Proteomic\nAnalysis of Tissue Proteins Related to Lateral\nLymph Node Metastasis in Papillary Thyroid Microcarcinoma

Patients with lateral lymph node metastasis (LLNM) may\nexperience\nhigher locoregional recurrence rates and poorer prognoses compared\nto those without LLNM, highlighting the need for effective preoperative\nstratification to reliably assess risk LLNM. In this study, we collected\nPTMC samples from Peking Union Medical College Hospital and employed\ndata-independent acquisition mass spectrometry proteomics technique\nto identify protein profiles in PTMC tissues with and without LLNM.\nPseudo temporal analysis and single sample gene set enrichment analysis\nwere conducted in combination with The Cancer Genome Atlas Thyroid\nCarcinoma for functional coordination analysis and the construction\nof a prediction model based on random forest. Non-negative matrix\nfactorization (NMF) clustering was utilized to classify molecular\nsubtypes of PTMC. Our findings revealed that the differential activation\nof pathways such as MAPK and PI3K was critical in enhancing the lateral\nlymph node metastatic potential of PTMC. We successfully screened\nbiomarkers via machine learning and public databases, creating an\neffective prediction model for metastasis. Additionally, we explored\nthe mechanism of metastasis-associated PTMC subtypes via NMF clustering.\nThese insights into LLNM mechanisms in PTMC may contribute to future\nbiomarker screening and the identification of therapeutic targets.