ORIGINAL RESEARCH article
Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
This article is part of the Research TopicNovel Immune Markers and Predictive Models for Diagnosis, Immunotherapy and Prognosis in Lung CancerView all articles
DDR1 as a Key Prognostic Biomarker in Non-Small Cell Lung Cancer: Identification, Validation, and Potential Therapeutic Implications
Provisionally accepted
- 1Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
- 2Department of Nuclear Medicine, The First People's Hospital of Yunnan Province, Kunming, China
- 3Department of Pathology, The First People's Hospital of Yunnan Province, Kunming, China
- 4No.926 Hospital, Joint Logistics Support Force of PLA, Kaiyuan, China
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Abstract Background: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related death, with a limited response to immune checkpoint inhibitors (ICIs). Discoidin domain receptor 1 (DDR1) is a collagen-binding kinase that is implicated in tumor progression and immune escape, but its role in NSCLC is unclear. This study aimed to clarify the clinical significance and therapeutic potential of DDR1 via bioinformatics, machine learning, in vitro experiments, and clinical sample analysis. Materials and Methods: NSCLC patients were stratified by DDR1 expression based on retrospective RNA-seq data from The Cancer Genome Atlas (TCGA); after quality control, 495 lung adenocarcinoma (LUAD) and 481 lung squamous cell carcinoma (LUSC) tumor samples, together with 57 LUAD and 48 LUSC normal samples, were retained for further analysis. The analyses included survival, mutation, immune landscape, drug sensitivity, single-cell heterogeneity, and functional Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, accounting for the heterogeneity among NSCLC subtypes. A machine learning-based 4-gene prognostic model was constructed and externally validated using two independent datasets: GSE30219
Keywords: discoidin domain receptor 1, Non-small cell lung cancer, bioinformatics, machine learning, Immunotherapy
Received: 22 Aug 2025; Accepted: 17 Nov 2025.
Copyright: © 2025 Lu, Qian, Sun, Zhang, Cui, Su, Xv and Wang. 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:
Dongdong Xv, 8421965@qq.com
ShaoBo Wang, wshbo_98@126.com
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