ArticleDiscover oncology2025
Integrative bulk RNA analysis unveils immune evasion mechanisms and predictive biomarkers of osimertinib resistance in non-small cell lung cancer.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Non-small cell lung cancer (NSCLC) is one of the most prevalent and deadliest cancers worldwide, accounting for a significant global health burden. Targeted therapies such as osimertinib, a third-generation EGFR inhibitor, have transformed the treatment landscape for EGFR-mutant NSCLC by offering improved progression-free survival. However, the inevitable development of resistance remains a formidable challenge, necessitating deeper insights into its molecular underpinnings. In this study, we employed an integrative bioinformatics approach to analyze multi-cohort transcriptomic datasets, uncovering 126 resistance-associated genes, revealing 50 significant osimertinib resistance-related genes, and identifying eight key hub genes (KRT14, KRT16, KRT17, KRT5, KRT6A, KRT6B, TP63, and TRIM29) that contribute to immune evasion and tumor microenvironment remodeling. Integrated qPCR and Western blot analyses validated the significant upregulation of KRT14, KRT16, KRT6A, and TRIM29 in osimertinib-resistant cell lines (PC9 OR and HCC827 OR) at both transcriptional and translational levels, with KRT14 exhibiting the most pronounced upregulation. Functional assays demonstrated that KRT14 knockdown restored osimertinib sensitivity, suppressed proliferation, and impaired migration in resistant cells. Functional enrichment analyses revealed critical pathways, including p53 signaling and metabolic reprogramming, underlying resistance mechanisms. Batch effect analysis highlighted a marked reduction in effector immune cells, such as activated CD8 + T cells, alongside an increase in immunosuppressive populations, emphasizing the role of immune evasion in osimertinib resistance.We constructed a robust diagnostic model, nomoScore, based on the hub genes, achieving excellent predictive accuracy (AUC > 0.9) in training and validation datasets. These findings offer novel insights into resistance mechanisms and propose actionable strategies for integrating targeted and immunotherapies to improve outcomes for NSCLC patients. Future experimental and clinical studies are essential to validate and translate these findings into therapeutic advances.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.