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Abstract MIP-049: ATR–DEPENDENT REGULATION OF THE OVARIAN CANCER PROTEIN PALB2 AT DNA DOUBLE–STRAND BREAKS

2017· article· en· W2624138802 on OpenAlexaff
Rémi Buisson, Niraj Joshi, Chu Kwen Ho, Amélie Rodrigue, Tzeh Keong Foo, Émilie J.-L. Hardy, Wilhelm Haas, Bing Xia, Jean‐Yves Masson, Lee Zou

Bibliographic record

VenueClinical Cancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPALB2RAD51Homologous recombinationDNA repairBRCA2 ProteinDNA damageBiologyCancer researchOvarian cancerGeneticsCell biologyDNACancerMutationGermline mutationGene

Abstract

fetched live from OpenAlex

Abstract Cancer is a constant threat to humans since one out of three individuals will develop cancer during their lifetime. It has become increasingly clear that tumor formation can be triggered by mutations in enzymes involved in the surveillance of genome integrity, such as BRCA1, BRCA2 and PALB2. BRCA1, BRCA2 and PALB2 are essential players in double–strand break repair by homologous recombination and have been associated with a heightened lifetime risk for ovarian cancer development. Cancer cells with BRCA1/2 and PALB2 deficiency are extremely sensitive to inhibitors of the DNA repair protein PARP, which have recently emerged as promising anti–cancer drugs. However, mutations in BRCA1/2 and PALB2 account only for around 15–20 % of ovarian cancers overall. Developing new strategies to specifically target ovarian cancer is still presenting a major challenge. During homologous recombination, PALB2 links BRCA1 and BRCA2 to promote RAD51 filament formation at DNA double–strand breaks repair. PALB2 interacts directly with BRCA1 via its N–terminal coiled–coil domain and with BRCA2 via its C–terminal WD40 domain. After DNA damage, PALB2–BRCA1 interaction is enhanced to promote PALB2, BRCA2 and RAD51 localization to DNA double–strand breaks. However, how DNA damage promotes the interaction between PALB2 and BRCA1 is still not understood. In this study, we found that the phosphatidylinositol 3–kinase–like proteins kinase ATR is essential to promote PALB2 and RAD51 to DNA double–strand breaks by enhancing the interaction between PALB2 and BRCA1. We identified two functions of ATR important to enhance PALB2–BRCA1 interaction. First, ATR directly phosphorylates PALB2 on serine 59 after DNA damage. Secondly after DNA double–strand breaks resection, ATR down–regulates CDKs activity leading to the decrease of serine 64 phosphorylation on PALB2. Together, these dual events lead to a direct enhancement of the interaction between PALB2 and BRCA1. Furthermore, we generated PALB2 mutants mimicking the active and inactive state of PALB2. We showed that PALB2 phospho–mutants that recapitulated the active state of PALB2 are able to bypass the absence of ATR activity in cells while mutants that mimic the inactive state of PALB2 showed a defect even in presence of active ATR. These results explain for the first time why ATR is essential to promote DNA double–strand break repair by homologous recombination. My results suggest that that ovarian cancer cells that do not carry BRCA1/2 or PALB2 mutations may be rendered “BRCA–like” by treatment with ATR inhibitor, making them susceptible to treatments with PARPi and others DNA damaging drugs. Citation Format: Rémi Buisson, Niraj Joshi, Chu Kwen Ho, Amélie Rodrigue, Tzeh Keong Foo, Emilie Hardy, Wilhelm Haas, Bing Xia, Jean–Yves Masson and Lee Zou. ATR–DEPENDENT REGULATION OF THE OVARIAN CANCER PROTEIN PALB2 AT DNA DOUBLE–STRAND BREAKS [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr MIP-049.

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 score0.005
Threshold uncertainty score0.017

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.141
GPT teacher head0.469
Teacher spread0.328 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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