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Identification Of Prostate Cancer Bone Metastasis Related Genes And Potential Therapy Targets By Bioinformatics And In Vitro Experiments.

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Identification Of Prostate Cancer Bone Metastasis Related Genes And Potential Therapy Targets By Bioinformatics And In Vitro Experiments.

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An Orthotopic Murine Model of Human Prostate Cancer Metastasis

An Orthotopic Murine Model of Human Prostate Cancer Metastasis

Published on: September 18, 2013

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

Haiyang Jiang^1,2, Mingcheng Liu³, Yingfei Deng⁴

¹Department of Urology I, The Third Affiliated Hospital of Kunming Medical University (Peking University Cancer Hospital Yunnan, Yunnan Cancer Hospital, Cancer Center of Yunnan Province), Kunming, Yunnan, China.

Journal of Cellular and Molecular Medicine

|August 4, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Researchers identified seven key genes driving prostate cancer bone metastasis. APOC1, a highly expressed gene, significantly impacts cancer progression and may serve as a therapeutic target.

Keywords:

bone metastasis cell communication hub genes machine learning prostate cancer single cell analysis

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Related Experiment Videos

An Orthotopic Murine Model of Human Prostate Cancer Metastasis

An Orthotopic Murine Model of Human Prostate Cancer Metastasis

Published on: September 18, 2013

Pre-clinical Orthotopic Murine Model of Human Prostate Cancer

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Published on: August 29, 2016

Author Spotlight: Advancing Prostate Cancer Research Through Improved Tissue Sampling and Biobanking

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Published on: November 17, 2023

Area of Science:

Oncology
Genetics
Molecular Biology

Background:

The mechanisms behind prostate cancer (PCa) bone metastasis are not fully understood.
Identifying key genetic drivers is crucial for developing targeted therapies.

Purpose of the Study:

To identify hub genes associated with bone metastasis in prostate cancer.
To explore potential therapeutic targets and prognostic markers for PCa bone metastasis.

Main Methods:

Utilized machine learning, Gene Ontology (GO), KEGG, Gene Set Enrichment Analysis (GSEA), single-cell analysis, and Receiver Operating Characteristic (ROC) methods.
Analyzed data from TCGA and GEO databases, validated findings with patient specimens, and conducted in vitro experiments.

Main Results:

Identified seven hub genes (APOC1, CFH, NUSAP1, LGALS1, NR4A2, ADRB2, ZNF331) with high diagnostic accuracy (AUC 0.727-0.926).
Found APOC1, CFH, NUSAP1, and LGALS1 upregulated in bone metastasis tissues.
Discovered that APOC1 silencing inhibits PCa cell proliferation, clonality, and migration in vitro, and is linked to clinical features.

Conclusions:

Seven hub genes, particularly APOC1, are implicated in prostate cancer bone metastasis through mitochondrial metabolic reprogramming.
APOC1 shows promise as a therapeutic target and prognostic marker for prostate cancer with bone metastasis.