Dataset Information

Prostac: A New Composite Score With Potential Predictive Value in Prostate Cancer.

ABSTRACT: Prostate cancer (PCa) is the most commonly diagnosed solid organ cancer in men worldwide. Current diagnosis of PCa includes use of initial prostate specific antigen assay which has a high false positive rate, low specificity, and low sensitivity. The side effects of unnecessary prostate biopsies that healthy men are subjected to, often result in unintended health complications. New PCa biomarkers are being discovered to address this unmet need. Here, we report on the creation of a composite score (Prostac) based on three recently discovered PCa biomarkers, Plasmacytoma Variant Translocation 1 (PVT1) exons 4A, 4B, and 9. Statistical analysis of copy numbers derived from a real-time quantitative polymerase chain (qPCR) reaction - based assay, showed these PCa biomarkers to be linearly separable and significantly over expressed in PCa epithelial cells. We train a supervised learning algorithm using support vector machines to generate a classification hyperplane from which a user-friendly composite score is developed. Cross validation of Prostac using data from prostate epithelial cells (RWPE1) and PCa cells (MDA PCa 2b) accurately classified 100% of PCa cells. Creation of the Prostac score lays the groundwork for clinical trial of its use in PCa diagnosis.

SUBMITTER: Asante-Asamani EO

PROVIDER: S-EPMC8009179 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Prostac: A New Composite Score With Potential Predictive Value in Prostate Cancer.

Asante-Asamani E O EO Pal Gargi G Liu Leslie L Ogunwobi Olorunseun O OO

Frontiers in oncology 20210316

Prostate cancer (PCa) is the most commonly diagnosed solid organ cancer in men worldwide. Current diagnosis of PCa includes use of initial prostate specific antigen assay which has a high false positive rate, low specificity, and low sensitivity. The side effects of unnecessary prostate biopsies that healthy men are subjected to, often result in unintended health complications. New PCa biomarkers are being discovered to address this unmet need. Here, we report on the creation of a composite scor ...[more]

PMID: 33796469

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Project description:To screen target gene cluster by bioinformatics analysis and verify them by in vitro experiment and clinicopathological correlation analysis. We try to find a new biomarker with prognostic value for prostate cancer (PCa). 42 candidate marker genes were constructed by protein protein interaction (PPI) network and enriched by KEGG pathway to find out the gene cluster we are interested in. Prognostic model was established to preliminarily analyze the prognostic value of this gene cluster in PCa, and Cox risk regression was used for comparative analysis. Immunohistochemistry was used to detect the expression of each gene in clinical tissue microarray. Finally, we analyzed the correlation between each gene and their clinicopathological features of PCa combined with TCGA clinical data. Based on the analysis of PPI and KEGG, we found the target gene cluster (FCGR3A, HAVCR2, CCR7 and CD28). Prognostic model analysis showed that this gene cluster had the ability to predict biochemical recurrence, and the survival rate and ROC analysis showed favorable prediction effect. Univariate Cox regression analysis showed that the risk scores of Gleason score (GS), T stage, N stage and PSA were significantly different (P<0.05), and the risk ratio of high expression was 2.30 times that of low expression (P=0.004). However, it was not statistically significant in multivariate Cox regression analysis (P>0.05). The results of tissue microarray showed that FCGR3A and HAVCR2 were highly expressed in PCa (P<0.01), while the expression of CCR7 and CD28 had no significant difference (P>0.05). Kaplan-Meier analysis showed that there was significant difference in BCR free survival of FCGR3A and HAVCR2 (FCGR3A, P=0.010; HAVCR2, P=0.018), while the expression of CCR7 and CD28 had no significant difference on the survival and prognosis of PCa patients (P>0.05). TCGA clinical data analysis found that the expression of FCGR3A had a unique correlation with the clinicopathological features of PCa, which was closely related to the tumor stage. The expression of FCGR3A is related to BCR free survival of PCa patients. Therefore, FCGR3A is a new biomarker with potential prognostic value of PCa.

Project description:BackgroundOur previous studies demonstrated that a novel quinazoline derivative, DZ-50, inhibited prostate cancer epithelial cell invasion and survival by targeting insulin-like-growth factor binding protein-3 (IGFBP-3) and mediating epithelial-mesenchymal transition (EMT) conversion to mesenchymal-epithelial transition (MET). This study investigated the therapeutic value of DZ-50 agent in in vitro and in vivo models of advanced prostate cancer and the ability of the compound to overcome resistance to antiandrogen (enzalutamide) in prostate tumors.ApproachLNCaP and LNCaP-enzalutamide resistant human prostate cancer (LNCaP-ER) cells, as well as 22Rv1 and enzalutamide resistant, 22Rv1-ER were used as cell models. The effects of DZ-50 and the antiandrogen, enzalutamide (as single agents or in combination) on cell death, EMT-MET interconversion, and expression of IGFBP3 and the androgen receptor (AR), were examined. The TRAMP mouse model of prostate cancer progression was used as a pre-clinical model. Transgenic mice (20-wks of age) were treated with DZ-50 (100 mg/kg for 2 wks, oral gavage daily) and prostate tumors were subjected to immunohistochemical assessment of apoptosis, cell proliferation, markers of EMT and differentiation and IGFBP-3 and AR expression. A tissue microarray (TMA) was analyzed for expression of IGBP-3, the target of DZ-50 and its association with tumor progression and biochemical recurrence.ResultsWe found that treatment with DZ-50 enhanced the anti-tumor response to the antiandrogen via promoting EMT to MET interconversion, in vitro. This DZ-50-mediated phenotypic reversal to MET leads to prostate tumor re-differentiation in vivo, by targeting nuclear IGFBP-3 expression (without affecting AR). Analysis of human prostate cancer specimens and TCGA patient cohorts revealed that overexpression of IGBP-3 protein correlated with tumor recurrence and poor patient survival.ConclusionsThese findings provide significant new insights into (a) the predictive value of IGFBP-3 in prostate cancer progression and (b) the antitumor action of DZ-50, [in combination or sequencing with enzalutamide] as a novel approach for the treatment of therapeutically resistant prostate cancer.

Dataset Information

Prostac: A New Composite Score With Potential Predictive Value in Prostate Cancer.

Publications

Prostac: A New Composite Score With Potential Predictive Value in Prostate Cancer.

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