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Record W3047663499 · doi:10.1158/1538-7445.pedca19-a14

Abstract A14: Exploiting DNA damage repair defects to enhance PD-L1 expression in Ewing sarcoma

2020· article· en· W3047663499 on OpenAlexaboutno aff
Lisa M. Maurer, Rose M. Venier, Claire M. Julian, Kelly M. Bailey

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsnot available
Fundersnot available
KeywordsOlaparibCancer researchBiologyDNA damagePoly ADP ribose polymeraseApoptosisPARP inhibitorCell cultureDNA repairMolecular biologyPolymeraseGenetics

Abstract

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Abstract Objective: The purpose of this work is to determine whether PD-L1 expression can be upregulated by PARP inhibitor treatment in Ewing tumor cells harboring DNA damage repair defects. Further, we aimed to determine whether enhanced PD-L1 expression renders Ewing cells more susceptible to T-cell mediated apoptosis following PD-1 inhibition. Experimental Procedures: Patient-derived tumor organoids and monolayers (named PSaRC-318) were established from a viably cryofrozen metastatic lung lesion from a patient with Ewing sarcoma and a paternally inherited germline BARD1 mutation. A673, CHLA9, and CHLA10 Ewing tumor cell lines were also employed. Sensitivity of PSaRC-318 to the PARP inhibitors olaparib and talazoparib was established by performing IncuCyte apoptosis assays. PD-L1 expression was examined using RT-PCR, Western blot, and flow cytometry. BARD1, BRCA, and RAD51D siRNA were also utilized to test the role of specific DNA damage repair proteins on this effect. T-cell/tumor cell cocultures and tumor-primed T-cells were established. T cell-induced tumor cell apoptosis was monitored in real-time using IncuCyte caspase and annexin assays. Results: PSaRC-318 organoids demonstrate exquisite sensitivity to PARP inhibitors, with an IC50 for talazoparib of 3.54nM. Treatment of PARP inhibitor-resistant Ewing cell lines, such as CHLA10, with BARD1 siRNA rendered cells sensitive to PARP inhibition. Ewing tumor cells were found to upregulate tumor cell surface expression of the checkpoint protein PD-L1 in response to treatment with PARP inhibitors. The impact of BARD1, BRCA1, and RAD51D on PD-L1 expression in Ewing tumor cells was also determined. Next, Ewing tumor cells were pretreated with PARP inhibitors and then cocultured with tumor-primed T-cells. T cell-mediated tumor cell apoptosis was monitored in real time using caspase IncuCyte assays. PD-1 blocking antibody added to T-cell/tumor cell cocultures resulted in an increase in early tumor cell death compared to IgG controls. Conclusion: Single-agent PARP inhibitors have not demonstrated significant clinical benefit in relapsed Ewing sarcoma to date, suggesting that combinatorial therapy with PARP inhibitors may be a more effective approach. Here, we have shown that Ewing tumor cells with germline mutations in DNA-damage repair proteins, such as BARD1, can upregulate PD-L1 expression following treatment with PARP inhibitors. Thus, PARP inhibitor/anti-PD-1 therapy may be a logical combination for the treatment of relapsed Ewing sarcoma. Ongoing preclinical studies are continuing to examine this combination. Citation Format: Lisa M. Maurer, Rose M. Venier, Claire Julian, Kelly M. Bailey. Exploiting DNA damage repair defects to enhance PD-L1 expression in Ewing sarcoma [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A14.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.153
GPT teacher head0.467
Teacher spread0.315 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2020
Admission routes1
Has abstractyes

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