Literature DB >> 28753844

Transcriptome Wide Analysis of Magnetic Resonance Imaging-targeted Biopsy and Matching Surgical Specimens from High-risk Prostate Cancer Patients Treated with Radical Prostatectomy: The Target Must Be Hit.

Jan Philipp Radtke1, Mandeep Takhar2, David Bonekamp3, Claudia Kesch4, Nicholas Erho2, Marguerite du Plessis2, Christine Buerki2, Kaye Ong2, Elai Davicioni2, Markus Hohenfellner4, Boris A Hadaschik5.   

Abstract

BACKGROUND: The most suspicious lesions on multiparametric magnetic resonance imaging (MRI) may be representative of final pathology.
OBJECTIVE: We connect imaging with high-precision spatial annotation of biopsies and genomic cancer signatures to compare the genomic signals of the index lesion and biopsy cores of adjacent and far away locations. DESIGN, SETTING, AND PARTICIPANTS: Eleven patients diagnosed with high-risk prostate cancer on MRI/transrectal ultrasound-fusion biopsy (Bx) and treated with radical prostatectomy (RP). Five tissue specimens were collected from each patient. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Whole transcriptome RNA-expression was profiled for each sample. Genomic signatures were used to compare signals in MRI invisible versus visible foci using Pearson's correlation and to assess intratumoral heterogeneity using hierarchical clustering. RESULTS AND LIMITATIONS: Ten RP and 27 Bx-samples passed quality control. Gene expression between RP and index Bx, but not adjacent benign samples, was highly correlated. Genomic Gleason grade classifier features measured across the different samples showed concordant expression across Bx and RP tumor samples, while an inverse expression pattern was observed between tumor and benign samples indicating the lack of a strong field-effect. The distribution of low and high Prostate Imaging Reporting and Data System (PI-RADS) samples was 10 and 11, respectively. Genomics of all low PI-RADS samples resembled benign tissue and most high PI-RADS samples resembled cancer tissue. A strong association was observed between PI-RADS version 2 and Decipher as well as the genomic Gleason grade classifier score. Clustering analysis showed that most samples cluster tightly by patient. One patient showed unique tumor biology in index versus secondary lesion suggesting the presence of intrapatient heterogeneity and the utility in profiling multiple foci identified by MRI.
CONCLUSIONS: MRI-targeted Bx-genomics show excellent correlation with RP-genomics and confirm the information captured by PI-RADS. Sampling of the target lesion must be precise as correlation between index and benign lesions was not seen. PATIENT
SUMMARY: In this report, we tested if targeted prostate sampling using magnetic resonance imaging-fusion biopsy allows to genetically describe index tumors of prostate cancer. We found that imaging genomics correlated well with final prostatectomy provided that the target is hit precisely.
Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biopsy; Genomics; Multiparametric magnetic resonance imaging; Prostate cancer; Risk assessment

Mesh:

Year:  2017        PMID: 28753844     DOI: 10.1016/j.euf.2017.01.005

Source DB:  PubMed          Journal:  Eur Urol Focus        ISSN: 2405-4569


  9 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.  Transcriptomic heterogeneity in multifocal prostate cancer.

Authors:  Simpa S Salami; Daniel H Hovelson; Jeremy B Kaplan; Romain Mathieu; Aaron M Udager; Nicole E Curci; Matthew Lee; Komal R Plouffe; Lorena Lazo de la Vega; Martin Susani; Nathalie Rioux-Leclercq; Daniel E Spratt; Todd M Morgan; Matthew S Davenport; Arul M Chinnaiyan; Joanna Cyrta; Mark A Rubin; Shahrokh F Shariat; Scott A Tomlins; Ganesh S Palapattu
Journal:  JCI Insight       Date:  2018-11-02

3.  Heterogeneity in Genomic Risk Assessment from Tissue Based Prognostic Signatures Used in the Biopsy Setting and the Impact of Magnetic Resonance Imaging Targeted Biopsy.

Authors:  Sanoj Punnen; Radka Stoyanova; Deukwoo Kwon; Isildinha M Reis; Nachiketh Soodana-Prakash; Chad R Ritch; Bruno Nahar; Mark L Gonzalgo; Bruce Kava; Yang Liu; Himanshu Arora; Sandra M Gaston; Rosa P Castillo Acosta; Alan Dal Pra; Matthew Abramowitz; Oleksandr N Kryvenko; Elai Davicioni; Alan Pollack; Dipen J Parekh
Journal:  J Urol       Date:  2020-12-24       Impact factor: 7.450

4.  Correlation between genomic index lesions and mpMRI and 68Ga-PSMA-PET/CT imaging features in primary prostate cancer.

Authors:  Claudia Kesch; Jan-Philipp Radtke; Axel Wintsche; Manuel Wiesenfarth; Mariska Luttje; Claudia Gasch; Svenja Dieffenbacher; Carine Pecqueux; Dogu Teber; Gencay Hatiboglu; Joanne Nyarangi-Dix; Tobias Simpfendörfer; Gita Schönberg; Antonia Dimitrakopoulou-Strauss; Martin Freitag; Anette Duensing; Carsten Grüllich; Dirk Jäger; Michael Götz; Niels Grabe; Michal-Ruth Schweiger; Sascha Pahernik; Sven Perner; Esther Herpel; Wilfried Roth; Kathrin Wieczorek; Klaus Maier-Hein; Jürgen Debus; Uwe Haberkorn; Frederik Giesel; Jörg Galle; Boris Hadaschik; Heinz-Peter Schlemmer; Markus Hohenfellner; David Bonekamp; Holger Sültmann; Stefan Duensing
Journal:  Sci Rep       Date:  2018-11-12       Impact factor: 4.379

5.  Spatial distribution of biopsy cores and the detection of intra-lesion pathologic heterogeneity.

Authors:  Brian P Calio; Sandeep Deshmukh; Donald Mitchell; Christopher G Roth; Anne E Calvaresi; Kim Hookim; Peter McCue; Edouard J Trabulsi; Costas D Lallas
Journal:  Ther Adv Urol       Date:  2019-04-28

6.  Genomic Evaluation of Multiparametric Magnetic Resonance Imaging-visible and -nonvisible Lesions in Clinically Localised Prostate Cancer.

Authors:  Marina A Parry; Shambhavi Srivastava; Adnan Ali; Alessio Cannistraci; Jenny Antonello; João Diogo Barros-Silva; Valentina Ubertini; Vijay Ramani; Maurice Lau; Jonathan Shanks; Daisuke Nonaka; Pedro Oliveira; Thomas Hambrock; Hui Sun Leong; Nathalie Dhomen; Crispin Miller; Ged Brady; Caroline Dive; Noel W Clarke; Richard Marais; Esther Baena
Journal:  Eur Urol Oncol       Date:  2018-09-05

Review 7.  Radiogenomics influence on the future of prostate cancer risk stratification.

Authors:  Vinayak Banerjee; Shu Wang; Max Drescher; Ryan Russell; M Minhaj Siddiqui
Journal:  Ther Adv Urol       Date:  2022-09-19

Review 8.  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

Review 9.  Entering an era of radiogenomics in prostate cancer risk stratification.

Authors:  Nachiketh Soodana-Prakash; Radka Stoyanova; Abhishek Bhat; Maria C Velasquez; Omer E Kineish; Alan Pollack; Dipen J Parekh; Sanoj Punnen
Journal:  Transl Androl Urol       Date:  2018-09
  9 in total

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