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Record W2235405584 · doi:10.1056/nejmoa1506859

DNA-Repair Defects and Olaparib in Metastatic Prostate Cancer

2015· article· en· W2235405584 on OpenAlexfundno aff
Joaquı́n Mateo, Suzanne Carreira, Shahneen Sandhu, Susana Miranda, Helen Mossop, Raquel Pérez-López, Daniel Nava Rodrigues, Dan R. Robinson, Aurelius Omlin, Nina Tunariu, Gunther Boysen, Núria Porta, Penny Flohr, Alexa Gillman, Ines Figueiredo, Claire Paulding, George Seed, Suneil Jain, Christy Ralph, Andrew Protheroe, Syed A. Hussain, Robert J. Jones, Tony Elliott, Ursula McGovern, Diletta Bianchini, Jane Goodall, Zafeiris Zafeiriou, Chris T. Williamson, Roberta Ferraldeschi, Ruth Riisnaes, Bernardette Ebbs, Gemma Fowler, Desamparados Roda, Wei Yuan, Yi‐Mi Wu, Xuhong Cao, Rachel Brough, Helen N. Pemberton, Roger A’Hern, Amanda Swain, Lakshmi P. Kunju, Rosalind A. Eeles, Gerhardt Attard, Christopher J. Lord, Alan Ashworth, Mark A. Rubin, Karen E. Knudsen, Felix Y. Feng, Arul M. Chinnaiyan, Emma Hall, Johann S. de Bono

Bibliographic record

VenueNew England Journal of Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
FundersNational Cancer InstituteStand Up To CancerGenentechEuropean Society for Medical OncologyCilagAstellas PharmaNational Institute for Health and Care ResearchSanofiPublic Health AgencyProstate Cancer UKGlaxoSmithKlineLes Laboratories Pierre FabreMedical Research CouncilCelgeneBristol-Myers SquibbProstate Cancer FoundationAmerican Association for Cancer ResearchAstraZenecaRoyal Marsden NHS Foundation TrustPfizerOncolytics BiotechCancer Research UK
KeywordsOlaparibPoly ADP ribose polymeraseProstate cancerDNA repairPolymeraseCancer researchPARP inhibitorMedicineInternal medicineOncologyProstateDNACancerBiologyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Prostate cancer is a heterogeneous disease, but current treatments are not based on molecular stratification. We hypothesized that metastatic, castration-resistant prostate cancers with DNA-repair defects would respond to poly(adenosine diphosphate [ADP]-ribose) polymerase (PARP) inhibition with olaparib. METHODS: We conducted a phase 2 trial in which patients with metastatic, castration-resistant prostate cancer were treated with olaparib tablets at a dose of 400 mg twice a day. The primary end point was the response rate, defined either as an objective response according to Response Evaluation Criteria in Solid Tumors, version 1.1, or as a reduction of at least 50% in the prostate-specific antigen level or a confirmed reduction in the circulating tumor-cell count from 5 or more cells per 7.5 ml of blood to less than 5 cells per 7.5 ml. Targeted next-generation sequencing, exome and transcriptome analysis, and digital polymerase-chain-reaction testing were performed on samples from mandated tumor biopsies. RESULTS: Overall, 50 patients were enrolled; all had received prior treatment with docetaxel, 49 (98%) had received abiraterone or enzalutamide, and 29 (58%) had received cabazitaxel. Sixteen of 49 patients who could be evaluated had a response (33%; 95% confidence interval, 20 to 48), with 12 patients receiving the study treatment for more than 6 months. Next-generation sequencing identified homozygous deletions, deleterious mutations, or both in DNA-repair genes--including BRCA1/2, ATM, Fanconi's anemia genes, and CHEK2--in 16 of 49 patients who could be evaluated (33%). Of these 16 patients, 14 (88%) had a response to olaparib, including all 7 patients with BRCA2 loss (4 with biallelic somatic loss, and 3 with germline mutations) and 4 of 5 with ATM aberrations. The specificity of the biomarker suite was 94%. Anemia (in 10 of the 50 patients [20%]) and fatigue (in 6 [12%]) were the most common grade 3 or 4 adverse events, findings that are consistent with previous studies of olaparib. CONCLUSIONS: Treatment with the PARP inhibitor olaparib in patients whose prostate cancers were no longer responding to standard treatments and who had defects in DNA-repair genes led to a high response rate. (Funded by Cancer Research UK and others; ClinicalTrials.gov number, NCT01682772; Cancer Research UK number, CRUK/11/029.).

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.054
GPT teacher head0.357
Teacher spread0.302 · 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 designObservational
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

Citations2,187
Published2015
Admission routes1
Has abstractyes

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