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| 2. |
- Berglund, Emelie, et al.
(författare)
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Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity
- 2018
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.
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| 3. |
- 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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| 4. |
- 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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| 6. |
- 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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| 7. |
- Marklund, Maja, et al.
(författare)
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Spatio-temporal analysis of prostate tumors in situ suggests the pre-existence of ADT-resistance
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The molecular mechanisms by which potentially lethal castration-resistant prostate cancer emerge in advanced metastatic prostate cancer are still poorly understood. Intratumor heterogeneity is believed to contribute to the fact that a majority of affected men succumb to the disease within a few years. In this study, we will challenge the conventional notion that castration-resistant prostate cancer cells evolve as a consequence of treatment. To examine the temporal aspects of resistance, we analyze tumor heterogeneity in core needle biopsies collected pre-and post-treatment. 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 identified several distinct intratumoral cell populations, characterized by their unique gene expression profiles. Strikingly, certain minor cell populations present before treatment exhibited gene expression profiles that matched those of resistant tumor cell clusters. Such resistant clusters were confirmed by the localization of the androgen receptor to the nuclei in cancer cells present after treatment. Our data also demonstrate that stromal cells adjacent to resistant tumor factors do not express AR before treatment (or after), which can be used to increase the power in predicting resistant tumors.
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| 9. |
- Ritsinger, Viveca, et al.
(författare)
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Sustained prognostic implications of newly detected glucose abnormalities in patients with acute myocardial infarction : Longterm follow-up of the Glucose Tolerance in Patients with Acute Myocardial Infarction cohort
- 2015
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Ingår i: Diabetes & Vascular Disease Research. - : SAGE Publications. - 1479-1641 .- 1752-8984. ; 12:1, s. 23-32
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To investigate long-term prognostic importance of newly discovered glucose disturbances in patients with acute myocardial infarction (AMI). Methods: During 1998-2001, consecutive patients with AMI (n=167) and healthy controls (n=184) with no previously known diabetes were investigated with an oral glucose tolerance test (OGTT). Patients and controls were separately followed up for cardiovascular events (first of cardiovascular mortality/AMI/stroke/heart failure) during a decade. Results: In all, 68% of the patients and 35% of the controls had newly detected abnormal glucose tolerance (AGT). Cardiovascular event (n=72, p=0.0019) and cardiovascular mortality (n=31, p=0.031) were more frequent in patients with newly detected AGT. Regarding patients, a Cox proportional-hazard regression analysis identified AGT (hazard ratio (HR): 2.30; 95% confidence interval (CI): 1.24-4.25; p=0.008) and previous AMI (HR: 2.39; CI: 1.31-4.35; p=0.004) as prognostically important. Conclusion: An OGTT at discharge after AMI disclosed a high proportion of patients with previously unknown AGT which had a significant and independent association with long-term prognosis.
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| 11. |
- Tarish, Firas L., et al.
(författare)
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Castration radiosensitizes prostate cancer tissue by impairing DNA double-strand break repair
- 2015
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Ingår i: Science Translational Medicine. - : American Association for the Advancement of Science (AAAS). - 1946-6234 .- 1946-6242. ; 7:312
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Tidskriftsartikel (refereegranskat)abstract
- Chemical castration improves responses to radiotherapy in prostate cancer, but the mechanism is unknown. We hypothesized that this radiosensitization is caused by castration-mediated down-regulation of non-homologous end joining (NHEJ) repair of DNA double-strand breaks (DSBs). To test this, we enrolled 48 patients with localized prostate cancer in two arms of the study: either radiotherapy first or radiotherapy after neoadjuvant castration treatment. We biopsied patients at diagnosis and before and after castration and radiotherapy treatments to monitor androgen receptor, NHEJ, and DSB repair in verified cancer tissue. We show that patients receiving neoadjuvant castration treatment before radiotherapy had reduced amounts of the NHEJ protein Ku70, impaired radiotherapy-induced NHEJ activity, and higher amounts of unrepaired DSBs, measured by gamma-H2AX foci in cancer tissues. This study demonstrates that chemical castration impairs NHEJ activity in prostate cancer tissue, explaining the improved response of patients with prostate cancer to radiotherapy after chemical castration.
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