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Cell line modeling to study biomarker panel in prostate cancer.

ABSTRACT: African-American men with prostate cancer (PCa) present with higher-grade and -stage tumors compared to Caucasians. While the disparity may result from multiple factors, a biological basis is often strongly suspected. Currently, few well-characterized experimental model systems are available to study the biological basis of racial disparity in PCa. We report a validated in vitro cell line model system that could be used for the purpose.We assembled a PCa cell line model that included currently available African-American PCa cell lines and LNCaP (androgen-dependent) and C4-2 (castration-resistant) Caucasian PCa cells. The utility of the cell lines in studying the biological basis of variance in a malignant phenotype was explored using a multiplex biomarker panel consisting of proteins that have been proven to play a role in the progression of PCa. The panel expression was evaluated by Western blot and RT-PCR in cell lines and validated in human PCa tissues by RT-PCR. As proof-of-principle to demonstrate the utility of our model in functional studies, we performed MTS viability assays and molecular studies.The dysregulation of the multiplex biomarker panel in primary African-American cell line (E006AA) was similar to metastatic Caucasian cell lines, which would suggest that the cell line model could be used to study an inherent aggressive phenotype in African-American men with PCa. We had previously demonstrated that Protein kinase D1 (PKD1) is a novel kinase that is down regulated in advanced prostate cancer. We established the functional relevance by over expressing PKD1, which resulted in decreased proliferation and epithelial mesenchymal transition (EMT) in PCa cells. Moreover, we established the feasibility of studying the expression of the multiplex biomarker panel in archived human PCa tissue from African-Americans and Caucasians as a prelude to future translational studies.We have characterized a novel in vitro cell line model that could be used to study the biological basis of disparity in PCa between African-Americans and Caucasians.

SUBMITTER: NickKholgh B

PROVIDER: S-EPMC4942245 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Cell line modeling to study biomarker panel in prostate cancer.

NickKholgh Bita B Fang Xiaolan X Winters Shira M SM Raina Anvi A Pandya Komal S KS Gyabaah Kenneth K Fino Nora N Balaji K C KC

The Prostate 20151102 3

<h4>Background</h4>African-American men with prostate cancer (PCa) present with higher-grade and -stage tumors compared to Caucasians. While the disparity may result from multiple factors, a biological basis is often strongly suspected. Currently, few well-characterized experimental model systems are available to study the biological basis of racial disparity in PCa. We report a validated in vitro cell line model system that could be used for the purpose.<h4>Methods</h4>We assembled a PCa cell l ...[more]

PMID: 26764245

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Project description:BackgroundProstate cancer diagnosis using the PSA test remains controversial because of overdiagnosis and overtreatment of potentially indolent cancers. There remains a need to increase the diagnostic lead time and to target treatment to patients with significant disease. One possible approach to overcome the limitations of PSA is to screen men for the molecular signature of early PCA, monitor the rate of disease progression and target treatment to patients who are likely to benefit from it. Such an approach requires a large panel of markers that define a molecular clock for PCA. We recently developed a panel of 19 markers for the non-invasive detection of PCA from urine DNA. It raised the possibility that additional methylation markers could be successfully analyzed from urine DNA, a prerequisite for increasing the diagnostic lead time and enabling disease monitoring.MethodsWe developed semi-quantitative polymerase chain reaction assays for 13 additional markers and determined their methylation status in 150 urine DNAs from 94 patients with elevated PSA. Eighty five samples were obtained following DRE and 65 samples were from first void. We combined the data of the 13 new markers with the previously reported 19 markers and calculated the sensitivity, specificity, negative and positive predictive values at every threshold from one to 32 positive markers.ResultsUsing 10of32 positive markers as the threshold to recommend a biopsy yields a sensitivity of 81% (95% CI 0.68-0.93) and 93% (95% CI 0.84-1.02) and a specificity of 76% (95% CI 0.63-0.88) and 77% (95% CI 0.63-0.91) from DRE and FV DNA, respectively. The PPV was 71% and 77% and the NPV was 85% and 93% from DRE and FV, respectively.ConclusionsThis study shows that large marker panels can be analyzed from urine DNA without loss of sensitivity or specificity. Using 32 markers improved the stratification of patients undergoing screening for PCA particularly for patients below the 10of32 threshold. The results show the utility of larger biomarker panels for PCA diagnosis and suggest that the development of the panels needed to monitor disease progression could be successfully accomplished.

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Cell line modeling to study biomarker panel in prostate cancer.

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Cell line modeling to study biomarker panel in prostate cancer.

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