Lisha Wang, Jing Chen, Lidan Xing, Chunling Wang, Jiajia Liu
this study demonstrates that NSF-based multidimensional analysis integrating PGM-based GPC3 protein detection and Septin9/RASSF1A methylation profiling provides substantial complementary diagnostic value to conventional pathology. The combined approach reduces missed diagnosis rates and offers objective risk stratification for patients with equivocal histological findings, presenting a promising strategy for precision diagnosis of liver cancer.
BACKGROUND: liver cancer remains a leading cause of cancer mortality worldwide, with many patients diagnosed at advanced stages due to limitations in current diagnostic methods. Morphological pathological diagnosis of liver biopsy samples often suffers from insufficient sensitivity, particularly in distinguishing malignant lesions from benign conditions with atypical cellular changes. There is a critical need for objective, precise biomarker detection methods to supplement traditional pathology and reduce missed diagnosis rates.
METHODS: this study developed and validated a novel multidimensional diagnostic approach utilizing needle sheath flushing solution (NSF) obtained after ultrasound-guided liver puncture. We established a personal glucose meter (PGM)-based Glypican-3 (GPC3) protein detection system using carboxylated magnetic nanomaterials. Simultaneously, Septin9 and RASSF1A gene methylation was analyzed in shed cells from the same NSF samples. Detection thresholds were determined through stratified randomization and ROC curve analysis. The diagnostic performance of individual and combined methods was evaluated against final clinical diagnosis as the gold standard.
RESULTS: a total of 312 patients were enrolled, comprising 185 tumor cases and 127 benign disease controls. The PGM-based GPC3 detection achieved 83.2% sensitivity and 81.1% specificity (AUC = 0.8217). Septin9 and RASSF1A methylation analysis yielded sensitivities of 72.4% and 47.0%, respectively, with combined methylation detection reaching 81.1% sensitivity and 87.4% specificity (AUC = 0.8424). The integrated strategy combining GPC3, gene methylation, and morphological pathology outperformed all single methods, achieving an AUC of 0.8846, 93.0% sensitivity, and 91.7% negative predictive value. For 68 patients with indeterminate atypical cell pathology, GPC3 and/or methylation positivity was associated with 2.82-fold higher risk of malignancy (P < 0.05).
CONCLUSIONS: this study demonstrates that NSF-based multidimensional analysis integrating PGM-based GPC3 protein detection and Septin9/RASSF1A methylation profiling provides substantial complementary diagnostic value to conventional pathology. The combined approach reduces missed diagnosis rates and offers objective risk stratification for patients with equivocal histological findings, presenting a promising strategy for precision diagnosis of liver cancer.