❌

Reading view

WNT7A correlates with immunosuppression and predicts adverse prognosis in lung adenocarcinoma: Potential implication of the NF-kappaB/CCL2 Axis

Cytokine. 2026 Apr 6;202:157144. doi: 10.1016/j.cyto.2026.157144. Online ahead of print.

ABSTRACT

BACKGROUND: The remodeling of the tumor immune microenvironment (TME) is a pivotal determinant of therapeutic efficacy and clinical outcome in Lung Adenocarcinoma (LUAD). While WNT signaling is a known oncogenic driver, the specific immunomodulatory role of WNT7A and its potential crosstalk with inflammatory pathways in LUAD remain to be fully elucidated. We sought to define the prognostic value of WNT7A and explore the molecular mechanisms by which it may foster an immunosuppressive TME.

METHODS: We performed a multi-omics analysis utilizing the TCGA-LUAD cohort (N = 508) and validated findings in an independent external cohort (GSE30219, N = 293). The prognostic significance of WNT7A was evaluated using Kaplan-Meier and multivariate Cox regression analyses. TME composition was dissected via ssGSEA, focusing on myeloid-derived suppressor cell (MDSC) infiltration. Mechanistic pathways were identified using Gene Set Enrichment Analysis (GSEA) and gene co-expression networks.

RESULTS: High WNT7A expression was identified as a significant predictor of poor Overall Survival (OS) in the TCGA cohort (P < 0.05) and validated in the external cohort (P < 0.05). Multivariate analysis confirmed WNT7A as an independent prognostic risk factor (HR = 1.085, P = 0.036). Immunologically, WNT7A expression was positively correlated with MDSC infiltration (R = 0.43, P < 0.001), suggesting a shift towards an immune-tolerant phenotype. Mechanistically, GSEA revealed a robust activation of inflammatory signaling in the high-WNT7A group. Specifically, the TNFA Signaling via NF-κB pathway was significantly enriched(NES = 2.52, P < 0.001). Consistent with this pathway activation, WNT7A showed a statistically significant positive correlation with CCL2 (P < 0.001), a critical chemokine for MDSC recruitment, implicating the NF-κB/CCL2 axis in this process.

CONCLUSION: WNT7A serves as a prognostic biomarker linked to immune evasion in LUAD, potentially by modulating the NF-κB/CCL2/MDSC axis. This study identifies WNT7A as a potential therapeutic target to remodel the immune microenvironment, providing a rationale for future investigations into WNT-targeted strategies to improve immunotherapy efficacy.

PMID:41946008 | DOI:10.1016/j.cyto.2026.157144

  •  

Iron Physiology and Its Impact on Atopic Diseases: An EAACI Taskforce Report

Allergy. 2026 Apr 6. doi: 10.1111/all.70325. Online ahead of print.

ABSTRACT

Iron is essential for oxygen transport, energy metabolism, and immune regulation. Yet iron deficiency is the most common micronutrient disorder across all age groups, affecting nearly one quarter of the global population. Iron deficiency triggers nutritional immunity, a host defense mechanism that withholds and redistributes iron, contributing to increased morbidity and mortality. This review outlines normal iron physiology, distribution and absorption pathways and on the consequences of deficiency across body compartments, with particular attention to type 2-driven diseases. Beyond anemia, insufficient iron availability disrupts immune homeostasis by promoting type 2 inflammation, elevating IgE, and activating mast cells and eosinophils. Regulatory macrophages, the central hub of iron cycling, adopt an inflammatory, iron-sequestering state that reinforces malabsorption and redistribution. Epidemiology studies show higher iron-deficiency risk in allergic individuals; low maternal iron or early-life iron predisposes to eczema, wheeze, and asthma, while food-allergen elimination (notably cow's milk) further worsens anemia risk. Clinical evidence indicates that restoring iron status through diet, supplementation, or fortification lowers IgE levels, improves lung function, and alleviates symptoms of rhinitis, urticaria, and asthma. Iron may therefore represent a modifiable determinant of allergic disease development and severity. Integrating iron assessment and nutritional care into allergy management may reduce disease burden and slow the progression of allergic march.

PMID:41943501 | DOI:10.1111/all.70325

  •  

Molecular and Phenotypic Characterization of Fluid-Derived Patient-Derived Cell and Organoid Models in Advanced Gastric Cancer

J Gastric Cancer. 2026 Apr;26(2):260-278. doi: 10.5230/jgc.2026.26.e19.

ABSTRACT

PURPOSE: Patient-derived cells (PDCs) and patient-derived organoids (PDOs) are complementary preclinical models widely used in translational cancer research. However, their molecular and functional differences have not been systematically characterized. This study established and analyzed paired PDC and PDO models derived from the same gastric cancer ascites to delineate platform-dependent molecular and functional profiles.

MATERIALS AND METHODS: Malignant ascites or pleural fluid obtained from 6 patients with advanced gastric cancer were used to establish paired PDC and PDO models. All pairs underwent comprehensive multi-omics profiling, integrating genomic, transcriptomic, and proteomic data. Phenotypic characterization included morphological, histological, proliferative, and cell cycle analyses. Drug sensitivity assays were performed using 4 chemotherapeutic agents commonly used to treat gastric cancer.

RESULTS: The 6 paired PDC and PDO models exhibited distinct morphological characteristics. Whole-genome analyses demonstrated high concordance among primary tumors, PDCs, and PDOs, confirming tumor representation across platforms. Multi-omics profiling identified platform-dependent molecular signatures; PDOs were enriched for extracellular matrix remodeling and stemness, whereas PDCs displayed proliferation- and immune-related signatures. Clinically relevant biomarkers, including HER2 and MET alterations, were concordant with primary tumors. Notably, drug responses differed between platforms and patients, indicating platform-dependent and patient-specific chemosensitivity.

CONCLUSIONS: Paired PDC and PDO models derived from the same patients preserved core patient-specific tumor characteristics while exhibiting distinct molecular and functional profiles. These findings underscore the culture platform as a critical determinant of experimental outcomes and therapeutic responses. Therefore, careful selection of an appropriate preclinical model is essential to accurately address biological questions and optimize precision oncology strategies.

PMID:41942359 | DOI:10.5230/jgc.2026.26.e19

  •  

Protective Effects of the Ethyl Acetate Fraction from Madeng'ai on Lipopolysaccharide-Induced Acute Lung Injury in Mice: Insights from Integrated Multi-Omics Analysis

J Ethnopharmacol. 2026 Apr 4:121650. doi: 10.1016/j.jep.2026.121650. Online ahead of print.

ABSTRACT

ETHNOPHARMACOLOGICAL RELEVANCE: Madeng'ai (MDA) is a traditional medicinal plant of the Dong ethnic group. Its roots have been widely used in folk medicine for clearing heat and removing toxins, alleviating swelling and relieving pain, dispersing blood stasis and arresting bleeding, as well as promoting wound healing. It is taxonomically classified as a variety of Potentilla freyniana Bornm.

AIM OF THE STUDY: Acute lung injury (ALI) is a life-threatening pulmonary disorder associated with high mortality, underscoring the urgent need to explore novel therapeutic strategies. This study aimed to evaluate the protective effects of the ethyl acetate fraction of MDA (MEA) against LPS-induced ALI in mice and to investigate its underlying mechanisms.

MATERIALS AND METHODS: LC-MS/MS was employed to tentatively identify the bioactive components of MEA. A mouse model of ALI was established by LPS induction. The protective effects of MEA were evaluated through assessments of lung histopathology, inflammatory cytokine levels, and oxidative stress markers. The underlying mechanisms were systematically investigated by integrating transcriptomics, metabolomics, network pharmacology, molecular docking, and Western blotting.

RESULTS: MEA significantly attenuated LPS-induced pulmonary pathological lesions, pulmonary edema, and excessive inflammatory responses in ALI mice. Comprehensive bioinformatics analyses predicted potential mechanisms involving oxidative stress and the regulation of metabolic pathways. Experimental validation via Western blotting confirmed that MEA inhibited TLR4-mediated inflammatory signaling and modulated the PI3K/AKT pathway, thereby exerting multi-pathway protective effects against ALI.

CONCLUSIONS: Collectively, this study confirms that MEA, as a traditional herbal extract, holds potential as an adjuvant therapeutic agent for ALI, providing experimental evidence for the modernization and development of ethnic medicines.

PMID:41941987 | DOI:10.1016/j.jep.2026.121650

  •  

TRIM36 and CAMK2N2 regulate ferroptosis and antigen presentation in small cell lung cancer

iScience. 2026 Mar 11;29(4):115310. doi: 10.1016/j.isci.2026.115310. eCollection 2026 Apr 17.

ABSTRACT

Small cell lung cancer (SCLC) is a highly aggressive tumor with poor prognosis. Ferroptosis is closely linked to tumor antigen presentation: it affects antigen presentation efficiency via immunostimulatory signals, while CD8+ T cell activation induced by antigen presentation promotes tumor cell ferroptosis by secreting IFNγ. This study used multi-omics analyses and machine learning to screen key genes, verified by in vitro/in vivo experiments. TRIM36 and CAMK2N2 were significantly upregulated in SCLC, negatively correlating with patient survival, effector memory CD8+ T cell infiltration, and tumor MHC I expression. They suppress SCLC antigen presentation via ferroptosis-dependent/independent mechanisms, limiting T cell function. TRIM36 and CAMK2N2 are promising SCLC biomarkers and therapeutic targets, providing clues to unravel ferroptosis-antigen presentation associations in tumor cells and optimize immunotherapeutic strategies.

PMID:41940332 | PMC:PMC13049528 | DOI:10.1016/j.isci.2026.115310

  •  

ASTROREPOMICS: A curated transcriptomic database for reproductive biology in space

iScience. 2026 Mar 10;29(4):115309. doi: 10.1016/j.isci.2026.115309. eCollection 2026 Apr 17.

ABSTRACT

Spaceflight imposes substantial physiological stress on reproductive systems, yet relevant transcriptomic data remain fragmented across repositories. To address this need, we developed ASTROREPOMICS, a web-based platform that integrates 17 rigorously normalized and batch-corrected transcriptomic datasets spanning multiple species and reproductive tissues. The platform supports reproducible cross-study and cross-species analyses through standardized metadata and an intuitive user interface. We highlight its utility through two example analyses: (1) irradiated mouse sperm exhibited suppression of RNA splicing and protein-processing pathways alongside activation of interferon- and GPCR-associated programs; and (2) a multi-species intersected-DEG assessment between irradiated rat mammary tissue and microgravity-exposed zebrafish embryos uncovered conserved signatures involving RNA metabolism, cytokine signaling, and angiogenesis. By consolidating dispersed datasets and offering tailored analytical capabilities, ASTROREPOMICS provides a centralized resource for hypothesis generation and strengthens the research infrastructure needed to advance reproductive health studies in space, supporting long-term efforts to safeguard fertility during deep-space exploration.

PMID:41940322 | PMC:PMC13049440 | DOI:10.1016/j.isci.2026.115309

  •  

Decoding macrophage heterogeneity in the pulmonary fibrosis lung cancer transition

Front Immunol. 2026 Mar 20;17:1787094. doi: 10.3389/fimmu.2026.1787094. eCollection 2026.

ABSTRACT

Pulmonary fibrosis (PF) significantly increases the risk of lung cancer (LC), but the mechanisms underlying this transition remain unclear. This overview positions macrophage heterogeneity as a central node within the PF-LC continuum. First, we describe important subpopulations of profibrotic and pro-tumor macrophages, including SPP1+, MERTK+, TREM2+, and MARCO+ cells, using high-resolution spatial and single-cell omics technologies. Next, we analyze the fundamental mechanisms that determine their function: the fibrotic microenvironment (e.g., extracellular matrix stiffness, hypoxia) induces profound metabolic reprogramming (e.g., Warburg effect, lipid peroxidation) and stabilizes epigenetic memory (e.g., DNA methylation, histone modifications), locking them into a pathogenic state. This reprogramming occurs through two main pathways: (1) metabolic reprogramming, characterized by aerobic glycolytic conversion and dysregulated lipid metabolism, which stimulates both pathogenic functions and suppression of T cell activity; (2) Epigenetic modifications, including stabilized alterations in DNA methylation, histone modifications, and superactivator patterns, which maintain cells in a tumor-promoting phenotype. As central nodes of communication, these macrophages interact pathologically with fibroblasts and epithelial cells through secreted factors and extracellular vesicles, forming self-reinforcing feedback loops that promote disease progression. We are studying the crucial role of new technologies, particularly multi-omic spatial models and high-precision organoids, in fostering mechanistic discoveries. These discoveries pave the way for new macrophage-focused therapeutic strategies, including the precise stratification of patients using biomarkers from liquid biopsies (such as soluble SPP1 and MARCO) and the development of targeted drug delivery systems for the selective modulation of macrophage function, thus establishing a new paradigm for therapeutic interventions in pulmonary fibrosis with concomitant lung cancer.

PMID:41939908 | PMC:PMC13046558 | DOI:10.3389/fimmu.2026.1787094

  •  

Multi-omics integration and machine learning reveal gut-immune signatures in idiopathic pulmonary fibrosis: insights from bulk RNA-seq, single-cell profiles, spatial transcriptomics, and experimental validation

Front Immunol. 2026 Mar 19;17:1730289. doi: 10.3389/fimmu.2026.1730289. eCollection 2026.

ABSTRACT

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease with limited treatment options and a poor prognosis. Recent studies suggest a critical role for the gut-immune-lung axis in IPF, yet the underlying molecular mechanisms remain unclear.

METHODS: The current study performed in silico multi-omics integration of publicly available datasets, including bulk RNA-seq, single-cell and spatial transcriptomics, as well as peripheral blood multi-omics data to uncover key molecular signatures in IPF. Furthermore, machine learning techniques were utilized to identify core genes, whereas functional analyses and Mendelian randomization were conducted to evaluate the causal relationships among gut microbiota, immune cells, and IPF. Additionally, experimental validation using qPCR and ELISA assays was conducted in vitro, in vivo, and in patient plasma to confirm the expression patterns of key genes.

RESULTS: Across integrated public bulk, single-cell, spatial, and blood multi-omics, CXCL13, IL33, TLR4, and IGF1 were identified as core IPF genes consistently linked to immune infiltration and fibrotic remodeling. Deconvolution, scRNA-seq, and spatial mapping localized their dysregulation to fibroblasts and immune compartments (notably B-cell, macrophage, and mast-cell axes), highlighting fibroblast-immune crosstalk in fibrotic foci. A four-gene model robustly distinguished IPF from controls across cohorts. Mendelian randomization supported a gut-immune-lung axis, indicating causal effects of specific gut taxa on IPF risk via immune phenotypes. qPCR/ELISA in TGF-β1-stimulated fibroblasts, bleomycin mouse lungs, and patient plasma corroborated upregulation of IL33, CXCL13, IGF1 and downregulation of TLR4. Drug-signature reversal nominated cucurbitacin I and temsirolimus; molecular docking was performed as a preliminary in silico, computer-simulation-based assessment of potential ligand-protein interactions between these compounds and the four core targets.

CONCLUSION: This study provides new insights into the importance of gut-immune-lung axis in IPF and identifies CXCL13, IL33, TLR4, and IGF1 as diagnostic signatures and therapeutic targets. By integrating public multi-omics resources with experimental validation, our findings offer a foundation for future diagnostic and treatment strategies aimed at modulating the gut microbiota and immune system in IPF.

PMID:41939867 | PMC:PMC13043422 | DOI:10.3389/fimmu.2026.1730289

  •  

Integrative Multi-Omics and Single-Cell Analysis Reveal THOC3 and THOC7 as Oncogenic RNA Processing Regulators in Lung Adenocarcinoma

Int J Med Sci. 2026 Mar 9;23(4):1408-1430. doi: 10.7150/ijms.128975. eCollection 2026.

ABSTRACT

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality worldwide. Although the transcription-export (TREX) complex plays a central role in RNA maturation and nuclear export, the clinical and biological relevance of individual THO Complex Subunit (including THOC1, THOC2, THOC3, THOC5, THOC6, and THOC7) in LUAD is not well defined. We performed integrative analyses combining bulk transcriptomics from TCGA/GTEx and independent GEO cohorts, survival modeling, DNA methylation profiling, protein-level annotation from public resources, protein-protein interaction network analysis, immune infiltration estimation (TIMER), and single-cell RNA sequencing (scRNA-seq) to evaluate the relevance of THOC3 and THOC7 in LUAD. Across TCGA and external GEO validation datasets, THOC3 and THOC7 were consistently upregulated in LUAD and associated with poorer overall and disease-free survival, whereas other THO complex members showed weaker or inconsistent associations. Given these comparatively consistent and reproducible signals, we therefore prioritized THOC3 and THOC7 for downstream multi-layer analyses. Epigenetic profiling and interaction network analyses placed both genes within conserved RNA processing and export programs linked to genome maintenance pathways. Single-cell transcriptomic analysis provided additional resolution, demonstrating predominant enrichment of THOC3 and THOC7 in malignant epithelial clusters, with THOC3 aligning with transcriptional programs associated with DNA replication and repair, and THOC7 with proliferative and checkpoint-related states. Notably, expression of both genes was also detectable in myeloid and neutrophil subsets, and THOC7 expression remained elevated in recurrent LUAD samples, indicating association with aggressive and treatment-resistant disease states. Collectively, by integrating bulk, single-cell, epigenetic, and immune profiling across multiple independent cohorts, this study identifies THOC3 and THOC7 as reproducible molecular correlates of aggressive LUAD phenotypes. These highlight dysregulated RNA export programs as potential biomarkers of poor prognosis and motivate future functional studies to assess RNA export dependencies in LUAD.

PMID:41938520 | PMC:PMC13048885 | DOI:10.7150/ijms.128975

  •  

A Data-driven Approach for Biomarker Discovery based on U-centered Distance Correlation Network: Multi-omics Warning Signals for Non-small Cell Lung Cancer

Comb Chem High Throughput Screen. 2026 Mar 27. doi: 10.2174/0113862073445368260131002109. Online ahead of print.

ABSTRACT

INTRODUCTION/OBJECTIVE: Lung cancer is the leading cause of cancer-related mortality worldwide, and non-small cell lung cancer (NSCLC) accounts for the majority of cases. Alterations in metabolic activities play important roles in NSCLC development, wherein related genes and metabolites interact with each other, involving multiple forms.

METHODS: To comprehensively understand the pathogenic mechanisms and improve the performance of clinical early, precise diagnosis, this study proposed a data-driven approach for biomarker discovery based on U-centered distance correlation network (DCN) to investigate NSCLC metabolism-related reactions. In DCN, changes in molecular relationships during NSCLC initiation and progression are measured using the t-statistics of U-centered distance correlation for network construction, in which prospective warning signals representing NSCLC onset can be identified without human intervention. Additionally, the network construction criterion in DCN can precisely and effectively capture both linear and nonlinear molecular relationships in simple and biologically relevant manners.

RESULTS: DCN was successfully employed to analyze NSCLC metabolism-related metabolomics and genomics datasets. Statistical analyses confirmed that compared with other algorithms, the gene and metabolite biomarker panels identified by DCN provided more reliable diagnostic capabilities for clinical NSCLC detection. Biological analyses revealed that disturbed energy metabolism and lipid metabolism occurred during tumor cell proliferation and growth in NSCLC patients.

DISCUSSION: The gene ASPA and metabolite aspartic acid were significantly decreased in NSCLC samples, suggesting that the corresponding amino acid metabolic activities were intricately linked to NSCLC progression.

CONCLUSION: These findings demonstrated that DCN can further facilitate NSCLC studies to improve clinical outcomes in patients.

PMID:41937706 | DOI:10.2174/0113862073445368260131002109

  •  

Integration of multi-omics and machine learning to identify core genes in PANoptosisof lung adenocarcinoma and their mechanisms in the tumor microenvironment and therapeutic potential

Naunyn Schmiedebergs Arch Pharmacol. 2026 Apr 5. doi: 10.1007/s00210-026-05251-7. Online ahead of print.

ABSTRACT

Lung adenocarcinoma (LUAD) is one of the leading causes of cancer-related deaths worldwide, and its complex tumor microenvironment (TME) is a key barrier to treatment. PANoptosis is a novel programmed cell death mechanism that integrates features of pyroptosis, apoptosis, and necroptosis. However, its core regulatory network and cell specific role in LUAD are still unclear. This study integrated three LUAD transcriptome datasets, screened differentially expressed genes through bioinformatics analysis, and intersected with PANoptosis-related genes to construct a protein interaction network, using a combination of 113 machine learning algorithms to screen and validate core genes and using CIBERSORT and single-cell transcriptome data to analyze the spatial expression characteristics of immune cell infiltration and core genes. Finally, the intervention mechanism of core targets and ginsenosides was validated through molecular docking, immunohistochemistry, and cell experiments (CCK-8, Western Blot). Six core genes of LUAD PANoptosis, including IRF1, NLRP3, CASP1, TIMP1, S100A8, and TLR4, were identified in the study. Single-cell analysis revealed that these genes were significantly enriched in M2 macrophages. Functional enrichment indicates that they jointly regulate death- and inflammation-related pathways such as NF-κB signaling and NOD-like receptor signaling. In vitro experiments have confirmed that ginsenosides can induce PANoptosis, promote tumor cell death, or inhibit LUAD cell proliferation by upregulating the ZBP1/AIM2/RIPK3/CASP1 death complex and inhibiting the TLR4/NLRP3 survival signaling axis. This study systematically revealed a PANoptosis core gene network centered on M2 macrophages in LUAD, elucidating a new mechanism by which ginsenosides induce integrated cell death by regulating this network. This provides new potential targets and theoretical basis for the immunotherapy of LUAD and the development of traditional Chinese medicine monomers.

PMID:41935997 | DOI:10.1007/s00210-026-05251-7

  •  
❌