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Abstract B005: Regulation of replication-induced PARP1/PARP2 activation by base excision repair: Implications for PARP and PARG inhibitor resistance

2024· article· en· W4399505374 on OpenAlexaboutno aff
Md Ibrahim, Md Maruf Khan, Wynand P. Roos, Rasha Q. Al-Rahaleh, Faisal Hayat, Marie E. Migaud, Robert W. Sobol

Bibliographic record

VenueMolecular Cancer Therapeutics · 2024
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsnot available
Fundersnot available
KeywordsXRCC1PARP1Base excision repairPARP inhibitorPoly ADP ribose polymeraseCancer researchDNA repairDNA damageMolecular biologyPolymeraseBiologyChemistryDNAGenetics

Abstract

fetched live from OpenAlex

Abstract Acquired poly (ADP-ribose) polymerases (PARP)-inhibitor (PARPi) and/or poly (ADP-ribose) glycohydrolase (PARG)-inhibitor (PARGi) resistance in BRCA1/2-defective tumors is common, emphasizing the need for identifying new targets. Protein poly ADP-ribosylation (PARylation) is a posttranslational modification of proteins catalyzed by PARP to form poly-(APD-ribose) (PAR) chains on itself and chromatin-associated proteins in response to DNA damage. Our study reveals that PARylation occurs in a replication-, PARP1-, and PARP2-dependent manner even in undamaged cells. Using proximity labeling, specifically Split-TurboID, we found that replication-dependent PARylation recruits the base excision repair (BER) factors XRCC1, POLB, APTX, and LIG3. These factors, in turn, suppress further PARylation. The BER factors XRCC1, POLB, APTX, or LIG3 promote PARPi and PARGi resistance as loss of these replication-associated BER (R-BER) factors re-sensitizes cancer cells to these inhibitors. Of interest, BRCA1 and BRCA2 localize with R-BER factors in undamaged cells. Lastly, XRCC1, POLB, APTX, and LIG3 depletion activate the S-phase checkpoint kinase CHK1, and targeting either this kinase or ATR under these conditions overcomes PARGi resistance in glioblastoma and ovarian cancer cells. In conclusion, our data highlight the crucial role of R-BER in protecting the cell during S-phase and propose a potential intervention strategy for resistant tumors. Citation Format: Md Ibrahim, Md Maruf Khan, Wynand P. Roos, Rasha Q. Al-Rahaleh, Faisal Hayat, Marie E. Migaud, Robert W. Sobol. Regulation of replication-induced PARP1/PARP2 activation by base excision repair: Implications for PARP and PARG inhibitor resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B005.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

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)0.0110.002

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 head0.050
GPT teacher head0.360
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2024
Admission routes1
Has abstractyes

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