J Neurol Surg B Skull Base 2017; 78(S 01): S1-S156
DOI: 10.1055/s-0037-1600567
Oral Presentations
Georg Thieme Verlag KG Stuttgart · New York

RNA Deep Sequencing of Adamantinomatous Craniopharyngioma Reveals Molecular Divergence between Younger and Older Patients

Douglas Hardesty
1   Barrow Neurological Institute, Phoenix, Arizona, United States
,
Ashish Yeri
2   Translational Genomics Research Institute, Phoenix, Arizona, United States
,
Taylor Beecroft
2   Translational Genomics Research Institute, Phoenix, Arizona, United States
,
Beth Hermes
1   Barrow Neurological Institute, Phoenix, Arizona, United States
,
Jennifer Eschbacher
1   Barrow Neurological Institute, Phoenix, Arizona, United States
,
Kendall Jensen
2   Translational Genomics Research Institute, Phoenix, Arizona, United States
,
Peter Nakaji
1   Barrow Neurological Institute, Phoenix, Arizona, United States
› Author Affiliations
Further Information

Publication History

Publication Date:
02 March 2017 (online)

 

Introduction: Adamantinomatous craniopharyngiomas (aCP) are usually driven genetically by mutations of the β-catenin pathway. However, these tumors have heterogeneity in clinical aggressiveness and occur along a bimodal age distribution for unclear reasons. Our group recently performed the first RNA deep-sequencing of aCPs, and here we report subset analysis elucidating expression-based molecular differences across the aCP bimodal age distribution.

Methods: aCp surgical specimens from our institutional biobank were histologically confirmed by an attending neuropathologist to ensure that no papillary subtypes were included. Total RNA was extracted from each specimen and libraries generated for RNA whole-transcriptome deep-sequencing and analysis with the Illumina HiSEq. 2500 platform.

Results: Thirteen unique aCp from thirteen patients (seven under age 30, six over age 30) underwent RNA deep-sequencing to an average depth of 37 million reads, with 50–70% of the reads assigned to the human genome. We identified a panel of oncological signaling pathways including USP6, MYH3, KRT16, and ANGPTL7 that are highly differentially expressed between patients diagnosed before and after age 30. Hierarchical clustering for age at tumor diagnosis using whole-transcriptome differentially expressed RNA elicited significant divergence between the two groups.

Conclusions: We have identified a set of signaling pathways already implicated in other cancers that are differentially expressed in aCp based on its bimodal age distribution. Furthermore, whole transcriptome RNA expression clustering demonstrates significant molecular divergence between younger and older patients. This supports a unique pathogenesis between aCp patient age groups and may result in future personalized treatment based on patient age.

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