Genetic landscape of prostate cancer conspicuity on multiparametric MRI: a protocol for a systematic review and bioinformatic analysis

BMJ Open. 2020 Jan 27;10(1):e034611. doi: 10.1136/bmjopen-2019-034611.

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.

Keywords: cancer genetics; magnetic resonance imaging; prostate disease; urological tumours.

Publication types

  • Systematic Review

MeSH terms

  • Computational Biology / methods*
  • Genomics
  • Humans
  • Image-Guided Biopsy
  • Male
  • Multiparametric Magnetic Resonance Imaging / methods*
  • Neoplasm Grading
  • Prostatic Neoplasms / diagnosis*
  • Prostatic Neoplasms / diagnostic imaging
  • Prostatic Neoplasms / genetics*
  • Prostatic Neoplasms / pathology
  • Research Design
  • Risk Factors
  • Tumor Burden