Multi-omics protein signaling networks identify sex-specific therapeutic candidates in lung adenocarcinoma

Background: Lung adenocarcinoma shows distinct differences between males and females in incidence, prognosis, and treatment response, suggesting unique molecular mechanisms that remain underexplored. This study aims to identify sex-specific molecular signatures and therapeutic targets in lung adenocarcinoma using multi-omics approaches to inform personalized treatment strategies. Methods: We conducted an integrative analysis of transcriptomic and proteomic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and The Cancer Genome Atlas (TCGA) datasets, comparing male and female lung adenocarcinoma profiles. Transcription factor activity was assessed using TIGER on gene expression data, while kinase activity was evaluated with PTM-SEA on proteomic data. These results were combined to build a kinase-transcription factor signaling network. Potential sex-specific drugs were identified using the PRISM drug screening database. Results: The analysis revealed significant sex-based differences in transcription factor and kinase activity. Notably, NR3C1, AR, and AURKA exhibited sex-biased expression and activity. The constructed signaling network highlighted druggable pathways linked to cancer-related processes, with distinct profiles in males and females. PRISM screening identified glucocorticoid receptor agonists and aurora kinase inhibitors as promising sex-specific therapeutic candidates. Conclusions: Our findings underscore the importance of considering sex differences in lung adenocarcinoma molecular profiles. The integration of transcriptomic and proteomic data reveals sex-specific pathways and potential therapies, paving the way for personalized treatment approaches tailored to male and female patients.