ORIGINAL RESEARCH article
Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
This article is part of the Research TopicImmune Predictive and Prognostic Biomarkers in Immuno-Oncology: Refining the Immunological Landscape of CancerView all 55 articles
Integrating Zinc Homeostasis Network and Immune Landscape: A Five-Gene Prognostic Framework for Precision Oncology in Lung Adenocarcinoma
Provisionally accepted
- 1Fuzong Clinical Medical College of Fujian Medical University, Fuzhou, China
- 2Fuzong Teaching Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, China
- 3Fuzong Clinical Medical College of Fujian Medical University & The 900th Hospital of Joint Logistic Support Force,, Fuzhou, China
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Background: Lung adenocarcinoma (LUAD) exhibits marked heterogeneity in clinical outcomes and therapeutic responses, underscoring the imperative for reliable prognostic biomarkers. Dysregulation of zinc homeostasis is an emerging hallmark of cancer, contributing to tumor progression through multifaceted mechanisms including exacerbated oxidative stress and sustained oncogenic signaling. This study aimed to develop and validate a novel prognostic signature based on zinc homeostasis network-related genes for stratifying LUAD patients into distinct risk groups to predict clinical outcomes and inform therapeutic strategies. Methods: Transcriptomic and clinical profiles of LUAD cases from the TCGA database were integrated to screen for differentially expressed genes (DEGs) involved in zinc homeostasis network. A prognostic risk model was constructed via univariate, multivariate, and LASSO regression analyses, and externally validated using GEO datasets. Model performance was evaluated using a nomogram, time-dependent ROC curves, and decision curve analysis. To characterize immune microenvironment heterogeneity across risk subgroups, we applied seven deconvolution algorithms, ssGSEA and single-cell profiling. Spearman correlation analysis and Wilcoxon rank-sum tests were used for investigating the associations between risk stratification and immunomodulatory markers, tumor mutational burden (TMB), as well as the predicted responsiveness to conventional chemotherapeutic and targeted therapies. In vitro experiments validated the expression levels of key candidate genes and confirmed their biological functions. Results: Differential expression analysis identified 124 zinc homeostasis network-related DEGs, of which 16 showed significant prognostic relevance. A five-gene risk model stratified patients into distinct prognostic groups, with high-risk cases showing markedly reduced overall survival. Risk score correlated positively with advanced clinical stages. Multivariate Cox regression confirmed the model as independently predictive of LUAD prognosis. A nomogram integrating risk score and clinical features was constructed for predicting 1-, 3-, and 5-year survival. Immune profiling showed that low-risk cases had hot tumor phenotypes, elevated immune scores and infiltration by immune cells, while those at high risk showed raised levels of immunotherapy resistance markers and increased TMB. Drug sensitivity analysis indicated differential responses to chemotherapeutic and targeted agents across risk groups. Independent knockdown of SLC16A3 or overexpression of EGR2 significantly suppressed malignant behaviors in LUAD cells. Additionally, SLC16A3 downregulation reduced cisplatin sensitivity in LUAD cells.
Keywords: Immunotherapy, LUAD, Prognostic model, Tumor Microenvironment, zinc homeostasis network
Received: 23 Aug 2025; Accepted: 09 Dec 2025.
Copyright: © 2025 Yu, Cheng, Xu, Zhang, Zhang, Chen, Zhou and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Zongyang Yu
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