Multiomics Biomarkers for Differential Diagnosis of Pleural Effusion: Integration of Proteomic Markers and Single-Cell Transcriptomics

<h4>Background</h4>Differential diagnosis of pleural effusion remains challenging despite medical thoracoscopy (MT). We investigated whether integrating proteomic biomarkers with single-cell transcriptomics and genomic mutation profiling could improve diagnostic accuracy and reveal mechanistic insights.<h4>Methods</h4>We prospectively enrolled 564 patients with pleural effusion undergoing medical thoracoscopy. Pleural fluid biomarkers (adenosine deaminase, carcinoembryonic antigen, cytokeratin-19 fragment, neuron-specific enolase) were measured. Single-cell RNA sequencing profiled immune landscapes across disease etiologies. Driver mutation profiling was performed on malignant pleural effusion samples using targeted next-generation sequencing encompassing 15 cancer-related genes. Diagnostic performance was evaluated against histopathological diagnosis.<h4>Results</h4>Final diagnoses included inflammatory PE (<i>n</i> = 95, 16.8%), tuberculous PE (<i>n</i> = 299, 53.0%), and malignant PE (<i>n</i> = 170, 30.1%). For tuberculous PE, ADA achieved AUC 0.916 (sensitivity 83.3% and specificity 89.4%). For malignant PE, combined CEA/CYFRA21-1 achieved AUC 0.957 (sensitivity 98.2% and specificity 98.7%). Single-cell analysis revealed distinct immune signatures: Tuberculous PE showed M1 macrophage polarization (M1/M2 ratio 9.48) strongly correlating with ADA levels (rho = 0.68, <i>p</i> < 0.001), whereas malignant PE exhibited immunosuppressive features with elevated M2 macrophages and reduced NK cells. Mutation profiling of malignant PE revealed EGFR (46.5%), TP53 (34.7%), and PIK3CA (8.2%) as the most frequently mutated genes. EGFR-mutant tumors exhibited significantly higher CEA levels (<i>p</i> = 0.033) and more immunosuppressive microenvironments with increased M2 macrophages (<i>p</i> < 0.001) and decreased CD8+ T cells (<i>p</i> < 0.001). The sequential multibiomarker algorithm achieved 96.5% sensitivity and 98.7% specificity for malignant PE detection, with 85.3% overall three-way classification accuracy.<h4>Conclusions</h4>Multiomics integration combining proteomic biomarkers with single-cell immune profiling and genomic mutation characterization achieves high diagnostic accuracy for pleural effusion while revealing disease-specific immune mechanisms and mutation-driven therapeutic opportunities.