11 research outputs found
Global Hypomethylation (LINE-1) and Gene-Specific Hypermethylation (GSTP1) on Initial Negative Prostate Biopsy as Markers of Prostate Cancer on a Rebiopsy
Cohort profile: the Turin prostate cancer prognostication (TPCP) cohort
IntroductionProstate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors. To further improve current prognostication models, we established the Turin Prostate Cancer Prognostication (TPCP) cohort, an Italian retrospective biopsy cohort of patients with PCa and long-term follow-up. This work presents this new cohort with its main characteristics and the distributions of some of its core variables, along with its potential contributions to PCa research.MethodsThe TPCP cohort includes consecutive non-metastatic patients with first positive biopsy for PCa performed between 2008 and 2013 at the main hospital in Turin, Italy. The follow-up ended on December 31st 2021. The primary outcome is the occurrence of metastasis; death from PCa and overall mortality are the secondary outcomes. In addition to numerous clinical variables, the study’s prognostic variables include histopathologic information assigned by a centralized uropathology review using a digital pathology software system specialized for the study of PCa, tumor DNA methylation in candidate genes, and features extracted from digitized slide images via Deep Neural Networks.ResultsThe cohort includes 891 patients followed-up for a median time of 10 years. During this period, 97 patients had progression to metastatic disease and 301 died; of these, 56 died from PCa. In total, 65.3% of the cohort has a Gleason score less than or equal to 3 + 4, and 44.5% has a clinical stage cT1. Consistent with previous studies, age and clinical stage at diagnosis are important prognostic factors: the crude cumulative incidence of metastatic disease during the 14-years of follow-up increases from 9.1% among patients younger than 64 to 16.2% for patients in the age group of 75-84, and from 6.1% for cT1 stage to 27.9% in cT3 stage.DiscussionThis study stands to be an important resource for updating existing prognostic models for PCa on an Italian cohort. In addition, the integrated collection of multi-modal data will allow development and/or validation of new models including new histopathological, digital, and molecular markers, with the goal of better directing clinical decisions to manage patients with PCa
DataSheet_1_Nomograms predicting local and distant recurrence and disease-specific mortality for R0/R1 soft tissue sarcomas of the extremities.docx
BackgroundPrognostic models for patients with soft tissue sarcoma (STS) of the extremities have been developed from large multi-institutional datasets with mixed results. We aimed to develop predictive nomograms for sarcoma-specific survival (SSS) and, for the first time, long-term local recurrence (LR) and distant recurrence (DR) in patients with STS of the extremities treated at our institution.Patients and methodsData from patients treated at Humanitas Cancer Center from 1997 to 2015 were analyzed. Variable selection was based on the clinical knowledge and multivariable regression splines algorithm. Perioperative treatments were always included in the model. Prognostic models were developed using Cox proportional hazards model, and model estimates were plotted in nomograms predicting SSS at 5 and 10 years and LR and DR at 2, 5, and 10 years. Model performance was estimated internally via bootstrapping, in terms of optimism-corrected discrimination (Harrell C-index) and calibration (calibration plots).ResultsData on 517 patients were analyzed. At 5 and 10 years, SSS was 68.1% [95% confidence interval (CI), 63.8–72.1] and 55.6% (50.5–60.3), respectively. LR was 79.1% (95% CI, 75.3–82.4), 71.1% (95% CI, 66.7–75.1), and 66.0% (95% CI, 60.7–70.7) at 2, 5, and 10 years, respectively, whereas DR was 65.9% (95% CI, 61.6–69.9), 57.5% (95% CI, 53.0–61.8), and 52.1% (95% CI, 47.1–56.8) at 2, 5, and 10 years, respectively. SSS nomogram included age, gender, margins, tumor size, grading, and histotype. LR and DR nomograms incorporated mostly the same variables, except for age for DR; LR nomogram did not include gender but included anatomic site. The optimism-corrected C-indexes were 0.73 and 0.72 for SSS at 5 and 10 years, respectively; 0.65, 0.64, and 0.64 for LR at 2, 5, and 10 years, respectively; and 0.68 for DR at 2, 5, and 10 years. Predicted probabilities were close to the observed ones for all outcomes.ConclusionsWe developed and validated three nomograms for STS of the extremities predicting the probability of SSS at 5 and 10 years and LR and DR at 2, 5, and 10 years. By accounting for the perioperative treatment, these models allow prediction for future patients who had no perioperative treatment, thus being useful in the clinical decision-making process.</p
Single-nucleotide polymorphisms in DNMT3B gene and DNMT3B mRNA expression in association with prostate cancer mortality.
Global DNA hypomethylation in prostate cancer development and progression: a systematic review.
Quantity and quality of nucleic acids extracted from archival formalin fixed paraffin embedded prostate biopsies
Abstract Background In Sweden, human tissue samples obtained from diagnostic and surgical procedures have for decades been routinely stored in a formalin-fixed, paraffin-embedded, form. Through linkage with nationwide registers, these samples are available for molecular studies to identify biomarkers predicting mortality even in slow-progressing prostate cancer. However, tissue fixation causes modifications of nucleic acids, making it challenging to extract high-quality nucleic acids from formalin fixated tissues. Methods In this study, the efficiency of five commercial nucleic acid extraction kits was compared on 30 prostate biopsies with normal histology, and the quantity and quality of the products were compared using spectrophotometry and Agilent’s BioAnalyzer. Student’s t-test’s and Bland-Altman analyses were performed in order to investigate differences in nucleic acid quantity and quality between the five kits. The best performing extraction kits were subsequently tested on an additional 84 prostate tumor tissues. A Spearman’s correlation test and linear regression analyses were performed in order to investigate the impact of tissue age and amount of tissue on nucleic acid quantity and quality. Results Nucleic acids extracted with RNeasy® FFPE and QIAamp® DNA FFPE Tissue kit had the highest quantity and quality, and was used for extraction from 84 tumor tissues. Nucleic acids were successfully extracted from all biopsies, and the amount of tumor (in millimeter) was found to have the strongest association with quantity and quality of nucleic acids. Conclusions To conclude, this study shows that the choice of nucleic acid extraction kit affects the quantity and quality of extracted products. Furthermore, we show that extraction of nucleic acids from archival formalin-fixed prostate biopsies is possible, allowing molecular studies to be performed on this valuable sample collection
Interchangeability of light and virtual microscopy for histopathological evaluation of prostate cancer
Virtual microscopy (VM) holds promise to reduce subjectivity as well as intra- and inter-observer variability for the histopathological evaluation of prostate cancer. We evaluated (i) the repeatability (intra-observer agreement) and reproducibility (inter-observer agreement) of the 2014 Gleason grading system and other selected features using standard light microscopy (LM) and an internally developed VM system, and (ii) the interchangeability of LM and VM. Two uro-pathologists reviewed 413 cores from 60 Swedish men diagnosed with non-metastatic prostate cancer 1998-2014. Reviewer 1 performed two reviews using both LM and VM. Reviewer 2 performed one review using both methods. The intra- and inter-observer agreement within and between LM and VM were assessed using Cohen's kappa and Bland and Altman's limits of agreement. We found good repeatability and reproducibility for both LM and VM, as well as interchangeability between LM and VM, for primary and secondary Gleason pattern, Gleason Grade Groups, poorly formed glands, cribriform pattern and comedonecrosis but not for the percentage of Gleason pattern 4. Our findings confirm the non-inferiority of VM compared to LM. The repeatability and reproducibility of percentage of Gleason pattern 4 was poor regardless of method used warranting further investigation and improvement before it is used in clinical practice
Estimation of Relative and Absolute Risks in a Competing-Risks Setting Using a Nested Case-Control Study Design: Example From the ProMort Study
In this paper, we describe the Prognostic Factors for Mortality in Prostate Cancer (ProMort) study and use it to demonstrate how the weighted likelihood method can be used in nested case-control studies to estimate both relative and absolute risks in the competing-risks setting. ProMort is a case-control study nested within the National Prostate Cancer Register (NPCR) of Sweden, comprising 1,710 men diagnosed with low- or intermediate-risk prostate cancer between 1998 and 2011 who died from prostate cancer (cases) and 1,710 matched controls. Cause-specific hazard ratios and cumulative incidence functions (CIFs) for prostate cancer death were estimated in ProMort using weighted flexible parametric models and compared with the corresponding estimates from the NPCR cohort. We further drew 1,500 random nested case-control subsamples of the NPCR cohort and quantified the bias in the hazard ratio and CIF estimates. Finally, we compared the ProMort estimates with those obtained by augmenting competing-risks cases and by augmenting both competing-risks cases and controls. The hazard ratios for prostate cancer death estimated in ProMort were comparable to those in the NPCR. The hazard ratios for dying from other causes were biased, which introduced bias in the CIFs estimated in the competing-risks setting. When augmenting both competing-risks cases and controls, the bias was reduced
Single-nucleotide polymorphisms in DNMT3B gene and DNMT3B mRNA expression in association with prostate cancer mortality
DataSheet_1_Cohort profile: the Turin prostate cancer prognostication (TPCP) cohort.pdf
IntroductionProstate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors. To further improve current prognostication models, we established the Turin Prostate Cancer Prognostication (TPCP) cohort, an Italian retrospective biopsy cohort of patients with PCa and long-term follow-up. This work presents this new cohort with its main characteristics and the distributions of some of its core variables, along with its potential contributions to PCa research.MethodsThe TPCP cohort includes consecutive non-metastatic patients with first positive biopsy for PCa performed between 2008 and 2013 at the main hospital in Turin, Italy. The follow-up ended on December 31st 2021. The primary outcome is the occurrence of metastasis; death from PCa and overall mortality are the secondary outcomes. In addition to numerous clinical variables, the study’s prognostic variables include histopathologic information assigned by a centralized uropathology review using a digital pathology software system specialized for the study of PCa, tumor DNA methylation in candidate genes, and features extracted from digitized slide images via Deep Neural Networks.ResultsThe cohort includes 891 patients followed-up for a median time of 10 years. During this period, 97 patients had progression to metastatic disease and 301 died; of these, 56 died from PCa. In total, 65.3% of the cohort has a Gleason score less than or equal to 3 + 4, and 44.5% has a clinical stage cT1. Consistent with previous studies, age and clinical stage at diagnosis are important prognostic factors: the crude cumulative incidence of metastatic disease during the 14-years of follow-up increases from 9.1% among patients younger than 64 to 16.2% for patients in the age group of 75-84, and from 6.1% for cT1 stage to 27.9% in cT3 stage.DiscussionThis study stands to be an important resource for updating existing prognostic models for PCa on an Italian cohort. In addition, the integrated collection of multi-modal data will allow development and/or validation of new models including new histopathological, digital, and molecular markers, with the goal of better directing clinical decisions to manage patients with PCa.</p