Moseley, A. | bioRxiv Science

bioRxiv2020

Effective psychological treatment for PTSD changes the dynamics of specific large-scale brain networks

AO_SCPLOWBSTRACTC_SCPLOWVery little is known about the role of effective cognitive therapy in reversing imbalances in brain activity after trauma. We hypothesised that exaggerated threat perception characteristic of post-traumatic stress disorder (PTSD), and subsequent recovery from this disorder, are underpinned by changes in the dynamics of large-scale brain networks. Here, we use a novel data-driven approach with high temporal precision to find recurring brain networks from fMRI data and estimate when these networks become active during exposure to either trauma reminders or neutral pictures. We found that PTSD patients spend less time in two default mode sub-networks in contrast to trauma-exposed healthy controls, and that PTSD symptom severity correlates positively with time spent in the salience network during exposure to trauma reminders. The former are important for different aspects of self-referential processing and the latter for detection of threat. Importantly, the decreased time in the default mode sub-networks is rebalanced after successful cognitive therapy for PTSD. Our results show that remittance of PTSD through trauma-focused cognitive therapy is associated with the successful reinstatement of a healthy balance in self-referential and threat detection brain networks.

neuroscience↗

bioRxiv2019

From the clinic to the bench and back again in one dog year: identifying new treatments for sarcoma using a cross-species personalized medicine pipeline

Cancer drug discovery is an inefficient process, with more than 90% of newly-discovered therapies failing to gain regulatory approval. Patient-derived models of cancer offer a promising new approach to identifying personalized treatments; however, for rare cancers, such as sarcomas, access to patient samples can be extremely limited, which precludes development of patient-derived models. To address the limited access to patient samples, we have turned to pet dogs with naturally-occurring sarcomas. Although sarcomas make up less than 1% of all cancers in humans, sarcomas represent at least 15% of all cancers in dogs. Dogs with naturally-occurring sarcomas also have intact immune systems, an accelerated pace of cancer progression, and share the same environment as humans, making them ideal models that bridge key gaps between mouse models and human sarcomas.\n\nHere, we develop a framework for a personalized medicine pipeline that integrates drug screening, validation, and genomics to identify new therapies. We tested this paradigm through the study of a pet dog, Teddy, who presented with six synchronous leiomyosarcomas. By integrating patient-derived cancer models, in vitro drug screens, and in vivo validation we identified proteasome inhibitors as a potential therapy for Teddy. After showing an initial response to the proteasome inhibitor, bortezomib, Teddy developed rapid resistance, and tumor growth resumed. Whole exome sequencing revealed substantial genetic heterogeneity across Teddys multiple recurrent tumors and metastases, suggesting that intra-patient heterogeneity was responsible for the heterogeneous clinical response. Ubiquitin proteomics coupled with exome sequencing revealed multiple candidate driver mutations in proteins related to the proteasome pathway. Together, our results demonstrate how the comparative study of canine sarcomas can offer rapid insights into the process of developing personalized medicine approaches that can lead to new treatments for sarcomas in both humans and canines.

cancer biology↗