Lu Zhang , Jianxin Ying , Jian Ke , Likun Ma , Yamin Zhou
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引用次数: 0
Abstract
Background and Objective
Prostate cancer (PCa) is the second most commonly diagnosed cancer in males, the mechanism of PCa with bone metastasis remains unclear. In this study, we aimed to utilize a retrospective clinical study to evaluate the diagnostic value of bone metastases from PCa and provide reference values for future applications.
Methods
We retrospectively collected a total of 200 samples including 100 PCa patients with bone metastatic and 100 without from June 2019 to August 2021. Transrectal ultrasonography (TRUS) was applied for observing the microvascular blood flow in the lesion. The serum levels of prostate specific antigen (PSA), vascular endothelial growth factor 2 (VEGF2), interleukin-6 (IL-6) and Pro-gastrin-releasing peptide (ProGRP) was determined using Enzyme-linked immunosorbent assay Kit. Regression model was constructed to analyze the risk factors for PCa with bone metastasis, the prognosis value of which was evaluated using receiver operating characteristic (ROC) curves. Ultimately, dataset GSE32269 was employed for validation.
Results
The focal blood perfusion was significantly improved in patients with bone metastasis than those without (P < 0.01). The examination results indicated that PCa patients with bone metastasis had higher levels of PSA, VEGF2, IL-6 and ProGRP than non-bone metastasis (P < 0.01). Moreover, the regression analysis indicated that the four cytokines were the risk factors for bone metastasis, and the ROC curves further confirmed that PSA and VEGF2 had high value of prediction value for bone metastasis with AUC of 0.901 and 0.8519.
Conclusion
The expression of PSA and VEGF2 in serum had high prognosis value for bone metastasis in PCa patients.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered.
Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.