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Radiogenomics Reveals Correlation between Quantitative Texture Radiomic Features of Biparametric MRI and Hypoxia-Related Gene Expression in Men with Localised Prostate Cancer.
Ogbonnaya, Chidozie N; Alsaedi, Basim S O; Alhussaini, Abeer J; Hislop, Robert; Pratt, Norman; Nabi, Ghulam.
Afiliação
  • Ogbonnaya CN; Division of Imaging Science and Technology, University of Dundee, Dundee DD1 4HN, UK.
  • Alsaedi BSO; College of Basic Medical Sciences, Abia State University, Uturu 441103, Nigeria.
  • Alhussaini AJ; Statistics Department, University of Tabuk, Tabuk 47512, Saudi Arabia.
  • Hislop R; Division of Imaging Science and Technology, University of Dundee, Dundee DD1 4HN, UK.
  • Pratt N; Department of Medical Imaging, Al-Amiri Hospital, Ministry of Health, Sulaibikhat 1300, Kuwait.
  • Nabi G; Cytogenetic, Human Genetics Unit, Ninewells Hospital and Medical School, Dundee DD1 9SY, UK.
J Clin Med ; 12(7)2023 Mar 30.
Article em En | MEDLINE | ID: mdl-37048688
ABSTRACT

OBJECTIVES:

To perform multiscale correlation analysis between quantitative texture feature phenotypes of pre-biopsy biparametric MRI (bpMRI) and targeted sequence-based RNA expression for hypoxia-related genes. MATERIALS AND

METHODS:

Images from pre-biopsy 3T bpMRI scans in clinically localised PCa patients of various risk categories (n = 15) were used to extract textural features. The genomic landscape of hypoxia-related gene 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 important hypoxia-related genes with 28 radiomic texture features. Then, cBioportal was accessed, and a gene-specific query was executed to extract the Oncoprint genomic output graph of the selected hypoxia-related genes from The Cancer Genome Atlas (TCGA). Based on each selected gene profile, correlation analysis using Pearson's coefficients and survival analysis using Kaplan-Meier estimators were performed.

RESULTS:

The quantitative bpMR imaging textural features, including the histogram and grey level co-occurrence matrix (GLCM), correlated with three hypoxia-related genes (ANGPTL4, VEGFA, and P4HA1) based on RNA sequencing using the TempO-Seq method. Further radiogenomic analysis, including data accessed from the cBioportal genomic database, confirmed that overexpressed hypoxia-related genes significantly correlated with a poor survival outcomes, with a median survival ratio of 81.11133.00 months in those with and without alterations in genes, respectively.

CONCLUSION:

This study found that there is a correlation between the radiomic texture features extracted from bpMRI in localised prostate cancer and the hypoxia-related genes that are differentially expressed. The analysis of expression data based on cBioportal revealed that these hypoxia-related genes, which were the focus of the study, are linked to an unfavourable survival outcomes in prostate cancer patients.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article