MétaCan
Menu
Back to cohort
Record W3184904659 · doi:10.1158/0008-5472.can-21-0774

Acquired <i>RAD51C</i> Promoter Methylation Loss Causes PARP Inhibitor Resistance in High-Grade Serous Ovarian Carcinoma

2021· article· en· W3184904659 on OpenAlexfundno aff
Ksenija Nesic, Olga Kondrashova, Rachel M. Hurley, Cordelia D. McGehee, Cassandra J. Vandenberg, Gwo‐Yaw Ho, Elizabeth Lieschke, Genevieve Dall, Nirashaa Bound, Kristy Shield‐Artin, Marc R. Radke, Ashan Musafer, Zi Qing Chai, Mohammad Reza Eftekhariyan Ghamsari, Maria I. Harrell, Damien Kee, Inger Olesen, Orla McNally, Nadia Traficante, Australian Ovarian Cancer Study, Anna DeFazio, David D.L. Bowtell, Elizabeth M. Swisher, S. John Weroha, Kátia Nones, Nicola Waddell, Scott H. Kaufmann, Alexander Dobrovic, Matthew J. Wakefield, Clare L. Scott

Bibliographic record

VenueCancer Research · 2021
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesCancer Council TasmaniaCancer Council VictoriaCancer Council South AustraliaVictorian Cancer AgencyEntertainment Industry FoundationStand Up To CancerMedical Research CouncilPeter MacCallum FoundationAstraZeneca AustraliaMedical Research and Materiel CommandEisaiOvarian Cancer Research FundCancer AustraliaNational Cancer InstituteAustralian Cancer Research FoundationMayo Foundation for Medical Education and ResearchState Government of VictoriaAustralian GovernmentCancer Council NSWOvarian Cancer AustraliaNational Breast Cancer FoundationClovis OncologySierra OncologyNational Ovarian Cancer CoalitionAmerican Association for Cancer ResearchNational Health and Medical Research CouncilCancer Research InstituteAstraZenecaOvarian Cancer Research Fund AllianceNational Institutes of Health
KeywordsSerous fluidPARP inhibitorOvarian carcinomaMethylationCancer researchMedicineOvarian cancerOncologyInternal medicineBiologyPoly ADP ribose polymeraseCancerGeneGeneticsPolymerase

Abstract

fetched live from OpenAlex

Abstract In high-grade serous ovarian carcinoma (HGSC), deleterious mutations in DNA repair gene RAD51C are established drivers of defective homologous recombination and are emerging biomarkers of PARP inhibitor (PARPi) sensitivity. RAD51C promoter methylation (meRAD51C) is detected at similar frequencies to mutations, yet its effects on PARPi responses remain unresolved. In this study, three HGSC patient-derived xenograft (PDX) models with methylation at most or all examined CpG sites in the RAD51C promoter show responses to PARPi. Both complete and heterogeneous methylation patterns were associated with RAD51C gene silencing and homologous recombination deficiency (HRD). PDX models lost meRAD51C following treatment with PARPi rucaparib or niraparib, where a single unmethylated copy of RAD51C was sufficient to drive PARPi resistance. Genomic copy number profiling of one of the PDX models using SNP arrays revealed that this resistance was acquired independently in two genetically distinct lineages. In a cohort of 12 patients with RAD51C-methylated HGSC, various patterns of meRAD51C were associated with genomic “scarring,” indicative of HRD history, but exhibited no clear correlations with clinical outcome. Differences in methylation stability under treatment pressure were also observed between patients, where one HGSC was found to maintain meRAD51C after six lines of therapy (four platinum-based), whereas another HGSC sample was found to have heterozygous meRAD51C and elevated RAD51C gene expression (relative to homozygous meRAD51C controls) after only neoadjuvant chemotherapy. As meRAD51C loss in a single gene copy was sufficient to cause PARPi resistance in PDX, methylation zygosity should be carefully assessed in previously treated patients when considering PARPi therapy. Significance: Homozygous RAD51C methylation is a positive predictive biomarker for sensitivity to PARP inhibitors, whereas a single unmethylated gene copy is sufficient to confer resistance.

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 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 categoriesMeta-epidemiology (narrow)
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 score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.093
GPT teacher head0.402
Teacher spread0.309 · 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.

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

Citations86
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicPARP inhibition in cancer therapyFrench-language works237,207