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An absolute human stemness index associated with oncogenic dedifferentiation
Hailong Zheng1, Kai Song1, Yelin Fu1
1Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150086, China.
Briefings in Bioinformatics
|March 3, 2020
Summary
This study introduces a novel stemness index using relative gene expression orderings (REOs). This robust index accurately evaluates cancer stemness, correlating with prognosis and tumor grade.
Area of Science:
- Cancer biology
- Stem cell research
- Bioinformatics
Background:
- Cancer progression involves acquiring stemness features, crucial for understanding tumor behavior.
- Existing stemness evaluation methods lack intuitive range and are sensitive to technical variations.
- Relative expression orderings (REOs) offer robust gene expression analysis, unaffected by batch effects.
Purpose of the Study:
- To develop and validate an absolute stemness index based on relative expression orderings (REOs).
- To assess the index's performance in evaluating stemness in differentiated cells and cancer tissues.
- To explore the index's correlation with clinical parameters like prognosis and tumor grade.
Main Methods:
- Developed an absolute stemness index utilizing gene pair relative expression orderings (REOs).
- Validated the index against culture time in differentiated stem cells.
- Applied the index to cancer and normal tissue samples to assess differences and intratumor heterogeneity.
Main Results:
- The REO-based stemness index demonstrated higher correlation with stem cell differentiation time compared to previous methods.
- Significant differences in stemness index were observed between cancer and normal tissues, revealing intratumor heterogeneity.
- Higher stemness index values correlated with poorer prognosis and higher histological grade, indicating greater dedifferentiation.
Conclusions:
- The absolute REO-based stemness index provides a robust and intuitive measure of cancer stemness.
- This index effectively differentiates between cancer and normal tissues and captures stemness heterogeneity.
- The stemness index shows potential for assisting tumor grading and has implications for cancer diagnostics and therapeutics.
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