Literature DB >> 30563651

Multiparametric Magnetic Resonance Imaging Features Identify Aggressive Prostate Cancer at the Phenotypic and Transcriptomic Level.

Alp Tuna Beksac1, Shivaram Cumarasamy1, Ugo Falagario1, Paige Xu1, Mandeep Takhar2, Mohamed Alshalalfa2, Akriti Gupta1, Sonya Prasad1, Alberto Martini1, Hari Thulasidass1, Richa Rai1, Mark Berger3, Stefanie Hectors3, Jennifer Jordan2, Elai Davicioni2, Sujit Nair1, Kenneth Haines4, Sara Lewis3, Ardeshir Rastinehad1, Kamlesh Yadav1, Isuru Jayaratna1, Bachir Taouli3, Ashutosh Tewari5.   

Abstract

PURPOSE: Multiparametric magnetic resonance imaging is a diagnostic tool for prostate cancer with limited data on prognostic use. We sought to determine whether multiparametric magnetic resonance could predict aggressive prostate cancer features.
MATERIALS AND METHODS: We retrospectively analyzed the records of 206 patients who underwent radical prostatectomy between 2013 and 2017. All patients had available RNA expression data on the final pathology specimen obtained from a location corresponding to a lesion location on multiparametric magnetic resonance imaging. The association between the PIRADS™ (Prostate Imaging Reporting and Data System) score and adverse pathology features were analyzed. We also performed differential transcriptomic analysis between the PIRADS groups. Factors associated with adverse pathology were analyzed using a multivariable logistic regression model.
RESULTS: Lesion size (p = 0.03), PIRADS score (p = 0.02) and extraprostatic extension (p = 0.01) associated significantly with the Decipher® score. Multivariable analysis showed that the PIRADS score (referent PIRADS 3, OR 8.1, 95% CI 1.2-57.5, p = 0.04), the Gleason Grade Group (referent 3, OR 5.6, 95% CI 1.5-21.1, p = 0.01) and prostate specific antigen (OR 1.103, 95% CI 1.011-1.203) were risk factors for adverse pathology findings. The difference between PIRADS 4 and 5 did not reach significance (OR 1.9, 95% CI 0.8-4.5, p = 0.12). However, the PI3K-AKT-mTOR, WNT-β and E2F signaling pathways were more active in PIRADS 5 than in PIRADS 4 cases.
CONCLUSIONS: The PIRADS score is associated with adverse pathology results, increased metastatic risk and differential genomic pathway activation.
Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  diagnostic imaging; genomics; magnetic resonance imaging; prostatectomy; prostatic neoplasms

Mesh:

Substances:

Year:  2018        PMID: 30563651     DOI: 10.1016/j.juro.2018.06.041

Source DB:  PubMed          Journal:  J Urol        ISSN: 0022-5347            Impact factor:   7.450


  6 in total

1.  Correlation between MRI phenotypes and a genomic classifier of prostate cancer: preliminary findings.

Authors:  Andrei S Purysko; Cristina Magi-Galluzzi; Omar Y Mian; Sarah Sittenfeld; Elai Davicioni; Marguerite du Plessis; Christine Buerki; Jennifer Bullen; Lin Li; Anant Madabhushi; Andrew Stephenson; Eric A Klein
Journal:  Eur Radiol       Date:  2019-03-07       Impact factor: 5.315

2.  Correlation of Prostate-Imaging Reporting and Data Scoring System scoring on multiparametric prostate magnetic resonance imaging with histopathological factors in radical prostatectomy material in Turkish prostate cancer patients: a multicenter study of the Urooncology Association.

Authors:  Fuat Kızılay; Serdar Çelik; Sinan Sözen; Bora Özveren; Saadettin Eskiçorapçı; Mahir Özgen; Haluk Özen; Bülent Akdoğan; Güven Aslan; Fehmi Narter; Çağ Çal; Levent Türkeri
Journal:  Prostate Int       Date:  2020-02-08

3.  Does Multiparametric Magnetic Resonance of Prostate Outperform Risk Calculators in Predicting Prostate Cancer in Biopsy Naïve Patients?

Authors:  Ugo Giovanni Falagario; Giovanni Silecchia; Salvatore Mariano Bruno; Michele Di Nauta; Mario Auciello; Francesca Sanguedolce; Paola Milillo; Luca Macarini; Oscar Selvaggio; Giuseppe Carrieri; Luigi Cormio
Journal:  Front Oncol       Date:  2021-01-08       Impact factor: 6.244

4.  Unified model involving genomics, magnetic resonance imaging and prostate-specific antigen density outperforms individual co-variables at predicting biopsy upgrading in patients on active surveillance for low risk prostate cancer.

Authors:  Alp Tuna Beksac; Parita Ratnani; Zachary Dovey; Sneha Parekh; Ugo Falagario; Reza Roshandel; Stanislaw Sobotka; Deepshikha Kewlani; Avery Davis; Rachel Weil; Hafis Bashorun; Ivan Jambor; Sara Lewis; Kenneth Haines; Ashutosh K Tewari
Journal:  Cancer Rep (Hoboken)       Date:  2021-12-20

Review 5.  Radiomics in prostate cancer: an up-to-date review.

Authors:  Matteo Ferro; Ottavio de Cobelli; Gennaro Musi; Francesco Del Giudice; Giuseppe Carrieri; Gian Maria Busetto; Ugo Giovanni Falagario; Alessandro Sciarra; Martina Maggi; Felice Crocetto; Biagio Barone; Vincenzo Francesco Caputo; Michele Marchioni; Giuseppe Lucarelli; Ciro Imbimbo; Francesco Alessandro Mistretta; Stefano Luzzago; Mihai Dorin Vartolomei; Luigi Cormio; Riccardo Autorino; Octavian Sabin Tătaru
Journal:  Ther Adv Urol       Date:  2022-07-04

Review 6.  Genetic Landscape of Prostate Cancer Conspicuity on Multiparametric Magnetic Resonance Imaging: A Systematic Review and Bioinformatic Analysis.

Authors:  Joseph M Norris; Benjamin S Simpson; Marina A Parry; Clare Allen; Rhys Ball; Alex Freeman; Daniel Kelly; Hyung L Kim; Alex Kirkham; Sungyong You; Veeru Kasivisvanathan; Hayley C Whitaker; Mark Emberton
Journal:  Eur Urol Open Sci       Date:  2020-07
  6 in total

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