Knight, W. | bioRxiv Science

bioRxiv2022

Quisinostat is a brain-penetrant radiosensitizer in glioblastoma

In recent years, histone deacetylase inhibitors (HDACi) have garnered considerable interest for the treatment of adult and pediatric malignant brain tumors. However, owing to their broad-spectrum nature and inability to effectively penetrate the blood-brain barrier, HDACi have failed to provide significant clinical benefit to glioblastoma (GBM) patients to date. Moreover, global inhibition of HDACs results in widespread toxicity, highlighting the need for selective isoform targeting. While no isoform-specific HDACi are currently available, the second-generation hydroxamic acid-based HDACi quisinostat possesses sub-nanomolar specificity for class I HDAC isoforms, particularly HDAC1 and 2. Recently, we demonstrated that HDAC1 is the essential HDAC in GBM. Here, we provide the first report on the neuro-pharmacokinetic, pharmacodynamic and radiation-sensitizing properties of quisinostat in preclinical models of GBM. We demonstrate that quisinostat is a well-tolerated and brain-penetrant molecule that significantly extends survival when administered in combination with radiation in vivo. The pharmacokinetic-pharmacodynamic-efficacy relationship was established by correlating free drug concentrations and evidence of target modulation in the brain with survival benefit. Together, these data provide a strong rationale for clinical development of quisinostat as a radiosensitizer for the treatment of GBM.

cancer biology↗

bioRxiv2021

A comparative study between state-of-the-art MRI deidentification and AnonyMI, a new method combining re-identification risk reduction and geometrical preservation

Deidentifying MRIs constitutes an imperative challenge, as it aims at precluding the possibility of re-identification of a research subject or patient, but at the same time it should preserve as much geometrical information as possible, in order to maximize data reusability and to facilitate interoperability. Although several deidentification methods exist, no comprehensive and comparative evaluation of deidentification performance has been carried out across them. Moreover, the possible ways these methods can compromise subsequent analysis has not been exhaustively tested. To tackle these issues, we developed AnonyMI, a novel MRI deidentification method, implemented as a user-friendly 3D Slicer plugin-in, which aims at providing a balance between identity protection and geometrical preservation. To test these features, we performed two series of analyses on which we compared AnonyMI to other two state-of-the-art methods, to evaluate, at the same time, how efficient they are at deidentifying MRIs and how much they affect subsequent analyses, with particular emphasis on source localization procedures. Our results show that all three methods significantly reduce the re-identification risk but AnonyMI provides the best geometrical conservation. Notably, it also offers several technical advantages such as a user-friendly interface, multiple input-output capabilities, the possibility of being tailored to specific needs, batch processing and efficient visualization for quality assurance.

neuroscience↗