RESUMO
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.
Assuntos
Neoplasias da Mama/classificação , Proteína Quinase CDC2/metabolismo , Monoéster Fosfórico Hidrolases/metabolismo , Proteoma/análise , Proteômica/métodos , Receptor ErbB-2/metabolismo , Espectrometria de Massas em Tandem/métodos , Neoplasias da Mama/metabolismo , Neoplasias da Mama/patologia , Proteína Quinase CDC2/genética , Feminino , Ensaios de Triagem em Larga Escala , Humanos , Monoéster Fosfórico Hidrolases/genética , Proteoma/metabolismo , Receptor ErbB-2/genética , Receptores de Estrogênio/metabolismoRESUMO
Fibroblast growth factors (FGFs) serve numerous regulatory functions in complex organisms, and their corresponding therapeutic potential is of growing interest to academics and industrial researchers alike. However, applications of these proteins are limited due to their low stability. Here we tackle this problem using a generalizable computer-assisted protein engineering strategy to create a unique modified FGF2 with nine mutations displaying unprecedented stability and uncompromised biological function. The data from the characterization of stabilized FGF2 showed a remarkable prediction potential of in silico methods and provided insight into the unfolding mechanism of the protein. The molecule holds a considerable promise for stem cell research and medical or pharmaceutical applications.
Assuntos
Desenho Assistido por Computador , Fator 2 de Crescimento de Fibroblastos/genética , Fator 2 de Crescimento de Fibroblastos/metabolismo , Engenharia de Proteínas , Estabilidade Proteica , Sequência de Aminoácidos , Animais , Simulação por Computador , Evolução Molecular Direcionada , Células-Tronco Embrionárias/citologia , Células-Tronco Embrionárias/metabolismo , Fator 2 de Crescimento de Fibroblastos/química , Humanos , Mutação Puntual , Dobramento de ProteínaRESUMO
Human pluripotent stem cells (hPSC) require signaling provided by fibroblast growth factor (FGF) receptors. This can be initiated by the recombinant FGF2 ligand supplied exogenously, but hPSC further support their niche by secretion of endogenous FGF2. In this study, we describe a role of tyrosine kinase expressed in hepatocellular carcinoma (TEC) kinase in this process. We show that TEC-mediated FGF2 secretion is essential for hPSC self-renewal, and its lack mediates specific differentiation. Following both short hairpin RNA- and small interfering RNA-mediated TEC knockdown, hPSC secretes less FGF2. This impairs hPSC proliferation that can be rescued by increasing amounts of recombinant FGF2. TEC downregulation further leads to a lower expression of the pluripotency markers, an improved priming towards neuroectodermal lineage, and a failure to develop cardiac mesoderm. Our data thus demonstrate that TEC is yet another regulator of FGF2-mediated hPSC pluripotency and differentiation. Stem Cells 2017;35:2050-2059.