Cell Death Dis. 2026 Apr 14. doi: 10.1038/s41419-026-08712-2. Online ahead of print.

ABSTRACT

Lung adenocarcinoma (LUAD), a leading cause of cancer mortality, involves incompletely understood epigenetic-metabolic crosstalk. We identified ANP32E as a key regulator through multi-omics (TCGA, scRNA-seq) and clinical analyses, finding its overexpression correlates with poor prognosis. Functionally, ANP32E knockdown suppressed proliferation, migration, and glycolysis in LUAD cells (A549/H1975) and attenuated xenograft growth, while overexpression promoted tumorigenesis. Mechanistically, ANP32E transcriptionally upregulates histone demethylase KDM3B, reducing repressive H3K9me2 marks at the EGFR promoter to enhance EGFR transcription. This activates PI3K/AKT signaling, inducing inhibitory GSK3β phosphorylation. Combined with ANP32E-mediated GSK3β suppression, this dual inactivation liberates oncogenic glycolysis. Crucially, KDM3B silencing or EGFR inhibition (Cetuximab) abrogated ANP32E-driven phenotypes. High-throughput screening identified Penta-O-galloyl-β-D-glucose (PGG) as an ANP32E-targeting compound, with molecular dynamics confirming binding. PGG dose-dependently inhibited the ANP32E/KDM3B/EGFR axis in vitro and suppressed tumor growth in vivo. Thus, ANP32E drives LUAD progression via KDM3B/EGFR-mediated GSK3β inactivation, representing a prognostic biomarker and therapeutic target validated by PGG.

PMID:41980942 | DOI:10.1038/s41419-026-08712-2

Int J Gen Med. 2026 Mar 24;19:590621. doi: 10.2147/IJGM.S590621. eCollection 2026.

ABSTRACT

Inflammatory bowel disease (IBD) involves chronic intestinal inflammation driven by gut-brain axis imbalance, fostering complications through an "inflammation-neuro-coagulation" triad. Current staging systems inadequately capture the dynamics of this multidimensional network. Therefore, integrated multi-omics analyses-including metagenomics, metabolomics, and single-cell transcriptomics-are essential to construct dynamic models that monitor coagulation, microbiome, and metabolism for precise assessment of disease activity and thrombotic or bleeding risks. Interventions targeting gut-brain axis nodes, such as eliminating tissue factor-positive (TF⁺) T cells or modulating vagal activity, show potential to disrupt the inflammation-coagulation cycle, although rigorous randomized trials are still needed. Artificial intelligence (AI)-assisted systems that integrate real-time biomarker monitoring with multi-omics predictions represent a novel paradigm for managing IBD-related coagulation dysfunction. Key challenges include elucidating gut-brain-liver axis regulation of coagulation and characterizing platelet functional heterogeneity. Future efforts must prioritize ethically compliant multi-omics platforms and racially stratified risk models to advance personalized coagulation management in IBD.

PMID:41913906 | PMC:PMC13033200 | DOI:10.2147/IJGM.S590621

J Int Med Res. 2026 Mar;54(3):3000605261430163. doi: 10.1177/03000605261430163. Epub 2026 Mar 16.

ABSTRACT

ObjectiveTo explore the potential involvement of PANoptosis-related genes in gastric cancer susceptibility through multiomics analyses.MethodsSummary-data-based Mendelian randomization was performed by integrating blood-derived methylation, gene expression, and protein quantitative trait loci data with genome-wide association study results. The findings were further evaluated in The Cancer Genome Atlas cohort, followed by protein-protein interaction analysis, drug prediction, and molecular docking.ResultsSummary-data-based Mendelian randomization and colocalization analyses identified several traits suggestively associated with gastric cancer risk. Genetically predicted higher expression of apoptosis and caspase activation inhibitor (AVEN) and hepatocyte growth factor (HGF) as well as higher HGF protein levels were associated with increased risk, whereas higher levels of protein phosphatase 2 regulatory subunit B beta (PPP2R2B) appeared to be protective. Multiomics integration suggested epigenetic regulation of HGF and PPP2R2B. The Cancer Genome Atlas analysis corroborated the dysregulation of these candidates, with high AVEN expression associated with poorer survival. Protein-protein interaction and drug prediction analyses highlighted functional networks and potential therapeutics, supported by molecular docking demonstrating strong HGF-binding affinities. However, these associations did not reach statistical significance in the independent validation cohort, possibly due to limited statistical power.ConclusionsThis study identified AVEN, HGF, and PPP2R2B as potential candidate genes for gastric cancer. These findings require further validation in larger cohorts.

PMID:41840829 | DOI:10.1177/03000605261430163