Immune Infiltration Research Articles

Lipid metabolism genes AKR1B1 and PPARD as potential biomarkers of intervertebral disc degeneration and their correlation with immune infiltration

Lipid metabolism genes AKR1B1 and PPARD as potential biomarkers of intervertebral disc degeneration and their correlation with immune infiltration

Brachytherapy: Perspectives for combined treatments with immunotherapy.

Brachytherapy: Perspectives for combined treatments with immunotherapy.

Comprehensive characterization of T cell subtypes in lung adenocarcinoma: Prognostic, predictive, and therapeutic implications.

Comprehensive characterization of T cell subtypes in lung adenocarcinoma: Prognostic, predictive, and therapeutic implications.

Identification and verification of a combined ferroptosis- and pyroptosis-related signature for a prognostic classifier and immunosuppressive targets in colorectal cancer.

Identification and verification of a combined ferroptosis- and pyroptosis-related signature for a prognostic classifier and immunosuppressive targets in colorectal cancer.

Uncovering potential biomarkers of endometriosis: transcriptomic and single-cell analysis

BackgroundThe link between programmed cell death (PCD) and mitochondria has been documented in various diseases. However, its role in endometriosis (EMS) remains unexplored. This study aims to identify potential biomarkers in EMS associated with both PCD and mitochondrial functions.MethodsThis analysis incorporates datasets related to EMS, PCD-related genes (PCD-RGs), and mitochondria-related genes (MRGs) sourced from public repositories. To uncover potential biomarkers, differential expression analysis, weighted gene co-expression network analysis (WGCNA), Boruta feature selection, expression validation, and diagnostic assessments were conducted. Functional analyses, immune infiltration profiling, and the construction of regulatory networks further elucidated the mechanisms through which these biomarkers may influence EMS. Finally, single-cell data were leveraged to examine the expression and functionality of these biomarkers at a granular level.ResultsApoptosis-inducing factor mitochondria-associated 1 (AIFM1) and pyruvate dehydrogenase kinase 4 (PDK4) were identified as potential biomarkers, with PDK4 upregulated and AIFM1 downregulated in EMS. Both genes demonstrated strong diagnostic potential. Enrichment analyses indicated their involvement in pathways associated with the cell cycle. Immune infiltration analyses revealed that AIFM1 had a significant positive correlation with resting dendritic cells and a negative correlation with M2 macrophages, whereas PDK4 was positively associated with M2 macrophages and inversely related to follicular helper T cells. Moreover, AIFM1 and PDK4 were regulated by 16 miRNAs (e.g., hsa-mir-16-5p) and 18 lncRNAs (e.g., LINC00294). Single-cell analysis further revealed dynamic expression trends of these potential biomarkers across cell differentiation stages, including gametocytes, monocytes, mesenchymal stem cells, and neutrophils.ConclusionIn this study, potential biomarkers (AIFM1 and PDK4) related to PCD and mitochondria were identified in EMS, offering valuable insights for the diagnosis and therapeutic strategies for the disease.

CLIC1 and IFITM2 expression in brain tissue correlates with cognitive impairment via immune dysregulation in sepsis and Alzheimer's disease.

CLIC1 and IFITM2 expression in brain tissue correlates with cognitive impairment via immune dysregulation in sepsis and Alzheimer's disease.

The critical role of COL1A1 revealed by integrated bioinformatics analysis of differentially-expressed genes in colorectal cancer and inflammatory bowel disease.

The critical role of COL1A1 revealed by integrated bioinformatics analysis of differentially-expressed genes in colorectal cancer and inflammatory bowel disease.

Different Immune Infiltrate in Idiopathic Pulmonary Fibrosis Patients With Stable and Progressive Disease

Different Immune Infiltrate in Idiopathic Pulmonary Fibrosis Patients With Stable and Progressive Disease

Role of intrarenal complement production in kidney transplantation

Abstract Systemic complement is a major contributor to the onset and progression of kidney graft injury. However, the kidney itself as an important site of complement production. Renal-derived complement plays a key role in graft dysfunction, unlike in some other solid organ transplants. Complement factors are generated by multiple renal cell types under both physiological and pathological conditions and renal complement production has been shown to mediate ischemia/reperfusion injury and acute cellular and humoral rejection but protective effects of the complement cascade have been reported as well. More recently, intracellular complement production and activation (complosome) has also been shown to be an important regulator of key metabolic and cellular functions in renal cells and in immune kidney infiltrates, adding complexity to the field. Herein, we review current knowledge on the role of renal-derived complement in the pathophysiology of kidney graft damage and the current landscape of complement targeted therapeutics in kidney transplantation.

Increased ACSL6 Expression Predicts a Favorable Prognosis in Triple-negative Breast Cancer.

Long-chain acyl-coenzyme A synthases (ACSLs) are responsible for the catalysis of fatty acids into their corresponding fatty acyl-CoAs. The dysregulation of ACSLs has been increasingly recognized in cancer patients. However, the function of ACSL6 in triple-negative breast cancer (TNBC) is still completely unknown. In this study, immunohistochemistry was applied to detect ACSL6 protein expression using a TNBC tissue microarray. Additionally, the mRNA levels of ACSL6 in human normal tissues and pancancer tissues were analyzed using Genotype Tissue Expression (GTEx) datasets and The Cancer Genome Atlas (TCGA) database. The correlations between the levels of ACSL6 expression and clinical characteristics were analyzed. The survival analysis of ACSL6 in TNBC was carried out using the Kaplan‒Meier Plotter online tool. Associations of ACSL6 with immune infiltration analyses were conducted using the ESTIMATE, CIBERSORT, and TISIDB databases. The relationship between ACSL6 and sensitivity to drugs was analyzed from Genomics of Drug Sensitivity in Cancer (GDSC). The results indicated a significant increase in ACSL6 expression in TNBC tissues compared to adjacent normal tissues. However, high ACSL6 expression was significantly associated with favorable survival outcomes in TNBC patients. Enrichment analysis revealed that coexpressed genes of ACSL6 were significantly enriched in various immunity processes. ACSL6 was positively correlated with the infiltration of memory CD4 T cells, while a negative correlation was found between ACSL6 and M2 macrophages and resting dendritic cells. Further analysis revealed that high levels of ACSL6 correlated with increased survival outcomes in cancer patients who received immunotherapy. Altogether, the current findings highlight the potential value of ACSL6 as a diagnostic and prognostic marker in the treatment of TNBC.

Transcriptomic analysis reveals the function of m6A regulators in aged cochlea.

Transcriptomic analysis reveals the function of m6A regulators in aged cochlea.

Identification of telomere-related diagnostic markers in osteoarthritis based on bioinformatics analysis and machine learning.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues. Finally, potential drugs targeting candidate genes were predicted. Three telomere-related genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

UFMylation in tumorigenesis: Mechanistic insights and therapeutic opportunities.

UFMylation in tumorigenesis: Mechanistic insights and therapeutic opportunities.

Novel diagnostic biomarkers regulating macrophages autophagy in ischemic cardiomyopathy: An analysis integrating bulk RNA sequencing with single-cell RNA sequencing.

Novel diagnostic biomarkers regulating macrophages autophagy in ischemic cardiomyopathy: An analysis integrating bulk RNA sequencing with single-cell RNA sequencing.

Vitamin D enhances the effect of Soufeng sanjie formula in alleviating joint inflammation in CIA mice through VDR-NOTCH3/DLL4 signaling in macrophages.

Vitamin D enhances the effect of Soufeng sanjie formula in alleviating joint inflammation in CIA mice through VDR-NOTCH3/DLL4 signaling in macrophages.

Discovery of core genes and intercellular communication role in osteosarcoma.

Osteosarcoma is a primary malignant bone tumor that affects children and young adults. Understanding the molecular mechanisms underlying osteosarcoma is critical to develop effective treatments. This study aimed to identify core genes and explore the role of intercellular communication in osteosarcoma. We used GSE87437 and GSE152048 dataset to conduct a weighted correlation network analysis (WGCNA) and identify co-expression modules. The enriched biological processes and cellular components of the genes in the steelblue module were analyzed. Next, we explored the expression, diagnostic value, correlation, and association with immune infiltrate of CCSER1 and LOC101929154. Finally, we utilized CIBERSORT algorithm to predict the infiltrated immune cells in osteosarcoma tissues. Our results identified 44 co-expression modules, and the steelblue module was mainly associated with axon development, axonogenesis, and innervation. CCSER1 and LOC101929154 were significantly upregulated in osteosarcoma tissues with poor response to preoperative chemotherapy. Moreover, the expressions of CCSER1 and LOC101929154 were positively correlated. The area under the receiver operating characteristic curve of CCSER1 and LOC101929154 was 0.800 and 0.773, respectively. The expression of CCSER1 was negatively correlated with follicular helper T cells and positively correlated with M0 macrophages, while LOC101929154 was negatively correlated with activated mast cells. Besides, CD4 memory-activated T cells were observed at lower levels in patients who responded well to chemotherapy. Our study identified core genes CCSER1 and LOC101929154 and provided insight into the intercellular communication profile in osteosarcoma. Our results suggested that targeting CCSER1, LOC101929154, and CD4 memory-activated T cells may be a promising strategy for the treatment of osteosarcoma.

Integrating Single-Cell Sequencing and Transcriptome Analysis to Investigate the Role of Ferroptosis in Ischemic Stroke and the Molecular Mechanisms of Immune Checkpoints.

Integrating Single-Cell Sequencing and Transcriptome Analysis to Investigate the Role of Ferroptosis in Ischemic Stroke and the Molecular Mechanisms of Immune Checkpoints.

Single‐Cell Profiling Reveals Conserved Differentiation and Partial EMT Programs Orchestrating Ecosystem‐Level Antagonisms in Head and Neck Cancer

ABSTRACTHead and neck squamous cell carcinoma (HNSC) exhibits profound intratumoral heterogeneity, driven by dynamic interactions between malignant cells and the tumour microenvironment (TME). Using consensus non‐negative matrix factorisation (cNMF) on multi‐site HNSC single‐cell transcriptomes, we resolving conserved meta‐programs define cellular ecosystems. Six major epithelial programmes emerged, including a differentiation‐associated programme (Epi_Diff) correlated with SPDEF activity and favourable patient prognosis, and an invasive programme (Epi_pEMT) potentially controlled by TEAD4‐mediated ECM remodelling, exhibiting partial EMT markers (VIM, TGFB1). Compartment‐specific crosstalk analysis revealed Epi_pEMT cells may coordinate with mCAF1 fibroblasts and TAM(SPP1) through COL1A1‐CD44 and SPP1‐CD44 signalling, suggesting potential formation of a pro‐invasive niche. Conversely, Epi_Diff cells may interact with NK/T cells through CEACAM5‐CD8A and CCL5‐ACKR2, and may contribute to inhibit immune infiltration. Multi‐compartment correlation analysis revealed three ecosystem‐level patterns: (1) Inverse association between Epi_Diff and Epi_pEMT (Spearman R = −0.43); (2) Negative correlation between mCAF1 abundance and cCAF frequency (R = −0.48); (3) TAM(SPP1) dominance inversely correlating with both TAM(C1Q) (R = −0.43) and NK/T infiltration (R = −0.36). These axes suggest a potential hierarchical ecology framework where lineage‐specific polarisation and inter‐compartment synergies may collectively govern disease progression.

Analysis of ferroptosis-related key genes and regulatory networks in diabetic foot ulcers.

Diabetic foot ulcers (DFUs) is a severe complication of diabetes. Recent evidence suggests that ferroptosis, a form of regulated necrosis, may play a significant role in the progression of DFU. However, the precise molecular mechanisms remain elusive. This study aims to identify ferroptosis-related genes (FRGs) and the signaling pathways involved in DFU progression by analyzing the gene expression profiles of DFU. Differentially expressed genes (DEGs) were identified by analyzing gene expression data from two DFU-related datasets (GSE38396, and GSE143735). FRGs were collected from both datasets and the literature. DEGs were then intersected with FRGs to identify ferroptosis-related differentially expressed genes (FRDEGs) in DFU. Functional enrichment analysis, protein-protein interaction (PPI) network analysis, receiver operating characteristic (ROC) curve analysis, and regulatory network interaction analysis (including mRNA-miRNA, mRNA-transcription factor (TF), and mRNA-drug interactions) were performed on the FRDEGs. Additionally, immune infiltration analysis was conducted using CIBERSORTx. Finally, skin tissue samples from clinical patients were collected, and the expression levels of FRDEGs in DFU samples were validated through reverse transcription quantitative real-time PCR (RT-qPCR), immunohistochemistry (IHC) and Immunofluorescence (IF), to uncover potential new targets for the diagnosis and treatment of DFU. A total of 14 DFUs samples (non-healing group) and 12 control samples (healing group) were obtained in this study. We identified 276 DEGs in DFUs samples compared to controls, with 121 up-regulated and 155 down-regulated genes. By intersecting DEGs with ferroptosis-related genes, we identified 10 FRDEGs (AURKA, CTH, FBLN1, FTL, GLS2, KDM5C, MYH9, PCNA, PYCR1, and SPARC). The GO and KEGG analysis results showed that FRDEGs were mainly enriched in biological processes such as amino acid biosynthesis and tight junction pathways. Further analysis of FRDEGs identified ten hub genes closely associated with 112 TFs, 34 miRNAs, and 50 drugs or molecular compounds. Additionally, RT-qPCR validation of skin tissue samples from 8 DFU patients and 8 controls showed that AURKA were significantly up-regulated in DFU, IHC and IF analysis further demonstrated elevated AURKA protein expression in DFU samples. Moreover, AURKA was identified as a potential diagnostic marker for diabetic wound healing, with high diagnostic accuracy based on ROC curve analysis (AUC = 0.950 in the combined dataset, and AUC = 0.881 in the validation dataset). These findings highlight AURKA as a key gene involved in ferroptosis and a potential target for the diagnosis and monitoring of DFUs. This study identified FRDEGs associated with DFUs, highlighting AURKA as a key diagnostic marker. These findings offer valuable insights into the molecular mechanisms driving DFUs and suggest potential therapeutic targets for their management.

TME-responsive nanocomposite hydrogel with targeted capacity for enhanced synergistic chemoimmunotherapy of MYC-amplified osteosarcoma.

TME-responsive nanocomposite hydrogel with targeted capacity for enhanced synergistic chemoimmunotherapy of MYC-amplified osteosarcoma.