Presence Of High-grade Prostate Cancer Research Articles

MP33-08 GUT MICROBIOTA PROFILE ASSOCIATED WITH HIGH-GRADE PROSTATE CANCER

You have accessJournal of UrologyProstate Cancer: Basic Research & Pathophysiology I (MP33)1 Sep 2021MP33-08 GUT MICROBIOTA PROFILE ASSOCIATED WITH HIGH-GRADE PROSTATE CANCER Kazutoshi Fujita, Makoto Matsushita, Daisuke Motooka, Koji Hatano, Shota Fukae, Norihiko Kawamura, Eisuke Tomiyama, Yujiro Hayashi, Eri Banno, Tetsuya Takao, Shingo Takada, Shinichi Yachida, Takafumi Minami, Masahiro Nozawa, Kazuhiro Yoshimura, Hirotsugu Uemura, Shota Nakamura, and Norio Nonomura Kazutoshi FujitaKazutoshi Fujita More articles by this author , Makoto MatsushitaMakoto Matsushita More articles by this author , Daisuke MotookaDaisuke Motooka More articles by this author , Koji HatanoKoji Hatano More articles by this author , Shota FukaeShota Fukae More articles by this author , Norihiko KawamuraNorihiko Kawamura More articles by this author , Eisuke TomiyamaEisuke Tomiyama More articles by this author , Yujiro HayashiYujiro Hayashi More articles by this author , Eri BannoEri Banno More articles by this author , Tetsuya TakaoTetsuya Takao More articles by this author , Shingo TakadaShingo Takada More articles by this author , Shinichi YachidaShinichi Yachida More articles by this author , Takafumi MinamiTakafumi Minami More articles by this author , Masahiro NozawaMasahiro Nozawa More articles by this author , Kazuhiro YoshimuraKazuhiro Yoshimura More articles by this author , Hirotsugu UemuraHirotsugu Uemura More articles by this author , Shota NakamuraShota Nakamura More articles by this author , and Norio NonomuraNorio Nonomura More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002042.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The gut microbiota is involved in a variety of diseases that affect the entire body. Diet and body size influence the gut microbiota and are important risk factors for prostate cancer (PCa). However, the association between the gut microbiota and PCa is not well understood. To clarify this association, we analysed the gut microbiota profiles of men with high-grade PCa. METHODS: We collected rectal swab samples of 189 Japanese men who were suspected of PCa based on screening such as MRI or prostate specific antigen (PSA) tests and underwent prostate biopsies from December 2018 to March 2020 at the Osaka University Hospital, Osaka Police Hospital and Osaka General Medical Center. All hospitals are located in Osaka, Japan. RESULTS: One hundred fifty-two Japanese men undergoing prostate biopsies were included in the study and divided into two cohorts: discovery cohort (114 subjects, 72 with cancer and 42 without cancer) and external test cohort (38 subjects, 24 with cancer and 14 without cancer). The gut microbiota in the discovery cohort was compared between two groups, a high-grade PCa group (men with Gleason score 7 or higher PCa) and a negative+low-grade PCa group (men with negative biopsy or Gleason score 6 PCa) using 16S rRNA gene sequencing. Alpha diversity and beta diversity did not differ significantly between the two groups. Using the linear discriminant analysis (LDA) effect size (LEfSe) method, the relative abundance of Rikenellaceae, Alistipes, and Lachnospira were shown to be significantly increased in patients with high-grade PCa (LDA score>2.5). Phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) showed a significant increase in five metabolic pathways: multiple amino acid metabolisms, phenylalanine, tryptophan, tyrosine, and histidine (LDA score>2.0). In the receiver operating characteristic (ROC) curve analysis, the index calculated from the amount of 18 bacterial genera, including Lachnospira, which were selected by least absolute shrinkage and selection operator (LASSO) regression, detected high-grade PCa in the discovery cohort with higher accuracy than the prostate-specific antigen (PSA) test (area under the curve (AUC)=0.85 vs. 0.74). Validation of the index in the test cohort showed similar results (AUC = 0.81 vs. 0.67). CONCLUSIONS: The results demonstrate an association between a gut microbiota composed of 18 genera and the presence of high-grade PCa in Japanese men. This gut microbiota profile could be a novel useful marker for the detection of high-grade PCa with greater accuracy than the PSA test. Source of Funding: The Japanese Urological Association, Yakult Bio-Science Foundation © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e609-e609 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Kazutoshi Fujita More articles by this author Makoto Matsushita More articles by this author Daisuke Motooka More articles by this author Koji Hatano More articles by this author Shota Fukae More articles by this author Norihiko Kawamura More articles by this author Eisuke Tomiyama More articles by this author Yujiro Hayashi More articles by this author Eri Banno More articles by this author Tetsuya Takao More articles by this author Shingo Takada More articles by this author Shinichi Yachida More articles by this author Takafumi Minami More articles by this author Masahiro Nozawa More articles by this author Kazuhiro Yoshimura More articles by this author Hirotsugu Uemura More articles by this author Shota Nakamura More articles by this author Norio Nonomura More articles by this author Expand All Advertisement Loading ...

The role of magnetic resonance imaging in active surveillance of prostate cancer.

Active surveillance (AS) is an important strategy to avoid overtreatment of prostate cancer (PCa) and has become the standard of care for low-risk patients. The role of magnetic resonance imaging (MRI) in AS has expanded due to its ability to risk stratify patients with suspected or known PCa, and MRI has become an integral part of the AS protocols at various institutions. A negative pre-biopsy MRI result is associated with a very high negative predictive value for a Gleason score ≥ 3+4. A positive MRI result in men who are otherwise eligible for AS has been shown to be associated with the presence of high-grade PCa and therefore with ineligibility. In addition, MRI can be used to guide and determine the timing of per-protocol biopsy during AS. However, there are several MRI-related issues that remain unresolved, including the lack of a consensus and guidelines; concerns about gadolinium deposition in various tissues; and increased demand for higher efficiency and productivity. Similarly, the need for the combined use of targeted and systematic sampling is still a matter of debate when lesions are visible on MRI. Here, we review the current AS guidelines, as well as the accepted roles of MRI in patient selection and monitoring, the potential uses of MRI that are still in question, and the limitations of the method.

Evaluation of serum fatty acid binding protein-4 (FABP-4) as a novel biomarker to predict biopsy outcomes in prostate biopsy naïve patients.

To investigate the role of serum fatty acid-binding protein-4 (FABP-4) as a surrogate of obesity and metabolic syndrome in the prediction of the outcome of prostate biopsy. A prospective pilot study was conducted for patients undergoing prostate needle biopsy (PNB) for clinically suspected prostate cancer (PCa) between June 2016 and August 2017. Fifty consecutive patients with biopsy-proven PCa were included as study group and 50 consecutive patients with negative biopsy were included as a control group. Receiver Operating Characteristic (ROC) curve was used to calculate the area under the curve (AUC) to compare the accuracy of the different parameters in the diagnosis as well as the presence of high-grade PCa (Gleason score 8-9) at PNB. Predictors of the outcome were analyzed using univariate and multivariate logistic regression analysis. FABP-4 (AUC: 0.75; P < 0.001) and PSA-density (AUC: 0.84; P < 0.001) were the most accurate to detect PCa at PNB. On multivariate analysis, FABP-4 > 22.5ng/ml (OR: 16.6; 95% CI 2.8-98; P = 0.002) and PSA-density > 0.38ng/ml/ml OR: 17.7; 95% CI 5.3-59; P < 0.001) were independent predictors of PCa detection. Regarding high-grade PCa at PNB, FABP-4 (AUC: 0.79; P < 0.001) and %Free-PSA (AUC: 0.75; P < 0.001) were the most accurate. Independent predictors of high-grade PCa were FABP-4 > 32.3ng/ml OR: 9.2; 95% CI 1.8-45; P = 0.006) and %Free-PSA ≤ 21.9 (OR: 5.5; 95% CI 1.1-27; P = 0.03). FABP-4 is an independent predictor for both the diagnosis and high-grade Gleason score at PNB. This novel biomarker might have a promising role in optimizing PNB outcomes.

Analytical validation of an mRNA-based urine test to predict the presence of high-grade prostate cancer

BackgroundThe challenge for prostate cancer (PCa) diagnosis is to improve the ability to distinguish indolent from aggressive PCa. Increased urinary levels of Distal-less Homeobox 1 (DLX1) and Homeobox C6 (HOXC6) mRNA have been associated with high-grade PCa (Gleason Score ≥7). Reverse transcriptase PCR (RT-PCR)-assays for the quantification of DLX1 and HOXC6 mRNA levels were developed, and clinical validation showed that these urinary markers can significantly improve accuracy for detection of high-grade PCa at biopsy. The aim of this study was to validate the analytical performance of these mRNA-based assays, including specimen stability and analytical sensitivity, specificity, precision, repeatability and reproducibility.MethodsAnalytical validation of the RT-PCR assays for DLX1, HOXC6 and KLK3 was performed using in vitro transcribed (IVT) specimens of the target genes, covering all aspects of the analytical method including assay sensitivity, specificity, linearity, precision, repeatability and reproducibility using pre-specified acceptance criteria. To confirm that the mRNA assays are sufficient robust for use in clinical routine laboratories, the performance characteristics were verified in an independent laboratory using post-DRE collected urine samples from 101 men scheduled for prostate biopsy.ResultsA stabilization buffer, developed for urine preservation under standard pre-processing conditions, makes sample shipment from clinics to laboratories easily feasible. The mRNA in urine samples, preserved in this stabilization buffer, is stable at room temperature up to 5 days from collection, resulting in 100% evaluable rate. The long term stability of the mRNAs in the buffer was shown by similar clinical performances using RNA values obtained immediately after urine collection (area under curve (AUC) 0.72(95% CI: 0.61–0.83)) and after 1-year storage (AUC 0.71 (95% CI: 0.60–0.81)). Test performance was not compromised by most common inhibitors and bacterial strains found in urine. However, an inhibitory effect of hemoglobin was observed.All precision, reproducibility, instrument and inter-laboratory variation data obtained for the mRNA-based assays met the pre-specified acceptance criteria of a standard deviation less than or equal to 0.5 crossing point. The analysis of 99 whole urine samples at two laboratories indicated a very strong positive correlation (r = 0.997, P < 0.001). The test outcome in terms of absolute difference in likelihood for high-grade PCa upon biopsy was less than 2% between the two sites.ConclusionsThis study illustrates the robustness of the mRNA assays, enabling testing in clinical routine laboratories and molecular pathology laboratories where the here described automated RNA extraction and PCR platforms are available.

The 4Kscore Predicts the Grade and Stage of Prostate Cancer in the Radical Prostatectomy Specimen: Results from a Multi-institutional Prospective Trial

BackgroundThe 4Kscore accurately predicts aggressive prostate cancer (PCa) on prostate biopsy. ObjectiveWe assessed how well the 4Kscore predicts pathology at radical prostatectomy (RP). Design, setting, and participantsAmong 1312 men who prospectively underwent a 4Kscore and biopsy of the prostate at 26 sites throughout the United States from October 2013 to April 2014, we selected men who were diagnosed with cancer and underwent RP. Outcome measurements and statistical analysisThe primary outcome was the presence of high-grade PCa or extracapsular extension. We assessed the association between the 4Kscore and the grade and extent of PCa at RP using the Wilcoxon rank sum test. We used logistic regression to investigate the added value of the 4Kscore in predicting a high-grade or non–organ-confined tumor when added to available postbiopsy clinical predictive tools. Results and limitationsA total of 144 men were diagnosed with PCa and underwent RP. Higher 4Kscores were associated with higher grade at RP. For men with Gleason scores ≥6, 7, and 8 cancers in the surgical specimen, the median 4Kscores were 7% (interquartile range [IQR]: 4–2), 25% (IQR: 12–38), and 47% (IQR: 24–66) (p<0.0001), respectively. The median 4Kscore among men with non–organ-confined cancer was significantly higher then men with organ-confined cancers (36% [IQR: 19–58] vs 19% [IQR: 9–35]; p=0.002). The 4Kscore did not significantly add to available clinical prediction tools for determining the likelihood of a high grade or non–organ-confined cancer; however, we were limited by a small sample size for this analysis. ConclusionsIn a subset of men who underwent RP, the 4Kscore was significantly associated with pathologic grade and extracapsular extension in the surgical specimen, with higher scores associated with higher grade and more aggressive histology. The 4Kscore test may be helpful in selecting men who are likely to have adverse pathologic features at RP that may preclude them from being safely observed. Patient summaryAmong men with prostate cancer who underwent removal of the prostate, the 4Kscore was associated with the final grade and extent of cancer.

Come Biopsiare Solo i Pazienti con Tumore Prostatico ad Alto Grado?

Fuzzy logic and Artificial Neural Networks (ANN) are complementary technologies that together generate neuro-fuzzy system. The aim of our study is to compare 2 models for predicting the presence of high-grade prostate cancer (Gleason score 7 or more). We evaluated data from 1000 men with PSA less than 50 ng/mL, who underwent prostate biopsy. A prostate cancer was found in 313 (31%), and in 172 (17.2%) we detected high-grade prostate cancer. With those data, we developed 2 Co-Active Neuro-Fuzzy Inference Systems to predict the presence of high-grade prostate cancer. The first model had four input neurons (PSA, free PSA percentage [%freePSA], PSA density, and age) and the second model had three input neurons (PSA, %freePSA, and age). The model with four input neurons (PSA, %freePSA, PSA density, and age) showed better performances than the one with three input neurons (PSA, %freePSA, and age). In fact the average testing error was 0.42 for the model with four input neurons and 0.44 for the other model. The addition of PSA density to the model has allowed to obtain better results for the diagnosis of high grade prostate cancer.

DEVELOPMENT OF A NOMOGRAM FOR PREDICTING HIGH- GRADE PROSTATE CANCER ON BIOPSY: THE SIGNIFICANCE OF SERUM TESTOSTERONE LEVELS

BACKGROUND: A screening method that focuses on the early detection of high-grade prostate cancer is required. In this study, two sets of nomograms were developed, one to predict the presence of prostate cancer, and the other to predict the presence of high-grade prostate cancer (defined as Gleason Score > or =7). PATIENTS AND METHODS: Prostate biopsies were obtained from 396 men with an abnormal serum level of prostate-specific antigen (PSA). Using factors including age, PSA, follicle stimulating hormone (FSH), serum teststerone level and prostate volume of the transitional zone (TZ), nomograms were created that incorporated these factors. External validations were performed involving 174 males, including 103 normal and 71 prostate cancer cases from our institution. RESULTS: Out of the 396 patients referred for prostate biopsy, 146 were found to have prostate cancer. On logistic regression analysis, age, PSA, prostate volume of the TZ and FSH were significant predictors of prostate cancer, while serum PSA, and testosterone levels were significant predictors of high-grade prostate cancer. The pretreatment testosterone level was found to be a significant biomarker for predicting the pathological features. CONCLUSION: The testosterone level might be a useful biomarker to be included in conventional PSA screening programs to further improve the efficacy of detecting potentially lethal carcinomas.

POD-08.07: A comparison of predictive nomograms for the presence of high grade prostate cancer: the PCPT risk calculator, the Spurgeon CART and the Windsor model

The ability to predict the absence or presence of high grade prostate cancer on biopsy may help in the selection of patients for prostate biopsy. The Prostate Cancer Prevention Trial (PCPT) has generated a predictive calculator for the presence of high-grade prostate cancer and this can be used over the internet. A classification and regression tree (CART) has been produced to predict high-grade prostate cancer and this utilises information gleaned from prostate ultrasound. The aim was to compare the accuracy of these nomograms for the prediction of all and high-grade prostate cancer with a locally generated logistic regression (‘Windsor Model’).

Nomogram for the prediction of high-grade prostate cancer on ultrasound-guided needle biopsy

4621 Background: Prostate cancer is characterized by a wide spectrum of biologic heterogeneity that results in divergent clinical outcomes. Thus, not all patients benefit from aggressive therapy. Tumor grade is the most important of the clinicopathologic factors that predict tumor aggressiveness and therefore drive decisions regarding aggressive local therapy vs. observation. The goal of this study was to develop a nomogram for the prediction of high-grade prostate cancer (defined as Gleason ≥ 7) using pre-biopsy factors. Methods: Data were prospectively collected on 1,699 referred men with a serum PSA of ≤ 10 ng/ml who underwent a prostate biopsy (minimum 6 cores). Variables analyzed included: age, race, family history, digital rectal exam (DRE), prostate-specific antigen (PSA), PSA density (PSAD), prostate volume, PSA doubling time (PSADT), and ultrasound (US) findings. Thirty percent of the data were randomly reserved for study validation. Logistic regression analysis was performed to estimate the relative risk (RR) and 95% confidence intervals (CI). Results: The cohort was characterized as follows (values: median ± SD): age = 66.0 ± 7.5 years, PSA = 5.0 ± 2.5 ng/ml/cc, PSAD = 0.12 ± 0.10 ng/ml/cc, volume = 35.0 ± 23.6 cc. High-grade prostate cancer was detected in 157 subjects (9.2%). The results of the multivariate analysis are shown in the table and a user-friendly nomogram was constructed based on these results. Using the independent validation set the area under the ROC was 0.74 for the model. Conclusions: The presence of high-grade prostate cancer was successfully predicted using a multi-factor logistic regression-based model. Models such as this have the potential to significantly reduce the number of biopsy procedures performed when subsequent therapy is contingent upon the detection of high-grade prostate cancer. No significant financial relationships to disclose.

Prediction of aggressive prostate cancer on biopsy using classification and regression tree analysis (CART)

4720 Background: Prostate cancer screening allows for the early detection of disease; however, not all cancer patients are candidates for intervention due patient co-morbidities and the indolent nature of some tumors. Distinguishing patients who are likely to harbor aggressive prostate cancer could significantly reduce the number of prostate biopsies performed in men that would be offered treatment only in the presence of high-grade prostate cancer. Methods: Data were collected on 1,563 consecutive referred men with a serum prostate specific antigen (PSA) of ≤ 10 ng/ml who underwent an initial prostate biopsy. Predictors of aggressive cancer (defined as Gleason sum ≥ 7) were identified using CART analysis that considered demographic variables (age, race, reason for referral, history of vasectomy, and family history), digital rectal exam findings, serum prostate–specific antigen levels (PSA), TRUS findings (prostate volume, hypoechoic lesion) and PSA density (serum PSA/prostate volume). The model building was carried out on 70% of the data (randomly selected training set) and study validation was carried using the remaining 30% of the data (validation set). Results: 408 (26.1%) of men had prostate cancer. Of these, 129 (31.6%) were determined to be Gleason ≥ 7. CART analysis created a decision tree that identified the following groups to be at high-risk for the detection of Gleason ≥ 7 prostate cancer: (1) PSAD > 0.165 ng/ml/cc; and (2) PSAD ≤ 0.165 ng/ml/cc and age > 57.5 years, and prostate volume > 22.7 cc. The performance of the decision tree is shown below: Conclusions: CART analysis successfully identified groups at high risk for the diagnosis of Gleason ≥ 7 prostate cancer. Application of this model to clinical practice would result in a 33.5% reduction in unnecessary biopsies when a diagnosis of high-grade prostate cancer would be the primary determinant of subsequent treatment decisions. No significant financial relationships to disclose.

Prediction of aggressive prostate cancer on biopsy using classification and regression tree analysis (CART)

4720 Background: Prostate cancer screening allows for the early detection of disease; however, not all cancer patients are candidates for intervention due patient co-morbidities and the indolent nature of some tumors. Distinguishing patients who are likely to harbor aggressive prostate cancer could significantly reduce the number of prostate biopsies performed in men that would be offered treatment only in the presence of high-grade prostate cancer. Methods: Data were collected on 1,563 consecutive referred men with a serum prostate specific antigen (PSA) of ≤ 10 ng/ml who underwent an initial prostate biopsy. Predictors of aggressive cancer (defined as Gleason sum ≥ 7) were identified using CART analysis that considered demographic variables (age, race, reason for referral, history of vasectomy, and family history), digital rectal exam findings, serum prostate–specific antigen levels (PSA), TRUS findings (prostate volume, hypoechoic lesion) and PSA density (serum PSA/prostate volume). The model building was carried out on 70% of the data (randomly selected training set) and study validation was carried using the remaining 30% of the data (validation set). Results: 408 (26.1%) of men had prostate cancer. Of these, 129 (31.6%) were determined to be Gleason ≥ 7. CART analysis created a decision tree that identified the following groups to be at high-risk for the detection of Gleason ≥ 7 prostate cancer: (1) PSAD > 0.165 ng/ml/cc; and (2) PSAD ≤ 0.165 ng/ml/cc and age > 57.5 years, and prostate volume > 22.7 cc. The performance of the decision tree is shown below: Conclusions: CART analysis successfully identified groups at high risk for the diagnosis of Gleason ≥ 7 prostate cancer. Application of this model to clinical practice would result in a 33.5% reduction in unnecessary biopsies when a diagnosis of high-grade prostate cancer would be the primary determinant of subsequent treatment decisions. No significant financial relationships to disclose.