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Exploring the therapeutic targets and signaling mechanisms of quercetin activity against radiation skin ulcer based on the observational research of network pharmacology.

Radiation skin ulcer is a common adverse complication after radiotherapy. Currently, there is no efficient therapy for this complication. In this study, we searched for the potential pathological targets of radiation skin ulcer and the potential pharmacological targets of quercetin, respectively, and obtained the potential therapeutic targets after intersection. Subsequently, an array of bioinformatics assessments on possible therapeutic targets was conducted, encompassing functional enrichment studies, analysis of protein interaction networks, identification of key targets, and validation through molecular docking. The enrichment analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways shows that the therapeutic effect of quercetin on radiation skin ulcer may be through targeting aging cells. In addition, we identified 5 core targets, including AKT1, EGFR, MAPK3, SRC, and TP53. They are significantly enriched in EGFR tyrosine kinase inhibitors (SRC, AKT1, EGFR, and MAPK3) and epidermal growth factor receptor signaling pathways (SRC, EGFR, and AKT1), indicating the importance of EGFR signaling. Quercetin may have a therapeutic effect on radiation skin ulcer by targeting aging cells. Specifically, it may act through 4 core targets, including AKT1, EGFR, SRC, and TP53.

Quercetin

Multi-omics profiling of cerebrospinal fluid in autoimmune encephalitis: insights into pathogenesis and therapeutic targets.

BACKGROUND: Autoimmune encephalitis (AIE) is a rare, severe inflammatory brain disease, with its pathogenesis not yet fully elucidated. This study aimed to characterize proteomic and metabolomic alterations in the cerebrospinal fluid (CSF) of AIE patients and identify potential therapeutic targets. METHODS: 65 consecutive AIE patients and age-matched concurrent controls were enrolled, respectively. Clinical characteristics, including blood and CSF laboratory findings, were compared between the two groups, and CSF samples were collected for multi-omics analysis. Differentially expressed proteins (DEPs) and metabolites (DEMs) between AIE patients and controls were identified using data-independent acquisition-based proteomics and targeted liquid chromatography-mass spectrometry-based metabolomics, followed by integrated multi-omics analysis. RESULTS: Compared with controls, AIE patients had lower levels of triglyceride and C1q, but higher HDL-CH levels, neutrophil counts, and eosinophil counts in blood. CSF leukocyte, erythrocyte, lymphocyte, and mononuclear cell counts were also elevated in AIE patients. Proteomic analysis identified 163 DEPs, with enrichment of 87 canonical pathways primarily associated with immune-inflammatory responses, neuronal-synaptic dysfunction, and cell signaling and metabolic pathways. Metabolomic analysis recognized 21 DEMs, predominantly amino acids, lipids, and carbohydrates, which were involved in lipid-carbohydrate metabolism and immune regulation. Integrated multi-omics analysis validated these findings and identified several potential therapeutic targets for AIE, including the IL6-STAT3 axis. CONCLUSIONS: Integrated multi-omics analysis systematically delineates cellular and molecular alterations underlying AIE. Immune-inflammatory response and lipid metabolism are pivotal in AIE progression and the IL6-STAT3 axis holds promise as a potential therapeutic target.

Humans

Identification and genetic validation of potential therapeutic targets for pulmonary hypertension through multi-omics causal inference.

Pulmonary hypertension (PH) underscores the urgent need for novel therapeutic targets. This study aimed to employ a proteome-wide Mendelian randomization (MR) approach to systematically identify circulating proteins causally associated with PH, thereby providing genetically validated candidate targets for drug development. We adopted a 2-sample MR design, integrating large-scale plasma proteomic quantitative trait loci (pQTL) data (encompassing 4148 proteins) and summary statistics from a large-scale PH genome-wide association study (2047 cases, 8301 controls). Candidate targets were screened through a multilayered analytical pipeline comprising proteomic MR, transcriptomic MR, and summary-data-based Mendelian randomization. The ultimately identified MR-Identified Causal Candidate Targets (MR-ICTs) underwent rigorous Bayesian colocalization analysis, followed by biological characterization through functional enrichment analysis, single-cell transcriptomics, and phenome-wide association studies. Through robust genetic causal inference, this study provides that circulating proteins such as LYZ, GREM2, NID1, and PF4V1 play causal roles in PH pathogenesis. These findings offer a set of rigorously genetically validated, high-priority therapeutic targets for developing novel PH treatments, specifically addressing key pathological mechanisms such as innate immunity, BMP signaling pathway dysregulation, and platelet activation. Our multi-dimensional analysis ultimately identified 6 MR-ICTs causally associated with PH. Notably, the causal associations for lysozyme C (LYZ), gremlin-2 (GREM2), nidogen-1 (NID1), and platelet factor 4 variant 1 (PF4V1) were stringently validated by Bayesian colocalization analysis (posterior probability for hypothesis 4 [PPH4], indicating a shared causal variant, > 0.99). Functional enrichment analysis revealed significant involvement of these targets in immune response and TGF-β signaling pathways. Single-cell analysis further elucidated their cell-type-specific expression, with LYZ predominantly expressed in monocytes and PF4V1 almost exclusively in platelets.

Hypertension, Pulmonary

Potential therapeutic targets for ovarian hyperstimulation syndrome revealed by proteome-wide mendelian randomization and colocalization analysis.

Ovarian hyperstimulation syndrome (OHSS) is a severe complication associated with assisted reproductive technologies, characterized by metabolic, immune and vascular disorders. Understanding the molecular mechanisms underlying OHSS could reveal potential therapeutic targets and improve patient outcomes. In this study, We aimed to utilize proteome-wide Mendelian randomization (MR) and colocalization analysis to identify plasma proteins associated with OHSS and evaluate their potential as therapeutic targets through druggability assessment. We employed proteome-wide MR analysis summary data-based Mendelian randomization (SMR) analysis and phenome-wide association study (PheWAS) analysis to establish causal relationships between plasma proteins and OHSS. Colocalization analysis confirmed overlaps between proteins and genetic signals associated with OHSS. Pathway and network analyses were conducted to explore biological functions and protein interactions, while drug-target databases were queried for potential therapeutic interventions. Our results showed that 4 key proteins, including Suprabasin (SBSN), SLAMF4 (CD244), Enolase 3 (ENO3) and Thioredoxin domain-containing protein 12 (TXNDC12) were identified as significant contributors to OHSS. Pathway enrichment and interaction analyses further supported their involvement in metabolic, immune and structural pathways related to OHSS. Drug availability for colocalized proteins reveled potential drug targets for ENO3 (2-deoxy-D-glucose), CD244 (lenalidomide) and TXNDC12 (Auranofin), while no potential drug targets were identified for SBSN. Over all, our study identified15 plasma proteins, including SBSN, CD244, ENO3, and TXNDC12, as key contributors to the risk of OHSS through MR and colocalization analysis. These proteins were involved in metabolic regulation, immune response and antioxidant pathways, highlighting potential therapeutic targets and suggesting new directions for treatment strategies.

Humans

Multi-omics approaches in idiopathic pulmonary fibrosis: from molecular mechanisms to therapeutic targets and precision medicine.

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with limited therapeutic options and marked molecular heterogeneity. Despite available antifibrotic therapies, disease progression remains poorly predictable, highlighting the need for improved mechanistic understanding and therapeutic targeting. This review summarizes recent advances in multi-omics research to elucidate the molecular mechanisms underlying IPF and to identify potential biomarkers and pharmacological targets. Multi-omics studies, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome profiling, and single-cell sequencing, have revealed key pathogenic mechanisms in IPF. Genetic susceptibility factors such as MUC5B promoter variants and telomere-related genes contribute to disease risk. Epigenetic regulation, including DNA methylation, histone modifications, and non-coding RNAs, plays a central role in fibrotic remodeling. Transcriptomic and proteomic analyses have identified dysregulated signaling pathways, including TGF-β, mTOR, cellular senescence, and extracellular matrix remodeling. Metabolomic alterations indicate disrupted lipid and amino acid metabolism. Importantly, integration of multi-omics datasets enables the identification of molecular endotypes, candidate biomarkers, and potential therapeutic targets. However, challenges including data integration, tissue heterogeneity, limited cohort size, and the need for functional validation remain important barriers to clinical translation. Continued development of multi-omics approaches may facilitate more accurate disease classification and support the development of personalized therapeutic strategies for IPF.

biomarkers

Circulating inflammatory proteins as causal drivers and therapeutic targets in asthma: insights from genetic and pathway-based analyses.

OBJECTIVE: To identify circulating inflammatory proteins with potential causal roles in asthma development through integrated genetic and pathway-based analyses, and to evaluate their potential as therapeutic targets. METHODS: We used genetically anchored instrumental variables from 180 protein quantitative trait loci (pQTLs) to assess the causal effects of 91 circulating inflammatory proteins on asthma risk, using large-scale GWAS datasets. Analytical robustness was evaluated through pleiotropy and heterogeneity testing. Functional enrichment and literature-based pathway analyses were performed to support biological plausibility and validate findings. RESULTS: Four proteins showed significant causal effects on asthma: CCL19 and LIFR were protective (OR = 0.89 and 0.91, p&#x2009;&#x2264;&#x2009;6.8E-03), while ARTN and IL6 were associated with increased risk (OR = 1.15 and 1.18, p&#x2009;&#x2264;&#x2009;1.1E-04). We also identified reverse causal effects of asthma on 11 cytokines, including MMP10, TGFB1, IL33, and IL18R1. Most of these proteins were enriched in pathways related to cytokine signaling and immune response (p&#x2009;<&#x2009;0.001). All identified proteins had prior literature support linking them to asthma or airway inflammation. CONCLUSIONS: Our findings highlight a subset of circulating inflammatory proteins that are likely causal in asthma pathogenesis and may serve as promising targets for therapeutic intervention. These results offer novel insights into the immunological mechanisms underlying asthma and support the utility of genetic causal inference in target prioritization.

Asthma

Editor's Choice - Aquaporin-4: A Predictor and Therapeutic Target for Permanent Paraplegia after Endovascular Thoraco-abdominal Aortic Aneurysm Repair.

OBJECTIVE: Endovascular thoraco-abdominal aortic aneurysm (TAAA) repair can impair spinal cord perfusion, leading to paraplegia. The mechanisms driving this devastating complication are poorly understood. This study aimed to interrogate the cerebrospinal fluid (CSF) proteome in patients after TAAA repair to identify biomarkers that herald permanent paraplegia. It also aimed to investigate a potential therapeutic target identified by proteomics using an in vivo model of ischaemic spinal cord injury (iSCI). METHODS: CSF was collected for proteomic analysis from patients before and following TAAA repair. A differentially expressed protein identified in human paraplegic subjects was subsequently interrogated in a rodent model of iSCI. The protein composition of CSF was analysed using tandem mass tag proteomics. Neurological examinations were carried out by a blinded neurologist and T2 weighted magnetic resonance imaging (MRI) was used to measure spinal cord volume and oedema. A rodent model of iSCI was used to investigate a clinically relevant therapeutic target informed by proteomic findings. RESULTS: CSF analysis was taken from 37 patients, all of whom had aneurysm repair using a custom branched and or fenestrated device (median age 73.5 years, range 67 - 78 years; 27 men, ten women; Crawford classification: six type I, 11 type II, 15 type III, three type IV, and two type V). Five patients remained permanently paraplegic and seven recovered from transient paraplegia. The CSF of patients who remained paraplegic contained approximately fourfold more aquaporin-4 (AQP4) (41.8 &#xb1; 19.2 ng/mL, n = 5) than those who recovered from paraplegia (10.8 &#xb1; 1.3 ng/mL, n = 7; p = .005) or did not develop paraplegia (10.8 &#xb1; 1.2 ng/mL, n = 25; p = .004). Permanently paraplegic patients had CSF AQP4 levels > 15 ng/mL and this was associated with greater cord oedema on T2 weighted MRI (1.77 &#xb1; 0.19 vs. 1.03 &#xb1; 0.36; p = .032). In a rodent model of iSCI, AQP4 inhibition preserved spinal neurons and glia in the dorsal horn and intermediate zones of white matter (p = .004) and protected against ischaemia induced paraplegia (p < .001). CONCLUSION: The AQP4 level in the CSF of a patient represents a prognostic marker of permanent paraplegia after TAAA repair and highlights a novel therapeutic target. These findings represent a conceptual advance in the management of iSCI.

Paraplegia

Phosphoproteomics delineates hepatocellular carcinoma subtypes and pinpoints therapeutic targets.

BACKGROUND AND AIMS: Only a minority of patients could benefit from systemic therapy owing to the high heterogeneity of HCC. Therefore, a deeper understanding of the pathogenesis of HCC is essential for precision therapy. Genomic and proteomic studies of HCC have enhanced our understanding of HCC. However, the phosphoproteomic characterization of HCC remains poorly understood. APPROACH AND RESULTS: We conducted an in-depth analysis of a clinical cohort of HCC using high-coverage phosphoproteomic. Effective therapeutic targets were validated using liver cancer cell lines and HCC patient-derived xenograft mouse models that correspond to the phosphoproteomic subtypes of HCC. Phosphoproteomic analysis classified HCC into 3 subtypes, A, B, and C, with increasing malignancy and correlation with clinical features, including patient prognosis, tumor staging, serum alpha-fetoprotein levels, tumor thrombus, and tumor size. Phosphoproteomic subtyping deeply reflected the biological characteristics and clinical features of patients with HCC&#x200b;&#x200b;&#x200b;&#x200b;&#x200b;&#x200b;. The profiles of HCC-dysregulated kinase activities inferred from the different phosphoproteomic subtypes consistently identify increased kinase activity related to cell proliferation. Subtype-C HCC patients showed the most significant dysregulation, indicating a potential therapeutic target. The corresponding drug, bosutinib, demonstrated efficacy in inhibiting the growth of subtype C tumors in liver cancer cell lines and HCC patient-derived xenograft mouse models representative of the phosphoproteomic HCC subtypes. CONCLUSIONS: Our study provides a comprehensive exploration of the phosphoproteomic landscape of HCC, establishing new subtypes that match clinical features and identifying potential therapeutic targets for the most malignant C subtype.

Carcinoma, Hepatocellular

Integrating multi-ancestry common and rare variant mapping accelerates therapeutic target discovery.

Integrating human genetics into therapeutic discovery accelerates drug development. However, ancestral biases in historical cohorts have left critical functional variation largely uncharted. Here, we leverage the diverse NIH All of Us Research Program to conduct comprehensive common- and rare-variant association analyses for 624 quantitative traits across 369,655 ancestrally diverse individuals. We identified 6,181 genome-wide significant locus-trait associations (526 novel) and 416 gene-trait associations (105 novel) via rare-variant burden testing. By integrating fine-mapping with computational variant-effect predictors, we systematically prioritized rare, likely causal variants driving these signals. Jointly modeling common and rare variation with protein-class annotations significantly improved the identification of known drug targets compared to common-variant analysis alone. Notably, we identified NRG4 as a high-confidence candidate therapeutic target for preserving kidney function. Our findings demonstrate that characterization of rare and common variation across diverse populations enhances causal gene discovery and identifies novel, actionable therapeutic targets.

Journal Article

Integrated multi-omics analysis and functional experiments reveals PPAP2C as a potential prognostic biomarker and therapeutic target in breast cancer.

BACKGROUND: This study aims to systematically elucidate the clinical significance and biological function of the phospholipid phosphatase (PLPP) family member (PPAP2C) phosphatidic acid phosphatase type 2C in breast cancer, and to evaluate its potential as a prognostic biomarker and therapeutic target. METHODS: Gene expression data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) databases were integrated to characterize the expression profile of PLPP family members, focusing on PPAP2C in breast cancer. The prognostic value of PPAP2C, initially identified at the mRNA level (TCGA, (METABRIC) Molecular Taxonomy of Breast Cancer International Consortium, Gene Expression Omnibus (GEO)), was confirmed at the protein level by immunohistochemistry (IHC) on tissue microarrays (TMA). The oncogenic functions of PPAP2C were investigated in triple-negative breast cancer (TNBC) cells through CRISPR-Cas9-mediated knockout and ectopic overexpression, with assessment of key phenotypes including proliferation, colony formation, migration, and invasion. In vivo validation was subsequently performed using an MDA-MB-231 xenograft model. RESULTS: PPAP2C exhibits the most significant overexpression pattern across 33 cancer types (upregulated in 16 cancers, downregulated in only 3). Compared with normal tissues, PPAP2C showed specific overexpression in breast cancer tissues and was significantly associated with advanced clinical stages and aggressive subtypes (HER2+ and TNBC). Survival analysis demonstrated that high PPAP2C expression correlated with significantly shorter overall survival and disease-free survival, which was further validated in METABRIC and GEO cohorts. Tissue microarray analysis confirmed higher PPAP2C protein positivity in tumor tissues (94.7%) than in adjacent normal tissues (59.7%), with worse OS and RFS in high-expression groups. Multivariate analysis identified PPAP2C as an independent prognostic factor for OS. Functional experiments revealed that PPAP2C knockout (via 5-bp/1-bp frameshift mutations) suppressed TNBC cell proliferation, colony formation, migration, and invasion, while overexpression enhanced these phenotypes. In vivo studies further demonstrated complete tumor regression in MDA-MB-231 xenografts upon PPAP2C knockout. CONCLUSION: This study identifies PPAP2C as a key oncogenic driver and a robust independent prognostic biomarker in breast cancer. The findings provide compelling evidence that PPAP2C represents a promising therapeutic target, offering a new strategic avenue for precision therapy, particularly for aggressive breast cancer subtypes.

PLPP2

Machine learning identifies ac4C-related prognostic signature and TUBA1C as therapeutic target in COAD.

To explore the role of N4-acetylcytidine (ac4C)-related genes (acRGs) in colon adenocarcinoma (COAD) and identify reliable prognostic biomarkers and potential therapeutic targets. Multi-source transcriptomic datasets (TCGA-COAD, GSE39582, GSE17536) and single-cell RNA-seq data were analyzed. Ten machine learning algorithms were integrated to construct an acRG-based prognostic signature (acRGBS). Immune microenvironment (TME) and genomic profiling were performed, with in vitro functional experiments validating TUBA1C's role. acRGBS, comprising four hub genes (SARAF, CDC42SE2, TSPYL2, TUBA1C), effectively stratified COAD patients into high- and low-risk groups with distinct survival outcomes and was an independent prognostic factor. High-risk patients exhibited increased genomic instability and immunosuppressive TME, while low-risk patients had favorable immunotherapy response. TUBA1C was overexpressed in COAD cells, and its knockdown inhibited proliferation/migration and induced apoptosis. The acRGBS is a robust prognostic tool for COAD, and TUBA1C serves as a candidate therapeutic target, providing new insights for personalized COAD management.

Humans

SLC1A5 and NUMA1 are potential regulators and therapeutic targets of ferroptosis in diffuse large B-cell lymphoma.

BACKGROUND: Ferroptosis, a form of regulated cell death driven by iron-dependent lipid peroxidation, has emerged as a potential therapeutic target in various cancers, including diffuse large B-cell lymphoma (DLBCL). This study aimed to identify and characterize ferroptosis-related panel genes with prognostic value in DLBCL. METHODS: Transcriptomic data from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were analyzed to identify differentially expressed genes (DEGs) in DLBCL samples. Gene set variation analysis (GSVA) and network topology analysis were performed to identify key ferroptosis-related genes. Lasso regression was utilized to construct a prognostic model based on the identified panel genes. In vitro experiments, including gene silencing, overexpression, and ferroptosis induction, were conducted to evaluate the functional roles of the identified genes, NUMA1 and SLC1A5, in DLBCL cells. RESULTS: A panel of ferroptosis-related genes with prognostic value, including NUMA1 and SLC1A5, was identified in DLBCL samples. Silencing SLC1A5 or overexpressing NUMA1 in DLBCL cells enhanced sensitivity to ferroptosis inducers, increased intracellular labile iron and lipid peroxidation levels, promoted mitochondrial damage, and modulated the expression of key ferroptosis markers. Furthermore, SLC1A5 silencing or NUMA1 overexpression augmented radiation-induced ferroptosis in DLBCL cells. CONCLUSION: NUMA1 and SLC1A5 are potential ferroptosis regulators and therapeutic targets in DLBCL. Silencing the ferroptosis-suppressive transporter SLC1A5 or restoring NUMA1 expression promotes lipid peroxidation and ferroptotic cell death, thereby sensitizing DLBCL cells to ferroptosis and enhancing radiosensitivity-providing a rationale for novel ferroptosis-based therapeutic strategies.

Humans

Oncogenic EME1 promotes tumor progression and immune modulation in human cancers with therapeutic targeting potential.

BACKGROUND: EME1, a critical DNA repair endonuclease, has emerged as a potential oncogene implicated in genome instability and cancer progression. However, its pan-cancer roles, prognostic significance, immune interactions, and therapeutic targeting remain underexplored. METHODS: We conducted a comprehensive pan-cancer analysis integrating multi-omics data from public databases, including TIMER2.0, GEPIA2, TISIDB, and cBioPortal, to evaluate EME1 expression, genetic alterations, and their association with clinical outcomes, immune infiltration, and molecular pathways. Virtual screening of 3180 FDA-approved drugs and molecular dynamics (MD) simulations were employed to identify and validate potential EME1 inhibitors. RESULTS: EME1 was significantly overexpressed in various human cancers and positively associated with advanced tumor grade and stage. High EME1 expression and mutations were linked to poor overall and disease-free survival. Immunogenomic profiling revealed strong positive correlations between EME1 and myeloid-derived suppressor cells (MDSCs), alongside a negative association with endothelial cell function, suggesting immunosuppressive roles. Machine learning models based on EME1-associated genes demonstrated high predictive accuracy for liver hepatocellular carcinoma (AUC&#x2009;>&#x2009;0.90). Virtual screening identified eight promising drug candidates, including Everolimus and Dioscin, with strong binding affinities. MD simulations confirmed the stability of these interactions, particularly for Dioscin. CONCLUSION: This study reveals the multifaceted oncogenic roles of EME1 in tumor progression, immune evasion, and prognosis. It proposes EME1 as a promising biomarker and therapeutic target across multiple cancer types. The identified drug candidates warrant further in vitro and in vivo validation for potential repurposing in EME1-targeted cancer therapy.

EME1

Insights into FACT in Cancers with Targeted Therapeutic Implications.

Facilitates chromatin transcription (FACT) is an evolutionarily conserved chromatin remodeling factor. It controls chromatin states in an ATP-independent manner via the regulation of chromatin assembly and disassembly. Through such regulation, FACT is involved in controlling transcription and other DNA-transacting processes such as replication and repair. However, it is surprisingly found to be upregulated in various cancers, and upregulated FACT induces oncogenesis and supports cancer cell survival, aggressiveness and metastasis, thus implying it to be a prognostic marker for cancer with an attractive targeted therapeutic potential. Here, we describe the involvement of FACT in various cancers with mechanistic insights and potential targeted therapeutic implications.

Humans

A Multi-omics Exploration Revealing SLIT2 as a Prime Therapeutic Target for Peripheral Facial Paralysis: Integrating Single-Cell Transcriptomics and Plasma Proteome Data.

Peripheral facial paralysis (PFP) is a common neurological disorder characterized by facial-nerve dysfunction. Identifying therapeutic targets and understanding the molecular and cellular mechanisms underlying PFP are crucial for developing effective treatment strategies. This study combined Mendelian randomization (MR) analysis and single-cell RNA sequencing (scRNA-seq) to explore potential therapeutic candidates and their roles in PFP pathophysiology. The MR analysis included 1925 publicly available plasma protein cis-heritability instruments. Instrumental variables were selected for MR analysis to identify plasma proteins associated with PFP, followed by colocalization analysis to evaluate shared genetic variants between the identified proteins and PFP. After the initial identification of plasma proteins associated with Bell's palsy using MR analysis, a rat model of facial-nerve injury was established to further dissect underlying mechanisms at cellular and molecular levels. Using scRNA-seq technology, we delved deeply into cellular Heterogeneity and dynamic changes in gene expression in the facial-nerve nucleus tissues under both injured and control conditions, thereby achieving a systematic study ranging from macroscopic genetic associations to microscopic cellular functions. Finally, expression patterns were preliminarily validated by performing in vitro immunofluorescence analysis on the facial-nerve nucleus samples of SD rats. The MR analysis results identified 30 plasma proteins significantly associated with PFP, with nine target genes showing differential expression in the scRNA-seq data. Colocalization analysis demonstrated that slit guidance Ligand 2 (SLIT2), semaphorin 4D (SEMA4D), EGF containing fibulin extracellular matrix protein 1 (EFEMP1), and sprouty related EVH1 domain containing 2 (SPRED2) shared causal variants with PFP. SLIT2 was highly expressed in the microglia and inhibitory neurons in the experimental group, whereas SEMA4D showed elevated expression across multiple glial cell types in the same group. In contrast, EFEMP1 and SPRED2 showed distinct expression patterns in fibroblasts and oligodendrocytes. The role of SLIT2 has been previously well-documented in many central nervous system diseases. However, for the first time, this study detected SLIT2 alteration after facial-nerve injury. Altered intercellular signaling, particularly enhanced SLIT2-ROBO signaling between neurons and glial cells, was observed in the PFP group. Pseudotime analysis revealed dynamic SLIT2 expression during microglia and inhibitory neuron differentiation, mirroring changes in ROBO1 expression. Immunofluorescence analysis of rat facial-nerve nucleus samples verified that SLIT2 protein levels were significantly increased in the facial-nerve nuclei of injured samples. In conclusion, despite the fact that this study is primarily founded on animal models and despite notable differences existing between animals and humans in terms of the facial motor nucleus, this study successfully identified SLIT2 as potential therapeutic targets for PFP. The SLIT2-ROBO axis stands out as a particularly promising candidate. SLIT2 may play a role in modulating neuroimmune interactions and promoting nerve repair. These findings provide a foundation for future clinical studies and targeted interventions to enhance recovery from PFP. Future research should focus on human sample validation to enhance clinical translation.

Animals

GPR3 in neuro-metabolic-immune-reproductive nexus - a potential therapeutic target for Multi-System diseases.

BACKGROUND: GPR3(G-protein-coupled receptor 3), an orphan G-protein-coupled receptor (GPCR) with constitutive Gs activity, is expressed in the brain, liver, ovary, and other tissues, regulating cell proliferation, differentiation, and apoptosis across the nervous, reproductive, immune, and metabolic systems. This review synthesizes evidence on its integrated signaling and physiological functions to address the lack of a comprehensive multisystem pathophysiology overview. METHODS: A systematic literature search was conducted on PubMed and Web of Science, using keywords such as "GPR3", "GPCR", "neurodegeneration", "metabolism", "immune", "reproduction", "agonist", "inhibitor", and "therapeutic target". This search identified GPR3's roles in neurodegenerative diseases, immune inflammation, reproduction, and energy metabolism. The analysis focused on signaling pathways, ligand regulation, and therapeutic potential. RESULTS: The research indicates that GPR3 is involved in neuronal survival, synaptic plasticity, and microglial activity via the cAMP/PKA, PI3K/Akt, and &#x3b2; - arrestin pathways. It promotes amyloid - &#x3b2; formation in Alzheimer's disease (AD), yet provides neuroprotection in Parkinson's disease (PD) models. It may contribute to anxiety/depression - like states, maintain oocyte meiotic arrest in the ovary, and activate thermogenic genes in adipose tissue. GPR3 modulates immune responses. Using oleic acid (OA) and diphenyleneiodonium (DPI) as activators, and AF64394 and cannabidiol (CBD) as antagonists, it shows potential in disease models. CONCLUSION: GPR3 acts as a central molecular hub integrating neural, metabolic, immune, and reproductive signaling, highlighting its potential as a therapeutic target for chronic multisystem disorders. However, its dual roles in certain pathologies and translation challenges necessitate further research.

Humans

Immune landscape and novel therapeutic targets of epidermal growth factor receptor and anaplastic lymphoma kinase wild type never-smoker lung adenocarcinoma.

BACKGROUND: Never-smoker lung adenocarcinoma (NSLA) exhibits distinct immunosuppressive profiles and a lower tumor mutation burden compared with lung adenocarcinoma in smokers. These correlate with poor responses to immune checkpoint inhibitors. In this study, we aimed to elucidate the tumor-immune microenvironment of NSLA without epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) alterations and identify novel therapeutic targets. METHODS: We analyzed genome, transcriptome, and proteomic data from 102 NSLA tumor samples and 16 normal adjacent tissues. We classified tumors into distinct immune clusters (IC) based on gene signatures by profiling the tumor-infiltrating immune cells. RESULTS: The tumors were stratified into three ICs: hot, intermediate, and cold. Notably, only 21 (20.6%) patients exhibited hot IC enriched in cytotoxic T cells, natural killer cells, and B-cell signatures, which correlated with improved recurrence-free survival. Cold ICs (37.3%) exhibited higher myeloid-derived suppressor cell (MDSC) levels and M2 macrophage signatures, with poor immune cell infiltration and relatively low stimulatory cytokines and chemokines expression. CEACAM1, and NECTIN2 were upregulated in intermediate and cold ICs and correlated with MDSC and M2 macrophage infiltration. High expression of these genes was associated with poor survival outcomes. Protein-protein network analysis of 20 upregulated molecules associated with cancer- and driver-related proteins in cold IC identified XPO 1 as a key component. CONCLUSION: Our proteogenomic analysis highlighted the immunosuppressive properties of NSLA without EGFR and ALK alterations and identified novel therapeutic targets. These findings may provide novel treatment strategies that could improve the clinical outcomes of patients with NSLA.

Humans

KLHL17 as a Prognostic Indicator and Therapeutic Target in Cervical Cancer: A Comprehensive Analysis.

INTRODUCTION: This study aims to clarify the role of kelch like family member 17 (KLHL17) in cervical cancer (CESC) is unclear. OBJECTIVE: To clarify this uncertainty, our research employed bioinformatics analysis coupled with experimental corroboration. METHODS: We utilized the Cancer Genome Atlas (TCGA) database to assess the expression of KLHL17 in various cancers, specifically CESC, and to explore its association with clinical characteristics, diagnostic utility, and prognostic significance in CESC. The current investigation delved into the potential regulatory pathways related to KLHL17, examining its connection with the infiltration of immune cells, the expression of immune checkpoint genes, the status of microsatellite instability (MSI), and the efficacy of diverse therapeutic agents in CESC. The research analyzed KLHL17 expression patterns using single-cell sequencing data from CESC samples and investigated the genetic variations of KLHL17 within this context. KLHL17 expression was validated using GSE145372. The presence and levels of KLHL17 in different cell lines were validated through quantitative real-time PCR (qRT-PCR) assays. RESULTS: KLHL17 exhibited irregular expression profiles across various cancer types, including CESC. Furthermore, increased KLHL17 levels in CESC patients were significantly associated with a lower progression-free survival (PFS) rate (hazard ratio: 1.62; 95% confidence interval: 1.01-2.60, p = 0.044). Moreover, KLHL17 expression emerged as a distinct prognostic indicator for CESC patients (p = 0.031). It has been associated with various biological pathways, such as cytokine-cytokine receptor interaction, primary immunodeficiency, cell adhesion molecules (CAMs), chemokine signaling pathway, steroid hormone biosynthesis, and others. The expression levels of KLHL17 were found to correlate with the presence of immune cells, the expression of immune checkpoint genes, and the status of MSI within CESC. Furthermore, KLHL17 expression exhibited a significant and inverse correlation with XMD15-27, rTRAIL, Paclitaxel, tp4ek, and tp4ek-k6. Furthermore, KLHL17 was found to be significantly positively regulated in CESC cell lines. DISCUSSION: The findings suggest that KLHL17 is involved in the progression of CESC and may serve as a potential prognostic marker and therapeutic target. KLHL17's association with immune cell infiltration and immune checkpoint genes indicates a role in immuneevasion. Future research should focus on validating these findings through independent datasets and experimental studies to elucidate the molecular mechanisms underlying KLHL17's role in CESC progression and immune regulation. CONCLUSION: KLHL17 is a promising prognostic marker and potential therapeutic target in CESC.

Humans