ArticleOncoTargets and therapy2017
Identification of key pathways and genes with aberrant methylation in prostate cancer using bioinformatics analysis.
Article in OncoTargets and therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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
9 citing papers in PubMed, 15 citations in OpenAlex.
- DiCE: differential centrality-ensemble analysis based on gene expression profiles and protein-protein interaction network.Nucleic acids research · 2025Article
- DiCE: differential centrality-ensemble analysis based on gene expression profiles and protein-protein interaction network.bioRxiv : the preprint server for biology · 2025Article
- Early detection and diagnosis of cancer with interpretable machine learning to uncover cancer-specific DNA methylation patterns.Biology methods & protocols · 2024Article
- Integrative analysis of transcriptomic and metabolomic profiles reveals enhanced arginine metabolism in androgen-independent prostate cancer cells.BMC cancer · 2023Article
- Analysis of genetic biomarkers, polymorphisms in ADME-related genes and their impact on pharmacotherapy for prostate cancer.Cancer cell international · 2023Review
- Prostate Cancer: Genetics, Epigenetics and the Need for Immunological Biomarkers.International journal of molecular sciences · 2023Review
- Quantitative SWATH-Based Proteomic Profiling for Identification of Mechanism-Driven Diagnostic Biomarkers Conferring in the Progression of Metastatic Prostate Cancer.Frontiers in oncology · 2020Article
- The Relevance of Gender in Tumor-Influencing Epigenetic Traits.Epigenomes · 2019Review
- The future of prostate cancer research: bringing data together, looking back and forward.Translational andrology and urology · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prostate cancer (PCa), a multifocal clinically heterogeneous disease, is the most commonly diagnosed non-cutaneous neoplasm in men worldwide. The epigenome of PCa is a typical representation of catastrophic model of epigenetic alterations during tumorigenesis and its progression. Alterations in methylation patterns in tumor suppressors, cell cycle, oncogenes and metabolism-related genes are the most commonly observed epigenetic alterations in PCa. In this study, we have developed a computational strategy to identify methylated biomarker signature panels as potential targets of PCa by screening >160 genes reported to be epigenetically dysregulated, and shortlisted 26 differentially methylated genes (DMGs) that significantly contribute to oncogenesis. The gene ontology and functional enrichment analysis were performed, which showed that identified DMGs contribute to cellular and metabolic processes such as cell communication, cell cycle, response to drugs, apoptosis and p53 signaling. The top hub genes
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.