ArticleGenes & diseases2026
Integrative high-throughput studies to develop novel targets and drugs for the treatment of advanced prostate cancer.
Article in Genes & diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A fatty acid metabolism-based deep learning model predicts biochemical recurrence and identifies NUDT19 as a candidate metabolic factor in prostate cancer.World journal of surgical oncology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Androgen deprivation therapies targeting the androgen receptor (AR) signaling pathway are the primary treatment strategy for prostate cancer. However, these therapies often lead to castration resistance. Developing novel agents targeting AR-independent oncogenes is critical to address this challenge, particularly for advanced castration-resistant prostate cancer. This study identified three potential tumor drivers of advanced prostate cancer, including CDC20, DTL, and RRM2, through integrative bioinformatic screening that considered gene dependency using CRISPRi/RNAi database, clinical relevance, and experimental validation with CRISPR-Cas13-mediated gene ablation. Further mechanistic studies revealed that CDC20, DTL, and RRM2 were transcriptionally regulated by the RB1/E2F1 axis, mediating cell cycle progression in prostate cancer. Additionally, we identified novel agents targeting these candidates through virtual screening and drug-sensitive tests, utilizing our established small-molecule library. These agents exhibited superior anti-tumor efficacy compared with AR antagonists
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.