DDR1 as a key prognostic biomarker in non-small cell lung cancer: identification, validation, and potential...

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.

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 (GPL570 platform, 278 NSCLC samples) and GSE41271 (GPL6884 platform, 274 NSCLC samples). The biological functions of DDR1 were further evaluated via in vitro assays and immunohistochemistry (IHC) of clinical samples.

High DDR1 expression was correlated with advanced T stage (P<0.05), poor progression-free survival (PFS) (HR = 1.62, P<0.001), and an immunosuppressive microenvironment. Drug sensitivity analysis revealed that high DDR1 expression was associated with reduced sensitivity to methotrexate but increased sensitivity to vinblastine, doxorubicin, cisplatin, and docetaxel, with no significant difference observed for gefitinib. Single-cell heterogeneity analysis revealed that DDR1 was enriched in tumor-associated macrophages and neutrophils. A LASSO and random survival forest (RSF) machine learning algorithm revealed a 4-gene signature (PKP2, DKK1, TEF, and GJB5) with strong prognostic value (C-index=0.728). DDR1 knockdown suppressed cell proliferation, migration, and invasion and induced apoptosis in NSCLC cell lines. IHC of clinical samples confirmed DDR1 overexpression in 55.88% of NSCLC patients.

Our study demonstrated that DDR1 promotes tumor progression and immune evasion and is frequently overexpressed in NSCLC patients, suggesting that DDR1 is a potential prognostic biomarker and therapeutic target.