Lung cancer in never-smoking patients (LCINS) has gradually gained attention in recent years, and emerging evidence points to a potential role of the gut microbiota in LCINS by modulating host immunity and metabolism. In this study, metagenomics was performed on stool samples from 24 LCINS patients and 18 healthy individuals. LCINS patients exhibited reduced microbial richness in α-diversity compared with healthy controls, and differences in principal component distribution were observed. Pathway enrichment analyses revealed that LPS biosynthesis capacity was significantly increased, whereas the fatty acid biosynthesis pathway was significantly decreased in LCINS. A total of 317 differentially abundant species were identified, including 29 assigned to the module most strongly associated with LCINS based on weighted gene co-expression network (WGCNA). Then, 36 machine learning–based diagnostic models were constructed based on these 29 species, with the glmBoost + Ridge model showing the best performance for LCINS discrimination (AUC = 0.855). SHAP (SHapley Additive exPlanations) identified Clostridium aminophilum as a protective factor and the top contributor to model performance (SHAP value = 0.068), with a single-species AUC of 0.743. In vitro , the culture supernatant of Clostridium aminophilum markedly suppressed A549 cell proliferation and migration. In vivo , oral administration of Clostridium aminophilum (5 × 10 ⁶ CFU) for 21 days significantly suppressed tumor growth in subcutaneous A549-derived xenograft models. These findings suggest a significant association between LCINS and the gut microbiota, characterized by a marked depletion of Clostridium aminophilum . Notably, metabolites derived from Clostridium aminophilum were shown to inhibit lung cancer progression. IMPORTANCE: Lung cancer remains the leading cause of cancer incidence and mortality worldwide, and the proportion of lung cancer in patients who have never smoked (LCINS) has been steadily increasing. However, the potential role of the gut microbiota in this disease has not been fully explored. In this study, we characterized the gut microbial spectrum of LCINS patients using metagenomic sequencing and developed a lung cancer predictive model with translational potential. Importantly, we identified a beneficial bacterium, Clostridium aminophilum , which may be developed as a probiotic to support conventional lung cancer treatments. These findings offer promising avenues for early diagnosis, adjunctive therapy, and personalized management of gut microbiota in LCINS patients.

Background: While neutrophil extracellular traps (NETs) have been shown to contribute to cancer progression, including that of lung adenocarcinoma, the mechanisms underlying NET formation within the tumor immune microenvironment (TIME) remain incompletely understood. Notably, neutrophil infiltration has been strongly linked to tumor necrosis factor alpha-inducible protein 6 (TNFAIP6) expression. Methods: In vitro and in vivo experiments were performed. DNA pulldown coupled with mass spectrometry, bioinformatics analyses, immunohistochemistry, and dual-luciferase reporter assays were conducted. DNA pulldown Western blotting, chromatin immunoprecipitation–quantitative PCR, and dual-luciferase reporter assays using truncated promoter constructs were also employed. Results: TNFAIP6 expressed by lung adenocarcinoma cells was shown to induce NET formation (a form of programmed cell death called NETosis). Mechanistically, TNFAIP6 interacted with CD44 in lung adenocarcinoma cells, leading to increased extracellular availability of secreted phosphoprotein 1 (SPP1) within the TIME and the subsequent promotion of NETosis. Additionally, nucleophosmin 1 (NPM1) significantly enhances the transcriptional activation of TNFAIP6 and associates with the −2000 to −1700 bp region of its promoter. Conclusions: These findings delineate a regulatory model in which lung adenocarcinoma cells directly stimulate NETosis through the NPM1–TNFAIP6–CD44–SPP1 axis, suggesting that therapeutic targeting of this pathway may attenuate tumor progression.

Background: Neutrophil extracellular traps (NETs) promote tumor progression and immune evasion across multiple cancers. However, the mechanisms governing NET formation (NETosis) within the tumor immune microenvironment remain incompletely understood. Low P2RY13 expression is associated with the pro-tumor activity of neutrophils in lung adenocarcinoma. Methods: Pan-cancer bioinformatics analyses were performed, including differential gene expression, prognostic, tumor-infiltrating immune cell, and NET scoring analyses. Single-cell profiling was conducted using the Tumor Immune Single-cell Hub 2 database. Immunohistochemical (IHC) and multiplex immunofluorescence (mIF) staining of tissue microarrays (TMAs) was performed to validate findings in lung adenocarcinoma (LUAD), liver hepatocellular carcinoma (LIHC), and colorectal cancer (CRC). In vitro validation was conducted using gene modulation, tumor-cell-conditioned medium (CM) education, tumor-associated macrophage (TAM)-like macrophage CM transfer, immunofluorescence staining, and ELISA. Results: Bioinformatics analyses suggested that P2RY13 is frequently dysregulated in multiple cancers and that low P2RY13 expression is associated with poor prognosis and reduced immunotherapy responsiveness. Single-cell analyses revealed that P2RY13 is predominantly expressed in TAMs rather than tumor cells. Macrophages without detectable P2RY13 transcripts were markedly enriched in tumor tissues compared with paired normal tissues, and their high infiltration appeared to be associated with elevated NET scores. Tissue microarray-based IHC and mIF analyses further validated this infiltration pattern in LUAD, LIHC, and CRC. In vitro, CM from P2RY13-silenced, tumor-educated TAM-like macrophages enhanced neutrophil NETosis, whereas P2RY13 re-expression attenuated this effect. Furthermore, TMA staining indicated a positive correlation between P2RY13⁻CD68⁺ TAM infiltration and NET expression in the three malignancies. Conclusions: We identified a potentially conserved NETosis-regulating pattern in multiple cancers in which P2RY13-negative TAMs promote NET formation and are associated with adverse clinical outcomes. These findings suggest a previously unrecognized tumor-promoting mechanism and highlight potential therapeutic targets for cancer treatment.

Background/Objectives: Ischemic skeletal muscle undergoes metabolic remodeling that may influence vascular repair. We investigated whether coniferaldehyde (CA) regulates a phosphoglycerate kinase 1 (PGK1)–3-phosphoglycerate (3PG)–L-serine axis in mouse hindlimb ischemia (HLI). Methods: Gastrocnemius tissue from Sham, HLI, and HLI+CA mice (n = 6/group) underwent bulk RNA sequencing and untargeted metabolomics. Public single-cell data and hypoxic human skeletal muscle cells (HSkMCs) were used to examine PGK1. AlphaFold3 modeling, molecular dynamics simulation, and a cellular thermal shift assay (CETSA) were used to evaluate a potential CA–PGK1 interaction. HSkMC-conditioned media were applied to human umbilical vein endothelial cells (HUVECs), with 3PG supplementation where indicated. Results: Amino-acid biosynthesis and glycine/serine/threonine metabolism were enriched in HLI muscle. 3PG increased in HLI versus Sham (p = 0.0170) and decreased in HLI+CA versus HLI (p = 0.0358); L-serine followed the same pattern (p = 0.0274 and p = 0.0428, respectively). Pgk1 expression also increased in HLI versus Sham (p = 0.00348) and decreased in HLI+CA versus HLI (p = 0.00249). Hypoxia increased HSkMC PGK1 together with extracellular 3PG and serine, whereas CA attenuated all three. Modeling predicted a stable CA–PGK1 complex, and CETSA supported a potential CA–PGK1 interaction in cell lysates. Conditioned medium from CA-treated hypoxic HSkMCs improved HUVEC viability, redox, tube-formation, and wound-closure readouts, reduced reactive oxygen species, and increased glutathione peroxidase 4 (GPX4) and solute carrier, family 7 member 11 (SLC7A11); 3PG supplementation reversed these effects. Conclusions: CA modulates a PGK1-linked 3PG/L-serine metabolic axis, while 3PG exposure altered endothelial phenotypes in the conditioned-medium model.