Biology subjects

Walker-Samuel, S.

Publications and source records attributed to Walker-Samuel, S..

22 records · Page 2Linked to original sources

bioRxiv2017

Development of noninvasive biomarkers of response to proteasome inhibitor therapy (ixazomib) by imaging disrupted protein homeostasis in mouse models of solid tumors

With clinically-approved proteasome inhibitors now a standard of care for multiple myeloma, and increasing interest in their use in solid tumors, methods for monitoring therapeutic response in vivo are critically required. Here, we show that tumor protein homeostasis can be noninvasively monitored, using chemical exchange (CEST) magnetic resonance imaging (MRI) as a surrogate marker for proteasome inhibition, alongside diffusion MRI and relaxometry. We show that the in vivo CEST signal associated with amides and amines increases in proportion to proteasome inhibitor dose (ixazomib) and the magnitude of therapeutic effect in colorectal cancer xenografts. Moreover, we show that SW1222 and LS174T human colorectal cancer cell lines demonstrate differing sensitivities to ixazomib, which was reflected in our MRI measurements. We also found evidence of a mild stimulation in tumor growth at low ixazomib doses. Our results therefore identify CEST MRI as a promising method for safely and noninvasively monitoring changes in tumor protein homeostasis.

biophysics↗

bioRxiv2017

Non-invasive measurement of hepatic venous oxygen saturation (ShvO2) with quantitative susceptibility mapping in normal mouse liver and livers bearing colorectal metastases

PurposeThe purpose of this prospective study was to investigate the potential of QSM to non-invasively measure hepatic venous oxygen saturation (ShvO2).\n\nMaterials & MethodsAll animal studies were performed in accordance with the UK Home Office Animals Science Procedures Act (1986) and UK National Cancer Research Institute (NCRI) guidelines. QSM data was acquired from a cohort of mice (n=10) under both normoxic (medical air, 21% O2/ balance N), and hyperoxic conditions (100% O2). Susceptibility measurements were taken from large branches of the portal and hepatic vein under each condition and were used to calculate venous oxygen saturation in each vessel. Blood was extracted from the IVC of three mice under norm- and hyperoxic conditions, and oxygen saturation was measured using a blood gas analyser to act as a gold standard. QSM data was also acquired from a cohort of mice bearing colorectal liver metastases (CRLM). SvO2 was calculated from susceptibility measurements made in the portal and hepatic veins, and compared to the healthy animals.\n\nResultsSvO2 calculated from QSM measurements showed a significant increase of 14.93% in the portal vein (p < 0.05), and an increase of 21.39% in the hepatic vein (p < 0.01). Calculated results showed excellent agreement with those from the blood gas analyser (26.14% increase). ShvO2 was significantly lower in the disease cohort (30.18 {+/-} 11.6%), than the healthy animals (52.67 {+/-} 17.8%) (p < 0.05), but differences in the portal vein were not significant.\n\nConclusionQSM is a feasible tool for non-invasively measuring hepatic venous oxygen saturation and can detect differences in oxygen consumption in livers bearing colorectal metastases.

biophysics↗

bioRxiv2017

Deep learning diffusion fingerprinting to detect brain tumour response to chemotherapy

Artificial neural networks are being widely implemented for a range of different biomedical imaging applications.Convolutional neural networks are by far the most popular type of deep earning architecture,but often require very large datasets for robust training and evaluation We introduce deep learning diffusion fingerprinting (DLDF), which we have used to classifydiffusion-weighted magnetic resonance imaging voxels in a mouse model of glioblastoma (GL261 cell line), both prior to and in response to Temozolomide (TMZ) chemotherapy.We show that, even with limited training, DLDF can automatically segment brain tumours from normal brain, can automatically distinguish between young and older (after 9 days of growth) tumours and that DLDF can detect whether or not a tumour has been treated with chemotherapy.Our results also suggest that DLDF can detect localised changes in the underlying tumour microstructure, which are not evident using conventional measurements of the apparent diffusion coefficient (ADC).Tissue category maps generated by DLDF showed regions containing a mixture of normal brain and tumour cells, and in some cases evidence of tumour invasion across the corpus callosum, which were broadly consistent with histology.In conclusion, DLDF shows the potential for applying deep learning on a pixel-wise level,which reduces the need for vast training datasets and could easily be applied to other multi-dimensional imaging acquisitions\n\nAbbreviations

biophysics↗

bioRxiv2017

Quantitation of brain tumour microstructure response to Temozolomide therapy using non-invasive VERDICT MRI

There has been slow progress in the development of new therapeutic strategies for treating brain tumours, partly because assessment of treatment response is difficult and largely reliant on simple bi-dimensional measurements of MRI contrast-enhancing regions. Hence, there is a clinical need to develop improved imaging techniques for monitoring treatment response. In this study, we evaluate VERDICT (Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors) MRI in mouse glioblastomas for the quantification of tumour microstructure and assessment of response to Temozolomide (TMZ) chemotherapy, and, we investigate the feasibility of applying VERDICT MRI in a range of human gliomas. VERDICT MRI detected response to TMZ earlier than structural and apparent diffusion coefficient (ADC) measurements. A significant reduction in the cell radius parameter was detected three days earlier than ADC and six days earlier than structural MRI. Histological analysis showed the same trend as VERDICT of decreased intracellular volume fraction in the TMZ-treated mice. Vascular volume fraction was not altered by TMZ, which was consistent with optical projection tomography measurements. In patients, glioblastoma compartmental volume fractions showed good agreement with mouse glioblastoma parameters. The VERDICT parameters varied across the human gliomas, with raised intracellular volume fraction in the oligodendrogliomas and elevated cell radius in both low-grade tumours subtypes. In conclusion, our results suggest that VERDICT MRI is more sensitive at detecting TMZ response than structural or ADC measurements. In patients, VERDICT is feasible within clinical scan times, and performed best at characterising glioblastoma. Further optimisation should improve assessment of different glioma subtypes.

biophysics↗