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

J Transl Med. 2026 Mar 20. doi: 10.1186/s12967-026-08022-3. Online ahead of print.

ABSTRACT

BACKGROUND: Lung adenocarcinoma (LUAD) is a predominant contributor to cancer‑related mortality globally. Lung‑associated fibroblasts (LAFs) are intricately linked to tumorigenesis and the tumor microenvironment (TME), but their heterogeneity and prognostic relevance in LUAD remain incompletely understood. This study aimed to systematically characterize LAF subsets across the spectrum of pulmonary disease, identify LAF subpopulations associated with LUAD prognosis, and construct a robust LAF‑based prognostic signature.

METHODS: We employed a multi-omics approach, leveraging bulk RNA data of 2719 patients from 19 LUAD cohorts, single-cell RNA (scRNA) sequencing data of 368,904 cells from 93 samples, and spatial transcriptomics data of 15,673 spots from 6 samples to characterize the landscape of LAFs across various stages of pulmonary disease. We employed multiple advanced machine learning algorithms to construct and validate a robust nuclear division LAFs (nLAFs) risk score (nLRS) prediction model.

RESULTS: We observed a dynamic and gradual increase in the proportion of LAFs during the progression of LUAD. Throughout this process, we identified nine LAFs subtypes and found nLAFs are significantly associated with the prognosis of LUAD. Utilizing 100 machine learning algorithm combinations and integrating nLAFs marker genes, we developed a five gene based nLRS model, which demonstrated superior performance than other 49 published models in predicting clinical outcomes for LUAD. Additionally, we observed distinct biological functions and immune cell infiltration in the TME between high and low nLRS groups. Exploratory analysis of pan-cancer immunotherapy cohorts suggested that patients with high nLRS scores may exhibit resistance to immunotherapy in some cancer types, but prospective validation in LUAD-specific cohorts is required. Conversely, high nLRS patients displayed increased sensitivity to chemotherapeutic and targeted therapies in preclinical models.

CONCLUSION: Our study introduces a candidate five-gene signature derived from nLAFs that may serve as a robust prognostic biomarker pending prospective validation, offering insights into personalized therapeutic strategies for LUAD patients.

PMID:41862916 | DOI:10.1186/s12967-026-08022-3