| 1. |
- Vicari, Marco, et al.
(author)
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Spatial multimodal analysis of transcriptomes and metabolomes in tissues
- 2023
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In: Nature Biotechnology. - 1087-0156 .- 1546-1696.
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Journal article (peer-reviewed)abstract
- We present a spatial omics approach that combines histology, mass spectrometry imaging and spatial transcriptomics to facilitate precise measurements of mRNA transcripts and low-molecular-weight metabolites across tissue regions. The workflow is compatible with commercially available Visium glass slides. We demonstrate the potential of our method using mouse and human brain samples in the context of dopamine and Parkinson’s disease.
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| 2. |
- Vicari, Marco, et al.
(author)
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Spatial multimodal analysis of transcriptomes and metabolomes in tissues
- 2024
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In: Nature Biotechnology. - : Nature Research. - 1087-0156 .- 1546-1696. ; 42:7, s. 1046-1050
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Journal article (peer-reviewed)abstract
- We present a spatial omics approach that combines histology, mass spectrometry imaging and spatial transcriptomics to facilitate precise measurements of mRNA transcripts and low-molecular-weight metabolites across tissue regions. The workflow is compatible with commercially available Visium glass slides. We demonstrate the potential of our method using mouse and human brain samples in the context of dopamine and Parkinson’s disease.
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| 3. |
- Bergenstråhle, Ludvig, et al.
(author)
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Super-resolved spatial transcriptomics by deep data fusion
- 2022
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In: Nature Biotechnology. - : Nature Research. - 1087-0156 .- 1546-1696. ; 40:4, s. 476-479
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Journal article (peer-reviewed)abstract
- Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone.
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| 4. |
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| 5. |
- Erickson, A, et al.
(author)
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Spatially resolved clonal copy number alterations in benign and malignant tissue
- 2022
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 608:7922, s. 360-
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Journal article (peer-reviewed)abstract
- Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.
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| 6. |
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| 7. |
- Erickson, Andrew, et al.
(author)
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The spatial landscape of clonal somatic mutations in benign and malignant tissue
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Other publication (other academic/artistic)abstract
- Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we provide an unsupervised approach to study spatial genome integrity in situ to gain molecular insight into clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120 000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.
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| 8. |
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| 9. |
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| 10. |
- Kvastad, Linda, et al.
(author)
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The spatial landscape of transcriptomes and genomes in pediatric brain tumors
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Other publication (other academic/artistic)abstract
- Treatment of pediatric brain tumors is continually being improved; still, there is a great need for new treatment options. Here we explore the spatial transcriptomic and genomic landscape in a cohort of pediatric brain tumors using a new generation of unbiased methodologies. We demonstrate the gene expression patterns of the essential cancer-related gene programs of epithelial-to-mesenchymal transition (EMT), the reverse process mesenchymal-to-epithelial transition (MET), and tumor microenvironment (TME) observations through microglia. Furthermore, we identify the gene expression of SPP1 by microglia in the TME as a potential prognostic mRNA marker - in pediatric brain tumor relapse patients.
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