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Mulholland, P.

Publications and source records attributed to Mulholland, P..

3 recordsLinked to original sources

Spatio-temporal summation of perimetric stimuli in healthy observers

Spatial summation of perimetric stimuli has been used to derive conclusions about the spatial extent of retinal-cortical convergence, mostly from the size of the critical area of summation (Riccos area, RA) and critical number of Retinal Ganglion Cells (RGCs). However, spatial summation is known to change dynamically with stimulus duration. Conversely, temporal summation and critical duration also vary with stimulus size. Such an important and often neglected spatio-temporal interaction has important implications for modelling perimetric sensitivity in healthy observers and for formulating hypotheses for changes measured in disease. In this work, we performed experiments on visually heathy observers confirming the interaction of stimulus size and duration in determining summation responses in photopic conditions. We then propose a simplified computational model that captures these aspects of perimetric sensitivity by modelling the total retinal input, the combined effect of stimulus size, duration and retinal cones-to-RGC ratio. We additionally show that, in the macula, the enlargement of RA with eccentricity might not correspond to a constant critical number of RGCs, as often reported, but to a constant critical total retinal input. We finally compare our results with previous literature and show possible implications for modelling disease, especially glaucoma.

neuroscience↗

Metabolic-imaging of human glioblastoma explants: a new precision-medicine model to predict tumor treatment response early

BackgroundGlioblastoma (GB) is the most severe form of brain cancer, with a 12-15 month median survival. Surgical resection, temozolomide (TMZ) treatment, 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 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 then 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 promoter methylated tumors for the MGMT gene 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 ex-vivo 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.

molecular biology↗

DNA methylation and survival differences associated with the type of IDH mutation in 1p/19q non-codeleted astrocytomas

Somatic mutations in the isocitrate dehydrogenase genes IDH1 and IDH2 occur at high frequency in several tumour types. Even though these mutations are confined to distinct hotspots, we show that gliomas are the only tumour type with an exceptionally high percentage of IDH1R132H mutations. This high prevalence is important as IDH1R132H is presumed to be relatively poor at producing D-2-hydroxyglutarate (D-2HG) whereas high concentrations of this oncometabolite are required to inhibit TET2 DNA demethylating enzymes. Indeed, patients harbouring IDH1R132H mutated tumours have lower levels of genome-wide DNA-methylation, and an associated increased gene expression, compared to tumours with other IDH1/2 mutations ("non-R132H mutations"). This reduced methylation is seen in multiple tumour types and thus appears independent of site of origin. For 1p/19q non-codeleted glioma patients, we show that this difference is clinically relevant: in samples of the randomised phase III CATNON trial, patients harbouring non-R132H mutated tumours have better outcome (HR 0.41, 95% CI [0.24, 0.71], p=0.0013). Non-R132H mutated tumours also had a significantly lower proportion of tumours assigned to prognostically poor DNA-methylation classes (p<0.001). IDH mutation-type was independent in a multivariable model containing known clinical and molecular prognostic factors. To confirm these observations, we validated the prognostic effect of IDH mutation type on a large independent dataset. The observation that non-R132H mutated 1p/19q non-codeleted gliomas have a more favourable prognosis than their IDH1R132H mutated counterpart is clinically relevant and should be taken into account for patient prognostication. Single sentence summaryAstrocytoma patients with tumours harbouring IDH mutations other than p.R132H have increased DNA methylation levels and longer survival

cancer biology↗