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| 2. |
- Chelebian, Eduard, et al.
(författare)
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Morphological Features Extracted by AI Associated with Spatial Transcriptomics in Prostate Cancer
- 2021
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 13:19
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Tidskriftsartikel (refereegranskat)abstract
- Simple Summary Prostate cancer has very varied appearances when examined under the microscope, and it is difficult to distinguish clinically significant cancer from indolent disease. In this study, we use computer analyses inspired by neurons, so-called 'neural networks', to gain new insights into the connection between how tissue looks and underlying genes which program the function of prostate cells. Neural networks are 'trained' to carry out specific tasks, and training requires large numbers of training examples. Here, we show that a network pre-trained on different data can still identify biologically meaningful regions, without the need for additional training. The neural network interpretations matched independent manual assessment by human pathologists, and even resulted in more refined interpretation when considering the relationship with the underlying genes. This is a new way to automatically detect prostate cancer and its genetic characteristics without the need for human supervision, which means it could possibly help in making better treatment decisions. Prostate cancer is a common cancer type in men, yet some of its traits are still under-explored. One reason for this is high molecular and morphological heterogeneity. The purpose of this study was to develop a method to gain new insights into the connection between morphological changes and underlying molecular patterns. We used artificial intelligence (AI) to analyze the morphology of seven hematoxylin and eosin (H & E)-stained prostatectomy slides from a patient with multi-focal prostate cancer. We also paired the slides with spatially resolved expression for thousands of genes obtained by a novel spatial transcriptomics (ST) technique. As both spaces are highly dimensional, we focused on dimensionality reduction before seeking associations between them. Consequently, we extracted morphological features from H & E images using an ensemble of pre-trained convolutional neural networks and proposed a workflow for dimensionality reduction. To summarize the ST data into genetic profiles, we used a previously proposed factor analysis. We found that the regions were automatically defined, outlined by unsupervised clustering, associated with independent manual annotations, in some cases, finding further relevant subdivisions. The morphological patterns were also correlated with molecular profiles and could predict the spatial variation of individual genes. This novel approach enables flexible unsupervised studies relating morphological and genetic heterogeneity using AI to be carried out.
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- Erickson, Andrew, et al.
(författare)
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The spatial landscape of clonal somatic mutations in benign and malignant tissue
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Annan publikation (övrigt vetenskapligt/konstnärligt)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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- Figiel, Sandy, et al.
(författare)
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Spatial transcriptomic analysis of virtual prostate biopsy reveals confounding effect of tissue heterogeneity on genomic signatures
- 2023
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Ingår i: Molecular Cancer. - : Springer Nature. - 1476-4598. ; 22:1, s. 162-
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Genetic signatures have added a molecular dimension to prognostics and therapeutic decision-making. However, tumour heterogeneity in prostate cancer and current sampling methods could confound accurate assessment. Based on previously published spatial transcriptomic data from multifocal prostate cancer, we created virtual biopsy models that mimic conventional biopsy placement and core size. We then analysed the gene expression of different prognostic signatures (OncotypeDx®, Decipher®, Prostadiag®) using a step-wise approach with increasing resolution from pseudo-bulk analysis of the whole biopsy, to differentiation by tissue subtype (benign, stroma, tumour), followed by distinct tumour grade and finally clonal resolution. The gene expression profile of virtual tumour biopsies revealed clear differences between grade groups and tumour clones, compared to a benign control, which were not reflected in bulk analyses. This suggests that bulk analyses of whole biopsies or tumour-only areas, as used in clinical practice, may provide an inaccurate assessment of gene profiles. The type of tissue, the grade of the tumour and the clonal composition all influence the gene expression in a biopsy. Clinical decision making based on biopsy genomics should be made with caution while we await more precise targeting and cost-effective spatial analyses.
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- Kvastad, Linda, et al.
(författare)
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The spatial landscape of transcriptomes and genomes in pediatric brain tumors
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Annan publikation (övrigt vetenskapligt/konstnärligt)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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| 7. |
- Lamb, Alastair D, et al.
(författare)
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Aiming for a holistic integrated service for men diagnosed with prostate cancer – Definitions of standards and skill sets for nurses and allied healthcare professionals
- 2017
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Ingår i: European Journal of Oncology Nursing. - : Elsevier BV. - 1462-3889. ; 29, s. 31-38
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Tidskriftsartikel (refereegranskat)abstract
- Purpose To establish a comprehensive set of recommendations for the service structure and skill set of nurses and allied healthcare professionals in prostate cancer care. Methods Using components of formal consensus methodology, a 30-member multidisciplinary panel produced 53 items for discussion relating to the provision of care for prostate cancer patients by specialist nurses and allied healthcare professionals. Items were developed by two rounds of email correspondence in which, first, items were generated and, second, items refined to form the basis of a consensus meeting which constituted the third round of review. The fourth and final round was an email review of the consensus output. Results The panel agreed on 33 items that were appropriate for recommendations to be made. These items were grouped under categories of “Environment” and “Patient Pathway” and included comments on training, leadership, communication and quality assessment as well as specific items related to prostate diagnosis clinics, radical treatment clinics and follow-up survivor groups. Conclusions Specialist nurses and allied healthcare professionals play a vital role alongside urologists and oncologists to provide care to men with prostate cancer and their families. We present a set of standards and consensus recommendations for the roles and skill-set required for these practitioners to provide gold-standard prostate cancer care. These recommendations could form the basis for development of comprehensive integrated prostate cancer pathways in prostate cancer centres as well as providing guidance for any units treating men with prostate cancer.
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| 9. |
- Marklund, Maja, et al.
(författare)
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Spatio-temporal analysis of prostate tumors in situ suggests pre-existence of treatment-resistant clones
- 2022
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- The molecular mechanisms underlying lethal castration-resistant prostate cancer remain poorly understood, with intratumoral heterogeneity a likely contributing factor. To examine the temporal aspects of resistance, we analyze tumor heterogeneity in needle biopsies collected before and after treatment with androgen deprivation therapy. By doing so, we are able to couple clinical responsiveness and morphological information such as Gleason score to transcriptome-wide data. Our data-driven analysis of transcriptomes identifies several distinct intratumoral cell populations, characterized by their unique gene expression profiles. Certain cell populations present before treatment exhibit gene expression profiles that match those of resistant tumor cell clusters, present after treatment. We confirm that these clusters are resistant by the localization of active androgen receptors to the nuclei in cancer cells post-treatment. Our data also demonstrates that most stromal cells adjacent to resistant clusters do not express the androgen receptor, and we identify differentially expressed genes for these cells. Altogether, this study shows the potential to increase the power in predicting resistant tumors. Spatial heterogeneity in prostate cancer can contribute to its resistance to androgen deprivation therapy (ADT). Here, the authors analyse prostate cancer samples before and after ADT using Spatial Transcriptomics, and find heterogeneous pre-treatment tumour cell populations and stromal cells that are associated with resistance.
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