American journal of clinical and experimental immunology最新文献

Background: Leucine rich pentatricopeptide repeat containing (LRPPRC) protein is a multifunctional protein involved in cell cycle progression and tumor development. However, its prognostic significance and association with immune infiltration in Liver hepatocellular carcinoma (LIHC) remain unclear.

Methods: We utilized transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases of LIHC patients to investigate the potential pro-cancer role of LRPPRC, including differential expression of LRPPRC in LIHC, prognostic value, clinicopathological features, immune cell infiltration relevance and function enrichment analysis.

Results: Our findings suggest that LRPPRC is upregulated in LIHC and exhibits correlations with survival, clinical stage, and tumor grade in LIHC patients. Additionally, immune infiltration analysis revealed significant negative correlations between LRPPRC expression and multiple tumor-infiltrating immune cells, including CTLs, DCs, pDCs, B cells, Th17 cells, neutrophils, T cells, Mast cells, Th1 cells, Tregs, and NK cells, whereas a significant positive correlation was observed with infiltration of Th2 cells, T helper cells and Tcms. Furthermore, functional enrichment analysis indicated that LRPPRC may be involved in G2m checkpoint, mitotic spindle, E2f targets, Wnt Beta catenin signaling, spermatogenesis and other processes.

Single-cell sequencing is an emerging technology that can effectively identify cell types in tumors. In the tumor microenvironment of bladder cancer, macrophages play a crucial role in invasion and immune escape. This study aimed to assess the expression of macrophage-related genes (MRGs) in the tumor microenvironment of bladder cancer patients and construct a prognostic model based on MRGs using bioinformatics methods.

Methods: Single-cell sequencing data from bladder cancer patients was downloaded from the GEO. After quality control and cell type identification, macrophages in the samples were extracted for re-clustering. Feature genes were then identified, and MRGs were assessed. Genetic data from TCGA database bladder cancer patients was also downloaded and organized. The intersection of MRGs and the TCGA gene set was determined. Clinical information was connected with this intersection, and the data was divided into training and validation sets. The training set was used for model construction and the validation set for model verification. A prognostic model based on MRGs was built using the LASSO algorithm and Cox regression. Patients were divided into high-risk and low-risk groups based on their prognostic features, and survival information in the training and validation sets was observed. The predictive ability of the model was assessed using a ROC curve, followed by a calibration plot to predict 1-, 3-, and 5-year survival rates.

Results: Four cell types were identified, and after extracting macrophages, three cell subgroups were clustered, resulting in 1,078 feature genes. The top 100 feature genes from each macrophage subgroup were extracted and intersected with TCGA expressed genes to construct the model. A risk prediction model composed of CD74, METRN, PTPRR, and CDC42EP5 was obtained. The survival and ROC curves showed that this model had good predictive ability. A calibration curve also demonstrated good prognostic ability for patients.

Conclusion: This study, based on single-cell data, TCGA data, and clinical information, constructed an MRG-based prognostic model for bladder cancer using multi-omics methods. This model has good accuracy and reliability in predicting the survival and prognosis of patients with bladder cancer, providing a reference for understanding the interaction between MRGs and bladder cancer.

Around 80 to 85% of all lung cancers are non-small cell lung cancer (NSCLC). Previous research has aimed at exploring the genetic basis of NSCLC through individual approaches, but studies have yet to investigate the results of combining them. Here we show that analyzing NSCLC genetics through three approaches simultaneously creates unique insights into our understanding of the disease. Through a combination of previous research and bioinformatics tools, we determined 35 NSCLC candidate genes. We analyzed these genes in 3 different approaches. First, we found the gene fusions between these candidate genes. Second, we found the common superfamilies between genes. Finally, we identified mutational signatures that are possibly associated with NSCLC. Each approach has its individual, unique results. Fusion relationships identify specific gene fusion targets, common superfamilies identify possible avenues to determine novel target genes, and identifying NSCLC associated mutational signatures has diagnostic and prognostic benefits. Combining the approaches, we found that gene CD74 has significant fusion relationships, but it has no association with the other two approaches, suggesting that CD74 is associated with NSCLC mainly because of its fusion relationships. Targeting the gene fusions of CD74 may be an alternative NSCLC treatment. This genetic analysis has indeed created unique insight into NSCLC genes. Both the results from each of the approaches separately and combined allow pursuit of more effective treatment strategies for this cancer. The methodology presented can also apply to other cancers, creating insights that current analytical methods could not find.

Background: CD4⁺ T cell responses in HCV infection have a crucial role in the immunopathology of hepatitis C virus (HCV) infection. Our aim was to investigate the frequency of Th1, Th17, and Th22 cells in HCV-infected patients and elucidate their role in the progression of the disease.

Methods: Twenty-six HCV-infected patients and 26 healthy individuals were recruited. Peripheral blood mononuclear cells (PBMCs) were stained to separate CD4, IFN-γ, IL-17, and IL-22 producing cells using flow cytometry.

Results: Results showed that the mean expression of IL-22 in CD4⁺ T cells was significantly lower in HCV-infected patients compared to healthy controls. About correlation with clinical factor and T subsets, a negative correlation between the frequency of CD4⁺ IFN-γ⁺ cells and Thyroxine level (T4) was observed in the patients. The data showed a positive link between thyroid-stimulating hormone (TSH), cholesterol levels, and the frequency of Th17 cells. In addition, a positive correlation was seen between serum creatinine level with both Th1 and Th17. Ultimately, it was found that there was a positive link between viral burden and IL-17⁺ IL-22⁺ cells and a negative correlation between viral load and pure Th22.

Conclusions: Our findings indicate that Th22 cells may play a part in the immunopathology of HCV and show the associations between Thelper subsets and the clinical signs of the disease.

This article reviews the role of high-density lipoprotein cholesterol (HDL-C) in the elderly population, questioning the established view that advocates the ubiquitous health benefits of HDL cholesterol. High levels of HDL-C have been found to be associated with an increased risk of debilitating fractures, dementia, and cardiovascular disease, predominantly affecting older men, through the use of large population-based studies such as the ASPREE trial and the UK Biobank. Possible mechanisms are closely linked to cholesterol crystallization and altered HDL particle function. These findings call for a refinement of the understanding of high-density lipoprotein cholesterol (HDL-C), which implies adjustments to clinical guidelines and risk assessment strategies in older populations.

NAA40 belongs to the N-terminal acetyltransferase (NATs) family, responsible for protein N-terminal modification, and it exerts crucial roles across various cancers. However, its impact on patient prognosis and immune infiltration in hepatocellular carcinoma (HCC) remains elusive. To address this, our study delved into the comprehensive analysis of NAA40 in the context of cancer. Our pan-cancer analysis unveiled elevated NAA40 expression in multiple tumor types, including BLCA, BRCA, CHOL, COAD, ESCA, HNSC, LIHC, LUAD, LUSC, STAD, and THCA. Additionally, through a comprehensive examination across various cancer types within TCGA, we discovered that high NAA40 gene expression correlated with poor prognosis in HCC, pointing toward its role in promoting oncogenesis. Further investigation illuminated the association of increased NAA40 expression with T stage, pathologic stage, tumor status, and histologic grade. Interestingly, we noted a significant inverse correlation between NAA40 expression and the infiltration levels of immune cells, such as DC cells, neutrophils, NK cells, and T cells, in liver cancer. This observation underpins the hypothesis that NAA40 influences HCC development by modulating immune cell infiltration. Functional enrichment analysis provided valuable insights into the pathways influenced by NAA40. Enriched pathways encompassed oxidative phosphorylation, xenobiotic metabolism, bile acid metabolism, fatty acid metabolism, G2M checkpoint, and E2F targets. These findings collectively position NAA40 as a potential biomarker for prognostic prediction and monitoring the effects of immunotherapy in HCC.

Background: Glycosyltransferases (GT) play a crucial role in glycosylation reactions, and aberrant expression of glycosyltransferase-related genes (GTs) leads to abnormal glycosylation, which is associated with tumor progression. However, the prognostic value of aberrant expression of GTs in ovarian cancer (OC) and the correlation between GTs and tumor microenvironment (TME) remain unknown.

Methods: TCGA and GSE53963 databases were used to obtain data on OC patient samples. The association of GTs with OC was analyzed. Molecular subtypes were identified by consensus unsupervised clustering, followed by immune infiltration and functional enrichment analyses. Survival analysis was performed using Kaplan-Meier curves and log-rank tests. Least Absolute Shrinkage and Selection Operator (LASSO) and multifactorial cox regression were used to screen for signature genes associated with OC and used to establish prognostic models.

Result: OC patients were categorized into 5 GTs clusters using consensus unsupervised cluster analysis. Clusters D and E showed significant differences between survival, signaling pathways and immune infiltration. Then, a risk model was developed based on the 12 signature genes, which provides a more accurate evaluation of the prognosis of OC patients. We categorized patients into high-risk and low-risk groups based on the risk score and found that the survival of patients in the high-risk group was significantly lower than that in the low-risk group. Moreover, the risk score was significantly correlated with tumor microenvironment, immune infiltration, and chemotherapy sensitivity.

Conclusion: Overall, we performed a comprehensive analysis of GTs in OC patients and developed a risk model for OC. Our findings will provide a new insight to OC prognosis and treatment.

In recent years, a shift in prenatal screening methods has been observed, moving away from traditional approaches such as ultrasound and maternal serologic markers towards the utilization of noninvasive prenatal testing (NIPT) based on cfDNA extracted from peripheral blood. This cutting-edge technology has established itself as the primary screening method, attributed to its superior detection rate and reduced false-positive rate. Although NIPT predominantly focuses on screening for chromosomal abnormalities, it currently does not encompass the identification of single-gene disorders. Considering that single-gene disorders contribute significantly to birth defects, accounting for 7.5% to 12% of cases, it becomes imperative to integrate screening for single-gene disorders into the birth defect prevention and control system. This study aims to provide a succinct overview of the recent advancements in NIPT specifically tailored for monogenic disorders.

Chronic obstructive pulmonary disease (COPD) is marked by both lung-related and systemic symptoms, notably chronic inflammation. Despite pulmonary rehabilitation (PR) being a critical treatment for COPD, its influence on systemic inflammation remains unclear. This meta-analysis was conducted to assess PR's effect on circulating inflammatory markers in COPD patients. We systematically reviewed databases like PubMed, EMBASE, and Web of Science to select randomized controlled trials and observational studies that investigated the impact of PR on systemic inflammation. We calculated the mean differences (MD) in inflammatory markers before and after PR using a random-effects model and assessed the risk of bias with established tools. Our study included six investigations (four RCTs, two observational) with 147 COPD patients. Our findings show notable increases in IL-6 (MD 0.44, 95% CI 0.17-0.70, P = 0.001), CRP (MD 0.56, 95% CI 0.31-0.81, P<0.00001), and TNF-alpha (MD 0.41, 95% CI 0.12-0.70, P = 0.005) following PR. However, sensitivity analysis pinpointed the study by El-Kader et al. as a key influence on these results. Excluding this study led to nonsignificant changes. Thus, our meta-analysis uncovers an unanticipated rise in inflammatory markers post-PR in COPD patients, questioning the assumed anti-inflammatory benefits of PR.

Objective: The aim of this study was to explore the laboratory results in severe as asthma patients with omalizumab therapy and provide evidence for estimating omalizumab efficacy.

Methods: Retrospective study of 18 patients with severe asthma received omalizumab therapy in Shanghai General Hospital from 2020 to 2022 was performed. The basic data of patients were collected. The absolute number and the percentage of basophil and eosinophil in peripheral blood, total IgE level in serum, and as pulmonary function were detected at the beginning of treatment and 4 months after treatment. Differences between two groups were analyzed using Paired T test.

Results: The most common allergens collected from patients with moderate to severe asthma were dust mite (positive ratio 55.56%), mixed mold (16.67%), cat and dog dander, and Aspergillus fumigatus (11.11%). There was no significant difference in eosinophil and basophil counts in peripheral blood between the two groups. However, serum total IgE levels increased from (437.55±279.35) KU/L to (1071.42±721.28) KU/L (P=0.004), and FEV1/FVC ratio increased from (65.53±14.15)% to (73.91±13.63)% (P=0.005) after 4 months of treatment.

Conclusions: The existing laboratory indicators for evaluation of omalizumab efficacy are still very limited, and new biomarkers need to be further developed. Elevated serum IgE levels at four weeks of treatment and FEV1/FVC may be potential indicators for omalizumab monitoring.