1
|
Inoue T, Shin T. Current magnetic resonance imaging-based diagnostic strategies for prostate cancer. Int J Urol 2023; 30:1078-1086. [PMID: 37592819 DOI: 10.1111/iju.15281] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 08/02/2023] [Indexed: 08/19/2023]
Abstract
Recent developments in multiparametric MRI and MRI-targeted biopsy have made it possible to detect clinically significant cancers more accurately and efficiently than ever before. Furthermore, software that enables easy MRI/US image fusion has been developed and is already available on the market, and this has provided a tailwind for the spread of MRI-based prostate cancer diagnostic strategies. Such precise diagnosis of prostate cancer localization is essential for highly accurate focal therapy. In addition, a recent large-scale study applying MRI to community screening for prostate cancer has reported its usefulness. By contrast, concerns about overdiagnosis and overtreatment, the existence of inter-reader variability in MRI diagnosis, and issues with current MRI-targeted biopsy have emerged. In this article, we review the development of multiparametric MRI and MRI-targeted biopsy to date and the current issues and discuss future directions.
Collapse
Affiliation(s)
- Toru Inoue
- Department of Urology, Oita University Faculty of Medicine, Oita, Japan
| | - Toshitaka Shin
- Department of Urology, Oita University Faculty of Medicine, Oita, Japan
| |
Collapse
|
2
|
Yang L, Li XM, Zhang MN, Yao J, Song B. Nomogram Models for Distinguishing Intraductal Carcinoma of the Prostate From Prostatic Acinar Adenocarcinoma Based on Multiparametric Magnetic Resonance Imaging. Korean J Radiol 2023; 24:668-680. [PMID: 37404109 DOI: 10.3348/kjr.2022.1022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 04/29/2023] [Accepted: 05/16/2023] [Indexed: 07/06/2023] Open
Abstract
OBJECTIVE To compare multiparametric magnetic resonance imaging (MRI) features of intraductal carcinoma of the prostate (IDC-P) with those of prostatic acinar adenocarcinoma (PAC) and develop prediction models to distinguish IDC-P from PAC and IDC-P with a high proportion (IDC ≥ 10%, hpIDC-P) from IDC-P with a low proportion (IDC < 10%, lpIDC-P) and PAC. MATERIALS AND METHODS One hundred and six patients with hpIDC-P, 105 with lpIDC-P and 168 with PAC, who underwent pretreatment multiparametric MRI between January 2015 and December 2020 were included in this study. Imaging parameters, including invasiveness and metastasis, were evaluated and compared between the PAC and IDC-P groups as well as between the hpIDC-P and lpIDC-P subgroups. Nomograms for distinguishing IDC-P from PAC, and hpIDC-P from lpIDC-P and PAC, were made using multivariable logistic regression analysis. The discrimination performance of the models was assessed using the receiver operating characteristic area under the curve (ROC-AUC) in the sample, where the models were derived from without an independent validation sample. RESULTS The tumor diameter was larger and invasive and metastatic features were more common in the IDC-P than in the PAC group (P < 0.001). The distribution of extraprostatic extension (EPE) and pelvic lymphadenopathy was even greater, and the apparent diffusion coefficient (ADC) ratio was lower in the hpIDC-P than in the lpIDC-P group (P < 0.05). The ROC-AUCs of the stepwise models based solely on imaging features for distinguishing IDC-P from PAC and hpIDC-P from lpIDC-P and PAC were 0.797 (95% confidence interval, 0.750-0.843) and 0.777 (0.727-0.827), respectively. CONCLUSION IDC-P was more likely to be larger, more invasive, and more metastatic, with obviously restricted diffusion. EPE, pelvic lymphadenopathy, and a lower ADC ratio were more likely to occur in hpIDC-P, and were also the most useful variables in both nomograms for predicting IDC-P and hpIDC-P.
Collapse
Affiliation(s)
- Ling Yang
- Department of Radiology, West China Hospital, Sichuan University, Sichuan, China
| | - Xue-Ming Li
- Department of Radiology, West China Hospital, Sichuan University, Sichuan, China
| | - Meng-Ni Zhang
- Department of Pathology, West China Hospital, Sichuan University, Sichuan, China
| | - Jin Yao
- Department of Radiology, West China Hospital, Sichuan University, Sichuan, China.
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Sichuan, China.
| |
Collapse
|
3
|
Yu X, Liu R, Song L, Gao W, Wang X, Zhang Y. Differences in the pathogenetic characteristics of prostate cancer in the transitional and peripheral zones and the possible molecular biological mechanisms. Front Oncol 2023; 13:1165732. [PMID: 37456243 PMCID: PMC10348634 DOI: 10.3389/fonc.2023.1165732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 06/13/2023] [Indexed: 07/18/2023] Open
Abstract
Since the theory of modern anatomical partitioning of the prostate was proposed, the differences in the incidence and pathological parameters of prostate cancer between the peripheral zone and transition zone have been gradually revealed. It suggests that there are differences in the pathogenic pathways and molecular biology of prostate cancer between different regions of origin. Over the past decade, advances in sequencing technologies have revealed more about molecules, genomes, and cell types specific to the peripheral and transitional zones. In recent years, the innovation of spatial imaging and multiple-parameter magnetic resonance imaging has provided new technical support for the zonal study of prostate cancer. In this work, we reviewed all the research results and the latest research progress in the study of prostate cancer in the past two decades. We summarized and proposed several vital issues and focused directions for understanding the differences between peripheral and transitional zones in prostate cancer.
Collapse
Affiliation(s)
- Xudong Yu
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
- Beijing Tumor Minimally Invasive Medical Center of Integrated Traditional Chinese and Western Medicine, Dongzhimen Hospital, Beijing University of Chinese Medicine and Beijing Municipal Health Commission, Beijing, China
| | - Ruijia Liu
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Lianying Song
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Wenfeng Gao
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Xuyun Wang
- Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
| | - Yaosheng Zhang
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
- Beijing Tumor Minimally Invasive Medical Center of Integrated Traditional Chinese and Western Medicine, Dongzhimen Hospital, Beijing University of Chinese Medicine and Beijing Municipal Health Commission, Beijing, China
| |
Collapse
|
4
|
Steiner I, Flores-Tellez TDNJ, Mevel R, Ali A, Wang P, Schofield P, Behan C, Forsythe N, Ashton G, Taylor C, Mills IG, Oliveira P, McDade SS, Zaiss DM, Choudhury A, Lacaud G, Baena E. Autocrine activation of MAPK signaling mediates intrinsic tolerance to androgen deprivation in LY6D prostate cancer cells. Cell Rep 2023; 42:112377. [PMID: 37060563 DOI: 10.1016/j.celrep.2023.112377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/12/2022] [Accepted: 03/23/2023] [Indexed: 04/16/2023] Open
Abstract
The emergence of castration-resistant prostate cancer remains an area of unmet clinical need. We recently identified a subpopulation of normal prostate progenitor cells, characterized by an intrinsic resistance to androgen deprivation and expression of LY6D. We here demonstrate that conditional deletion of PTEN in the murine prostate epithelium causes an expansion of transformed LY6D+ progenitor cells without impairing stem cell properties. Transcriptomic analyses of LY6D+ luminal cells identified an autocrine positive feedback loop, based on the secretion of amphiregulin (AREG)-mediated activation of mitogen-activated protein kinase (MAPK) signaling, increasing cellular fitness and organoid formation. Pharmacological interference with this pathway overcomes the castration-resistant properties of LY6D+ cells with a suppression of organoid formation and loss of LY6D+ cells in vivo. Notably, LY6D+ tumor cells are enriched in high-grade and androgen-resistant prostate cancer, providing clinical evidence for their contribution to advanced disease. Our data indicate that early interference with MAPK inhibitors can prevent progression of castration-resistant prostate cancer.
Collapse
Affiliation(s)
- Ivana Steiner
- Prostate Oncobiology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Teresita Del N J Flores-Tellez
- Prostate Oncobiology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Renaud Mevel
- Stem Cell Biology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Amin Ali
- Prostate Oncobiology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK; Belfast-Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Pengbo Wang
- Prostate Oncobiology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Pieta Schofield
- Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Caron Behan
- Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Nicholas Forsythe
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, BT9 7BL Northern Ireland, UK; Belfast-Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Garry Ashton
- Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Catherine Taylor
- The Christie NHS Foundation Trust, Manchester Academic Health Sciences Centre, M20 4BX Manchester, UK
| | - Ian G Mills
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, BT9 7BL Northern Ireland, UK; Belfast-Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK; Nuffield Department of Surgical Sciences, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK; Department of Clinical Sciences and Centre for Cancer Biomarkers, University of Bergen, 7804 Bergen, Norway
| | - Pedro Oliveira
- Department of Pathology, The Christie NHS Foundation Trust, M20 4BX Manchester, UK
| | - Simon S McDade
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, BT9 7BL Northern Ireland, UK; Belfast-Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Dietmar M Zaiss
- Department of Immune Medicine, University Regensburg, Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, and Leibniz Institute for Immunotherapy (LIT), 93053 Regensburg, Germany
| | - Ananya Choudhury
- The Christie NHS Foundation Trust, Manchester Academic Health Sciences Centre, M20 4BX Manchester, UK; The University of Manchester, Manchester Cancer Research Centre, M20 4BX Manchester, UK; Belfast-Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Georges Lacaud
- Stem Cell Biology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK
| | - Esther Baena
- Prostate Oncobiology Group, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK; Belfast-Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park, SK10 4TG Macclesfield, UK.
| |
Collapse
|
5
|
Lophatananon A, Byrne MHV, Barrett T, Warren A, Muir K, Dokubo I, Georgiades F, Sheba M, Bibby L, Gnanapragasam VJ. Assessing the impact of MRI based diagnostics on pre-treatment disease classification and prognostic model performance in men diagnosed with new prostate cancer from an unscreened population. BMC Cancer 2022; 22:878. [PMID: 35953766 PMCID: PMC9367076 DOI: 10.1186/s12885-022-09955-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 07/31/2022] [Indexed: 11/30/2022] Open
Abstract
Introduction Pre-treatment risk and prognostic groups are the cornerstone for deciding management in non-metastatic prostate cancer. All however, were developed in the pre-MRI era. Here we compared categorisation of cancers using either only clinical parameters or with MRI enhanced information in men referred for suspected prostate cancer from an unscreened population. Patient and methods Data from men referred from primary care to our diagnostic service and with both clinical (digital rectal examination [DRE] and systematic biopsies) and MRI enhanced attributes (MRI stage and combined systematic/targeted biopsies) were used for this study. Clinical vs MRI data were contrasted for clinico-pathological and risk group re-distribution using the European Association of Urology (EAU), American Urological Association (AUA) and UK National Institute for Health Care Excellence (NICE) Cambridge Prognostic Group (CPG) models. Differences were retrofitted to a population cohort with long-term prostate cancer mortality (PCM) outcomes to simulate impact on model performance. We further contrasted individualised overall survival (OS) predictions using the Predict Prostate algorithm. Results Data from 370 men were included (median age 66y). Pre-biopsy MRI stage reassignments occurred in 7.8% (versus DRE). Image-guided biopsies increased Grade Group 2 and ≥ Grade Group 3 assignments in 2.7% and 2.9% respectively. The main change in risk groups was more high-risk cancers (6.2% increase in the EAU and AUA system, 4.3% increase in CPG4 and 1.9% CPG5). When extrapolated to a historical population-based cohort (n = 10,139) the redistribution resulted in generally lower concordance indices for PCM. The 5-tier NICE-CPG system outperformed the 4-tier AUA and 3-tier EAU models (C Index 0.70 versus 0.65 and 0.64). Using an individualised prognostic model, changes in predicted OS were small (median difference 1% and 2% at 10- and 15-years’ respectively). Similarly, estimated treatment survival benefit changes were minimal (1% at both 10- and 15-years’ time frame). Conclusion MRI guided diagnostics does change pre-treatment risk groups assignments but the overall prognostic impact appears modest in men referred from unscreened populations. Particularly, when using more granular tiers or individualised prognostic models. Existing risk and prognostic models can continue to be used to counsel men about treatment option until long term survival outcomes are available.
Supplementary Information The online version contains supplementary material available at 10.1186/s12885-022-09955-w.
Collapse
Affiliation(s)
- Artitaya Lophatananon
- Division of Population Health, Health Services Research & Primary Care Centre, University of Manchester, Manchester, UK
| | - Matthew H V Byrne
- Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Tristan Barrett
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Anne Warren
- Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Kenneth Muir
- Division of Population Health, Health Services Research & Primary Care Centre, University of Manchester, Manchester, UK
| | - Ibifuro Dokubo
- Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Fanos Georgiades
- Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.,Division of Urology, Department of Surgery, University of Cambridge, Cambridge, UK
| | - Mostafa Sheba
- Kasr Al Any School of Medicine, Cairo University, Giza, Egypt
| | - Lisa Bibby
- Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Vincent J Gnanapragasam
- Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK. .,Division of Urology, Department of Surgery, University of Cambridge, Cambridge, UK. .,Cambridge Urology Translational Research and Clinical Trials Office, Addenbrooke's Hospital, Cambridge Biomedical Campus, Cambridge, UK.
| |
Collapse
|
6
|
Ali A, Du Feu A, Oliveira P, Choudhury A, Bristow RG, Baena E. Prostate zones and cancer: lost in transition? Nat Rev Urol 2022; 19:101-115. [PMID: 34667303 DOI: 10.1038/s41585-021-00524-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/17/2021] [Indexed: 12/16/2022]
Abstract
Localized prostate cancer shows great clinical, genetic and environmental heterogeneity; however, prostate cancer treatment is currently guided solely by clinical staging, serum PSA levels and histology. Increasingly, the roles of differential genomics, multifocality and spatial distribution in tumorigenesis are being considered to further personalize treatment. The human prostate is divided into three zones based on its histological features: the peripheral zone (PZ), the transition zone (TZ) and the central zone (CZ). Each zone has variable prostate cancer incidence, prognosis and outcomes, with TZ prostate tumours having better clinical outcomes than PZ and CZ tumours. Molecular and cell biological studies can improve understanding of the unique molecular, genomic and zonal cell type features that underlie the differences in tumour progression and aggression between the zones. The unique biology of each zonal tumour type could help to guide individualized treatment and patient risk stratification.
Collapse
Affiliation(s)
- Amin Ali
- Prostate Oncobiology Group, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK.,The Christie NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Alexander Du Feu
- Prostate Oncobiology Group, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK
| | - Pedro Oliveira
- The Christie NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK
| | - Ananya Choudhury
- The Christie NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK.,The University of Manchester, Manchester Cancer Research Centre, Manchester, UK.,Belfast-Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK
| | - Robert G Bristow
- The Christie NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK.,The University of Manchester, Manchester Cancer Research Centre, Manchester, UK.,Belfast-Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK
| | - Esther Baena
- Prostate Oncobiology Group, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK. .,Belfast-Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK.
| |
Collapse
|
7
|
Pockros B, Stensland KD, Parries M, Frankenberger E, Canes D, Moinzadeh A. Preoperative MRI PI-RADS scores are associated with prostate cancer upstaging on surgical pathology. Prostate 2022; 82:352-358. [PMID: 34878175 DOI: 10.1002/pros.24280] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Revised: 11/18/2021] [Accepted: 11/23/2021] [Indexed: 01/10/2023]
Abstract
INTRODUCTION Prostate Imaging Reporting and Data System (PI-RADS) scores can help identify clinically significant prostate cancer and improve patient selection for prostate biopsies. However, the role of PI-RADS scores in patients already diagnosed with prostate cancer remains unclear. The purpose of this study was to evaluate the association of PI-RADS scores with prostate cancer upstaging. Upstaging on final pathology harbors a higher risk for biochemical recurrence with important implications for additional treatments, morbidity, and mortality. METHODS All patients from a single high-volume institution who underwent a prostate multiparametric magnetic resonance imaging and radical prostatectomy between 2016 and 2020 were included in this retrospective analysis. Univariable and multivariable analyses were conducted to investigate potential associations with upstaging events, defined by pT3, pT4, or N1 on final pathology. A logistic regression model was constructed for the prediction of upstaging events based on PI-RADS score, prostate-specific antigen density (PSA-D), and biopsy Gleason grade groups. We built receiver operative characteristic (ROC) curves to measure the area under the curve of different predictive models. RESULTS Two hundred and ninety-four patients were included in the final analysis. Upstaging events occurred in 137 (46.5%) of patients. On univariable analysis, patients who were upstaged on final pathology had significantly higher PI-RADS scores (odds ratio [OR] 2.34 95% confidence interval [CI] 1.64-3.40, p < 0.001) but similar PSA-D (OR 2.70 95% 0.94-8.43, p = 0.188) compared with patients who remained pT1 or pT2 on final pathology. On multivariable analysis, PI-RADS remained independently significantly associated with upstaging, suggesting it is an independent risk predictor for upstaging. Lymph node metastasis only occurred in patients with PI-RADS 4 or 5 lesions (n = 15). Our model using PSA-D, biopsy Gleason grade, and PI-RADS had a predictive AUC of 0.69 for upstaging events, an improvement from 0.59 using biopsy Gleason grade alone. CONCLUSION PI-RADS scores are independent predictors for upstaging events and may play an important role in forecasting biochemical recurrence and lymph node metastasis. Modern nomograms should be updated to include PI-RADS to predict lymph node metastases and the likelihood of biochemical recurrence more accurately.
Collapse
Affiliation(s)
| | | | - Molly Parries
- Tufts University School of Medicine, Boston, Massachusetts, USA
| | - Edward Frankenberger
- Division of Urology, Lahey Hospital and Medical Center, Burlington, Massachusetts, USA
| | - David Canes
- Division of Urology, Lahey Hospital and Medical Center, Burlington, Massachusetts, USA
| | - Alireza Moinzadeh
- Division of Urology, Lahey Hospital and Medical Center, Burlington, Massachusetts, USA
| |
Collapse
|
8
|
Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization. Int J Mol Sci 2021; 22:ijms22189971. [PMID: 34576134 PMCID: PMC8465891 DOI: 10.3390/ijms22189971] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 09/06/2021] [Accepted: 09/10/2021] [Indexed: 12/24/2022] Open
Abstract
Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.
Collapse
|
9
|
Erickson A, Hayes A, Rajakumar T, Verrill C, Bryant RJ, Hamdy FC, Wedge DC, Woodcock DJ, Mills IG, Lamb AD. A Systematic Review of Prostate Cancer Heterogeneity: Understanding the Clonal Ancestry of Multifocal Disease. Eur Urol Oncol 2021; 4:358-369. [PMID: 33888445 DOI: 10.1016/j.euo.2021.02.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 01/31/2021] [Accepted: 02/26/2021] [Indexed: 11/24/2022]
Abstract
CONTEXT Studies characterising genomic changes in prostate cancer (PCa) during natural progression have greatly increased our understanding of the disease. A better understanding of the evolutionary history of PCa would allow advances in diagnostics, prognostication, and novel therapies that together will improve patient outcomes. OBJECTIVE To review the molecular heterogeneity of PCa and assess recent efforts to profile intratumoural heterogeneity and clonal evolution. EVIDENCE ACQUISITION We screened a total of 1313 abstracts from PubMed published between 2009 and 2020, of which we reviewed 84 full-text articles. We excluded 49, resulting in 35 studies for qualitative analysis. EVIDENCE SYNTHESIS In studies of primary disease (16 studies, 4793 specimens), there is a lack of consensus regarding the monoclonal or polyclonal origin of primary PCa. There is no consistent mutation giving rise to primary PCa. Detailed clonal analysis of primary PCa has been limited by current techniques. By contrast, clonal relationships between PCa metastases and a potentiating clone have been consistently identified (19 studies, 732 specimens). Metastatic specimens demonstrate consistent truncal genomic aberrations that suggest monoclonal metastatic progenitors. CONCLUSIONS The relationship between the clonal dynamics of PCa and clinical outcomes needs further investigation. It is likely that this will provide a biological rationale for whether radical treatment of the primary tumour benefits patients with oligometastatic PCa. Future studies on the mutational burden in primary disease at single-cell resolution should permit the identification of clonal patterns underpinning the origin of lethal PCa. PATIENT SUMMARY Prostate cancers arise in different parts of the prostate because of DNA mutations that occur by chance at different times. These cancer cells and their origin can be tracked by DNA mapping. In this review we summarise the state of the art and outline what further science is needed to provide the missing answers.
Collapse
Affiliation(s)
- Andrew Erickson
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Alicia Hayes
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK
| | - Timothy Rajakumar
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
| | - Clare Verrill
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Oxford National Institute for Health Research Biomedical Research Centre, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK
| | - Richard J Bryant
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK
| | - Freddie C Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK
| | - David C Wedge
- Manchester Cancer Research Centre, University of Manchester, Manchester, UK
| | - Dan J Woodcock
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Oxford Big Data Institute, University of Oxford, Oxford, UK
| | - Ian G Mills
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK
| | - Alastair D Lamb
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK; Department of Urology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Oxford NIHR Biomedical Research Centre, University of Oxford, UK.
| |
Collapse
|
10
|
Rajwa P, Pradere B, Quhal F, Mori K, Laukhtina E, Huebner NA, D'Andrea D, Krzywon A, Shim SR, Baltzer PA, Renard-Penna R, Leapman MS, Shariat SF, Ploussard G. Reliability of Serial Prostate Magnetic Resonance Imaging to Detect Prostate Cancer Progression During Active Surveillance: A Systematic Review and Meta-analysis. Eur Urol 2021; 80:549-563. [PMID: 34020828 DOI: 10.1016/j.eururo.2021.05.001] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Accepted: 05/04/2021] [Indexed: 12/20/2022]
Abstract
CONTEXT Although magnetic resonance imaging (MRI) is broadly implemented into active surveillance (AS) protocols, data on the reliability of serial MRI in order to help guide follow-up biopsy are inconclusive. OBJECTIVE To assess the diagnostic estimates of serial prostate MRI for prostate cancer (PCa) progression during AS. EVIDENCE ACQUISITION We systematically searched PubMed, Scopus, and Web of Science databases to select studies analyzing the association between changes on serial prostate MRI and PCa progression during AS. We included studies that provided data for MRI progression, which allowed us to calculate diagnostic estimates. We compared Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) accuracy with institution-specific definitions. EVIDENCE SYNTHESIS We included 15 studies with 2240 patients. Six used PRECISE criteria and nine institution-specific definitions of MRI progression. The pooled PCa progression rate, which included histological progression to Gleason grade ≥2, was 27%. The pooled sensitivity and specificity were 0.59 (95% confidence interval [CI] 0.44-0.73) and 0.75 (95% CI 0.66-0.84) respectively. There was significant heterogeneity between included studies. Depending on PCa progression prevalence, the pooled negative predictive value for serial prostate MRI ranged from 0.81 (95% CI 0.73-0.88) to 0.88 (95% CI 0.83-0.93) and the pooled positive predictive value ranged from 0.37 (95% CI 0.24-0.54) to 0.50 (95% CI 0.36-0.66). There were no significant differences in the pooled sensitivity (p = 0.37) and specificity (p = 0.74) of PRECISE and institution-specific schemes. CONCLUSIONS Serial MRI still should not be considered a sole factor for excluding PCa progression during AS, and changes on MRI are not accurate enough to indicate PCa progression. There was a nonsignificant trend toward improved diagnostic estimates of PRECISE recommendations. These findings highlight the need to further define the optimal triggers and timing of biopsy during AS, as well as the need for optimizing the quality, interpretation, and reporting of serial prostate MRI. PATIENT SUMMARY Our study suggests that serial prostate magnetic resonance imaging (MRI) alone in patients on active surveillance is not accurate enough to reliably rule out or rule in prostate cancer progression. Other clinical factors and biomarkers along with serial MRI are required to safely tailor the intensity of follow-up biopsies.
Collapse
Affiliation(s)
- Pawel Rajwa
- Department of Urology, Medical University of Vienna, Vienna, Austria; Department of Urology, Medical University of Silesia, Zabrze, Poland
| | - Benjamin Pradere
- Department of Urology, Medical University of Vienna, Vienna, Austria
| | - Fahad Quhal
- Department of Urology, Medical University of Vienna, Vienna, Austria; Department of Urology, King Fahad Specialist Hospital, Dammam, Saudi Arabia
| | - Keiichiro Mori
- Department of Urology, Medical University of Vienna, Vienna, Austria; Department of Urology, The Jikei University School of Medicine, Tokyo, Japan
| | - Ekaterina Laukhtina
- Department of Urology, Medical University of Vienna, Vienna, Austria; Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
| | - Nicolai A Huebner
- Department of Urology, Medical University of Vienna, Vienna, Austria
| | - David D'Andrea
- Department of Urology, Medical University of Vienna, Vienna, Austria
| | - Aleksandra Krzywon
- Department of Biostatistics and Bioinformatics, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland
| | - Sung Ryul Shim
- Department of Preventive Medicine, Korea University College of Medicine, Seoul, Korea
| | - Pascal A Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Raphaële Renard-Penna
- Department of Radiology, Pitié-Salpétrière Hospital, Paris-Sorbonne University, Paris, France
| | | | - Shahrokh F Shariat
- Department of Urology, Medical University of Vienna, Vienna, Austria; Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia; Department of Urology, Weill Cornell Medical College, New York, NY, USA; Department of Urology, University of Texas Southwestern, Dallas, TX, USA; Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria; Department of Urology, Second Faculty of Medicine, Charles University, Prague, Czech Republic.
| | | |
Collapse
|
11
|
Magnetic Resonance Imaging Based Radiomic Models of Prostate Cancer: A Narrative Review. Cancers (Basel) 2021; 13:cancers13030552. [PMID: 33535569 PMCID: PMC7867056 DOI: 10.3390/cancers13030552] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Revised: 01/18/2021] [Accepted: 01/27/2021] [Indexed: 12/11/2022] Open
Abstract
Simple Summary The increasing interest in implementing artificial intelligence in radiomic models has occurred alongside advancement in the tools used for computer-aided diagnosis. Such tools typically apply both statistical and machine learning methodologies to assess the various modalities used in medical image analysis. Specific to prostate cancer, the radiomics pipeline has multiple facets that are amenable to improvement. This review discusses the steps of a magnetic resonance imaging based radiomics pipeline. Present successes, existing opportunities for refinement, and the most pertinent pending steps leading to clinical validation are highlighted. Abstract The management of prostate cancer (PCa) is dependent on biomarkers of biological aggression. This includes an invasive biopsy to facilitate a histopathological assessment of the tumor’s grade. This review explores the technical processes of applying magnetic resonance imaging based radiomic models to the evaluation of PCa. By exploring how a deep radiomics approach further optimizes the prediction of a PCa’s grade group, it will be clear how this integration of artificial intelligence mitigates existing major technological challenges faced by a traditional radiomic model: image acquisition, small data sets, image processing, labeling/segmentation, informative features, predicting molecular features and incorporating predictive models. Other potential impacts of artificial intelligence on the personalized treatment of PCa will also be discussed. The role of deep radiomics analysis-a deep texture analysis, which extracts features from convolutional neural networks layers, will be highlighted. Existing clinical work and upcoming clinical trials will be reviewed, directing investigators to pertinent future directions in the field. For future progress to result in clinical translation, the field will likely require multi-institutional collaboration in producing prospectively populated and expertly labeled imaging libraries.
Collapse
|
12
|
Alanee S, Peabody J, Menon M. AUTHOR REPLY. Urology 2020; 146:188. [DOI: 10.1016/j.urology.2020.07.071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
|
13
|
Walker C, Singhal U, Tosoian JJ. EDITORIAL COMMENT. Urology 2020; 146:187-188. [PMID: 33272425 DOI: 10.1016/j.urology.2020.07.070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Colton Walker
- Department of Urology, University of Michigan, Ann Arbor, MI
| | - Udit Singhal
- Department of Urology, University of Michigan, Ann Arbor, MI
| | - Jeffrey J Tosoian
- Department of Urology, University of Michigan, Ann Arbor, MI; University of Michigan Rogel Cancer Center, Ann Arbor, MI; Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI
| |
Collapse
|
14
|
How should radiologists incorporate non-imaging prostate cancer biomarkers into daily practice? Abdom Radiol (NY) 2020; 45:4031-4039. [PMID: 32232525 DOI: 10.1007/s00261-020-02496-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
OBJECTIVE To review the current body of evidence surrounding non-imaging biomarkers in patients with known or suspected prostate cancer. RESULTS Several non-imaging biomarkers have been developed and are available that aim to improve risk estimates at several clinical junctures. For patients with suspicion of prostate cancer who are considering first-time or repeat biopsy, blood- and urine-based assays can improve the prediction of harboring clinically significant disease and may reduce unnecessary biopsy. Blood- and urine-based biomarkers have been evaluated in association with prostate MRI, offering insights that might augment decision-making in the pre and post-MRI setting. Tissue-based genomic and proteomic assays have also been developed that provide independent assessments of prostate cancer aggressiveness that can complement imaging. CONCLUSION A growing number of non-imaging biomarkers are available to assist in clinical decision-making for men with known or suspected prostate cancer. An appreciation for the intersection of imaging and biomarkers may improve clinical care and resource utilization for men with prostate cancer.
Collapse
|
15
|
Schiavina R, Droghetti M, Novara G, Bianchi L, Gaudiano C, Panebianco V, Borghesi M, Piazza P, Mineo Bianchi F, Guerra M, Corcioni B, Fiorentino M, Giunchi F, Verze P, Pultrone C, Golfieri R, Porreca A, Mirone V, Brunocilla E. The role of multiparametric MRI in active surveillance for low-risk prostate cancer: The ROMAS randomized controlled trial. Urol Oncol 2020; 39:433.e1-433.e7. [PMID: 33191117 DOI: 10.1016/j.urolonc.2020.10.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 10/19/2020] [Accepted: 10/22/2020] [Indexed: 11/30/2022]
Abstract
BACKGROUND We aim to evaluate the impact of multiparametric magnetic resonance imaging and fusion-target biopsy for early reclassification of patients with low-risk Prostate Cancer in a randomized trial. MATERIALS AND METHODS Between 2015 and 2018, patients diagnosed with Prostate Cancer after random biopsy fulfilling PRIAS criteria were enrolled and centrally randomized (1:1 ratio) to study group or control group. Patients randomized to study group underwent multiparametric magnetic resonance imaging at 3 months from enrollment: patients with positive findings (PIRADS-v2>2) underwent fusion-target biopsy; patients with negative multiparametric magnetic resonance imaging or confirmed ISUP - Grade Group 1 at fusion-target biopsy were managed according to PRIAS schedule and 12-core random biopsy was performed at 12 months. Patients in control group underwent PRIAS protocol, including a confirmatory 12-core random biopsy at 12 months. Primary endpoint was a reduction of reclassification rate at 12-month random biopsy in study group at least 20% less than controls. Reclassification was defined as biopsy ISUP Grade Group 1 in >2 biopsy cores or disease upgrading. RESULTS A total of 124 patients were randomized to study group (n = 62) or control group (n = 62). Around 21 of 62 patients (34%) in study group had a positive multiparametric magnetic resonance imaging, and underwent fusion-target biopsy, with 11 (17.7%) reclassifications. Considering the intention-to-treat population, reclassification rate at 12-month random biopsy was 6.5% for study group and 29% for control group, respectively (P < 0.001). CONCLUSIONS The early employment of multiparametric magnetic resonance imaging for active surveillance patients enrolled after random biopsy consents to significantly reduce reclassifications at 12-month random biopsy.
Collapse
Affiliation(s)
- Riccardo Schiavina
- Department of Urology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Matteo Droghetti
- Department of Urology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy.
| | - Giacomo Novara
- Department of Surgery, Oncology, and Gastroenterology - Urology Clinic University of Padua, Padua, Italy
| | - Lorenzo Bianchi
- Department of Urology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Caterina Gaudiano
- Department of Radiology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | | | - Marco Borghesi
- Department of Urology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Pietro Piazza
- Department of Urology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Federico Mineo Bianchi
- Department of Urology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Marco Guerra
- Department of Urology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Beniamino Corcioni
- Department of Radiology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Michelangelo Fiorentino
- Department of Pathology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Francesca Giunchi
- Department of Pathology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Paolo Verze
- Department of Medicine, Surgery, Dentistry "Scuola Medica Salernitana", University of Salerno, Salerno, Italy
| | - Cristian Pultrone
- Department of Urology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Rita Golfieri
- Department of Radiology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| | - Angelo Porreca
- Department of Urology, Policlinico Abano Terme, Abano Terme, Italy
| | - Vincenzo Mirone
- Department of Urology, University of Naples, Federico II, Naples, Italy
| | - Eugenio Brunocilla
- Department of Urology, S.Orsola-Malpighi University Hospital, University of Bologna, Bologna, Italy
| |
Collapse
|
16
|
Fiard G, Norris JM, Nguyen TA, Stavrinides V, Olivier J, Emberton M, Moore CM. What to expect from a non-suspicious prostate MRI? A review. Prog Urol 2020; 30:986-999. [PMID: 33008718 DOI: 10.1016/j.purol.2020.09.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 07/06/2020] [Accepted: 09/04/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Many guidelines now recommend multiparametric MRI (mpMRI) prior to an initial or repeat prostate biopsy. However, clinical decision making for men with a non-suspicious mpMRI (Likert or PIRADS score 1-2) varies. OBJECTIVES To review the most recent literature to answer three questions. (1) Should we consider systematic biopsy if mpMRI is not suspicious? (2) Are there additional predictive factors that can help decide which patient should have a biopsy? (3) Can the low visibility of some cancers be explained and what are the implications? SOURCES A narrative review was performed in Medline databases using two searches with the terms "MRI" and "prostate cancer" and ("diagnosis" or "biopsy") and ("non-suspicious" or "negative" or "invisible"); "prostate cancer MRI visible". References of the selected articles were screened for additional articles. STUDY SELECTION Studies published in the last 5 years in English language were assessed for eligibility and selected if data was available to answer one of the three study questions. RESULTS Considering clinically significant cancer as ISUP grade≥2, the negative predictive value (NPV) of mpMRI in various settings and populations ranges from 76% to 99%, depending on cancer prevalence and the type of confirmatory reference test used. NPV is higher among patients with prior negative biopsy (88-96%), and lower for active surveillance patients (85-90%). The PSA density (PSAd) with a threshold of PSAd<0.15ng/ml/ml was the most studied and relevant predictive factor used in combination with mpMRI to rule out clinically significant cancer. Finally, mpMRI-invisible tumours appear to differ from a histopathological and genetic point of view, conferring clinical advantage to invisibility. LIMITATIONS Most published data come from expert centres and results may not be reproducible in all settings. CONCLUSION mpMRI has high diagnostic accuracy and in cases of negative mpMRI, PSA density can be used to determine which patient should have a biopsy. Growing knowledge of the mechanisms and genetics underlying MRI visibility will help develop more accurate risk calculators and biomarkers.
Collapse
Affiliation(s)
- G Fiard
- UCL Division of Surgery and Interventional Science, University College London, London, UK; Department of Urology, University College London Hospital NHS Foundation Trust, London, UK; Department of Urology, Grenoble Alpes University Hospital, Grenoble, France; Université Grenoble Alpes, CNRS, Grenoble INP, TIMC-IMAG, Grenoble, France.
| | - J M Norris
- UCL Division of Surgery and Interventional Science, University College London, London, UK; Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | - T A Nguyen
- Department of urology, université de Brest, CHRU, Brest, France
| | - V Stavrinides
- UCL Division of Surgery and Interventional Science, University College London, London, UK; Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | - J Olivier
- UCL Division of Surgery and Interventional Science, University College London, London, UK; Department of urology, Lille university, CHU Lille, Lille, France
| | - M Emberton
- UCL Division of Surgery and Interventional Science, University College London, London, UK; Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | - C M Moore
- UCL Division of Surgery and Interventional Science, University College London, London, UK; Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| |
Collapse
|
17
|
Norris JM, Simpson BS, Freeman A, Kirkham A, Whitaker HC, Emberton M. Conspicuity of prostate cancer on multiparametric magnetic resonance imaging: A cross-disciplinary translational hypothesis. FASEB J 2020; 34:14150-14159. [PMID: 32920937 PMCID: PMC8436756 DOI: 10.1096/fj.202001466r] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 08/03/2020] [Accepted: 08/24/2020] [Indexed: 11/11/2022]
Abstract
Pre-biopsy multiparametric magnetic resonance imaging (mpMRI) has transformed the risk stratification and diagnostic approach for suspected prostate cancer. The majority of clinically significant prostate cancers are visible on pre-biopsy mpMRI, however, there are a subset of significant tumors that are not detected by mpMRI. The radiobiological mechanisms underpinning mpMRI-visibility and invisibility of these cancers remain uncertain. Emerging evidence suggests that mpMRI-visible tumors are enriched with molecular features associated with increased disease aggressivity and poor clinical prognosis, which is supported by short-term endpoints, such as biochemical recurrence following surgery. Furthermore, at the histopathological level, mpMRI-visible tumors appear to exhibit increased architectural and vascular density compared to mpMRI-invisible disease. It seems probable that the genomic, pathological, radiological, and clinical features of mpMRI-visible and mpMRI-invisible prostate cancers are interrelated. Here, we propose a novel cross-disciplinary theory that links genomic and molecular evidence with cellular and histopathological appearances, elucidating both the mpMRI visibility and clinical status of significant prostate cancer.
Collapse
Affiliation(s)
- Joseph M Norris
- UCL Division of Surgery & Interventional Science, University College London, London, UK.,Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Benjamin S Simpson
- UCL Division of Surgery & Interventional Science, University College London, London, UK
| | - Alex Freeman
- Department of Pathology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Alex Kirkham
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Hayley C Whitaker
- UCL Division of Surgery & Interventional Science, University College London, London, UK
| | - Mark Emberton
- UCL Division of Surgery & Interventional Science, University College London, London, UK.,Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
| |
Collapse
|
18
|
Murphy RG, Roddy AC, Srivastava S, Baena E, Waugh D, M. O’Sullivan J, McArt DG, Jain S, LaBonte M. Prostate cancer heterogeneity assessment with multi-regional sampling and alignment-free methods. NAR Genom Bioinform 2020; 2:lqaa062. [PMID: 32856020 PMCID: PMC7440682 DOI: 10.1093/nargab/lqaa062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 07/16/2020] [Accepted: 08/05/2020] [Indexed: 11/14/2022] Open
Abstract
Combining alignment-free methods for phylogenetic analysis with multi-regional sampling using next-generation sequencing can provide an assessment of intra-patient tumour heterogeneity. From multi-regional sampling divergent branching, we validated two different lesions within a patient's prostate. Where multi-regional sampling has not been used, a single sample from one of these areas could misguide as to which drugs or therapies would best benefit this patient, due to the fact these tumours appear to be genetically different. This application has the power to render, in a fraction of the time used by other approaches, intra-patient heterogeneity and decipher aberrant biomarkers. Another alignment-free method for calling single-nucleotide variants from raw next-generation sequencing samples has determined possible variants and genomic locations that may be able to characterize the differences between the two main branching patterns. Alignment-free approaches have been applied to relevant clinical multi-regional samples and may be considered as a valuable option for comparing and determining heterogeneity to help deliver personalized medicine through more robust efforts in identifying targetable pathways and therapeutic strategies. Our study highlights the application these tools could have on patient-aligned treatment indications.
Collapse
Affiliation(s)
- Ross G Murphy
- Movember FASTMAN Centre of Excellence, Patrick G Johnston Centre for Cancer Research, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast BT9 7AE, UK
| | - Aideen C Roddy
- Movember FASTMAN Centre of Excellence, Patrick G Johnston Centre for Cancer Research, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast BT9 7AE, UK
| | - Shambhavi Srivastava
- Movember FASTMAN Centre of Excellence, Patrick G Johnston Centre for Cancer Research, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast BT9 7AE, UK
- Molecular Oncology, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, UK
- Belfast–Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, UK
| | - Esther Baena
- Belfast–Manchester Movember Centre of Excellence, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, UK
- Prostate Oncobiology, Cancer Research UK Manchester Institute, The University of Manchester, Alderley Park SK10 4TG, UK
| | - David J Waugh
- Movember FASTMAN Centre of Excellence, Patrick G Johnston Centre for Cancer Research, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast BT9 7AE, UK
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, QLD 4000, Australia
| | - Joe M. O’Sullivan
- Movember FASTMAN Centre of Excellence, Patrick G Johnston Centre for Cancer Research, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast BT9 7AE, UK
- Northern Ireland Cancer Centre, Belfast Health & Social Care Trust, Belfast BT9 7JL, UK
| | - Darragh G McArt
- Movember FASTMAN Centre of Excellence, Patrick G Johnston Centre for Cancer Research, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast BT9 7AE, UK
| | - Suneil Jain
- Movember FASTMAN Centre of Excellence, Patrick G Johnston Centre for Cancer Research, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast BT9 7AE, UK
- Northern Ireland Cancer Centre, Belfast Health & Social Care Trust, Belfast BT9 7JL, UK
| | - Melissa J LaBonte
- Movember FASTMAN Centre of Excellence, Patrick G Johnston Centre for Cancer Research, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast BT9 7AE, UK
| |
Collapse
|
19
|
Norris JM, Simpson BS, Parry MA, Allen C, Ball R, Freeman A, Kelly D, Kim HL, Kirkham A, You S, Kasivisvanathan V, Whitaker HC, Emberton M. Genetic Landscape of Prostate Cancer Conspicuity on Multiparametric Magnetic Resonance Imaging: A Systematic Review and Bioinformatic Analysis. EUR UROL SUPPL 2020; 20:37-47. [PMID: 33000006 PMCID: PMC7497895 DOI: 10.1016/j.euros.2020.06.006] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Context Multiparametric magnetic resonance imaging (mpMRI) detects most, but not all, clinically significant prostate cancer. The genetic basis of prostate cancer visibility and invisibility on mpMRI remains uncertain. Objective To systematically review the literature on differential gene expression between mpMRI-visible and mpMRI-invisible prostate cancer, and to use bioinformatic analysis to identify enriched processes or cellular components in genes validated in more than one study. Evidence acquisition We performed a systematic literature search of the Medline, EMBASE, PubMed, and Cochrane databases up to January 2020 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. The primary endpoint was differential genetic features between mpMRI-visible and mpMRI-invisible tumours. Secondary endpoints were explanatory links between gene function and mpMRI conspicuity, and the prognostic value of differential gene enrichment. Evidence synthesis We retrieved 445 articles, of which 32 met the criteria for inclusion. Thematic synthesis from the included studies showed that mpMRI-visible cancer tended towards enrichment of molecular features associated with increased disease aggressivity, including phosphatase and tensin homologue (PTEN) loss and higher genomic classifier scores, such as Oncotype and Decipher. Three of the included studies had accompanying publicly available data suitable for further bioinformatic analysis. An over-representation analysis of these datasets revealed increased expression of genes associated with extracellular matrix components in mpMRI-visible tumours. Conclusions Prostate cancer that is visible on mpMRI is generally enriched with molecular features of tumour development and aggressivity, including activation of proliferative signalling, DNA damage, and inflammatory processes. Additionally, there appears to be concordant cellular components and biological processes associated with mpMRI conspicuity, as highlighted by bioinformatic analysis of large genetic datasets. Patient summary Prostate cancer that is detected by magnetic resonance imaging (MRI) tends to have genetic features that are associated with more aggressive disease. This suggests that MRI can be used to assess the likelihood of aggressive prostate cancer, based on tumour visibility.
Collapse
Affiliation(s)
- Joseph M Norris
- UCL Division of Surgery & Interventional Science, University College London, London, UK.,London Deanery of Urology, London, UK.,Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Benjamin S Simpson
- UCL Division of Surgery & Interventional Science, University College London, London, UK
| | - Marina A Parry
- UCL Cancer Institute, University College London, London, UK
| | - Clare Allen
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Rhys Ball
- Department of Pathology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Alex Freeman
- Department of Pathology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Daniel Kelly
- School of Healthcare Sciences, Cardiff University, Wales, UK
| | - Hyung L Kim
- Department of Urology, Cedars-Sinai Medical Center, West Hollywood, CA, USA
| | - Alex Kirkham
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Sungyong You
- Department of Urology, Cedars-Sinai Medical Center, West Hollywood, CA, USA.,Department of Biomedical Sciences, Cedars-Sinai Medical Center, West Hollywood, CA, USA
| | - Veeru Kasivisvanathan
- UCL Division of Surgery & Interventional Science, University College London, London, UK.,Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Hayley C Whitaker
- UCL Division of Surgery & Interventional Science, University College London, London, UK
| | - Mark Emberton
- UCL Division of Surgery & Interventional Science, University College London, London, UK.,Department of Urology, University College London Hospitals NHS Foundation Trust, London, UK
| |
Collapse
|
20
|
Norris JM, Simpson BS, Parry MA, Kasivisvanathan V, Allen C, Ball R, Freeman A, Kelly D, Kirkham A, Whitaker HC, Emberton M. Genetic correlates of prostate cancer visibility (and invisibility) on multiparametric magnetic resonance imaging: it's time to take stock. BJU Int 2020; 125:340-342. [PMID: 31600865 DOI: 10.1111/bju.14919] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Joseph M Norris
- Unviersity College London (UCL) Division of Surgery and Interventional Science, UCL, London, UK
- London Deanery of Urology, London, UK
- Department of Urology, University College London Hospitals NHS Foundation Trust (UCLH), London, UK
| | - Benjamin S Simpson
- Unviersity College London (UCL) Division of Surgery and Interventional Science, UCL, London, UK
| | | | - Veeru Kasivisvanathan
- Unviersity College London (UCL) Division of Surgery and Interventional Science, UCL, London, UK
- London Deanery of Urology, London, UK
- Department of Urology, University College London Hospitals NHS Foundation Trust (UCLH), London, UK
- Department of Urology, Frimley Health NHS Foundation Trust, London, UK
| | | | - Rhys Ball
- Department of Pathology, UCLH, London, UK
| | | | - Daniel Kelly
- School of Healthcare Sciences, Cardiff University, Wales, UK
| | | | - Hayley C Whitaker
- Unviersity College London (UCL) Division of Surgery and Interventional Science, UCL, London, UK
| | - Mark Emberton
- Unviersity College London (UCL) Division of Surgery and Interventional Science, UCL, London, UK
- London Deanery of Urology, London, UK
| |
Collapse
|
21
|
Noh TI, Tae JH, Kim HK, Shim JS, Kang SG, Sung DJ, Cheon J, Lee JG, Kang SH. Diagnostic Accuracy and Value of Magnetic Resonance Imaging-Ultrasound Fusion Transperineal Targeted and Template Systematic Prostate Biopsy Based on Bi-parametric Magnetic Resonance Imaging. Cancer Res Treat 2020; 52:714-721. [PMID: 32054151 PMCID: PMC7373864 DOI: 10.4143/crt.2019.716] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 02/05/2020] [Indexed: 01/08/2023] Open
Abstract
Purpose The purpose of this study was to investigate the diagnostic value of magnetic resonance imaging (MRI)–ultrasound (US) fusion transperineal targeted biopsy (FTB) and fusion template systematic biopsy (FSB) for prostate cancer (PCa) and clinically significant prostate cancer (csPCa) (intermediate/high grade [Gleason score ≥ 3+4]) based on bi-parametric MRI (bpMRI). Materials and methods Retrospectively, we analyzed 300 patients with elevated prostate-specific antigen (≥ 4.0 ng/mL) and/or abnormal findings in a digital rectal examination at the Korea University Hospital. All 300 men underwent bpMRI-US fusion transperineal FTB and FSB in the period from April 2017 to March 2019. Results PCas were detected in 158 of 300 men (52.7%), and the prevalence of csPCa was 34.0%. CsPCas were detected in 12 of 102 (11.8%) with Prostate Imaging-Reporting and Data System (PI-RADS) 3, 42 of 92 (45.7%) with PI-RADS 4, respectively; and 45 of 62 (72.6%) men with PI-RADS 5, respectively. BpMRI showed a sensitivity of 95.1% and negative predictive value of 89.6% for csPCa. FTB detected additional csPCa in 33 men (12.9%) compared to FSB. Compared to FTB, FSB detected additional csPCa in 10 men (3.9%). Conclusion BpMRI-US FTB and FSB improved detection of PCa and csPCa. The accuracy of bi-parametric MRI is comparable with that of multi-parametric MRI. Further, it is rapid, simpler, cheaper, and no side effects of contrast media. Therefore, it is expected that bpMRI-US transperineal FTB and FSB could be a good alternative to conventional US-guided transrectal biopsy, which is the current gold standard.
Collapse
Affiliation(s)
- Tae Il Noh
- Department of Urology, Korea University School of Medicine, Seoul, Korea
| | - Jong Hyun Tae
- Department of Urology, Korea University School of Medicine, Seoul, Korea
| | - Hyung Keun Kim
- Department of Urology, Korea University School of Medicine, Seoul, Korea
| | - Ji Sung Shim
- Department of Urology, Korea University School of Medicine, Seoul, Korea
| | - Sung Gu Kang
- Department of Urology, Korea University School of Medicine, Seoul, Korea
| | - Deuk Jae Sung
- Department of Urology, Korea University School of Medicine, Seoul, Korea.,Department of Radiology, Korea University School of Medicine, Seoul, Korea
| | - Jun Cheon
- Department of Urology, Korea University School of Medicine, Seoul, Korea
| | - Jeong Gu Lee
- Department of Urology, Korea University School of Medicine, Seoul, Korea
| | - Seok Ho Kang
- Department of Urology, Korea University School of Medicine, Seoul, Korea
| |
Collapse
|
22
|
Norris JM, Simpson BS, Parry MA, Allen C, Ball R, Freeman A, Kelly D, Kirkham A, Kasivisvanathan V, Whitaker HC, Emberton M. Genetic landscape of prostate cancer conspicuity on multiparametric MRI: a protocol for a systematic review and bioinformatic analysis. BMJ Open 2020; 10:e034611. [PMID: 31992607 PMCID: PMC7045175 DOI: 10.1136/bmjopen-2019-034611] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 12/30/2019] [Accepted: 01/09/2020] [Indexed: 12/31/2022] Open
Abstract
INTRODUCTION The introduction of multiparametric MRI (mpMRI) has enabled enhanced risk stratification for men at risk of prostate cancer, through accurate prebiopsy identification of clinically significant disease. However, approximately 10%-20% of significant prostate cancer may be missed on mpMRI. It appears that the genomic basis of lesion visibility or invisibility on mpMRI may have key implications for prognosis and treatment. Here, we describe a protocol for the first systematic review and novel bioinformatic analysis of the genomic basis of prostate cancer conspicuity on mpMRI. METHODS AND ANALYSIS A systematic search of MEDLINE, PubMed, EMBASE and Cochrane databases will be conducted. Screening, data extraction, statistical analysis and reporting will be performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Included papers will be full text articles, written between January 1980 and December 2019, comparing molecular characteristics of mpMRI-visible lesions and mpMRI-invisible lesions at the DNA, DNA-methylation, RNA or protein level. Study bias and quality will be assessed using a modified Newcastle-Ottawa score. Additionally, we will conduct a novel bioinformatic analysis of supplementary material and publicly available data, to combine transcriptomic data and reveal common pathways highlighted across studies. To ensure methodological rigour, this protocol is written in accordance with the PRISMA Protocol 2015 checklist. ETHICS AND DISSEMINATION Ethical approval will not be required, as this is an academic review of published literature. Findings will be disseminated through publications in peer-reviewed journals, and presentations at national and international conferences. PROSPERO REGISTRATION NUMBER CRD42019147423.
Collapse
Affiliation(s)
- Joseph M Norris
- UCL Division of Surgery & Interventional Science, University College London, London, UK
| | - Benjamin S Simpson
- UCL Division of Surgery & Interventional Science, University College London, London, UK
| | - Marina A Parry
- UCL Cancer Institute, University College London, London, UK
| | - Clare Allen
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Rhys Ball
- Department of Pathology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Alex Freeman
- Department of Pathology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Daniel Kelly
- School of Healthcare Sciences, Cardiff University, Cardiff, South Glamorgan, UK
| | - Alex Kirkham
- Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Veeru Kasivisvanathan
- UCL Division of Surgery & Interventional Science, University College London, London, UK
| | - Hayley C Whitaker
- UCL Division of Surgery & Interventional Science, University College London, London, UK
| | - Mark Emberton
- UCL Division of Surgery & Interventional Science, University College London, London, UK
| |
Collapse
|
23
|
|
24
|
Salami SS, Kaplan JB, Nallandhighal S, Takhar M, Tosoian JJ, Lee M, Yoon J, Hovelson DH, Plouffe KR, Kaffenberger SD, Schaeffer EM, Karnes RJ, Lotan TL, Morgan TM, George AK, Montgomery JS, Davenport MS, You S, Tomlins SA, Curci NE, Kim HL, Spratt DE, Udager AM, Palapattu GS. Biologic Significance of Magnetic Resonance Imaging Invisibility in Localized Prostate Cancer. JCO Precis Oncol 2019; 3:1900054. [PMID: 32914029 DOI: 10.1200/po.19.00054] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/22/2019] [Indexed: 11/20/2022] Open
Abstract
PURPOSE Multiparametric magnetic resonance imaging (mpMRI) is used widely for prostate cancer (PCa) evaluation. Approximately 35% of aggressive tumors, however, are not visible on mpMRI. We sought to identify the molecular alterations associated with mpMRI-invisible tumors and determine whether mpMRI visibility is associated with PCa prognosis. METHODS Discovery and validation cohorts included patients who underwent mpMRI before radical prostatectomy and were found to harbor both mpMRI-visible (Prostate Imaging and Reporting Data System 3 to 5) and -invisible (Prostate Imaging and Reporting Data System 1 or 2) foci on surgical pathology. Next-generation sequencing was performed to determine differential gene expression between mpMRI-visible and -invisible foci. A genetic signature for tumor mpMRI visibility was derived in the discovery cohort and assessed in an independent validation cohort. Its association with long-term oncologic outcomes was evaluated in a separate testing cohort. RESULTS The discovery cohort included 10 patients with 26 distinct PCa foci on surgical pathology, of which 12 (46%) were visible and 14 (54%) were invisible on preoperative mpMRI. Next-generation sequencing detected prioritized genetic mutations in 14 (54%) tumor foci (n = 8 mpMRI visible, n = 6 mpMRI invisible). A nine-gene signature (composed largely of cell organization/structure genes) associated with mpMRI visibility was derived (area under the curve = 0.89), and the signature predicted MRI visibility with 75% sensitivity and 100% specificity (area under the curve = 0.88) in the validation cohort. In the testing cohort (n = 375, median follow-up 8 years) there was no significant difference in biochemical recurrence, distant metastasis, or cancer-specific mortality in patients with predicted mpMRI-visible versus -invisible tumors (all P > .05). CONCLUSION Compared with mpMRI-invisible disease, mpMRI-visible tumors are associated with underexpression of cellular organization genes. mpMRI visibility does not seem to be predictive of long-term cancer outcomes, highlighting the need for biopsy strategies that detect mpMRI-invisible tumors.
Collapse
Affiliation(s)
- Simpa S Salami
- Michigan Medicine, Ann Arbor, MI.,University of Michigan Rogel Cancer Center, Ann Arbor, MI
| | | | | | | | | | | | - Junhee Yoon
- Cedars-Sinai Medical Center, Los Angeles, CA
| | | | | | - Samuel D Kaffenberger
- Michigan Medicine, Ann Arbor, MI.,University of Michigan Rogel Cancer Center, Ann Arbor, MI
| | | | | | | | - Todd M Morgan
- Michigan Medicine, Ann Arbor, MI.,University of Michigan Rogel Cancer Center, Ann Arbor, MI
| | - Arvin K George
- Michigan Medicine, Ann Arbor, MI.,University of Michigan Rogel Cancer Center, Ann Arbor, MI
| | - Jeffrey S Montgomery
- Michigan Medicine, Ann Arbor, MI.,University of Michigan Rogel Cancer Center, Ann Arbor, MI
| | | | | | - Scott A Tomlins
- Michigan Medicine, Ann Arbor, MI.,University of Michigan Rogel Cancer Center, Ann Arbor, MI
| | | | - Hyung L Kim
- Cedars-Sinai Medical Center, Los Angeles, CA
| | - Daniel E Spratt
- University of Michigan Rogel Cancer Center, Ann Arbor, MI.,Michigan Medicine, Ann Arbor, MI
| | - Aaron M Udager
- Michigan Medicine, Ann Arbor, MI.,University of Michigan Rogel Cancer Center, Ann Arbor, MI
| | - Ganesh S Palapattu
- Michigan Medicine, Ann Arbor, MI.,University of Michigan Rogel Cancer Center, Ann Arbor, MI.,Medical University of Vienna, Vienna, Austria
| |
Collapse
|