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Record W4409630140 · doi:10.1158/1538-7445.am2025-4320

Abstract 4320: Investigating the role of the RNA-binding protein DEAD box ATPase 55 (DDX55) in castration resistant prostate cancer

2025· article· en· W4409630140 on OpenAlexaff
Ziwei Cai, Syam Prakash Somasekharan

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsProstate cancerDEAD boxCancerATPaseCancer researchBiologyRNAMedicineInternal medicineBiochemistryEnzymeGene

Abstract

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Abstract Prostate cancer (PCA) is the second most frequent cancer diagnosis made in men with a global death rate of 0.4 million every year. Most PCA development requires the activity of androgen receptor (AR) activity, which required the binding of androgen. Therefore, a significant number of patients receive androgen deprivation therapy (ADT) that reduces the level of androgens, leading to a reduction in cancer growth. However, due to selective pressure, the treated PCA can relapse and become castration-resistant prostate cancer (CRPC) which is androgen-independent and highly invasive and metastatic. An urgent need for research to identify standard biomarkers and therapeutic targets are required to better manage CRPC. DEAD-box helicases are highly conserved, multifunctional proteins, many of which play a role in promoting cancer progression. However, their involvement in prostate cancer progression remains largely unexplored. DDX55, a recently discovered DEAD-box helicase, has not yet been studied in the context of prostate cancer, and its function remains uncharacterized. Our preliminary data suggests that DDX55 protein is more highly expressed in castration-resistant prostate cancer (CRPC) compared to hormone-naïve prostate cancer (HNPC). Gene expression studies using next-generation RNA sequencing revealed that silencing DDX55 reduces the expression of several AR downstream target genes, without affecting AR mRNA expression or protein levels. By further analysis, we confirmed that DDX55 silencing reduced the activity of AR, and re-expression of a DDX55 plasmid restored AR activity in DDX55 silenced cancer cells. By co-immunoreaction and mass spectrometry, we found DDX55 is complex with AR and AR coregulator and histone acetylase CBP. We observed silencing of DDX55 reduced epigenetic H3K27ac mark required for open chromatin conformation. Additionally, re-expression of a DDX55 plasmid in DDX55 silenced cells restored AR activity and H3K27ac. We propose that DDX55 regulates CBP for H3K27ac to induce chromatin accessibility for the expression of AR downstream target genes. To further understand this, we conducted pilot animal experiments, and found that DDX55 is a regulator of PCA progression. Our project will characterize DDX55 in prostate cancer by analysing its expression in a large repertoire of cancer specimens to determine its potential as a diagnostic marker, investigate the molecular mechanism through which DDX55 regulates AR activation, with the goal of identifying new therapeutic targets for prostate cancer, and develop an animal model to study the role of DDX55 in cancer progression to study its involvement in vivo invasion and metastasis. This research is expected to advance our understanding of the mechanisms of prostate cancer progression and help identify ways to target it for improved management of the disease. Citation Format: Ziwei (Mia) Cai, Syam Somasekharan. Investigating the role of the RNA-binding protein DEAD box ATPase 55 (DDX55) in castration resistant prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4320.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.354
Teacher spread0.323 · 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 designBench or experimental
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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