Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis
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Robin W. Jansen1, Paul van Amstel1, Roland M. Martens1, Irsan E. Kooi2, Pieter Wesseling3,4, Adrianus J. de Langen5, Catharina W. Menke-Van der Houven van Oordt6, Bernard H.E. Jansen1, Annette C. Moll7, Josephine C. Dorsman2, Jonas A. Castelijns1, Pim de Graaf1 and Marcus C. de Jong1
1Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
2Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands
3Department of Pathology, VU University Medical Center, Amsterdam, The Netherlands
4Department of Pathology, Princess Máxima Center for Pediatric Oncology and University Medical Center Utrecht, Utrecht, The Netherlands
5Department of Respiratory Diseases, VU University Medical Center, Amsterdam, The Netherlands
6Department of Medical Oncology, VU University Medical Center, Amsterdam, The Netherlands
7Department of Ophthalmology, VU University Medical Center, Amsterdam, The Netherlands
Marcus C. de Jong, email: [email protected]
Keywords: radiogenomics; non-invasive; genotyping; biomarker; precision medicine
Received: August 11, 2017 Accepted: February 26, 2018 Published: April 13, 2018
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 EGFR-mutations and ALK-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.
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