Ferroptosis-related gene transferrin receptor protein 1 expression correlates with the prognosis and tumor immune microenvironment in cervical cancer.

Background: Ferroptosis is a non-apoptotic iron-dependent form of cell death implicated in various cancer pathologies. However, its precise role in tumor growth and progression of cervical cancer (CC) remains unclear. Transferrin receptor protein 1 (TFRC), a key molecule associated with ferroptosis, has been identified as influencing a broad range of pathological processes in different cancers. However, the prognostic significance of TFRC in CC remains unclear. The present study utilized bioinformatics to explore the significance of the ferroptosis-related gene TFRC in the progression and prognosis of CC. Methods: We obtained RNA sequencing data and corresponding clinical information on patients with CC from The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx) and Gene Expression Omnibus (GEO) databases. Using least absolute shrinkage and selection operator (LASSO) Cox regression, we then generated a multigene signature of five ferroptosis-related genes (FRGs) for the prognostic prediction of CC. We investigated the relationship between TFRC gene expression and immune cell infiltration by employing single-sample GSEA (ssGSEA) analysis. The potential functional role of the TFRC gene was evaluated through gene set enrichment analysis (GSEA). Immunohistochemistry and qPCR was employed to assess TFRC mRNA and protein expression in 33 cases of cervical cancer. Furthermore, the relationship between TFRC mRNA expression and overall survival (OS) was investigated in patients. Results: CC samples had significantly higher TFRC gene expression levels than normal tissue samples. Higher TFRC gene expression levels were strongly associated with higher cancer T stages and OS events. The findings of multivariate analyses illustrated that the OS in CC patients with high TFRC expression is shorter than in patients with low TFRC expression. Significant increases were observed in the levels of TFRC mRNA and protein expression in patients diagnosed with CC. Conclusion: Increased TFRC expression in CC was associated with disease progression, an unfavorable prognosis, and dysregulated immune cell infiltration. In addition, it highlights ferroptosis as a promising therapeutic target for CC.

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

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

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

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

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

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

WTAP promotes the progression of ulcerative colitis by silencing the expression of CES2 through m6A modification.

OBJECTIVE: This study will explore the function of WTAP, the critical segment of m6A methyltransferase complex, in UC and its regulation on immune response. METHODS: The expression levels of key proteins were detected in colon tissues which were derived from UC patients and mice. Macrophage polarization and CD4+ T cell infiltration were detected by flow cytometry and IF staining. ELISA assay was utilized to analyze the level of the inflammatory cytokines. m6A-RIP-PCR, actinomycin D test, and RIP assays were utilized to detect the m6A level, stability, and bound proteins of CES2 mRNA. A dual luciferase reporter assay was conducted to confirm the transcriptional interactions between genes. A co-culture system of intestinal epithelium-like organs was constructed to detect the primary mouse intestinal epithelial cells (PMIEC) differentiation. The interaction between proteins was detected via Co-IP assay. RESULTS: The expression of WTAP and CES2 in UC tissues was increased and decreased, respectively. Knockdown of WTAP inhibited the progression of UC in mice by inhibiting M1 macrophage polarization and CD4+ T cell infiltration. WTAP combined YTHDF2 to promote the m6A modification of CES2 mRNA and inhibited its expression. CES2 co-expressed with EPHX2 and overexpression of CES2 promoted the differentiation of PMIEC. The inhibitory effect of WTAP knockdown on the progress of UC was partially abrogated by CES2 knockdown. CONCLUSION: WTAP/YTHDF2 silences CES2 by promoting its m6A modification and then promotes the progression of UC. WTAP could be a promoting therapy target of UC.

A Mature Tertiary Lymphoid Structure with a Ki-67-Positive Proliferating Germinal Center Is Associated with a Good Prognosis and High Intratumoral Immune Cell Infiltration in Advanced Colorectal Cancer.

Tertiary lymphoid structures (TLSs) are complex lymphocyte clusters that arise in non-lymphoid tissues due to inflammation or cancer. A mature TLS with proliferating germinal centers is associated with a favorable prognosis in various cancers. However, the effect of TLS maturity on advanced colorectal cancer (CRC) remains unexplored. We analyzed the significance of TLS maturity and tumor Ki-67 expression in surgically resected tumors from 78 patients with pathological T4 CRC. Mature TLS was defined as the organized infiltration of T and B cells with Ki-67-positive proliferating germinal centers. We analyzed the relationship between TLS maturity and intratumoral immune cell infiltration. Mature TLS with germinal center Ki-67 expression was associated with microsatellite instability and improved survival; however, high tumor Ki-67 expression was associated with poor survival in the same cohort. Multivariate analysis identified the absence of mature TLS as an independent predictor of poor post-recurrence overall survival. Intratumoral infiltration of T lymphocytes and macrophages was significantly elevated in tumors with mature TLS compared to those lacking it. High Ki-67 levels and absent mature TLS were identified as poor prognostic factors in advanced CRC. Mature TLS could serve as a promising marker for patients at high-risk of CRC.

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

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

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

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

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

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

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.

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

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

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.

Bioinformatics analysis of the role of lysosome-related genes in breast cancer.

This study aimed to investigate the roles of lysosome-related genes in BC prognosis and immunity. Transcriptome data from TCGA and MSigDB, along with lysosome-related gene sets, underwent NMF cluster analysis, resulting in two subtypes. Using lasso regression and univariate/multivariate Cox regression analysis, an 11-gene signature was successfully identified and verified. High- and low-risk populations were dominated by HR+ sample types. There were differences in pathway enrichment, immune cell infiltration, and immune scores. Sensitive drugs targeting model genes were screened using GDSC and CCLE. This study constructed a reliable prognostic model with lysosome-related genes, providing valuable insights for BC clinical immunotherapy.

Lysosome-related genes can be used to predict survival outcomes in BRCA patients.Significant differences were showed in the immune status of patient with different prognoses.Immunotherapy may show better therapeutic results in low-risk patients.The most promising targeted drugs in the low-risk group are mainly Lapatinib, Palbociclib and Ribociclib.

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.

An immune biomarker associated with EMT serves as a predictor for prognosis and drug response in bladder cancer.

BACKGROUND: Bladder cancer (BLCA), which develops from the upper endometrial of the bladder, is the sixth most prevalent cancer across the globe. WDHD1 (WD repeat and HMG-box DNA binding protein 1 gene) directly affects signaling, the cell cycle, and the development of the cell skeleton. Uncertainty surrounds WDHD1's function in BLCA immunity and prognosis, though. MATERIALS AND METHODS: Using weighed gene co-expression network analysis (WGCNA), initially, we first identified 32 risk factors in genes with differential expression for this investigation. Then, using a variety of bioinformatic techniques and experimental validation, we examined the connections between WDHD1 and BLCA expression, clinical pathological traits, WDHD1-related proteins, upper-skin-intermediate conversion (EMT), immune cell immersion, convergence factors, immune markers, and drug sensitivity. RESULT: The findings demonstrated that we constructed a 32-gene risk-predicting model where WDHD1 was elevated as a representative gene expression in BLCA and related to a range of clinical traits. Furthermore, high WDHD1 expression was a standalone predictor associated with a worse survival rate. The most commonly recruited cells and their evolutionary patterns were highlighted to better comprehend WDHD1's function in cancer. High WDHD1 expression was associated with many aspects of immunology. Finally, the study found that individuals with high expression of WDHD1 were drug-sensitive to four different broad-spectrum anti-cancer drugs. CONCLUSION: These results describe dynamic changes in the tumor microenvironment in BLCA and provide evidence for the hypothesis that WDHD1 is a novel biomarker of tumor development. WDHD1 may therefore be a useful target for the detection and management of BLCA.

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.

Characteristics of the immune environment in prostate cancer as an adjunct to immunotherapy.

Background and Aims: The tumor microenvironment (TME) exerts an important role in carcinogenesis and progression. Several investigations have suggested that immune cell infiltration (ICI) is of high prognostic importance for tumor progression and patient survival in many tumors, particularly prostate cancer. The pattern of immune infiltration of PCa, on the other hand, has not been thoroughly understood. Methods: The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets on PCa were obtained, and several datasets were merged into one data set using the "ComBat" algorithm. The ICI profiles of PCa patients were then to be uncovered by two computer techniques. The unsupervised clustering method was utilized to identify three ICI patterns in tumor samples, and Principal Component Analysis (PCA) was conducted to estimate the ICI score. Results: Three different clusters of three ICIs were identified in 1341 PCa samples, which also correlated with different clinical features/characteristics and biological pathways. Patients with PCa are classified into high and low subtypes based on the ICI scores extracted from immune-associated signature genes. High ICI score subtypes are associated with a worse prognosis, which may intrigue the activation of cancer-related and immune-related pathways such as pathways involving Toll-like receptors, T-cell receptors, JAK-STAT, and natural killer cells. The ICI score was linked to tumor mutation load and immune/cancer-relevant signaling pathways, which explain prostate cancer's poor prognosis. Conclusion: The findings of this study not only advanced our knowledge of the mechanism of immune response in the prostate tumor microenvironment but also provided a novel biomarker, that is, the ICI score, for disease prognosis and guiding precision immunotherapy.

Signature identification based on immunogenic cell death-related lncRNAs to predict the prognosis and immune activity of patients with endometrial carcinoma.

Background: Endometrial carcinoma (EC) is one of the most prevalent gynecologic malignancies and requires further classification for treatment and prognosis. Long non-coding RNAs (lncRNAs) and immunogenic cell death (ICD) play a critical role in tumor progression. Nevertheless, the role of lncRNAs in ICD in EC remains unclear. This study aimed to explore the role of ICD related-lncRNAs in EC via bioinformatics and establish a prognostic risk model based on the ICD-related lncRNAs. We also explored immune infiltration and immune cell function across prognostic groups and made treatment recommendations. Methods: A total of 552 EC samples and clinical data of 548 EC patients were extracted from The Cancer Genome Atlas (TCGA) database and University of California Santa Cruz (UCSC) Xena, respectively. A prognostic-related feature and risk model was developed using the least absolute shrinkage and selection operator (LASSO). Subtypes were classified with consensus cluster analysis and validated with t-Distributed Stochastic Neighbor Embedding (tSNE). Kaplan-Meier analysis was conducted to assess differences in survival. Infiltration by immune cells was estimated by single sample gene set enrichment analysis (ssGSEA), Tumor IMmune Estimation Resource (TIMER) algorithm. Quantitative polymerase chain reaction (qPCR) was used to detect lncRNAs expression in clinical samples and cell lines. A series of studies was conducted in vitro and in vivo to examine the effects of knockdown or overexpression of lncRNAs on ICD. Results: In total, 16 ICD-related lncRNAs with prognostic values were identified. Using SCARNA9, FAM198B-AS1, FKBP14-AS1, FBXO30-DT, LINC01943, and AL161431.1 as risk model, their predictive accuracy and discrimination were assessed. We divided EC patients into high-risk and low-risk groups. The analysis showed that the risk model was an independent prognostic factor. The prognosis of the high- and low-risk groups was different, and the overall survival (OS) of the high-risk group was lower. The low-risk group had higher immune cell infiltration and immune scores. Consensus clustering analysis divided the samples into four subtypes, of which cluster 4 had higher immune cell infiltration and immune scores. Conclusions: A prognostic signature composed of six ICD related-lncRNAs in EC was established, and a risk model based on this signature can be used to predict the prognosis of patients with EC.

Identification of NR3C2 as a functional diagnostic and prognostic biomarker and potential therapeutic target in non-small cell lung cancer.

Background: Non-small cell lung cancer (NSCLC), including the lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) subtypes, is a malignant tumor type with a poor 5-year survival rate. The identification of new powerful diagnostic biomarkers, prognostic biomarkers, and potential therapeutic targets in NSCLC is urgently required. Methods: The UCSC Xena, UALCAN, and GEO databases were used to screen and analyze differentially expressed genes, regulatory modes, and genetic/epigenetic alterations in NSCLC. The UCSC Xena database, GEO database, tissue microarray, and immunohistochemistry staining analyses were used to evaluate the diagnostic and prognostic values. Gain-of-function assays were performed to examine the roles. The ESTIMATE, TIMER, Linked Omics, STRING, and DAVID algorithms were used to analyze potential molecular mechanisms. Results: NR3C2 was identified as a potentially important molecule in NSCLC. NR3C2 is expressed at low levels in NSCLC, LUAD, and LUSC tissues, which is significantly related to the clinical indexes of these patients. Receiver operating characteristic curve analysis suggests that the altered NR3C2 expression patterns have diagnostic value in NSCLC, LUAD, and especially LUSC patients. Decreased NR3C2 expression levels can help predict poor prognosis in NSCLC and LUAD patients but not in LUSC patients. These results have been confirmed both with database analysis and real-world clinical samples on a tissue microarray. Copy number variation contributes to low NR3C2 expression levels in NSCLC and LUAD, while promoter DNA methylation is involved in its downregulation in LUSC. Two NR3C2 promoter methylation sites have high sensitivity and specificity for LUSC diagnosis with clinical application potential. NR3C2 may be a key participant in NSCLC development and progression and is closely associated with the tumor microenvironment and immune cell infiltration. NR3C2 co-expressed genes are involved in many cancer-related signaling pathways, further supporting a potentially significant role of NR3C2 in NSCLC. Conclusions: NR3C2 is a novel potential diagnostic and prognostic biomarker and therapeutic target in NSCLC.

Comprehensive analysis of clinical and biological value of ING family genes in liver cancer.

BACKGROUND: Liver cancer (LIHC) is a malignant tumor that occurs in the liver and has a high mortality in cancer. The ING family genes were identified as tumor suppressor genes. Dysregulated expression of these genes can lead to cell cycle arrest, senescence and/or apoptosis. ING family genes are promising targets for anticancer therapy. However, their role in LIHC is still not well understood. AIM: To have a better understanding of the important roles of ING family members in LIHC. METHODS: A series of bioinformatics approaches (including gene expression analysis, genetic alteration analysis, survival analysis, immune infiltration analysis, prediction of upstream microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) of ING1, and ING1-related gene functional enrichment analysis) was applied to study the expression profile, clinical relationship, prognostic significance and immune infiltration of ING in LIHC. The relationship between ING family genes expression and tumor associated immune checkpoints was investigated in LIHC. The molecular mechanism of ING1 mediated hepatocarcinogenesis was preliminarily discussed. RESULTS: mRNA/protein expression of different ING family genes in LIHC was analyzed in different databases, showing that ING family genes were highly expressed in LIHC. In 47 samples from 366 LIHC patients, the ING family genes were altered at a rate of 13%. By comprehensively analyzing the expression, clinical pathological parameters and prognostic value of ING family genes, ING1/5 was identified. ING1/5 was related to poor prognosis of LIHC, suggesting that they may play key roles in LIHC tumorigenesis and progression. One of the target miRNAs of ING1 was identified as hsa-miR-214-3p. Two upstream lncRNAs of hsa-miR-214-3p, U91328.1, and HCG17, were identified. At the same time, we found that the expression of ING family genes was correlated with immune cell infiltration and immune checkpoint genes. CONCLUSION: This study lays a foundation for further research on the potential mechanism and clinical value of ING family genes in the treatment and prognosis of LIHC.