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Abstract A37: Development of screening methods to identify Translesion DNA Synthesis inhibitors

2017· article· en· W2604688580 on OpenAlexaboutno aff
Florencia Villafañez, Alejandra Iris García, María Florencia Pansa, Sofía Carbajosa, José Luís Bocco, Gastón Soria

Bibliographic record

VenueMolecular Cancer Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsProliferating cell nuclear antigenDNA polymerasePolymeraseDNA replicationDNA damageBiologyDNA repairDNAUbiquitinMolecular biologyContext (archaeology)Cell biologyBiochemistryGene

Abstract

fetched live from OpenAlex

Abstract Translesion DNA synthesis (TLS) is a DNA damage tolerance process that employs specialized polymerases to bypass DNA damage during replication. Recent evidence indicates that TLS is a key process that promotes the development of resistance to cancer treatments that induce DNA damage (i.e. Cisplatin). Thus, the inhibition of TLS emerges as a promising strategy for cancer therapy. However, to date, specific chemical inhibitors of TLS are not available. The main goal of our project is to identify specific inhibitors of TLS that can be used as a proof of concept in cancer therapy by developing cell-based assays that explore TLS markers. Our rational is that since TLS polymerases recruitment to sites of DNA damage is a key step for TLS success, we can indirectly monitor TLS efficiency in a given context by studying two key markers of TLS polymerases recruitment: 1) The mono-ubiquitylation of the replication auxiliary factor PCNA and 2) the accumulation of a TLS polymerase into replication foci. We thus developed two screening methods that allow us to promptly identify inhibitors of PCNA ubiquitylation and TLS polymerases recruitment into DNA damage sites. The first marker, PCNA mono-ubiquitylation, is assessed through a western-Blot-based platform where the identification of unmodified PCNA and mono-ubiquitylated PCNA are achieved by two different antibodies coupled to fluorescent infrared detection using a fluorescence scanner. For the second marker, TLS polymerase recruitment to damage sites, we developed stable cell lines expressing TLS polymerases fused to fluorescent proteins and we analyze polymerases recruitment through an imaging-based assay. In this poster we describe the results of a pilot screening using an open source library of kinase inhibitors from GlaxoSmithKline (known as PKIS2), and the early validation of the identified hits. Citation Format: Florencia Villafañez, Alejandra Iris García, María Florencia Pansa, Sofía Carbajosa, José Luis Bocco, Gastón Soria. Development of screening methods to identify Translesion DNA Synthesis inhibitors [abstract]. In: Proceedings of the AACR Special Conference on DNA Repair: Tumor Development and Therapeutic Response; 2016 Nov 2-5; Montreal, QC, Canada. Philadelphia (PA): AACR; Mol Cancer Res 2017;15(4_Suppl):Abstract nr A37.

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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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.158
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 science0.0010.001
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 head0.096
GPT teacher head0.471
Teacher spread0.375 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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