Frontiers in Oncology (Sep 2022)

Metabolic-imaging of human glioblastoma live tumors: A new precision-medicine approach to predict tumor treatment response early

  • Mariangela Morelli,
  • Francesca Lessi,
  • Serena Barachini,
  • Serena Barachini,
  • Romano Liotti,
  • Romano Liotti,
  • Nicola Montemurro,
  • Paolo Perrini,
  • Orazio Santo Santonocito,
  • Carlo Gambacciani,
  • Matija Snuderl,
  • Francesco Pieri,
  • Filippo Aquila,
  • Azzurra Farnesi,
  • Antonio Giuseppe Naccarato,
  • Paolo Viacava,
  • Francesco Cardarelli,
  • Gianmarco Ferri,
  • Gianmarco Ferri,
  • Paul Mulholland,
  • Diego Ottaviani,
  • Fabiola Paiar,
  • Gaetano Liberti,
  • Francesco Pasqualetti,
  • Francesco Pasqualetti,
  • Michele Menicagli,
  • Paolo Aretini,
  • Giovanni Signore,
  • Sara Franceschi,
  • Chiara Maria Mazzanti

DOI
https://doi.org/10.3389/fonc.2022.969812
Journal volume & issue
Vol. 12

Abstract

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BackgroundGlioblastoma (GB) is the most severe form of brain cancer, with a 12-15 month median survival. Surgical resection, temozolomide (TMZ) treatment, and radiotherapy 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 approaches that do not fully respect the complexity of GB cell biology and fail to test efficiently anti-cancer treatments. Therefore, better treatment screening approaches are needed. In this study, we have developed a novel functional precision medicine approach to test the response to anticancer treatments in organoids derived from the resected tumors of glioblastoma patients.MethodsGB organoids were grown for a short period of time to prevent any genetic and morphological evolution and divergence from the tumor of origin. We chose metabolic imaging by NAD(P)H fluorescence lifetime imaging microscopy (FLIM) to predict early and non-invasively ex-vivo anti-cancer treatment responses of GB organoids. TMZ was used as the benchmark drug to validate the approach. Whole-transcriptome and whole-exome analyses were performed to characterize tumor cases stratification.ResultsOur functional precision medicine approach was completed within one week after surgery and two groups of TMZ Responder and Non-Responder tumors were identified. FLIM-based metabolic tumor stratification was well reflected at the molecular level, confirming the validity of our approach, highlighting also new target genes associated with TMZ treatment and identifying a new 17-gene molecular signature associated with survival. The number of MGMT gene promoter methylated tumors was higher in the responsive group, as expected, however, some non-methylated tumor cases turned out to be nevertheless responsive to TMZ, suggesting that our procedure could be synergistic with the classical MGMT methylation biomarker.ConclusionsFor the first time, FLIM-based metabolic imaging was used on live glioblastoma organoids. Unlike other approaches, ex-vivo patient-tailored drug response is performed at an early stage of tumor culturing with no animal involvement and with minimal tampering with the original tumor cytoarchitecture. This functional precision medicine approach can be exploited in a range of clinical and laboratory settings to improve the clinical management of GB patients and implemented on other cancers as well.

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