Immune Cell Infiltration Research Articles

Novel Aortic Dissection Model Links Endothelial Dysfunction and Immune Infiltration.

Aortic dissection (AD) is the separation of medial layers of the aorta and is a major cause of death in patients with connective tissue disorders such as Marfan syndrome. However, molecular triggers instigating AD, its temporospatial progression, and how vascular cells in each vessel layer interact and participate in the pathological process remain incompletely understood. To unravel the underlying molecular mechanisms of AD, we generated a spontaneous AD mouse model. We incorporated a novel missense variant (p.G234D) in FBN1, the gene for fibrillin-1, identified in a patient with nonsyndromic familial AD into mice using the CRISPR/Cas9 system. We performed molecular pathological analyses of the aortic lesions by histology, immunofluorescence staining, electron microscopy, synchrotron-based imaging, and single-cell RNA sequencing. Biochemical analysis was performed to examine the binding capacity of mutant human FBN1G234D protein to LTBPs (latent TGFβ [transforming growth factor-beta] binding proteins), and signaling pathways in the mutant aortic wall were examined by the Western blot analysis. Fifty percent of the Fbn1G234D/G234D mutant mice died within 5 weeks of age from multiple intimomedial tears that expanded longitudinally and progressed to aortic rupture accompanied by massive immune cell infiltration. Fbn1G234D/G234D endothelial cells exhibited altered mechanosensing with loss of parallel alignment to blood flow and upregulation of VCAM-1 and ICAM-1 as early as 1 week of age. Single-cell RNA sequencing, validated by immunostaining, revealed a cluster of monocyte/macrophage predominantly in the intima at 3 weeks of age before the dissection, and the second cluster of macrophages increased during the progression of intimomedial tears, exhibiting strong CCR2+ and both M1- and M2-like features. Consistently, upregulation of MMP2/9 was observed. Biochemically, FBN1G234D lost the ability to bind to LTBP-1, -2, and -4, resulting in the downregulation of TGFβ signaling in the aortic wall. We show that interactions involving endothelial cells and macrophages/monocytes in the intima, where the ECM (extracellular matrix) microenvironment contains reduced TGFβ signaling, contribute to the initiation of AD. Our novel AD mouse model provides a unique opportunity to identify target molecules involved in the intimomedial tears that can be utilized for the development of therapeutic strategies.

KLF12 as a potential biomarker for lateral pelvic lymph node metastases in advanced rectal cancer

Rectal cancer accounts for approximately 40% of colorectal cancer cases, and lateral pelvic lymph node (LPLN) metastasis in rectal cancer significantly increases the local recurrence rate. Despite its clinical significance, studies on the molecular biology of LPLN metastasis are relatively scarce. In this study, we aimed to elucidate the underlying mechanisms by identifying hub regulatory genes in LPLN tissues and analyzing differentially expressed genes shared between tumor and pericarcinomatous tissues within our clinical cohort. To investigate the biological functions of these hub regulatory genes, we performed GSEA, GO, and KEGG pathway analyses on mRNA-Seq data. Among the identified hub genes, KLF12 emerged as a pivotal regulatory gene in rectal cancer. We further explored its clinical relevance and biological function. Our findings, validated using public databases, clinical cohort data, and immunohistochemistry (IHC), identified KLF12 as a specific marker for LPLN. Additionally, KLF12 expression exhibited a strong correlation with disease-free survival (DFS). According to clinical data, significant differences in KLF12 expression exist between groups based on factors such as age, gender, tumor location, pathological N stage, and postoperative tumor residue. Both treatment outcomes (DFS) and receiver operating characteristic curves (AUCs) were significantly associated with KLF12 expression. Furthermore, KLF12 demonstrated a strong association with immune cell infiltration, immune checkpoint expression, and immunophenoscore (IPS), indicating its potential regulatory role in immunotherapy. Functional molecular experiments revealed that KLF12 overexpression inhibited the proliferation, migration, and invasion of SW620 cells. In conclusion, leveraging mRNA-Seq data, TCGA database analysis, immune infiltration data, and biological function assessments, we confirmed that KLF12 could serve as an effective predictive marker and potential therapeutic target for LPLN metastasis. These findings suggest that KLF12 may be instrumental in assessing predictive risk and identifying novel therapeutic targets for patients with rectal cancer.

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.

Age dependent susceptibility and immune responses to La Crosse virus infection in non-human primates

La Crosse virus (LACV) is a primary cause of pediatric viral encephalitis in the United States but rarely causes disease in adults. We tested whether cynomolgus macaques displayed a similar age-dependent susceptibility to LACV. Immune responses from naïve or LACV infected weanling (9–15 months), juvenile (19–23 months) or adult (> 6 years) animals were measured and infected animals were monitored for disease. Naïve weanling animals had fewer dendritic cells in their blood and weaker induction of IFN-stimulated genes (ISG) and chemokines when PBMCs were stimulated in vitro. While no infected animals developed disease, the weaker innate response in naive weanlings correlated with increased viral RNA in plasma from 2 of 3 infected weanlings out to 7 days post infection (dpi). Activated CD8+ T cells and neutralizing antibody proportions were similar amongst all ages. However, CD4+ T cells proportions were increased in young animals relative to adults. This suggests the CD4+ adaptive response in young animals may be bolstering an initially weak innate response to clear virus. Finally, because macaques were resistant to disease, we infected 3 common marmosets intranasally with LACV. Marmoset were selected due to their susceptibility to viral encephalitis. Although no animals showed disease signs, one animal had evidence of infection in the nasal mucosa out to 23 days with associated vacuolization, edema and immune cell infiltration.

Arginine methylation modulates tumor fate and prognosis in clear cell renal cell carcinoma

BackgroundArginine methylation, a key post-translational modification, plays a pivotal role in regulating various cellular processes and has been implicated in cancer progression. However, the potential of arginine methylation-related genes as prognostic markers in clear cell renal cell carcinoma (ccRCC) remains underexplored.MethodsWe utilized public transcriptomic datasets from TCGA, E-MTAB-1980 and ICGC, for model construction and validation. Single-cell RNA sequencing datasets were employed to evaluate gene expression patterns at the cellular level. Consensus clustering, KM survival analysis, and GSVA were applied to identify molecular subtypes and related pathways. Univariate and multivariate Cox regression analyses were applied to develop an arginine methylation-related signature (AMS). Immune profiling, mutation landscape, and drug sensitivity prediction were also employed to explore the model’s association with clinical features, immune infiltration, mutation burden, and therapeutic responses.ResultsThe AMS demonstrated robust prognostic performance, with consistent validation across external cohorts. High-risk patients exhibited significantly worse survival, elevated TMB, and an immunosuppressive tumor microenvironment characterized by increased infiltration of regulatory immune cells. Single-cell RNA sequencing revealed key prognostic genes expressed predominantly in cancer and immune cells, supporting their role in tumor progression and immune interactions.ConclusionThe arginine methylation-based prognostic model provides a reliable framework for survival risk stratification in ccRCC and holds promise for guiding personalized therapeutic strategies. Future research should emphasize clinical validation of this model and explore its potential role in optimizing immunotherapy and targeted treatment strategies for ccRCC.

Bioinformatics and experimental validation of ferroptosis-related genes in steroid-induced osteonecrosis of the femoral head

BackgroundSteroid-induced osteonecrosis of the femoral head (SONFH) is a progressive condition that causes increasing disability. It is thought to result from reduced blood flow and oxygen levels in the femoral head, with reactive oxygen species (ROS) playing a key role in triggering ferroptosis. However, the role of ferroptosis in SONFH progression remains underexplored. This study aimed to identify and validate key genes associated with ferroptosis in SONFH using bioinformatics.MethodsThe study analyzed the SONFH dataset GSE123568, which includes data from 30 SONFH patients and 10 controls. Weighted gene co-expression network analysis (WGCNA) was used to identify differentially expressed genes (DEGs) between the SONFH and control groups. Core genes were identified by intersecting DEGs with ferroptosis-related genes retrieved from FerrDb V2. The diagnostic performance of the key genes was assessed using the receiver operating characteristic (ROC) curve, and a predictive nomogram model was developed. Interaction analysis of these genes was conducted to explore their link with immune infiltration. The expression of these genes in bone tissue from SONFH patients was validated. Finally, drug-protein interactions were predicted using the DSigDB database.ResultsDifferential expression analysis identified 384 DEGs, which were significantly involved in inflammatory pathways. WGCNA revealed four key genes after intersecting DEGs with relevant module genes and ferroptosis-related genes. A nomogram model based on these genes demonstrated strong reliability and validity. Immune infiltration analysis showed significant differences between SONFH patients and controls, with notable associations between immune cell infiltration and the expression of the four core genes. Validation through quantitative real-time PCR (qRT-PCR) and Western blot confirmed that the expression of GCLC, GABARAPL2, CISD2, and NCOA4 was significantly lower in SONFH bone tissue compared to controls (P < 0.05). Additionally, potential therapeutic drugs targeting these genes, including Diethyl sulfate, Meloxicam, and NIMUSTINE, were predicted.ConclusionThis study identifies GABARAPL2, CISD2, NCOA4, and GCLC as potential diagnostic biomarkers associated with immune cell infiltration in SONFH, offering new insights for future research and clinical applications.

Prognostic Implications and Therapeutic Potential of MXD Genes in Gastric Cancer.

MAX dimerization (MXD) genes play integral roles in various types of tumors. The expression patterns, prognostic value, potential mechanisms, and roles in immunotherapy of MXD genes in gastric cancer (GC) remain not fully elucidated. We aimed to explore the role of MXDs in GC. The Wilcoxon rank sum test and t-test were employed to evaluate the differential expression of the MXD gene family members in GC tissues compared to non-paired normal gastric tissues. cBioPortal was utilized for examining genetic alterations within the MXD gene family. R software, specifically version 3.6.3, was used to scrutinize the expression patterns of MXD genes in GC, their correlation with clinical parameters, and to generate a correlation heat map. The survival package (v3.2-10) and the Cox regression model were implemented to evaluate the prognostic significance of the MXD gene family. The pROC package (v1.17.0.1) was applied to assess the diagnostic potential of the MXD gene family. R software (v3.6.3) was also used to explore potential regulatory networks involving members of the MXD gene family and related genes. The GSVA package (v1.34.0) was leveraged to investigate the link between the expression of the MXD gene family and immune cell infiltration. Visualization was facilitated by the ggplot2 (v3.3.3), survminer (v0.4.9), and clusterProfiler (v3.14.3) packages. Gene Set Cancer Analysis (GSCA) was employed to determine the sensitivity of the MXD gene family's expression to drugs from the GDSC database. The expression levels of MXD genes were validated across various cell lines using quantitative real-time PCR (qRT-PCR). MXD1 was significantly upregulated in GC, while MXD3 and MXD4 were significantly downregulated. Significant correlations were identified between the expression levels of MXD3 and the T stage (p = 0.041) and age (p = 0.001) of GC patients. Additionally, a notable association was observed between MXD4 expression and the histologic grade (p = 0.006) in GC patients. Low MXD3 expression was associated with a poor prognosis in GC. Low MXD3 expression was an independent prognostic factor for poor outcomes in GC patients. MXD3 demonstrated some accuracy in predicting tumor and normal tissue outcomes (AUC = 0.884). MXDs mediate gastric carcinogenesis and progression by regulating immune cells and pathways, including endocytosis, cell cycle, and apoptosis. The expression of the MXD gene family was associated with immune cell infiltration and drug sensitivity. MXD3 and MXD4 expression levels were significantly downregulated in GC cell lines, while MXD1 expression was significantly upregulated. The MXD gene family may serve as novel biomarkers of poor prognosis and as potential immunotherapeutic targets for GC.

High Flavonoid Content in Apium graveolens Nanocrystals Improves Colitis in Dextran Sodium Sulfate-induced Colitis Mice.

To develop medicinal plant nanoparticles as colitis alternative/supplementary therapy. Limited reports exist on the effectiveness of medicinal plant nanocrystals in treating or preventing colitis. We investigated the effect of canonizing Apium graveolens (AG) on improving dextran sodium sulfate (DSS)- induced (4%) colitis. Nanonization was performed via the bead milling process. The nanocrystal product was characterized (i.e., particle size, zeta potential (ZP), polydispersity index (PDI) values) and freezedried. Total flavonoids and phenolic compounds in nanocrystal products were compared with ethanolic extract of AG (AGEE). Anti-colitis activity of AG-nanocrystal water suspensions (AGNS) was compared to AG bulk powder suspensions (AGBS). Colitis severity was determined via physiological, macroscopic, and microscopic colon assessment. In addition, the fecal Enterobacteriaceae population and urine glucose levels were determined. The AG nanoparticle products are 200-400 nm, with PDI values 0.5-0.6, and ZP values -12 to -20 mV. The total flavonoid and phenolic compounds of AGNS were 115.12±4.32 ppm and 37.11±0.34 ppm, respectively. This value is higher compared to the content in AGEE. AGNS (350 mg/kg) improves physiological (i.e., fecal blood), macroscopic (i.e., length, diameter), and microscopic (i.e., structure and immune cell infiltration) colon conditions in a comparable level to the positive control of 5-aminosalicylic acid (100 mg/kg). AGNS have a compelling ability to restore colon microscopic and Enterobacteriaceae population compared to AGBS (700 mg/kg). AGNS (350 mg/kg) also recovered colon permeability as marked by the lower urine glucose concentration (9.90±0.15 mg/dL) compared to colitis mice (12.43±0.09 mg/dL). The nanonization of AG contributes to improved anti-colitis activities compared to AGBS. Nanonization of medicinal plants will reduce organic solvent extraction, which supports the sustainable development goals.

Exploring shared pathogenic mechanisms and biomarkers in hepatic fibrosis and inflammatory bowel disease through bioinformatics and machine learning

BackgroundThe coexistence of hepatic fibrosis (HF) and inflammatory bowel disease (IBD) represents a significant clinical concern due to their poorly characterized shared pathogenic mechanisms. Current limitations in identifying common biomarkers for comorbid cases impede early dual diagnosis and therapeutic interventions.MethodsDifferentially expressed genes (DEGs) were screened, followed by Weighted Gene Co-expression Network Analysis (WGCNA) to identify disease-associated modules. The key diagnostic biomarkers were determined via a protein-protein interaction (PPI) network combined with two machine learning algorithms. The logistic regression model was subsequently developed based on these key genes. Immune cell infiltration profiling of both diseases was assessed via the CIBERSORT algorithm. The construction of genes-miRNAs and genes-TFs (Transcription Factors) regulatory networks were based on the NetworkAnalyst website. Potential drug-gene interactions were predicted utilizing the DSigDB database. The expression and distribution of these genes were validated through single-cell sequencing analysis.ResultsA sum of 119 up-regulated genes and 17 down-regulated genes were screened, which were enriched in categories associated with immune cell infiltration and chemotaxis, cytokine regulation, metabolic processes, enzymatic activity, and extracellular matrix deposition, based on enrichment analysis. WGCNA revealed four disease-associated gene modules. Four shared diagnostic genes for both diseases were screened, including MMP2, COL1A2, STAT1, and CXCL1. ROC curve analysis confirmed robust diagnostic performance as AUC > 0.7 for individual genes and AUC > 0.85 for combined model. M1 macrophages were significantly increased in both pathologies of diseases. A total of 462 drugs were predicted targeting these biomarkers in the DSigDB database. The four key diagnostic gene expression patterns across diverse cell subpopulations were visualized by single-cell sequencing analysis.ConclusionMMP2, COL1A2, CXCL1, and STAT1 were identified as shared biomarkers for IBD and HF, providing a molecular basis for early diagnosis and precision medicine approaches. It elucidated the similarities between HF and IBD in terms of immunity, metabolism, and fibrosis.

Mitochondria-related genes as prognostic signature of endometrial cancer and the effect of MACC1 on tumor cells.

Mitochondria are essential organelles involved in cell metabolism and are closely linked to various metabolic disorders. In this study, we aimed to develop a prognostic model for endometrial cancer (EC) patients based on mitochondria-related genes (MRGs), and to investigate the role of MACC1 in EC. As shown in the graphic summary, we retrieved gene expression and clinical data from open-access databases. To construct a predictive signature, we applied the Lasso Cox regression algorithm to MRGs. The predictive performance, immune features, and anti-tumor response of the mitochondrial signature were evaluated through multiple algorithms. Additionally, expression levels of key genes were validated using quantitative Real-Time PCR and Western Blot. A total of 2030 MRGs were retrieved, and 267 were found to be prognostically relevant. Eight MRGs-MACC1, CMPK2, NDUFAF6, DUSP18, TOMM40L, MT-TP, SAMM50, and MAIP1-were identified to construct a prognostic signature for EC. The MRG signature demonstrated significant associations with drug sensitivity, immune therapy, and immune cell infiltration. Based on comprehensive bioinformatic analysis, MACC1 was identified as the most promising MRG candidate in EC. Systematic experimental validation, including both in vitro and in vivo approaches, demonstrated that MACC1down-regulationsignificantly suppressed EC progression, highlighting its potential as a therapeutic target.

Systemic Inactivation of TREX1 Induces Selective Inflammation of the Tumor Microenvironment and Invigorated T Cell-Mediated Tumor Control.

Therapeutic innate immune stimulation within the tumor microenvironment can potentiate endogenous antitumor T cell immunity. Strategies for controlled activation of cGAS/STING signaling are currently under intense investigation. DNase 3'-repair exonuclease 1 (TREX1) is essential for cellular DNA disposal, which prevents autoimmunity ensuing from cGAS/STING activation by endogenous DNA. TREX1-deficient tumor cells elicit enhanced protective immunity in syngeneic models. Here, we showed that induced inactivation of the Trex1 gene in host (non-cancer) cells yields improved type I IFN- and T cell-dependent control of established TREX1-competent tumors. Host TREX1 deficiency was well tolerated and triggered selective immune cell infiltration into tumors but not into other tissues. Induced systemic loss of TREX1 in tumor-bearing mice resulted in enhanced intra-tumoral T cell proliferation and massive increase in numbers of effector and effector-like 'exhausted' cells, enabling complete rejection in combination with checkpoint inhibition. To conclude, systemic TREX1 inhibition is a promising approach to boost anti-tumor immunity and to overcome immune evasion mediated by cancer cell-intrinsic cGAS/STING inactivation.

Tumour-infiltrating immune cells as a novel prognostic model for bladder cancer

Bladder cancer (BLCA) is the tenth most commonly diagnosed cancer and poses a significant challenge due to its complexity and associated high morbidity and mortality rates in the absence of optimal treatment. The tumor microenvironment (TME) is recognized as a critical factor in tumor initiation, progression and therapeutic response, and offers numerous potential targets for intervention. A comprehensive understanding of immune infiltration patterns in BLCA is essential for the development of effective prevention and treatment strategies. In this study, bioinformatics analysis was used to identify differentially expressed genes (DEGs) and tumor-infiltrating immune cells (TIICs) between BLCA tissues and adjacent normal tissues. Weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) analysis were used to identify the top 10 hub genes with the most significant co-expression effects, and their potential relationship with patient prognosis was then predicted. The random survival forest (RSF) model was used to further identify six variables among the hub genes and establish a novel scoring system, defined as the tumor-infiltrating immune score (TIIS) to predict the prognosis of BLCA patients. In addition, the correlation analysis between TIIS and drug sensitivity was investigated using the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) databases. Patients with high TIIS were found to have a poor prognosis but may be more sensitive to Cisplatin and certain novel agents. This study provided a systematic analysis of immune cell infiltration in BLCA and established TIIS to predict patient prognosis and the efficacy of specific drugs in the treatment of BLCA.

Knockdown NEK7 stimulates anti-tumor immune responses by NLRP3/PD-L1 signaling in esophageal cancer

BackgroundEsophageal cancer is a prevalent malignancy with limited treatment options. The study aimed to understand the role and mechanism of NEK7 in esophageal cancer development.MethodsRNA sequencing compared esophageal cancer tissues with adjacent tissues, and real-time PCR validated NEK7 expression. Co-IP identified NLRP3 as NEK7’s binding partner. We also study the effects of NEK7 knockdown on cell viability, apoptosis, migration, invasion, and the expression of NLRP3/PD-L1 in esophageal carcinoma cell lines. TIMER 2.0 analyzed immune infiltration. An animal model was used to investigate the impact of NEK7 knockdown on tumor size, survival rates, and immune cell infiltration. Licochalcone B blocked NEK7/NLRP3, enhancing CD8 T cell-mediated tumor killing. PD-1’s role in T cell viability was also assessed.ResultsNEK7 was observed to be markedly elevated in both tumor tissues of esophageal cancer and EC109 cells. Moreover, silencing NEK7 reduced cell viability, migration, and invasion, while enhancing cell apoptosis in vitro. Knockdown of NEK7 caused a notable reduction in levels of NLRP3 and PD-L1 in EC109 cells. NEK7 expression showed a positive correlation with immune cell infiltration. Knockdown of NEK7 decreased PD-L1 expression, while upregulation of NEK7 increased PD-L1 expression, then reversed by NLRP3 knockdown. In animal studies, NEK7 knockdown reduced tumor size and volume while improving survival. It also promoted CD4 and CD8 T cell infiltration while inhibiting Treg cells and PD-1 + CD4 and CD8 T cells. Licochalcone B blocked NEK7/NLRP3 binding, decreased cell viability of EC109 cells, and enhanced the activity of co-cultured CD8 T cells. Furthermore, Licochalcone B and anti-PD-1 treatment increased the killing ratio of EC109 cells.ConclusionIn conclusion, NEK7 is a key regulator in the progression of esophageal cancer and the immune evasion. Targeting the NEK7/NLRP3 pathway may have therapeutic potential for the treatment of esophageal cancer.Graphical abstract

Intrapleural dual blockade of IL-6 and PD-L1 reprograms CAF dynamics and the tumor microenvironment in lung cancer-associated malignant pleural effusion

BackgroundMalignant pleural effusion (MPE) is a severe complication in lung cancer, characterized by an immunosuppressive tumor microenvironment (TME) and limited therapeutic options. This study investigates the role of IL-6 in regulating immune suppression and tumor progression in MPE and evaluates the efficacy of dual IL-6 and PD-L1 blockade.MethodsIL-6 levels were measured in MPE and paired serum samples from lung cancer patients, and correlations with PD-L1 expression and clinical outcomes were analyzed using publicly available datasets. RNA sequencing and immune deconvolution were used to assess immune cell infiltration. CAFs and immune cell infiltration were further evaluated using flow cytometry, immunohistochemistry, and multiplex immunofluorescence. In vitro co-culture systems were employed to simulate the MPE microenvironment and explore IL-6 interactions with CAFs, as well as its regulatory effect on tumor cell PD-L1 expression.ResultsIL-6 levels were significantly elevated in MPE compared to paired serum and correlated with higher PD-L1 expression and poor survival outcomes in lung cancer patients. In the MPE mouse model, combination therapy with IL-6 and PD-L1 blockade reduced MPE volume, tumor burden, and PD-L1 expression, while enhancing T cell infiltration and alleviating TME immunosuppression. IL-6 was found to drive a positive feedback loop with iCAFs, promoting an immunosuppressive environment. In vitro, IL-6 from the MPE upregulated tumor cell PD-L1 expression the IL-6/STAT3 pathway.ConclusionThis study identifies IL-6 as a critical contributor of immune suppression and tumor progression in MPE. The combination of IL-6 and PD-L1 blockade effectively alleviated immunosuppression and reduced tumor burden, offering a potential therapeutic approach for MPE management.

A Novel Diagnostic and Subtype Classification Model Based on RNA N6-Methyladenosine Regulators for Behçet’s Uveitis

ABSTRACT Purpose To investigate the role of RNA N6-methyladenosine (m6A) regulators in the diagnosis and subtype classification of Behçet’s uveitis, aiming to establish a novel predictive model and explore distinct molecular patterns for personalized therapeutic approaches. Methods Data from the Gene Expression Omnibus GSE209567 dataset comprising 22 Behçet’s uveitis patients and 15 controls were analyzed for m6A regulator expression. Differentially expressed genes were identified using the “limma” R package, followed by random forest (RF) and support vector machine (SVM) model construction to select critical m6A regulators. A nomogram model was developed for prediction, and consensus clustering identified distinct m6A and gene-regulating patterns. Immune cell infiltration analysis was conducted using ssGSEA, and m6A scores were computed to quantify molecular patterns. Results Eleven m6A regulators were significantly differentially expressed. The top four candidate m6A regulators (FTO, YTHDF2, CBLL1, and METTL14) were identified to predict the risk of Behçet’s uveitis. A nomogram was constructed based on the four candidate m6A regulators to visualize the association between the expression levels of the candidate with the risk of onset of Behçet’s uveitis. Two distinct m6A patterns and gene patterns were identified, validated by consensus clustering. High m6A scores were associated with more severe disease stages, with differential immune cell infiltration observed between subtypes. Immune-related genes, such as LRRN3 and DAAM2, were identified as key in differentiating m6A patterns. Conclusion M6A modification plays an important role in the occurrence of uveitis. Distinct m6A patterns and gene clusters highlight their potential for early diagnosis and personalized treatment.

IL-33/ST2 drives inflammatory pain via CCL2 signaling and activation of TRPV1 and TRPM8

Innate immunity is the first line of host defense and contributes to pain. However, how innate immune system interacts with sensory neurons to govern pain remains poorly understood. Here, we report that interleukin 33(IL-33) initiates pain hypersensitivity that requires chemokine (C-C motif) ligand 2 (CCL2) secretion from infiltrated macrophages and neutrophils and activation of transient receptor potential vanilloid 1 (TRPV1) and transient receptor potential melastatin 8 (TRPM8) channels in sensory neurons. Blocking CCL2 receptor (CCR2) attenuates IL-33- induced and Complete Freund’s adjuvant (CFA)-induced thermal hyperalgesia and blocking TRPV1 and TRPM8 attenuates IL-33-induced mechanical and thermal hypersensitivity and cold allodynia respectively. Furthermore, depletion of macrophages reduces IL-33-induced pain and expression of CCL2 and suppression of tumorigenicity 2 (ST2) in hindpaw skin and inhibition of CCR2 prevents recruitment of macrophages and neutrophils. Our findings reveal an unrecognized neuroimmune crosstalk of IL-33-CCL2 signaling from infiltrated immune cells with TRPV1/TRPM8 in sensory neurons to facilitate pain states.

DNA glycosylase (NEIL3) overexpression associated with low tumor immune infiltration and poor overall patient survival in endometrial cancer

Endometrial cancer (EC) is the most common gynecological malignancy. Although prognosis is favorable for patients with an early-stage disease, those with recurrent or more advanced disease have low response rates to chemotherapy and poor clinical outcomes. Previously, we have shown that DNA repair gene (NEIL3) is required for retaining replication fork integrity during replication stress. Here, we examined whether the overexpression of NEIL3 in endometrial cancer associated with altered genomic instability, tumor immunogenicity and anti-tumor immunity in endometrial tumor. In this study, we show that endometrial cancer patients with tumors that a have high NEIL3 expression associated with worse overall survival (OS) outcomes in patients. In addition, tumor with high NEIL3 expression is associated with high number of mutation and chromosomal instability. Furthermore, NEIL3 expression in EC tumors positively correlated with mutation of DNA polymerase eta (POLE) and TP53 as well as high expression of replicative polymerases genes (POLE, POLD1 and POLA1). In contrast, tumor with high NEIL3 expression exhibit low tumor immunogenicity and poor anti-tumor immune cell infiltration. Our findings may have important clinical implications for utilizing NEIL3 as a potential prognostic biomarker to stratify EC patients and as a target to enhance immunotherapy response in endometrial cancer. However, our NEIL3 overexpression associated observation still requires further experimental-based scientific validation studies.

Exploration on the potential predictive value of regulator of G-protein signaling 2 in the efficacy of concurrent chemoradiotherapy on cervical squamous cell carcinoma

Objective: Concurrent chemotherapy and radiotherapy (CCRT) has been applied as a therapeutic modality for cervical squamous cell carcinoma (CESC). Our aim is to investigate the potential marker(s) of the efficacy of CCRT in CESC. Material and Methods: Potential candidates predictive of the efficacy of CCRT in CESC were identified. Differentially expressed genes (DEGs) were screened, followed by performing functional enrichment analyses. CCRT-related biomarkers were identified. In addition, the CIBERSORT algorithm was employed to determine the immune cell infiltration. Immune cell subsets from donors and specific cytokines were evaluated, and the biological functions of CESC cells following cisplatin treatment or coculture with M2 macrophages were explored. Results: A total of 56 DEGs were singled out. These DEGs were enriched in pathways relevant to CESC and CCRT. They were narrowed down to eight CCRT-related biomarkers with good predictive values. Notably, most of the biomarkers were negatively correlated with M2 macrophages (P < 0.05), and regulator of G-protein signaling 2 (RGS2) exhibited low expression in CESC (P < 0.05). Flow cytometry results revealed that patients with CCRT-resistant CESC had high percentages of M2 macrophages, CD4 T cells, regulatory T cells and T helper 2 cells but low percentages of T helper 1 cells, and T helper 17 cells, M1 macrophages, and CD8 T cells (P < 0.05). Aside from interleukin (IL4) and IL-10, the remaining specific cytokines exhibited low expression in patients with CCRT-resistant CESC (P < 0.05). Furthermore, the cell cycle progression and metastasis of CESC cells were evidently promoted by M2 macrophages but were suppressed by cisplatin intervention (P < 0.05). Moreover, in CESC cells, cisplatin repressed the levels of IL-4 and IL-10 yet boosted those of the remaining cytokines, whereas M2 macrophages had the opposite effects (P < 0.05). RGS2 silencing promoted the phosphorylation of phosphatidylinositol 3-kinase/protein kinase B/transcriptional signal transducer and activator 6 in macrophages, whereas RGS2 overexpression had the opposite effect (P < 0.05). Conclusion: This study interpreted and explored the possible predictive values of RGS2 in the efficacy of CCRT in CESC. It may provide other insights for the management of CESC.

Identification of genetic indicators linked to immunological infiltration in idiopathic pulmonary fibrosis.

This study employed bioinformatics to investigate potential molecular markers associated with idiopathic pulmonary fibrosis (IPF) and examined their correlation with immune-infiltrating cells. Microarray data for IPF were retrieved from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and module genes were identified through Limma analysis and weighted gene co-expression network analysis. Enrichment analysis and protein-protein interaction network development were performed on the DEGs. Machine learning algorithms, including least absolute shrinkage and selection operator regression, random forest, and extreme gradient boosting, were applied to identify potential key genes. The predictive accuracy was assessed through a nomogram and a receiver operating characteristic (ROC) curve. Additionally, the correlation between core genes and immune-infiltrating cells was assessed utilizing the CIBERSORT algorithm. An IPF model was established in a human fetal lung fibroblast 1 (HFL-1) through induction with transforming growth factor β1 (TGF-β1), and validation was conducted via reverse transcription-quantitative polymerase chain reaction. A sum of 1246 genes exhibited upregulation, whereas 879 genes were downregulated. Pathway enrichment analysis and functional annotation revealed that DEGs were predominantly involved in extracellular processes. Four key genes - cd19, cxcl13, fcrl5, and slamf7 - were identified. Furthermore, ROC analysis demonstrated high predictive accuracy for these 4 genes. Compared to healthy individuals, lung tissues from IPF patients exhibited an increased presence of plasma cells, CD4 memory-activated T cells, M0 macrophages, activated dendritic cells, resting NK cells, and M2 macrophage infiltration. The upregulation of cd19, cxcl13, fcrl5, and slamf7 in TGF-β1-treated HFL-1 cells was confirmed, aligning with the findings from the microarray data analysis. cd19, cxcl13, fcrl5, and slamf7 serve as diagnostic markers for IPF, providing fresh perspectives regarding the fundamental pathogenesis and molecular mechanisms associated with this condition.

Aberrant expression of CNTRL was associated with poor prognosis, immune response and progression in glioma

This study investigated the biological functions and prognostic significance of centromere protein L (CNTRL) in glioma. mRNA expression data and clinical information were obtained from TCGA, CGGA, and an independent cohort of 207 glioma patients. CNTRL expression levels were quantified using qRT-PCR. Functional analyses, including Gene Ontology and KEGG pathway enrichment, were conducted to elucidate the biological roles of CNTRL. Kaplan–Meier survival curves and Cox regression analyses were applied to evaluate its association with overall survival, and a nomogram was constructed to predict individual survival. Additionally, the tumor microenvironment and immune cell infiltration were analyzed. Glioma cell lines were transfected with CNTRL-targeting shRNA to explore its functional role in cell proliferation, migration, and invasion, utilizing CCK-8, colony formation, scratchy and Transwell assays. The results revealed that CNTRL is ubiquitously expressed in brain tissues and is significantly upregulated in glioma. Higher CNTRL expression was positively correlated with increased tumor grade and were associated with poor prognosis in glioma patients. Furthermore, univariate and multivariate Cox regression analyses identified CNTRL as an independent prognostic factor for glioma survival. The nomogram model integrating CNTRL expression and clinical parameters demonstrated robust predictive performance for patient survival. Functional enrichment analyses suggested that CNTRL is involved in key cellular processes such as cell cycle, DNA repair, and chromatin remodeling. CNTRL expression was positively associated with enhanced immune cell infiltration and activation within the tumor microenvironment, as well as with the expression of immune checkpoint molecules, implicating its potential role in immune evasion mechanisms. In vitro, CNTRL knockdown significantly inhibited glioma cell proliferation, migration, and invasion. Notably, suppression of CNTRL led to reduced expression of the cell cycle regulator WEE1 in glioma cells. This study provides comprehensive evidence that CNTRL contributes to glioma progression by regulating the cell cycle and immune-related processes. Targeting CNTRL could represent a promising therapeutic strategy for glioma. These findings underscore the potential of CNTRL as a prognostic biomarker and a therapeutic target in glioma management.