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Neoplastic and blood-based biomarkers of response in patients with advanced endometrial cancer: Results from NRG GY012.

2023· article· en· W4379281712 on OpenAlexaff
Helen Mackay, Andrew B. Nixon, Danielle Enserro, David Bender, B.J. Rimel, Matthew A. Powell, Debra L. Richardson, Laura L. Holman, Nitya Alluri, Cara Mathews, Ruchi Garg, Sarah Gill, Daniela Matei, Charles A. Leath, Floor Backes, Aimee C. Fleury, Elizabeth M. Swisher

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
FundersNational Institutes of Health
KeywordsMedicineOlaparibPARP inhibitorOncologyBiomarkerOvarian cancerInternal medicineEndometrial cancerPALB2Somatic cellCirculating tumor cellMultiplexLoss of heterozygosityCancerGermline mutationBioinformaticsGeneMetastasisPoly ADP ribose polymeraseBiologyMutation

Abstract

fetched live from OpenAlex

5525 Background: NRG GY012 is a randomized, 3-arm phase II study, comparing olaparib (O) and the combination of cediranib and olaparib (CO) to the reference arm cediranib (C) for metastatic pre-treated, endometrial cancer (EC). The trial found a trend towards benefit for CO and no benefit for O compared to C. Archival tumor and prospective blood samples were collected for biomarker analysis. Methods: Targeted next-generation sequencing (BROCA-GO) was used to detect pathogenic variants (PV) and loss of heterozygosity (LOH) in DNA from paired blood and archival cancers. The LOH cut-off was identified at 11% for HRD based on testing ovarian cancers with known HRD. Plasma samples collected at baseline, cycle 2 day 1, and end-of-treatment were analyzed via multiplex ELISA for 25 angiogenic and inflammatory circulating protein biomarkers (Angiome); IL6 was of specific interest. Prognostic associations with PFS and OS were analyzed using proportional hazards models (PhM) stratified by histology and adjusted for treatment assignment. Predictive associations (PFS and OS) were analyzed using PhM stratified by histology and including main effects for both treatment assignment and biomarker group plus an interaction term. Results: In 97 patients (pts) with evaluable tumor, BROCA-GO identified 370 somatic PV; TP53 (61%) was the most commonly mutated gene. PV in homologous recombination repair (HRR) genes were identified in 5 cases (5%). Somatic PVs were identified in BRCA2, RAD51B and PALB2. 1 pt had a germline BRCA1 PV. 2 cases had somatic PV that might restore HRR: 1 case with a somatic BRCA2 PV had somatic PVs in CHD4 and TP53BP1; the TP53BP1 frameshift PV was present only in the recurrent and not primary cancer. LOH was available for 45 cases. LOH high occurred in 16 (35.6%) cases and was exclusive to EC with TP53 mutations (p=0.0003). LOH was not associated with outcome in any of the arms. For the circulating biomarker analysis (N=96), median IL-6 was 4pg/ml. IL-6 levels >4pg/ml were associated with increased risk of progression (HR: 1.59; 95% CI: (1.04-2.42); p-value=0.032). In predictive analyses, pts with IL-6 > 4 pg/ml receiving C or C+O had increased PFS (3.8 mo vs 1.9 mo) and OS (11.9 mo vs 5.7 mo) compared to pts receiving O, the interaction p value did not reach statistical significance. Conclusions: LOH high status was not associated with outcome to O. There were too few cases with HRR PVs to determine their relationship to PARPi response. The restriction of LOH high to cancers with TP53 mutation may suggest that genomic LOH in ECs correlates better with aneuploidy than with HRR function indicating that at least some biomarkers of PARPi response vary between tumor types. IL-6 levels were prognostic of PFS but were not predictive of either OS or PFS for pts receiving C compared to pts receiving O in this small study. Further analysis of the complete Angiome and integration with the BROCA-GO dataset are ongoing. Clinical trial information: NCT03660826 .

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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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.080
GPT teacher head0.446
Teacher spread0.367 · 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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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