Macrophage mitochondrial bioenergetics and tissue invasion are boosted by an Atossa-Porthos axis in Drosophila.

Cellular metabolism must adapt to changing demands to enable homeostasis. During immune responses or cancer metastasis, cells leading migration into challenging environments require an energy boost, but what controls this capacity is unclear. Here, we study a previously uncharacterized nuclear protein, Atossa (encoded by CG9005), which supports macrophage invasion into the germband of Drosophila by controlling cellular metabolism. First, nuclear Atossa increases mRNA levels of Porthos, a DEAD-box protein, and of two metabolic enzymes, lysine-α-ketoglutarate reductase (LKR/SDH) and NADPH glyoxylate reductase (GR/HPR), thus enhancing mitochondrial bioenergetics. Then Porthos supports ribosome assembly and thereby raises the translational efficiency of a subset of mRNAs, including those affecting mitochondrial functions, the electron transport chain, and metabolism. Mitochondrial respiration measurements, metabolomics, and live imaging indicate that Atossa and Porthos power up OxPhos and energy production to promote the forging of a path into tissues by leading macrophages. Since many crucial physiological responses require increases in mitochondrial energy output, this previously undescribed genetic program may modulate a wide range of cellular behaviors.

FAM122A functions as a tumor suppressor in oral squamous cell carcinoma.

Family with sequence similarity 122a (FAM122A), identified as an endogenous inhibitor of protein phosphatase 2A (PP2A) previously, is involved in multiple important physiological processes, and essential for the growth of acute myeloid leukemia and hepatocellular carcinoma cells. However, the function of FAM122A in oral squamous cell carcinoma (OSCC) is undetermined. In this study, by analyzing TCGA and GEO databases, we found that the expression of FAM122A was significantly down-regulated in head and neck squamous cell carcinoma and OSCC patients, meanwhile this low expression was tightly associated with the poor prognosis and advanced clinical stage during OSCC development. The similar low expression pattern of FAM122A could also been seen in OSCC cell lines compared with normal human oral keratinocytes. Further, we demonstrated that FAM122A knockdown significantly promoted the growth, clonogenic potential as well as migration capabilities of OSCC cells, while these alterations could be rescued by the re-expression of FAM122A. Over-expression of FAM122A suppressed OSCC cell proliferation and migration. FAM122A also inhibited the epithelial-mesenchymal transition (EMT) in OSCC cells by the up-regulation of epithelial marker E-cadherin and down-regulation of mesenchymal markers Fibronectin and Vimentin, which is presumably mediated by transforming growth factor ß receptor 3 (TGFBR3), a novel tumor suppressor. In addition, FAM122A could induce T cell infiltration in OSCC, indicating that FAM122A might influence the immune cell activity of tumor environment and further interfere the tumor development. Collectively, our results suggest that FAM122A functions as a tumor suppressor in OSCC and possibly acts as a predictive biomarker for the diagnosis and/or treatment of OSCC.

Integrative Proteomics and N-Glycoproteomics Analyses of Rheumatoid Arthritis Synovium Reveal Immune-Associated Glycopeptides.

Rheumatoid arthritis (RA) is a typical autoimmune disease characterized by synovial inflammation, synovial tissue hyperplasia, and destruction of bone and cartilage. Protein glycosylation plays key roles in the pathogenesis of RA but in-depth glycoproteomics analysis of synovial tissues is still lacking. Here, by using a strategy to quantify intact N-glycopeptides, we identified 1260 intact N-glycopeptides from 481 N-glycosites on 334 glycoproteins in RA synovium. Bioinformatics analysis revealed that the hyper-glycosylated proteins in RA were closely linked to immune responses. By using DNASTAR software, we identified 20 N-glycopeptides whose prototype peptides were highly immunogenic. We next calculated the enrichment scores of nine types of immune cells using specific gene sets from public single-cell transcriptomics data of RA and revealed that the N-glycosylation levels at some sites, such as IGSF10_N2147, MOXD2P_N404, and PTCH2_N812, were significantly correlated with the enrichment scores of certain immune cell types. Furthermore, we showed that aberrant N-glycosylation in the RA synovium was related to increased expression of glycosylation enzymes. Collectively, this work presents, for the first time, the N-glycoproteome of RA synovium and describes immune-associated glycosylation, providing novel insights into RA pathogenesis.

Clinical value of FAT1 mutations to indicate the immune response in colorectal cancer patients.

Immunotherapy is currently approved for CRC whose tumors have high MSI-H. To find additional biomarkers for immunotherapy in CRC, targeted sequencing was performed on tumor tissues from a discovery cohort of 161 CRC patients. Validation cohorts from the cBioPortal were also used for survival and tumor cell infiltration analyses. The FAT1-mutated CRC group often co-occurred with MSI events and displayed a higher tumor mutational burden compared to the FAT1 wild-type CRC. Overall survival was higher in patients with FAT1 mutations than in patients with wild type FAT1. The altered PI3K-AKT pathway and immune pathways were enriched in the FAT1-mutated CRC. A higher infiltration rate of immune cells including CD4+ T cells, CD8+ T cells, macrophages M1 and regulatory T cells were also observed in the colorectal tumors with FAT1 mutation compared to tumors with wild type FAT1. The results showed that CRC patients with FAT1 mutations exhibited an immunotherapy-favorable profile.

Identification of necroptosis-related genes in ankylosing spondylitis by bioinformatics and experimental validation.

The pathogenesis of ankylosing spondylitis (AS) remains unclear, and while recent studies have implicated necroptosis in various autoimmune diseases, an investigation of its relationship with AS has not been reported. In this study, we utilized the Gene Expression Omnibus database to compare gene expressions between AS patients and healthy controls, identifying 18 differentially expressed necroptosis-related genes (DENRGs), with 8 upregulated and 10 downregulated. Through the application of three machine learning algorithms-least absolute shrinkage and selection operation, support vector machine-recursive feature elimination and random forest-two hub genes, FASLG and TARDBP, were pinpointed. These genes demonstrated high specificity and sensitivity for AS diagnosis, as evidenced by receiver operating characteristic curve analysis. These findings were further supported by external datasets and cellular experiments, which confirmed the downregulation of FASLG and upregulation of TARDBP in AS patients. Immune cell infiltration analysis suggested that CD4+ T cells, CD8+ T cells, NK cells and neutrophils may be associated with the development of AS. Notably, in the group with high FASLG expression, there was a significant infiltration of CD8+ T cells, memory-activated CD4+ T cells and resting NK cells, with relatively less infiltration of memory-resting CD4+ T cells and neutrophils. Conversely, in the group with high TARDBP expression, there was enhanced infiltration of naïve CD4+ T cells and M0 macrophages, with a reduced presence of memory-resting CD4+ T cells. In summary, FASLG and TARDBP may contribute to AS pathogenesis by regulating the immune microenvironment and immune-related signalling pathways. These findings offer new insights into the molecular mechanisms of AS and suggest potential new targets for therapeutic strategies.

Differential genetic mutations and immune cell infiltration in high- and low-risk STAD: Implications for prognosis and immunotherapy efficacy.

This study investigates genetic mutations and immune cell dynamics in stomach adenocarcinoma (STAD), focusing on identifying prognostic markers and therapeutic targets. Analysis of TCGA-STAD samples revealed C > A as the most common single nucleotide variant (SNV) in both high and low-risk groups. Key mutated driver genes included TTN, TP53 and MUC16, with frame-shift mutations more prevalent in the low-risk group and missense mutations in the high-risk group. Interaction analysis of hub genes such as C1QA and CD68 showed significant correlations, impacting immune cell infiltration patterns. Using ssGSEA, we found higher immune cell infiltration (B cells, CD4+ T cells, CD8+ T cells, DC cells, NK cells) in the high-risk group, correlated with increased risk scores. xCell algorithm results indicated distinct immune infiltration levels between the groups. The study's risk scoring model proved effective in prognosis prediction and immunotherapy efficacy assessment. Key molecules like CD28, CD27 and SLAMF7 correlated significantly with risk scores, suggesting potential targets for high-risk STAD patients. Drug sensitivity analysis showed a negative correlation between risk scores and sensitivity to certain treatments, indicating potential therapeutic options for high-risk STAD patients. We also validated the carcinogenic role of RPL14 in gastric cancer through phenotypic experiments, demonstrating its influence on cancer cell proliferation, invasion and migration. Overall, this research provides crucial insights into the genetic and immune aspects of STAD, highlighting the importance of a risk scoring model for personalized treatment strategies and clinical decision-making in gastric cancer management.

ITGB2 related to immune cell infiltration as a potential therapeutic target of inflammatory bowel disease using bioinformatics and functional research.

Inflammatory bowel disease (IBD) is a chronic systemic inflammatory condition regarded as a major risk factor for colitis-associated cancer. However, the underlying mechanisms of IBD remain unclear. First, five GSE data sets available in GEO were used to perform 'batch correction' and Robust Rank Aggregation (RRA) to identify differentially expressed genes (DEGs). Candidate molecules were identified using CytoHubba, and their diagnostic effectiveness was predicted. The CIBERSORT algorithm evaluated the immune cell infiltration in the intestinal epithelial tissues of patients with IBD and controls. Immune cell infiltration in the IBD and control groups was determined using the least absolute shrinkage selection operator algorithm and Cox regression analysis. Finally, a total of 51 DEGs were screened, and nine hub genes were identified using CytoHubba and Cytoscape. GSE87466 and GSE193677 were used as extra data set to validate the expression of the nine hub genes. CD4-naïve T cells, gamma-delta T cells, M1 macrophages and resting dendritic cells (DCs) are the main immune cell infiltrates in patients with IBD. Signal transducer and activator of transcription 1, CCR5 and integrin subunit beta 2 (ITGB2) were significantly upregulated in the IBD mouse model, and suppression of ITGB2 expression alleviated IBD inflammation in mice. Additionally, the expression of ITGB2 was upregulated in IBD-associated colorectal cancer (CRC). The silence of ITGB2 suppressed cell proliferation and tumour growth in vitro and in vivo. ITGB2 resting DCs may provide a therapeutic strategy for IBD, and ITGB2 may be a potential diagnostic marker for IBD-associated CRC.

Unveiling the therapeutic prospects of IFNW1 and IFNA21: insights into glioma pathogenesis and clinical significance.

Glioma, a type of brain tumor, poses significant challenges due to its heterogeneous nature and limited treatment options. Interferon-related genes (IRGs) have emerged as potential players in glioma pathogenesis, yet their expression patterns and clinical implications remain to be fully elucidated. We conducted a comprehensive analysis to investigate the expression patterns and functional enrichment of IRGs in glioma. This involved constructing protein-protein interaction networks, heatmap analysis, survival curve plotting, diagnostic and prognostic assessments, differential expression analysis across glioma subgroups, GSVA, immune infiltration analysis, and drug sensitivity analysis. Our analysis revealed distinct expression patterns and functional enrichment of IRGs in glioma. Notably, IFNW1 and IFNA21 were markedly downregulated in glioma tissues compared to normal tissues, and higher expression levels were associated with improved overall survival and disease-specific survival. Furthermore, these genes showed diagnostic capabilities in distinguishing glioma tissues from normal tissues and were significantly downregulated in higher-grade and more aggressive gliomas. Differential expression analysis across glioma subgroups highlighted the association of IFNW1 and IFNA21 expression with key pathways and biological processes, including metabolic reprogramming and immune regulation. Immune infiltration analysis revealed their influence on immune cell composition in the tumor microenvironment. Additionally, elevated expression levels were associated with increased resistance to chemotherapeutic agents. Our findings underscore the potential of IFNW1 and IFNA21 as diagnostic biomarkers and prognostic indicators in glioma. Their roles in modulating glioma progression, immune response, and drug sensitivity highlight their significance as potential therapeutic targets. These results contribute to a deeper understanding of glioma biology and may inform the development of personalized treatment strategies for glioma patients.

Identification of endoplasmic reticulum stress genes in human stroke based on bioinformatics and machine learning.

After ischemic stroke (IS), secondary injury is intimately linked to endoplasmic reticulum (ER) stress and body-brain crosstalk. Nonetheless, the underlying mechanism systemic immune disorder mediated ER stress in human IS remains unknown. In this study, 32 candidate ER stress-related genes (ERSRGs) were identified by overlapping MSigDB ER stress pathway genes and DEGs. Three Key ERSRGs (ATF6, DDIT3 and ERP29) were identified using LASSO, random forest, and SVM-RFE. IS patients with different ERSRGs profile were clustered into two groups using consensus clustering and the difference between 2 group was further explored by GSVA. Through immune cell infiltration deconvolution analysis, and middle cerebral artery occlusion (MCAO) mouse scRNA analysis, we found that the expression of 3 key ERSRGs were closely related with peripheral macrophage cell ER stress in IS and this was further confirmed by RT-qPCR experiment. These ERS genes might be helpful to further accurately regulate the central nervous system and systemic immune response through ER stress and have potential application value in clinical practice in IS.

Apoptosis-related prognostic biomarkers and potential targets for acute kidney injury based on machine learning algorithm and in vivo experiments.

Acute kidney injury (AKI) is a common critical illness in hospitalized patients, characterized by a rapid decline in kidney function over a short period, which can seriously endanger the patient's life. Currently, there is a lack of precise and universal AKI diagnostic biomarkers in clinical practice. In this study, weighted gene coexpression network analysis (WGCNA), differential expression analysis, univariate and multivariate logistic regression analyses, receiver operating characteristic (ROC) curves, and immune cell infiltration were performed to identify apoptosis-related biomarkers that can be used for AKI diagnosis. Three core apoptosis-related genes (ARGs), CBFB, EGF and COL1A1, were identified as AKI biomarkers. More importantly, an apoptosis-related signature containing three hub ARGs was validated as a diagnostic model. The hub genes exhibited good correlations with glomerular filtration rate (GFR) and serum creatinine (SCr) in the Nephroseq kidney disease database. Additionally, CIBERSORT immune infiltration analysis indicated that these core ARGs may affect immune cell recruitment and infiltration in AKI patients. Subsequently, we investigated the alteration of the expression levels of three core ARGs in AKI samples using single-cell RNA sequencing analysis and analyzed the cell types that mainly expressed these ARGs. More importantly, the expression of core ARGs was validated in folic acid- and cisplatin-induced AKI mouse models. In summary, our study identified three diagnostic biomarkers for AKI, explored the roles of ARGs in AKI progression and provided new ideas for the clinical diagnosis and treatment of AKI.

Modulating the RPS27A/PSMD12/NF-κB pathway to control immune response in mouse brain ischemia-reperfusion injury.

BACKGROUND: Investigating immune cell infiltration in the brain post-ischemia-reperfusion (I/R) injury is crucial for understanding and managing the resultant inflammatory responses. This study aims to unravel the role of the RPS27A-mediated PSMD12/NF-κB axis in controlling immune cell infiltration in the context of cerebral I/R injury. METHODS: To identify genes associated with cerebral I/R injury, high-throughput sequencing was employed. The potential downstream genes were further analyzed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) analyses. For experimental models, primary microglia and neurons were extracted from the cortical tissues of mouse brains. An in vitro cerebral I/R injury model was established in microglia using the oxygen-glucose deprivation/reoxygenation (OGD/R) technique. In vivo models involved inducing cerebral I/R injury in mice through the middle cerebral artery occlusion (MCAO) method. These models were used to assess neurological function, immune cell infiltration, and inflammatory factor release. RESULTS: The study identified RPS27A as a key player in cerebral I/R injury, with PSMD12 likely acting as its downstream regulator. Silencing RPS27A in OGD/R-induced microglia decreased the release of inflammatory factors and reduced neuron apoptosis. Additionally, RPS27A silencing in cerebral cortex tissues mediated the PSMD12/NF-κB axis, resulting in decreased inflammatory factor release, reduced neutrophil infiltration, and improved cerebral injury outcomes in I/R-injured mice. CONCLUSION: RPS27A regulates the expression of the PSMD12/NF-κB signaling axis, leading to the induction of inflammatory factors in microglial cells, promoting immune cell infiltration in brain tissue, and exacerbating brain damage in I/R mice. This study introduces novel insights and theoretical foundations for the treatment of nerve damage caused by I/R, suggesting that targeting the RPS27A and downstream PSMD12/NF-κB signaling axis for drug development could represent a new direction in I/R therapy.

Age-related genes USP2 and ARG2 are involved in the reduction of immune cell infiltration in elderly patients with rheumatoid arthritis.

BACKGROUND: There are large differences in clinical manifestations and biological markers between elderly patients with rheumatoid arthritis (EPRA, age >60) and younger patients with RA (YPRA, age ≤60), partly owing to variations in the immune system of different age groups. Here, we focused on the changes of immune cell infiltration in YPRA and EPRA. METHODS: The R packages "ssGSEA" and "GSEA" were used to identify the changes in immune cell infiltration and immune-related pathways between the two groups. The R packages "WGCNA" and "DEseq2" were used to screen and verify age-related differentially expressed genes (DEGs). Hub genes were identified using Cytoscape and cytoHubba. Spearman correlation coefficient was conducted to evaluate correlations between hub age-related genes and immune cells. RESULTS: Compared with 54 established YPRA, several immune cells and immune-related pathways were markedly decreased in 29 EPRA synovial tissues. Moreover, 78 age-related DEGs related to amino acid and glycosphingolipid synthesis and metabolism were identified. USP2 and ARG2 were verified to be upregulated in EPRA, signifying that these two genes could effectively distinguish YPRA and EPRA and have potential as biomarkers. In addition, we found that USP2 was significantly negatively correlated with B cells and monocytes, while there was a significant negative association between ARG2 and T cells. CONCLUSIONS: In conclusion, this study is the first to systematically analyze changes in immune cell infiltration between YPRA and EPRA patients and obtain hub age-related genes, which may provide the basis for illuminating the pathogenesis of EPRA and informing treatment strategies.

Artificial neural network-based gene screening and immune cell infiltration analysis of osteosarcoma feature.

BACKGROUND: The present study aimed to construct an artificial neural network (ANN) model that leverages characteristic genes associated with osteosarcoma (OS) to enable accurate prognostication for OS patients. METHODS: Our research revealed 467 differentially expressed genes (DEGs) via gene expression contrast analysis, consisting of 345 downregulated genes and 122 upregulated genes. Gene Ontology (GO) enrichment analysis illuminated functions primarily encompassing T-cell activation, secretory granule lumen and antioxidant activity, among others. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, we discovered significant correlations between the DEGs and certain pathways, including phagosome, Staphylococcus aureus infection and human T-cell leukemia virus 1 infection. We then screened out 30 characteristic DEGs (CDEGs) based on random forest analysis and constructed the ANN model using the gene score matrix. To verify the credibility and accuracy of the ANN model, we performed internal and external validation processes, which affirmed our model's predictive capabilities. RESULTS: The study further delved into the analysis of immune cell infiltration and its correlation with the target CDEGs, revealing disparities in the infiltration of 22 types of immune cells across different groups and their interrelationships. Moreover, we probed the expression of the two foremost CDEGs (YES1 and MFNG) in OS and normal tissues. We noted a positive relationship between the expression of YES1 and MFNG in OS tissues and the clinicopathological characteristics of OS patients. CONCLUSIONS: Collectively, the findings of the present study validate the effectiveness of the CDEGs-based ANN model in predicting OS patients, which might facilitate early diagnosis and treatment of OS.

Relevance of pyroptosis-associated genes in nasopharyngeal carcinoma diagnosis and subtype classification.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is a highly aggressive and metastatic malignancy originating in the nasopharyngeal tissue. Pyroptosis is a relatively newly discovered, regulated form of necrotic cell death induced by inflammatory caspases that is associated with a variety of diseases. However, the role and mechanism of pyroptosis in NPC are not fully understood. METHODS: We analyzed the differential expression of pyroptosis-related genes (PRGs) between patients with and without NPC from the GSE53819 and GSE64634 datasets of the Gene Expression Omnibus (GEO) database. We mapped receptor operating characteristic profiles for these key PRGs to assess the accuracy of the genes for disease diagnosis and prediction of patient prognosis. In addition, we constructed a nomogram based on these key PRGs and carried out a decision curve analysis. The NPC patients were classified into different pyroptosis gene clusters by the consensus clustering method based on key PRGs, whereas the expression profiles of the key PRGs were analyzed by applying principal component analysis. We also analyzed the differences in key PRGs, immune cell infiltration and NPC-related genes between the clusters. Finally, we performed differential expression analysis for pyroptosis clusters and obtained differentially expressed genes (DEGs) and performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. RESULTS: We obtained 14 differentially expressed PRGs from GEO database. Based on these 14 differentially expressed PRGs, we applied least absolute shrinkage and selection operator analysis and the random forest algorithm to obtain four key PRGs (CHMP7, IL1A, TP63 and GSDMB). We completely distinguished the NPC patients into two pyroptosis gene clusters (pyroptosis clusters A and B) based on four key PRGs. Furthermore, we determined the immune cell abundance of each NPC sample, estimated the association between the four PRGs and immune cells, and determined the difference in immune cell infiltration between the two pyroptosis gene clusters. Finally, we obtained and functional enrichment analyses 259 DEGs by differential expression analysis for both pyroptosis clusters. CONCLUSIONS: PRGs are critical in the development of NPC, and our research on the pyroptosis gene cluster may help direct future NPC therapeutic approaches.

Revealing the contribution of somatic gene mutations to shaping tumor immune microenvironment.

Interaction between tumor cells and immune cells determined highly heterogeneous microenvironments across patients, leading to substantial variation in clinical benefits from immunotherapy. Somatic gene mutations were found not only to elicit adaptive immunity but also to influence the composition of tumor immune microenvironment and various processes of antitumor immunity. However, due to an incomplete view of associations between gene mutations and immunophenotypes, how tumor cells shape the immune microenvironment and further determine the clinical benefit of immunotherapy is still unclear. To address this, we proposed a computational approach, inference of mutation effect on immunophenotype by integrated gene set enrichment analysis (MEIGSEA), for tracing back the genomic factor responsible for differences in immunophenotypes. MEIGSEA was demonstrated to accurately identify the previous confirmed immune-associated gene mutations, and systematic evaluation in simulation data further supported its performance. We used MEIGSEA to investigate the influence of driver gene mutations on the infiltration of 22 immune cell types across 19 cancers from The Cancer Genome Atlas. The top associated gene mutations with infiltration of CD8 T cells, such as CASP8, KRAS and EGFR, also showed extensive impact on other immune components; meanwhile, immune effector cells shared critical gene mutations that collaboratively contribute to shaping distinct tumor immune microenvironment. Furthermore, we highlighted the predictive capacity of gene mutations that are positively associated with CD8 T cells for the clinical benefit of immunotherapy. Taken together, we present a computational framework to help illustrate the potential of somatic gene mutations in shaping the tumor immune microenvironment.

Immune cell infiltration and inflammatory landscape in primary brain tumours.

BACKGROUND: Primary malignant brain tumours are more than one-third of all brain tumours and despite the molecular investigation to identify cancer driver mutations, the current therapeutic options available are challenging due to high intratumour heterogeneity. In addition, an immunosuppressive and inflammatory tumour microenvironment strengthens cancer progression. Therefore, we defined an immune and inflammatory profiling of meningioma and glial tumours to elucidate the role of the immune infiltration in these cancer types. METHODS: Using tissue microarrays of 158 brain tumour samples, we assessed CD3, CD4, CD8, CD20, CD138, Granzyme B (GzmB), 5-Lipoxygenase (5-LOX), Programmed Death-Ligand 1 (PD-L1), O-6-Methylguanine-DNA Methyltransferase (MGMT) and Transglutaminase 2 (TG2) expression by immunohistochemistry (IHC). IHC results were correlated using a Spearman correlation matrix. Transcript expression, correlation, and overall survival (OS) analyses were evaluated using public datasets available on GEPIA2 in Glioblastoma (GBM) and Lower Grade Glioma (LGG) cohorts. RESULTS: Seven out of ten markers showed a significantly different IHC expression in at least one of the evaluated cohorts whereas CD3, CD4 and 5-LOX were differentially expressed between GBMs and astrocytomas. Correlation matrix analysis revealed that 5-LOX and GzmB expression were associated in both meningiomas and GBMs, whereas 5-LOX expression was significantly and positively correlated to TG2 in both meningioma and astrocytoma cohorts. These findings were confirmed with the correlation analysis of TCGA-GBM and LGG datasets. Profiling of mRNA levels indicated a significant increase in CD3 (CD3D, CD3E), and CD138 (SDC1) expression in GBM compared to control tissues. CD4 and 5-LOX (ALOX5) mRNA levels were significantly more expressed in tumour samples than in normal tissues in both GBM and LGG. In GBM cohort, GzmB (GZMB), SDC1 and MGMT gene expression predicted a poor overall survival (OS). Moreover, in LGG cohort, an increased expression of CD3 (CD3D, CD3E, CD3G), CD8 (CD8A), GZMB, CD20 (MS4A1), SDC1, PD-L1, ALOX5, and TG2 (TGM2) genes was associated with worse OS. CONCLUSIONS: Our data have revealed that there is a positive and significant correlation between the expression of 5-LOX and GzmB, both at RNA and protein level. Further evaluation is needed to understand the interplay of 5-LOX and immune infiltration in glioma progression.

A Bioinformatic Analysis of Gut Microbiota Related with Immune Cell Infiltration in Colorectal Cancer.

OBJECTIVE: The composition of microbiota which correlates with infiltrating immune cells and clinical signatures is not clarified in CRC. METHODS: We applied 4 kinds of bioinformatic tools GSVA (version: 1.42.0), ESTIMATE (version: 1.0.13), CIBERSORT (version: 2.0), and immune-related genes. RESULTS: We found that a total of 8 types of microbiotas appeared in the three immune correlation analyses. Among these microbiotas, significant enrichments in relative abundances associated with immune cell infiltration can be found for the dominant phyla Proteobacteria, Firmicutes, and Actinobacteria. Moreover, there existed correlations between some of the 8 microbiotas and clinical-related indicators. CONCLUSION: We identified some novel microbiotas involved in immune regulation in CRC.

High LGALS3 expression induced by HCP5/hsa-miR-27b-3p correlates with poor prognosis and tumor immune infiltration in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is widely recognized for its unfavorable prognosis. Increasing evidence has revealed that LGALS3 has an essential function in initiating and developing several malignancies in humans. Nevertheless, thorough analysis of the expression profile, clinical prognosis, pathway prediction, and immune infiltration of LGALS3 has not been fully explored in HCC. METHODS: In this study, an initial pan-cancer analysis was conducted to investigate the expression and prognosis of LGALS3. Following a comprehensive analysis, which included expression analysis and correlation analysis, noncoding RNAs that contribute to the overexpression of LGALS3 were subsequently identified. This identification was further validated using HCC clinical tissue samples. TIMER2 and GEPIA2 were employed to examine the correlation between LGALS3 and HCP5 with immunological checkpoints, cell chemotaxis, and immune infiltration in HCC. The R program was applied to analyze the expression distribution of immune score in in HCC patients with high and low LGALS3 expression. The expression profiles of immune checkpoints were also analyzed. Use R to perform GSVA analysis in order to explore potential signaling pathways. RESULTS: First, we conducted pan-cancer analysis for LGALS3 expression level through an in-depth analysis of public databases and found that HCC has a high LGALS3 gene and protein expression level, which were then verified in clinical HCC specimens. Meanwhile, high LGALS3 gene expression is related to malignant progression and poor prognosis of HCC. Univariate and multivariate analyses confirmed that LGALS3 could serve as an independent prognostic marker for HCC. Next, by combining comprehensive analysis and validation on HCC clinical tissue samples, we hypothesize that the HCP5/hsa-miR-27b-3p axis could serve as the most promising LGALS3 regulation mechanism in HCC. KEGG and GO analyses highlighted that the LGALS3-related genes were involved in tumor immunity. Furthermore, we detected a significant positive association between LGALS3 and HCP5 with immunological checkpoints, cell chemotaxis, and immune infiltration. In addition, high LGALS3 expression groups had significantly higher immune cell scores and immune checkpoint expression levels. Finally, GSVA analysis was performed to predict potential signaling pathways linked to LGALS3 and HCP5 in immune evasion and metabolic reprogramming of HCC. CONCLUSIONS: Our findings indicated that the upregulation of LGALS3 via the HCP5/hsa-miR-27b-3p axis is associated with unfavorable prognosis and increased tumor immune infiltration in HCC.

Glycolysis-related genes predict prognosis and indicate immune microenvironment features in gastric cancer.

BACKGROUND: Gastric cancer (GC) is a major contributor to cancer-related mortality. Glycolysis plays a pivotal role in tumor microenvironment (TME) reprogramming. In this research, the functions of glycolysis-associated genes (GRGs) were evaluated to predict the outcome and reveal the characteristics of the immune microenvironment in individuals with stomach cancer. METHODS: The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) cohort provided gene expression and clinical data for gastric cancer (GC) patients, which were further authenticated using datasets sourced from the Gene Expression Omnibus (GEO). By referencing the Molecular Signatures Database (MSigDB), a total of 326 GRGs were pinpointed. The various subtypes of GC were outlined through consensus clustering, derived from the expression patterns of these GRGs. Utilizing multivariate Cox regression analysis, a multigene risk score model was formulated. Both the CIBERSORT and ESTIMATE algorithms played a pivotal role in assessing the immune microenvironment. To delve into the biological functions of the key genes, wound healing, transwell invasion, and MTT assays were conducted. RESULTS: Based on the expression patterns of GRGs, patients were categorized into two distinct groups: the metabolic subtype, designated as cluster A, and the immune subtype, labeled as cluster B. Patients belonging to cluster B exhibited a poorer prognosis. A prognostic risk score model, formulated upon the expression levels of six key GRGs - ME1, PLOD2, NUP50, CXCR4, SLC35A3, and SRD35A3 - emerged as a viable tool for predicting patient outcomes. The downregulation of CXCR4 notably diminished the glycolytic capacity of gastric cancer (GC) cells, alongside their migratory, invasive, and proliferative capabilities. Intriguingly, despite the adverse prognostic implications associated with both the immune subtype (cluster B) and the high-risk cohort, these groups exhibited a favorable immune microenvironment coupled with elevated expression of immune checkpoint genes. Our investigations revealed a positive correlation between high CXCR4 expression and low ME1 expression with the infiltration of CD8+ T cells, as well as an enhanced responsiveness to treatment with an anti-PD-1 immune checkpoint inhibitor. CONCLUSIONS: In this study, we discovered that the expression profiles of GRGs hold the potential to forecast the prognosis of gastric cancer (GC) patients, thereby possibly aiding in clinical treatment decision-making.

Blocking the IFN-gamma signal in the choroid plexus confers resistance to experimental autoimmune encephalomyelitis.

Multiple sclerosis (MS) is an autoimmune disease characterized by inflammatory infiltration and demyelination in the central nervous system (CNS). IFN-gamma (IFN-γ), a critically important immunomodulator, has been widely studied in MS pathology. The confusing and complex effects of IFN-γ in MS patients and rodent models, however, cause us to look more closely at its exact role in MS. In this study, we identified the role of the IFN-γ signaling in the choroid plexus (CP) in the experimental autoimmune encephalomyelitis (EAE) model. We found that the IFN-γ signal was rapidly amplified when CNS immune cell infiltration occurred in the CP during the progressive stage. Furthermore, using two CP-specific knockdown strategies, we demonstrated that blocking the IFN-γ signal via knockdown of IFN-γR1 in the CP could protect mice against EAE pathology, as evidenced by improvements in clinical scores and infiltration. Notably, knocking down IFN-γR1 in the CP reduced the local expression of adhesion molecules and chemokines. This finding suggests that IFN-γ signaling in the CP may participate in the pathological process of EAE by preventing pathological T helper (Th) 17+ cells from infiltrating into the CNS. Finally, we showed that the unbalanced state of IFN-γ signaling between peripheral lymphocytes and the choroid plexus may determine whether IFN-γ has a protective or aggravating effect on EAE pathology. Above all, we discovered that IFN-γR1-mediated IFN-γ signaling in the CP was a vital pathway in the pathological process of EAE.