CellRank 2: unified fate mapping in multiview single-cell data

Weiler, Philipp; Lange, Marius; Klein, Michal; Pe’er, Dana; Theis, Fabian

doi:10.1038/s41592-024-02303-9

Cited by 6 publications

(1 citation statement)

References 98 publications

(178 reference statements)

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“…CellRank2 127 was used to establish the transition matrix based on diffusion pseudotime (DPT) 128 . The Cd33 + population of macrophages was selected as the starting point for the DPT analysis.…”

Section: Methodsmentioning

confidence: 99%

Cell of origin alters myeloid-mediated immunosuppression in lung adenocarcinoma

Yang,

Shulkin,

Gonzalez

et al. 2024

Preprint

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SUMMARYSolid carcinomas are often highly heterogenous cancers, arising from multiple epithelial cells of origin. Yet, how the cell of origin influences the response of the tumor microenvironment is poorly understood. Lung adenocarcinoma (LUAD) arises in the distal alveolar epithelium which is populated primarily by alveolar epithelial type I (AT1) and type II (AT2) cells. It has been previously reported thatGramd2+AT1 cells can give rise to a histologically-defined LUAD that is distinct in pathology and transcriptomic identity from that arising fromSftpc+AT2 cells1,2. To determine how cells of origin influence the tumor immune microenvironment (TIME) landscape, we comprehensively characterized transcriptomic, molecular, and cellular states within the TIME ofGramd2+AT1 andSftpc+AT2-derived LUAD using KRASG12Doncogenic driver mouse models. Myeloid cells within theGramd2+AT1-derived LUAD TIME were increased, specifically, immunoreactive monocytes and tumor associated macrophages (TAMs). In contrast, theSftpc+AT2 LUAD TIME was enriched for Arginase-1+myeloid derived suppressor cells (MDSC) and TAMs expressing profiles suggestive of immunosuppressive function. Validation of immune infiltration was performed using flow cytometry, and intercellular interaction analysis between the cells of origin and major myeloid cell populations indicated that cell-type specific markers SFTPD in AT2 cells and CAV1 in AT1 cells mediated unique interactions with myeloid cells of the differential immunosuppressive states within each cell of origin mouse model. Taken together,Gramd2+AT1-derived LUAD presents with an anti-tumor, immunoreactive TIME, while the TIME ofSftpc+AT2-derived LUAD has hallmarks of immunosuppression. This study suggests that LUAD cell of origin influences the composition and suppression status of the TIME landscape and may hold critical implications for patient response to immunotherapy.

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Section: Methodsmentioning

confidence: 99%

Cell of origin alters myeloid-mediated immunosuppression in lung adenocarcinoma

Yang,

Shulkin,

Gonzalez

et al. 2024

Preprint

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Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics

Gulati,

D’Silva,

Liu

et al. 2024

Nat Rev Mol Cell Biol

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An open-source framework for end-to-end analysis of electronic health record data

Heumos,

Ehmele,

Treis

et al. 2024

Nat Med

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With progressive digitalization of healthcare systems worldwide, large-scale collection of electronic health records (EHRs) has become commonplace. However, an extensible framework for comprehensive exploratory analysis that accounts for data heterogeneity is missing. Here we introduce ehrapy, a modular open-source Python framework designed for exploratory analysis of heterogeneous epidemiology and EHR data. ehrapy incorporates a series of analytical steps, from data extraction and quality control to the generation of low-dimensional representations. Complemented by rich statistical modules, ehrapy facilitates associating patients with disease states, differential comparison between patient clusters, survival analysis, trajectory inference, causal inference and more. Leveraging ontologies, ehrapy further enables data sharing and training EHR deep learning models, paving the way for foundational models in biomedical research. We demonstrate ehrapy’s features in six distinct examples. We applied ehrapy to stratify patients affected by unspecified pneumonia into finer-grained phenotypes. Furthermore, we reveal biomarkers for significant differences in survival among these groups. Additionally, we quantify medication-class effects of pneumonia medications on length of stay. We further leveraged ehrapy to analyze cardiovascular risks across different data modalities. We reconstructed disease state trajectories in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on imaging data. Finally, we conducted a case study to demonstrate how ehrapy can detect and mitigate biases in EHR data. ehrapy, thus, provides a framework that we envision will standardize analysis pipelines on EHR data and serve as a cornerstone for the community.

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CellRank 2: unified fate mapping in multiview single-cell data

Cited by 6 publications

References 98 publications

Cell of origin alters myeloid-mediated immunosuppression in lung adenocarcinoma

Cell of origin alters myeloid-mediated immunosuppression in lung adenocarcinoma

Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics

An open-source framework for end-to-end analysis of electronic health record data

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