Radiogenomics reveals significant correlation between quantitative texture radiomic features of biparametric MRI and hypoxia related gene expression in men with localised prostate cancer
Ontology highlight
ABSTRACT: The aim of this study was to perform the multiscale correlation between quantitative texture features phenotype of pre-biopsy biparametric MRI (bpMRI) and targeted sequence-based RNA expression for hypoxia-related genes. Images from pre-biopsy 3T bpMRI scans in clinically localised prostate cancer (PCa) patients of various risk categories (n=15) were used to extract textural features. The genomic landscape of hypoxia-related genes expression was obtained using post-radical prostatectomy tissue for targeted RNA expression profiling using the TempO-sequence method. The nonparametric Games Howell test was used to correlate the differential expression of the three important hypoxia-related genes with 28 radiomic texture features. Following this, cBioportal was accessed and a gene-oriented query was conducted to extract Oncoprint genomic output graph of the selected hypoxia-related genes from The Cancer Genome Atlas (TCGA). Correlation analysis using Pearson's coefficients calculated against each selected gene profile; survival analysis using Kaplan-Meier estimators were carried out. We found the quantitative bpMR imaging textural features, including histogram and grey level co-occurrence matrix (GLCM), correlated with hypoxia related genes (ANGPTL4, VEGFA, and P4HA1) seen on RNA sequencing using TempO-Seq method. Further radiogenomic analysis, including data accessed on cBioportal genomic database, confirmed that overexpressed hypoxia-related genes significantly correlated with a poor survival outcome, with a median survival of 81.11: 133.00 months in those with and without alterations of genes respectively. In summary, radiomic texture features of bpMRI in localised PCa correlate with the expression of hypoxia-related genes expression in prostate cancer. The expression data analysis showed that hypoxia-related genes are associated with poor survival.
INSTRUMENT(S): Illumina HiSeq 2500
ORGANISM(S): Homo sapiens
SUBMITTER: Chidozie Ogbonnaya
PROVIDER: E-MTAB-12593 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
ACCESS DATA