Today we would like to highlight three interesting studies that have successfully translated proteome-wide analysis into uncovering mode of action of a potential cancer drug, inflammatory signature associated with type 1 diabetes (T1D), and transcription factors involved in the development of B-cell lymphocytes.
1. Researchers from IOR Institute of Oncology Research in Bellinzona, PIQUR Therapeutics in Basel, and their collaborators characterized the in vitro and in vivo activity and the mechanism of action of a novel oral PI3K/mTOR inhibitor in preclinical lymphoma models. Among other experiments, Biognosys’ discovery proteomics services were used to determine protein phosphorylation changes in cells after the treatment with the inhibitor. The study is published in Clinical Cancer Research titled “PQR309 is a novel dual PI3K/mTOR inhibitor with pre-clinical antitumor activity in lymphomas as a single agent and in combination therapy”.
2. The group of Dr. Stefanie Hauck from Helmholtz Zentrum Munich and German Center for Diabetes Research performed an in-depth proteomic profiling of peripheral CD4+ T cells in a pediatric cohort in order to identify cellular signatures associated with the onset of the autoimmune disease type 1 diabetes (T1D). Using deep proteome profiling with LC-MS/MS data-independent acquisition (DIA) and Biognosys’ Spectronaut software for DIA data analysis, they identified nearly 6,000 proteins and revealed a specific inflammatory signature in patients with T1D. The study is published in the Journal of Proteome Research titled “The proteomic landscape of patient-derived CD4+ T cells in recent-onset type 1 diabetes”.
3. The group of Dr. Gerhard Mittler from the Max Planck Institute of Immunobiology and Epigenetics employed various mass spectrometry based workflows such as data independent acquisition (DIA), data-dependent acquisition (DDA), as well as multiple- and parallel- reaction monitoring (MRM and PRM) to study the transcription factors associated with the development of B-cell lymphocytes. Transcription factors are low abundant proteins, notoriously difficult to quantify with mass spectrometry. According to the authors, it is the first time that DIA workflow has been reported for proteomic studies looking specifically into transcription factors. The study is published in the Journal of Proteome Research titled “A comprehensive Proteomic Investigation of Ebf1 Heterozygosity in pro-B lymphocytes utilizing Data Independent Acquisition (DIA)”.