Anterior gradient 2 (AGR2) is an endoplasmic reticulum (ER)-resident protein disulfide isomerase (PDI) known to be overexpressed in many human epithelial cancers and is involved in cell migration, cellular transformation, angiogenesis, and metastasis. This protein inhibits the activity of the tumor suppressor p53, and its expression levels can be used to predict cancer patient outcome. However, the precise network of AGR2-interacting partners and clients remains to be fully characterized. Herein, we used label-free quantification and also stable isotope labeling with amino acids in cell culture-based LC-MS/MS analyses to identify proteins interacting with AGR2. Functional annotation confirmed that AGR2 and its interaction partners are associated with processes in the ER that maintain intracellular metabolic homeostasis and participate in the unfolded protein response, including those associated with changes in cellular metabolism, energy, and redox states in response to ER stress. As a proof of concept, the interaction between AGR2 and PDIA3, another ER-resident PDI, was studied in more detail. Pathway analysis revealed that AGR2 and PDIA3 play roles in protein folding in ER, including post-translational modification and in cellular response to stress. We confirmed the AGR2-PDIA3 complex formation in cancer cells, which was enhanced in response to ER stress. Accordingly, molecular docking characterized potential quaternary structure of this complex; however, it remains to be elucidated whether AGR2 rather contributes to PDIA3 maturation in ER, the complex directly acts in cellular signaling, or mediates AGR2 secretion. Our study provides a comprehensive insight into the protein-protein interaction network of AGR2 by identifying functionally relevant proteins and related cellular and biochemical pathways associated with the role of AGR2 in cancer cells.

• Keywords
• anterior gradient protein 2, mass spectrometry, protein disulfide isomerase, protein–protein interactions, secretory pathway,
• MeSH
• Chromatography, Liquid MeSH
• Humans MeSH
• Protein Interaction Maps MeSH
• Mucoproteins * metabolism   MeSH
• Neoplasms * MeSH
• Oncogene Proteins * metabolism   MeSH
• Protein Disulfide-Isomerases * MeSH
• Molecular Docking Simulation MeSH
• Tandem Mass Spectrometry MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• AGR2 protein, human MeSH Browser
• Mucoproteins * MeSH
• Oncogene Proteins * MeSH
• Protein Disulfide-Isomerases * MeSH

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.

• Keywords
• SWATH-MS, breast cancer, data independent acquisition, proteomics, tissue, transcriptomics, tumor classification,
• MeSH
• Phosphoric Monoester Hydrolases genetics   metabolism   MeSH
• Humans MeSH
• Breast Neoplasms classification   metabolism   pathology   MeSH
• CDC2 Protein Kinase genetics   metabolism   MeSH
• Proteome analysis   metabolism   MeSH
• Proteomics methods   MeSH
• Receptor, ErbB-2 genetics   metabolism   MeSH
• Receptors, Estrogen metabolism   MeSH
• High-Throughput Screening Assays MeSH
• Tandem Mass Spectrometry methods   MeSH
• Check Tag
• Humans MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• CDK1 protein, human MeSH Browser
• ERBB2 protein, human MeSH Browser
• Phosphoric Monoester Hydrolases MeSH
• phosphatidylinositol-3,4-bisphosphate 4-phosphatase MeSH Browser
• CDC2 Protein Kinase MeSH
• Proteome MeSH
• Receptor, ErbB-2 MeSH
• Receptors, Estrogen MeSH