Role In Immune Cell Infiltration Research Articles

Identification of potential metabolic biomarkers and immune cell infiltration for metabolic associated steatohepatitis by bioinformatics analysis and machine learning

Background: Metabolic associated steatohepatitis (MASH) represents a severe subtype of metabolic associated fatty liver disease (MASLD), with an increased risk of progression to cirrhosis and hepatocellular carcinoma. The nomenclature shift from nonalcoholic steatohepatitis (NASH)/nonalcoholic fatty liver disease (NAFLD) to MASH/MASLD, underscores the pivotal role of metabolic factors in disease progression. Diagnosis of MASH currently hinges on liver biopsy, a procedure whose invasive nature limits its clinical utility. This study aims to identify and validate metabolism-related genes (MRGs) markers for the non-invasive diagnosis of MASH. Methods: This study extracted multiple datasets from the GEO database to identify metabolism-related differentially expressed genes (MRDEGs). Protein-Protein Interaction (PPI) network and machine learning algorithms, including Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Random Forest (RF), were applied to screen for signature MRDEGs. The diagnostic performance of these MRDEGs was evaluated using the Receiver Operating Characteristic (ROC) curve and further validated using independent external datasets. Additionally, enrichment analysis was performed to uncover key driver pathways in MASH. The infiltration levels of various immune cell types were assessed using single sample Gene Set Enrichment Analysis (ssGSEA). Finally, Spearman correlation analysis confirmed the association between signature genes and immune cells. Results: We successfully identified seven signature MRDEGs, including CYP7A1, GCK, AKR1B10, HPRT1, GPD1, FADS2, and ENO3, through PPI network analysis and machine learning algorithms. The gene model displayed exceptional diagnostic performance in the training and validation cohorts, as evidenced by the area under ROC curve (AUC) exceeding 0.9. Further enrichment analysis revealed that signature MEDEGs were primarily involved in multiple biological pathways related to glucose and lipid metabolism. Immune infiltration analysis indicated a significant increase in the infiltration levels of activated CD8 T cells, gamma-delta T cells, natural killer cells, and CD56bright NK cells in patients with MASH. Conclusion: This study successfully identified seven signature MRDEGs as significant diagnostic biomarkers for MASH. The findings not only offer novel strategies for non-invasive diagnosis of MASH but also highlight the substantial role of immune cell infiltration in the progression of MASH.

Mesenchymal stem cell transplantation ameliorates inflammation in spinal cord injury by inhibiting lactylation-related genes.

Mesenchymal stem cell transplantation ameliorates inflammation in spinal cord injury by inhibiting lactylation-related genes.

Neuroimmune Interactions and Their Role in Immune Cell Trafficking in Cardiovascular Diseases and Cancer.

Sympathetic nerves innervate bone marrow and various immune organs, where norepinephrine-the primary sympathetic neurotransmitter-directly interacts with immune cells that express adrenergic receptors. This article reviewed the key molecular pathways triggered by sympathetic activation and explored how sympathetic activity influences immune cell migration. Norepinephrine serves as a chemoattractant for monocytes, macrophages, and stem cells, promoting the migration of myeloid cells while inhibiting the migration of lymphocytes at physiological concentrations. We also examined the role of immune cell infiltration in cardiovascular diseases and cancer. Evidence suggests that sympathetic activation increases myeloid cell infiltration into target tissues across various cardiovascular diseases, including atherosclerosis, hypertension, cardiac fibrosis, cardiac hypertrophy, arrhythmia, myocardial infarction, heart failure, and stroke. Conversely, inhibiting sympathetic activity may serve as a potential therapeutic strategy to treat these conditions by reducing macrophage infiltration. Furthermore, sympathetic activation promotes macrophage accumulation in cancer tissues, mirroring its effects in cardiovascular diseases, while suppressing T lymphocyte infiltration into cancerous sites. These changes contribute to increased cancer growth and metastasis. Thus, inhibiting sympathetic activation could help to protect against cancer by enhancing T cell infiltration and reducing macrophage presence in tumors.

Development of an Inflammation-related Gene-based Diagnostic Risk Model and Immune Infiltration Analysis in Bipolar Disorder.

This study aimed to construct a diagnostic risk model for Bipolar Disorder (BD) using inflammation-related genes (IRGs) and to explore the role of immune cell infiltration in BD pathogenesis. BD datasets (GSE23848, GSE124326, GSE39653, and GSE46449) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the edgeR package. The intersection of DEGs and IRGs was defined as differentially expressed IRGs. A LASSO regression model was used to identify optimal biomarkers, which were then utilized to construct a diagnostic risk model. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic accuracy of the biomarkers. Internal validation was performed with GSE124326, while external validation utilized GSE23848, GSE39653, and GSE46449. The xCell module in the IOBR package was employed to assess immune cell infiltration proportions. The relationship between IRGs, the diagnostic risk model, and immune cell dynamics was further analyzed. A total of 2345 DEGs were identified in GSE124326. GO and KEGG pathway enrichment analyses indicated that inflammatory pathways are critically involved in BD pathogenesis. A total of 69 BD-related IRGs were identified. Six key IRGs (IL33, DNASE1L3, IL2RA, CD70, CLEC5A, and SLPI) were identified through LASSO regression analysis and used to develop a diagnostic risk model. Internal and external validations confirmed the robust diagnostic performance of the risk model. Immuno-infiltration analysis showed significant differences in immune cell infiltration between BD patients and healthy controls. The diagnostic risk model and four potential biomarkers (DNASE1L3, IL2RA, CD70, and SLPI) showed strong correlations with various immune cell types. A diagnostic risk model for BD was constructed based on IRGs, highlighting the critical role of immune cell infiltration in BD pathogenesis.

Bioinformatics Analysis of Oxidative Stress-Related Genes and Immune Infiltration Patterns in Vitiligo.

Vitiligo is an autoimmune disorder characterized by pigment loss, and current treatment options remain inadequate. This study aims to identify oxidative stress-related biomarkers and hub genes associated with vitiligo diagnosis through genomic analysis and to examine the role of immune cell infiltration in the pathogenesis of vitiligo. The mRNA expression profile dataset GSE75819 was retrieved from the GEO database. Differential expression of oxidative stress-related genes in vitiligo was analyzed using R software. Protein-protein interaction (PPI) analysis, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted on the differentially expressed genes (DEGs). Immune cell infiltration between vitiligo and normal control groups was assessed using the CIBERSORT algorithm. Additionally, two machine learning algorithms were employed to identify hub genes, perform enrichment analyses, and evaluate their correlation with immune infiltration. A total of 415 Oxidative Stress-DEGs were identified in vitiligo, including 317 up-regulated and 98 down-regulated genes. PPI analysis highlighted the significance of certain ribosomal protein genes. KEGG enrichment analysis suggested an association between vitiligo and various neurodegenerative conditions, particularly through pathways such as oxidative phosphorylation and ribosome biogenesis. GO enrichment analysis indicated that the hub genes were significantly enriched in mitochondrial-related activities. Significant differences in immune infiltration patterns were observed between vitiligo patients and normal controls. Machine learning algorithms identified oxidative stress-related key genes associated with vitiligo, notably the DCT gene, whose expression was strongly linked to the activity of specific immune cell subsets and melanin biosynthetic pathways. Oxidative stress-related DEGs, ribosomal proteins, immune infiltration, and hub genes related to melanin biosynthesis, particularly DCT, are closely associated with the pathogenesis of vitiligo. These findings enhance our understanding of vitiligo and may aid in identifying therapeutic targets for the disease.

Integrating bulk and single-cell RNA sequencing data: unveiling RNA methylation and autophagy-related signatures in chronic obstructive pulmonary disease patients

Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous lung disease influenced by epigenetic modifications, particularly RNA methylation. Emerging evidence also suggests that autophagy plays a crucial role in immune cell infiltration and is implicated in COPD progression. This study aimed to investigate key RNA methylation regulators and explore the roles of RNA methylation and autophagy in COPD pathogenesis. We analyzed tissue-based bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) datasets from COPD and non-COPD patients, sourced from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified between COPD and non-COPD samples, and protein–protein interaction networks were constructed. Univariate logistic regression identified shared genes between DEGs and RNA methylation gene sets. Functional enrichment analyses, including Gene Ontology (GO), gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA), were performed. Weighted gene co-expression network analysis (WGCNA) and immune infiltration analysis were conducted. Integration with scRNA-seq data further elucidated changes in immune cell composition, and cell communication analysis assessed interactions between macrophages and other immune cells. AddModuleScore analysis quantified RNA methylation and autophagy effects. Finally, a COPD mouse model was used to validate the expression of critical RNA methylation genes (FTO and IGF2BP2) in lung macrophages via RT-qPCR and flow cytometry. As revealed, we identified 13 RNA methylation-related genes enriched in translation and methylation processes. GSEA and GSVA revealed significant enrichment of these genes in immune and autophagy pathways. WGCNA analysis pinpointed key hub genes linking RNA methylation and autophagy. Integrated scRNA-seq analysis demonstrated a marked reduction of macrophages in COPD, with FTO and IGF2BP2 emerging as critical RNA methylation regulators. Macrophages with elevated RNA methylation and autophagy scores had increased interactions with other immune cells. In COPD mouse models, decreased expression of FTO and IGF2BP2 in lung macrophages was validated. Taken together, this study highlights the significant roles of RNA methylation in relation to autophagy pathways in the context of COPD. We identified key RNA methylation-related hub genes, such as FTO and IGF2BP2, which were found to have decreased expression in COPD macrophages. These findings provide novel genetic insights into the epigenetic mechanisms of COPD and suggest potential avenues for developing diagnostic and therapeutic strategies.

Analysis and validation of biomarkers and immune cell infiltration profiles in unstable coronary atherosclerotic plaques using bioinformatics and machine learning.

Decreased stability of coronary atherosclerotic plaques correlates with a heightened risk of acute coronary syndrome (ACS). Thus, early diagnosis and treatment of unstable plaques are imperative in averting adverse cardiovascular events. This study aims to identify diagnostic biomarkers for unstable coronary atherosclerotic plaques and investigate the role of immune cell infiltration in their formation. The datasets GSE163154 and GSE111782, obtained from the gene expression omnibus (GEO) database, were amalgamated for bioinformatics analysis, using the dataset GSE43292 as a test set. Sequentially, we performed principal component analysis (PCA), differential gene expression analysis, enrichment analysis, weighted gene co-expression network analysis (WGCNA), utilized a machine learning algorithm to screen key genes, conducted receiver operating characteristic (ROC) curve analysis and nomogram model to assess biomarker diagnostic efficacy, validated the biomarkers, and analyzed immune cell infiltration. In conclusion, enrichment analyses demonstrate that genes are significantly enriched in inflammatory and immune-related pathways. We identified HSPA2 and GEM as key genes and validated them experimentally. Significant differences existed in immune cell infiltration between subgroups. Additionally, HSPA2 and GEM showed significant associations with a wide range of immune cells. HSPA2 and GEM can function as diagnostic biomarkers for unstable coronary atherosclerotic plaques. In combination with immune cell infiltration analyses, our study provides new insights into the future study of unstable plaque occurrence and molecular mechanisms.

Oncogenic and Immunological Roles of FRS2 and its Potential Value in Retroperitoneal Liposarcoma: from Bioinformatics Analysis to Clinicopathological Evidence.

Background: Retroperitoneal liposarcoma (RLPS) is a rare malignancy with no effective treatment beyond surgical intervention. Identifying novel therapeutic targets and prognostic markers is critical to improving outcomes. Fibroblast growth factor receptor substrate 2 (FRS2), located near MDM2 on chromosome 12q13-15, has a biological role and prognostic value in liposarcoma, which remain to be fully explored. Methods: Bioinformatics tools were used to analyze the differential expression of FRS2 across various malignancies using public databases, such as GTEx, TCGA, and cBioPortal. In sarcomas (SARC), clinicopathological features, prognostic outcomes, co-expressed genes, levels of tumor-infiltrating immune cells, immunostimulators, major histocompatibility complex (MHC) molecules, and immunochemokines were extracted from multiple public databases. Tumor specimens from 82 RLPS patients at our sarcoma center were collected, and FRS2 expression was assessed through immunohistochemistry. Results: FRS2 was found to be upregulated and amplified in most cancers. GEPIA 2 analysis showed significant variation in FRS2 mRNA expression across cancer types, especially in sarcomas (SARC). Lower FRS2 expression in SARC was correlated with improved overall survival (OS) and disease-free survival (DFS). FRS2 may affect the tumor immune microenvironment, inhibiting immune cell infiltration and promoting immune evasion. In our RLPS cohort, FRS2 overexpression was observed in 58.53% (48/82) of cases and was correlated with age (P = 0.009). High FRS2 expression was associated with poorer OS and DFS (P = 0.049 and P < 0.001, respectively), and multivariate analysis confirmed FRS2 as an independent prognostic factor. Conclusion: FRS2 may serve as a potential prognostic biomarker and therapeutic oncogene target. Additionally, FRS2 could play a role in immune cell infiltration in SARC and represents a promising immunotherapeutic target for cancer treatment.

Identification of amino acid metabolism‑related genes as diagnostic and prognostic biomarkers in sepsis through machine learning.

Previous research has highlighted the critical role of amino acid metabolism (AAM) in the pathophysiology of sepsis. The present study aimed to explore the potential diagnostic and prognostic value of AAM-related genes (AAMGs) in sepsis, as well as their underlying molecular mechanisms. Gene expression profiles from the Gene Expression Omnibus (GSE65682, GSE185263 and GSE154918 datasets) were analyzed. Based on weighted gene co-expression network analysis and machine learning algorithms, hub AAMGs were identified in the GSE65682 database. Subsequently, hub AAMGs were evaluated for their expression levels and diagnostic and prognostic significance in sepsis, as well as their interactions with regulatory pathways and role in immune cell infiltration. Additionally, trends in AAMG expression were validated using clinical samples, and their functions in sepsis were confirmed through an in vitro model. In total, four AAMGs were identified, two of which, methionine synthase (MTR) and methionine-R-isomerase 1 (MRI1), demonstrated significant differential expression in the GSE65682, GSE185263 and GSE154918 datasets, which was further validated using clinical samples. A diagnostic nomogram based on MTR and MRI1 expression demonstrated strong diagnostic effectiveness across the three aforementioned databases. Moreover, the expression of both genes were negatively correlated with sepsis prognosis and showed stratified prognostic capabilities. Newly identified pathways included KRAS and IL-2/STAT5 signaling. MTR and MRI1 negatively correlated with the infiltration of inflammatory cells, such as M1 macrophages and neutrophils, and positively correlated with anti-inflammatory cells, such as CD8+ T and dendritic cells. In vitro experiments further demonstrated that overexpression of MTR could mitigate the inhibition of cloning and proliferation induced by LPS and ATP in RAW 264.7 cells. These findings highlighted the potential of MTR and MRI1 as biomarkers for diagnosing and prognosticating sepsis, potentially acting through the regulation of methionine in the pathophysiology of this disease. The present study provided new insights into the role of AAM in the mechanisms underlying sepsis and in the potential development of future targeted therapies.

Pan-cancer TCGA analysis reveals the potential involvement of B-type lamins in dysregulating chromosome segregation in human cancer.

Lamins play a crucial role in maintaining nuclear structure and function. Our study investigates the expression patterns and clinical implications of B-type lamins with a special focus on lamin B2 across various cancer types using comprehensive RNA sequencing datasets. We found that high expression levels of lamin B1 and lamin B2 are associated with decreased overall and disease-free survival in cancer. This association is further pronounced when both lamins are co-expressed, indicating a compounded negative impact on patient prognosis. Additionally, we highlighted the relationship between B-type lamins and the tumor microenvironment. Lamin B1 mRNA expression shows a strong positive correlation with activated CD4+ T-cells and type 2 T-helper cells (Th2), suggesting its role in immune cell infiltration and response within tumors. Lamin B2 expression also correlates moderately with these immune cells, indicating a potential but lesser role in modulating the immune landscape. Notably, the epigenetic state of lamin B1 significantly affects the tumor microenvironment, suggesting a dual role in structural integrity and immune modulation. We have identified 9 lamin B2 interacting proteins that are co-expressed with B-type lamins in cancerous conditions and modulate cytokinesis and cell division pathways during tumorigenesis. Furthermore, we have identified specific molecular targets of B-type lamins that co-express with them in a range of human cancers and are potentially involved in dysregulating chromosome segregation and mRNA binding. Overexpression of these targets alongside B-type lamins correlates with poor prognosis in multiple cancers. These findings underscore the potential of B-type lamins as biomarkers for poor prognosis and as targets for cancer therapies.

Identification of a novel immune infiltration-related gene signature, MCEMP1, for coronary artery disease.

This study aims to identify a novel gene signature for coronary artery disease (CAD), explore the role of immune cell infiltration in CAD pathogenesis, and assess the cell function of mast cell-expressed membrane protein 1 (MCEMP1) in human umbilical vein endothelial cells (HUVECs) treated with oxidized low-density lipoprotein (ox-LDL). To identify differentially expressed genes (DEGs) of CAD, datasets GSE24519 and GSE61145 were downloaded from the Gene Expression Omnibus (GEO) database using the R "limma" package with p < 0.05 and |log2 FC| > 1. Gene ontology (GO) and pathway analyses were conducted to determine the biological functions of DEGs. Hub genes were identified using support vector machine-recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO). The expression levels of these hub genes in CAD were validated using the GSE113079 dataset. CIBERSORT program was used to quantify the proportion of immune cell infiltration. Western blot assay and qRT-PCR were used to detect the expression of hub genes in ox-LDL-treated HUVECs to validate the bioinformatics results. Knockdown interference sequences for MCEMP1 were synthesized, and cell proliferation and apoptosis were examined using a CCK8 kit and Muse® Cell Analyzer, respectively. The concentrations of IL-1β, IL-6, and TNF-α were measured with respective enzyme-linked immunosorbent assay (ELISA) kits. A total of 73 DEGs (four down-regulated genes and 69 up-regulated genes) were identified in the metadata (GSE24519 and GSE61145) cohort. GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results indicated that these DEGs might be associated with the regulation of platelet aggregation, defense response or response to bacterium, NF-kappa B signaling pathway, and lipid and atherosclerosis. Using SVM-RFE and LASSO, seven hub genes were obtained from the metadata. The upregulated expression of DIRC2 and MCEMP1 in CAD was confirmed in the GSE113079 dataset and in ox-LDL-treated HUVECs. The associations between the two hub genes (DIRC2 and MCEMP1) and the 22 types of immune cell infiltrates in CAD were found. MCEMP1 knockdown accelerated cell proliferation and suppressed cell apoptosis for ox-LDL-treated HUVECs. Additionally, MCEMP1 knockdown appeared to decrease the expression of inflammatory factors IL-1β, IL-6, and TNF-α. The results of this study indicate that MCEMP1 may play an important role in CAD pathophysiology.

Weighted gene co-expression network analysis reveals key biomarkers and immune infiltration characteristics for bronchial epithelial cells from asthmatic patients.

Asthma ranks among the most prevalent non-communicable diseases worldwide. Previous studies have elucidated the significant role of the immune system in its pathophysiology. Nevertheless, the immune-related mechanisms underlying asthma are complex and still inadequately understood. Thus, our objective was to investigate novel key biomarkers and immune infiltration characteristics associated with asthma by employing integrated bioinformatics tools. In this study, we conducted a weighted gene co-expression network analysis (WGCNA) to identify key modules and genes potentially implicated in asthma. Functional annotation of these key modules and genes was carried out through gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Additionally, we constructed a protein-protein interaction (PPI) network using the STRING database to identify 10 hub genes. Furthermore, we evaluated the relative proportion of immune cells in bronchial epithelial cell samples from 20 healthy individuals and 88 asthmatic patients using CIBERSORT. Finally, we validated the hub genes and explored their correlation with immune infiltration. Furthermore, 20 gene expression modules and 10 hub genes were identified herein. Among them, complement component 3 (C3), prostaglandin I2 receptor (PTGIR), parathyroid hormone-like hormone (PTHLH), and C-X3-C motif chemokine ligand 1 (CX3CL1) were closely correlated with the infiltration of immune cells. They may be novel candidate biomarkers or therapeutic targets for asthma. Furthermore, B cells memory, and plasma cells might play an important role in immune cell infiltration after asthma. C3, PTGIR, CX3CL1, and PTHLH have important clinical diagnostic values and are correlated with infiltration of multiple immune cell types in asthma. These hub genes, B cells memory, and plasma cells may become important biological targets for therapeutic asthma drug screening and drug design.

Spatial and single-cell explorations uncover prognostic significance and immunological functions of mitochondrial calcium uniporter in breast cancer

The mitochondrial calcium uniporter (MCU) is a transmembrane protein facilitating the entry of calcium ions into mitochondria from the cell cytosol. Maintaining calcium balance is crucial for enhancing cellular energy supply and regulating cell death. The interplay of calcium balance through MCU and the sodium-calcium exchanger is known, but its regulation in the breast cancer tumor microenvironment remains elusive. Further investigations are warranted to explore MCU’s potential in BRCA clinical pathology, tumor immune microenvironment, and precision oncology. Our study, employing a multi-omics approach, identifies MCU as an independent diagnostic biomarker for breast cancer (BRCA), correlated with advanced clinical status and poor overall survival. Utilizing public datasets from GEO and TCGA, we discern differentially expressed genes in BRCA and examine their associations with immune gene expression, overall survival, tumor stage, gene mutation status, and infiltrating immune cells. Spatial transcriptomics is employed to investigate MCU gene expression in various regions of BRCA, while spatial transcriptomics and single-cell RNA-sequencing methods explore the correlation between MCUs and immune cells. Our findings are validated through the analysis of 59 BRCA patient samples, utilizing immunohistochemistry and bioinformatics to examine the relationship between MCU expression, clinicopathological features, and prognosis. The study uncovers the expression of key gene regulators in BRCA associated with genetic variations, deletions, and the tumor microenvironment. Mutations in these regulators positively correlate with different immune cells in six immune datasets, playing a pivotal role in immune cell infiltration in BRCA. Notably, high MCU performance is linked to CD8 + T cells infiltration in BRCA. Furthermore, pharmacogenomic analysis of BRCA cell lines indicates that MCU inactivation is associated with increased sensitivity to specific small molecule drugs. Our findings suggest that MCU alterations may be linked to BRCA progression, unveiling new diagnostic and prognostic implications for MCU in BRCA. The study underscores MCU's role in the tumor immune microenvironment and cell cycle progression, positioning it as a potential tool for BRCA precision medicine and drug screening.

Junctional adhesion molecule-A deficient mice are protected from severe experimental autoimmune encephalomyelitis.

In multiple sclerosis and its animal model, experimental autoimmune encephalomyelitis (EAE), early pathological features include immune cell infiltration into the central nervous system (CNS) and blood-brain barrier (BBB) disruption. We investigated the role of junctional adhesion molecule-A (JAM-A), a tight junction protein, in active EAE (aEAE) pathogenesis. Our study confirms JAM-A expression at the blood-brain barrier and its luminal redistribution during aEAE. JAM-A deficient (JAM-A-/-) C57BL/6J mice exhibited milder aEAE, unrelated to myelin oligodendrocyte glycoprotein-specific CD4+ T-cell priming. While JAM-A absence influenced macrophage behavior on primary mouse brain microvascular endothelial cells (pMBMECs) under flow in vitro, it did not impact T-cell extravasation across primary mouse brain microvascular endothelial cells. At aEAE onset, we observed reduced lymphocyte and CCR2+ macrophage infiltration into the spinal cord of JAM-A-/- mice compared to control littermates. This correlated with increased CD3+ T-cell accumulation in spinal cord perivascular spaces and brain leptomeninges, suggesting JAM-A absence leads to T-cell trapping in central nervous system border compartments. In summary, JAM-A plays a role in immune cell infiltration and clinical disease progression in aEAE.

Lymphatic vessels in patients withcrescentic glomerulonephritis: association with renal pathology and prognosis.

Various immune cells, including T cells, B cells, macrophages, and neutrophilscontribute to the development of crescentic glomerulonephritis. Previous animal studies have suggested that lymphangiogenesis is involved in the migration of inflammatory cells and the activation of adaptive immunity. However, the extent of the association between lymphatic vessels and crescentic glomerulonephritis severity and prognosis remains unknown. In this study, we assessed lymphatic vessel density in 71 patients withcrescentic glomerulonephritis who underwent renal biopsies between June 2017 and June 2022. By immunohistochemistry and immunofluorescence, we identified increased lymphatic vessel density in thekidneys of patients with crescenticglomerulonephritiscompared to controls. Lymphatic vessels were categorized as total, periglomerular, and interstitial. Spearman's rank correlation analysis showed a positive correlation between total and periglomerular lymphatic vessel density and glomerular crescent proportion. High lymphatic vessel density (total and periglomerular) correlated with declining kidney function, increased proteinuria, and severe glomerular and interstitial pathology. Interstitial lymphatic vessel density had minimal relationship with renal lesions. After a median duration of 13 months of follow-up, higher total and periglomerular lymphatic vessel density was associated with poorer prognosis. Transcriptomic analysis revealed increased immune cell activation and migration in crescentic glomerulonephritis patients compared to healthy controls. Periglomerular lymphatic vessels might play a significant role in immune cell infiltration and renal injury. Elevated lymphatic vessel density in patients withcrescentic glomerulonephritis is associated with poor prognosisand may serve as a predictive factor for adverse outcomes in these patients.

Abstract 4558: A triterpenoid derivative has strong antitumor activities in gemcitabine-resistant advanced bladder cancer models and promotes immune cell infiltration in a high grade murine syngeneic model

Abstract Bladder cancer (BC) presents a formidable challenge in treatment and patient survival, requiring particular attention to advanced stages, such as muscle-invasive stage (MIBC), due to its potential for rapid progression and substantial impact on patient morbidity and mortality. The five-year survival rate for MIBC is a meager 30%, which drops further down to 8% once tumors metastasize. Advanced bladder cancers (High grade T1) are treated with intravesical therapy with Gemcitabine and Cisplatin (G+C) combination and Stage T2 are treated neoadjuvant with G+C and cystectomy, thereby decreasing the quality of life for patients with BC. Furthermore, tumors progress beyond responding to other chemotherapy regimens such as dose-dense treatment with Methotrexate +Vinblastine + Adriamycin and Cis-platin (MVAC), all of which will further decrease the quality of life with persistent adverse toxicity. Our laboratory has developed a novel compound derived from the pentacyclic triterpenoid, Ursolic acid, termed N-methyl piperazine conjugated-Ursolic acid, or UA4, and have demonstrated its antitumor activities against both Gem-Sensitive (Gem-S) and Gem-Resistant (Gem-R) human advanced BC cell lines, T24 and 5637. We tested the combination of Gem, UA4 and Gem + UA4 in a murine non-MIBC model (MB49) to investigate the role of immune cell infiltration during tumor development and treatment response. UA4 treatment was equally effective in chemo-sensitive and chemo-resistant cell lines at dosages between 4-5µM. Previous in vitro mechanistic studies on UA4 and UA4+Gem combination treatments revealed cell death occurred through apoptosis and autophagy, along with a highly selective form of mitochondrial-mediated autophagy (mitophagy). These findings were confirmed with transmission electron microscopy ultrastructural analysis, cell cycle phase analyses, excess, changes in mitochondrial membrane potential and reactive oxygen species measurements. Gem-S and Gem-R xenografts in athymic mice further supported UA4’s efficacy in vivo, demonstrating a significant reduction in both tumor weight and volume following oral gavage (100mg/kg), with mice exhibiting no signs of systemic toxicity. Combination treatment with UA4 and Gem synergistically increased antiproliferative activity. MB49 syngeneic mice model further supported UA4 as an effective therapy, and immunofluorescence assays with immune-related markers, suggested an anti-inflammatory effect in vivo. Overall, we demonstrate UA4 has a potential to be used as an efficacious, non-toxic compound for further adjuvant use in clinical settings. Citation Format: Juliette Rose Seremak, Kunj Bihari Gupta, Siva S. Panda, Bal L. Lokeshwar. A triterpenoid derivative has strong antitumor activities in gemcitabine-resistant advanced bladder cancer models and promotes immune cell infiltration in a high grade murine syngeneic model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4558.

Identification of immunogenic cell death-related genes involved in Alzheimer’s disease

Alzheimer's disease (AD) is the leading cause of dementia worldwide, with recent studies highlighting the potential role of immunogenic cell death (ICD) in the pathogenesis of this neurodegenerative disorder. A total of 52 healthy controls and 64 patients with AD were included. Compared to the controls, the patients with AD exhibited 2392 differentially expressed genes (DEGs), of which 1015 and 1377 were upregulated and downregulated genes, respectively. Among them, nine common genes were identified by intersecting the AD-related module genes with the DEGs and ICD-associated genes. Gene ontology (GO)analysis further revealed “positive regulation of cytokine production” as the most significant term. Moreover, the enriched molecular functions were primarily related to the inflammatory body complex, while the overlapping genes were significantly enriched in lipopolysaccharide binding. Kyoto encyclopedia of genes and genomes (KEGG) analysis also indicated that these overlapping genes were mainly enriched in immunity, inflammation, and lipid metabolism pathways. Furthermore, the following four hub genes were detected using machine learning algorithms: P2RX7, HSP90AA1, NT5E, and NLRP3. These genes demonstrated significant differences in expression between the AD and healthy control groups (P < 0.05). Additionally, the area under the curve values of these four genes were all > 0.7, indicating their potential diagnostic value for AD. We further validated the protein levels of these four genes in the hippocampus of 3xTg-AD and C57BL/6J mice, showing P2RX7 and HSP90AA1 expression levels consistent with the previously analyzed trends. Finally, the single-sample gene set enrichment analysis (ssGSEA) algorithm provided additional evidence by demonstrating the crucial role of immune cell infiltration and its link with the hub genes in AD progression. Our study results suggest that ICD-mediated elevation of HSP90AA1 and P2RX7 levels and the resulting induction of tau hyperphosphorylation and neuroinflammation are vital in the AD pathogenic mechanism.

Decreased TLR7 expression was associated with airway eosinophilic inflammation and lung function in asthma: evidence from machine learning approaches and experimental validation

BackgroundAsthma is a global public health concern. The underlying pathogenetic mechanisms of asthma were poorly understood. This study aims to explore potential biomarkers associated with asthma and analyze the pathological role of immune cell infiltration in the disease.MethodsThe gene expression profiles of induced sputum were obtained from Gene Expression Omnibus datasets (GSE76262 and GSE137268) and were combined for analysis. Toll-like receptor 7 (TLR7) was identified as the core gene by the intersection of two different machine learning algorithms, namely, least absolute shrinkage and selector operation (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), and the top 10 core networks based on Cytohubba. CIBERSORT algorithm was used to analyze the difference of immune cell infiltration between asthma and healthy control groups. Finally, the expression level of TLR7 was validated in induced sputum samples of patients with asthma.ResultsA total of 320 differential expression genes between the asthma and healthy control groups were screened, including 184 upregulated genes and 136 downregulated genes. TLR7 was identified as the core gene after combining the results of LASSO regression, SVM-RFE algorithm, and top 10 hub genes. Significant differences were observed in the distribution of 13 out of 22 infiltrating immune cells in asthma. TLR7 was found to be closely related to the level of several infiltrating immune cells. TLR7 mRNA levels were downregulated in asthmatic patients compared with healthy controls (p = 0.0049). The area under the curve of TLR7 for the diagnosis of asthma was 0.7674 (95% CI 0.631–0.904, p = 0.006). Moreover, TLR7 mRNA levels were negatively correlated with exhaled nitric oxide fraction (r = − 0.3268, p = 0.0347) and the percentage of peripheral blood eosinophils (%) (r = − 0.3472, p = 0.041), and positively correlated with forced expiratory volume in the first second (FEV1) (% predicted) (r = 0.3960, p = 0.0071) and FEV1/forced vital capacity (r = 0.3213, p = 0.0314) in asthmatic patients.ConclusionsDecreased TLR7 in the induced sputum of eosinophilic asthmatic patients was involved in immune cell infiltration and airway inflammation, which may serve as a new biomarker for the diagnosis of eosinophilic asthma.

Identification and validation of a ferroptosis-related signature for prediction of the prognosis and tumor microenvironment in patients with chromophobe renal cell carcinoma

BackgroundFerroptosis is a novel form of regulated cell death that is different from other forms, which has an important role in tumor growth inhibition. The purpose of this study was to construct and validate a prognostic signature related to ferroptosis in chromophobe renal cell carcinoma (ChRCC) and to explore its role in immune cell infiltration and systemic therapy.MethodsThe gene expression profiles of ChRCC patients obtained from The Cancer Genome Atlas (TCGA) database were used to identify differentially expressed prognostic ferroptosis-related genes (FRGs) by univariate Cox proportional hazards analyses. Ferroptosis molecular subtypes were obtained by consensus clustering analysis. The FRG-based signature in the training set was established by least absolute shrinkage and selection operator analysis and verified in the testing set. The association between molecular subtypes and the prognostic signature and immune microenvironment was explored to predict responses to immunotherapy. Immunohistochemistry was used to verify expression of the FRG-based signature externally.ResultsChRCC patients were divided into two FRG subtypes. Two FRGs (TFRC and SLC7A11) were identified to construct the prognostic signature. The high-risk group and cluster 2 had worse overall survival than the low-risk group and cluster 1, respectively. The low-risk group and cluster 1 had higher levels of immune cell infiltration and expression of MHC and immune checkpoint molecules than the high-risk group and cluster 2. The risk score was a predictor of overall survival and had a good predictive ability, which was verified in the testing set and evaluated by ROC and calibration curves. The high-risk group had a higher tumor mutation burden. The different sensitivities of targeted drugs in patients with different risks were evaluated. External immunohistochemical analysis showed that TFRC and SLC7A11 were highly expressed in tumor tissues compared with para-cancer normal tissues, and the expression level was significantly associated with a more advanced stage and worse cancer-specific survival.ConclusionsAn FRG signature was identified and validated to predict the clinicopathological features and prognosis of ChRCC. A significant association between the signature and immune cell infiltration, immune checkpoint expression, and drug response is helpful to guide comprehensive treatment of ChRCC.

Single-cell landscape and spatial transcriptomic analysis reveals macrophage infiltration and glycolytic metabolism in kidney renal clear cell carcinoma.

The present study investigates the clinical relevance of glycolytic factors, specifically PGAM1, in the tumor microenvironment of kidney renal clear cell carcinoma (KIRC). Despite the established role of glycolytic metabolism in cancer pathophysiology, the prognostic implications and key targets in KIRC remain elusive. We analyzed GEO and TCGA datasets to identify DEGs in KIRC and studied their relationship with immune gene expression, survival, tumor stage, gene mutations, and infiltrating immune cells. We explored Pgam1 gene expression in different kidney regions using spatial transcriptomics after mouse kidney injury analysis. Single-cell RNA-sequencing was used to assess the association of PGAM1 with immune cells. Findings were validated with tumor specimens from 60 KIRC patients, correlating PGAM1 expression with clinicopathological features and prognosis using bioinformatics and immunohistochemistry. We demonstrated the expression of central gene regulators in renal cancer in relation to genetic variants, deletions, and tumor microenvironment. Mutations in these hub genes were positively associated with distinct immune cells in six different immune datasets and played a crucial role in immune cell infiltration in KIRC. Single-cell RNA-sequencing revealed that elevated PGAM1 was associated with immune cell infiltration, specifically macrophages. Furthermore, pharmacogenomic analysis of renal cancer cell lines indicated that inactivation of PGAM1 was associated with increased sensitivity to specific small-molecule drugs. Altered PGAM1 in KIRC is associated with disease progression and immune microenvironment. It has diagnostic and prognostic implications, indicating its potential in precision medicine and drug screening.