In LC/MS/MS-based bottom-up proteomics, the separation and purification of peptides are crucial steps that significantly impact the identification and quantitation results. Peptide separation is influenced by various factors, necessitating the development of conditions that integrate both liquid chromatography (LC) and mass spectrometry (MS). Additionally, to maximize the utility of retention time information in LC, it is essential to accurately predict retention times under diverse conditions. Moreover, with the recent advancements in ion mobility spectroscopy, the significance of ion mobility data has grown. This paper summarizes the condition-specific separation behavior of phosphorylated peptides in reversed-phase chromatography and trapped ion mobility spectrometry (TIMS) that we have investigated and discusses how these findings can enhance sample preparation and quantitative analysis.

Phosphorylation, one of the post-translational modifications of the protein, confers negative charge and hydrophilicity to specific amino acids, affecting protein function by changing its conformational state, stability, or interactions with other molecules. Protein phosphorylation therefore plays an important role as a regulatory mechanism in a wide variety of biological processes. To accurately understand protein function, phosphoproteomics must not only identify modification sites, but also reveal all the details through quantitative and qualitative analysis of phosphoproteins. In recent years, various analytical strategies have been proposed for analyzing the phosphorylation status of proteins, facilitating the analysis of a very large number of phosphoproteins. Here, powerful analytical techniques for phosphoproteomics based on electrophoresis and mass spectrometry will be introduced, with a focus on ‘Phos-tag’. We believe that these analytical techniques will help accelerate our understanding of protein function involved in biological processes.

Recent cancer research has identified the existence of cancer stem cells (CSCs), which have been highlighted as the root cause of chemotherapeutic resistance and recurrence in cancer. Targeting cancer stem cells and their microenvironment (niche) holds great potential for developing innovative therapeutic strategies. However, there are still challenges due to the lack of easily accessible experimental model cells and insufficient information on CSC proteomics and genomics, as well as specific CSC markers. As a consequence, detailed molecular and functional information on cancer stem cells remains largely missing, making the development of targeted therapies extremely difficult.

To address these challenges, we have successfully established CSCs and their differentiation induction models from various patient tumor tissues/cells. By integrating comparative expression analyses of proteome and mRNA data from these models, we have made it possible to obtain detailed molecular information on cancer stem cells.

This article focuses on malignant glioma stem cells (GSC) as the primary analysis model. It introduces methodologies to understand the molecular network dynamics involved in the maintenance and differentiation-switching of glioma stem cells based on these quantitative molecular data in a comprehensive manner. Additionally, key factors mediating the mutual induction between CSC and cancer cells, as well as specific signals that have been successfully identified in a comprehensive manner as therapeutic targets through these analyses are highlighted.