Student and Faculty Publications
Publication Date
1-1-2023
Journal
Technology in Cancer Research & Treatment
Abstract
PURPOSE: Owing to the mortality associated with metastatic prostate cancer and the shortcomings of the current parameters in predicting the disease prognosis, we require the identification of viable biomarkers, which would help in the diagnosis and prognosis of the disease. We aimed to determine whether the interleukin-8 level in the tumor microenvironment could serve as a potential clinical diagnostic marker and prognostic factor for prostate cancer.
METHODS: The migration assay of prostate cancer cells was performed in an in vitro co-culture model. Cell lines PC3 and DU145 were divided into two groups and co-cultured with M0 and M2 macrophages, respectively. We used reverse transcription-quantitative polymerase chain reaction to detect M2 macrophage marker expression levels. Immunohistochemistry analyses of tissue microarrays were performed to analyze the correlation between the increased expression of interleukin-8 and the prognosis of prostate cancer. A retrospective analysis based on 142 residual serum specimens was performed to analyze the level of interleukin-8.
RESULTS: We observed that M2 macrophages promoted the migration of prostate cancer cells and significantly increased the concentrations of interleukin-8 in the co-culture supernatants. We observed increased expression of CD163 and interleukin-8 in prostate cancer tissues. Furthermore, the levels of interleukin-8 in the serum of prostate cancer patients were higher than those in healthy controls. Untreated patients had higher levels of interleukin-8, which could be a predictor of a higher metastasis rate.
CONCLUSION: These results suggest that interleukin-8 produced via bidirectional communication between prostate cancer cells and M2 macrophages is a putative biomarker for prostate cancer diagnosis and treatment.
Keywords
interleukin-8, prostate cancer, M2 macrophage, benign prostatic hypertrophy, biomarker
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Medical Sciences Commons, Oncology Commons
Comments
PMID: 37226533