Mass spectrometry (MS)-based single-cell proteomics (SCP) has become a credible player in the single-cell biology arena. Continuous technical improvements have pushed the boundaries of sensitivity and throughput. However, the computational efforts to support the analysis of these complex data have been missing. Strong batch effects coupled to high proportions of missing values complicate the analysis, causing strong entanglement between biological and technical variability. We propose a simple, yet powerful approach to address this need: linear models. We use linear regression to model and remove undesired technical factors while retaining the biological variability, even in the presence of high proportions of missing values. The key advantage of linear models lies in the interpretability of the results they generate. Inspired by previous research, we streamlined modelling and exploration of the patterns induced by known technical and biological factors. The exploration enables a thorough assessment of the model coefficients, and highlights key factors influencing SCP experiments. Further exploration of the unmodelled variance recovers unknown but biologically relevant patterns in the data, leveraging the power of single-cell proteomics technologies. We successfully applied our approach to a diverse collection of SCP datasets, and could demonstrate that it is also amenable for integrating datasets acquired using different technologies. Our approach represents a turning point for principled SCP data analysis, moving the tension point from how to perform the analysis to result generation and interpretation.
CONFERENCE KEYNOTE SPEAKERS

+ About Laurent Gatto
Laurent is an Associate Professor of Bioinformatics at the de Duve Institute, UCLouvain, in Belgium. His research group focuses on the development and application of statistical learning for the analysis, integration and comprehension of large scale biological data. The development and publication of scientific software is an integral part of the labs work, as reflected by their numerous contributions to the Bioconductor project. Laurent is an avid open and reproducible research advocate, making his research outputs openly available. He is a Software Sustainability Institute fellow, a Data and Software Carpentry instructor and a member of the Bioconductor technical advisory board.
Principled single-cell proteomics data analysis

+ About Gregor Hutter
As a neurosurgeon-scientist, Dr. Hutter witnesses the devastation that malignant brain tumors cause patients and their families first hand. His journey in academic medicine started as a resident in neuropathology, where he had a first glimpse on the complexity of human brain tumors.
Accompanying a friend from initial histopathological diagnosis to his neurological decline and death was deeply influenced his career choice. Dr. Hutter says the desire to help these patients motivates him to conduct basic and translational research, with the ultimate goal of translating research findings into clinical application.
Dr. Hutter established his research group in Basel, Switzerland in 2018 with focussing on developing combinatorial therapeutic approaches that locally target microglia and the adaptive immune system, and directly interfere with the tumor cells.
Novel Innate Immunotherapies Against Glioblastoma
Glioblastoma is an incurable brain tumor with a dire prognosis. Our lab focusses on the immunosuppressive microenvironment that co-evolves during tumorigenesis and plays a key role in determining the failure of current therapies. We have recently identified novel immune-inhibitory checkpoints on myeloid cells such as microglia and tumor-associated macrophages that can be targeted and have translational potential. Further, we are developing CAR T cell strategies that jointly target the tumor and reprogram tumor-associated myeloid cells. I will present preliminary data and a clinical trial outline of our CAR T cell program. Our longterm goal is to improve the quality of life and prognosis of GBM patients using personalized and local treatment strategies.

+ About Jonathan Kipnis
BJC Investigator, Alan A. and Edith L. Wolff Distinguished Professor of Pathology and Immunology.
Jonathan Kipnis is a neuroscientist, immunologist, and professor of pathology and immunology at the Washington University School of Medicine. His lab studies interactions between the immune system and nervous system. He is best known for his lab’s discovery of meningeal lymphatic vessels in humans and mice, which has impacted research on neurodegenerative diseases such as Alzheimer’s disease and multiple sclerosis, neuropsychiatric disorders, such as anxiety, and neurodevelopmental disorders such as autism and Rett syndrome.
(Bio adapted from Wikipedia)
New mechanistic insights into CNS immune privilege
The traditional dogma posited a separation between the immune and nervous systems, an idea referred to as the central nervous system’s immune privilege. Yet, contemporary research has brought to light ingenious adaptations occurring at the borders (meninges and perivascular spaces) of the central nervous system, positioning these as key locations for neuroimmune exchanges. Although both systems generally work in tandem to preserve homeostasis, under unusual conditions, they can form detrimental interactions that result in neurological or psychiatric illnesses. We will delve into recent insights that elucidate the crucial anatomical, cellular, and molecular mechanisms that facilitate neuroimmune interactions at the brain and spinal cord’s borders, as well as the potential impact of these interactions on central nervous system diseases.
