| 1. |
- Berger, Ashton C, et al.
(författare)
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A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.
- 2018
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Ingår i: Cancer Cell. - : Elsevier BV. - 1535-6108 .- 1878-3686. ; 33:4, s. 690-705.e9
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Tidskriftsartikel (refereegranskat)abstract
- We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories.
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| 2. |
- Firsova, Alexandra, et al.
(författare)
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Topographic atlas of cell states identifies regional gene expression in the adult human lung
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Single cell mRNA sequencing of the whole organ has become a popular technique to reveal rare types and subtypes of previously characterized cells as well as to distinguish and characterize gene expression of previously unknown cell types. Unsupervised clustering can reveal tens or even hundreds of variable genes that characterize cell types. Variation in gene expression is often observed within one cell type, and sometimes cannot be biologically explained without mapping of mRNA on tissue. In this study we aim to (i) map the majority of cell types of human lung, (ii) describe variability in their gene expression and (iii) relate this gene expression to cellular location and neighborhoods. Using three different spatial transcriptomics approaches, we mapped epithelial cell states of airways and submucosal gland, and defined cell type-unrelated gene expression variability along proximo-distal axis, including potential regulators and co-regulators of such cell states in the mesenchymal and immune cell niches. In addition, we mapped rare cell types, such as subtypes of neuroendocrine cells, ionocytes and tuft (brush) cells, revealing tracheal preference for ionocytes, and distal airways for GHRL-positive neuroendocrine cells. Finally, we used the created map as a reference for the diseased tissue from patients with stage II COPD and revealed perturbed cell states and COPD-specific imbalance of cell types, affecting immune and AT0 clusters.
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| 3. |
- Sikkema, Lisa, et al.
(författare)
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An integrated cell atlas of the lung in health and disease
- 2023
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Ingår i: Nature Medicine. - : Springer Nature. - 1078-8956 .- 1546-170X. ; 29:6, s. 1563-1577
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Tidskriftsartikel (refereegranskat)abstract
- Single-cell technologies have transformed our understanding of human tissues. Yet, studies typically capture only a limited number of donors and disagree on cell type definitions. Integrating many single-cell datasets can address these limitations of individual studies and capture the variability present in the population. Here we present the integrated Human Lung Cell Atlas (HLCA), combining 49 datasets of the human respiratory system into a single atlas spanning over 2.4 million cells from 486 individuals. The HLCA presents a consensus cell type re-annotation with matching marker genes, including annotations of rare and previously undescribed cell types. Leveraging the number and diversity of individuals in the HLCA, we identify gene modules that are associated with demographic covariates such as age, sex and body mass index, as well as gene modules changing expression along the proximal-to-distal axis of the bronchial tree. Mapping new data to the HLCA enables rapid data annotation and interpretation. Using the HLCA as a reference for the study of disease, we identify shared cell states across multiple lung diseases, including SPP1 + profibrotic monocyte-derived macrophages in COVID-19, pulmonary fibrosis and lung carcinoma. Overall, the HLCA serves as an example for the development and use of large-scale, cross-dataset organ atlases within the Human Cell Atlas.
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