Abstract
Background: Systemic metastasis is the main cause of death in patients with prostate cancer. It is necessary to establish a more accurate model to distinguish and predict patients with a high risk of metastasis to optimize individualized treatment.Methods: In this study, it was determined that hypoxia could affect the metastasis-free survival of patients with prostate cancer, and a hypoxia-related gene signature composed of seven genes for predicting metastasis was established and verified in different cohorts. The study further evaluated the effects of ALDOB expression on the proliferation and invasion of the LNCaP and DU145 cell lines under hypoxia and finally constructed a nomogram containing specific clinical characteristics of prostate cancer combined with the hypoxia gene signature to quantify the metastasis risk of individual patients.Results: The hypoxia-related gene signature was identified as an independent risk factor for metastasis-free survival in patients with prostate cancer. The expression of ALDOB increased under hypoxia and promoted the proliferation and invasion of LNCaP and DU145 cells. In addition, patients with a high risk score showed therapeutic resistance and immunosuppression. Compared with other parameters, the nomogram had the strongest predictive power and net clinical benefit.Conclusion: The study established a hypoxia-related gene signature and a nomogram to distinguish and predict patients with a high risk of prostate cancer metastasis, which may help to optimize individualized treatment and explore possible therapeutic targets.
Highlights
Prostate cancer is a global health threat
The single sample gene set enrichment analysis (ssGSEA) score among 50 pathological pathways was included in univariate Cox regression analysis to evaluate the effect of each pathological pathway on metastasis-free survival (MFS) (Supplementary File 2)
Patients were divided into high z-score and low z-score groups according to the median z-score for hypoxia
Summary
According to statistics published in 2020, among the 19.3 million new cancer cases, there were 1,414,259 cases of prostate cancer, accounting for 7.3% of the total cases and ranking third among 36 cancers (Sung et al, 2021). Of those diagnosed with prostate cancer, 3.8% face death, and systemic metastases remain the leading cause of death. It is necessary to establish a more accurate model to distinguish and predict patients with a high risk of metastasis to optimize individualized treatment
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