Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis

• Published in: Oncotarget Vol. 9; no. 28; pp. 20134 - 20155
• Main Authors: Jansen, Robin W, van Amstel, Paul, Martens, Roland M, Kooi, Irsan E, Wesseling, Pieter, de Langen, Adrianus J, Menke-Van der Houven van Oordt, Catharina W, Jansen, Bernard H E, Moll, Annette C, Dorsman, Josephine C, Castelijns, Jonas A, de Graaf, Pim, de Jong, Marcus C
• Format: Journal Article
• Language: English
• Published: United States Impact Journals LLC 13.04.2018
• Subjects: Review; precision medicine; radiogenomics; non-invasive; biomarker; genotyping
• ISSN: 1949-2553; 1949-2553
• DOI: 10.18632/oncotarget.24893

With targeted treatments playing an increasing role in oncology, the need arises for fast non-invasive genotyping in clinical practice. Radiogenomics is a rapidly evolving field of research aimed at identifying imaging biomarkers useful for non-invasive genotyping. Radiogenomic genotyping has the advantage that it can capture tumor heterogeneity, can be performed repeatedly for treatment monitoring, and can be performed in malignancies for which biopsy is not available. In this systematic review of 187 included articles, we compiled a database of radiogenomic associations and unraveled networks of imaging groups and gene pathways oncology-wide. Results indicated that ill-defined tumor margins and tumor heterogeneity can potentially be used as imaging biomarkers for 1p/19q codeletion in glioma, relevant for prognosis and disease profiling. In non-small cell lung cancer, FDG-PET uptake and CT-ground-glass-opacity features were associated with treatment-informing traits including -mutations and -rearrangements. Oncology-wide gene pathway analysis revealed an association between contrast enhancement (imaging) and the targetable VEGF-signalling pathway. Although the need of independent validation remains a concern, radiogenomic biomarkers showed potential for prognosis prediction and targeted treatment selection. Quantitative imaging enhanced the potential of multiparametric radiogenomic models. A wealth of data has been compiled for guiding future research towards robust non-invasive genomic profiling.