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Record W4409690752 · doi:10.1158/1538-7445.am2025-443

Abstract 443: Targeting therapeutic vulnerabilities mediated by epigenetic reprogramming in ARID1A and ARID1B dual-deficient gynecologic cancers

2025· article· en· W4409690752 on OpenAlexaff
Rebecca Ho, Bengul Gokbayrak, Eunice Li, Shary Chen, Chae Young Shin, David Huntsman, Nathan A. Lack, Yemin Wang

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsARID1AReprogrammingCancer researchEpigeneticsGynecologic cancerMedicineCancerBiologyInternal medicineGeneticsOvarian cancerMutationGene

Abstract

fetched live from OpenAlex

Abstract Background: Dedifferentiated carcinoma of the uterus and the ovary (DDEC collectively) are rare gynecologic cancers made of low-grade differentiated adenocarcinoma of the uterus or ovary juxtaposed against undifferentiated carcinoma. The two components are clonally related, and previous studies have suggested that loss of various switch/sucrose non-fermentable (SWI/SNF) proteins may contribute to the transformation of differentiated cancer cells to an undifferentiated state. Specifically, a third of all DDECs have co-inactivation of cBAF-specific subunits ARID1A and ARID1B. cBAF is one of the three major SWI/SNF complex subfamilies, and loss of ARID1A/B disrupts the chromatin remodeling function of cBAF. We hypothesize that epigenetic reprogramming in response to loss of cBAF activity will alter residual SWI/SNF complex assembly, creating vulnerabilities in DDEC that will allow for novel therapeutic opportunities. Methods: We generated an isogenic cell line with ARID1A/B dual loss to narrow down vulnerabilities in dual-deficient cells. Using this isogenic pair, we conducted a drop-out screen using EPIKOL, a CRISPR knockout library targeting epigenetic modifiers and cofactors. To validate the results, we genomically depleted and treated cells with small molecules to inhibit protein function. Additionally, to further understand the changes in SWI/SNF complex assembly when cBAF is lost, we conducted density gradient sedimentation assays with nuclear protein extracts isolated from the isogenic cell line pair. Finally, SWI/SNF inhibitors were added to bona fide ARID1A/B dual-deficient dedifferentiated carcinoma of the uterus and the ovary cell lines and xenografted tumors to test the generalizability of our findings. Results: EPIKOL screening identified that ARID1B-dependent, ARID1A-deficient cancer cells have increased reliance on ARID2 and PBRM1, two PBAF-specific subunits, upon ARID1B deletion. When ARID2 and PBRM1 were knocked out in ARID1A proficient and ARID1A/B dual-deficient cells, the latter had significant growth impairment. Furthermore, when treating the isogenic cell line pair with SWI/SNF inhibitors, we also noted increased sensitivity in the dual-deficient cell line. Moreover, we observed a shift towards PBAF assembly in the cells with ARID1A/B dual-loss, further supporting an increased dependency on the remaining SWI/SNF complexes in dual-deficient cells. Finally, we observed increased sensitivities towards SWI/SNF subunit inhibitors in other ARID1A/B dual-deficient ovarian and endometrial cancer cell lines and their xenografted tumors. Conclusion: ARID1A/B dual-deficient cancer cells have an increased reliance on the remaining SWI/SNF complexes for survival, thus highlighting a novel therapeutic option for DDEC with ARID1A/B dual loss. Citation Format: Rebecca Ho, Bengul Gokbayrak, Eunice Li, Shary Chen, Emma Guo, Chae Young Shin, David Huntsman, Nathan Lack, Yemin Wang. Targeting therapeutic vulnerabilities mediated by epigenetic reprogramming in ARID1A and ARID1B dual-deficient gynecologic cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 443.

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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)0.001
metaresearch head score (Gemma)0.000
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 score0.154
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.033
GPT teacher head0.369
Teacher spread0.337 · 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
Published2025
Admission routes1
Has abstractyes

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