Details

Autor(en) / Beteiligte

• Prince, Eric
• Whelan, Ros
• Donson, Andrew
• Staulcup, Susan
• Hengartner, Astrid
• Vijmasi, Trinka
• Agwu, Chibueze
• Lillehei, Kevin O
• Foreman, Nicholas K
• Johnston, James M
• Massimi, Luca
• Anderson, Richard C E
• Souweidane, Mark M
• Naftel, Robert P
• Limbrick, David D
• Grant, Gerald
• Niazi, Toba N
• Dudley, Roy
• Kilburn, Lindsay
• Jackson, Eric M
• Jallo, George I
• Ginn, Kevin
• Smith, Amy
• Chern, Joshua J
• Lee, Amy
• Drapeau, Annie
• Krieger, Mark D
• Handler, Michael H
• Hankinson, Todd C

Titel

Transcriptional analyses of adult and pediatric adamantinomatous craniopharyngioma reveals similar expression signatures regarding potential therapeutic targets

Ist Teil von

• Acta neuropathologica communications, 2020-05, Vol.8 (1), p.68-68, Article 68

Ort / Verlag

England: BioMed Central Ltd

Erscheinungsjahr

2020

Quelle

EZB-FREE-00999 freely available EZB journals

Beschreibungen/Notizen

• Adamantinomatous craniopharyngioma (ACP) is a biologically benign but clinically aggressive lesion that has a significant impact on quality of life. The incidence of the disease has a bimodal distribution, with peaks occurring in children and older adults. Our group previously published the results of a transcriptome analysis of pediatric ACPs that identified several genes that were consistently overexpressed relative to other pediatric brain tumors and normal tissue. We now present the results of a transcriptome analysis comparing pediatric to adult ACP to identify biological differences between these groups that may provide novel therapeutic insights or support the assertion that potential therapies identified through the study of pediatric ACP may also have a role in adult ACP. Using our compiled transcriptome dataset of 27 pediatric and 9 adult ACPs, obtained through the Advancing Treatment for Pediatric Craniopharyngioma Consortium, we interrogated potential age-related transcriptional differences using several rigorous mathematical analyses. These included: canonical differential expression analysis; divisive, agglomerative, and probabilistic based hierarchical clustering; information theory based characterizations; and the deep learning approach, HD Spot. Our work indicates that there is no therapeutically relevant difference in ACP gene expression based on age. As such, potential therapeutic targets identified in pediatric ACP are also likely to have relvance for adult patients.