Projects per year
Abstract
Combination drug therapy addresses the auxiliary cancer pathways of the tumor progression unaffected by the standard adjuvant treatments such as radio- and chemotherapy. It is a particularly attractive strategy to improve the treatment outcomes and the quality of life in patients with the deadliest brain cancer, glioblastoma (GB). Testing of combination drug treatment protocols requires reliable, efficient, and biologically accurate preclinical testbeds applicable before the transition to clinical trials. The 3D in vitro models of GB are a promising platform for pharmacological research. However, there is notable methodological uncertainty and a highly scattered data landscape regarding drug testing in 3D in vitro models of GB. In particular, it is not completely clear how to mimic clinically relevant dozing and schedule of the main chemotherapy drug for GB, temozolomide (TMZ) in 3D in vitro GB models. Here, the authors carefully explore the available literature on the application of TMZ in 3D in vitro models of GB, both as a sole agent and in combination with other medications. The joint analysis of the tumor modeling approaches, the employed assays, and the obtained treatment responses provided in this review may be used as a roadmap for future research in combination treatments of GB.
Original language | English |
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Article number | 2300197 |
Pages (from-to) | 1-23 |
Number of pages | 23 |
Journal | Advanced Therapeutics |
Volume | 6 |
Issue number | 11 |
Early online date | 9 Aug 2023 |
DOIs | |
Publication status | Published - Nov 2023 |
Bibliographical note
Copyright the Author(s) 2023. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- 3D culture
- combination drug testing
- drug repurposing
- glioblastoma
- in vitro models
Fingerprint
Dive into the research topics of 'Combination drug therapy of glioblastoma: lessons from 3D in vitro models and the roadmap for future research'. Together they form a unique fingerprint.Projects
- 1 Active
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Computational Neurosurgery Lab
Di Ieva, A., George, L., Azemi, G., Suero Molina, E., Russo, C., Liu, S., Guller, A., TABASSUM, M., Kumari, P., Igrunkova, A., Unnikrishnan, S. & Beheshti, A.
1/01/19 → …
Project: Research
Activities
- 1 Membership of committee
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Faculty of Medicine, Health and Human Sciences (Organisational unit)
Mitchell Sarkies (Member), Fiona Bright (Member), Katie De Luca (Member), Emre Ilhan (Member), Amy Nguyen (Member), Elizabeth Austin (Member), Ann Carrigan (Member), Karla Seaman (Member), Chris Bladen (Member), Annika van Hummel (Member), Jannah Baker (Member), Robert Ross (Member), Sian Genoud (Member), Emily Don (Chair), Nitin Chitranshi (Member), Rae-Anne Hardie (Chair), Rimante Ronto (Member), Gemma Sicouri (Member), Kelly Williams (Member), Syeda Somyyah Owais (Member), Anna Guller (Member), Robert Newport (Member), Marina Junqueira Santiago (Member), Philippe Gilchrist (Member), Jessamine Chen (Member), Ella Oar (Member), Alison Hogan (Member), Jodie Wills (Member), Kathleen Yin (Member), Gillian Hulst (Member), Benjamin Brown (Member), Loes Koring (Member), Stephney Whillier (Member), Milena Gandy (Member), Carly Johnco (Member), Lauren McLellan (Member) & Michael Swain (Member)
2020 → …Activity: Membership › Membership of committee
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Engineered microenvironments for 3D cell culture and regenerative medicine: challenges, advances, and trends
Guller, A. & Igrunkova, A., Jan 2023, In: Bioengineering. 10, 1, p. 1-8 8 p., 17.Research output: Contribution to journal › Editorial › peer-review
Open AccessFile3 Citations (Scopus)73 Downloads (Pure) -
Evaluation of adherence monitoring in buprenorphine treatment: a pilot study using timed drug assays to determine accuracy of testing
Jamshidi, N., Athavale, A., Tremonti, C., McDonald, C., Banukumar, S., Vazquez, S., Luquin, N., Santiago, M. & Murnion, B., Jul 2023, In: British Journal of Clinical Pharmacology. 89, 7, p. 1938-1947 10 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile4 Citations (Scopus)104 Downloads (Pure) -
Foundations of multiparametric brain tumor imaging characterization using machine learning
Jian, A., Jang, K., Russo, C., Liu, S. & Di Ieva, A., 2022, Machine learning in clinical neuroscience: foundations and applications. Staartjes, V. E., Regli, L. & Serra, C. (eds.). Switzerland: Springer, Springer Nature, p. 183-193 11 p. (Acta Neurochirurgica Supplement; vol. 134).Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
11 Citations (Scopus)