Systems biology-based analysis exploring shared biomarkers and pathogenesis of myocardial infarction combined with osteoarthritis.

Background: More and more evidence supports the association between myocardial infarction (MI) and osteoarthritis (OA). The purpose of this study is to explore the shared biomarkers and pathogenesis of MI complicated with OA by systems biology. Methods: Gene expression profiles of MI and OA were downloaded from the Gene Expression Omnibus (GEO) database. The Weighted Gene Co-Expression Network Analysis (WGCNA) and differentially expressed genes (DEGs) analysis were used to identify the common DEGs. The shared genes related to diseases were screened by three public databases, and the protein-protein interaction (PPI) network was built. GO and KEGG enrichment analyses were performed on the two parts of the genes respectively. The hub genes were intersected and verified by Least absolute shrinkage and selection operator (LASSO) analysis, receiver operating characteristic (ROC) curves, and single-cell RNA sequencing analysis. Finally, the hub genes differentially expressed in primary cardiomyocytes and chondrocytes were verified by RT-qPCR. The immune cell infiltration analysis, subtypes analysis, and transcription factors (TFs) prediction were carried out. Results: In this study, 23 common DEGs were obtained by WGCNA and DEGs analysis. In addition, 199 common genes were acquired from three public databases by PPI. Inflammation and immunity may be the common pathogenic mechanisms, and the MAPK signaling pathway may play a key role in both disorders. DUSP1, FOS, and THBS1 were identified as shared biomarkers, which is entirely consistent with the results of single-cell RNA sequencing analysis, and furher confirmed by RT-qPCR. Immune infiltration analysis illustrated that many types of immune cells were closely associated with MI and OA. Two potential subtypes were identified in both datasets. Furthermore, FOXC1 may be the crucial TF, and the relationship of TFs-hub genes-immune cells was visualized by the Sankey diagram, which could help discover the pathogenesis between MI and OA. Conclusion: In summary, this study first revealed 3 (DUSP1, FOS, and THBS1) novel shared biomarkers and signaling pathways underlying both MI and OA. Additionally, immune cells and key TFs related to 3 hub genes were examined to further clarify the regulation mechanism. Our study provides new insights into shared molecular mechanisms between MI and OA.

Construction of prognostic markers for gastric cancer and comprehensive analysis of pyroptosis-related long non-coding RNAs.

BACKGROUND: China's most frequent malignancy is gastric cancer (GC), which has a very poor survival rate, and the survival rate for patients with advanced GC is dismal. Pyroptosis has been connected to the genesis and development of cancer. The function of pyroptosis-related long non-coding RNAs (PRLs) in GC, on the other hand, remains uncertain. AIM: To explore the construction and comprehensive analysis of the prognostic characteristics of long non-coding RNA (lncRNA) related to pyroptosis in GC patients. METHODS: The TCGA database provided us with 352 stomach adenocarcinoma samples, and we obtained 28 pyroptotic genes from the Reactome database. We examined the correlation between lncRNAs and pyroptosis using the Pearson correlation coefficient. Prognosis-related PRLs were identified through univariate Cox analysis. A predictive signature was constructed using stepwise Cox regression analysis, and its reliability and independence were assessed. To facilitate clinical application, a nomogram was created based on this signature. we analyzed differences in immune cell infiltration, immune function, and checkpoints between the high-risk group (HRG) and low-risk group (LRG). RESULTS: Five hundred and twenty-three PRLs were screened from all lncRNAs (absolute correlation coefficient > 0.4, P < 0.05). Nine PRLs were included in the risk prediction signature that was created through stepwise Cox regression analysis. We determined the risk score for GC patients and employed the median value as the dividing line between HRG and LRG. The ability of the risk signature to predict the overall survival (OS) of GC is demonstrated by the Kaplan-Meier analysis, risk curve, receiver operating characteristic curve, and decision curve analysis curve. The risk signature was shown to be an independent prognostic factor for OS in both univariate and multivariate Cox regression analyses. HRG showed a more efficient local immune response or modulation compared to LRG, as indicated by the predicted signal pathway analysis and examination of immune cell infiltration, function, and checkpoints (P < 0.05). CONCLUSION: In general, we have created a brand-new prognostic signature using PRLs, which may provide ideas for immunotherapy in patients with GC.

Deciphering the role of ferroptosis in rheumatoid arthritis: Synovial transcriptome analysis and immune infiltration correlation.

The pathogenesis of rheumatoid arthritis (RA) remains elusive. The initiation of joint degeneration is characterized by the loss of self-tolerance in peripheral joints. Ferroptosis, a form of regulated cell death, holds significant importance in the pathophysiology of inflammatory arthritis, primarily due to iron accumulation and the subsequent lipid peroxidation. The present study investigated the association between synovial lesions and ferroptosis-related genes using previously published data from rheumatoid patients. Transcriptome differential gene analysis was employed to identify ferroptosis-related differentially expressed genes (FRDEGs). To validate FRDEGs and screen hub genes, we used weighted gene co-expression network analysis (WGCNA) and receiver operating characteristic (ROC) curves. Subsequently, immune infiltration analysis and single cell analysis were conducted to investigate the relationship between various synovial tissues cells and FRDEGs. The findings were further confirmed through reverse transcription-quantitative polymerase chain reaction (RT-qPCR), immunohistochemical staining, and immunofluorescence techniques. Upon intersecting DEGs with ferroptosis-related genes, we identified a total of 104 FRDEGs. Through the construction of a protein-protein interaction (PPI) network, we pinpointed the top 20 most highly concentrated genes as hub genes. Subsequent analyses using ROC curve and WGCNA validated eight FRDEGs: TIMP1, JUN, EGFR, SREBF1, ADIPOQ, SCD, AR, and FABP4. Immuno-infiltration analyses revealed significant infiltration of immune cell in RA synovial tissues and their correlations with the FRDEGs. Notably, TIMP1 demonstrated a positive correlation with various immune cell populations. Single-cell sequencing date of RA synovial tissue revealed predominant expression of TIMP1 is in fibroblasts. RT-qPCR, immunohistochemistry, and immunofluorescence analyses confirmed significant upregulation of TIMP1 at both mRNA and protein levels in RA synovial tissues and fibroblast-like synoviocytes (FLS). The findings provide novel insights into pathophysiology of peripheral immune tolerance deficiency in RA. The dysregulation of TIMP1, a gene associated with ferroptosis, was significantly observed in RA patients, suggesting its potential as a promising biomarker and therapeutic target.

Spatial immune landscapes of SARS-CoV-2 gastrointestinal infection: macrophages contribute to local tissue inflammation and gastrointestinal symptoms.

Background: In some patients, persistent gastrointestinal symptoms like abdominal pain, nausea, and diarrhea occur as part of long COVID-19 syndrome following acute respiratory symptoms caused by SARS-CoV-2. However, the characteristics of immune cells in the gastrointestinal tract of COVID-19 patients and their association with these symptoms remain unclear. Methodology: Data were collected from 95 COVID-19 patients. Among this cohort, 11 patients who exhibited gastrointestinal symptoms and underwent gastroscopy were selected. Using imaging mass cytometry, the gastrointestinal tissues of these patients were thoroughly analyzed to identify immune cell subgroups and investigate their spatial distribution. Results: Significant acute inflammatory responses were found in the gastrointestinal tissues, particularly in the duodenum, of COVID-19 patients. These alterations included an increase in the levels of CD68+ macrophages and CD3+CD4+ T-cells, which was more pronounced in tissues with nucleocapsid protein (NP). The amount of CD68+ macrophages positively correlates with the number of CD3+CD4+ T-cells (R = 0.783, p < 0.001), additionally, spatial neighborhood analysis uncovered decreased interactions between CD68+ macrophages and multiple immune cells were noted in NP-positive tissues. Furthermore, weighted gene coexpression network analysis was employed to extract gene signatures related to clinical features and immune responses from the RNA-seq data derived from gastrointestinal tissues from COVID-19 patients, and we validated that the MEgreen module shown positive correlation with clinical parameter (i.e., Total bilirubin, ALT, AST) and macrophages (R = 0.84, p = 0.001), but negatively correlated with CD4+ T cells (R = -0.62, p = 0.004). By contrast, the MEblue module was inversely associated with macrophages and positively related with CD4+ T cells. Gene function enrichment analyses revealed that the MEgreen module is closely associated with biological processes such as immune response activation, signal transduction, and chemotaxis regulation, indicating its role in the gastrointestinal inflammatory response. Conclusion: The findings of this study highlight the role of specific immune cell groups in the gastrointestinal inflammatory response in COVID-19 patients. Gene coexpression network analysis further emphasized the importance of the gene modules in gastrointestinal immune responses, providing potential molecular targets for the treatment of COVID-19-related gastrointestinal symptoms.

The role of innate immune cells in the colorectal cancer tumor microenvironment and advances in anti-tumor therapy research.

Innate immune cells in the colorectal cancer microenvironment mainly include macrophages, neutrophils, natural killer cells, dendritic cells and bone marrow-derived suppressor cells. They play a pivotal role in tumor initiation and progression through the secretion of diverse cytokines, chemokines, and other factors that govern these processes. Colorectal cancer is a common malignancy of the gastrointestinal tract, and understanding the role of innate immune cells in the microenvironment of CRC may help to improve therapeutic approaches to CRC and increase the good prognosis. In this review, we comprehensively explore the pivotal role of innate immune cells in the initiation and progression of colorectal cancer (CRC), alongside an extensive evaluation of the current landscape of innate immune cell-based immunotherapies, thereby offering valuable insights for future research strategies and clinical trials.

Development and Validation of a Stromal-Immune Signature to Predict Prognosis in Intrahepatic Cholangiocarcinoma.

Background: Intrahepatic cholangiocarcinoma (ICC) is a highly desmoplastic tumor with poor prognosis even after curative resection. We investigated the associations between the composition of the ICC stroma and immune cell infiltration and aimed to develop a stromal-immune signature to predict prognosis in surgically treated ICC. Patients and methods: We recruited 359 ICC patients and performed immunohistochemistry to detect α-smooth muscle actin (α-SMA), CD3, CD4, CD8, Foxp3, CD68, and CD66b. Aniline was used to stain collagen deposition. Survival analyses were performed to detect prognostic values of these markers. Recursive partitioning for a discrete-time survival tree was applied to define a stromal-immune signature with distinct prognostic value. We delineated an integrated stromal-immune signature based on immune cell subpopulations and stromal composition to distinguish subgroups with different recurrence-free survival (RFS) and overall survival (OS) time. Results: We defined four major patterns of ICC stroma composition according to the distributions of α-SMA and collagen: dormant (α-SMAlow/collagenhigh), fibrogenic (α-SMAhigh/collagenhigh), inert (α-SMAlow/collagenlow), and fibrolytic (α-SMAhigh/collagenlow). The stroma types were characterized by distinct patterns of infiltration by immune cells. We divided patients into six classes. Class I, characterized by high CD8 expression and dormant stroma, displayed the longest RFS and OS, whereas Class VI, characterized by low CD8 expression and high CD66b expression, displayed the shortest RFS and OS. The integrated stromal-immune signature was consolidated in a validation cohort. Conclusion: We developed and validated a stromal-immune signature to predict prognosis in surgically treated ICC. These findings provide new insights into the stromal-immune response to ICC.

Integrative analysis reveals key lysosomal genes as potential therapeutic targets in Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disorder with early autophagy deficits. Our study probed the role of lysosomal-related genes (LRGs) in AD. Using the Gene Expression Omnibus (GEO) database, we analyzed differentially expressed genes (DEGs) in AD. AD-related genes and lysosomal-related genes (LRGs) were extracted from public databases. Leveraging the UpSetR package, we identified differentially expressed LRGs (DE-LRGs). Subsequently, consensus cluster analysis was used to stratify AD patients into distinct molecular subtypes based on DE-LRGs. Immune cell patterns were studied via Single-Sample Gene Set Enrichment Analysis (ssGSEA). Molecular pathways were assessed through Gene Set Variation Analysis (GSVA), while Mendelian Randomization (MR) discerned potential gene-AD causations. To reinforce our bioinformatics findings, we conducted in vitro experiments. In total, 52 DE-LRGs were identified, with LAMP1, VAMP2, and CTSB as standout hub genes. Leveraging the 52 DE-LRGs, AD patients were categorized into three distinct molecular subtypes. Interestingly, the three aforementioned hub genes exhibited significant predictive accuracy for AD differentiation across the subtypes. The ssGSEA further illuminated correlations between LAMP1, VAMP2, and CTSB with plasma cells, fibroblasts, eosinophils, and endothelial cells. GSVA analysis underscored significant associations of LAMP1, VAMP2, and CTSB with NOTCH, TGFß, and P53 pathways. Compellingly, MR findings indicated a potential causative relationship between LAMP1, CTSB, and AD. Augmenting our bioinformatics conclusions, in vitro tests revealed that LAMP1 potentially alleviates AD progression by amplifying autophagic processes. LAMP1 and CTSB emerge as potential AD biomarkers, paving the way for innovative therapeutic interventions.

A prognostic model constructed by ferroptosis-associated genes (FAGs) in papillary renal cell carcinoma (PRCC) and its association with tumor mutation burden (TMB) and immune infiltration.

BACKGROUND: This study aimed to identify the prognostic-related differentially expressed ferroptosis-associated genes (DEFAGs) in papillary renal cell carcinoma (PRCC). METHODS: Data encompassing simple nucleotide variation, transcriptome profiles, and relevant clinical information of PRCC patients were sourced from The Cancer Genome Atlas (TCGA) database. The expression matrix of ferroptosis-associated genes (FAGs) was analyzed using the "limma" package in R to identify differentially expressed DEFAGs. Lasso regression analysis, along with univariate and multivariate Cox proportional hazards regressions, was employed to identify independent prognostic-related DEFAGs and formulate a nomogram. Additionally, we examined potential independent survival-related clinical risk factors and compared immune cell infiltration and tumor mutation burden (TMB) differences between high- and low-risk patient groups. RESULTS: A cohort of 321 patients were analyzed, revealing twelve FAGs significantly influencing the overall survival (OS) of PRCC patients. Among them, two mRNAs (GCLC, HSBP1) emerged as independent prognostic-related DEFAGs. Smoking status, tumor stage, and risk score were identified as independent clinical risk factors for PRCC. Furthermore, notable disparities in immune cell infiltration and function were observed between high- and low-risk groups. GCLC and HSBP1 were associated with various immune cells and functions, TMB, and immune evasion. CONCLUSION: This finding revealed two independent prognostic-related DEFAGs in PRCC and established a robust prognostic model, offering potential therapeutic targets and promising insights for the management of this disease.

Identification of the novel exhausted T cell CD8 + markers in breast cancer.

Cancer is one of the most concerning public health issues and breast cancer is one of the most common cancers in the world. The immune cells within the tumor microenvironment regulate cancer development. In this study, single immune cell data sets were used to identify marker gene sets for exhausted CD8 + T cells (CD8Tex) in breast cancer. Machine learning methods were used to cluster subtypes and establish the prognostic models with breast cancer bulk data using the gene sets to evaluate the impacts of CD8Tex. We analyzed breast cancer overexpressing and survival-associated marker genes and identified CD8Tex hub genes in the protein-protein-interaction network. The relevance of the hub genes for CD8 + T-cells in breast cancer was evaluated. The clinical associations of the hub genes were analyzed using bulk sequencing data and spatial sequencing data. The pan-cancer expression, survival, and immune association of the hub genes were analyzed. We identified biomarker gene sets for CD8Tex in breast cancer. CD8Tex-based subtyping systems and prognostic models performed well in the separation of patients with different immune relevance and survival. CRTAM, CLEC2D, and KLRB1 were identified as CD8Tex hub genes and were demonstrated to have potential clinical relevance and immune therapy impact. This study provides a unique view of the critical CD8Tex hub genes for cancer immune therapy.

Exploring anesthetic-induced gene expression changes and immune cell dynamics in atrial tissue post-coronary artery bypass graft surgery.

Background: This study leverages the GSE4386 dataset, obtained from atrial tissue samples post-coronary artery bypass graft (CABG) surgery, to investigate the impact of anesthetic agents (sevoflurane and propofol) on gene expression and immune cell infiltration. Methods: Hierarchical clustering and box plots were employed for dataset preprocessing, highlighting a significant outlier (sample GSM99282), subsequently removed to ensure data integrity. Differentially expressed genes (DEGs) were identified using volcano plots based on specific log-fold-change and P-value thresholds. Additional analyses included the Friends approach, Spearman's correlation, and gene set enrichment analysis (GSEA), exploring functional annotations and pathways. Results: Heatmaps and bubble plots depicted DEGs, revealing distinct expression patterns between the sevoflurane and propofol groups. Friends analysis identified top genes based on log fold changes, further correlated using Spearman's method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses illustrated functional annotations of DEGs, while GSEA highlighted enriched biological categories. Immune cell infiltration analysis showcased varied cellular presence post-CABG. ESTIMATE algorithm scores demonstrated differences in immune, stroma, and estimate scores. Microenvironment Cell Populations-counter (MCPcounter) revealed an increased abundance of cytotoxic lymphocytes in the sevoflurane group, confirmed by a single sample GSEA. CIBERSORT algorithm identified distinct immune cell compositions, highlighting differences in macrophage M0 prevalence between sevoflurane and propofol groups. Conclusions: This comprehensive analysis provides insights into anesthetic-induced gene expression changes and immune cell dynamics in atrial tissue post-CABG surgery. The identified DEGs and immune cell compositions offer potential biomarkers and therapeutic targets for refining anesthetic strategies in cardiac surgeries.

The granulocyte colony-stimulating factor produced during Streptococcus suis infection controls neutrophil recruitment in the blood without affecting bacterial clearance.

Streptococcus suis causes diseases in pigs and has emerged as a zoonotic agent. When infected, the host develops an exacerbated inflammation that can lead to septic shock and meningitis. Although neutrophils greatly infiltrate the lesions, their dynamics during S. suis infection remain poorly described. Moreover, very few studies reported on the production and role of a key factor in the regulation of neutrophils: the colony-stimulating granulocyte factor (G-CSF). In this study, we characterized the G-CSF-neutrophil axis in the pathogenesis of S. suis induced disease. Using a mouse model of S. suis infection, we first evaluated the recruitment of neutrophils and their activation profile by flow cytometry. We found that infection provokes a massive neutrophil recruitment from the bone marrow to the blood and spleen. In both compartments, neutrophils displayed multiple activation markers. In parallel, we observed high systemic levels of G-CSF, with a peak of production coinciding with that of neutrophil recruitment. We then neutralized the effects of G-CSF and highlighted its role in the release of neutrophils from the bone marrow to the blood. However, it did not affect bacteremia nor the cytokine storm induced by S. suis. In conclusion, systemic G-CSF induces the release of neutrophils from the bone marrow to the blood, but its role in inflammation or bacterial clearance seems to be compensated by unknown factors. A better understanding of the role of neutrophils and inflammatory mediators could lead to better strategies for controlling the infection caused by S. suis.

Comprehensive bioinformatic analysis reveals a fibroblast-related gene signature for the diagnosis of keloids.

Aim: A keloid is a fibroproliferative cutaneous disorder secondary to skin injury, caused by an imbalance in fibroblast proliferation and apoptosis. However, the pathogenesis is not fully understood. In this study, candidate genes for keloid were identified and used to construct a diagnostic model. Methods: Three datasets related to keloids were downloaded from NCBI Gene Expression Omnibus. Fibroblast-related genes were screened, and fibroblast scores for the samples were determined. Then, a weighted gene co-expression network analysis (WGCNA) was used to identify modules and genes associated with keloids and the fibroblast score. Differentially expressed genes (DEGs) between keloid and control samples were identified and compared with fibroblast-related genes and genes in the modules. Overlapping genes were evaluated using functional enrichment analyses. Signature genes were further screened, and a diagnostic model was constructed. Finally, correlations between immune cell frequences and signature genes were analyzed. Results: In total, 124 fibroblast-related genes were obtained, and the fibroblast score was an effective indicator of the sample type. WGCNA revealed five modules that were significantly correlated with both the disease state and fibroblast scores, including 1760 genes. Additionally, 589 DEGs were identified, including 16 that overlapped with fibroblast-related genes and genes identified in the WGCNA. These genes were related to cell proliferation and apoptosis and were involved in FoxO, Rap1, p53, Ras, MAPK, and PI3K-Akt pathways. Finally, a six fibroblast-related gene signature (CCNB1, EGFR, E2F8, BTG1, TP63, and IGF1) was identified and used for diagnostic model construction. The proportions of regulatory T cells and macrophages were significantly higher in keloid tissues than in controls. Conclusion: The established model based on CCNB1, EGFR, E2F8, BTG1, TP63, and IGF1 showed good performance and may be useful for keloid diagnosis.

Immunomodulation of wound healing leading to efferocytosis.

Effectively eliminating apoptotic cells is precisely controlled by a variety of signaling molecules and a phagocytic effect known as efferocytosis. Abnormalities in efferocytosis may bring about the development of chronic conditions, including angiocardiopathy, chronic inflammatory diseases and autoimmune diseases. During wound healing, failure of efferocytosis leads to the collection of apoptosis, the release of necrotic material and chronic wounds that are difficult to heal. In addition to the traditional phagocytes-macrophages, other important cell species including dendritic cells, neutrophils, vascular endothelial cells, fibroblasts and keratinocytes contribute to wounding healing. This review summarizes how efferocytosis-mediated immunomodulation plays a repair-promoting role in wound healing, providing new insights for patients suffering from various cutaneous wounds.

The relationship between metabolite mediated immune regulatory imbalance and the occurrence of malignant tumors of bone and articular cartilage: a Mendelian randomization study.

Background: This study aims to assess the causal relationship between immune cell characteristics and malignant tumors of bone and articular cartilage, focusing on the mediating role of metabolites. Using Mendelian randomization, we evaluated these relationships based on genetic variations to identify potential biomarkers and therapeutic targets. Methods: A two-sample Mendelian randomization analysis was conducted using GWAS data for immune cell features and 1,400 metabolites to investigate direct and mediating effects. Effective instrumental variables (IVs) were selected, and statistical analyses-including inverse variance weighting (IVW), weighted median, and mode-based methods-were performed using R software. This approach enabled the assessment of direct causal relationships as well as the potential mediating role of metabolites in the association between immune cell features and malignancies. Results: Significant causal relationships were identified between 26 immune phenotypes and the risk of malignant tumors of bone and articular cartilage. Notably, the HLA DR+ NK cell phenotype SSC-A showed a positive correlation with the risk of these malignancies. Further analysis revealed causal relationships with 67 metabolites, 38 of which were positively correlated and 29 negatively correlated. Mediation analysis highlighted the role of immune surveillance and metabolic dysregulation in tumor development, as evidenced by the association between the immune phenotype SSC-A on HLA DR+ NK cells and the metabolite 5-hydroxyhexanoate. Conclusion: The findings suggest significant causal relationships between immune phenotypes and malignant tumors of bone and articular cartilage, with metabolites potentially mediating these relationships. These insights lay the groundwork for further research and could contribute to the development of new biomarkers and treatment strategies.

Timing, initiation and function: An in-depth exploration of the interaction network among neutrophil extracellular traps related genes in acute pancreatitis.

BACKGROUND: Exogenous inhibition of neutrophil extracellular traps (NETs) was believed to alleviate acute pancreatitis (AP). This study aimed to comprehensively explore the key biological behavior of NETs including timing and pathogenesis in AP by integrating of single cell RNA sequencing(scRNA-seq) and bulk RNA-seq. METHODS: Differentially expressed NETs-related genes and the hub genes of NETs were screened by bulk RNA-seq. ScRNA-seq was used to identify the cell types in pancreas of AP mice and to depict the transcriptomic maps in neutrophils. The mouse AP models were build to verify the timing of initiation of NETs and underlying pathogenesis of damage on pancreas acinar cells. RESULTS: Tlr4 and Ccl3 were screened for hub genes by bulk RNA-seq. The trajectory analysis of neutrophils showed that high expression of Ccl3, Cybb and Padi4 can be observed in the middle stage during AP. Macrophages might be essential in the biological behavior of neutrophils and NETs. Through animal models, we presented that extensive NETs structures were formed at mid-stage of inflammation, accompanied by more serious pancreas and lung damage. NETs might promote necroptosis and macrophage infiltration in AP, and the damage on pancreatic injury could be regulated by Tlr4 pathway. Ccl3 was considered to recruit neutrophils and promote NETs formation. CONCLUSION: The findings explored the underlying timing and pathogenesis of NETs in AP for the first time, which provided gene targets for further studies.

Integrative and comprehensive pan-cancer analysis of ubiquitin specific peptidase 11 (USP11) as a prognostic and immunological biomarker.

The significance of USP11 as a critical regulator in cancer has garnered substantial attention, primarily due to its catalytic activity as a deubiquitinating enzyme. Nonetheless, a thorough evaluation of USP11 across various cancer types in pan-cancer studies remains absent. Our analysis integrates data from a variety of sources, including five immunotherapy cohorts, thirty-three cohorts from The Cancer Genome Atlas (TCGA), and sixteen cohorts from the Gene Expression Omnibus (GEO), two of which involve single-cell transcriptomic data. Our findings indicate that aberrant USP11 expression is predictive of survival outcomes across various cancer types. The highest frequency of genomic alterations was observed in uterine corpus endometrial carcinoma (UCEC), with single-cell transcriptome analysis revealing significantly higher USP11 expression in plasmacytoid dendritic cells and mast cells. Notably, USP11 expression was associated with the infiltration levels of CD8+ T cells and natural killer (NK) activated cells. Additionally, in the skin cutaneous melanoma (SKCM) phs000452 cohort, patients with higher USP11 mRNA levels during immunotherapy experienced a significantly shorter median progression-free survival. USP11 emerges as a promising molecular biomarker with significant potential for predicting patient prognosis and immunoreactivity across various cancer types.

VCAM-1 mediates proximal tubule-immune cell crosstalk in failed tubule recovery during AKI-to-CKD transition.

Studies in animal models suggest a linkage between inflammatory response to injury and subsequent nephron loss during acute kidney injury (AKI) to chronic kidney disease (CKD) transition. Failure of normal repair during CKD transition correlates with de novo expression of vascular cell adhesion protein-1 (VCAM-1) by a subset of injured proximal tubule cells. This study identifies the role of VCAM-1 expression in promoting the failed repair state. Single-cell transcriptome analysis of patients with AKI and CKD, and whole kidney RNA and protein analyses of mouse models of CKD, confirmed a marked increase of VCAM-1 expression in the proximal tubules of injured kidneys. In immortalized mouse proximal tubular (MPT) cells and primary cultured renal cells (PCRCs), VCAM-1 expression was induced by proinflammatory cytokines including TNFα and IL-1ß. Analyses of bulk RNA sequencing of TNFα-treated PCRCs or pseudo-bulk RNA sequencing of biopsies from the Kidney Precision Medicine Project (KPMP) datasets indicated activation of NF-κB and an enrichment of inflammatory response and cell adhesion pathways in VCAM-1-positive cells. Pharmacologic inhibition of NF-κB signaling or genetic deletion of myeloid differentiation factor 88 (Myd88) and TIR-domain-containing adapter-inducing interferon-ß (Trif) suppressed TNFα- and IL-1ß-induced VCAM-1 expression in vitro. TNFα stimulation or overexpression of VCAM-1 significantly increased splenocyte adhesion to the MPT monolayer in culture. These results demonstrate that persistence of proinflammatory cytokines after AKI can induce NF-κB-dependent VCAM-1 expression by proximal tubule cells, mediating increased immune cell adhesion to the tubule and thus promoting further tubule injury and greater risk of progression from AKI to CKD.

Prognostic Value of Insulin Growth Factor-Like Receptor 1 (IGFLR1) in Stage II and III Colorectal Cancer and Its Association with Immune Cell Infiltration.

IGFLR1 is a novel biomarker, and some evidences suggested that is involved in the immune microenvironment of CRC. Here, we explored the expression of IGFLR1 and its association with the prognosis as well as immune cell infiltration in CRC, with the aim to provide a basis for further studies on IGFLR1. Immunohistochemical staining for IGFLR1, TIM-3, FOXP3, CD4, CD8, and PD-1 was performed in eligible tissues to analyze the expression of IGFLR1 and its association with prognosis and immune cell infiltration. Then, we screened colon cancer samples from TCGA and grouped patients according to IGFLR1-related genes. We also evaluated the co-expression and immune-related pathways of IGFLR1 to identify the potential mechanism of it in CRC. When P < 0.05, the results were considered statistically significant. IGFLR1 and IGFLR1-related genes were associated with the prognosis and immune cell infiltration (P < 0.05). In stage II and III CRC tissue and normal tissue, we found (1) IGFLR1 was expressed in both the cell membrane and cytoplasm and which was differentially expressed between cancer tissue and normal tissue. IGFLR1 expression was associated with the expression of FOXP3, CD8, and gender but was not associated with microsatellite instability. (2) IGFLR1 was an independent prognostic factor and patients with high IGFLR1 had a better prognosis. (3) A model including IGFLR1, FOXP3, PD-1, and CD4 showed good prognostic stratification ability. (4) There was a significant interaction between IGFLR1 and GATA3, and IGFLR1 had a significant co-expression with related factors in the INFR pathway. IGFLR1 has emerged as a new molecule related to disease prognosis and immune cell infiltration in CRC patients and showed a good ability to predict the prognosis of patients.

The Lymphatic Highway: How Lymphatics Drive Lung Health and Disease.

The pulmonary lymphatic system has emerged as a critical regulator of lung homeostasis and a key contributor to the pathogenesis of respiratory diseases. As the primary conduit responsible for maintaining fluid balance and facilitating immune cell trafficking, the integrity of lymphatic vessels is essential for preserving normal pulmonary structure and function. Lymphatic abnormalities manifest across a broad spectrum of pulmonary disorders, underscoring their significance in respiratory health and disease. This review provides an overview of pulmonary lymphatic biology and delves into the involvement of lymphatics in four major lung diseases: chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), asthma, and lung transplant rejection. We examine how lymphatic abnormalities manifest in each of these conditions and investigate the mechanisms through which lymphatic remodeling and dysfunction contribute to disease progression. Furthermore, we explore the therapeutic potential of targeting the lymphatic system to ameliorate these debilitating respiratory conditions. Despite the current knowledge, several crucial questions remain unanswered, such as the spatial and temporal dynamics of lymphatic changes, the molecular crosstalk between lymphatics and the lung microenvironment, and the distinction between protective versus detrimental lymphatic phenotypes. Unraveling these mysteries holds the promise of identifying novel molecular regulators, characterizing lymphatic endothelial phenotypes, and uncovering bioactive mediators. By harnessing this knowledge, we can pave the way for the development of innovative disease-modifying therapies targeting the lymphatic highway in lung disorders.

Identification of Immune Gene Signature Associated with T Cells and Natural Killer Cells in Type 1 Diabetes.

Purpose: This study aimed to investigate the abnormal infiltration of immune cells in type 1 diabetes mellitus (T1D) and elucidate their regulatory mechanisms. Methods: Public T1D-related gene expression data were obtained from the Gene Expression Omnibus database.The GSE123658 dataset analyzed whole blood RNA-seq data from type 1 diabetic patients and healthy volunteers. The GSE110914 dataset analyzed neutrophils purified from peripheral blood of patients with symptomatic and pre-symptomatic type 1 diabetes (T1D), at risk of T1D, and healthy controls. Immune cell infiltration analysis was performed to identify abnormally infiltrating immune cells. Differentially expressed immune genes (DEIGs) in T1D samples were identified, followed by the construction of an immune gene signature (IGS) using a protein-protein interaction (PPI) network and Least absolute shrinkage and selection operator Cox regression analyses (LASSO Cox regression analyses). The regulatory mechanisms underlying IGS were explored using gene set enrichment analysis. Furthermore, expression validation, diagnostic efficacy evaluation, and upstream miRNA prediction of hub signature genes were performed. We verified the miRNA expression of the key gene colony stimulating factor 1 (CSF1) and microRNA-326 (miR-326) by reverse transcription-quantitative PCR (RT‒qPCR). Results: The proportion of infiltrating T and natural killer (NK) cells differed between the T1D and control samples, and 207 immune genes (IGs) related to these immune cells were extracted. After differential expression, PPI, and LASSO Cox regression analyses, four signature DEIGs were identified for IGS construction: notch receptor 1 (NOTCH1), Janus kinase 3 (JAK3), tumor necrosis factor receptor superfamily member 4(TNFRSF4), and CSF1. Key pathways such as the Toll-like receptor signaling pathway were significantly activated in the high-risk group. Moreover, the upregulation of CSF1 in T1D samples was confirmed using a validation dataset, and CSF1 showed high diagnostic efficacy for T1D. Furthermore, CSF1 was targeted by miR-326.We used validated key genes in T1D patients, several of which were confirmed by RT‒qPCR. Conclusion: In conclusion, the identified key IGs may play an important role in T1D. CSF1 can be developed as a novel diagnostic biomarker for T1D.