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Record W2898384408 · doi:10.1093/annonc/mdy284.005

Detection of circulating tumor DNA in de novo metastatic castrate sensitive prostate cancer

2018· article· en· W2898384408 on OpenAlexaffabout
Werner J. Struss, Gillian Vandekerkhove, Matti Annala, K.N. Chi, Martin Gleave, Alexander W. Wyatt

Bibliographic record

VenueAnnals of Oncology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsVancouver General Hospital
Fundersnot available
KeywordsMedicineProstate cancerProstatectomyOncologyCancerLoss of heterozygosityInternal medicineProstateCell-free fetal DNAPathologyGeneAlleleBiologyGenetics

Abstract

fetched live from OpenAlex

Background: De novo metastatic castrate sensitive prostate cancer (mPC) represents approximately 10% of prostate cancer diagnoses but almost 50% of mPC related deaths. Biomarkers are required to guide therapy intensification at time of diagnosis, but scant tumor material is available since most patients do not undergo prostatectomy. Plasma circulating tumor DNA (ctDNA) is a promising minimally-invasive biomarker in castration-resistant disease but remains untested in castrate-sensitive disease. Methods: We collected plasma cell-free DNA (cfDNA) at or near time of diagnosis from 51 de novo mPC patients enrolled at two academic centres. CfDNA and matched diagnostic needle biopsies were subjected to deep targeted sequencing across all exons of 73 prostate cancer relevant genes and analyzed independently for somatic alterations. Results: 22 of 31 (71%) ADT-naive patients had detectable ctDNA (fraction range 0.5-70%). A further 20 patients received between 1 and 49 days of ADT prior to cfDNA collection (median 23) and had significantly lower ctDNA fractions than ADT-naive patients (mean 6.0% vs 22.7%; p = 0.009). Although there was no relationship between Gleason score, serum PSA or age at diagnosis and ctDNA fraction, 11 of 13 patients (86%) with lung and/or liver metastases had detectable ctDNA. Excluding one case with hypermutation and mismatch repair deficiency detected only in ctDNA, 83% of non-silent mutations were concurrently identified in both tissue and ctDNA while 9.3% and 7.8% were unique to tissue or ctDNA respectively. 9 patients had truncating mutations and loss of heterozygosity across DNA repair genes BRCA2, ATM, CDK12 or MSH2. No AR gene alterations were detected. Conclusions: Plasma ctDNA is detected in the majority of patients with de novo mPCa and somatic mutations identified in ctDNA are highly concordant with the matched diagnostic prostate biopsy. Exposure to ADT prior to plasma collection significantly reduces ctDNA detection rates and ctDNA fraction. cfDNA analysis can detect important driver alterations and is complementary to tissue-based analyses. Legal entity responsible for the study: Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, British Columbia, Canada. Funding: Has not received any funding. Disclosure: All authors have declared no conflicts of interest.

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)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.039
GPT teacher head0.354
Teacher spread0.314 · 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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Citations2
Published2018
Admission routes2
Has abstractyes

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