MP20-07 NPTX1 IS A NOVEL SERUM BIOMARKER INDUCED BY ARPI TREATED PROSTATE CANCER AND ENRICHED IN LINEAGE PLASTICITY WITH BRN2 HIGH
Bibliographic record
Abstract
You have accessJournal of UrologyCME1 Apr 2023MP20-07 NPTX1 IS A NOVEL SERUM BIOMARKER INDUCED BY ARPI TREATED PROSTATE CANCER AND ENRICHED IN LINEAGE PLASTICITY WITH BRN2 HIGH Takeshi Namekawa, Joshua Scurll, Maxim Kobelev, Dwaipayan Ganguli, Olena Sivak, Martin Gleave, Vancouver, Canada, Eva Corey, Colm Morrissey, and Amina Zoubeidi Takeshi NamekawaTakeshi Namekawa More articles by this author , Joshua ScurllJoshua Scurll More articles by this author , Maxim KobelevMaxim Kobelev More articles by this author , Dwaipayan GanguliDwaipayan Ganguli More articles by this author , Olena SivakOlena Sivak More articles by this author , Martin GleaveMartin Gleave More articles by this author , Vancouver Vancouver More articles by this author , Canada Canada More articles by this author , Eva CoreyEva Corey More articles by this author , Colm MorrisseyColm Morrissey More articles by this author , and Amina ZoubeidiAmina Zoubeidi More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003245.07AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Androgen receptor (AR) pathway inhibition is the first-line therapy for metastatic prostate cancer (PCa). However, tumors invariably develop resistance to ARPI. We previously identified a transcription factor Brain-2 (BRN2), encoded by the gene POU3F2, as a master driver of NEPC which is an aggressive form of AR-independent phenotypes treatment resistant PCa. In this study, we identified a surrogate biomarker of BRN2 activity to monitor the progression of treatment resistant PCa. METHODS: To identify BRN2 serum marker, we analyzed BRN2 ChIPseq data from 2 NEPC and 2 neural-type lung squamous cell carcinoma (nLUSC) cell lines with a focus on shared BRN2 peaks. Annotated peaks from enhancers (EnhancerAtlas) and promoters (genes within 20kb) were selected for secreted proteins and were ranked by correlation with BRN2 expression in PCa patients. Validation of protein expression was performed by western blot. R-PLEX Assay kit was used to measure concentrations in culture media from NCI-H660 cells and in serum from mice with NCI-H660 xenograft or PDX tumors and from human PCa patients. RESULTS: We identified 51 candidate serum biomarkers for BRN2 activity (or expression?) using the methods described above. These biomarkers were ranked based on their expression and correlation with BRN2 expression in PCa patient samples across four public data sets. NPTX1 was identified as the top biomarker of BRN2 expression. We further validated association of NPTX1 and BRN2 expression by BRN2 overexpression in MR42D and 22Rv1, indicating that BRN2 positively regulates NPTX1 expression. Next, we showed that NPTX1 is present in culture media from NCI-H660 cells, and that NPTX1 serum concentration positively correlated with tumor volume in mice with NCI-H660 xenografts and with NPTX1 mRNA expression in LuCaP PDX models. Importantly, evaluation of patients’ samples showed that NPTX1 levels were high in 26/35 CRPC serum samples vs levels in serum of healthy volunteers, and that the NPTX1 serum levels were highest in 4/6 patients with high POU3F2 tumor expression. CONCLUSIONS: We identified and validated NPTX1 as a serum marker that can be readily detected in serum from NEPC patients with BRN2high tumours. Source of Funding: U.S. Army Medical Research and Development Command(W81XWH1810689) © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e277 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Takeshi Namekawa More articles by this author Joshua Scurll More articles by this author Maxim Kobelev More articles by this author Dwaipayan Ganguli More articles by this author Olena Sivak More articles by this author Martin Gleave More articles by this author Vancouver More articles by this author Canada More articles by this author Eva Corey More articles by this author Colm Morrissey More articles by this author Amina Zoubeidi More articles by this author Expand All Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".