Summary Accurate classification of breast tumors is vital for patient management decisions and enables more precise cancer treatment. Here, we present a quantitative proteotyping approach based on sequential windowed acquisition of all theoretical fragment ion spectra (SWATH) mass spectrometry and establish key proteins for breast tumor classification. The study is based on 96 tissue samples representing five conventional breast cancer subtypes. SWATH proteotype patterns largely recapitulate these subtypes; however, they also reveal varying heterogeneity within the conventional subtypes, with triple negative tumors being the most heterogeneous. Proteins that contribute most strongly to the proteotype-based classification include INPP4B, CDK1, and ERBB2 and are associated with estrogen receptor (ER) status, tumor grade status, and HER2 status. Although these three key proteins exhibit high levels of correlation with transcript levels (R > 0.67), general correlation did not exceed R = 0.29, indicating the value of protein-level measurements of disease-regulated genes. Overall, this study highlights how cancer tissue proteotyping can lead to more accurate patient stratification.
Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post‐translational turnover, we devised a strategy combining pulse stable isotope‐labeled amino acids in cells (pSILAC), data‐independent acquisition mass spectrometry (DIA‐MS), and a novel data analysis framework that resolves protein degradation rate on the level of mRNA alternative splicing isoforms and isoform groups. We demonstrated our approach by the genome‐wide correlation analysis between mRNA amounts and protein degradation across different strains of HeLa cells that harbor a high grade of gene dosage variation. The dataset revealed that specific biological processes, cellular organelles, spatial compartments of organelles, and individual protein isoforms of the same genes could have distinctive degradation rate. The protein degradation diversity thus dissects the corresponding buffering or concerting protein turnover control across cancer cell lines. The data further indicate that specific mRNA splicing events such as intron retention significantly impact the protein abundance levels. Our findings support the tight association between transcriptome variability and proteostasis and provide a methodological foundation for studying functional protein degradation.
The three members of the endocrine-fibroblast growth factor (FGF) family, FGF19, 21, and 23 are circulating hormones that regulate critical metabolic processes. FGF23 stimulates the assembly of a signaling complex composed of α-Klotho (KLA) and FGF receptor (FGFR) resulting in kinase activation, regulation of phosphate homeostasis, and vitamin D levels. Here we report that the C-terminal tail of FGF23, a region responsible for KLA binding, contains two tandem repeats, repeat 1 (R1) and repeat 2 (R2) that function as two distinct ligands for KLA. FGF23 variants with a single KLA binding site, FGF23-R1, FGF23-R2, or FGF23-wild type (WT) with both R1 and R2, bind to KLA with similar binding affinity and stimulate FGFR1 activation and MAPK response. R2 is flanked by two cysteines that form a disulfide bridge in FGF23-WT; disulfide bridge formation in FGF23-WT is dispensable for KLA binding and for cell signaling via FGFRs. We show that FGF23-WT stimulates dimerization and activation of a chimeric receptor molecule composed of the extracellular domain of KLA fused to the cytoplasmic domain of FGFR and employ total internal reflection fluorescence microscopy to visualize individual KLA molecules on the cell surface. These experiments demonstrate that FGF23-WT can act as a bivalent ligand of KLA in the cell membrane. Finally, an engineered Fc-R2 protein acts as an FGF23 antagonist offering new pharmacological intervention for treating diseases caused by excessive FGF23 abundance or activity.
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