An Integrative Multi-Omics Analysis Based on Nomogram for Predicting Prostate Cancer Bone Metastasis Incidence

Area of Science:

• Oncology
• Genomics
• Bioinformatics

Background:

• Bone metastasis is common in prostate cancer.
• Genomic and clinical research is ongoing for bone metastatic prostate cancer.
• Identifying patients at elevated risk of bone metastasis is crucial.

Purpose of the Study:

• To develop a predictive nomogram for prostate cancer bone metastasis.
• To identify genomic and molecular differences between high-risk and low-risk bone metastasis cohorts.

Main Methods:

• Utilized Surveillance, Epidemiology, and End Results (SEER) database to construct a predictive nomogram.
• Applied the nomogram to The Cancer Genome Atlas (TCGA) prostate cancer cohort to stratify patients.
• Performed comparative analyses of mutational landscapes, gene expression, and immune activity between risk cohorts.

Main Results:

• Developed a nomogram accurately predicting bone metastasis risk.
• Identified significant differences in gene fusions, copy number variations (CNVs), and single nucleotide variations (SNVs), particularly in the P53 gene, in high-risk patients.
• Constructed a competing endogenous RNA (ceRNA) network and identified hub genes (KIF14, MYH7, COL10A1).
• Observed elevated immune response activity and increased immune checkpoint signature in high-risk patients.

Conclusions:

• Successfully developed a nomogram for early detection of prostate cancer patients at elevated risk of bone metastasis.
• The findings provide insights into the molecular mechanisms underlying bone metastasis in prostate cancer.