Abstract
Background: aryngeal squamous cell carcinoma (LSCC) is characterized by complex interactions among systemic inflammation, immune dysregulation, and extracellular matrix remodeling. Circulating biomarkers reflecting these biological processes may provide valuable tools for disease detection and stratification; however, their integrated diagnostic value in primary LSCC remains insufficiently defined.
Methods: We conducted a case–control study including 50 treatment-naïve LSCC patients and 50 healthy controls. Levels of YKL-40, soluble urokinase plasminogen activator receptor (suPAR) and matrix metalloproteinase-9 (MMP-9) in serum were quantified using ELISA. Systemic inflammation was evaluated via the CRP/albumin ratio and neutrophil-to-lymphocyte ratio (NLR). Receiver operating characteristic (ROC) curves assessed the diagnostic performance of individual and combined biomarkers, and associations with tumor stage were analyzed according to the AJCC 8th edition.
Results: LSCC patients exhibited significantly higher serum levels of YKL-40 (112.6 ± 28.4 vs. 54.3 ± 15.7 ng/mL), suPAR (4.32 ± 0.98 vs. 2.15 ± 0.61 ng/mL), and MMP-9 (386.5 ± 82.3 vs. 201.7 ± 56.9 ng/mL), along with increased CRP/Alb ratio (0.186 ± 0.072 vs. 0.062 ± 0.028) and NLR (3.21 ± 1.04 vs. 1.68 ± 0.52) (all P < 0.001), compared to healthy controls. ROC analysis demonstrated good diagnostic accuracy for individual biomarkers (AUC values 0.74 to 0.85), while MMP-9 showed the highest individual performance (AUC = 0.85). An integrated multivariate model combining YKL-40, suPAR, MMP-9, CRP/Alb ratio, and NLR achieved superior diagnostic accuracy (AUC = 0.92), with 88.0% sensitivity and 90.0% specificity. Furthermore, advanced-stage patients had higher levels of YKL-40, suPAR, and MMP-9 than early-stage patients (P < 0.001), indicating a close association between biomarker expression and tumor progression.
Conclusions: An integrated panel of inflammation–immune–matrix remodeling biomarkers is markedly dysregulated in primary LSCC and demonstrates strong diagnostic and stage-stratification value. The combined biomarker model outperforms individual markers, supporting its utility in clinical evaluation and risk assessment.
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