Integrating network pharmacology and Mendelian randomization to explore potential targets of Fufang Banmao capsule against non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) represents a major global health burden with complex genetic etiology. While observational studies have identified numerous potential risk factors, establishing causal relationships remains challenging due to confounding and reverse causation. We conducted a comprehensive Mendelian randomization (MR) analysis to investigate causal relationships between circulating biomarkers, lung tissue gene expression levels, and NSCLC risk. The analysis employed three complementary MR methods: inverse variance weighted (IVW), MR Egger, and weighted median approaches. Genetic instruments were selected from 10 to 26 single nucleotide polymorphisms (SNPs) significantly associated with exposure variables. We validated key findings through quantitative real-time PCR (qRT-PCR) analysis in A549 and H1299 NSCLC cell lines. We examined multiple biomarkers including inflammatory mediators, immune-related proteins, and particularly focused on the HLA region within the major histocompatibility complex. Among circulating biomarkers, thymic stromal lymphopoietin demonstrated a statistically significant positive association with increased NSCLC risk (OR: 1.240, 95% CI: 1.073–1.433, p = 0.003). Gene expression analysis identified 18 genes with significant causal associations (FDR < 0.05), revealing a complex pattern of protective and risk-associated effects. qRT-PCR validation in A549 and H1299 cell lines confirmed differential expression patterns, with protective genes (HLA-DQB2, GMPPA) showing lower expression and risk-associated genes (VDR, P4HTM) showing higher expression in cancer cells compared to normal bronchial epithelial cells. Notable protective genes included HLA-DQB2 (OR: 0.917), HLA-DRB9 (OR: 0.875), and GMPPA (OR: 0.697), while risk-associated genes included VDR (OR: 1.825), P4HTM (OR: 1.520), and multiple HLA variants. Regional association analysis of the HLA-DQB2 locus revealed extremely high significance levels (p-values > 10^-135) within the MHC region on chromosome 6. This MR analysis provides robust genetic evidence for causal relationships between immune system regulation, inflammatory pathways, and NSCLC development, with experimental validation supporting the functional relevance of identified genetic associations.

Background: The increasing incidence of hyperlipidemia (HLP) is attributed to the imbalance in redox homeostasis, aberrant lipid metabolism, and the excessive intake of empty calories. Dajihan Pill (DJHP) is a Traditional Chinese Medicine (TCM) formula composed of Zingiberis Rhizoma (ZR), Piperis Longi Fructus (PLF), Alpiniae Officinarum Rhizome (AOR), and Cinnamomi Cortex (CC) in a ratio of 3:2:3:2. It exhibits a significant preventive effect on HLP. Certainly, the active components and the precise mechanism of action are not fully understood. Therefore, this study aims to elucidate the preventive and ameliorative mechanisms of DJHP against HLP by integrating network pharmacology, molecular docking, and experimental validation. Methods: Based on the pharmacological method, active ingredients in DJHP and targets were extracted from Traditional Chinese Medicine System Pharmacology (TCMSP) and UniProt. Then core compounds and targets were obtained by constructing “compounds-targets-disease” and proteinprotein interaction (PPI) network. Gene Ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were employed to elucidate further the associated action mechanism. The molecular binding mechanisms between the core ingredients and targets were elucidated through molecular docking. Additionally, the antioxidant capacities of DJHP extracts were investigated by assessing their DPPH, hydroxyl, and ABTS radical scavenging activities. Results: A total of 45 active compounds and 258 targets were identified in DJHP. Network analysis indicated that quercetin, beta-sitosterol, kaempferol, and oleic acid might serve as core bioactive compounds. Seven core targets, including AKT1, INS, and TNF, were identified as potential preventive targets. GO analysis suggested the improvement of HLP by DJHP may be related to the lipid metabolic process, high-density lipoprotein particle, triglyceride binding, and inflammatory response. The KEGG analysis indicated TNF, HIF-1, and AMPK signaling pathways were involved. The observations of active compounds binding with core targets indicated an excellent combination. Additionally, antioxidant results showed that DJHP exhibited significant DPPH, hydroxyl, and ABTS radical scavenging activities. Conclusion: Theoretical and experimental investigations indicate that DJHP can effectively modulate various signaling pathways and enhance the redox system, thus mitigating HLP. Our work provided a basis for the pharmacological study of DJHP in preventing HLP and further research.

Naotai formula (NTF) is clinically used for stroke treatment, yet its molecular mechanisms involving vascular and metabolic regulation remain unclear. This study combines network pharmacology (NP) and Mendelian randomization to explore NTF's therapeutic targets and pathways in stroke. Stroke-related genes were sourced from public databases, and NTF's active compounds were screened using SwissADME. Summary-data-based Mendelian randomization (SMR) analysis, combined with colocalization, integrated stroke genome-wide association study data with blood expression quantitative trait loci and protein quantitative trait loci datasets to identify genes/proteins causally linked to stroke risk. Protein-protein interaction (PPI) network and drug-compound-target networks were constructed using Cytoscape and R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses identified functional roles. Molecular docking assessed interactions between key compounds and prioritized targets. A total of 579 overlapping genes linked NTF and stroke. SMR identified 44 stroke-associated genes, with vascular endothelial growth factor A, angiotensinogen (AGT), and lipoprotein(a) replicated. Validation in Brain-eMeta supported eight of these targets, supporting tissue relevance. Enrichment analyses highlighted pathways including PPAR signaling, cholesterol metabolism, and vascular function. Core targets (Adiponectin, C1Q and collagen domain containing (ADIPOQ), Scavenger Receptor Class B Member 1 (SCARB1), and AGT) emerged from PPI networks. Molecular docking confirmed strong binding between NTF's Calycosin and AGT, a key renin-angiotensin system protein. NTF likely mitigates stroke by modulating genes involved in cholesterol metabolism and vascular regulation. The predicted Calycosin-AGT interaction provides a genetically informed hypothesis for a possible role in renin-angiotensin modulation. This integrative approach provides genetic and mechanistic insights into NTF's therapeutic efficacy.

Artesunate (ART), a natural compound derived from Artemisia annua, has shown promising clinical potentials in the treatment of various tumors, but the exact mechanism is unclear. Choroidal melanoma (CM) is a major malignant ocular tumor in adults, known for its significant malignancy and poor prognosis, with limited efficacy in current treatments. This study explored the anti-CM effects and mechanisms of ART using a combination of network pharmacology, molecular docking and experimental validation. Potential targets of ART were screened in PubChem, Swiss Target Prediction and Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database Analysis Platform databases, while target genes related to CM prognosis were selected from Online Mendelian Inheritance in Man (OMIM), GeneCards and DisGeNET databases. The intersection of these two groups of datasets yielded the target genes of ART involved in CM. Protein-protein interaction (PPI) network analysis of the intersecting targets, as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, were conducted to identify core targets and critical pathways. Molecular docking methods were performed to predict the binding interactions between ART and core targets. The effects of ART on CM were evaluated through CCK8, colony formation, transwell, as well as flow cytometry assays to detect apoptosis, cell cycle, reactive oxygen species (ROS). Western blot (WB) assays were conducted to investigate the impact of ART on key proteins and pathways associated with CM. Finally, in vivo assays were conducted to further validate the effects of ART on subcutaneous tumors in nude mice. Research has shown that key pathways and core targets for ART in treating CM were identified through a network pharmacology approach. Molecular docking results verified the strong binding affinity between ART and these core targets. The analysis and predicted results indicated that ART primarily exerted its effects on CM through various tumor-related pathways like apoptosis. The assays in vitro confirmed that ART significantly inhibited the proliferation and migration of CM cells. This was achieved by promoting apoptosis through activation of the p53 signaling pathway, causing cell cycle arrest at the G0/G1 phase by inhibiting the PI3K/AKT/mTOR signaling pathway and increasing the intracellular level of ROS by activating the NRF2/HO-1 signaling pathway. Additionally, the assays in vivo further validated the significant proliferation-inhibitory effect of ART on CM. This study, making the initial exploration, illustrated through network pharmacology combined with molecular docking and in vitro/in vivo assays, confirmed that ART exerted potential anti-cancer effects on CM by promoting apoptosis, inducing cell cycle arrest and increasing intracellular levels of ROS. These findings suggested that ART held significant therapeutic potential for CM.

Mechanistic Study of Clinacanthus Nutans in Treating Triple-Negative Breast Cancer Based on Network Pharmacology, Molecular Docking, and Experimental Validation

A novel Mendelian randomisation framework unravels one gene expression component, correlated with proliferation and genome stability-related features, associated with telomere length in lung adenocarcinoma tumours, which provides insights into how telomere length influences the genetic basis of lung cancer aetiology.

A novel Mendelian randomisation framework unravels one gene expression component, correlated with proliferation and genome stability-related features, associated with telomere length in lung adenocarcinoma tumours, which provides insights into how telomere length influences the genetic basis of lung cancer aetiology.

<P> Introduction: Callerya speciosa (C. speciosa), a traditional herbal medicine, is widely used in the treatment of Ankylosing Spondylitis (AS); however, its active components and therapeutic mechanisms remain unclear. </P> <P> Methods: The present work collected active compounds of C. speciosa, potential drug targets, and AS-related genes from literature and databases. Obtained Differentially Expressed Genes (DEGs) in AS through single-cell sequencing analysis, and identified intersecting targets among compounds, diseases, and DEGs. Protein-Protein Interaction (PPI) networks were constructed using STRING and Cytoscape to identify hub genes. Functional enrichment analysis (GO/KEGG) was performed via Metascape. Summary-data-based Mendelian Randomization (SMR) was applied to identify core targets with causal associations with AS. Molecular docking validated compoundtarget interactions. </P> <P> Results: Formononetin was identified as the key active compound. PPI and SMR analyses revealed TLR2, JAK2, and IL7R as core targets, whose elevated expression correlated with an increased risk of AS. GO/KEGG analysis indicated multi-target modulation of pathways, including Toll-like receptor signaling and JAK-STAT cascades. Molecular docking confirmed strong binding between Formononetin and these targets. </P> <P> Discussion: By integrating network pharmacology, SMR analysis, and single-cell sequencing studies, further insights were gained into how C. speciosa intervenes in the pathological processes associated with AS through a multi-component, multi-target, and multi-pathway collaborative action. These findings provide crucial theoretical and scientific support for the potential use of C. speciosa as a therapeutic agent for AS. </P> <P> Conclusion: This study elucidates the multi-component, multi-target mechanism of C. speciosa against AS, highlighting Formononetin's role in regulating TLR2, JAK2, and IL7R. These findings provide a scientific foundation for developing novel AS therapies based on C. speciosa.

BackgroundA lot of cancers including non-small cell lung cancer (NSCLC) arise in association with chronic inflammation. In this study, Mendelian randomization (MR) and gene function analyses were integrated to address the connection between circulating inflammatory cytokines and NSCLC, and the underlying biological processes and functional significance of the correlated inflammatory cytokines.MethodsWe employed the summary statistics of 91 inflammatory cytokines and NSCLC from the genome-wide association studies. The bidirectional MR analysis was used to identify cytokines causally associated with NSCLC. The Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were used to explore the biological pathways and functional significance of the cytokines involved in the causal relationship. By using 1400 blood metabolites data and the two-step MR with an inverse variance weighted (IVW) approach, we assessed the extent to which the effect of cytokines on the risk of NSCLC was mediated by metabolites.ResultsC–C motif chemokine ligand 11 (CCL11) (P = 0.008) and CCL2 (P = 0.026) were positively correlated with NSCLC, whereas TNF-related apoptosis inducing ligand (TRAIL) (P = 0.030) and signaling lymphocytic activation molecule family member 1 (SLAMF1) (P = 0.049) were negatively associated with NSCLC. Conversely, NSCLC led to an increase of CCL13 (P = 0.025) while stem cell factor (SCF) (P = 0.009), tumor necrosis factor beta (TNF-β) (P = 0.033), and interleukin-10 (IL-10) (P = 0.042) were downregulated in NSCLC. The KEGG analysis revealed that these eight cytokines were involved in 14 distinct pathways (all adjusted P < 0.05). The GO analysis showed enrichment of specific terms associated with these cytokines (all adjusted P < 0.05). The GSEA results indicated these eight cytokines were collectively enriched in 15 biological pathways. The top 5 pathways of the ranked list are Jak-STAT, PI3K-AKT, FAK-CDC42, RTK-PI3K and PLCG-Calcineurin signaling pathways (all P < 0.05 and false discovery rate < 0.25).The two-step MR analysis showed that 1-palmitoyl-2-linoleoyl-gpc (16:0/18:2) (PC(16:0/18:2(9Z,12Z))) (P = 3.87 × 10–5) mediates the connection between CCL2 and NSCLC, with mediated proportion of 19.4% (P = 0.039).ConclusionThe circulating inflammatory cytokines CCL11, CCL2, CCL13 and IL-10 are predominantly correlated with NSCLC, and the Jak-STAT, PI3K-AKT, FAK-CDC42, RTK-PI3K and PLCG-Calcineurin signaling pathways are closely enriched in the connection. In addition, alteration in lipid metabolism, especially phosphatidylcholine (PC) metabolism is independently linked with the risk of NSCLC induced by inflammatory cytokines.

This study aims to explore the causal relationships and mechanisms between NSCLC-related genes, metabolites, and NSCLC using Mendelian Randomization (MR). The study employed differential gene expression analysis, two-sample MR analysis, and mediation analysis, utilizing NSCLC Genome-Wide Association Study (GWAS) data from the Finngen database, gene data from the eQTLGen and pQTL databases, and NSCLC expression data from the Gene Expression Omnibus (GEO) database. First, two-sample MR analysis was performed to evaluate the causal relationships between expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) genes and NSCLC. Violin plots were then used to validate the expression levels of these genes in NSCLC. Finally, mediation analysis was conducted to explore the mediating role of metabolites in the relationship between gene expression and NSCLC development. Our study found a significant positive association between high expression of the CXCL10 gene and increased NSCLC risk. Further mediation analysis revealed that CXCL10 promotes NSCLC development by regulating the PUR. Specifically, the mediation effect was 0.039, with a mediation proportion of 25.4% and a P-value of 0.012. This study provides new insights into the molecular mechanisms of CXCL10 in NSCLC and suggests its potential as a biomarker for future targeted therapeutic strategies.

Strychni Semen, characterized by its bitter taste and warm properties, has been confirmed to possess anti-tumor properties. However, the molecular mechanism of Strychni Semen in treating non-small cell lung cancer (NSCLC) needs further study. This study aimed to explore the molecular mechanism of Strychni Semen in treating NSCLC based on network pharmacology and molecular docking. The active components and targets of Strychni Semen were retrieved from the TCMSP, supplemented by the HERB database and the related literature. NSCLC-related targets were retrieved from the GeneCards, OMIM and DisGenet databases. The intersection targets of Strychni Semen in treating NSCLC were obtained via an online platform. The Protein-Protein Interaction (PPI) network was subsequently constructed to deeply analyse the interrelationship of the intersection targets via the String database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were carried out via the Metascape database. The interactive networks between Strychni Semen and NSCLC were constructed via Cytoscape 3.9.1. Molecular docking detected interactions between the key components and the core targets. The core targets were validated via GEO datasets. 21 active components and 67 targets were identified, with 47 associated with NSCLC. The key active components were Stigmasterol, IcarideA, 2-Hydroxymethylanthraquinone, (+)-catechin, (2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one, (S)-Stylopine, Brucine and Isobrucine. The core targets were PTGS2, NR3C1, ESR1, CASP3 and PRKACA. Molecular docking revealed that these compounds undergo strong binding affinity with the core genes. GEO database indicated that PTGS2 was the most promising core target. In addition, Strychni Semen’s effects on NSCLC involved mainly the Calcium pathway, the Estrogen pathway, and the cGMP-PKG and cAMP pathways. This study visually demonstrated the mechanism of the therapeutic effect of Strychni Semen in NSCLC through multiple components, targets and pathways which provides a basis for clinical treatment and further experimental research.

BACKGROUND: Matrine has been reported inhibitory effects on ovarian cancer (OC) cell progression, development, and apoptosis. However, the molecular targets of matrine against OC and the underlying mechanisms of action remain elusive.OBJECTIVE: This study endeavors to unveil the potential targets of matrine against OC and to explore the intricate relationships between these targets and the pathogenesis of OC.METHODS: The effects of matrine on the OC cells (A2780 and AKOV3) viability, apoptosis, migration, and invasion was investigated through CCK-8, flow cytometry, wound healing, and Transwell analyses, respectively. Next, Matrine-related targets, OC-related genes, and ribonucleic acid (RNA) sequence data were harnessed from publicly available databases. Differentially expressed analyses, protein-protein interaction (PPI) network, and Venn diagram were involved to unravel the core targets of matrine against OC. Leveraging the GEPIA database, we further validated the expression levels of these core targets between OC cases and controls. Mendelian randomization (MR) study was implemented to delve into potential causal associations between core targets and OC. The AutoDock software was used for molecular docking, and its results were further validated using RT-qPCR in OC cell lines.RESULTS: Matrine reduced the cell viability, migration, invasion and increased the cell apoptosis of A2780 and AKOV3 cells ( 0.01). A PPI network with 578 interactions among 105 candidate targets was developed. Finally, six core targets (TP53, CCND1, STAT3, LI1B, VEGFA, and CCL2) were derived, among which five core targets (TP53, CCND1, LI1B, VEGFA, and CCL2) differential expressed in OC and control samples were further picked for MR analysis. The results revealed that CCND1 and TP53 were risk factors for OC. Molecular docking analysis demonstrated that matrine had good potential to bind to TP53, CCND1, and IL1B. Moreover, matrine reduced the expression of CCND1 and IL1B while elevating P53 expression in OC cell lines.CONCLUSIONS: We identified six matrine-related targets against OC, offering novel insights into the molecular mechanisms underlying the therapeutic effects of matrine against OC. These findings provide valuable guidance for developing more efficient and targeted therapeutic approaches for treating OC.

BackgroundCalorie preference refers to an individual's systematic inclination toward selecting foods based on their caloric density. The causal impact of dietary calorie preference on cancer development remains uncertain.MethodsIn this study, data on dietary calorie preference were sourced from a large-scale genome-wide association study (GWAS) database of food liking, while information on 18 cancer types was obtained from Finger R9 database. Two-sample Mendelian randomization (MR) analysis was conducted to assess the causal effects of Calorie Dietary Liking on 18 types of cancers. The inverse variance weighting (IVW) method was the primary analytical approach, with significant correlations further examined using Egger regression, MR-PRESSO, and weighted median methods.ResultsOur analyses revealed that a genetically predicted preference for high-calorie diets significantly raised the risk of non-Hodgkin lymphoma (NHL) (OR = 1.75, 95% CI 1.175 to 2.598), non-small cell lung cancer (NSCLC) (OR = 1.39, 95% CI 1.147 to 1.693), hepatocellular carcinoma (HCC) (OR = 2.06, 95% CI 1.097 to 3.866), and gastric cancer (GC) (OR = 1.47, 95% CI 1.087 to 1.991). Further subgroup analyses confirmed that high-calorie foods liking, particularly cheese liking, were strongly linked to an elevated HCC risk (OR = 2.43, 95% CI 1.509 to 3.899), while deep-fried food liking were associated with increased NSCLC risk (OR = 1.26, 95% CI 1.073 to 1.490). Low-calorie dietary liking showed causal association with the risk of prostate cancer (PCa) (OR = 0.85, 95% CI 0.745 to 0.965).ConclusionThis comprehensive MR analysis suggested that genetically predicted high-calorie food liking, as well as its subgroups, may be a risk factor in the development of NHL, NSCLC, HCC, and GC. A low-calorie diet may have a protective effect on the risk of PCa.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12672-025-03213-8.

Lung cancer is a major public health burden and among the highest incidence and mortality rates of the cancers. MicroRNAs (miRNAs) play an important role in the development of lung cancer. The aim of this study was to investigate whether there was a potential causal relation between miRNAs and non-small-cell lung cancer (NSCLC). 1,026 patients with NSCLC from The Cancer Genome Atlas (TCGA) were analyzed. NSCLC associated SNPs' allele scores were established, and candidate miRNAs were filtered from differential expression analysis. Mendelian randomization (MR) analysis was conducted for 5 candidate miRNA (hsa-miR-135b, hsa-miR-142, hsa-miR-182, hsa-miR-183 and hsa-miR-3607) and 76 candidate SNPs in lung adenocarcinoma (LUAD) group. According to the core assumptions of MR, there was no clear evidence of a causal relation between the 5 candidate miRNAs and LUAD. The reads per million miRNAs mapped (RPM) level of candidate miRNAs changed less than 3% per allele score. To our knowledge, this is the first study using the TCGA data set to investigate the causal relation between miRNAs and lung cancer using the MR approach, and also one of the first MR studies to use miRNA expression as an exposure factor, with the SNPs as instrumental variables.

Exploring novel drug targets for erectile dysfunction through plasma proteome with genome.