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Record W4414754323 · doi:10.1186/s11658-025-00785-9

RSL3 promotes PARP1 apoptotic functions by distinct mechanisms during ferroptosis

2025· article· en· W4414754323 on OpenAlexfundno aff
Dejian Chen, Fei Xie, Yimei Mo, Qin Du, Zheng Binjiao, Lingyan Chen

Bibliographic record

VenueCellular & Molecular Biology Letters · 2025
Typearticle
Languageen
FieldMedicine
TopicFerroptosis and cancer prognosis
Canadian institutionsnot available
FundersMedical Science and Technology Project of Zhejiang ProvinceWenzhou Medical UniversityScience and Technology Plan Project of Wenzhou, ChinaUniversity of South ChinaUniversity of AlbertaGuangzhou Medical University
KeywordsApoptosisCrosstalkPARP1Programmed cell deathDNA damageCell cycle

Abstract

fetched live from OpenAlex

The classical ferroptosis activator RSL3 targets enzymes with nucleophilic active sites, primarily acting on glutathione peroxidase 4 (GPX4) to trigger ferroptosis. Recent studies identify RSL3 as a potential pro-apoptotic agent. However, the mechanism by which RSL3 induces apoptosis during ferroptosis remains elusive. Poly(ADP-ribose) polymerase (PARP1) determines cell fate in response to DNA damage, where its loss or cleavage by activated caspase-3 induces apoptosis to attenuate tumor progression. We elucidate a novel mechanism underlying PARP1 regulation, encompassing both its caspase-dependent cleavage and full-length depletion during RSL3-mediated ferroptosis-apoptosis crosstalk. To investigate the role of RSL3 during ferroptosis, we treated several cancer cells of different histological types with varying doses of RSL3 to induce apoptosis. The regulatory proteins of PARP1 were analyzed using real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot analysis. The N6-methyladenosine (m6A) modification level of PARP1 was determined by m6A RNA immunoprecipitation (MeRIP)-qPCR analysis. Additionally, an RNA immunoprecipitation (RIP)-qPCR assay was performed to identify the target protein of the m6A site of PARP1. Furthermore, we established a mouse xenograft model of PARP inhibitor (PARPi)-resistant cells to analyze the effect of RSL3 on PARPi-resistant tumor growth. RSL3 triggers two parallel apoptotic pathways via increasing reactive oxygen species (ROS) production during ferroptosis: (1) caspase-dependent PARP1 cleavage and (2) DNA damage-dependent apoptosis resulting from reduced full-length PARP1. The latter occurs through inhibition of METTL3-mediated m6A modification and subsequent suppression of PARP1 translation. Moreover, we found that RSL3 retains pro-apoptotic functions in PARPi-resistant cells and effectively inhibits PARPi-resistant xenograft tumor growth in vivo. RSL3 orchestrates ferroptosis-apoptosis crosstalk via PARP1, demonstrating therapeutic potential against tumorigenesis, particularly in PARPi-resistant malignancies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.239
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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