Journal of Translational Medicine最新文献

Co-stimulatory molecules are imperative for CD8⁺ T cells to eliminate target cell and maintain sustained cytotoxicity. Despite an advanced understanding of the co-stimulatory molecules deficiency that results in tumor escape, the tumor cell-intrinsic mechanisms that regulate co-stimulatory molecules remain enigmatic, and an in-depth dissection could facilitate the improvement of treatment options. To this end, in this study, we report that the deficiency of the critical costimulatory molecule CD58, mediated by the expression of ATF4 in tumor cells, impairs the formation of immunological synapses (IS) and leads to the deterioration of antitumor immune function of CD8⁺ T cells. Mechanistically, ATF4 transcriptionally upregulated dynamin 1 (DNM1) expression leading to DNM1-dependent endocytosis (DDE)-mediated degradation of CD58. Furthermore, administration of DDE inhibitor prochlorperazine or ATF4 knockdown effectively restored CD58 expression, boosting CD8⁺ T cell cytotoxicity and immunotherapy efficiency. Thus, our study reveals that ATF4 in tumor cells weakens CD58 expression to interfere with complete IS formation, and indicates potential approaches to improve the cytolytic function of CD8⁺ T cell in tumor immunotherapy.

Background: Osteonecrosis (ON) is a debilitating orthopedic condition characterized by bone cell death due to impaired blood supply, leading to structural changes and disability. Osteoporosis (OP), a systemic skeletal disease, results in reduced bone density and quality, making bones fragile and prone to fractures. Although distinct, OP and ON share several risk factors such as corticosteroid use and smoking. This study aims to investigate the causal relationships between OP, bone mineral density (BMD), and ON using a bidirectional two-sample Mendelian randomization (MR) approach.

Methods: This study utilized genome-wide association study (GWAS) data for OP from the FinnGen database, and BMD data for the lumbar spine and femoral neck from the Genetic Factors for Osteoporosis (GEFOS) consortium. ON data were also obtained from the FinnGen database. All participants were of European descent. Genetic instruments were selected based on genome-wide significance, linkage disequilibrium, and strength (F-statistic). Bidirectional MR analysis was performed using inverse-variance weighted (IVW), MR-Egger regression, and weighted median methods to assess causality. Sensitivity analyses, including Cochran's Q test and MR-PRESSO, were conducted to evaluate heterogeneity and pleiotropy.

Results: MR analysis demonstrated a positive causal effect of OP on ON using the IVW method, with an odds ratio (OR) of 1.223 (95% CI: 1.026-1.459, P = 0.025). The weighted median method also confirmed this result with an OR (95% CI) 1.290 (1.021-1.630), P = 0.033. No significant causal effects were found between BMD (lumbar spine and femoral neck) and ON. Furthermore, ON did not exhibit a causal effect on OP or BMD. Sensitivity analyses confirmed the robustness of the results, showing no evidence of heterogeneity or pleiotropy.

Conclusion: This study provides evidence of a unidirectional causal relationship between OP and ON, suggesting that individuals with a genetic predisposition to OP have an increased risk of developing ON. These findings highlight the importance of early OP detection and management to potentially reduce ON incidence. The lack of a significant causal relationship between BMD and ON indicates that factors other than bone density, such as vascular health, may play a crucial role in ON development. Future research should explore these mechanisms further to inform clinical interventions.

Background: Intervertebral disc degeneration (IVDD) is a significant cause of global disability, reducing labor productivity, increasing the burden on public health, and affecting socio-economic well-being. Currently, there is a lack of recognized clinical approaches for molecular classification and precision therapy.

Methods: Chondrocyte differentiation and prognosis-related genes were extracted from single-cell RNA sequencing and multi-omics data in the Gene Expression Omnibus (GEO) database through chondrocyte trajectory analysis and non-parametric tests. Subsequently, a precise IVDD risk stratification system was developed using ConsensusClusterPlus analysis. The clinical significance of molecular typing was demonstrated through case-control trials involving IVDD patients. Specific inhibitors of molecular typing were predicted using the pRRophetic package in R language and then validated in vitro.

Results: A stratified model for IVDD, considering chondrocyte differentiation and demonstrating high clinical relevance, was developed using a set of 44 chondrocyte fate genes. Extensive analyses of multi-omics data confirmed the clinical relevance of this model, indicating that cases in the High Chondrocyte Scoring Classification (HCSC) group had the most favorable prognosis, whereas those in the Low Chondrocyte Scoring Classification (LCSC) group had the worst prognosis. Additionally, clinical case-control studies provided evidence of the utility of IVDD molecular typing in translational medicine. A gene expression-based molecular typing approach was used to create a matrix identifying potential inhibitors specific to each IVDD subtype. In vitro experiments revealed that gefitinib, a drug designed for LCSC, not only had protective effects on chondrocytes but also could induce the conversion of LCSC into the HCSC subgroup. Therefore, IVDD molecular typing played a critical role in assisting clinicians with risk stratification and enabling personalized treatment decisions.

Conclusion: The results of the study have provided a comprehensive and clinically relevant molecular typing for IVDD, involving a precise stratification system that offers a new opportunity for customizing personalized treatments for IVDD.

Background: Myocardial infarction (MI) and subsequent ischaemic cardiomyopathy (ICM) are the primary causes of heart failure. Inter-α trypsin inhibitor heavy chain 5 (ITIH5) is an extracellular matrix (ECM) protein and has been identified as a myocardial marker of ICM. However, its diagnostic value in patients with ICM and its function and molecular mechanism in regulating cardiac repair and remodelling after MI remain unknown.

Methods: Three microarray datasets including 117 ICM and 152 non-failing (NF) myocardial tissue samples were merged and analysed. Peripheral blood and clinical information were collected from 53 patients with ICM and 40 NF controls. The effects of ITIH5 on cellular interactions and cardiac remodelling was studied using ITIH5 RNAi adeno-associated virus and mouse MI model in vivo and in fibroblast-macrophage co-culture model in vitro.

Results: ITIH5 was upregulated in the myocardial tissue and peripheral blood of patients with ICM and could be an independent risk factor for ICM. Experiments in mice suggested that ITIH5 promotes cardiac fibrotic remodelling at all phases after MI. Downregulation of ITIH5 increased the risk of death within 7 d after MI but inhibited ventricular remodelling and improved cardiac function on the long-term. ITIH5 promotes the primary cardiac fibroblasts (CFs) proliferation, migration, and improves survival rather than activiation. Morover, ITIH5 directly promotes macrophage tissue infiltration, maturation, and profibrotic phenotype transformation, thereby promoting fibrotic remodelling. By using fibroblast-macrophage co-culture model, we demonstrated ITIH5 enhanced the fibroblast/macrophage crosstalk manifest as macrophage profibrotic phenotype transformation and CFs activation, mainly by enhancing the hyaluronan stability, the ability of ITIH5 to bind macrophage CD44 receptors and the downstream activation of the signal transduction and activator of transcription 3 pathway in macrophages.

Conclusions: ITIH5 could be used as a diagnostic marker for ICM. Moreover, ITIH5 expression was upregulated after MI, which accelerated ECM-fibroblast-macrophage interaction, thereby promoting macrophage profibrotic phenotype transformation, CFs activation, and cardiac fibrotic remodelling.

This review discusses findings related to neurological disorders, gut microbiota, and bariatric surgery, focusing on neurotransmitters, neuroendocrine, the pathophysiology of bacteria contributing to disorders, and possible therapeutic interventions. Research on neurotransmitters suggests that their levels are heavily influenced by gut microbiota, which may link them to neurological disorders such as Alzheimer's disease, Parkinson's disease, Multiple sclerosis, Depression, and Autism spectrum disorder. The pathophysiology of bacteria that reach and influence the central nervous system has been documented. Trends in microbiota are often observed in specific neurological disorders, with a prominence of pro-inflammatory bacteria and a reduction in anti-inflammatory types. Furthermore, bariatric surgery has been shown to alter microbiota profiles similar to those observed in neurological disorders. Therapeutic interventions, including fecal microbiota transplants and probiotics, have shown potential to alleviate neurological symptoms. We suggest a framework for future studies that integrates knowledge from diverse research areas, employs rigorous methodologies, and includes long-trial clinical control groups.

Background: Structural variations (SVs) are a pervasive and impactful class of genetic variation within the genome, significantly influencing gene function, impacting human health, and contributing to disease. Recent advances in deep learning have shown promise for SV detection; however, current methods still encounter key challenges in effective feature extraction and accurately predicting complex variations.

Methods: We introduce SVEA, an advanced deep learning model designed to address these challenges. SVEA employs a novel multi-channel image encoding approach that transforms SVs into multi-dimensional image formats, improving the model's ability to capture subtle genomic variations. Additionally, SVEA integrates multi-head self-attention mechanisms and multi-scale convolution modules, enhancing its ability to capture global context and multi-scale features. The model was trained and tested on a diverse range of genomic datasets to evaluate its accuracy and generalizability.

Results: SVEA demonstrated superior performance in detecting complex SVs compared to existing methods, with improved accuracy across various genomic regions. The multi-channel encoding and advanced feature extraction techniques contributed to the model's enhanced ability to predict subtle and complex variations.

Conclusions: This study presents SVEA, a deep learning model incorporating advanced encoding and feature extraction techniques to enhance structural variation prediction. The model demonstrates high accuracy, outperforming existing methods by approximately 4%, while also identifying areas for further optimization.

Background: Cancer stem cells (CSCs) are crucial for lung adenocarcinoma (LUAD). This study investigates tumor stem cell gene signatures in LUAD using single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq), aiming to develop a prognostic tumor stem cell marker signature (TSCMS) model.

Methods: LUAD scRNA-seq and RNA-seq data were analyzed. CytoTRACE software quantified the stemness score of tumor-derived epithelial cell clusters. Gene Set Variation Analysis (GSVA) identified potential biological functions in different clusters. The TSCMS model was constructed using Lasso-Cox regression, and its prognostic value was assessed through Kaplan-Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses. Immune infiltration was evaluated using the Cibersortx algorithm, and drug response prediction was performed using the pRRophetic package. TAF10 functional investigations in LUAD cells involved bioinformatics analysis, qRT-PCR, Western blot, immunohistochemistry, and assays for cell proliferation.

Results: Seven distinct cell clusters were identified by CytoTRACE, with epithelial cell cluster 1 (Epi_C1) showing the highest stemness potential. The TSCMS model included 49 tumor stemness-related genes; high-risk patients exhibited lower immune and ESTIMATE scores and increased tumor purity. Significant differences in immune landscapes and chemotherapy sensitivity were observed between risk groups. TAF10 positively correlated with RNA expression-based stemness scores in various tumors, including LUAD. It was over-expressed in LUAD cell lines and clinical tumor tissues, with high expression linked to poor prognosis. Silencing TAF10 inhibited LUAD cell proliferation and tumor sphere formation.

Conclusions: This study demonstrates the TSCMS model's prognostic value in LUAD, reveals insights into immune infiltration and therapeutic response, and identifies TAF10 as a potential therapeutic target.

Background: The ongoing emergence of evolving SARS-CoV-2 variants poses great threaten to the efficacy of authorized monoclonal antibody-based passive immunization or treatments. Developing potent broadly neutralizing antibodies (bNabs) against SARS-CoV-2 and elucidating their potential evolutionary pathways are essential for battling the coronavirus disease 2019 (COVID-19) pandemic.

Methods: Broadly neutralizing antibodies were isolated using single cell sorting from three COVID-19 convalescents infected with prototype SARS-CoV-2 strain. Their neutralizing activity against diverse SARS-CoV-2 strains were tested in vitro and in vivo, respectively. The structures of antibody-antigen complexes were resolved using crystallization or Cryo-EM method. Antibodyomics analyses were performed using the non-bias deep sequencing results of BCR repertoires.

Results: We obtained a series of RBD-specific monoclonal antibodies with highly neutralizing potency against a variety of pseudotyped and live SARS-CoV-2 variants, including five global VOCs and some Omicron subtypes such as BA.1, BA.2, BA.4/5, BF.7, and XBB. 2YYQH9 and LQLD6HL antibody cocktail also displayed good therapeutic and prophylactic efficacy in an XBB.1.16 infected hamster animal model. Cryo-EM and crystal structural analyses revealed that broadly neutralizing antibodies directly blocked the binding of ACE2 by almost covering the entire receptor binding motif (RBM) and largely avoided mutated RBD residues in the VOCs, demonstrating their broad and potent neutralizing activity. In addition, antibodyomics assays indicate that the germline frequencies of RBD-specific antibodies increase after an inactivated vaccine immunization. Moreover, the CDR3 frequencies of V_κ/λ presenting high amino acid identity with the broadly neutralizing antibodies were higher than those of V_H.

Conclusions: These data suggest that current identified broadly neutralizing antibodies could serve as promising drug candidates for COVID-19 and can be used for reverse vaccine design against future pandemics.

Background: Gastrointestinal metastases are rare in patients with thyroid carcinoma (TC), and their underlying mechanisms remain unclear. Thus, in this study, we aimed to explore the spatial distribution characteristics of TCs and associated gastrointestinal metastatic cells.

Methods: We used spatial transcriptomics to generate an atlas that captures spatial gene expression patterns in papillary thyroid cancer (PTC), anaplastic thyroid carcinoma (ATC), ATC-associated lymphatic metastasis (ATC-LM), and rare ATC-associated gastric metastasis (ATC-GM).

Results: We demonstrated that tumor-specific myeloid cells with high SFRP4 expression were correlated with TC dedifferentiation and poor prognosis. Moreover, we validated their close localization to CD44⁺ tissue stem cells using immunofluorescence staining and spatial transcriptomics. We also demonstrated that ATC-LM and ATC-GM tissues exhibited high levels of CD44⁺PKHD1L1⁺ cells, which could serve as markers for these two pathological types.

Conclusions: These findings highlight the dynamic changes in cell composition, intercellular communication, and potential markers associated with TC dedifferentiation and distant metastasis. Further research based on our findings may contribute to improving diagnostic and therapeutic strategies for patients with TC.