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

  • Clinical Proteomic Tumor Analysis Consortium
  • International Institute for Molecular Oncology
  • Medical University of Warsaw
  • Universidade de São Paulo
  • Mount Sinai Hospital
  • University of Texas MD Anderson Cancer Center
  • Icahn School of Medicine at Mount Sinai
  • Broad Institute
  • Massachusetts General Hospital Cancer Center
  • Washington University St. Louis
  • University of Miami
  • University of Michigan, Ann Arbor
  • University of Sannio
  • Henry Ford Health System
  • Nencki Institute of Experimental Biology of the Polish Academy of Sciences
  • Pomeranian Medical University in Szczecin
  • Baylor College of Medicine
  • Heliodor Swiecicki Clinical Hospital
  • National Institutes of Health

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number100851
JournalCell Genomics
Volume5
Issue number6
DOIs
StatePublished - Jun 11 2025

ASJC Scopus Subject Areas

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Genetics

Keywords

  • biomarkers
  • cancer
  • drug targets
  • kinase activity
  • machine learning
  • mass spectrometry
  • multiomics
  • proteomics
  • stemness
  • tumor plasticity

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