TY - JOUR
T1 - Patient-Derived Tumor Organoids for Guidance of Personalized Drug Therapies in Recurrent Glioblastoma
AU - Ratliff, Miriam
AU - Kim, Hichul
AU - Qi, Hao
AU - Kim, Minsung
AU - Ku, Bosung
AU - Azorin, Daniel Dominguez
AU - Hausmann, David
AU - Khajuria, Rajiv K.
AU - Patel, Areeba
AU - Maier, Elena
AU - Cousin, Loic
AU - Ogier, Arnaud
AU - Sahm, Felix
AU - Etminan, Nima
AU - Bunse, Lukas
AU - Winkler, Frank
AU - El-Khoury, Victoria
AU - Platten, Michael
AU - Kwon, Yong Jun
N1 - Funding Information:
Funding: This work was partially supported by a grant from the German Research Foundation (DFG, SFB1389—UNITE Glioblastoma) to M.R., D.A., F.S., L.B., F.W., and M.P.
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/6/12
Y1 - 2022/6/12
N2 - An obstacle to effective uniform treatment of glioblastoma, especially at recurrence, is genetic and cellular intertumoral heterogeneity. Hence, personalized strategies are necessary, as are means to stratify potential targeted therapies in a clinically relevant timeframe. Functional profiling of drug candidates against patient-derived glioblastoma organoids (PD-GBO) holds promise as an empirical method to preclinically discover potentially effective treatments of individual tumors. Here, we describe our establishment of a PD-GBO-based functional profiling platform and the results of its application to four patient tumors. We show that our PD-GBO model system preserves key features of individual patient glioblastomas in vivo. As proof of concept, we tested a panel of 41 FDA-approved drugs and were able to identify potential treatment options for three out of four patients; the turnaround from tumor resection to discovery of treatment option was 13, 14, and 15 days, respectively. These results demonstrate that this approach is a complement and, potentially, an alternative to current molecular profiling efforts in the pursuit of effective personalized treatment discovery in a clinically relevant time period. Furthermore, these results warrant the use of PD-GBO platforms for preclinical identification of new drugs against defined morphological glioblastoma features.
AB - An obstacle to effective uniform treatment of glioblastoma, especially at recurrence, is genetic and cellular intertumoral heterogeneity. Hence, personalized strategies are necessary, as are means to stratify potential targeted therapies in a clinically relevant timeframe. Functional profiling of drug candidates against patient-derived glioblastoma organoids (PD-GBO) holds promise as an empirical method to preclinically discover potentially effective treatments of individual tumors. Here, we describe our establishment of a PD-GBO-based functional profiling platform and the results of its application to four patient tumors. We show that our PD-GBO model system preserves key features of individual patient glioblastomas in vivo. As proof of concept, we tested a panel of 41 FDA-approved drugs and were able to identify potential treatment options for three out of four patients; the turnaround from tumor resection to discovery of treatment option was 13, 14, and 15 days, respectively. These results demonstrate that this approach is a complement and, potentially, an alternative to current molecular profiling efforts in the pursuit of effective personalized treatment discovery in a clinically relevant time period. Furthermore, these results warrant the use of PD-GBO platforms for preclinical identification of new drugs against defined morphological glioblastoma features.
KW - drug profiling
KW - glioblastoma
KW - intercellular calcium waves (ICW)
KW - patient-derived organoids
KW - personalized oncology
KW - precision medicine
KW - tumor cell network
KW - tumor microtube (TM)
UR - http://www.scopus.com/inward/record.url?scp=85131837427&partnerID=8YFLogxK
UR - https://pubmed.ncbi.nlm.nih.gov/35743016
U2 - 10.3390/ijms23126572
DO - 10.3390/ijms23126572
M3 - Article
C2 - 35743016
SN - 1661-6596
VL - 23
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
IS - 12
M1 - 6572
ER -