MétaCan
Menu
Back to cohort

Abstract B004: ATR-CHK1-WEE1 pathway is a critical dependency in the context of DNA damage and replicative stress in osteosarcoma

2022· article· en· W4296131466 on OpenAlexaboutno aff
Leanne C. Sayles, Henry J. Martell, Amanda Koehne, Kean-Hooi Ang, Chris Wilson, Michelle R. Arkin, E. Alejandro Sweet‐Cordero

Bibliographic record

VenueClinical Cancer Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsnot available
Fundersnot available
KeywordsGemcitabineCancer researchIn vivoContext (archaeology)Combination therapyWee1ApoptosisOsteosarcomaDNA damageMedicineBiologyCell cyclePharmacologyCancerInternal medicineDNAGenetics

Abstract

fetched live from OpenAlex

Abstract Osteosarcoma (OS) is characterized by widespread somatic copy number alterations (SCNAs) and structural variations (SVs) with few recurrent point mutations. We previously demonstrated proof-of-principle for a genome-informed strategy for treatment of OS based on rank-ordering SCNAs within specific oncogenes identified by WGS and RNAseq. Although we identified several potentially effective therapeutic strategies using this approach, it is likely that effective therapy for OS will require use of combination therapies. To identify new combination therapy approaches for OS, we used a panel of PDX-derived cell lines (PDXC) and performed a combination drug screen. We assessed 5 drug backbones against 15 targeted agents in 8 PDXC and 2 established OS cell lines. When we combined Gemcitabine with agents that target the ATR-CHK1-WEE1 pathway, we observed strong synergy across all PDXC tested. These results were validated in a secondary screen using a combination matrix across 10 PDXC. Use of targeted agents inhibiting ATR, CHK1 or WEE1 in combination with Gemcitabine led to decreased proliferation and a marked increase in apoptosis in vitro. In subcutaneous tumor models, we observed that decreased tumor growth with either ATRi or Gemcitabine alone, whereas tumors shrank when treated with the combination. However, when we treated OS774 in vivo, there was no effect on tumor growth for either single agent alone or when in combination. This effect was dependent on the presence of ATR as a PDXC with no ATR detectable by western blotting showed not effect in vivo. In an orthotopic model in which PDXC are implanted along the tibia, this combination therapy effectively decreased tumor growth. In a lung metastasis model, ATRi and Gemcitabine resulted a durable reduction in metastatic lesions over time. In summary, we have identified a susceptibility to the ATR-CHK1-WEE1 pathway when combined with gemcitabine. These studies suggest that further investigation ATR-CHK1-WEE1 and gemcitabine are warranted to address the unmet need for new therapeutic approaches for relapsed and recurrent OS patients. Citation Format: Leanne C. Sayles, Henry Martell, Amanda Koehne, Kean-Hooi Ang, Chris Wilson, Michelle Arkin, E. Alejandro Sweet-Cordero. ATR-CHK1-WEE1 pathway is a critical dependency in the context of DNA damage and replicative stress in osteosarcoma [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr B004.

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 score0.004
Threshold uncertainty score0.014

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)0.0040.001

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 head0.149
GPT teacher head0.493
Teacher spread0.344 · 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueClinical Cancer ResearchSame topicRNA modifications and cancerFrench-language works237,207