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Immunogenomic landscape of neuroendocrine small cell prostate cancer.

2019· article· en· W2921821362 on OpenAlexaff
Lucia Nappi, Claudia Kesch, Sepideh Vahid, Ladan Fazli, Bernhard J. Eigl, Christian Kollmannsberger, Martin Gleave, Amina Zoubeidi, Alexander W. Wyatt, Kim N.

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsBC Cancer AgencyUniversity of British Columbia
Fundersnot available
KeywordsProstate cancerMedicineAdenocarcinomaProstatectomyImmunohistochemistryProstateChromogranin APathologyCancerCancer researchOncologyInternal medicine

Abstract

fetched live from OpenAlex

217 Background: Neuroendocrine small cell prostate cancer (NEPC) is a lethal variant of prostate cancer (PCa) unresponsive to hormone therapy and associated with poor prognosis. Cisplatin induces short-lived responses and therefore alternative novel therapeutic options are urgently needed. Methods: Prostate specimens from radical prostatectomy or transurethral resection (benign prostate specimens n = 4, primary untreated or neoadjuvant hormone-treated adenocarcinoma n = 30, castrate-resistant prostate cancer-CRPC n = 38 and NEPC n = 16) were evaluated for PD-L1 (SpringBio, M4420), AR, chromogranin A, synaptophysin, NSE and CD56 expression by immunohistochemistry (IHC). Archival tissue from liver, lymph nodes and prostate from 30 additional patients with de novo and treatment emergent NEPC were analyzed for PD-L1 expression by IHC. The intensity was assessed as percentage of positive cells / mm2 of tissue. Targeted and whole exome sequencing of the high-density tumor areas were performed and correlated to the PD-L1 status (PD-L1+ve: > 1% of positive cells). OS was calculated from the date of diagnosis of NEPC to death. We set out to define PD-L1 expression and immunogenomic characteristics of NEPC. Results: PD-L1 was expressed in 0%, 5%, 10% and 41% of benign, adenocarcinoma, CRPC and NEPC specimens, respectively. The PD-L1 expression intensity was significantly higher in patients with NEPC (mean: 40%, range: 5-100%) compared to benign, adenocarcinoma and CRPC samples (mean: 0%, 2% and 8%, respectively, P < 0.0001). There was a higher prevalence of biallelic DNA Repair Defects (DRD) in the PD-L1+ve vs PD-L1-ve patients (65% vs 0%, P = 0.005). The median OS of the NEPC patients was 8.5 months vs 10.5 months in PD-L1+ve vs PD-L1-ve tumors (HR 1.24, 95% CI: 0.59-2.75, p = 0.55). Conclusions: NEPC have greater PD-L1 expression than adenoCa and CRPC. Biallelic DRD was exclusively observed in PD-L1+ve patients. Since PD-L1 expression and DRD have been associated to response to PARP and PD1/PD-L1 inhibitors in prostate and other cancers, further studies evaluating the activity of those agents in NEPC patients are warranted.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.091
GPT teacher head0.451
Teacher spread0.359 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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