Immune Characteristics Research Articles

Genetic predisposition to altered blood cell homeostasis is associated with glioma risk and survival

Glioma is a highly fatal and heterogeneous brain tumor with few known risk factors. Our study examines genetically predicted variability in blood cell indices in relation to glioma risk and survival in 3418 cases and 8156 controls. We find that increased platelet to lymphocyte ratio (PLR) confers an increased risk of glioma (odds ratio (OR) = 1.25, p = 0.005), especially tumors with isocitrate dehydrogenase (IDH) mutations (OR = 1.38, p = 0.007) and IDHmut 1p/19q intact (IDHmut-intact OR = 1.53, p = 0.004) tumors. Genetically inferred increased counts of lymphocytes (IDHmut-intact OR = 0.70, p = 0.004) and neutrophils (IDHmut OR = 0.69, p = 0.019; IDHmut-intact OR = 0.60, p = 0.009) show inverse associations with risk, which may reflect enhanced immune-surveillance. Considering survival, we observe higher mortality risk in patients with IDHmut 1p/19q with genetically predicted increased counts of lymphocytes (hazard ratio (HR) = 1.65, 95% CI: 1.24–2.20), neutrophils (HR = 1.49, 1.13–1.97), and eosinophils (HR = 1.59, 1.18–2.14). Polygenic scores for blood cell traits are also differentially associated with 17 tumor immune microenvironment features in a subtype-specific manner, including signatures related to interferon signaling, PD-1 expression, and T-cell/Cytotoxic responses. Our findings highlight immune-mediated susceptibility mechanisms with potential disease management implications.

Integrating single-cell RNA-seq and bulk RNA-seq to explore prognostic value and immune landscapes of methionine metabolism-related signature in breast cancer

BackgroundNeoadjuvant, endocrine, and targeted therapies have significantly improved the prognosis of breast cancer (BC). However, due to the high heterogeneity of cancer, some patients cannot benefit from existing treatments. Increasing evidence suggests that amino acids and their metabolites can alter the tumor malignant behavior through reshaping tumor microenvironment and regulation of immune cell function. Breast cancer cell lines have been identified as methionine-dependent, and methionine restriction has been proposed as a potential cancer treatment strategy.MethodsWe integrated transcriptomic and single-cell RNA sequencing (ScRNA-seq) analyses based on The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. Then we applied weighted gene co-expression network analysis (WGCNA) and Cox regression to evaluate methionine metabolism-related genes (MRGs) in BC, constructing and validating a prognostic model for BC patients. Immune landscapes and immunotherapy were further explored. Finally, in vitro experiments were conducted to assess the expression and function of key genes APOC1.ResultsIn this study, we established and validated a prognostic signature based on eight methionine-related genes to predict overall survival (OS) in BC patients. Patients were further stratified into high-risk and low-risk groups according to prognostic risk score. Further analysis revealed significant differences between two groups in terms of pathway alterations, immune microenvironment characteristics, and immune checkpoint expression. Our study shed light on the relationship between methionine metabolism and immune infiltration in BC. APOC1, a key gene in the prognostic signature, was found to be upregulated in BC and closely associated with immune cell infiltration. Notably, APOC1 was primarily expressed in macrophages. Subsequent in vitro experiments demonstrated that silencing APOC1 reduced the generation of tumor-associated macrophages (TAMs) with an M2 phenotype while significantly decreasing the proliferation, invasion, and migration of MDA-MB-231 and MDA-MB-468 breast cancer cell lines.ConclusionWe established a prognostic risk score consisting of genes associated with methionine metabolism, which helps predict prognosis and response to treatment in BC. The function of APOC1 in regulating macrophage polarization was explored.

Upregulation of interferon-γ response genes in monocytes and T cells identified by single-cell transcriptomics in patients with anti-citrullinated peptide antibody-positive early rheumatoid arthritis

IntroductionOur aim was to investigate the insufficiently understood differences in the immune system between anti-citrullinated peptide antibody (ACPA)-positive (ACPA+) and ACPA-negative (ACPA-) early rheumatoid arthritis (eRA) patients.MethodsWe performed multiple cytokine assays using sera from drug-naïve ACPA+ and ACPA- eRA patients. Additionally, we conducted single-cell RNA sequencing of CD45+ cells from peripheral blood samples to analyze and compare the distribution and functional characteristics of the cell subsets based on the ACPA status.ResultsSerum concentrations of interferon-γ (IFN-γ) and interleukin (IL)-12 were higher in ACPA+ eRA than in ACPA- eRA. Single-cell transcriptome analysis of 37,318 cells identified 17 distinct cell types and revealed the expansion of IL1B+ proinflammatory monocytes, IL7R+ T cells, and CD8+ CCL4+ T cells in ACPA+ eRA. Furthermore, we observed an enrichment of IFN-γ response genes in nearly all monocytes and T cells of ACPA+ eRA subsets. Heightened interactions between IFN-γ and IFN-γ receptors were observed in ACPA+ eRA, particularly between monocytes and T cells. We examined IFITM2 and IFITM3 as potential key markers in ACPA+ eRA given their pronounced upregulation and association with the IFN response. Specifically, the expression of these genes was elevated in IL1B+ proinflammatory monocytes (likely M1 monocytes), correlating with serum IFN-γ levels.DiscussionCompared to ACPA- eRA, ACPA+ eRA showed higher serum IFN-γ and IL-12 levels, upregulated IFN-γ response genes, and enhanced IFN-γ-driven monocyte-T cell interactions. These distinct immune features of the peripheral circulation in ACPA+ eRA suggest a role for type 1 helper T cell-related immunity in its pathogenesis.

Systems immunology integrates the complex endotypes of recessive dystrophic epidermolysis bullosa

Endotypes are characterized by the immunological, inflammatory, metabolic, and remodelling pathways that explain the mechanisms underlying the clinical presentation (phenotype) of a disease. Recessive dystrophic epidermolysis bullosa (RDEB) is a severe blistering disease caused by COL7A1 pathogenic variants. Although underscored by animal studies, the endotypes of human RDEB are poorly understood. To fill this gap, we apply systems immunology approaches using single-cell high-dimensional techniques to capture the signature of peripheral immune cells and the diversity of metabolic profiles in RDEB adults, sampled outside of any opportunistic infection and active cancer. Our study, demonstrates the particular inflammation and immunity characteristics of RDEB adults, with activated / effector T and dysfunctional natural killer cell signatures, concomitant with an overall pro-inflammatory lipid signature. Artificial intelligence prediction models and principal component analysis stress that RDEB is not solely confined to cutaneous issues but has complex systemic endotypes marked by immune dysregulation and hyperinflammation. By characterising the phenotype-endotype association in RDEB adults, our study lays the groundwork for translational interventions that could by lessening inflammation, alleviate the everlasting suffering of RDEB patients, while awaiting curative genetic therapies.

The Impact of the Lactation Period Gut Microbiota of Two Different Beef Cattle Breeds on Spring-Born Calves

To investigate the impact of maternal microbiota during lactation in different beef cattle breeds on their own immune levels, milk quality, and the growth and development of their offspring, this study measured the immune parameters, intestinal microbiota diversity, and milk quality of Pingliang red cattle and Simmental cattle, and performed a correlation analysis with the growth and development of their offspring. Our study showed that during lactation, Pingliang red cattle had significantly higher IL-6 levels than Simmental cattle, while the latter exhibited higher levels of immune factors such as IgG, IgA, IgM, IL-1β, and TNFα. The analysis of the intestinal microbiota of lactating cows found that Pingliang red cattle were rich in Bacteroidetes and Fibrobacteres, while Simmental cattle had a higher proportion of Actinobacteria. This difference may be related to the different adaptation strategies in energy metabolism and immune regulation between the two breeds. In addition, the analysis of milk quality between different beef cattle breeds revealed significant differences in protein, acidity, milk fat, and total solids. The correlation analysis found that Alistipes_communis, Firmicutes_bacterium_CAG_110, Alistipes_communis, Paludibacter_propionicigenes, Alistipes_sp._58_9_plus, and Bacteroidales_bacterium_55_9 were associated with both milk quality and the growth of offspring calves, including body weight, body length, chest girth, and cannon circumference. In conclusion, this study provides new insights into the intestinal microbiota, immune characteristics, and their effects on offspring health in different beef cattle breeds, and has important implications for breed selection and management strategies in the livestock industry.

Integrative analysis of ferroptosis in the hypoxic microenvironment of gastric cancer unveils the immune landscape and personalized therapeutic strategies

BackgroundFerroptosis is a cell death mode caused by excessive accumulation of lipid peroxides caused by disturbance of intracellular metabolic pathway, which is closely related to iron and cholesterol metabolism homeostasis. Its regulation within the hypoxic metabolic tumor microenvironment (TME) has the potential to improve the effectiveness of tumor immunotherapy. The predictive role of ferroptosis in gastric cancer (GC) hypoxia TME, particularly in relation to TME immune cell infiltration, has not been fully explained.MethodsBy analyzing the mRNA expression data of ferroptosis and hypoxia-related genes, a prediction model was constructed to evaluate further the predictive value of immune cell infiltration, clinical characteristics, and immunotherapy efficacy of gastric cancer, and the essential genes were validated.ResultsTwo distinct molecular states of ferroptosis-hypoxia were identified in GC. Notably, patients with high ferroptosis-hypoxia risk scores (FHRS) displayed significant levels of hypoxia and epithelial-mesenchymal transition (EMT), which were associated with unfavorable prognosis, increased chemoresistance, and heightened immunosuppression.ConclusionsThis study demonstrates that ferroptosis under hypoxic conditions significantly affects the modulation of the tumor immune microenvironment. The FHRS can independently predict prognosis in gastric cancer. Assessing the molecular status of ferroptosis-hypoxia in individual patients will help in selecting more suitable immunotherapy regimens by providing a better understanding of TME characteristics and predicting immunotherapeutic outcomes.

Identification of pyrimidine metabolism-based molecular subtypes and prognostic signature to predict immune landscape and guide clinical treatment in prostate cancer

Background We previously described the enrichment of plasma exosome metabolites in CRPC, PCa, and TFC cohorts, and found significant differences in pyrimidine metabolites. The PMGs is associated with the clinical prognosis of several cancers, but its biological role in PCa is still unclear. Methods This study extracted 98 reliable PMGs, and analyzed their somatic mutations, expression levels, and prognostic significance. Unsupervised clustering was applied to classify patients with PCa into clusters based on six PMGs that were related to the prognosis of PCa. The TME, gene mutations, and immune escape ability were compared among the clusters. A scoring algorithm based on prognostic PMGs, referred to as the PMGscore, was developed. TK1 was identified and the biological functions of TK1 were determined using loss-of-function experiments. RNA sequencing was subsequently performed to determine the molecules associated with the underlying mechanisms of TK1 function. Results In total, six out of 98 PMGs simultaneously exhibited differential expression in PCa and were correlated with BCR. Patients were clustered into two clusters according to the expression levels of these six PMGs, which reflected distinct clinical outcomes and immune cell infiltration characteristics. Clinical features, tumor prognosis, and functional annotation were analyzed. Subsequently, we constructed a prognostic signature using these six PMGs. In combination with other clinical traits, we found that the six PMGs’ prognostic signature was an independent prognostic factor for patients with PCa. Finally, we found that the expression of TK1 was higher in CRPC tissues than in PCa tissues in three GEO datasets. The results indicated that TK1 promotes the growth and metastasis of PCa cells. Conclusions We provide evidence for a PMG signature for PCa patients to accurately predict clinical prognosis. TK1 plays crucial roles in the progression of PCa cells and can be used as a potential therapeutic target for CRPC.

The systematic analysis of genes related to butyrate metabolism suggests that CDKN3 could serve as a promising therapeutic target for lung adenocarcinoma treatment

BackgroundMetabolic pathways are known to significantly impact the development and advancement of lung cancer. This study sought to establish a signature related to butyrate metabolism that is specifically linked to lung adenocarcinoma (LUAD).MethodsFor the purpose of identifying butyrate metabolism-related differentially expressed genes (BMR-DEGs) in the TCGA-LUAD dataset, we introduced transcriptome data. This was followed by the implementation of the univariate Cox and LASSO analyses in order to construct a LUAD gene signature. We performed a comprehensive analysis of gene function enrichment between the two populations at risk, thoroughly examined their immune microenvironment characteristics, and assessed the effectiveness of immunotherapy. Finally, the function of CDKN3 in LUAD was verified by in vitro experiments.ResultsThrough a comprehensive analysis of the TCGA-LUAD dataset, 51 significant BMR-DEGs were confirmed. Subsequently, five characteristic genes, CPS1, ABCC2, CDKN3, SLC2A1, and IGFBP1 were identified to create prognostic features for butyrate metabolism related outcomes in LUAD. Cox regression analysis determined that the pathological T stage, tumor stage, and RiskScore could serve as independent prognostic indicators. Analysis of the abundance of 22 immune infiltrating cells revealed that 15 immune cell types exhibited substantial differences and were strongly associated with risk ratings and prognosis. An important correlation exists between risk ratings and immunological checkpoints, which can be utilized to forecast the efficacy of treatment. In the high-risk group, there was an upregulation of the expression of PD-L2, PD-L1, and PD-1. Additionally, the risk score showed a positive correlation with TIDE and Exclusion score, while showing a negative correlation with Dysfunction score. Furthermore, the IC50 values for cisplatin, paclitaxel, and docetaxel were notably elevated in the high-risk group, indicating that these medications could potentially provide therapeutic advantages for this particular group. Finally, we determined that knockdown CDKN3 inhibited the proliferation and metastasis of LUAD cells.ConclusionWe identify and validate a novel BMR-related prognostic signature comprising 5 DEGs for LUAD patients. Our data might provide a new molecular target for LUAD treatment.

Multiomics characterization of breast angiosarcoma from an Asian cohort reveals enrichment for angiogenesis signaling pathway and tumor-infiltrating macrophages

IntroductionRecent epidemiological data suggests a rising incidence of breast angiosarcoma (AS-B) in the Western population, with over two-thirds related to irradiation or chronic lymphedema. However, unlike head and neck angiosarcoma (AS-HN), AS-B disease characteristics in Asia remain unclear.MethodsWe examined clinical patterns of angiosarcoma patients (n = 176) seen in an Asiantertiary cancer center from 1999 to 2021, and specifically investigated the molecular and immune features of AS-B in comparison to AS-HN. Data from whole genome sequencing (WGS), NanoString gene expression profiling and 10x Genomics Visium spatial transcriptomics were analyzed.ResultsMajority of cases were AS-HN (n = 104; 59.1%), while AS-B (n = 16, all females) accounted for 9.1% of the cases. The median age at diagnosis was 43 years (range, 26 to 74). Based on WGS, 4 of the 7 AS-B had non-synonymous somatic variants in 47 genes (range, 2 to 28 per case). These genes were functionally annotated and were enriched in cancer-related pathways such as regulation of cell differentiation, VEGFR and receptor tyrosine kinases signaling pathways. By NanoString gene expression profiling, ASB, compared to AS-HN, were enriched for angiogenesis, notch signaling and metastasis-associated matrix remodeling pathways. Additionally, AS-B were enriched for macrophages and CD8+ T cells expression signatures. Similarly, Visium spatial transcriptomics showed that AS-B were enriched for macrophages and T-cells.DiscussionIn conclusion, in our AS-B cases, we observed a convergence of both mutational and expression signatures on angiogenic-related pathways. Thus, anti-angiogenic therapy could be an option to treat AS-B.

Immunotherapy in Recurrent Ovarian Cancer

Background/Objectives: It remains challenging to treat recurrent ovarian cancer effectively as traditional interventions like chemotherapy and surgery have limited long-term efficacy, highlighting an urgent need for innovative approaches. Immunotherapy offers potential advantages in modulating the immune response against tumor cells and has emerged as a promising strategy in ovarian cancer management. This review discusses various immunotherapy modalities, including active and passive immune strategies, for recurrent ovarian cancer. Methods: We systematically reviewed recent immunotherapy advances for recurrent ovarian cancer, including the efficacy and mechanisms of single and dual immune checkpoint inhibitors, checkpoint inhibitor combinations with chemotherapy or radiotherapy, anti-angiogenic agents, PARP inhibitors, antibody–drug conjugates (ADC), tumor vaccines, and adoptive cell therapies (ACT). Additionally, we assessed emerging research on biomarkers predictive of immunotherapy responsiveness in ovarian cancer. Results: The findings indicate that immunotherapy, particularly combinations involving immune checkpoint inhibitors and other agents, demonstrates promising efficacy in recurrent ovarian cancer, with some therapies showing enhanced benefits in specific subtypes. The immune microenvironment in platinum-sensitive and -resistant cases exhibits distinct immunological profiles, influencing therapy outcomes. Several potential biomarkers have been identified, potentially aiding in patient stratification and treatment optimization. Conclusions: Immunotherapy significantly advances recurrent ovarian cancer treatment, with various combinations potentially improving outcomes. Further research on predictive biomarkers and immune microenvironment characteristics is crucial for personalizing immunotherapy approaches and enhancing their efficacy in managing recurrent ovarian cancer.

Decoupling Individual Host Response and Immune Cell Engager Cytotoxic Potency.

Immune cell engagers are molecular agents, usually antibody-based constructs, engineered to recruit immune cells against cancer cells and kill them. They are versatile and powerful tools for cancer immunotherapy. Despite the multiplication of engagers tested and accepted in the clinic, how molecular and cellular parameters influence their actions is poorly understood. In particular, disentangling the respective roles of host immune cells and engager biophysical characteristics is needed to improve their design and efficiency. Focusing here on harnessing antibody-dependent Natural Killer cell cytotoxicity, we measure the efficiency of 6 original bispecific antibodies (bsAb), associating an anti-HER2 nanobody and an anti-CD16 nanobody. In vitro cytotoxicity data using primary human NK cells on different target cell lines exposing different antigen densities were collected, exhibiting a wide range of bsAb dose response. In order to rationalize our observations, we introduce a simple multiscale model, postulating that the density of bsAb bridging the two cells is the main parameter triggering the cytotoxic response. We introduce two microscopic parameters: the surface cooperativity describing bsAb affinity at the bridging step and the threshold of bridge density determining the donor-dependent response. Both parameters permit ranking Abs and donors and predicting bsAb potency as a function of antibodies bulk affinities and receptor surface densities on cells. Our approach thus provides a general way to decouple donor response from immune engager characteristics, rationalizing the landscape of molecule design.

The role of histone lactylation genes in hepatocellular carcinoma prognostic models and their immune cell infiltration features: a comprehensive analysis of single-cell, spatial transcriptome, Mendelian randomization and experiment

IntroductionWith the increasing impact of hepatocellular carcinoma (HCC) on society, there is an urgent need to propose new HCC diagnostic biomarkers and identification models. Histone lysine lactylation (Kla) affects the prognosis of cancer patients and is an emerging target in cancer treatment. However, the potential of Kla-related genes in HCC is poorly understood.MethodsA variety of machine learning methods were used to construct and validate a model of differentially expressed Kla genes with comprehensive evaluations included ROC, Kaplan‒Meier curve, Cox regression, decision curve. Immune infiltration gathered with spatial transcriptome was performed using integrated data from multiple databases. Furthermore, single-cell analysis was used to discover the cell–cell communication and Mendelian randomization was used to study the causal relationships between immune cell and HCC. Lastly, qRT-PCR was used to verify the expression of Kla genes.ResultsWe established a model consisting of 12 genes that had well prognostic performance and were identified as independent prognostic factors. Single-cell analysis showed that CD8 T+ cells and conventional dendritic cells were enriched in HCC patients. Spatial transcriptomics analysis indicated that the Kla genes influenced the immune characteristics of HCC. Mendelian randomization results showed that TBNK and monocytes were the main risk factors. qRT-PCR validation results indicated that the expression of multiple genes in Huh7 cells was significantly higher than in LO2 cells.ConclusionOverall, a Kla-related model was established, which may provide new strategies and insights for the treatment and diagnosis of HCC.

Systematic identification of pathological mechanisms, prognostic biomarkers and therapeutic targets by integrating lncRNA expression variation in salivary gland mucoepidermoid carcinoma

Biologicalprocesses intricately intertwine with tumorigenesis, significantly influencing treatment outcomes and prognosis. However, the mechanisms fostering mucoepidermoid carcinoma (MEC) remain inadequately elucidated. This research utilizes expression profiles of lncRNAs from clinical MEC tissues and matched normal glandular tissues, integrating public data to explore the biological mechanisms and immune microenvironment characteristics of tumorigenesis. Gene set enrichment analysis identified key pathways, and a customized epithelial-mesenchymal transition (EMT) score elucidated the relationship between pathological processes and prognosis, while an immune signature revealed tumor microenvironment characteristics. MECs exhibited significant enrichment in EMT pathway, with key genes such as Secretogranin II, tissue factor pathway inhibitor 2, and periostin identified as contributors to the EMT process. High EMT scores correlated with upregulated EMT and immune response activity, indicating poor prognosis. Single-sample gene set enrichment analysis unveiled the tumors’ immune infiltration signature, suggesting active antigen presentation and a positive immune response for immunotherapy. Additionally, SLC2A1-AS1 and CERS6-AS1 were identified as potential mediators of EMT and the immune environment. This study provides insights into the biological processes of MEC tumorigenesis and identifies potential therapeutic targets for future research.

Host-microbe multiomic profiling identifies distinct COVID-19 immune dysregulation in solid organ transplant recipients

Coronavirus disease 2019 (COVID-19) poses significant risks for solid organ transplant recipients, who have atypical but poorly characterized immune responses to infection. We aim to understand the host immunologic and microbial features of COVID-19 in transplant recipients by leveraging a prospective multicenter cohort of 86 transplant recipients age- and sex-matched with 172 non-transplant controls. We find that transplant recipients have higher nasal SARS-CoV-2 viral abundance and impaired viral clearance, and lower anti-spike IgG levels. In addition, transplant recipients exhibit decreased plasmablasts and transitional B cells, and increased senescent T cells. Blood and nasal transcriptional profiling demonstrate unexpected upregulation of innate immune signaling pathways and increased levels of several proinflammatory serum chemokines. Severe disease in transplant recipients, however, is characterized by a less robust induction of pro-inflammatory genes and chemokines. Together, our study reveals distinct immune features and altered viral dynamics in solid organ transplant recipients.

Immune Cell Characteristics and Infections Associated with Chronic Obstructive Pulmonary Disease (COPD), Asthma, and Interstitial Lung Disease (ILD): A Mendelian Randomization Studies

Immune Cell Characteristics and Infections Associated with Chronic Obstructive Pulmonary Disease (COPD), Asthma, and Interstitial Lung Disease (ILD): A Mendelian Randomization Studies

Unravelling the Difference of Immune Microenvironment Characteristics between Esophageal Basaloid Squamous Cell Carcinoma and Conventional Esophageal Squamous Cell Carcinoma.

Esophageal basaloid squamous cell carcinoma (basaloid ESCC) is an uncommon variant of esophageal squamous cell carcinoma (ESCC). We characterized the tumor immune microenvironment features of basaloid ESCC, and compared them with conventional ESCC. One hundred and four basaloid ESCC patients and 55 conventional ESCC patients were included in Cohort 1. Among 104 basaloid ESCC, 81 were pure basaloid ESCC, and 23 were mixed basaloid ESCC with invasive basaloid ESCC components and ESCC components. In pure basaloid ESCC, there were more immature desmoplastic reaction (P<0.001), fewer peritumoral tertiary lymphoid structures (TLSs) (P<0.001), and lower tumor proportional score (TPS) and combined positive score (CPS) (P<0.001 and P=0.004) than in conventional ESCC. In mixed basaloid ESCC, the number of mature or intermediate desmoplastic reaction (P<0.001), the tumor-infiltrating lymphocytes (TILs) score (P=0.043), the proportion of stromal CD8+ TILs (P=0.047), the number of intratumoral CD20+ TILs (P<0.001), the number of peritumoral TLSs (P=0.001), the number of peritumoral matureTLSs (P=0.021), and the PD-L1 (22C3) CPS (P=0.016) were lower in the basaloid ESCC components than in the conventional ESCC components. In addition, the data of 141 ESCC patients with neoadjuvant chemoimmunotherapy (nICT) were collected to compare immunotherapeutic outcomes. Among 141 nICT-treated patients, 115 patients had residual tumor cells remaining, including 101 with conventional ESCC and 11 with basaloid ESCC. In basaloid ESCC, 18.2% patients had less than 10% residual viable tumor in the esophageal wall (effective response), which was lower than 58.6% in conventional ESCC (P=0.025). Our data indicated that basaloid ESCC had less benefits from immunotherapy than conventional ESCC, and manifested as immune "cold" with immature-type desmoplastic reaction, lower TILs, lower peritumoral TLSs, and lower PD-L1 expression than conventional ESCC.

Combined analysis of bulk, single-cell RNA sequencing, and spatial transcriptomics reveals the expression patterns of lipid metabolism and ferroptosis in the immune microenvironment of metabolic-associated fatty liver disease.

This study aims to identify key biomarkers associated with ferroptosis and lipid metabolism and investigate their roles in the progression of metabolic dysfunction-associated fatty liver disease (MAFLD). It further explores interactions between these biomarkers and the immune-infiltration environment, shedding light on how ferroptosis and lipid metabolism influence immune dynamics in MAFLD. Single-cell RNA sequencing data from liver samples were analyzed to evaluate expression variations related to ferroptosis and lipid metabolism in MAFLD patients. Gene scores were assessed to explore their impact on the immune microenvironment, particularly hepatocyte-macrophage communication. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to Bulk-RNA-Seq data to identify gene clusters associated with ferroptosis and lipid metabolism. The analyses were integrated into a risk assessment system and predictive model, with validation conducted through in vivo experiments. Integration of single-cell and WGCNA data identified 11 key genes linked to ferroptosis and lipid metabolism (e.g., IER5L, SOCS2, KLF9), significantly influencing the liver's immune microenvironment. The risk assessment system and predictive model achieved an AUC of 0.92 and revealed distinct immune and biological characteristics in MAFLD patients across risk levels. The expression patterns and biological roles of these genes were confirmed in in vivo studies. This study establishes a strong link between ferroptosis- and lipid metabolism-related gene expression and MAFLD's complexity. It provides novel insights into disease mechanisms, supporting personalized prognosis and targeted therapeutic strategies for MAFLD patients.

Association of Inducible Nitric Oxide Synthase (iNOS) Gene Diversity with Immunity Characteristics in Kampung Chicken

Association of Inducible Nitric Oxide Synthase (iNOS) Gene Diversity with Immunity Characteristics in Kampung Chicken

Peripheral Single‐Cell Immune Characteristics Contribute to the Diagnosis of Alzheimer's Disease and Dementia With Lewy Bodies

ABSTRACTObjectiveAlzheimer's disease (AD) and dementia with Lewy bodies (DLB) are common neurodegenerative diseases with distinct but overlapping pathogenic mechanisms. The clinical similarities between these diseases often result in high misdiagnosis rates, leading to serious consequences. Peripheral blood mononuclear cells (PBMCs) are easy to collect and can accurately reflect the immune characteristics of both DLB and AD.MethodsWe utilized time‐of‐flight mass cytometry (CyTOF) with single‐cell resolution to quantitatively analyze peripheral PBMCs, identifying 1228 immune characteristics. Based on the top‐selected immune features, we constructed immunological elastic net (iEN) models.ResultsThese models demonstrated high diagnostic efficacy in distinguishing diseased samples from healthy donors as well as distinguishing AD and DLB cases. The selected features reveal that the primary peripheral immune characteristic of AD is a decrease in total T cells, while DLB is characterized by low expression of I‐kappa‐B‐alpha (IKBα) in the classical monocyte subset.ConclusionsThese findings suggest that peripheral immune characteristics could serve as potential biomarkers, facilitating the diagnosis of neurodegenerative diseases.

Construction of an Oxidative Stress Risk Model to Analyze the Correlation Between Liver Cancer and Tumor Immunity.

Hepatocellular carcinoma (HCC) remains one of the most lethal cancers globally. Despite advancements in immunotherapy, the prognosis for patients with HCC continues to be poor. As oxidative stress plays a significant role in the onset and progression of various diseases, including metabolism-related HCC, comprehending its mechanism in HCC is critical for effective diagnosis and treatment. This study utilized the TCGA dataset and a collection of oxidative stress genes to determine the expression of oxidative stress-related genes in HCC and their association with overall survival using diverse bioinformatics methods. A novel prognostic risk model was developed, and the TCGA cohort was divided into high-risk and low-risk groups based on each tumor sample's risk score. Levels of immune cell infiltration and the expression of immune checkpoint-related genes in different risk subgroups were analyzed to investigate the potential link between tumor immunity and oxidative stress-related features. The expression of model genes in actual samples was validated through immunohistochemistry, and their mRNA and protein expression levels were measured in cell cultures. Four oxidative stress-related genes (EZH2, ANKZF1, G6PD, and HMOX1) were identified and utilized to create a predictive risk model for HCC patient overall survival, which was subsequently validated in an independent cohort. A significant correlation was found between the expression of these prognostic genes and the infiltration of tumor immune cells. Elevated expression of EZH2, ANKZF1, G6PD, and HMOX1 was observed in both HCC tissues and cell lines. The combined assessment of EZH2, ANKZF1, G6PD, and HMOX1 gene expression can serve as a model to evaluate the risk of oxidative stress in HCC. Furthermore, there is a notable correlation between the expression of these risk model genes and tumor immunity.