Junior Research Group completes SMART-CARE

With his skills in biomedical data science and experience in collaborative studies, Dr. Lu leads a junior group sitting at the interface between the experimental, clinical and computational teams in SMART-CARE. The junior group aims to develop new computational methods for the robust and sensitive mining of primary mass spectrometry data, as well as the efficient integrating of mass spectrometry data with other omics and clinical data, which will serve as a solid foundation for patient stratification and biomarker discovery. Thereby, the group plays a central role to achieve SMART-CARE’s aims to establish stable mass spectrometry-based systems medicine workflows that can be used for biomarker discovery, patient stratification, or adjustment of treatment decisions.

Dr. Junyan Lu’s research focuses on the design and application of statistical and machine learning methods for the analysis and integration of large-scale omics data, including proteomics, metabolomics, genomics, transcriptomics, epigenomics, and ex vivo drug screening data, with the aims of identifying novel biomarkers for cancer patient stratification. During the past six years as a postdoc and later as research staff (machine learning expert) at European Molecular Biology Laboratory, Dr. Lu has established extensive collaborations with physician-scientists and experimental biologists at the National Center for Tumor Diseases, Heidelberg University Hospital, the Chemical Biology Core Facility at EMBL, the University of Erlangen and the University Hospital Zurich. In varying team constellations, he has assumed the role of lead bioinformatics/data science expert.

In one of those collaborations, Dr. Lu developed a computational workflow for processing, benchmarking, quality control, and visualization of mass spectrometry proteomics data of primary tumor samples using different platforms. He performed systematic analyses of the proteomic data with other omics data, in order to characterize the proteomic landscape and identify protein-based markers for prognosis and drug response in chronic lymphocytic leukemia (CLL) (Meier-Abt and Lu et al., Blood, 2021). Dr. Lu also implemented data analytical approaches and accompanying software for the analysis of high-throughput drug perturbation data and applied multi-omics integration methods to understand the pathway changes that underlie the heterogeneous drug response and disease outcomes in blood cancer patients (Dietrich, Oleś, Lu et al., J Clin Invest, 2018; Lu and Cannizzaro et al., Nature Cancer, 2021). This work led to the identification of a novel RNA-expression-based biomarker for stratifying patients with CLL, which has promising potential for clinical translation.

Dr. Lu stresses out “SMART-CARE is really unique in its way as it brings so many talented teams from the fields of experimental mass spectrometry, clinical research, computational biology and data science. I am very excited about the things we can achieve through this collaboration. I believe our research outputs will not only enrich the scientific community but also benefit a large number of cancer patients.”