also exhibited significant differences in immune cell infiltration, with MC3 showing the highest scores. Additionally, the MC3 subtype demonstrated the poorest response to immunotherapy, while the MC1 subtype was the most sensitive. WGCNA analysis identified gene modules associated with the metabolic index, with SLC5A1, NT5DC4, and MTHFD2 emerging as prognostic markers. Gene and protein expression analysis validated the upregulation of MTHFD2 in ESCA. MTHFD2 promotes the progression of ESCA and may be a potential therapeutic target for ESCA. CONCLUSION: The established metabolic index and identified metabolic genes offer potential for prognostic assessment and personalized therapeutic interventions for ESCA, underscoring the importance of targeting metabolism-immune interactions in ESCA. MTHFD2 promotes the progression of ESCA and may be a potential therapeutic target for ESCA.