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MP68-10 HOXB13 EXPRESSION AND ITS ROLE IN PROSTATE CANCER PROGRESSION AND NEUROENDOCRINE DIFFERENTIATION

2019· article· en· W2929490553 on OpenAlexaboutno aff
Farzana Faisal, Mohammed Alshalalfa, Elai Davicioni, R. Jeffrey Karnes, William Isaacs, Tamara L. Lotan, Edward M. Schaeffer

Bibliographic record

VenueThe Journal of Urology · 2019
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProstate cancerNeuroendocrine differentiationCancerProstateExpression (computer science)OncologyInternal medicine

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyProstate Cancer: Basic Research & Pathophysiology II (MP68)1 Apr 2019MP68-10 HOXB13 EXPRESSION AND ITS ROLE IN PROSTATE CANCER PROGRESSION AND NEUROENDOCRINE DIFFERENTIATION Farzana Faisal*, Mohammed Alshalalfa, Elai Davicioni, R. Jeffrey Karnes, William Isaacs, Tamara Lotan, and Edward Schaeffer Farzana Faisal*Farzana Faisal* , Mohammed AlshalalfaMohammed Alshalalfa , Elai DavicioniElai Davicioni , R. Jeffrey KarnesR. Jeffrey Karnes , William IsaacsWilliam Isaacs , Tamara LotanTamara Lotan , and Edward SchaefferEdward Schaeffer View All Author Informationhttps://doi.org/10.1097/01.JU.0000557025.09954.39AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: HOXB13 expression is involved in normal prostate development, is a known regulator of androgen receptor (AR)-mediated transcriptomes in prostatic tissue, and is also maintained in the formation of prostatic adenocarcinoma (PCa). In breast and other hormone-sensitive gynecological cancers, deregulated expression of HOXB13 correlates with aggressive tumor phenotypes and poor response to hormonal therapies. The predictive role of HOXB13 expression within prostate tumor progression and its associated outcomes remains unexplored. METHODS: We utilized HOXB13 RNA transcriptome expression from several datasets of PCa radical prostatectomy (RP) genome-wide expression profiles from the Decipher GRID registry and public cohorts (n=6,679). We compared levels of HOXB13 expression by tumor progression and by histology (adenocarcinoma, neuroendocrine/small cell). We assessed the association of HOXB13 expression with pathologic/oncologic outcomes and risk of metastasis based on genomic signatures (Decipher score). Finally, we analyzed gene expression profiling of canonical AR and AR-V7 targets to investigate the association of HOXB13 with AR signaling. RESULTS: There was a stepwise increase in the expression of HOXB13 from benign tissue, to primary tumor, to metastatic PCa (p=0.01). Increased levels of HOXB13 expression were associated with higher pathologic grade group (p<0.001), metastasis (p=0.001), and higher Decipher scores (p<0.001). In two retrospective cohorts (Hopkins, Mayo), higher HOXB13 expression was associated with decreased metastasis-free survival (p=0.02 and p=0.003, respectively). HOXB13 expression was also highly correlated to AR/AR-V7 target genes, NKX3-1 (r=0.73), and FOXA1 (r=0.67). Lower HOXB13 was associated with neuroendocrine biomarkers NCAM1 and ASXL3. Furthermore, HOXB13 expression was decreased in metastatic castrate-resistant PCa and neuroendocrine and small cell prostatic carcinoma (p<0.001). CONCLUSIONS: In primary PCa, HOXB13 expression increases with progression and is associated with higher AR signaling and adverse pathologic and oncologic outcomes. Though, its expression is lowered when PCa becomes castrate-resistant and when these cancers develop neuroendocrine differentiation. These data support the hypothesis that increased levels of HOXB13 confer a more aggressive PCa phenotype with metastatic potential. Future research can explore the role of HOXB13 not only as a biomarker of aggressive disease but also as a therapeutic target in PCa. Source of Funding: None Baltimore, MD; Vancouver, Canada; Rochester, MN; Baltimore, MD; Chicago, IL© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e979-e979 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Farzana Faisal* More articles by this author Mohammed Alshalalfa More articles by this author Elai Davicioni More articles by this author R. Jeffrey Karnes More articles by this author William Isaacs More articles by this author Tamara Lotan More articles by this author Edward Schaeffer More articles by this author Expand All Advertisement PDF downloadLoading ...

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 score0.040
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0400.006

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 head0.013
GPT teacher head0.316
Teacher spread0.304 · 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
Published2019
Admission routes1
Has abstractyes

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