Proteomic-based stemness score measures oncogenic dedifferentiation and enables the identification of druggable targets.

基于蛋白质组学的干性评分衡量致癌去分化,并能够识别可成药靶点

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作者:Kołodziejczak-Guglas Iga, Simões Renan L S, de Souza Santos Emerson, Demicco Elizabeth G, Lazcano Segura Rossana N, Ma Weiping, Wang Pei, Geffen Yifat, Storrs Erik, Petralia Francesca, Colaprico Antonio, da Veiga Leprevost Felipe, Pugliese Pietro, Ceccarelli Michele, Noushmehr Houtan, Nesvizhskii Alexey I, Kamińska Bożena, Priebe Waldemar, Lubiński Jan, Zhang Bing, Lazar Alexander J, Kurzawa Paweł, Mesri Mehdi, Robles Ana I, Ding Li, Malta Tathiane M, Wiznerowicz Maciej
Cancer progression and therapeutic resistance are closely linked to a stemness phenotype. Here, we introduce a protein-expression-based stemness index (PROTsi) to evaluate oncogenic dedifferentiation in relation to histopathology, molecular features, and clinical outcomes. Utilizing datasets from the Clinical Proteomic Tumor Analysis Consortium across 11 tumor types, we validate PROTsi's effectiveness in accurately quantifying stem-like features. Through integration of PROTsi with multi-omics, including protein post-translational modifications, we identify molecular features associated with stemness and proteins that act as active nodes within transcriptional networks, driving tumor aggressiveness. Proteins highly correlated with stemness were identified as potential drug targets, both shared and tumor specific. These stemness-associated proteins demonstrate predictive value for clinical outcomes, as confirmed by immunohistochemistry in multiple samples. The findings emphasize PROTsi's efficacy as a valuable tool for selecting predictive protein targets, a crucial step in customizing anti-cancer therapy and advancing the clinical development of cures for cancer patients.

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