Yi Chuan. 2026 Sep;48(9):931-945. doi: 10.16288/j.yczz.25-275.

ABSTRACT

The abundance of omics data has significantly advanced the development of multi-omics data integration techniques. Non-linear embedding approaches for data integration have gradually become the mainstream in multi-omics research, as these approaches can substantially improve cancer analysis by enhancing the quality of the embeddings. However, current multi-omics data integration methods are typically confined to omics measurements, neglecting domain-specific prior knowledge encompassing biological pathways. In this study, we proposed a multi-omics integrated classification model, PathTransGCN, based on pathway self-attention and graph convolutional networks (GCN). The model integrated biological pathway information into multi-omics data analysis with the aim of enhancing the accuracy of cancer classification. Multi-omics data for breast cancer (BRCA), non-small cell lung cancer (NSCLC), and low-grade glioma (LGG) were obtained from The Cancer Genome Atlas (TCGA) and UCSC Xena databases. These data included gene mutations, DNA methylation, copy number variations, and gene expression, and were used to assess the model's generalizability across different cancers. First, PathTransGCN employed a pathway self-attention module to learn latent representations of samples across different pathways, thereby obtaining multi-omics integration vectors. Concurrently, a patient similarity network (PSN) was constructed using the similarity network fusion (SNF) approach. Second, the integrated vectors and the PSN were jointly fed into a GCN for end-to-end training, enabling precise classification of cancer subtypes. Through multi-omics data analysis of the BRCA dataset, PathTransGCN outperformed several popular algorithms (such as MoGCN and DeePathNet) in the five-class classification of cancer subtypes, achieving an accuracy rate of 87.6% and an F1 score of 86.4%. Moreover, the model demonstrated robust generalization capabilities across both NSCLC and LGG datasets, while effectively identifying key disease-associated biomarkers at the pathway level. Experimental results demonstrate that PathTransGCN exhibits outstanding performance in integrating omics data and delivering interpretable classification outcomes, presenting significant potential for clinical applications.

PMID:42751828 | DOI:10.16288/j.yczz.25-275

Front Immunol. 2026 Sep 2;17:1902053. doi: 10.3389/fimmu.2026.1902053. eCollection 2026.

ABSTRACT

Childhood asthma is a highly heterogeneous chronic respiratory disease, and its onset and progression are intricately linked to genetic susceptibility, environmental exposure, immune development, and the establishment of the early-life microbiome. In recent years, studies on the gut and respiratory microbiomes have suggested that the composition, metabolic functions, and interactions of microbial communities with the host immune system may be involved in the formation of asthma susceptibility, shaping of inflammatory phenotypes, and disease progression in children. The gut-lung axis, as an important pathway connecting gut microbiome, respiratory immunity, and systemic inflammatory responses, provides a new perspective for understanding the early mechanisms of childhood asthma. This article reviews the characteristics of the respiratory and gut microbiomes associated with childhood asthma, with a focus on the roles of the gut-lung axis, microbial metabolites, mucosal immune regulation, and environmental exposure. It also evaluates the research progress of probiotics, prebiotics, nutritional interventions, and novel microecological therapies. Additionally, the potential of microbial maturity, microbial metabolites, and immunophenotypes as biomarkers for risk prediction, phenotype stratification, and treatment response is analyzed. Furthermore, the role of multi-omics integration in supporting the identification of responsive populations, matching of intervention strategies, and dynamic monitoring of efficacy is discussed. Current evidence suggests that the microbiome offers promising targets for risk assessment and precision prevention of childhood asthma. However, relevant research still faces challenges such as ambiguous causality, high cohort heterogeneity, limited reproducibility of candidate biomarkers, inconsistent intervention outcomes, and insufficient evidence of long-term safety. At present, most biomarkers and multi-omics models remain in the stage of association discovery, lacking unified thresholds, cross-cohort validation, and biomarker-guided randomized controlled trials in children. Therefore, they cannot be routinely used for patient stratification or intervention selection. Future efforts should rely on standardized longitudinal birth cohorts, multi-omics integration, external validation, and high-quality clinical trials to clarify the incremental value of microbiome biomarkers over traditional clinical indicators and their clinical utility in the individualized management of childhood asthma.

PMID:42751182 | PMC:PMC13580037 | DOI:10.3389/fimmu.2026.1902053

Phenomics. 2026 May 20;6(3):213-229. doi: 10.1007/s43657-026-00322-4. eCollection 2026 Jun.

ABSTRACT

Early cancer detection remains challenging due to the lack of reliable pan-cancer screening methods, particularly blood-based biomarkers. Using a novel three-tiered validation framework combining artificial intelligence (AI)-powered literature mining of 180,000 PubMed articles (1950-2024), multiomics integration across major databases, and extensive clinical validation, we identified macrophage migration inhibitory factor (MIF) as a promising blood-based biomarker for pan-cancer detection. Multiomics analysis revealed consistent MIF upregulation across 21 cancer types at the transcriptional level and across 12 cancer types at the protein level. Clinical validation in independent cohorts (n = 4,269) showed that serum MIF protein levels discriminated effectively between cancer patients and healthy controls (median AUC = 0.994) and between cancer and benign conditions (median AUC = 0.881). Notably, comparative analyses showed that MIF demonstrated superior or comparable performance to established cancer-specific markers, including AFP for hepatocellular carcinoma (MIF AUC = 0.885 vs. AFP AUC: 0.744-0.887) and CA125 for ovarian cancer (MIF AUC = 0.831 vs. CA125 AUC: 0.58-0.71). Meta-analysis of 28 cohorts (n = 5,347) confirmed the diagnostic efficacy of MIF (pooled AUC: 0.782). This cost-effective, blood-based ELISA approach establishes MIF as a valuable tool for broad applications in cancer screening.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s43657-026-00322-4.

PMID:42750739 | PMC:PMC13578188 | DOI:10.1007/s43657-026-00322-4

Mater Today Bio. 2026 Aug 18;40:103583. doi: 10.1016/j.mtbio.2026.103583. eCollection 2026 Oct.

ABSTRACT

TLR4 activation and the cascade of neutrophil extracellular trap (NET) formation exacerbate excessive inflammation and organ damage in the pathogenesis of acute lung injury (ALI), yet effective pharmacological interventions remain unavailable. Nanoaggregates derived from natural products offer promising avenue by leveraging synergistic anti-inflammatory effects. In this study, we surprisingly discovered that leonurine and ursolic acid spontaneously self-assemble into nanoparticles (LUNP) through non-covalent interactions, achieving a drug loading capacity of 100%. The LUNP platform exhibits superior biophysical properties, including enhanced mucus penetration, pH-responsive drug release, improved cellular uptake, and prolonged retention within inflamed lung tissue. Mechanistically, LUNP ameliorates ALI by dampening TLR4/MyD88/NF-κB-driven inflammatory activation, thereby remodeling the microenvironment to limit NOX4-PAD4-mediated NET formation. Notably, inhalational LUNP exhibits outstanding biosafety with minimal off-target distribution. Overall, this work introduces a synergistic self-assembled nanoplatform for precise pulmonary intervention in ALI, showcasing its ability to safely and effectively orchestrate the coordinated modulation of multiple pathological pathways. In summary, by inhibiting both TLR4 activation and NET formation, the synergistic LUNP platform offers an efficient, safe, and easily accessible therapeutic strategy for ALI, providing a promising solution for clinical translation.

PMID:42750707 | PMC:PMC13577835 | DOI:10.1016/j.mtbio.2026.103583

J Thorac Oncol. 2026 Sep 16:104204. doi: 10.1016/j.jtho.2026.104204. Online ahead of print.

ABSTRACT

BACKGROUND: Early-stage EGFR-mutant lung adenocarcinoma (LUAD) demonstrates heterogeneous outcomes after curative surgery, yet adjuvant treatment decisions are guided by pathological stage alone. Following the ADAURA trial, adjuvant osimertinib is the standard of care for resected stage IB-IIIA EGFR-mutant LUAD; however, real-world data demonstrate that up to 40% of patients remain disease-free at five years without adjuvant osimertinib, underscoring the need for improved risk stratification.

PATIENTS AND METHODS: We performed integrated clinical, genomic and transcriptomic profiling of 400 patients with resected stage IA-IIIA EGFR-mutant LUAD. EGFR-mutant recurrence risk models integrating clinical, genomic and transcriptomic data were developed and validated across one internal and three external cohorts.

RESULTS: Genomic instability, including TP53 co-mutations, copy number alterations and APOBEC-associated mutational signatures, increased with pathological stage. RBM10 co-mutations were enriched in tumours with L858R mutations and correlated with upregulation of WNT signalling and epithelial-mesenchymal transition. Transcriptomic features outperformed clinical or genomic variables alone in predicting recurrence risk, and a multi-omic model demonstrated superior and reproducible performance, achieving a median concordance index of 75.4% across four independent validation cohorts. The multi-omic model stratified recurrence risk within individual pathological stages, including stage I disease, and identified patients most likely to benefit from adjuvant EGFR TKI.

CONCLUSIONS: These findings define the molecular heterogeneity of early-stage EGFR-mutant LUAD and support multi-omic risk stratification to inform adjuvant EGFR TKI decisions beyond pathological stage. Prospective validation in larger cohorts will be required to confirm these findings.

PMID:42749051 | DOI:10.1016/j.jtho.2026.104204

Eur J Immunol. 2026 Sep;56(9):e70283. doi: 10.1002/eji.70283.

ABSTRACT

T cell-based immunotherapies have achieved remarkable success in hematological malignancies but remain limited in solid tumors. Natural killer (NK) cells offer a compelling complementary approach, given their ability to recognize and kill tumor cells independently of neoantigen presentation and MHC class I expression. This study integrates multiomic analyses, clinical trial data, and transcriptomic analyses to systematically identify solid tumor indications most likely to benefit from NK cell-based therapies. Immunohistochemical analysis revealed that NK cells infiltrate multiple tumor types, with the highest abundance in kidney tumors. Systematic review of 177 clinical trials identified variable efficacy across solid tumor indications, without a clearly superior tumor type or intervention. Transcriptomic profiling of over 10,000 TCGA samples assessed NK cell infiltration, cytotoxic fitness, and tumor microenvironment composition, highlighting kidney renal cell carcinoma, lung adenocarcinoma and squamous cell carcinoma, cervical and endocervical cancers, and mesothelioma as promising candidates for future clinical evaluation. Together, these findings provide a multimodal framework to prioritize tumor indications and improve the rational design of future NK cell clinical trials.

PMID:42745669 | PMC:PMC13579203 | DOI:10.1002/eji.70283

Nat Genet. 2026 Sep 15. doi: 10.1038/s41588-026-02751-3. Online ahead of print.

ABSTRACT

Inflammation accelerates evolutionary dynamics of hematopoietic stem cells (HSCs) in clonal hematopoiesis and myeloid neoplasms. We studied HSCs, progenitors and immune cells from patients with myeloproliferative neoplasms at baseline and following interferon-α (IFNα) treatment, the only therapy to deplete mutated stem cells. We deployed single-cell multiomics methods that distinguish the IFNα effects on mutated stem cells from the admixed wild-type HSCs, with respect to their differentiation, transcriptomes, immunophenotypes and chromatin accessibility. IFNα simultaneously activated HSCs into two polarized states: a lymphoid progenitor expansion associated with an anti-inflammatory state and an inflammatory myeloid progenitor state derived from HSCs. The augmented lymphoid differentiation balanced the typical myeloproliferative-neoplasm-induced myeloid bias, associated with normalized blood counts. Somatic mutations modified the effects of IFNα on HSC differentiation and cell cycle entry rates. Clonal fitness upon IFNα exposure was due to resistance of CALR- or JAK2-mutated stem cells to differentiate into inflammatory myeloid progenitors.

PMID:42745000 | DOI:10.1038/s41588-026-02751-3

Biochim Biophys Acta Rev Cancer. 2026 Sep 15:189717. doi: 10.1016/j.bbcan.2026.189717. Online ahead of print.

ABSTRACT

Breast cancer deaths are mainly caused by metastasis to distant organs, not by the primary tumor. Bone, lung, liver, and brain are the most common metastatic sites, each showing different clinical behaviors and treatment responses-a pattern often called metastatic organotropism. Bulk omics can provide tissue-level information, but they fall short in identifying rare metastasis-initiating clones or capturing how tumor cells adapt to distinct organ microenvironments. With recent progress in single-cell sequencing, multi-omics integration, and spatial profiling, it is now possible to study metastasis at much finer cellular and spatial resolution. In this review, we synthesize current evidence from two complementary perspectives. First, we summarize pan-organ programs associated with metastatic competence, including partial epithelial-mesenchymal transition, lineage plasticity, stem-like states, stress tolerance, metabolic flexibility, immune evasion, and stromal-vascular remodeling. Second, we discuss how these programs are reshaped by organ-specific microenvironments: osteolytic and mixed bone remodeling and marrow dormancy in bone, inflammatory vascular niches in lung, tolerogenic antigen presentation and hepatic metabolism in liver, and blood-brain/blood-tumor barrier constraints, glial crosstalk, neuronal interactions, and lipid-metabolic adaptation in brain. We also highlight how CTC/CTM profiling, spatial mapping, and longitudinal integration refine the understanding of dissemination, dormancy, colonization, outgrowth, and treatment resistance. Although these approaches hold translational promise, most remain at the discovery or early validation stage and require assay simplification, prospective testing, and cross-center standardization. Overall, single-cell and spatial multi-omics are reframing breast cancer metastasis as a dynamic, multi-stage, and tissue-shaped process, providing a foundation for future biomarker development and mechanism-guided therapeutic strategies.

PMID:42744123 | DOI:10.1016/j.bbcan.2026.189717

Respir Investig. 2026 Sep 15;64(6):101515. doi: 10.1016/j.resinv.2026.101515. Online ahead of print.

ABSTRACT

The lung microbiome is increasingly recognized as an important factor in idiopathic pulmonary fibrosis (IPF) and hypersensitivity pneumonitis (HP), two interstitial lung diseases with overlapping clinical features but distinct underlying mechanisms and management. This systematic review, conducted in accordance with PRISMA guidelines, evaluated the current evidence regarding lung microbiome alterations in IPF and HP. A literature search was performed using PubMed as the primary database and supplemented by Google Scholar searches. The review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD420261415180). Fourteen unique studies met the inclusion criteria, comprising 13 studies involving IPF and 2 studies involving HP, with one study overlapping between the two disease groups. Current evidence suggests that IPF is associated with increased bacterial burden, reduced microbial diversity, and enrichment of specific taxa, including Streptococcus and Staphylococcus, which have been linked to immune activation and fibrotic progression. In contrast, limited available evidence suggests that HP may exhibit a lower bacterial burden, with microbial patterns influenced predominantly by environmental exposures, including bacterial and fungal antigens from occupational and domestic sources. Emerging studies highlight host-microbiome and environment-microbiome interactions in disease progression. Overall, the current evidence supports a role for microbial dysbiosis in IPF, whereas microbiome alterations in HP appear to be more closely associated with environmental microbial exposures. However, conclusions regarding HP should be interpreted cautiously due to the limited number of studies. Further longitudinal and multi-omics studies are needed to clarify causality and identify robust microbial biomarkers for diagnosis and therapy.

PMID:42743786 | DOI:10.1016/j.resinv.2026.101515

Discov Oncol. 2026 Aug 1;17(1):1333. doi: 10.1007/s12672-026-05700-y.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) remains biologically heterogeneous, and molecular states linking tumor-cell intrinsic programs with post-translational regulation, immune contexture and drug-specific vulnerability remain incompletely defined. ZDHHC16 is a DHHC-family palmitoyl acyltransferase, but its clinical relevance and biological context in HCC remain unclear.

METHODS: Public transcriptomic, clinical, single-cell, proteomic, palmitoylome, immune-related and pharmacogenomic datasets were integrated to characterize ZDHHC16 in HCC. ZDHHC16 expression, exploratory survival separation, cellular localization, pathway activity, palmitoylation-associated candidates, immune microenvironment features and predicted drug response were evaluated. siRNA-mediated knockdown, MTT assays and colony formation assays were performed in HepG2 and Huh7 cells.

RESULTS: ZDHHC16 was upregulated in HCC. In exploratory Kaplan-Meier analyses restricted to primary tumors and using endpoint-specific data-derived cutoffs, the curves showed expression-group separation for overall survival, disease-free interval and progression-free interval (unadjusted log-rank P = 0.019, 0.019 and 0.011, respectively). These analyses were not adjusted for clinical covariates and do not establish independent prognostic value. Single-cell analysis localized ZDHHC16 mainly to malignant epithelial-related compartments. ZDHHC16 knockdown reduced MTT-based cell viability and clonogenic growth in HepG2 and Huh7 cells. ZDHHC16-high tumors were enriched for cell-cycle progression, DNA replication, DNA repair, RNA processing, ubiquitin-mediated proteolysis and proteasome-related programs. After deduplication at the gene-symbol level, palmitoylome-guided integration nominated 28 transcriptionally correlated palmitoylation-associated candidates, including EZH2, PI4K2A and ZDHHC6; the screen did not establish direct ZDHHC16 substrates. ZDHHC16-high tumors also showed immune-remodeled features and drug-specific predicted IC50 patterns.

CONCLUSIONS: Integrated data support ZDHHC16 as a marker of a malignant epithelial, growth-associated HCC state accompanied by palmitoylation- and proteostasis-related programs, altered immune contexture and drug-specific predicted IC50 patterns. Direct ZDHHC16-dependent palmitoylation, independent prognostic value and therapeutic utility require biochemical and prospective clinical validation.

PMID:42742876 | PMC:PMC13578202 | DOI:10.1007/s12672-026-05700-y

Front Oncol. 2026 Aug 31;16:1956981. doi: 10.3389/fonc.2026.1956981. eCollection 2026.

ABSTRACT

INTRODUCTION: Maternal Embryonic Leucine Zipper Kinase (MELK) is a key regulator of the G2/M checkpoint and a recognized pan-cancer oncogene; however, its regulatory mechanisms and clinical significance in lung adenocarcinoma (LUAD) remain incompletely understood. This study aimed to investigate the molecular, prognostic, immune, and therapeutic relevance of MELK in LUAD.

METHODS: An integrated multi-omics approach was employed, incorporating gene-expression, survival, transcriptomic, immune-infiltration, regulatory-network, molecular docking, and molecular dynamics analyses. The potential MELK-associated ceRNA regulatory axis was investigated using bioinformatic approaches and subsequently evaluated by qRT-PCR in lung cancer cell lines. The therapeutic potential of candidate MELK-binding compounds was further explored using molecular docking and molecular dynamics simulations.

RESULTS: MELK was markedly overexpressed in LUAD (*log₂FC = 4.19) and was significantly associated with poor overall survival (HR = 1.63), with stronger prognostic associations in patients with stage I disease (HR = 2.07) and female smokers (HR = 1.50). MELK exhibited a strong positive correlation with FOXM1 (R = 0.834), supporting its coordinated involvement in the G2/M regulatory program. High MELK expression was associated with reduced effector immune-cell infiltration and increased enrichment of exhausted CD8⁺ T cells and regulatory T cells. Integrated regulatory analyses identified a putative **TMPO-AS1/hsa-let-7b-5p/MELK/FOXM1* ceRNA network characterized by increased TMPO-AS1 and MELK expression and reduced hsa-let-7b-5p expression. These expression patterns were further supported by qRT-PCR analysis in lung cancer cell lines. Molecular docking and molecular dynamics simulations identified *hesperidin* as a candidate MELK-binding compound with favorable predicted binding affinity and stable complex behavior.

CONCLUSION: These findings provide an integrated view of MELK dysregulation in LUAD, linking its G2/M-associated activity with post-transcriptional regulation, immune features, and potential therapeutic targeting. The *TMPO-AS1/hsa-let-7b-5p/MELK/FOXM1* axis may represent a promising molecular framework for understanding MELK-mediated LUAD progression and identifying prognostic biomarkers and therapeutic opportunities.

PMID:42741133 | PMC:PMC13572222 | DOI:10.3389/fonc.2026.1956981

Diagnostics (Basel). 2026 Aug 22;16(17):2686. doi: 10.3390/diagnostics16172686.

ABSTRACT

Microvascular invasion (MVI) is a critical prognostic indicator for recurrence and survival in hepatocellular carcinoma (HCC); however, its accurate preoperative assessment remains clinically challenging. Postoperative histopathology is subject to sampling bias and time delays, while traditional imaging techniques lack the molecular specificity required to predict MVI. Liquid biopsy, through the analysis of circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), circulating tumor RNA (ctRNA), and extracellular vesicles (EVs), provides a minimally invasive approach for capturing tumor-derived molecular and cellular signals associated with vascular invasion. This narrative review comprehensively summarizes the current evidence linking these four liquid biopsy analyte categories to MVI in HCC, evaluates their integration into multi-omics predictive models, including multi-marker, clinicopathological-integrated, and imaging-integrated strategies, and proposes an evidence-level framework that categorizes blood biomarkers according to the strength of their support for MVI prediction, distinguishing direct histopathological validation from indirect associations with aggressive tumor biology. Key challenges are critically examined, including the variable specificity of individual biomarkers for MVI, the lack of head-to-head comparative studies, the absence of standardized pre-analytical and analytical protocols, and the methodological limitations of current prediction models. As a narrative review, this work does not employ systematic review methodology, and the evidence synthesis should be interpreted accordingly. The review provides a framework for understanding how liquid biopsy-based MVI risk stratification may inform surgical and perioperative decision-making following prospective validation.

PMID:42739118 | PMC:PMC13564874 | DOI:10.3390/diagnostics16172686

Cells. 2026 Aug 28;15(17):1564. doi: 10.3390/cells15171564.

ABSTRACT

KRAS G12C mutation is a clinically relevant driver in non-small cell lung cancer (NSCLC), yet the signaling networks that modulate malignant behavior in this context remain incompletely defined. In this study, we examined the functional role of FOXD3 and its relationship with NF-κB signaling in KRAS G12C-mutant NSCLC models. Stable FOXD3 overexpression was established in SW1573 and LU65 cells. FOXD3 reduced cell viability, migration, and invasion while increasing caspase 3/7 activity in both cell lines. Transcriptomic profiling in LU65 cells followed by Hallmark enrichment analysis identified TNFα signaling via NF-κB as a prominently altered pathway associated with FOXD3 overexpression. Consistently, NF-κB dual-luciferase assays showed reduced basal NF-κB transcriptional activity in FOXD3-overexpressing cells. TNFα stimulation partially reversed the inhibitory effects of FOXD3 on proliferation, migration, and invasion and attenuated FOXD3-induced apoptosis. In addition, stable FOXD3 overexpression suppressed xenograft growth in vivo. Collectively, these findings support a functional association between FOXD3 overexpression and reduced NF-κB-related transcriptional activity in KRAS G12C-mutant NSCLC models, although the present data do not establish direct causal mediation by NF-κB.

PMID:42738858 | PMC:PMC13564895 | DOI:10.3390/cells15171564

Cancers (Basel). 2026 Sep 3;18(17):2844. doi: 10.3390/cancers18172844.

ABSTRACT

Background: Pleural effusion is a common clinical presentation in both benign and malignant conditions. The advent of liquid biopsy allowed new possibilities for non-invasive molecular profiling using body fluids. Pleural fluid, by virtue of its proximity to thoracic malignancies and its rich tumour-derived content, represents a particularly compelling matrix for liquid biopsy analysis. This review synthesises current evidence regarding the diagnostic, predictive, and prognostic utility of pleural liquid biopsy in clinical medicine. Methods: A narrative review was conducted using PubMed, MEDLINE, and EMBASE databases. Search terms included combinations of "pleural effusion", "liquid biopsy", "circulating tumour DNA", "circulating tumour cells", "exosomes", "next-generation sequencing", and "biomarkers". Priority was given to original research articles, systematic reviews, and meta-analyses published between 2013 and 2026. Results: Pleural fluid contains a diverse repertoire of tumour-derived analytes, including cell-free and circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), exosomes, and soluble proteins. These biomarkers enable molecular characterisation of underlying malignancies with sensitivity that often exceeds that of plasma-based liquid biopsy and complements histological tissue biopsy. Detection of actionable mutations, including EGFR, ALK, KRAS, and BRAF alterations, directly informs targeted therapy selection. Furthermore, serial sampling facilitates real-time monitoring of therapeutic resistance, disease progression, and clonal evolution. Conclusions: Pleural liquid biopsy offers a minimally invasive, reproducible, and clinically informative approach to molecular profiling in patients with pleural disease, particularly those with thoracic malignancies. Despite existing challenges in standardisation and analytical sensitivity, its integration into routine clinical pathways holds significant promise for advancing personalised oncological care. Multi-omics integration and artificial intelligence may further consolidate its role in therapeutic decision-making.

PMID:42738365 | PMC:PMC13565450 | DOI:10.3390/cancers18172844

Biology (Basel). 2026 Sep 4;15(17):1549. doi: 10.3390/biology15171549.

ABSTRACT

OBJECTIVE: This study established a rat model of lipopolysaccharide (LPS)-induced acute lung injury (ALI) to evaluate pathological damage, collagen deposition, inflammatory cytokine levels, and key gene/protein expression following Hedyotis diffusa water extract (HDWE) intervention. Combined with ultra-high-performance liquid chromatography-quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS), transcriptomic analysis, and molecular simulation, this study identified the bioactive components of HDWE, evaluated their potential interactions with ALI-related targets, and explored the multi-omics-based protective mechanisms of HDWE.

METHODS: Thirty-six Sprague-Dawley (SD) rats were randomly divided into six groups: Control group, ALI group, DXMS group, HDWE-L group (100 mg/kg), HDWE-M group (200 mg/kg), and HDWE-H group (300 mg/kg). Hematoxylin and eosin (H&E) and Masson's trichrome staining were used to evaluate lung pathological changes and collagen deposition. Enzyme-linked immunosorbent assay (ELISA) was used to measure serum tumor necrosis factor-α TNF-α interleukin-1β IL-1β, erleukin-6 (IL-6), and interleukin-10 (IL-10) levels. Transcriptomic analysis identified differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), receiver operating characteristic (ROC), and immune infiltration analyses. Quantitative real-time polymerase chain reaction (qRT-PCR) detected the mRNA expression levels of SPHK1, RELA, and NFKBIA. Immunohistochemistry evaluated the expression of eight hub targets, including endothelin-1 (EDN1), sphingosine kinase 1 (SPHK1), intercellular adhesion molecule 1 (ICAM1), interleukin-17 (IL-17), prostaglandin-endoperoxide synthase 2 (PTGS2/COX-2), NF-κB p65 (encoded by RELA), WT1-associated protein (WTAP), and myeloperoxidase (MPO). UHPLC-Q-Orbitrap HRMS characterized HDWE constituents. Molecular docking analysis was performed between 22 compounds and eight hub targets, followed by 100 ns molecular dynamics simulations and molecular mechanics-Poisson-Boltzmann surface area (MM/PBSA) binding free energy calculations for five core targets. Compared with the control group, the ALI group showed increased levels of TNF-α (86%), IL-1β (107%), and IL-6 (66%), accompanied by a 43% reduction in IL-10 and a 300% increase in lung collagen deposition. All HDWE doses alleviated inflammatory responses, with medium-dose HDWE showing the most pronounced effects. Specifically, medium-dose HDWE increased IL-10 levels by 52% and reduced IL-6, TNF-α, and IL-1β levels by 18%, 22%, and 11%, respectively. Transcriptomic analysis identified 2512 DEGs between the control group and ALI groups, 832 exclusive DEGs between the ALI group and HDWE-M groups, and 876 overlapping DEGs enriched in TNF, IL-17, and NF-κB signaling pathways. The eight-hub-gene diagnostic model achieved an area under the curve (AUC) of 0.969. RELA, SPHK1, and four other hub genes showed positive correlations with Th1, Th17, and neutrophil infiltration. In the ALI group, SPHK1, RELA, and NFKBIA mRNA expression levels were 1.30-, 0.96-, and 0.71-fold of those in the control group, respectively. Compared with the ALI group, high-dose HDWE treatment and low-dose HDWE treatment reduced SPHK1 expression to 0.62- and 0.57-fold, respectively, and increased NFKBIA expression to 1.68- and 1.58-fold, respectively. High-dose HDWE treatment reduced RELA expression to 0.43-fold. The expression levels of inflammation-related proteins were increased in the ALI group and were reduced after HDWE treatment. Twenty-two HDWE components were identified, 16 of which met the docking criteria. Asperulosidic acid exhibited favorable predicted binding affinities with all eight targets, with calculated binding free energies of -14.74, -14.92, -17.58, -23.04, and -16.10 kcal/mol for MPO, IL-17, NF-κB p65, PTGS2/COX-2, and SPHK1, respectively.

CONCLUSIONS: This study provides systematic in vivo pharmacodynamic and in silico component-target evidence regarding the protective effects of HDWE against LPS-induced ALI. HDWE treatment increased NFKBIA expression and reduced SPHK1, RELA, and multiple inflammatory protein levels, suggesting that HDWE may regulate the IL-17/NF-κB-associated inflammatory network, although direct causal relationships require further validation. Asperulosidic acid may represent a key bioactive component with broad target-binding potential. This study was limited by the use of an LPS-induced rat ALI model without gene knockout or target inhibitor validation; therefore, further functional experiments are required to confirm the proposed regulatory mechanisms.

PMID:42737981 | PMC:PMC13564518 | DOI:10.3390/biology15171549