METABOLIC-IMAGING OF HUMAN GLIOBLASTOMA EXPLANTS: A NEW PRECISION-MEDICINE MODEL TO PREDICT TREATMENT RESPONSE EARLY

Background: Glioblastoma (GB) is the most severe form of brain cancer, with a 12-15 month median survival. Surgical resection, temozolomide (TMZ) and radiotherapy (RT) remain the primary therapeutic options for GB, and no new therapies have been introduced in recent years. This therapeutic standstill is primarily due to preclinical models that do not reflect the complexity of GB cell biology and fail to test anti-cancer treatments valuably. Better preclinical models for compound screening are therefore needed. Methods: In-vitro 3D glioblastoma live explants (GB-EXPs) were derived from patients′ resected tumors. We then applied metabolic imaging by fluorescence lifetime imaging microscopy (FLIM) on to GB-EXPs to assess drug response, using TMZ as our benchmark drug. Whole-transcriptome and whole-exome analyses were performed. Results: Using FLIM we were able to stratify samples in Responder and Non-Responder tumors. Our functional precision medicine approach was successfully completed within 1 week of surgery. FLIM-based tumor samples stratification was well reflected at the molecular level, highlighting new targets associated with TMZ treatment and identifying a molecular signature associated with survival. Conclusions: To the best of our knowledge, this is the first time that FLIM-based metabolic imaging is used on live glioblastoma 3D explants to test anti-neoplastic drugs rapidly. FLIM-based readouts of drug response in GB explants could improve precision treatment of patients with GB and the identification of new anti-GB drugs. ### Competing Interest Statement The authors have declared no competing interest.