Objective: To evaluate the application of CXC chemokine receptor-4 (CXCR4) combined with alpha-methylacyl-CoA racemase (P504S) or P63 protein in the differential diagnosis of benign and malignant prostatic diseases.
Methods: The EnVision immunohistochemical method was used to detect the expressions of CXCR4, P504S and P63 protein in 40 specimens of PCa not treated by any anticancer therapy and 30 specimens of BPH tissues. The correlation was analyzed between CXCR4 expression and the characteristics of PCa metastasis.
Results: Of the 40 cases of PCa, 33 (82.5%) were stained positive for CXCR4, 37 (92.5%) for P504S and 2 (5%) for P63 protein. Of the 30 cases of BPH, 5 (16.6%) exhibited positivity for CXCR4, 1 for P504S and all for P63. P504S + P63 showed a higher rate of correct diagnosis of PCa than either CXCR4 + P63 or P504S + CXCR4. There was a statistically significant correlation between CXCR4 expression and cancer metastasis (P < 0.05).
Conclusion: P504S, CXCR4 and P63 are useful tumor markers for the diagnosis and differentiation of benign and malignant prostatic diseases. CXCR4 gives a high rate of correct diagnosis when combined with P504S or P63, and has an important application value in the differential diagnosis of benign and malignant prostatic diseases.
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Article Synopsis
- A noninvasive machine learning model was developed to detect P504s/P63 status and diagnose prostate cancer (PCa) using preoperative MRI data.
- A retrospective analysis involved 315 patients, categorizing them into atypical hyperplasia, benign prostatic hyperplasia, and PCa based on P504s/P63 expression, with radiomic features extracted from MRI sequences.
- The random forest algorithm showed the best performance with an AUC of 0.920, indicating its effectiveness in accurately predicting prostate conditions when using T2WI sequences combined with other methodologies.
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