TL;DR: Quantitative proteomics analysis of CSRP3-knockdown versus control pig satellite cells reveals protein expression changes at day 2 of differentiation, elucidating CSRP3's role in modulating pig satellite cell differentiation.
Abstract: To elucidate the mechanism by which CSRP3 modulates pig satellite cell differentiation, quantitative proteomics analysis of CSRP3-knockdown versus control pig satellite cells at day 2 of differentiation was performed. Proteins from pig satellite cells were extracted using RIPA buffer supplemented with PMSF and a protease inhibitor cocktail. Cell proteins were solubilized in 7M urea and 2M thiourea, and protein concentrations were quantified using the Bradford Protein Assay Kit. Proteins were digested following the FASP method. The resulting peptides were analyzed using a Q-Exactive high-resolution mass spectrometer coupled with a Nano-Acquity nano HPLC system. Data processing for peak picking and alignment was performed using Pyogenesis QI for Proteomics software (build 2.0, Nonlinear Dynamics, Newcastle, UK).
TL;DR: A machine learning-based classifier accurately predicts the origin of primary and metastatic squamous cell carcinomas from various sites, achieving high validation accuracy and identifying a simplified five-marker panel for routine screening, with implications for SCCUP diagnosis and metastasis.
Abstract: Squamous cell carcinoma (SCC) occurs across multiple organs with highly similar histology, making the diagnosis of SCC of unknown primary (SCCUP) particularly challenging. To address this, we established a machine learning–based 39-protein biomarker classifier (39PBC) trained on proteomic profiles from 387 SCC samples collected at seven tertiary hospitals. The classifier accurately predicted the origin of primary and metastatic SCCs from cervical, esophageal, lung, nasopharyngeal, and head and neck sites, with validation in internal (n = 324) and external (n = 63) cohorts yielding AUCs of 0.924–0.961 and 0.971 and accuracies above 87%. Immunohistochemistry of 509 cases further identified a simplified five-marker panel (four robust site-specific markers CCDC6, LGALS7, LGALS9, and P16, together with EBER) suitable for routine screening. Importantly, 39PBC demonstrated reliable performance in real-world SCCUP and dual-primary cases. Proteomic profiling also uncovered distinct prognostic and molecular landscapes, implicating metabolic activation as a driver of progression and immune modulation as a site-specific feature. Together, these findings establish a clinically applicable workflow that integrates high-resolution proteomics with practical IHC validation, offering a public resource to improve SCCUP diagnosis, enable cost-effective clinical translation, and provide mechanistic insights into SCC metastasis.
TL;DR: This study identifies Ifi44-interacting proteins, including Ly6E, which coordinates interactions with CD109, CD59, and Siglec1, revealing a mechanism of immune cell recruitment through Ifi44 and Ly6E interactions.
Abstract: We used proteomics to identify Ifi44-interacting proteins and elucidated a mechanism of function for an Ifi family receptor. We describe here a mechanism related to immune cell recruitment through Ly6E which appears to be a major function of Ifi44.
TL;DR: Quantitative proteomics analysis of CSRP3-knockdown versus control pig satellite cells reveals protein expression changes at day 2 of differentiation, elucidating CSRP3's role in modulating pig satellite cell differentiation.
Abstract: To elucidate the mechanism by which CSRP3 modulates pig satellite cell differentiation, quantitative proteomics analysis of CSRP3-knockdown versus control pig satellite cells at day 2 of differentiation was performed. Proteins from pig satellite cells were extracted using RIPA buffer supplemented with PMSF and a protease inhibitor cocktail. Cell proteins were solubilized in 7M urea and 2M thiourea, and protein concentrations were quantified using the Bradford Protein Assay Kit. Proteins were digested following the FASP method. The resulting peptides were analyzed using a Q-Exactive high-resolution mass spectrometer coupled with a Nano-Acquity nano HPLC system. Data processing for peak picking and alignment was performed using Pyogenesis QI for Proteomics software (build 2.0, Nonlinear Dynamics, Newcastle, UK).
TL;DR: This study identifies Ifi44-interacting proteins, including Ly6E, which coordinates interactions with CD109, CD59, and Siglec1, revealing a mechanism of immune cell recruitment through Ifi44 and Ly6E interactions.
Abstract: We used proteomics to identify Ifi44-interacting proteins and elucidated a mechanism of function for an Ifi family receptor. We describe here a mechanism related to immune cell recruitment through Ly6E which appears to be a major function of Ifi44.