Optimization of Apta-Sensing Platform for Detection of Prostate Cancer Marker PCA3.
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ABSTRACT:
SUBMITTER: Takita S
PROVIDER: S-EPMC8657731 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:There is widespread interest in circulating tumor cells (CTCs) in blood. Direct detection of CTCs (often < 1/mL) is complicated by a number of factors, but the presence of ?10(3) to 10(4) copies of target RNA per CTC, coupled with simple enrichments, can greatly increase detection capability. In this study we used resonance frequency shifts induced by mass-amplifying gold nanoparticles to detect a hybridization sandwich bound to functionalized nanowires. We selected PCA3 RNA as a marker for prostate cancer, optimized antisense binding sites, and defined conditions allowing single nucleotide mismatch discrimination, and used a hybrid resonator integration scheme, which combines elements of top-down fabrication with strengths of bottom-up fabrication, with a view to enable multiplexed sensing. Bound mass calculated from frequency shifts matched mass estimated by counting gold nanoparticles. This represents the first demonstration of use of such nanoresonators, which show promise of both excellent specificity and quantitative sensitivity.
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Project description:The prostate cancer antigen 3 (PCA3/DD3) gene is a highly specific biomarker upregulated in prostate cancer (PCa). In order to understand the importance of PCA3 in PCa we investigated the organization and evolution of the PCA3 gene locus.We have employed cDNA synthesis, RTPCR and DNA sequencing to identify 4 new transcription start sites, 4 polyadenylation sites and 2 new differentially spliced exons in an extended form of PCA3. Primers designed from these novel PCA3 exons greatly improve RT-PCR based discrimination between PCa, PCa metastases and BPH specimens. Comparative genomic analyses demonstrated that PCA3 has only recently evolved in an anti-sense orientation within a second gene, BMCC1/PRUNE2. BMCC1 has been shown previously to interact with RhoA and RhoC, determinants of cellular transformation and metastasis, respectively. Using RT-PCR we demonstrated that the longer BMCC1-1 isoform - like PCA3 - is upregulated in PCa tissues and metastases and in PCa cell lines. Furthermore PCA3 and BMCC1-1 levels are responsive to dihydrotestosterone treatment.Upregulation of two new PCA3 isoforms in PCa tissues improves discrimination between PCa and BPH. The functional relevance of this specificity is now of particular interest given PCA3's overlapping association with a second gene BMCC1, a regulator of Rho signalling. Upregulation of PCA3 and BMCC1 in PCa has potential for improved diagnosis.
| S-EPMC2655648 | biostudies-literature
Project description:Purpose:Preclinical evaluation of PCA3 and AMACR transcript simultaneous detection in urine to diagnose clinical significant prostate cancer (prostate cancer with Gleason score ?7) in a Russian cohort. Patients and Methods:We analyzed urine samples of patients with a total serum PSA ?2 ng/mL: 31 men with prostate cancer scheduled for radical prostatectomy, 128 men scheduled for first diagnostic biopsy (prebiopsy cohort). PCA3, AMACR, PSA and GPI transcripts were detected by multiplex reverse transcription quantitative polymerase chain reaction, and the results were used for scores for calculation and statistical analysis. Results:There was no significant difference between clinically significant and nonsignificant prostate cancer PCA3 scores. However, there was a significant difference in the AMACR score (patients scheduled for radical prostatectomy p=0.0088, prebiopsy cohort p=0.029). We estimated AUCs, optimal cutoffs, sensitivities and specificities for PCa and csPCa detection in the prebiopsy cohort by tPSA, PCA3 score, PCPT Risk Calculator and classification models based on tPSA, PCA3 score and AMACR score. In the clinically significant prostate cancer ROC analysis, the PCA3 score AUC was 0.632 (95%CI: 0.511-0.752), the AMACR score AUC was 0.711 (95%CI: 0.617-0.806) and AUC of classification model based on the PCA3 score, the AMACR score and total PSA was 0.72 (95%CI: 0.58-0.83). In addition, the correlation of the AMACR score with the ratio of total RNA and RNA of prostate cells in urine was shown (tau=0.347, p=6.542e-09). Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Conclusion:The AMACR score is a good predictor of clinically significant prostate cancer. Significant amounts of nonprostate RNA in urine may be a limitation for the AMACR score use. Evaluation of the AMACR score and classification models based on it for clinically significant prostate cancer detection with larger samples and a follow-up analysis is promising.
| S-EPMC7505712 | biostudies-literature
Project description:Importance:Potential survival benefits from treating aggressive (Gleason score, ?7) early-stage prostate cancer are undermined by harms from unnecessary prostate biopsy and overdiagnosis of indolent disease. Objective:To evaluate the a priori primary hypothesis that combined measurement of PCA3 and TMPRSS2:ERG (T2:ERG) RNA in the urine after digital rectal examination would improve specificity over measurement of prostate-specific antigen alone for detecting cancer with Gleason score of 7 or higher. As a secondary objective, to evaluate the potential effect of such urine RNA testing on health care costs. Design, Setting, and Participants:Prospective, multicenter diagnostic evaluation and validation in academic and community-based ambulatory urology clinics. Participants were a referred sample of men presenting for first-time prostate biopsy without preexisting prostate cancer: 516 eligible participants from among 748 prospective cohort participants in the developmental cohort and 561 eligible participants from 928 in the validation cohort. Interventions/Exposures:Urinary PCA3 and T2:ERG RNA measurement before prostate biopsy. Main Outcomes and Measures:Presence of prostate cancer having Gleason score of 7 or higher on prostate biopsy. Pathology testing was blinded to urine assay results. In the developmental cohort, a multiplex decision algorithm was constructed using urine RNA assays to optimize specificity while maintaining 95% sensitivity for predicting aggressive prostate cancer at initial biopsy. Findings were validated in a separate multicenter cohort via prespecified analysis, blinded per prospective-specimen-collection, retrospective-blinded-evaluation (PRoBE) criteria. Cost effects of the urinary testing strategy were evaluated by modeling observed biopsy results and previously reported treatment outcomes. Results:Among the 516 men in the developmental cohort (mean age, 62 years; range, 33-85 years) combining testing of urinary T2:ERG and PCA3 at thresholds that preserved 95% sensitivity for detecting aggressive prostate cancer improved specificity from 18% to 39%. Among the 561 men in the validation cohort (mean age, 62 years; range, 27-86 years), analysis confirmed improvement in specificity (from 17% to 33%; lower bound of 1-sided 95% CI, 0.73%; prespecified 1-sided P?=?.04), while high sensitivity (93%) was preserved for aggressive prostate cancer detection. Forty-two percent of unnecessary prostate biopsies would have been averted by using the urine assay results to select men for biopsy. Cost analysis suggested that this urinary testing algorithm to restrict prostate biopsy has greater potential cost-benefit in younger men. Conclusions and Relevance:Combined urinary testing for T2:ERG and PCA3 can avert unnecessary biopsy while retaining robust sensitivity for detecting aggressive prostate cancer with consequent potential health care cost savings.
| S-EPMC5710334 | biostudies-literature
Project description:Majority of patients with indolent prostate cancer (PCa) can be managed with active surveillance. Therefore, finding biomarkers for classifying patients between indolent and aggressive PCa is essential. In this study, we investigated urinary marker panels composed of urinary glycopeptides and/or urinary prostate-specific antigen (PSA) for their clinical utility in distinguishing non-aggressive (Grade Group 1) from aggressive (Grade Group ≥ 2) PCa. Urinary glycopeptides acquired via data-independent acquisition mass spectrometry (DIA-MS) were quantitatively analyzed, where prostatic acid phosphatase (ACPP), clusterin (CLU), alpha-1-acid glycoprotein 1 (ORM1), and CD antigen 97 (CD97) were selected to be evaluated in various combinations with and without urinary PSA. Targeted parallel reaction monitoring (PRM) assays of the glycopeptides from urinary ACPP and CLU were investigated along with urinary PSA for the ability of aggressive PCa detection. The multi-urinary marker panels, combined via logistic regression, were statistically evaluated using bootstrap resampling and validated by an independent cohort. Majority of the multi-urinary marker panels (e.g., a panel consisted of ACPP, CLU, and Urinary PSA) achieved area under the curve (AUC) ranged from 0.70 to 0.85. Thus, multi-marker panels investigated in this study showed clinically meaningful results on aggressive PCa detection to separate Grade Group 1 from Grade Group 2 and above warranting further evaluation in clinical setting in future.
| S-EPMC9437030 | biostudies-literature
Project description:BackgroundTMPRSS2:ERG (T2:ERG) and prostate cancer antigen 3 (PCA3) are the most advanced urine-based prostate cancer (PCa) early detection biomarkers.ObjectiveValidate logistic regression models, termed Mi-Prostate Score (MiPS), that incorporate serum prostate-specific antigen (PSA; or the multivariate Prostate Cancer Prevention Trial risk calculator version 1.0 [PCPTrc]) and urine T2:ERG and PCA3 scores for predicting PCa and high-grade PCa on biopsy.Design, setting, and participantsT2:ERG and PCA3 scores were generated using clinical-grade transcription-mediated amplification assays. Pretrained MiPS models were applied to a validation cohort of whole urine samples prospectively collected after digital rectal examination from 1244 men presenting for biopsy.Outcome measurements and statistical analysisArea under the curve (AUC) was used to compare the performance of serum PSA (or the PCPTrc) alone and MiPS models. Decision curve analysis (DCA) was used to assess clinical benefit.Results and limitationsAmong informative validation cohort samples (n=1225 [98%], 80% from patients presenting for initial biopsy), models incorporating T2:ERG had significantly greater AUC than PSA (or PCPTrc) for predicting PCa (PSA: 0.693 vs 0.585; PCPTrc: 0.718 vs 0.639; both p<0.001) or high-grade (Gleason score >6) PCa on biopsy (PSA: 0.729 vs 0.651, p<0.001; PCPTrc: 0.754 vs 0.707, p=0.006). MiPS models incorporating T2:ERG score had significantly greater AUC (all p<0.001) than models incorporating only PCA3 plus PSA (or PCPTrc or high-grade cancer PCPTrc [PCPThg]). DCA demonstrated net benefit of the MiPS_PCPTrc (or MiPS_PCPThg) model compared with the PCPTrc (or PCPThg) across relevant threshold probabilities.ConclusionsIncorporating urine T2:ERG and PCA3 scores improves the performance of serum PSA (or PCPTrc) for predicting PCa and high-grade PCa on biopsy.Patient summaryIncorporation of two prostate cancer (PCa)-specific biomarkers (TMPRSS2:ERG and PCA3) measured in the urine improved on serum prostate-specific antigen (or a multivariate risk calculator) for predicting the presence of PCa and high-grade PCa on biopsy. A combined test, Mi-Prostate Score, uses models validated in this study and is clinically available to provide individualized risk estimates.
| S-EPMC4644724 | biostudies-literature
Project description:Targeting specifically primary prostate cancer (PCa) cells for immune therapy, gene therapy or molecular imaging is of high importance. The PCA3 long non-coding RNA is a unique PCa biomarker and oncogene that has been widely studied. This gene has been mainly exploited as an accurate diagnostic urine biomarker for PCa detection. In this study, the PCA3 promoter was introduced into a new transcriptional amplification system named the 3-Step Transcriptional Amplification System (PCA3-3STA) and cloned into type 5 adenovirus. PCA3-3STA activity was highly specific for PCa cells, ranging between 98.7- and 108.0-fold higher than that for benign primary prostate epithelial or non-PCa cells, respectively. In human PCa xenografts, PCA3-3STA displayed robust bioluminescent signals at levels that are sufficient to translate to positron emission tomography (PET)-based reporter imaging. Remarkably, when freshly isolated benign or cancerous prostate biopsies were infected with PCA3-3STA, the optical signal produced from primary PCa biopsies was significantly higher than from benign prostate biopsies (4.4-fold, p < 0.0001). PCA3-3STA therefore represents a PCa-specific expression system with the potential to target, with high accuracy, primary or metastatic PCa epithelial cells for imaging, vaccines, or gene therapy.
| S-EPMC4811461 | biostudies-literature
Project description:While now recognized as an aid to predict repeat prostate biopsy outcome, the urinary PCA3 (prostate cancer gene 3) test has also been recently advocated to predict initial biopsy results. The objective is to evaluate the performance of the PCA3 test in predicting results of initial prostate biopsies and to determine whether its incorporation into specific nomograms reinforces its diagnostic value. A prospective study included 601 consecutive patients addressed for initial prostate biopsy. The PCA3 test was performed before ?12-core initial prostate biopsy, along with standard risk factor assessment. Diagnostic performance of the PCA3 test was evaluated. The three available nomograms (Hansen's and Chun's nomograms, as well as the updated Prostate Cancer Prevention Trial risk calculator; PCPT) were applied to the cohort, and their predictive accuracies were assessed in terms of biopsy outcome: the presence of any prostate cancer (PCa) and high-grade prostate cancer (HGPCa). The PCA3 score provided significant predictive accuracy. While the PCPT risk calculator appeared less accurate; both Chun's and Hansen's nomograms provided good calibration and high net benefit on decision curve analyses. When applying nomogram-derived PCa probability thresholds ?30%, ?6% of HGPCa would have been missed, while avoiding up to 48% of unnecessary biopsies. The urinary PCA3 test and PCA3-incorporating nomograms can be considered as reliable tools to aid in the initial biopsy decision.
| S-EPMC3794752 | biostudies-literature
Project description:The association of prostate cancer antigen 3 (PCA3) polymorphism (SNP, rs544190G>A) with metastatic prostate cancer in European descent has been reported. Our aim of the current study was to re-validate the effect of PCA3 polymorphism on prostate cancer risk in an Eastern Chinese population and then estimate possible genetic discrepancies among population.Taqman assay was employed to determine genotype of SNP rs544190 in 1015 ethnic Han Chinese patients with prostate cancer and 1032 cancerfree controls. Simultaneously, odds ratios (OR) and 95% confidence intervals (95%CI) for risk relationship were calculated by logistic regression models.The statistically significant relationship between PCA3 rs544190G>A and higher prostate cancer risk was not found. Stratification analysis revealed that there was no remarkable association of rs544190 variant AG/AA genotype with prostate cancer risk in every subgroup, except for patients with Gleason score ?7(3+4).Although the results demonstrated that SNP rs544190 was not involved in prostate cancer risk in Eastern Chinese descent, unlike in European population, these might have clinical implications on prostate cancer heterogeneity around the World. To validate these findings, well-designed studies with different ethnic populations are warranted.
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Project description:Prostate cancer antigen 3(PCA3) is a long non-coding RNA, which was found increased expression in CaP patients than healthy individual. In this study, the individual nucleic acid of PCA3 and PSA was recombinant expressed as a reference reagent, and a quantitative RT-PCR with TaqMan assay was developed to examine the copies of PCA3 and PSA gene in urine. The results showed that the area under the receiver operating characteristic curve (AUROC) was 0.717, 0.444 and 0.916 for the number of PCA3 copy, PSA copy and for the score of PCA3/PSA RNA, respectively. Additionally, the AUROC for serum tPSA was 0.674 with a low specificity of 12.07%. Finally, the algorithm of PCA3 RNA versus PSA RNA was evaluated and corroborated as CaP biomarker by conducting a multicentric clinical trial. This study not only validated the developed technique of qRT-PCR with TaqMan assay for examination of urinary PCA3 and PSA RNA, it also demonstrated that the score of the PCA/PSA RNA was a reliable signature for CaP diagnosis.
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