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Programming a Ferroptosis‐to‐Apoptosis Transition Landscape Revealed Ferroptosis Biomarkers and Repressors for Cancer Therapy.

Authors :
Vinik, Yaron
Maimon, Avi
Dubey, Vinay
Raj, Harsha
Abramovitch, Ifat
Malitsky, Sergey
Itkin, Maxim
Ma'ayan, Avi
Westermann, Frank
Gottlieb, Eyal
Ruppin, Eytan
Lev, Sima
Source :
Advanced Science. May2024, Vol. 11 Issue 17, p1-21. 21p.
Publication Year :
2024

Abstract

Ferroptosis and apoptosis are key cell‐death pathways implicated in several human diseases including cancer. Ferroptosis is driven by iron‐dependent lipid peroxidation and currently has no characteristic biomarkers or gene signatures. Here a continuous phenotypic gradient between ferroptosis and apoptosis coupled to transcriptomic and metabolomic landscapes is established. The gradual ferroptosis‐to‐apoptosis transcriptomic landscape is used to generate a unique, unbiased transcriptomic predictor, the Gradient Gene Set (GGS), which classified ferroptosis and apoptosis with high accuracy. Further GGS optimization using multiple ferroptotic and apoptotic datasets revealed highly specific ferroptosis biomarkers, which are robustly validated in vitro and in vivo. A subset of the GGS is associated with poor prognosis in breast cancer patients and PDXs and contains different ferroptosis repressors. Depletion of one representative, PDGFA‐assaociated protein 1(PDAP1), is found to suppress basal‐like breast tumor growth in a mouse model. Omics and mechanistic studies revealed that ferroptosis is associated with enhanced lysosomal function, glutaminolysis, and the tricarboxylic acid (TCA) cycle, while its transition into apoptosis is attributed to enhanced endoplasmic reticulum(ER)‐stress and phosphatidylethanolamine (PE)‐to‐phosphatidylcholine (PC) metabolic shift. Collectively, this study highlights molecular mechanisms underlying ferroptosis execution, identified a highly predictive ferroptosis gene signature with prognostic value, ferroptosis versus apoptosis biomarkers, and ferroptosis repressors for breast cancer therapy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21983844
Volume :
11
Issue :
17
Database :
Academic Search Index
Journal :
Advanced Science
Publication Type :
Academic Journal
Accession number :
177113612
Full Text :
https://doi.org/10.1002/advs.202307263