ORCID Profile
0000-0001-8831-3244
Current Organisation
University College Dublin
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Publisher: Springer Science and Business Media LLC
Date: 05-08-2014
DOI: 10.1007/S00345-014-1365-7
Abstract: To compare the prostate cancer prevention trial risk calculator (PCPT-RC) and European randomized study of screening for prostate cancer risk calculator (ERSPC-RC) in a unique unscreened population from the West of Ireland. Data was prospectively recorded for all 556 consecutive men who underwent prostate biopsy at our institution as part of the Rapid Access Prostate Assessment Clinic program in Ireland. The estimated probabilities of detecting prostate cancer and high-grade disease were calculated using the PCPT and ERSPC risk calculators. For each calculator the discriminative ability, calibration and clinical utility was assessed. Prostate cancer was detected in 49% and high-grade prostate cancer in 34% of men. Receiver operating characteristic curve analysis demonstrated that the PCPT-RCs outperformed the ERSPC-RCs for the prediction of prostate cancer areas underneath the ROC curve (AUC 0.628 vs. 0.588, p = 0.0034) and for the prediction of high-grade prostate cancer (AUC 0.792 vs. 0.690, p = 0.0029). Both risk calculators generally over-predicted the risk of prostate cancer and high-grade disease across a wide range of predicted probabilities. Decision curve analysis suggested greater net benefit using the PCPT-RCs in this population. Multivariable nomograms can further aid patient counselling for early prostate cancer detection. In unscreened men from Western Ireland, the PCPT-RCs provided better discrimination for overall prostate cancer and high-grade disease compared to the ERSPC-RC. However, both tools overpredicted the risk of cancer detection on biopsy, and it is possible that a different set of predictive variables may be more useful in this population.
Publisher: MDPI AG
Date: 03-12-2020
DOI: 10.3390/IJMS21239233
Abstract: The diagnosis and treatment of prostate cancer (PCa) is a major health-care concern worldwide. This cancer can manifest itself in many distinct forms and the transition from clinically indolent PCa to the more invasive aggressive form remains poorly understood. It is now universally accepted that glycan expression patterns change with the cellular modifications that accompany the onset of tumorigenesis. The aim of this study was to investigate if differential glycosylation patterns could distinguish between indolent, significant, and aggressive PCa. Whole serum N-glycan profiling was carried out on 117 prostate cancer patients’ serum using our automated, high-throughput analysis platform for glycan-profiling which utilizes ultra-performance liquid chromatography (UPLC) to obtain high resolution separation of N-linked glycans released from the serum glycoproteins. We observed increases in hybrid, oligomannose, and biantennary digalactosylated monosialylated glycans (M5A1G1S1, M8, and A2G2S1), bisecting glycans (A2B, A2(6)BG1) and monoantennary glycans (A1), and decreases in triantennary trigalactosylated trisialylated glycans with and without core fucose (A3G3S3 and FA3G3S3) with PCa progression from indolent through significant and aggressive disease. These changes give us an insight into the disease pathogenesis and identify potential biomarkers for monitoring the PCa progression, however these need further confirmation studies.
Publisher: Elsevier BV
Date: 10-2017
DOI: 10.1016/J.EURURO.2017.03.027
Abstract: Approximately 4-25% of patients with early prostate cancer develop disease recurrence following radical prostatectomy. To identify a molecular subgroup of prostate cancers with metastatic potential at presentation resulting in a high risk of recurrence following radical prostatectomy. Unsupervised hierarchical clustering was performed using gene expression data from 70 primary resections, 31 metastatic lymph nodes, and 25 normal prostate s les. Independent assay validation was performed using 322 radical prostatectomy s les from four sites with a mean follow-up of 50.3 months. Molecular subgroups were identified using unsupervised hierarchical clustering. A partial least squares approach was used to generate a gene expression assay. Relationships with outcome (time to biochemical and metastatic recurrence) were analysed using multivariable Cox regression and log-rank analysis. A molecular subgroup of primary prostate cancer with biology similar to metastatic disease was identified. A 70-transcript signature (metastatic assay) was developed and independently validated in the radical prostatectomy s les. Metastatic assay positive patients had increased risk of biochemical recurrence (multivariable hazard ratio [HR] 1.62 [1.13-2.33] p=0.0092) and metastatic recurrence (multivariable HR=3.20 [1.76-5.80] p=0.0001). A combined model with Cancer of the Prostate Risk Assessment post surgical (CAPRA-S) identified patients at an increased risk of biochemical and metastatic recurrence superior to either model alone (HR=2.67 [1.90-3.75] p<0.0001 and HR=7.53 [4.13-13.73] p<0.0001, respectively). The retrospective nature of the study is acknowledged as a potential limitation. The metastatic assay may identify a molecular subgroup of primary prostate cancers with metastatic potential. The metastatic assay may improve the ability to detect patients at risk of metastatic recurrence following radical prostatectomy. The impact of adjuvant therapies should be assessed in this higher-risk population.
Publisher: Wiley
Date: 07-08-2015
DOI: 10.1002/PROS.23051
Publisher: MDPI AG
Date: 25-10-2017
Publisher: Elsevier BV
Date: 02-2023
DOI: 10.1016/J.PATHOL.2022.08.001
Abstract: Diagnosis and assessment of patients with prostate cancer is dependent on accurate interpretation and grading of histopathology. However, morphology does not necessarily reflect the complex biological changes occurring in prostate cancer disease progression, and current biomarkers have demonstrated limited clinical utility in patient assessment. This study aimed to develop biomarkers that accurately define prostate cancer biology by distinguishing specific pathological features that enable reliable interpretation of pathology for accurate Gleason grading of patients. Online gene expression databases were interrogated and a pathogenic pathway for prostate cancer was identified. The protein expression of key genes in the pathway, including adaptor protein containing a pleckstrin homology (PH) domain, phosphotyrosine-binding (PTB) domain, and leucine zipper motif 1 (Appl1), Sortilin and Syndecan-1, was examined by immunohistochemistry (IHC) in a pilot study of 29 patients with prostate cancer, using monoclonal antibodies designed against unique epitopes. Appl1, Sortilin, and Syndecan-1 expression was first assessed in a tissue microarray cohort of 112 patient s les, demonstrating that the monoclonal antibodies clearly illustrate gland morphologies. To determine the impact of a novel IHC-assisted interpretation (the utility of Appl1, Sortilin, and Syndecan-1 labelling as a panel) of Gleason grading, versus standard haematoxylin and eosin (H&E) Gleason grade assignment, a radical prostatectomy s le cohort comprising 114 patients was assessed. In comparison to H&E, the utility of the biomarker panel reduced subjectivity in interpretation of prostate cancer tissue morphology and improved the reliability of pathology assessment, resulting in Gleason grade redistribution for 41% of patient s les. Importantly, for equivocal IHC-assisted labelling and H&E staining results, the cancer morphology interpretation could be more accurately applied upon re-review of the H&E tissue sections. This study addresses a key issue in the field of prostate cancer pathology by presenting a novel combination of three biomarkers and has the potential to transform clinical pathology practice by standardising the interpretation of the tissue morphology.
No related grants have been discovered for William Watson.