Evidence map›Paper›PMID 39703506›Full record

ArticleFrontiers in immunology2024

Immune-related diagnostic markers for benign prostatic hyperplasia and their potential as drug targets.

YaXuan Wang, Jing Wang, Jibin Liu, HaiXia Zhu

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–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

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

YaXuan Wang *Cancer Research Centre Nantong, Affiliated Tumor Hospital of Nantong University & Nantong Tumor Hospital, Nantong, China.
Jing Wang *Department of Oncology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China.
Jibin LiuCancer Research Centre Nantong, Affiliated Tumor Hospital of Nantong University & Nantong Tumor Hospital, Nantong, China.
HaiXia ZhuCancer Research Centre Nantong, Affiliated Tumor Hospital of Nantong University & Nantong Tumor Hospital, Nantong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Benign prostatic hyperplasia (BPH) is a common issue among older men. Diagnosis of BPH currently relies on imaging tests and assessment of urinary flow rate due to the absence of definitive diagnostic markers. Developing more accurate markers is crucial to improve BPH diagnosis. Method: The BPH dataset utilized in this study was sourced from the Gene Expression Omnibus (GEO). Initially, differential expression and functional analyses were conducted, followed by the application of multiple machine learning techniques to identify key diagnostic markers. Subsequent investigations have focused on elucidating the functions and mechanisms associated with these markers. The ssGSEA method was employed to evaluate immune cell scores in BPH samples, facilitating the exploration of the relationship between key diagnostic markers and immune cells. Additionally, molecular docking was performed to assess the binding affinity of these key markers to therapeutic drugs for BPH. Tissue samples from BPH patients were collected for experimental validation of the expression differences of the aforementioned genes. Result: A total of 185 differential genes were identified, comprising 67 up-regulated and 118 down-regulated genes. These genes are implicated in pathways that regulate extracellular matrix tissue composition and cellular responses to transforming growth factor beta stimulation, as well as critical signaling pathways such as AMPK and mTOR. Through the application of various machine learning techniques, DACH1, CACNA1D, STARD13, and RUNDC3B were identified as key diagnostic markers. The ssGSEA algorithm further corroborated the association of these diagnostic genes with diverse immune cells. Moreover, molecular docking analysis revealed strong binding affinities of these markers to tamsulosin and finasteride, suggesting their potential as drug targets. Finally, experimental validation confirmed the expression differences of DACH1, CACNA1D, STARD13, and RUNDC3B in BPH tissues. Conclusion: This study introduces novel immune-related diagnostic markers for BPH and highlights their promise as new drug targets, providing a valuable approach for predictive diagnosis and targeted therapy of BPH.

Indexed as

BiomarkersMolecular Docking SimulationProstatic HyperplasiaGene Expression ProfilingHumansMachine LearningMaleTranscriptomeBiomarkersbiomarkersBPHdrug targetimmune signaturesmachine learning

Identifiers

PMID39703506
PMCPMC11655502

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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.