| 1. |
- Garcia-Alonso, Luz, et al.
(författare)
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Mapping the temporal and spatial dynamics of the human endometrium in vivo and in vitro
- 2021
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 53:12, s. 1698-
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Tidskriftsartikel (refereegranskat)abstract
- The endometrium, the mucosal lining of the uterus, undergoes dynamic changes throughout the menstrual cycle in response to ovarian hormones. We have generated dense single-cell and spatial reference maps of the human uterus and three-dimensional endometrial organoid cultures. We dissect the signaling pathways that determine cell fate of the epithelial lineages in the lumenal and glandular microenvironments. Our benchmark of the endometrial organoids reveals the pathways and cell states regulating differentiation of the secretory and ciliated lineages both in vivo and in vitro. In vitro downregulation of WNT or NOTCH pathways increases the differentiation efficiency along the secretory and ciliated lineages, respectively. We utilize our cellular maps to deconvolute bulk data from endometrial cancers and endometriotic lesions, illuminating the cell types dominating in each of these disorders. These mechanistic insights provide a platform for future development of treatments for common conditions including endometriosis and endometrial carcinoma. Single-cell and spatial transcriptomic profiling of the human endometrium highlights pathways governing the proliferative and secretory phases of the menstrual cycle. Analyses of endometrial organoids show that WNT and NOTCH signaling modulate differentiation into the secretory and ciliated epithelial lineages, respectively.
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| 2. |
- Lomakin, Artem, et al.
(författare)
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Spatial genomics maps the structure, nature and evolution of cancer clones
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 611:7936, s. 594-602
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Tidskriftsartikel (refereegranskat)abstract
- Genome sequencing of cancers often reveals mosaics of different subclones present in the same tumour. Although these are believed to arise according to the principles of somatic evolution, the exact spatial growth patterns and underlying mechanisms remain elusive. Here, to address this need, we developed a workflow that generates detailed quantitative maps of genetic subclone composition across whole-tumour sections. These provide the basis for studying clonal growth patterns, and the histological characteristics, microanatomy and microenvironmental composition of each clone. The approach rests on whole-genome sequencing, followed by highly multiplexed base-specific in situ sequencing, single-cell resolved transcriptomics and dedicated algorithms to link these layers. Applying the base-specific in situ sequencing workflow to eight tissue sections from two multifocal primary breast cancers revealed intricate subclonal growth patterns that were validated by microdissection. In a case of ductal carcinoma in situ, polyclonal neoplastic expansions occurred at the macroscopic scale but segregated within microanatomical structures. Across the stages of ductal carcinoma in situ, invasive cancer and lymph node metastasis, subclone territories are shown to exhibit distinct transcriptional and histological features and cellular microenvironments. These results provide examples of the benefits afforded by spatial genomics for deciphering the mechanisms underlying cancer evolution and microenvironmental ecology.
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| 3. |
- Wadie, Bishoy, et al.
(författare)
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Use of viral motif mimicry improves the proteome-wide discovery of human linear motifs
- 2022
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Ingår i: Cell Reports. - : Elsevier. - 2211-1247. ; 39:5
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Tidskriftsartikel (refereegranskat)abstract
- Linear motifs have an integral role in dynamic cell functions, including cell signaling. However, due to their small size, low complexity, and frequent mutations, identifying novel functional motifs poses a challenge. Viruses rely extensively on the molecular mimicry of cellular linear motifs. In this study, we apply systematic motif prediction combined with functional filters to identify human linear motifs convergently evolved also in viral proteins. We observe an increase in the sensitivity of motif prediction and improved enrichment in known instances. We identify >7,300 non-redundant motif instances at various confidence levels, 99 of which are supported by all functional and structural filters. Overall, we provide a pipeline to improve the identification of functional linear motifs from interactomics datasets and a comprehensive catalog of putative human motifs that can contribute to our understanding of the human domain-linear motif code and the associated mechanisms of viral interference.
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