Journal of Shanghai Jiao Tong University (Medical Science) ›› 2026, Vol. 46 ›› Issue (4): 451-466.doi: 10.3969/j.issn.1674-8115.2026.04.005

• Basic research • Previous Articles    

Bioinformatic analysis and validation of the RNA-binding protein HuR promoting non-small cell lung cancer progression via ITGB1

Peng Qianqian, Song Jinghan, Xu Xingyi, Xiao Hui()   

  1. Department of Respiratory and Critical Care Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
  • Received:2025-09-25 Accepted:2025-12-23 Online:2026-04-15 Published:2026-04-15
  • Contact: Xiao Hui E-mail:xiaohui771210@163.com
  • Supported by:
    National Natural Science Foundation of China(82172692)

Abstract:

Objective ·To systematically identify the key downstream target genes of the RNA-binding protein human antigen R (HuR) in non-small cell lung cancer (NSCLC) and to elucidate the molecular mechanisms through which HuR influences tumor progression by regulating this target. Methods ·Based on the The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, the differential expression of HuR in NSCLC and adjacent tissues was analyzed. HuR protein levels were detected via immunohistochemistry and validated by using the GSE19188 dataset. Using TCGA data, the relationship between HuR expression and clinicopathological parameters was analyzed; survival analysis was performed, and univariate and multivariate Cox regression analyses were conducted to assess prognostic factors, followed by the construction of a nomogram model to predict survival rates. The ESTIMATE package and CIBERSORT algorithm were used to analyze the correlation between HuR expression and the tumor immune microenvironment. A Transwell assay was employed to detect changes in the migration and invasion capabilities of A549 cells after HuR knockdown. RNA-seq was used to screen for differentially expressed genes (DEGs), and hub genes were identified by combining protein-protein interaction (PPI) network analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for functional enrichment. Mechanistically, RNA immunoprecipitation (RIP) was used to validate the direct binding between HuR and integrin β 1 (ITGB1) mRNA. Furthermore, real-time quantitative PCR (RT-qPCR) and Western blotting were performed to detect the expression changes of ITGB1 at the mRNA and protein levels, respectively, after HuR knockdown. Results ·HuR was significantly overexpressed in lung cancer tissues, independently associated with poor prognosis (P=0.045), and negatively correlated with characteristics of an immunosuppressive microenvironment. Functional experiments demonstrated that HuR knockdown significantly inhibited the migration (P<0.001) and invasion (P=0.002) capabilities of lung cancer cells. Bioinformatic analysis identified ITGB1 as the core hub gene downstream of HuR, and enrichment analysis revealed its significant involvement in pathways such as the extracellular matrix (ECM)-receptor interaction. RIP assays confirmed that HuR directly binds to ITGB1 mRNA. Further RT-qPCR and Western blotting results indicated that HuR knockdown led to significant downregulation of ITGB1 at both the mRNA (P=0.001) and protein levels, suggesting that HuR primarily exerts its post-transcriptional regulatory role by maintaining ITGB1 mRNA stability. Conclusion ·HuR promotes NSCLC progression by directly binding to and stabilizing ITGB1 mRNA, thereby activating downstream signaling pathways. The discovery of the HuR-ITGB1 regulatory axis not only provides a novel perspective for understanding the pathogenesis of lung cancer but also offers a potential target for prognosis assessment and targeted therapy.

Key words: non-small cell lung cancer (NSCLC), human antigen R (HuR), bioinformatic analysis, hub gene, immune cell infiltration, predictive model

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