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Abstract B013: Chromosomal rearrangements at the YAP/TAZ pathway genes are associated with heterogeneity and stem cell-like castration-resistant prostate cancer

2025· article· en· W4417001662 on OpenAlexaff
Marjorie Roskes, Alexander Martinez‐Fundichely, Sandra Cohen, Metin Balaban, Chen Khuan Wong, Weiling Li, T. González, Anisha B. Tehim, Hao Xu, Shahd ElNaggar, Matthew Myers, Andrea Sboner, Benjamin J. Raphael, Yu Chen, Ekta Khurana

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHippo pathway signaling and YAP/TAZ
Canadian institutionsMcGill University
Fundersnot available
KeywordsEpigenomicsProstate cancerAndrogen receptorEpigeneticsTranscriptomeChromoplexyGeneChromatinCancer

Abstract

fetched live from OpenAlex

Abstract Untreated prostate tumors depend on androgen receptor (AR) for growth and thus are treated with hormonal therapy. However, resistance almost always emerges as tumors evolve into a castration-resistant state. The evolution of resistance can follow different paths, and castration-resistant prostate cancer (CRPC) exhibits multiple epigenomic subtypes: androgen receptor-dependent CRPC-AR, and lineage plastic subtypes CRPC-SCL (stem cell-like), CRPC-WNT (Wnt-dependent), and CRPC-NE (neuroendocrine). By transcriptomic profiling of tissue, and whole-genome sequencing (WGS) of tissue and cell-free DNA (cfDNA) from 500 patient samples, we relate genomic variants with epigenomic state. We annotate fractional contribution of each subtype for all patient samples using deconvolution approaches with a set of signature genes and accessible chromatin sites. We confirm that AR amplifications at the genomic level are associated with the emergence of CRPC-AR, and RB1 biallelic loss is associated with CRPC-NE. Importantly, we find chromosomal rearrangements in the YAP/TAZ pathway are associated with the presence of CRPC-SCL. In particular, we find complex rearrangements on chromosome 4, which are supported by patient-matched Hi-C data, and decrease promoter interactions of MOB1B, a YAP/TAZ pathway inhibitor, with its enhancers. Together, the genomic variants in the pathway can predict CRPC-SCL with 79% accuracy. By computing cancer cell fraction (CCF) of the genomic events, we find high concordance between the CCF of genomic events and the fraction of their associated epigenomic subtype. Thus, higher CCF of chr 4 rearrangements corresponds to higher tumor fraction of CRPC-SCL. Our study shows how genomic events enable transition to different CRPC states that exhibit differential therapeutic susceptibilities. Citation Format: Marjorie Roskes, Alexander Martinez-Fundichely, Sandra Cohen, Metin Balaban, Chen Khuan. Wong, Weiling Li, Tonatiuh A. Gonzalez, Anisha B. Tehim, Hao Xu, Shahd ElNaggar, Matthew Myers, Andrea Sboner, Benjamin J. Raphael, Yu Chen, Ekta Khurana. Chromosomal rearrangements at the YAP/TAZ pathway genes are associated with heterogeneity and stem cell-like castration-resistant prostate cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Cancer Evolution: The Dynamics of Progression and Persistence; 2025 Dec 4-6; Albuquerque, NM. Philadelphia (PA): AACR; Cancer Res 2025;85(23_Suppl):Abstract nr B013.

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 score0.008
Threshold uncertainty score0.026

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.041
GPT teacher head0.332
Teacher spread0.290 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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