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Abstract A004: Radiotherapy sensitizes preclinical models to DNA damage response agents

2024· article· en· W4399504666 on OpenAlexaboutno aff
Pablo Binder, Theoni Katopodi, Lyndsey Hanson, Charlotte R. Bell, Eimear Flanagan, Paul Farrington, Nick Moore, Emily K. Wright, Yin Xin Ho, Tobias Bunday, Stewart Brown, Amy Cantrell, Yaël Mamane, J. Greenall, Shannon Sharman, John F. Woolley, Lorraine M. Mooney, Jane Kendrew

Bibliographic record

VenueMolecular Cancer Therapeutics · 2024
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsnot available
Fundersnot available
KeywordsRadiation therapyIn vivoCancer researchDNA damagePharmacologyViability assayMedicineCancerIn vitroBiologyInternal medicineDNABiochemistry

Abstract

fetched live from OpenAlex

Abstract Introduction Radiotherapy is a key treatment for various cancers, with nearly 50% of all cancer patients receiving it as part of their therapeutic plan. It can activate cytotoxic signaling pathways to promote cancer cell death but also trigger cytoprotective mechanisms that respond to cellular damage. These cytoprotective mechanisms can be inhibited by targeted anticancer agents such as DNA damage response (DDR) agents, suggesting that radiotherapy could enhance the efficacy of these drugs. This study presents data showing radiotherapy enhances the potency of DDR agents in preclinical models. Methods and experimental procedures The MDA-MB-436 breast and A549 lung cancer cell lines were utilized to establish in vitro assays and in vivo models for the study. Agents targeting DNA-PK (AZD7648) and PARP (niraparib) were used as they work on pathways crucial for the repair of radiation-induced DNA double-strand breaks. The effects on cell viability and DDR biomarkers were assessed after treatment with irradiation (IR), compound or in combination both in vitro and in vivo. Targeted X-rays were delivered using an Xstrahl CIX3 cabinet irradiator, in vivo radiotherapy was delivered to the tumor only. Data An increased sensitivity to DDR agents when combined with radiotherapy was observed in vitro in both cell lines, compared to standalone treatments. A single dose of radiotherapy significantly reduced cell viability beyond the effects of radiotherapy or compound treatment alone. The induction of biomarkers by radiotherapy as monotherapy or in combination with DDR inhibitors was assessed. Changes in biomarker expression were consistent with those observed in the in vivo xenograft models. The administration of fractionated dosing regimens for radiotherapy was well-tolerated in vivo. Combination of radiotherapy with the DDR compounds led to tumor growth delay and enhanced survival outcomes. Conclusion In summary, in vitro assays and in vivo models have been established to investigate the synergistic effects of the combination of radiotherapy and DDR agents. Radiotherapy increased sensitivity of 2 human cancer cell lines to the DDR agents in vitro, and lead to tumor growth delay in vivo. These assays can be used as preclinical tools to identify novel compounds or mechanisms that can be successfully combined with radiotherapy. Citation Format: Pablo Binder, Theoni Katopodi, Lyndsey Hanson, Charlotte R. Bell, Eimear Flanagan, Paul Farrington, Nick Moore, Emily Wright, Yin Xin Ho, Tobias Bunday, Stewart Brown, Amy Cantrell, Yael Mamane, Jon Greenall, Shannon Sharman, John Woolley, Lorraine M. Mooney, Jane Kendrew. Radiotherapy sensitizes preclinical models to DNA damage response agents [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 A004.

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 score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.003

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 head0.102
GPT teacher head0.406
Teacher spread0.304 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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