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DOI: 10.1055/s-0036-1581722
Radiogenomic rCBV-imaging visualizes the moleculare signature of IDH-mutant and wildtype gliomas
Zielsetzung:
The recent identification of isocitrate dehydrogenase (IDH) mutations in gliomas and several other cancers suggests that this pathway is involved in oncogenesis; however effector functions are complex and yet incompletely understood. To study the regulatory effects of IDH on hypoxia-inducible-factor 1-alpha (HIF1A), a driving force in hypoxia-initiated angiogenesis, we performed mRNA-expression and genotype/imaging phenotype correlation analysis.
Material und Methodik:
We studied differenzial mRNA expression profiles from 288 samples with low-grade diffuse and anaplastic gliomas from The Cancer Genome Atlas (TCGA) on HIF1A and related downstream signaling on a single-gene and pathway level, as well as upstream biological causes and probable downstream effects between mutant and wild-type IDH tumors. Genotype/imaging phenotype correlation analysis was performed with relative cerebral blood volume (rCBV) MRI – a robust and non-invasive estimate of tumor angiogenesis – in 73 treatment-naive patients with low-grade and anaplastic gliomas.
Ergebnisse:
We show decreased expression of HIF1A target genes on a single-gene and pathway level, strong inhibition of upstream regulators such as HIF1A and downstream biological functions such as angio- and vasculogenesis in IDH-mutant tumors. Our radiogenomic imaging approach revealed that these differenzial mRNA-expression signatures translate into distinct phenotypes, with increased levels of rCBV in IDH wild-type tumors, where a one-unit increase in rCBV corresponded to a two-third decrease in the odds for an IDH-mutation and correctly predicted IDH mutation status in 89% of patients.
Schlussfolgerungen:
Together, these findings (1) show that IDH-mutation status is associated with a distinct angiogenesis transcriptome signature which is non-invasively predictable with rCBV-imaging and (2) highlight the potential future of radiogenomics (i.e. the correlation between cancer imaging and genomic features) towards a more accurate diagnostic workup of brain tumors.