Biomarker Discovery through Single-cell Proteome and Network Model

Our groundbreaking research on "Biomarker Discovery through Single-cell Proteome and Network Model" leverages cutting-edge techniques to unravel disease heterogeneity and progression at the cellular level. By seamlessly integrating advanced technologies such as antibody-based cell sorting, CyTOF mass cytometry, and LC-MS proteomics, we conduct comprehensive multi-dimensional analyses of immune cell subtypes and intracellular proteins, encompassing expression levels, proteoforms, mutations, post-translational modifications, and structural alterations. Utilizing diverse biological models and an extensive array of clinical samples, we generate integrated multi-dimensional proteomic data. Through the application of sophisticated computational methods to this rich dataset, we unveil key mechanisms related to early diagnosis, treatment prognosis, and therapeutic targets, culminating in the discovery of clinically relevant biomarkers. Furthermore, our research extends into the realm of targeted therapy development by simulating the effects of mimic peptides or compounds on critical regulatory nodes within protein-protein interaction networks. This groundbreaking approach paves the way for personalized medicine strategies in cancer treatment and other complex diseases, potentially revolutionizing patient care and outcomes.