ArticleOncology letters2015
Genomic profiling screens small molecules of metastatic prostate carcinoma.
Article in Oncology letters, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 19 citations in OpenAlex.
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- Identification of potential immunotherapy biomarkers for breast cancer by bioinformatics analysis.Bioscience reports · 2022Article
- Sperm Autoantigenic Protein 17 Predicts the Prognosis and the Immunotherapy Response of Cancers: A Pan-Cancer Analysis.Frontiers in immunology · 2022Article
- Identification of Signature Genes and Construction of an Artificial Neural Network Model of Prostate Cancer.Journal of healthcare engineering · 2022Article
- Genome-wide RNA-sequencing dataset reveals the prognostic value and potential molecular mechanisms of lncRNA in non-homologous end joining pathway 1 in early stage Pancreatic Ductal Adenocarcinoma.Journal of Cancer · 2020Article
- Gene expression feature selection for prostate cancer diagnosis using a two-phase heuristic-deterministic search strategy.IET systems biology · 2018Article
- Integrative molecular network analysis identifies emergent enzalutamide resistance mechanisms in prostate cancer.Oncotarget · 2017Article
- Inhibition of KPNA4 attenuates prostate cancer metastasis.Oncogene · 2017Article
- Microarray and qPCR Analyses of Wallerian Degeneration in Rat Sciatic Nerves.Frontiers in cellular neuroscience · 2017Article
- Novel Nine-Exon AR Transcripts (Exon 1/Exon 1b/Exons 2-8) in Normal and Cancerous Breast and Prostate Cells.International journal of molecular sciences · 2016Article
- Paradoxical overexpression of MBNL2 in hepatocellular carcinoma inhibits tumor growth and invasion.Oncotarget · 2016Article
- Ingenuity Pathway Analysis of Gene Expression Profiles in Distal Nerve Stump following Nerve Injury: Insights into Wallerian Degeneration.Frontiers in cellular neuroscience · 2016Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the present study was to investigate the pathogenesis of metastatic prostate carcinoma, to find the metabolic pathways changed in the disease and to screen out the potential therapeutic drugs. GSE38241 was downloaded from Gene Expression Omnibus; the Geoquery package was applied to preprocessed expression profiling, and the differentially-expressed genes (DEGs) were selected with limma (linear regression model packages). Next, WikiPathways cluster analysis was performed for DEGs on a Gene Set Analysis Toolkit V2 platform, and DEGs with hypergeometric algorithms were calculated through gene set enrichment analysis. A total of 1,126 DEGs were identified between the normal prostate and metastatic prostate carcinoma. In addition,
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