Prostac: A New Composite Score With Potential Predictive Value in Prostate Cancer.
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ABSTRACT:
SUBMITTER: Asante-Asamani EO
PROVIDER: S-EPMC8009179 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundRecent studies have shown that certain small nucleolar RNAs (H/ACA snoRNAs) and the protein dyskerin (DKC1) are upregulated in prostate cancer and are thought to contribute to progression of disease. These components convert uridine to pseudouridine (abbreviated ψ), a type of post-transcriptional modification of RNA. Given the increased abundance of H/ACA snoRNAs and expression of DKC1 in prostate carcinomas, and because whole-body turnover of RNA increases in support of rapidly-growing cancer cells, we examined the value of pseudouridine as a biomarker for prostate cancer.MethodsUsing a monoclonal antibody against pseudouridine, we tested its ability to distinguish between two 25-base RNA oligonucleotide sequences that differed by only one ψ-substitution, and subsequently measured ψ in RNA isolated from several prostate cancer cell lines representing different stages of disease using dot blot assays and pseudouridinylated RNA linked immunosorbent assay (PURLISA). We also performed immunohistochemistry on a tissue micro array (12 cases/24 cores) containing prostate adenocarcinomas and normal adjacent tissue (NAT).ResultsHigh levels of pseudouridine were detected in androgen-independent cell lines (PC3 and Du145) compared to androgen-sensitive (LNCaP) and immortalized human prostate (RWPE) cells. Immunohistochemistry of a tissue micro array (TMA) containing normal adjacent and cancerous prostate tissue revealed a significant difference in immunoreactivity between normal and malignant tissue (P ≤ 0.0001).ConclusionOur results provide new information on the relationship between pseudouridine expression and clinical progression of prostate cancer.
| S-EPMC6734038 | biostudies-literature
Project description:Although prostate cancer is a common occurrence among males, the relationship between existing risk prediction models remains unclear. The objective of this hospital-based retrospective study is to investigate the impact of polygenic risk scores (PRSs) on the incidence and prognosis of prostate cancer in the Han Chinese population. A total of 24,778 male participants including 903 patients with prostate cancer at Taichung Veterans General Hospital were enrolled in the study. PRS was calculated using 269 single nucleotide polymorphisms and their corresponding effect sizes from the polygenic score catalog. The association between PRS and the risk prostate cancer was evaluated using Cox proportional hazards regression model. Among the 24,778 participants, 903 were diagnosed with prostate cancer. The risk of prostate cancer was significantly higher in the highest quartile of PRS distribution compared to the lowest (hazard ratio = 4.770, 95% CI = 3.999-5.689, p < 0.0001), with statistical significance across all age groups. Patients in the highest quartile were diagnosed with prostate cancer at a younger age (66.8 ± 8.3 vs. 69.5 ± 8.8, p = 0.002). Subgroup analysis of patients with localized or stage 4 prostate cancer showed no significant differences in biochemical failure or overall survival. This hospital-based cohort study observed that a higher PRS was associated with increased susceptibility to prostate cancer and younger age of diagnosis. However, PRS was not found to be a significant predictor of disease stage and prognosis. These findings suggest that PRS could serve as a useful tool in prostate cancer risk assessment.
| S-EPMC11372043 | biostudies-literature
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.
| S-EPMC9730230 | biostudies-literature
Project description:Screening of differentially expressed genes between benign and prostate tumors with respect to different prostate cancer gleason score 6 and 8 Keywords: disease subtype analysis
2010-03-31 | GSE15484 | GEO
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.
| S-EPMC6627542 | biostudies-literature
Project description:Background:A reliable screening tool that could contribute to the identification of women with an increased risk of postpartum hemorrhage would be of great clinical significance. Objectives:The aim of this study was to examine the added predictive value of a bleeding assessment tool for postpartum hemorrhage exceeding 1000 mL. Patients/Methods:Prospective two-center cohort study among 1147 pregnant women visiting the outpatient clinic or the maternity ward who completed a bleeding assessment tool prior to birth. The condensed MCMDM-1VWD bleeding assessment tool was adjusted to a questionnaire that could be used as a self-assessment bleeding tool. A score of ?4 was considered to be abnormal. Results:In the 1147 pregnant women in our cohort, bleeding scores ranged from -3 to 13, with a median of 1 (IQR -1 to 3); 197 (17%) women developed postpartum hemorrhage. Among women with a history of postpartum hemorrhage 29% developed postpartum hemorrhage. Among 147 women with an abnormal bleeding score (?4), 27 (18%) developed postpartum hemorrhage, whereas the remaining 170 cases of postpartum hemorrhage had a normal bleeding score. Despite the high incidence of postpartum hemorrhage, the ability of the bleeding score to predict postpartum hemorrhage was poor: area under receiver operating curve 0.53 (95% CI 0.49-0.58) for postpartum hemorrhage (PPH) ?1000 mL. Conclusions:A history of significant postpartum hemorrhage was associated with an increased risk of subsequent postpartum hemorrhage. However, screening with a bleeding assessment tool did not help to discriminate women who will develop postpartum hemorrhage from women who will not.
| S-EPMC6462748 | biostudies-literature
Project description:Bibliometric and Altmetric analyses provide different perspectives regarding research impact. This study aimed to determine whether Altmetric score was associated with citation rate independent of established bibliometrics. Citations related to a previous cohort of 100 most cited articles in surgery were collected and a 3-year interval citation gain calculated. Citation count, citation rate index, Altmetric score, 5-year impact factor, and Oxford Centre for Evidence-Based Medicine levels were used to estimate citation rate prospect. The median interval citation gain was 161 (i.q.r. 83-281); 74 and 62 articles had an increase in citation rate index (median increase 2.8 (i.q.r. -0.1 to 7.7)) and Altmetric score (median increase 3 (0-4)) respectively. Receiver operating characteristic (ROC) curve analysis revealed that citation rate index (area under the curve (AUC) 0.86, 95 per cent c.i. 0.79 to 0.93; P < 0.001) and Altmetric score (AUC 0.65, 0.55 to 0.76; P = 0.008) were associated with higher interval citation gain. An Altmetric score critical threshold of 2 or more was associated with a better interval citation gain when dichotomized at the interval citation gain median (odds ratio (OR) 4.94, 95 per cent c.i. 1.99 to 12.26; P = 0.001) or upper quartile (OR 4.13, 1.60 to 10.66; P = 0.003). Multivariable analysis revealed only citation rate index to be independently associated with interval citation gain when dichotomized at the median (OR 18.22, 6.70 to 49.55; P < 0.001) or upper quartile (OR 19.30, 4.23 to 88.15; P < 0.001). Citation rate index and Altmetric score appear to be important predictors of interval citation gain, and better at predicting future citations than the historical and established impact factor and Oxford Centre for Evidence-Based Medicine quality descriptors.
| S-EPMC7893457 | biostudies-literature
Project description:To evaluate whether prostate volume (PV) would provide additional predictive utility to the prostate health index (phi) for predicting prostate cancer (PCa) or clinically significant prostate cancer, we designed a prospective, observational multicenter study in two prostate biopsy cohorts. Cohort 1 included 595 patients from three medical centers from 2012 to 2013, and Cohort 2 included 1025 patients from four medical centers from 2013 to 2014. Area under the receiver operating characteristic curves (AUC) and logistic regression models were used to evaluate the predictive performance of PV-based derivatives and models. Linear regression analysis showed that both total prostate-specific antigen (tPSA) and free PSA (fPSA) were significantly correlated with PV (all P < 0.05). [-2]proPSA (p2PSA) was significantly correlated with PV in Cohort 2 (P< 0.001) but not in Cohort 1 (P= 0.309), while no significant association was observed between phi and PV. When combining phi with PV, phi density (PHID) and another phi derivative (PHIV, calculated as phi/PV0.5) did not outperform phi for predicting PCa or clinically significant PCa in either Cohort 1 or Cohort 2. Logistic regression analysis also showed that phi and PV were independent predictors for both PCa and clinically significant PCa (all P < 0.05); however, PV did not provide additional predictive value to phi when combining these derivatives in a regression model (all models vs phi were not statistically significant, all P > 0.05). In conclusion, PV-based derivatives (both PHIV and PHID) and models incorporating PV did not improve the predictive abilities of phi for either PCa or clinically significant PCa.
| S-EPMC7523603 | biostudies-literature
Project description:Background and Objectives: The molecular mechanisms of lung cancer are still unclear. Investigation of immune cell infiltration (ICI) and the hub gene will facilitate the identification of specific biomarkers. Materials and Methods: Key modules of ICI and immune cell-associated differential genes, as well as ICI profiles, were identified using lung cancer microarray data from the single sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network analysis (WGCNA) in the gene expression omnibus (GEO) database. Protein-protein interaction networks were used to identify hub genes. The receiver operating characteristic (ROC) curve was used to assess the diagnostic significance of the hub genes, and survival analysis was performed using gene expression profiling interactive analysis (GEPIA). Results: Significant changes in ICI were found in lung cancer tissues versus adjacent normal tissues. WGCNA results showed the highest correlation of yellow and blue modules with ICI. Protein-protein interaction networks identified four hub genes, namely CENPF, AURKA, PBK, and CCNB1. The lung adenocarcinoma patients in the low hub gene expression group showed higher overall survival and longer median survival than the high expression group. They were associated with a decreased risk of lung cancer in patients, indicating their potential role as cancer suppressor genes and potential targets for future therapeutic development. Conclusions: CENPF, AURKA, PBK, and CCNB1 show great potential as biomarkers and immunotherapeutic targets specific to lung cancer. Lung cancer patients' prognoses are often foreseen using matched prognostic models, and genes CENPF, AURKA, PBK, and CCNB1 in lung cancer may serve as therapeutic targets, which require further investigations.
| S-EPMC10051862 | biostudies-literature
Project description:IntroductionIn advanced-stage NSCLC, tumor proportion score (TPS) is typically used to predict the efficacy of immune checkpoint inhibitors (ICIs). Nevertheless, in other cancer types, the combined positive score (CPS), which covers programmed death-ligand 1 (PD-L1) expression on both tumor and surrounding immune cells, is used. We investigated the predictive value of CPS in comparison to TPS in advanced NSCLC.MethodsA monocenter, retrospective study was performed in patients with advanced NSCLC treated with ICI monotherapy between 2015 and 2021. Hematoxylin and eosin and PD-L1 were stained on baseline tumor biopsy samples to score PD-L1 by both TPS and CPS. Positivity for TPS and CPS was defined as a score of 1% or above. Progression-free survival and overall survival (OS) were assessed for TPS and CPS scores.ResultsAmong the 187 included patients, PD-L1 positivity was found in 112 patients (59.9%) by TPS and 135 patients (72.2%) by CPS. There was no significant difference in OS between TPS- and TPS+ patients (p = 0.20). Nevertheless, CPS+ patients did have a longer OS than CPS- patients (p = 0.006). OS was superior in both TPS-/CPS+ and TPS+/CPS+ as compared with TPS-/CPS- cases (p = 0.018 and p = 0.015, respectively), whereas no considerable differences in OS were found between TPS-/CPS+ and TPS+/CPS+ cases.ConclusionsThis retrospective real-world population study revealed that CPS differentiated OS better than TPS in patients with advanced NSCLC with ICI monotherapy. Remarkably, this was driven by the performance of the TPS-/CPS+ subgroup, indicating that CPS may be a better predictive biomarker for ICI efficacy.
| S-EPMC10480627 | biostudies-literature