Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and in vitro experiments

1 Aug 2024

Abstract excerpt

The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cancer, Lipids, and Metabolism
Share to Prostate Cancer Treatment and Research
Share to RNA modifications and cancer

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 39098992
DOI: 10.1111/jcmm.18511

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and in vitro experimentsPMID 39098992Read ↗

Identification of the hub genes associated with prostate cancer tumorigenesisSemantic proximity Read ↗

ARPC1A correlates with poor prognosis in prostate cancer and is up-regulated by glutamine metabolism to promote tumor cell migration, invasion and cytoskeletal changesSemantic proximity Read ↗

Prostate cancer invasion and metastasis: insights from mining genomic dataSemantic proximity Read ↗

Bioinformatics analysis identified hub genes in prostate cancer tumorigenesis and metastasisSemantic proximity Read ↗

Joint analysis of WES and RNA-Seq identify signature genes related to metastasis in prostate cancer.Semantic proximity Read ↗

Identification of metastasis-related genes for predicting prostate cancer diagnosis, metastasis and immunotherapy drug candidates using machine learning approachesSemantic proximity Read ↗

An Amplified Fatty Acid-Binding Protein Gene Cluster in Prostate Cancer: Emerging Roles in Lipid Metabolism and MetastasisSemantic proximity Read ↗

Identification of prostate cancer hub genes and therapeutic agents using bioinformatics approachSemantic proximity Read ↗

Identification of HCG18 and MCM3AP-AS1 That Associate With Bone Metastasis, Poor Prognosis and Increased Abundance of M2 Macrophage Infiltration in Prostate CancerSemantic proximity Read ↗

Candidate biomarkers and gene modules investigation for bone tumor samples derived from castration-resistant prostate cancer bone metastasis patients using WGCNASemantic proximity Read ↗

Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysisSemantic proximity Read ↗

Identification and validation of hub genes based on machine learning in prostate cancer and AOX1 is an oxidative stress-related biomarkerSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.