Gene Signature Research Articles

Prediction of prognosis and immune response in lung adenocarcinoma based on mitophagy and lactate-related gene signatures.

Lung adenocarcinoma (LUAD) causes leading death worldwide. Mitophagy and lactate metabolism accumulation are distinctive features of LUAD. We aimed to identify lactate-related genes (LRGs) signatures based on mitophagy for predicting prognosis and immune response in LUAD. The gene expression and clinical data were downloaded from TCGA and GEO database. First, the subtype analysis was analyzed based on 29 mitophagy genes. Survival, immune, and function differences between the different subtypes were analyzed. Then, based on mitophagy genes and 14 LRGs, the best LRGs were screened to construct a risk score model and combined with clinical factors to establish a nomogram for predicting patient survival. Finally, the expression level and molecular function of the key candidate gene OGDH were verified by in vitro experiments. All the LUAD samples were divided into 2 subtypes: sub1 and sub2. The sub2 possessed worse survival. Immune score, immune checkpoint genes, and human leucocyte antigen genes in sub1 were higher than in sub2. Six optimal mitophagy-related LRGs were used to construct a risk score model. A high-risk score indicates poorer survival, higher tumor mutation burden, and higher drug sensitivity. The nomogram was robust in predicting LUAD survival. The experiments in vitro showed that knockdown of OGDH inhibited the proliferation, migration and invasion in LUAD cells. A nomogram based on the construction of the mitophagy-related lactate genes predicts prognosis and immune response in LUAD. These results could help with risk stratification and targeted therapy for LUAD.

Qualitative Transcriptional Signature for Predicting the Pathological Response of Colorectal Cancer to FOLFIRI Therapy

FOLFIRI (5-FU, leucovorin, irinotecan) is the first-line chemotherapy for metastatic colorectal cancer (mCRC), but response rates are under 50%. This study aimed to develop a predictive signature for FOLFIRI response in mCRC patients. Firstly, Spearman’s rank correlation and Wilcoxon rank-sum test were used to select chemotherapy response genes and gene pairs, respectively. Then, an optimization procedure was used to determine the final signature. A predictive signature consisting of three gene pairs (3-GPS) was identified. In the training set, 3-GPS achieved an accuracy of 0.94. In a validation set of 60 samples, predicted responders had significantly better progression-free survival than the predicted non-responders (HR = 0.47, p = 0.01). A comparable result was observed in an additional validation set of 27 samples (HR = 0.06, p = 0.02). The co-expressed genes of the signature were enriched in pathways associated with the immunotherapy response, and they interacted extensively with FOLFIRI-related genes. Notably, the expression of signature genes significantly correlated with various immune cell types, including plasma cells and memory-resting CD4+ T cells. In conclusion, the REO-based signature effectively identifies mCRC patients likely to benefit from FOLFIRI. Furthermore, these signature genes may play a crucial role in the chemotherapy.

Targeting CD206+ macrophages disrupts the establishment of a key antitumor immune axis.

CD206 is a common marker of a putative immunosuppressive "M2" state in tumor-associated macrophages (TAMs). We made a novel conditional CD206 (Mrc1) knock-in mouse to specifically visualize and/or deplete CD206+ TAMs. Early depletion of CD206+ macrophages and monocytes (Mono/Macs) led to the indirect loss of conventional type I dendritic cells (cDC1), CD8 T cells, and NK cells in tumors. CD206+ TAMs robustly expressed CXCL9, contrasting with stress-responsive Spp1-expressing TAMs and immature monocytes, which became prominent with early depletion. CD206+ TAMs differentially attracted activated CD8 T cells, and the NK and CD8 T cells in CD206-depleted tumors were deficient in Cxcr3 and cDC1-supportive Xcl1 and Flt3l expressions. Disrupting this key antitumor axis decreased tumor control by antigen-specific T cells in mice. In human cancers, a CD206Replete, but not a CD206Depleted Mono/Mac gene signature correlated robustly with CD8 T cell, cDC1, and NK signatures and was associated with better survival. These findings negate the unqualified classification of CD206+ "M2-like" macrophages as immunosuppressive.

METTL2B m3C RNA transferase: oncogenic role in ovarian cancer progression via regulation of the mTOR/AKT pathway and its link to the tumor immune microenvironment

BackgroundAberrant expression of N3-methylcytidine methyltransferase 2B (METTL2B) has been observed in various human malignancies, including those of the prostate, liver, breasts, and bladder. However, its role in ovarian cancer (OC) remains largely unexplored. This research preliminarily investigated METTL2B expression in OC and elucidated the associated molecular mechanisms.MethodsWe utilized three publicly available cancer-related databases (Genotype-Tissue Expression, Gene Expression Omnibus, and The Cancer Genome Atlas) to identify gene signatures in patients with OC and normal individuals with a specific focus on METTL2B. The role of METTL2B in OC was evaluated using patient survival data, and its impact on oncogenic behaviors in both cell and animal models, including growth potential, migration, invasion, and the tumor microenvironment, was examined. This assessment was conducted using bioinformatics tools such as Gene Set Cancer Analysis, GeneMANIA, and Tumor Immune Single-cell Hub 2. Additionally, the association between drug sensitivity and METTL2B expression was analyzed using CellMiner.ResultsMETTL2B expression was significantly elevated in OC, highlighting its potential clinical value in the diagnosis and prognosis of OC. Patients with lower METTL2B expression exhibited favorable survival. Furthermore, METTL2B knockdown significantly disrupted oncogenic behaviors in OC cell lines by suppressing the mTOR/AKT signaling pathway. Additionally, bioinformatics-based Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses suggested a close correlation between METTL2B and immune responses.ConclusionsOur research confirmed the upregulation of METTL2B in OC, suggesting its oncogenic function. However, METTL2B expression was negatively correlated with the infiltration scores of multiple immune cells, including cytotoxic cells and T cells, indicating its complex role in the tumor immune microenvironment. These findings highlight the significant clinical value of METTL2B in the diagnosis and prognosis of OC.

Chronic inflammation deters natural killer cell fitness and cytotoxicity in myeloid leukemia

AbstractNatural killer (NK) cells play an integral role in immunosurveillance against myeloid malignancies, with their mature phenotype and abundance linked to prolonged treatment-free remission in chronic myeloid leukemia (CML). However, NK cell function is suppressed during the disease, and the orchestrators of this impairment are not fully understood. Using a chimeric BCR::ABL1+ CML mouse model, we characterized the impact of the leukemic microenvironment on NK cell function. We showed that NK cells have reduced counts, immature phenotype, poor cytotoxicity, and altered expression of activating and inhibitory receptors in CML mice, which revert to a steady state upon BCR::ABL1 inhibition. Single-cell RNA sequencing revealed an inflammatory cytokine response in CML-exposed NK cells, highlighted by the tumor necrosis factor α (TNFα)-induced gene signature, upregulation of TNFα receptor 2, and enrichment of SOCS family genes such as Cish, the critical NK cell checkpoint. Ex vivo exposure of healthy NK cells to leukemic soluble factors compromised target-specific NK cell degranulation, which was partially rescued by targeting Cish or TNFα. In alignment with these findings, NK cells from healthy donors displayed suppressed cytotoxicity when exposed to plasma from untreated patients with CML, with a partial restoration upon Cish or TNFα inhibition. Furthermore, NK cells from newly diagnosed patients with CML predestined for blast crisis showed an enrichment of the TNFα-induced proinflammatory gene signature identified in CML mice. These results suggest that targeting inflammatory signaling could enhance NK cell-based immunotherapies for CML.

Multi-modal transcriptomics: integrating machine learning and convolutional neural networks to identify immune biomarkers in atherosclerosis

BackgroundAtherosclerosis, a complex chronic vascular disorder with multifactorial etiology, stands as the primary culprit behind consequential cardiovascular events, imposing a substantial societal and economic burden. Nevertheless, our current understanding of its pathogenesis remains imprecise. In this investigation, our objective is to establish computational models elucidating molecular-level markers associated with atherosclerosis. This endeavor involves the integration of advanced machine learning techniques and comprehensive bioinformatics analyses.Materials and methodsOur analysis incorporated data from three publicly available the Gene Expression Omnibus (GEO) datasets: GSE100927 (104 samples, 30,558 genes), which includes atherosclerotic lesions and control arteries from carotid, femoral, and infra-popliteal arteries of deceased organ donors; GSE43292 (64 samples, 23,307 genes), consisting of paired carotid endarterectomy samples from 32 hypertensive patients, comparing atheroma plaques and intact tissues; and GSE159677 (30,498 single cells, 33,538 genes), examining single-cell transcriptomes of calcified atherosclerotic core plaques and adjacent carotid artery tissues from patients undergoing carotid endarterectomy. Utilizing single-cell sequencing, highly variable atherosclerotic monocyte subpopulations were systematically identified. We analyzed cellular communication patterns with temporal dynamics. The bioinformatics approach Weighted Gene Co—expression Network Analysis (WGCNA) identified key modules, constructing a Protein-Protein Interaction (PPI) network from module-associated genes. Three machine-learning models derived marker genes, formulated through logistic regression and validated via convolutional neural network(CNN) modeling. Subtypes were clustered based on Gene Set Variation Analysis (GSVA) scores, validated through immunoassays.ResultsThree pivotal atherosclerosis-associated genes—CD36, S100A10, CSNK1A1—were unveiled, offering valuable clinical insights. Profiling based on these genes delineated two distinct isoforms: C2 demonstrated potent microbicidal activity, while C1 engaged in inflammation regulation, tissue repair, and immune homeostasis. Molecular docking analyses explored therapeutic potential for Estradiol, Zidovudine, Indinavir, and Dronabinol for clinical applications.ConclusionThis study introduces three signature genes for atherosclerosis, shaping a novel paradigm for investigating clinical immunological medications. It distinguishes the high biocidal C2 subtype from the inflammation-modulating C1 subtype, utilizing identified signature gene as crucial targets.

Visium spatial transcriptomics and proteomics identifies novel hepatic cell populations and transcriptomic signatures of alcohol-associated hepatitis.

Alcohol-associated hepatitis (AH) is the clinical manifestation of alcohol-associated liver disease (ALD). AH is a complex disease encompassing the dysregulation of many cells and cell subpopulations. This study used a hepatic spatial transcriptomic and proteomic approach (10X Genomics Visium) to identify hepatic cell populations and their associated transcriptomic and proteomic alterations in human AH. Formalin-fixed paraffin-embedded liver tissue from AH patients (n = 2) and non-ALD controls (donors) (n = 2) were used for Visium spatial transcriptomic and proteomic analysis. AH cell clusters and cell markers were drastically different in regard to tissue pattern and number of cell types compared to non-ALD controls. Cholangiocytes, endothelial cells, macrophages, and stellate cells were more profuse in AH relative to non-ALD controls. Transcriptionally, proliferating cell nuclear antigen-positive (PCNA+) hepatocytes in AH more closely resembled cholangiocytes suggesting they were non-functional hepatocytes derived from cholangiocytes. Furthermore, mitochondria protein-coding genes were reduced in AH versus non-ALD control hepatocytes, suggesting reduced functionality and loss of regenerative mechanisms. Macrophages in AH exhibited elevated gene expression involved in exosomes as compared to non-ALD controls. The most upregulated macrophage genes observed in AH were those involved in exosome trafficking. Gene and protein signatures of disease-associated hepatocytes (ANXA2+/CXCL1+/CEACAM8+) were elevated in AH and could visually identify a pre-malignant lesion. This study identified global cell type alterations in AH and distinct transcriptomic changes between AH and non-ALD controls. These findings characterize cellular plasticity and profuse transcriptomic and proteomic changes that are apparent in AH and contribute to the identification of novel therapeutics.

Severe toxicities in amazonian populations and the role of precision medicine in acute lymphoblastic leukemia treatment.

Corticosteroids, such as prednisone or dexamethasone, constitute integral components of antineoplastic regimens for Acute Lymphoblastic Leukemia (ALL) therapy, albeit accompanied by significant adverse effects. The multifactorial nature of interindividual variability in drug response, encompassing genetic polymorphisms, underscores the complexity of pharmacotherapy outcomes. However, pharmacogenetic investigations hitherto have predominantly focused on cohorts of European and North American descent, thus limiting the generalizability of findings to populations with minimal representation. Indigenous populations in Brazil, particularly those inhabiting the Amazon region, exhibit a distinctive genetic heritage, predominantly characterized by Native American ancestry. These populations frequently manifest suboptimal therapeutic responses and elevated mortality rates following ALL treatment. Therefore, delineating the molecular signatures of genes implicated in the corticosteroid pathway within these indigenous cohorts assumes paramount importance. This study identified novel variants within genes associated with the glucocorticoid pathway in indigenous Amazonian populations and conducted comparative analyses of variant frequencies across diverse global populations. The findings underscore the genetic uniqueness of indigenous groups and highlight the potential impact of genetic factors on adverse responses to ALL treatment. Precision medicine approaches tailored to the genetic peculiarities of indigenous populations emerge as imperative strategies for optimizing therapeutic efficacy and mitigating treatment-related toxicities in these communities.

IL-2-inducible T cell kinase deficiency sustains chimeric antigen receptor T cell therapy against tumor cells.

Despite the revolutionary achievements of chimeric antigen receptor (CAR) T cell therapy in treating cancers, especially leukemia, several key challenges still limit its therapeutic efficacy. Of particular relevance is the relapse of cancer in large part, as a result of exhaustion and short persistence of CAR-T cells in vivo. IL-2-inducible T cell kinase (ITK) is a critical modulator of the strength of T-cell receptor (TCR) signaling, while its role in CAR signaling is unknown. By electroporation of clustered regularly interspaced short palindromic repeats (CRISPR) associated protein 9 (Cas9) ribonucleoprotein (RNP) complex into CAR-T cells, we successfully deleted ITK in CD19-CAR-T cells with high efficiency. Bulk and single-cell RNA sequencing (scRNA-seq) analyses revealed down-regulation of exhaustion and up-regulation of memory gene signatures in ITK-deficient CD19-CAR-T cells. Our results further demonstrated a significant reduction of T cell exhaustion and enhancement of T cell memory, with significant improvement of CAR-T cell expansion and persistence both in vitro and in vivo. Moreover, ITK-deficient CD19-CAR-T cells showed better control of tumor relapse. Our work provides a promising strategy of targeting ITK to develop sustainable CAR-T products for clinical use.

Post-ischemic inactivation of HIF Prolyl Hydroxylases in endothelium promotes maladaptive kidney repair by inducing glycolysis.

Ischemic acute kidney injury (AKI) is common in hospitalized patients and increases the risk for chronic kidney disease (CKD). Impaired endothelial cell (EC) functions are thought to contribute in AKI to CKD transition, but the underlying mechanisms remain unclear. Here, we identify a critical role for endothelial oxygen sensing prolyl hydroxylase domain (PHD) enzymes 1-3 in regulating post-ischemic kidney repair. In renal endothelium, we observed compartment-specific differences in the expression of the three PHD isoforms in both mice and humans. Post-ischemic concurrent inactivation of endothelial PHD1, PHD2, and PHD3 but not PHD2 alone promoted maladaptive kidney repair characterized by exacerbated tissue injury, fibrosis, and inflammation. Single-cell RNA-seq analysis of the post-ischemic endothelial PHD1, PHD2 and PHD3 deficient (PHDTiEC) kidney revealed an endothelial hypoxia and glycolysis related gene signature, also observed in human kidneys with severe AKI. This metabolic program was coupled to upregulation of the SLC16A3 gene encoding the lactate exporter monocarboxylate transporter 4 (MCT4). Strikingly, treatment with the MCT4 inhibitor syrosingopine restored adaptive kidney repair in PHDTiEC mice. Mechanistically, MCT4 inhibition suppressed pro-inflammatory EC activation reducing monocyte-endothelial cell interaction. Our findings suggest avenues for halting AKI to CKD transition based on selectively targeting the endothelial hypoxia-driven glycolysis/MCT4 axis.

Potential biomarkers for MCL1 inhibitor sensitivity

MCL1 is an anti-apoptotic member of the BCL2 protein family, and its overexpression is associated with poor prognosis across various cancers. Small molecule inhibitors targeting MCL1 are currently in clinical trials for TNBC and other malignancies. However, one major challenge in the clinical application of MCL1 inhibitors is the inherent or acquired resistance to these drugs. Additionally, there is a lack of predictive biomarkers to identify which tumors will respond to MCL1 inhibition. We identified a four-gene functional signature that promotes MCL1 inhibitor resistance in TNBC cells. This gene signature (GS) can distinguish resistant from sensitive TNBC cell lines. Factors encoded by these four genes promote MCL1 inhibitor resistance at least in part through regulation of the ERK signaling pathway. This mechanism involves the upregulation of BCL2 and the downregulation of BIM, which contribute to the inhibitor resistance. Thus, we have discovered a functional GS that drives MCL1 inhibitor resistance. Currently, the MCL1 inhibitor GS-9716 is in clinical trials for TNBC therapy. If validated in clinical samples, this GS could potentially serve as a predictive biomarker for therapy response and help guide the selection of combination therapies to enhance the effectiveness of MCL1 inhibitors.

A novel necroptosis-related genes signature to predict prognosis and treatment response in bladder cancer

BackgroundNecroptosis, a form of programmed inflammatory cell death, plays a crucial role in tumor development, necrosis, metastasis, and immune response. This study aimed to explore the role of necroptosis in BLCA and construct a new prognostic model to guide clinical treatment and predict individualized treatment response.MethodsThe transcriptome profiling and the corresponding clinical data of BLCA patients were obtained from the Cancer Genome Atlas database (TCGA) and GEO databases. Univariate, multivariate and LASSO Cox regression analyses were used to identify and construct prognostic features associated with necroptosis. We constructed and validated a prognostic model associated with the patient’s overall survival (OS). A nomogram was established to predict the survival rates of BLCA patients. Finally, the correlation between risk scores and tumor immune microenvironment, somatic mutations, immunotherapy, and chemotherapy was comprehensively analyzed.ResultsThe study found two distinct NRG clusters and three gene subtypes, with significant differences in pathway enrichment and immune cell infiltration associated with different NRG clusters in the TME. In addition, we screened out six necroptosis prognosis-related genes (including PPP2R3A; CERCAM; PIK3IP1; CNTN1; CES1 and CD96) to construct a risk score prognostic model. Significant differences in overall survival rate, immune cell infiltration status, and somatic mutations existed between the high and low-risk scores in BLCA patients. Finally, drug sensitivity analysis showed that high-risk patients benefited more from immunotherapy and chemotherapy drugs.ConclusionThis study explores the importance of necroptosis in the prognosis of patients with BLCA, and the prognostic features associated with necroptosis that we identified can serve as new biomarkers to help develop more precise treatment strategies.

The local molecular signature of human peripheral neuropathic pain.

Focal nerve injuries are often associated with neuropathic pain. Preclinical research suggests altered neuroimmune signalling underlies such neuropathic pain; however, its cause remains poorly understood in humans. In this multicentre cohort study, we describe the local cellular and molecular signature of neuropathic pain at the lesion site, using Morton's neuroma as a human model system of neuropathic pain (n = 22; 18 women) compared with nerves from participants without nerve injury (n = 11; 4 women). Immunofluorescent staining revealed demyelination and chronic infiltration of immune cells in Morton's neuroma. RNA bulk sequencing identified 3349 differentially expressed genes between Morton's neuroma and controls. Gene ontology enrichment analysis and weighted gene co-expression network analyses revealed modules specific for host defence and neurogenesis. Deconvolution analysis confirmed higher densities of macrophages and B cells in Morton's neuroma than control samples. Modules associated with defence response, neurogenesis, and muscle system development as well as macrophage cell populations identified by deconvolution correlated with patients' paroxysmal or evoked pain. Of note, we identified a consistently differentially expressed gene signature (MARCO, CD163, STAB1), indicating the presence of a specific M(GC) subset of macrophages. MARCO gene expression correlated with paroxysmal pain. Targeted immunofluorescent analyses confirmed higher densities of intraneural CD163+MARCO+ macrophage subsets in Morton's neuroma. Our findings provide detailed insight into the local molecular signature in the context of human focal nerve injury. There is clear evidence for an ongoing role of the immune system in chronic peripheral neuropathic pain in humans, with macrophages and specifically the M(GC) MARCO+ subset implicated.

Integration of the bulk transcriptome and single-cell transcriptome reveals efferocytosis features in lung adenocarcinoma prognosis and immunotherapy by combining deep learning

BackgroundEfferocytosis (ER) refers to the process of phagocytic clearance of programmed dead cells, and studies have shown that it is closely related to tumor immune escape.MethodsThis study was based on a comprehensive analysis of TCGA, GEO and CTRP databases. ER-related genes were collected from previous literature, univariate Cox regression was performed and consistent clustering was performed to categorize lung adenocarcinoma (LUAD) patients into two subgroups. Lasso regression and multivariate Cox regression analyses were used to construct ER-related prognostic features, and multiple immune infiltration algorithms were used to assess the correlation between the extracellular burial-related risk score (ERGRS) and tumor microenvironment (TME). And the key gene HAVCR1 was identified by deep learning, etc. Finally, pan-cancer analysis of the key genes was performed and in vitro experiments were conducted to verify the promotional effect of HAVCR1 on LUAD progression.ResultsA total of 33 ER-related genes associated with the prognosis of LUAD were identified, and the prognostic signature of ERGRS was successfully constructed to predict the overall survival (OS) and treatment response of LUAD patients. The high-risk group was highly enriched in some oncogenic pathways, while the low-ERGRS group was highly enriched in some immune-related pathways. In addition, the high ERGRS group had higher TMB, TNB and TIDE scores and lower immune scores. The low-risk group had better immunotherapeutic response and less likelihood of immune escape. Drug sensitivity analysis revealed that BRD-K92856060, monensin and hexaminolevulinate may be potential therapeutic agents for the high-risk group. And ERGRS was validated in several cohorts. In addition, HAVCR1 is one of the key genes, and knockdown of HAVCR1 in vitro significantly reduced the proliferation, migration and invasion ability of lung adenocarcinoma cells.ConclusionOur study developed a novel prognostic signature of efferocytosis-related genes. This prognostic signature accurately predicted survival prognosis as well as treatment outcome in LUAD patients and explored the role of HAVCR1 in lung adenocarcinoma progression.

Single-cell RNA sequencing reveals immune microenvironment niche transitions during the invasive and metastatic processes of ground-glass nodules and part-solid nodules in lung adenocarcinoma

BackgroundRadiographically, ground-glass nodules (GGN) and part-solid nodules (PSN) in lung adenocarcinoma (LUAD) have significant heterogeneity in their clinical manifestations, biological characteristics, and prognosis. This study aimed to explore the heterogeneity of LUAD in different radiological phenotypes and associated factors influencing tumor evolution.MethodsWe performed single-cell RNA sequencing (scRNA-seq) on tumor tissues from eight and seven cases of GGN– and PSN–LUAD, respectively, at different disease stages, including minimally invasive adenocarcinoma (MIA), invasive adenocarcinoma (IAC), and metastatic lung cancer (MLC). Additionally, we analyzed adjacent normal tissues from four cases. Immunohistochemistry, multiplex immunofluorescence, and external scRNA-seq data were employed to confirm the expression of signature genes as well as the distribution patterns of CXCL9 + TAMs and TREM2 + TAMs. A LUAD mouse model was generated using gene editing, organoid culture, and orthotopic transplantation techniques, and comprehensive analyses such as histopathology, RNA sequencing, and Western blotting were performed to validate key pathways.ResultsDiverse cellular compositions were observed in the tumor microenvironment (TME) during GGN– and PSN–LUAD invasion and metastasis. Notably, CXCL9 + and TREM2 + tumor-associated macrophages (TAMs) exhibited the most significant enrichment changes. It was found that GGN–LUAD exhibited a stronger immune response than PSN–LUAD, with increased interaction between CXCL9 + TAMs and CD8 + tissue-resident memory T cells during invasion stage (MIA–IAC). Conversely, greater interactions between TREM2 + TAMs and tumor cells were observed in PSN–LUAD during the MLC stage. Additionally, TREM2 + TAMs were found to differentiate into TREM2 + /SPP1 + and TREM2 + /SPP1– TAMs at different stages, which promotes tumor progression. This study also emphasizes that during the transdifferentiation process of GGN– and PSN–LUAD, IFN-γ activates the STAT1 signaling pathway to regulate the activation of CXCL9 + TAMs, and further recruiting CD8 + Trm cells and activating T cells through MHC class I antigen presentation. The role of the IFN-γ/STAT1 pathway in the occurrence and development of LUAD was further validated by animal experiments.ConclusionsOur findings offer a potential therapeutic strategy to maintain a dynamic balance within the TME and improve the immunotherapy efficacy by modulating the relative proportions and functional states of CXCL9 + TAMs and TREM2 + TAMs.

The diagnostic value investigation of programmed cell death genes in heart failure

BackgroundWe aimed to identify the potential diagnostic markers and associated molecular mechanisms based on programmed cell death (PCD)-related genes in patients with heart failure (HF).MethodsThree HF gene expression data were extracted from the GEO database, including GSE57345 (training data), GSE141910 and GSE76701 (validation data), followed by differentially PCD related genes (DPCDs) was shown between HF and control samples. Enrichment and protein-protein interaction (PPI) network analyses were performed based on the DPCDs. Subsequently, a diagnostic model was constructed and validated after exploring the diagnostic markers using machine learning. A nomogram was used to determine the clinical diagnostic value. Diagnostic marker-based immune, transcription network, and gene set enrichment (GSE) analyses were performed. Finally, the drug-target network was investigated.ResultsTwenty DPCDs were revealed between the two groups. These genes, such as Serpin Family E Member 1 (SERPINE1), are mainly enriched in pathways such as the regulation of the inflammatory response. A PPI network was constructed using 14 DPCDs. Eight diagnostic markers, such as SERPINE1, CD38 molecule (CD38), and S100 calcium-binding protein A9 (S100A9), were explored using machine learning algorithms, followed by diagnostic model construction. A nomogram and immune-associated analysis was used to validate the diagnostic value of these genes and the model. Moreover, the transcription regulation network and drug-target interactions were further investigated. Finally, qRT-PCR confirmed that the expression levels of eight signature genes (CD14, CD38, CTSK, LAPTM5, S100A9, SERPINE1, SLC11A1, and STAT3) were significantly elevated in the observation group, consistent with the results of bioinformatics analysis.ConclusionsThis study constructed a valuable diagnostic model for HF using the eight identified DPCDs as diagnostic markers.

Pharmacodynamics of the S1P1 receptor modulator cenerimod in a phase 2b randomised clinical trial in patients with moderate to severe SLE

BackgroundSystemic lupus erythematosus (SLE) is a complex autoimmune disease characterised by autoreactive T and B lymphocytes. Sphingosine-1-phosphate (S1P) is involved in lymphocyte egress from peripheral lymphoid organs into the circulation....

Comprehensive Analysis of RNA Methylation Regulated gene signature and Immune Infiltration in Ischemia/Reperfusion-Induced Acute Kidney Injury.

The morbidity and mortality of acute kidney injury (AKI) are increasing. Epigenetic regulation and immune cell infiltration are thought to be involved in the AKI. However, the relationship between epigenetic regulation and immune cell infiltration in AKI has not been elucidated. This study was conducted to identify the differentially expressed genes (DEGs), differentially expressed RNA methylation genes (DEMGs), and infiltrated immune cells in the kidneys of ischemia reperfusion induced- acute kidney injury (IRI-AKI) models and further explore their relationships in IRI-AKI. This is a bioinformatic analysis using R programming language in 3 selected IRI-AKI datasets from the Gene Expression Omnibus (GEO) database, including 16 IRI-AKI kidney tissues and 10 normal kidney tissues. The DEGs were screened, and enrichment pathways were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The DEMGs and core DEMGs were identified using the R package. The ROC curve was plotted to predict disease occurrence of 7 core DEMGs. The correlation of 7 core DEMGs and other genes was analyzed using Pearson's correlation test. The gene set enrichment analysis (GSEA) of each DEMG was conducted using the R package. The upstream miRNAs and transcript factors of 7 core DEMGs were predicted based on the RegNetwork database and Cytoscape software. The STITCH database was used to predict the possible binding compounds of the 7 core DEMGs. Immune cell infiltration in kidney tissues between the IRI-AKI group and control group was evaluated using the R package. A total of 2367 DEGs were obtained, including 1180 upregulated and 1187 downregulated genes in IRI-AKI kidney associated with the cell structure, proliferation, molecule binding/interaction, and signaling pathways such as the leucocyte migration and chemokine signaling pathways. Ten DEMGs were identified, with Ythdf1, Rbm15, Trmt6, Hnrnpc, and Dnmt1 being significantly upregulated, while Lrpprc, Cyfip2, Mettl3, Ncbp2, and Nudt7 were significantly downregulated in IRI-AKI tissues. The molecules interacting with 7 core DEMGs were identified. Significant changes in the infiltration of 8 types of immune cells were observed in IRI-AKI kidneys compared to normal controls. The significant correlation between 6 core DEMGs and the infiltration of immune cells was observed. IRI may induce AKI through RNA methylation to regulate the expression of genes involved in immune cell infiltration.

Transcriptomic analysis of skeletal muscle regeneration across mouse lifespan identifies altered stem cell states.

In aging, skeletal muscle regeneration declines due to alterations in both myogenic and non-myogenic cells and their interactions. This regenerative dysfunction is not understood comprehensively or with high spatiotemporal resolution. We collected an integrated atlas of 273,923 single-cell transcriptomes and high-resolution spatial transcriptomic maps from muscles of young, old and geriatric mice (~5, 20 and 26 months old) at multiple time points following myotoxin injury. We identified eight immune cell types that displayed accelerated or delayed dynamics by age. We observed muscle stem cell states and trajectories specific to old and geriatric muscles and evaluated their association with senescence by scoring experimentally derived and curated gene signatures in both single-cell and spatial transcriptomic data. This revealed an elevation of senescent-like muscle stem cell subsets within injury zones uniquely in aged muscles. This Resource provides a holistic portrait of the altered cellular states underlying muscle regenerative decline across mouse lifespan.

Identification of early Alzheimer’s disease subclass and signature genes based on PANoptosis genes

Identification of early Alzheimer’s disease subclass and signature genes based on PANoptosis genes