98%
921
2 minutes
20
Non-small cell lung cancer (NSCLC) patients without gene driver mutations receive anti-PD1 treatments either as monotherapy or in combination with chemotherapy based on PD-L1 expression in tumor tissue. Anti-PD1 antibodies target various immune system components, perturbing the balance between immune cells and soluble factors. In this study, we identified the immune signatures of NSCLC patients associated with different clinical outcomes through network analysis. : Twenty-seven metastatic NSCLC patients were assessed at baseline for the levels of circulating CD137 T cells (total, CD4, and CD8) via cytofluorimetry, along with 14 soluble checkpoints and 20 cytokines through Luminex analysis. Hierarchical clustering and connectivity heatmaps were executed, analyzing the response to therapy (R vs. NR), performance status (PS = 0 vs. PS > 0), and overall survival (OS < 3 months vs. OS > 3 months). The clustering of immune checkpoints revealed three groups with a significant differential proportion of six checkpoints between patients with PS = 0 and PS > 0 ( < 0.0001). Furthermore, significant pairwise correlations among immune factors evaluated in R were compared to the lack of significant correlations among the same immune factors in NR patients and vice versa. These comparisons were conducted for patients with PS = 0 vs. PS > 0 and OS < 3 months vs. OS > 3 months. The results indicated that NR with PS > 0 and OS ≤ 3 months exhibited an inflammatory-specific signature compared to the contrasting clinical conditions characterized by a checkpoint molecule-based network ( < 0.05). Identifying various connectivity immune profiles linked to response to therapy, PS, and survival in NSCLC patients represents significant findings that can optimize therapeutic choices.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11939851 | PMC |
http://dx.doi.org/10.3390/cancers17060922 | DOI Listing |
PLoS One
September 2025
Department of Biomedicine, Health and Life Convergence Sciences, BK21 Four, College of Pharmacy, Mokpo National University, Muan, Republic of Korea.
Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer-related deaths, remaining a significant challenge in terms of early detection, effective treatment, and improving patient survival rates. In this study, we investigated the anticancer mechanism of rubiarbonol B (Ru-B) and its derivative 3-O-acetylrubiarbonol B (ARu-B), a pentacyclic terpenoid in gefitinib (GEF)-sensitive and -resistant NSCLC HCC827 cells. Concentration- and time-dependent cytotoxicity was observed for both Ru-B and ARu-B.
View Article and Find Full Text PDFJ Thorac Oncol
July 2025
Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York.
Introduction: TNM staging systems create prognostic categories by anatomic extent of disease. Whether therapeutically important molecular alterations in NSCLC augment the prognostic information of TNM staging is unclear. To study this, we analyzed molecular data from the ninth edition of the lung cancer staging system.
View Article and Find Full Text PDFJ Thorac Oncol
August 2025
Department of Radiation Medicine, Markey Cancer Center, University of Kentucky, Lexington, Kentucky.
Introduction: Cigarette smoking negatively affects lung cancer prognosis. Incorporating smoking history into stage-stratified survival analyses may improve prognostication.
Methods: Using the International Association for the Study of Lung Cancer ninth edition NSCLC database, we evaluated the association between smoking status at diagnosis and overall survival (OS) using Kaplan-Meier plots and multivariate Cox proportional hazard regression models adjusted for age, region, sex, histologic type, performance status, and TNM stage.
Brief Bioinform
August 2025
Department of Respiratory Medicine, The Second Affiliated Hospital of Xi'an Jiaotong University, No. 157, Xiwu Road, Xincheng District, Xi'an 710004, China.
Accurate tumor mutation burden (TMB) quantification is critical for immunotherapy stratification, yet remains challenging due to variability across sequencing platforms, tumor heterogeneity, and variant calling pipelines. Here, we introduce TMBquant, an explainable AI-powered caller designed to optimize TMB estimation through dynamic feature selection, ensemble learning, and automated strategy adaptation. Built upon the H2O AutoML framework, TMBquant integrates variant features, minimizes classification errors, and enhances both accuracy and stability across diverse datasets.
View Article and Find Full Text PDFDrug Dev Res
September 2025
R. C. Patel Institute of Pharmaceutical Education and Research, Shirpur, Maharashtra, India.
Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality, with "epidermal growth factor receptor (EGFR)" mutations playing a pivotal role in tumor progression and carcinogenesis. "Third-generation epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs)," such as Osimertinib, have significantly improved treatment outcomes by overcoming resistance mechanisms like the T790M mutation. However, Osimertinib's clinical application is limited by cardiotoxicity concerns, necessitating safer alternatives.
View Article and Find Full Text PDF