Combining Classic and Novel Neutrophil-Related Biomarkers to Identify Non-Small-Cell Lung Cancer

• Published in: Cancers 2024-01, Vol.16 (3), p.513
• Main Authors: Ren, Yunzhao, Wang, Qinchuan, Xu, Chenyang, Guo, Qian, Dai, Ruoqi, Xu, Xiaohang, Zhang, Yuhao, Wu, Ming, Wu, Xifeng, Tu, Huakang
• Format: Article
• Language: English
• Subjects: Angiogenesis; Biological markers; Biomarkers; Biotechnology industry; Body mass index; Cancer; Carcinoembryonic antigen; CEA (Oncology); Clinical medicine; Consent; Cytokines; Cytotoxicity; Development and progression; Diagnosis; Epidemiology; Ethylenediaminetetraacetic acid; Inflammation; Interleukin 1; Interleukin 1 receptor antagonist; Interleukin 1 receptors; Interleukin 6; Interleukins; Leukocytes (neutrophilic); Lung cancer; Lung cancer, Non-small cell; Lung diseases; Lymphocytes; Medical colleges; Metastasis; Neutrophils; Non-small cell lung carcinoma; Oncology, Experimental; Patients; Plasma; Prediction models; Proteins; Reclassification; Risk factors; Small cell lung carcinoma; Tumorigenesis
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers16030513

Recent studies have revealed that neutrophils play a crucial role in cancer progression. This study aimed to explore the diagnostic value of neutrophil-related biomarkers for non-small-cell lung cancer (NSCLC). We initially assessed the associations between classic neutrophil-related biomarkers (neutrophil-to-lymphocyte ratio (NLR), absolute neutrophil counts (NEU), absolute lymphocyte counts (LYM)) and NSCLC in 3942 cases and 6791 controls. Then, we measured 11 novel neutrophil-related biomarkers via Luminex Assays in 132 cases and 66 controls, individually matching on sex and age (±5 years), and evaluated their associations with NSCLC risk. We also developed the predictive models by sequentially adding variables of interest and assessed model improvement. Interleukin-6 (IL-6) (odds ratio (OR) = 10.687, 95% confidence interval (CI): 3.875, 29.473) and Interleukin 1 Receptor Antagonist (IL-1RA) (OR = 8.113, 95% CI: 3.182, 20.689) shows strong associations with NSCLC risk after adjusting for body mass index, smoking status, NLR, and carcinoembryonic antigen. Adding the two identified biomarkers to the predictive model significantly elevated the model performance from an area under the receiver operating characteristic curve of 0.716 to 0.851 with a net reclassification improvement of 97.73%. IL-6 and IL-1RA were recognized as independent risk factors for NSCLC, improving the predictive performance of the model in identifying disease.