Speaker: 赵洋研究员，中国计量科学研究院

Title: Proteomics Data Quality Control and Deep Analysis for Precision Oncology

Language: Chinese

Time & Venue: 2025.12.23 10:00 N224

Abstract: Proteomics is becoming an essential foundation for precision oncology, but its clinical use is still limited by challenges in data quality, reproducibility, and consistency across platforms. Overcoming these obstacles requires not only new technologies but also standardized systems that ensure results are both reliable and easy to interpret. In this presentation, I will first introduce recent progress from my laboratory in proteomics data quality control and advanced analysis methods. We have developed robust standards for proteomic measurements that allow accurate alignment and reproducible assessment across different platforms. At the same time, we created computational tools for evaluating data quality and performing in-depth analysis, which together provide a strong foundation for clinically meaningful research. Building on this foundation, I will then present two examples of translational applications. First, by combining proteomics, glycoproteomics, transcriptomics, and genomics, we systematically studied brain metastases from lung adenocarcinoma. This comprehensive approach revealed strong differences both within and between tumors, uncovered new treatment opportunities, and defined molecular subtypes that may guide personalized therapy. Second, we built an AI-powered multi-omics platform for hepatocellular carcinoma (HCC) liver transplantation. By integrating tissue imaging, proteogenomic features, and deep learning, this framework enables accurate prediction of recurrence after transplantation, addressing a long-standing clinical challenge in liver cancer care.

Together, these advances show how data quality assurance, multi-omics integration, and artificial intelligence can work together to move proteomics from the lab to the clinic, improving patient outcomes in the era of precision medicine.