Metabolic imaging across scales reveals distinct prostate cancer phenotypes

Hyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer

Astrocytic networks as a novel therapeutic target in Parkinson’s disease

Parkinson’s disease (PD) is a neurodegenerative condition with the highest rise in disability and is currently incurable. Dopamine replacement therapies reduce motor symptoms temporarily, but do not address non-motor symptoms (NMS) of PD, and often cause serious side effects; with up to 10 million people with PD worldwide and predicted economic burden of over £79 billion in the US alone by 2037, the unmet clinical need is large. Deeper understanding of PD pathology is required to create new transformative therapies. One cell type that received increasing attention in PD recently is astrocytes. Astrocytes express multiple familial PD-associated genes as much, or more than neurones, and develop alpha-synuclein (a-syn) immunoreactivity which correlates with dopaminergic loss. Their causal involvement in PD symptom development was demonstrated in vitro and in vivo, where healthy astrocytes could rescue functions of neurones carrying PD mutations and reduce motor symptoms in rodent models, and diseased astrocytes could induce PD-resembling dysfunction in heathy neurones or animal models. A key aspect of astrocyte biology is their ability to form large networks transmitting calcium signals. Abnormal calcium signalling is also a hallmark of PD. We hypothesised that astrocyte networks are dysregulated in PD, and normalising calcium transmission in astrocyte networks could reduce a-syn aggregation and inflammation. Our first target is connexin43 (Cx43) which connects astrocytes via gap junctions (GJs) and promotes calcium transmission, and dysregulation of which is linked to inflammasome activation through hemichannel (HC) opening

Integrative analysis of spatial transcriptomics, metabolomics, and histologic changes illustrated in tissue injury studies

Recent developments in spatially resolved omics have expanded studies linking gene expression, epigenetic alterations, protein levels, and metabolite intensity to tissue histology. The integration of multiple spatial measurements can offer new insights into alterations propagating across modalities, however, it also presents experimental and computational challenges.  To set the multimodal data into a shared coordinate system for enhanced integration and analysis, we propose MAGPIE, a framework for co-registering spatially resolved transcriptomics and spatial metabolomics measurements on the same or consecutive tissue sections, present within their existing histological context. Further, we showcase the utility of the MAGPIE framework on spatial multi-omics data from lung tissue, an inherently heterogeneous tissue type with integrity challenges and for which we developed an experimental sampling strategy to allow multimodal data generation. In these case studies, we were able to link pharmaceutical co-detection with endogenous responses in rat lung tissue following inhalation of a small molecule, which had previously been stopped during preclinical development with findings of lung irritation, and to characterise the metabolic and transcriptomic landscape in a mouse model of drug-induced pulmonary fibrosis in conjunction with histopathology annotations. The generalisability and scalability of the MAGPIE framework were further benchmarked on public datasets from multiple species and tissue types, demonstrating applicability to both DESI and MALDI mass spectrometry imaging together with Visium-enabled transcriptomic assessment. MAGPIE highlights the refined resolution and increased interpretability of spatial multimodal analyses in studying tissue injury, particularly in a pharmacological context, and offers a modular, accessible computational workflow for data integration.QC 20241016</p

Metabolic imaging across scales reveals distinct prostate cancer phenotypes

Acknowledgements: This study was supported by Prostate Cancer UK (PCUK; Grant PA14-012), Cancer Research UK (CRUK; Grant C19212/A27150), AstraZeneca, and the National Institute for Health and Care Research (NIHR) Cambridge Biomedical Research Centre (BRC; Grant NIHR203312). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. N.S. was supported by the Gates Cambridge Trust and is now a Research Fellow of Emmanuel College, Cambridge. A.Y.W. is supported by the Urological Malignancies Programme of the Cancer Research UK Cambridge Centre (C9685/A25177) and NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). V.J.G. acknowledges infrastructure support from the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). Additional support provided from the Cancer Research UK Cambridge Centre, the Cambridge Experimental Cancer Medicine Centre, a Wellcome Trust Strategic Award, Addenbrooke’s Charitable Trust, the Canadian Institute For Advanced Research, and Cambridge University Hospitals National Health Service Foundation Trust. The authors thank Dr Julia Jones of the Cancer Research UK Cambridge Institute for her help with the RNAscope component of the study.AbstractHyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer.</jats:p

Metabolic imaging across scales reveals distinct prostate cancer phenotypes.

Hyperpolarised magnetic resonance imaging (HP-13C-MRI) has shown promise as a clinical tool for detecting and characterising prostate cancer. Here we use a range of spatially resolved histological techniques to identify the biological mechanisms underpinning differential [1-13C]lactate labelling between benign and malignant prostate, as well as in tumours containing cribriform and non-cribriform Gleason pattern 4 disease. Here we show that elevated hyperpolarised [1-13C]lactate signal in prostate cancer compared to the benign prostate is primarily driven by increased tumour epithelial cell density and vascularity, rather than differences in epithelial lactate concentration between tumour and normal. We also demonstrate that some tumours of the cribriform subtype may lack [1-13C]lactate labelling, which is explained by lower epithelial lactate dehydrogenase expression, higher mitochondrial pyruvate carrier density, and increased lipid abundance compared to lactate-rich non-cribriform lesions. These findings highlight the potential of combining spatial metabolic imaging tools across scales to identify clinically significant metabolic phenotypes in prostate cancer