Non-invasive metabolic imaging of brain tumours in the era of precision medicine

Abstract

The genomic revolution in cancer has uncovered a variety of mutations in primary brain tumors. This has created an urgent need to develop non-invasive imaging biomarkers to assess and integrate this genetic information in the clinical management of patients. Metabolic reprogramming is a central hallmark of cancers including brain tumors. Many of the molecular pathways implicated in brain tumors directly reprogram metabolism. This provides the opportunity to devise in vivo metabolism-based imaging modalities for patient stratification, to improve diagnosis, and to monitor treatment response. Metabolic phenomena like the Warburg effect and altered mitochondrial metabolism can be leveraged to image brain tumors using techniques like positron emission tomography (PET) imaging and Magnetic Resonance (MR) metabolic imaging. Moreover, genetic alterations such as isocitrate dehydrogenase mutations produced unique metabolic signatures that can be detected using MR spectroscopy. There is a growing need to translate our understanding of the molecular aspects of brain tumors to in vivo imaging in patients. Metabolism-based imaging provides a unique platform to achieve this. In this review we examine the molecular basis for metabolic reprograming in brain tumors and examine current non-invasive metabolic imaging strategies to interrogate them, for the ultimate goal of guiding and improving patient care.

Through Scalp and Skull NIR‐II Photothermal Therapy of Deep Orthotopic Brain Tumors with Precise Photoacoustic Imaging Guidance

“…For orthotopic tumor model (Figure ), noninvasive clear pinpointing deep brain tumor through skull and scalp is of significant importance for image guided surgery and therapy . Before systematic injection of P1 NPs and P1 RGD NPs, bioluminescence imaging showed that glioma cells labeled with luciferase were highly bioactive (Figure b), while magnetic resonance imaging results revealed the location of tumor beneath skull at a depth of 3 mm with confirmed tumor size (Figure c).…”

Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE‐MRI derived biomarkers in multicenter oncology trials

“…[5][6][7][8][9][14][15][16][17] As the quantitative measurements derived from DWI (eg, mean diffusivity) and DCE (eg, volume transfer constant) are utilized in clinical trials of new treatment strategies, or for precision medicine and personalized cancer care, the technical confidence of these measurements in repeatability and reproducibility is ever more critical. [18][19][20] Expert task forces of the Quantitative Imaging Biomarkers Alliance (QIBA) have devoted significant resources to write DWI and DCE profiles and review over 1000 scientific articles in this area, but such literature review efforts have yielded few original articles with adequately described testretest data. The lack of repeatability and reproducibility literature in this area creates a roadblock for clinical translation of quantitative DWI and DCE-MRI.…”

A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

“…Analyses of patient-derived tumor organoids, for example, could include predictive modeling and experimental validation for development of treatment strategies, both initially and with recurrence [235–237]. The influence of Warburg status could also be integrated into such personalized models if monitoring its influence on responsiveness of cancer to chemotherapy proves useful for selectively killing tumors [238]. Moreover, yeast phenomic models could be tailored to individual patients to examine more complex interactions: for example, in the background of homologous recombination deficiency [145].…”