Proteomic characterization of head and neck paraganglioma and its molecular classification

Background Head and neck paragangliomas (HNPGLs) are rare neuroendocrine tumors that pose significant challenges in both diagnosis and treatment. The pathogenic mechanism remains unclear, and there is no proteomic analysis-based molecular classification. Therefore, gaining a deeper understanding of this disease from the protein level is crucial because proteins play a fundamental role in the occurrence and development of tumors. Methods We collected 44 tumor samples from patients diagnosed with HNPGL. The adrenal paraganglioma tissue ( N = 46) was used as the disease control group and the chorda tympani nerves ( N = 18) were used as the control group. High-pH reversed-phase liquid chromatography and liquid chromatography with tandem mass spectrometry analyses were used to build an integrated protein database of tumor samples. We then obtained two sets of differentially expressed proteins between the tumor group and the control group to identify the unique proteomic signatures of HNPGLs. Ingenuity pathway analysis annotations were used to perform the functional analysis. Subsequently, we developed a clinically relevant molecular classification for HNPGLs that connected the clinical characteristics with meaningful proteins and pathways to explain the varied clinical manifestations. Results We identified 6,640 proteins in the HNPGL group, and 314 differentially expressed proteins unique to HNPGL were discovered via inter-group comparison. We identified two HNPGL subgroups that significantly differed in clinical manifestation and proteomic characteristics. On the basis of the proteomic results, we proposed a pathogenic mechanism underlying HNPGL. Conclusion We conducted a comprehensive analysis of the molecular mechanisms of HNPGL to build, for the first time, a clinically relevant molecular classification. By focusing on differential proteomic analyses between different types of paragangliomas, we were able to obtain a comprehensive description of the proteomic characteristics of HNPGL, which will be valuable for the search for significant biomarkers as a new treatment method for HNPGL.