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Impact of AR-V7 and other androgen receptor splice variant expression on outcomes of post-prostatectomy salvage therapy.

2022· article· en· W4226221611 on OpenAlexaff
Keisuke Otani, David J. Konieczkowski, Michael Drumm, Yukako Otani, Shulin Wu, Elai Davicioni, Philip J. Saylor, Chin‐Lee Wu, Jason A. Efstathiou, David T. Miyamoto

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsGenome British Columbia
FundersRadiological Society of North America
KeywordsProstate cancerProstatectomyMedicineAndrogen receptorAndrogen deprivation therapySalvage therapyBiochemical recurrenceOncologyRadiation therapyInternal medicineCancerCancer researchChemotherapy

Abstract

fetched live from OpenAlex

274 Background: Radiotherapy (RT) with or without androgen deprivation therapy (ADT) plays a key role in salvage therapy of prostate cancer recurrent after prostatectomy. However, not all patients benefit from salvage therapy, and there is an unmet need for biomarkers to distinguish responders from non-responders. Prostate cancer depends on androgen receptor (AR) signaling, and expression of AR splice variants (ARVs) that enable androgen-independent AR signaling is associated with resistance to ADT in the metastatic setting. Recent in vitro data suggest that ARVs also mediate DNA repair after irradiation, suggesting that ARV expression may also be a biomarker of RT resistance. However, the landscape of ARVs in primary prostate cancer and its effect on treatment outcomes remain unexplored. Here we hypothesize that ARVs are detectable in primary prostate cancer and may modulate response to salvage RT + ADT. Methods: We retrospectively identified 46 prostate cancer patients treated with prostatectomy followed by salvage RT+ ADT at a single institution from 1995 to 2012. The indication for salvage therapy was biochemical failure after undetectable post-operative PSA in 72%, gross local recurrence in 17%, and persistently elevated PSA after surgery in 11%. Median RT dose was 64.8 Gy, and all patients received concurrent ADT. We comprehensively interrogated the landscape of ARVs by performing ultra-deep targeted RNA-seq of archival formalin-fixed paraffin-embedded prostatectomy samples. Using a custom library of > 3000 primers spanning all AR exons and introns, we evaluated 21 native splice junction sites and 20 splice variants with a mean depth of coverage of > 5000x. Decipher score was also evaluated. We tested for association between splice variant expression and clinical outcomes using the log-rank test and Cox proportional hazards model. Results: In total, 76% of patients had one or more detectable AR splice variants. The most commonly detected variants were AR-45 in 41%, AR-V9 in 20%, and AR-V7 in 13%. At a median follow-up of 33.8 months, biochemical progression-free survival (BPFS) at 3 years was 60%, distant metastasis-free survival was 90%, and overall survival was 100%. Among detected splice variants, only AR-V7 was associated with differential clinical outcomes, with a median BPFS of 10.9 months in AR-V7 positive vs 73.4 months in AR-V7 negative patients ( p = 0.0020, HR 5.23, 95% CI 1.62-16.87). Conclusions: Using ultra-deep targeted RNA-Seq, we provide among the first comprehensive descriptions of the ARV landscape in primary prostate cancer. Moreover, we show that detectable AR-V7 in prostatectomy specimens was associated with inferior outcomes following salvage RT+ADT, suggesting for the first time that AR-V7 may modulate outcomes for localized as well as metastatic disease. Ongoing work includes comparison with Decipher score and validation in independent cohorts.

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 score0.005

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.126
GPT teacher head0.502
Teacher spread0.376 · 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
Published2022
Admission routes1
Has abstractyes

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