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Using NBN to predict biochemical relapse following image-guided radiotherapy (IGRT) for intermediate-risk prostate cancer (IR-PCa).

2014· article· en· W2589743022 on OpenAlexaff
Alejandro Berlín, Emilie Lalonde, Gaetano Zafarana, Jenna Sykes, Varune Rohan Ramnarine, Wan L. Lam, Alice Meng, Michael Milosevic, Theodorus van der Kwast, Paul C. Boutros, Robert G. Bristow

Bibliographic record

VenueJournal of Clinical Oncology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsPrincess Margaret Cancer CentreOntario Institute for Cancer ResearchUniversity of TorontoUniversity of British ColumbiaUniversity Health Network
Fundersnot available
KeywordsMedicineProstate cancerImage-guided radiation therapyOncologyCohortProstatectomyProportional hazards modelInternal medicineHazard ratioCancerRadiation therapyProstate

Abstract

fetched live from OpenAlex

26 Background: Despite the use of clinical prognostic factors, 20 to 40% of patients with intermediate-risk prostate cancer (IR-PCa) fail local treatment for unexplained reasons. Given that an accurate DNA damage response (DDR) may be associated with genetic instability and radioresponse, we investigated whether copy number alterations (CNAs) in DDR genes are predictive or prognostic following local treatment. Methods: Using array comparative genomic hybridization (aCGH), we characterized CNAs in biopsies derived from 126 IR-PCa pts. who underwent image-guided radiotherapy (IGRT). We studied the DDR-sensing genes: MRE11A, RAD50, NBN, ATM, and ATR. The IGRT cohort (median dose: 76.4Gy; median follow-up: 7.8yrs) was compared to a radical prostatectomy (RP) cohort (154 pts. from Memorial Sloan-Kettering Cancer Center database; median follow-up: 4.8yrs). CNAs were then tested for their independent prognostic capability using Kaplan-Meir method and Cox proportional hazard models. Results: In our IGRT cohort, m,ost frequent DDR gene CNAs were: NBN 20 of 126 (15.9%), ATR 11of 126 (8.7%), and ATM 7 of 126 (5.5%). NBN CNAs were mainly gains (19/20) and strongly correlated with increased NBN-mRNA abundance compared to NBN-neutral cases (p=0.016). CNAs in DDR genes were not associated with GS, prostate-specific antigen, or T-stage. Importantly, NBN gain ranked among the top 3.3% of all genes in terms of its strength of association with the percent of the genome altered (PGA). After adjusting for clinical factors in a multivariate model, NBN gain was a significant independent predictor of 5 years-biochemical relapse-free rate (bRFR) following IGRT (48.6% versus 78.8%; HR = 3.14, 95% CI: 1.42-6.94, p=0.004). No DDR CNA was prognostic in the RP cohort. Increased NBN mRNA expression correlated to radioresistance in vitro (i.e. clonogenic surviving fraction after 3Gy) in five prostate cancer cell lines (R2= 0.665). This relationship was not observed for any of the other DDR genes. Conclusions: NBN copy number gain or increased expression correlates with tumor genomic instability, decreased bRFR (IGRT- but not surgery-treated pts.) and intrinsic prostate cancer cell radioresistance. If validated in independent IGRT cohorts, NBN gain could be the first PCa predictive biomarker to facilitate local treatment decisions using precision medicine approaches.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.051
GPT teacher head0.431
Teacher spread0.380 · 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
Published2014
Admission routes1
Has abstractyes

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