The use of ultrasound as a diagnostic imaging tool is well known, particularly during pregnancy where ultrasound is used to create images of the developing foetus. In recent years, a growing number of therapeutic applications of ultrasound have also been demonstrated. The goal of therapeutic ultrasound is to modify the function or structure of the tissue, rather than produce an anatomical image. This is possible because the mechanical vibrations caused by the ultrasound waves can affect tissue in different ways, for example, by causing the tissue to heat up, or by generating internal radiation forces that can agitate the cells or tissue scaffolding. These ultrasound bioeffects offer a huge potential to develop new ways to treat major diseases such as cancer, to improve the delivery of drugs while minimising side-effects, and to treat a wide spectrum of neurological and psychiatric conditions. The fundamental challenge shared by all applications of therapeutic ultrasound is that the ultrasound energy must be delivered accurately, safely, and non-invasively to the target region within the body. This is difficult because bones and other tissue interfaces can severely distort the shape of the ultrasound beam. This has a significant impact on the safety and effectiveness of therapeutic ultrasound, and presents a major hurdle for the wider clinical acceptance of these exciting technologies. In principle, any distortions to the ultrasound beam could be accounted for using advanced computer models. However, the underlying physics is complex, and the scale of the modelling problem requires extremely large amounts of computer memory. Using existing software, a single simulation running on a supercomputer can take many days to complete, which is too long to be clinically useful. The aim of this proposal is to develop more efficient computer models to accurately predict how ultrasound waves travel through the human body. This will involve implementing new approaches that efficiently divide the computational problem across large numbers of interconnected computer cores on a supercomputer. New approaches to reduce the huge quantity of output data will also be implemented, including calculating clinically important parameters while the simulation runs, and optimising how the data is stored to disk. We will also develop a professional user interface and package the code within the regulatory framework required for medical software. This will allow end-users, such as doctors, to easily use the code for applications in therapeutic ultrasound without needing to be an expert in computer science. In collaboration with our clinical partners, the computer models will then be applied to different applications of therapeutic ultrasound to allow the precise delivery of ultrasound energy to be predicted for the individual patient.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

The normal and healthy functioning of cells is controlled by a plethora of nano-molecuiar machines which are made up of protein molecules, each of whose shape and mechanism of action is defined by the genetic information encoded in DNA. Assembly of many of these nano-machines, requires help from specialised nano-machines called chaperones, which look after component proteins until they are required, and ensure that the correct components are combined into the final working nano-machine. One of the most important of these chaperones is called HSP90. This is responsible for assisting the assembly of many of the nano-machines that monitor the health of the cell and transmit messages between and within cells. One of these - TOR - is particularly important for monitoring the nutritional health of the cell, and over-activity or defects in TOR are associated with diseases such as cancer, diabetes and unhealthy ageing. We wish to understand how the HSP90 chaperone, with the collaboration of two other nano-machines R2TP and TTT, facilitates the assembly of nano-machines based around TOR. To do this we will use very high magnification electron microscopes and intense X-ray beams, to look at the atomic structures of the different nano-machines involved, to work out which parts are critical for activity, and which parts of different nano-machines make contact with each other during the assembly process. This information will help us understand how TOR is regulated by these chaperones, and will point at new ways of controlling TOR activity with novel drugs.

Advanced prostate cancer is characterised by the emergence of resistance to hormone therapy, and is invariably fatal. The biological mechanisms underlying the evolution to an aggressive, treatment-resistant state are diverse, and have not yet been fully characterised. Further understanding of these mechanisms will allow the development of targeted treatment strategies. Our DNA is exposed to damage in various forms each day, and relies on our body's innate mechanisms to repair this, and protect our genetic code. Recent evidence has identified defects in the ability to repair damage to DNA in 20-30% of advanced prostate cancer patients. This results in the accumulation of DNA damage, which makes cancer cells dependent on alternative pathways for survival, which we can exploit therapeutically, with agents targeting DNA repair pathways, such as PARP and ATR inhibitors. However, there is a need for more robust tests to easily identify patients who may benefit from such therapies. DNA repair defects enable the accumulation of DNA damage, which can be expressed as proteins (neo-antigens) on the cancer cell. These make the cancer more visible to the immune system, and therefore more vulnerable to treatments which act on immune cells to trigger an anti-cancer immune response, such as immune checkpoint inhibitors. A new DNA repair defect, RNASEH2B loss, commonly present in advanced prostate cancer, has recently been identified, and is associated with heightened sensitivity to PARP/ATR inhibition. It is located on chromosome 13, close to RB1, a gene which is frequently deleted in aggressive forms of PC, at a late stage in the disease evolution, and is associated with poor outcomes. Our preliminary data suggests these genes are often deleted together, and this may contribute to the development of aggressive 'basal/neuroendocrine' PC cells which drive hormone resistance. We hypothesise that patients with RNASEH2B loss represent a novel cohort of patients with distinct biology who may respond to PARP/ATR inhibitors and/or immunotherapy. Here, I seek to explore the incidence of this co-deletion in prostate cancer, and its impact on tumour evolution and sensitivity to PARP/ATR inhibitors and immunotherapy. I hope to demonstrate that RNASEH2B/RB1 loss is identifiable within peripheral blood samples, and can be easily measured to identify candidates for treatment. If I demonstrate enhanced sensitivity to PARPi, ATRi or immunotherapy in pre-clinical models, I will endeavour to establish a proof of concept phase II trial of PARPi +/- ATRi (arm 1) and immunotherapy (arm 2) in RNASEH2B/RB1 deficient prostate cancer. I envisage that this research will enable better molecular stratification of advanced prostate cancer, and identify and target aggressive, resistant PC cells to enable us to develop novel therapeutic strategies to transform the treatment and outcomes for patients.

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