Evidence map›Paper›PMID 40656519›Full record

ArticleHuman mutation2025

Identification of Enzalutamide-Related Genes for Prognosis and Immunotherapy in Prostate Adenocarcinoma.

Lian Fang, Zongming Jia, Tao Zou, Ouyang Song, Jun Ouyang, Yufeng Hou, Zhiyu Zhang, Xuefeng Zhang

Abstract read
In one paragraph

Article in Human mutation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Lian FangDepartment of Urology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.ORCID 0009-0009-8831-9481
Zongming JiaDepartment of Urology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Tao ZouDepartment of Urology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Ouyang SongDepartment of Urology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Jun OuyangDepartment of Urology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.ORCID 0009-0004-5273-7845
Yufeng HouDepartment of Urology, The Fourth Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
Zhiyu ZhangDepartment of Urology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.ORCID 0000-0001-5499-8011
Xuefeng ZhangDepartment of Urology, First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.ORCID 0000-0001-6731-6665

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Enzalutamide is classified as a novel antiandrogen medication; however, the majority of patients ultimately develop resistance to it. Consequently, conducting an in-depth investigation into potential targets of enzalutamide is essential for addressing the drug resistance observed in patients and for facilitating the discovery of new therapeutic targets. The SwissTargetPrediction database was used to identify targets linked to enzalutamide and to assess these targets in the prostate adenocarcinoma (PRAD) dataset sourced from the TCGA database. By employing various datasets and applying different machine learning methods for clustering, researchers constructed and validated both diagnostic and prognostic models for PRAD. A correlation analysis with the androgen receptor revealed TDP1 as the gene most significantly associated with enzalutamide. In addition, this study examined the relationship between TDP1 and immune infiltration. The expression levels of TDP1 and its prognostic correlation in PRAD patients were validated through immunofluorescence staining of 60 PRAD tissue specimens. Cluster analysis revealed a notable correlation among the 24 genes related to enzalutamide with regard to both prognosis and immune infiltration in PRAD patients. The diagnostic model, which incorporates various machine learning techniques, exhibits robust predictive ability for PRAD diagnosis, while the prognostic model employing the LASSO algorithm has also shown encouraging outcomes. Among the various prognostic genes linked to enzalutamide, TDP1 stands out as an important indicator of prognosis. Furthermore, immunofluorescence experiments confirmed that an increased expression of TDP1 is associated with a worse prognosis in patients with PRAD. Our results underscore the substantial potential of TDP1 as a novel diagnostic and prognostic biomarker for individuals diagnosed with PRAD.

Indexed as

AdenocarcinomaImmunotherapyPhenylthiohydantoinProstatic NeoplasmsBenzamidesBiomarkers, TumorDatabases, GeneticDrug Resistance, NeoplasmGene Expression Regulation, NeoplasticHumansMachine LearningMaleNitrilesPrognosisReceptors, AndrogenBenzamidesBiomarkers, TumorenzalutamideNitrilesPhenylthiohydantoinReceptors, Androgenbiomarkerenzalutamidegene functionmachine learningprognosis

Identifiers

PMID40656519
PMCPMC12253995

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.