bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2024–10–27
eight papers selected by
Xiao Qin, University of Oxford
  1. Mapping lineage-traced cells across time points with moslin.
  2. Single-cell multi-modal integrative analyses highlight functional dynamic gene regulatory networks directing human cardiac development.
  3. Patient-Derived Organoids: A Game-Changer in Personalized Cancer Medicine.
  4. Measuring multiple intracellular biochemical properties of proteins with next-generation sequencing.
  5. Key characteristics of carcinogens meet hallmarks for prevention-cutting the Gordian knot.
  6. Editorial: Hereditary colorectal cancer syndromes and risk assessment in the era of precision medicine.
  7. Spatial analysis by current multiplexed imaging technologies for the molecular characterisation of cancer tissues.
  8. On the identification of differentially-active transcription factors from ATAC-seq data.
  1. Genome Biol. 2024 Oct 21. 25(1): 277
    Mapping lineage-traced cells across time points with moslin.
    Marius Lange, Zoe Piran, Michal Klein, Bastiaan Spanjaard, Dominik Klein, Jan Philipp Junker, Fabian J Theis, Mor Nitzan.
      Simultaneous profiling of single-cell gene expression and lineage history holds enormous potential for studying cellular decision-making. Recent computational approaches combine both modalities into cellular trajectories; however, they cannot make use of all available lineage information in destructive time-series experiments. Here, we present moslin, a Gromov-Wasserstein-based model to couple cellular profiles across time points based on lineage and gene expression information. We validate our approach in simulations and demonstrate on Caenorhabditis elegans embryonic development how moslin predicts fate probabilities and putative decision driver genes. Finally, we use moslin to delineate lineage relationships among transiently activated fibroblast states during zebrafish heart regeneration.
    Keywords:  Cellular dynamics; Fate decisions; Lineage tracing; Optimal transport; Regeneration
    DOI:  https://doi.org/10.1186/s13059-024-03422-4
  2. Cell Genom. 2024 Oct 16. pii: S2666-979X(24)00299-4. [Epub ahead of print] 100680
    Single-cell multi-modal integrative analyses highlight functional dynamic gene regulatory networks directing human cardiac development.
    Alyssa R Holman, Shaina Tran, Eugin Destici, Elie N Farah, Ting Li, Aileena C Nelson, Adam J Engler, Neil C Chi.
      Illuminating the precise stepwise genetic programs directing cardiac development provides insights into the mechanisms of congenital heart disease and strategies for cardiac regenerative therapies. Here, we integrate in vitro and in vivo human single-cell multi-omic studies with high-throughput functional genomic screening to reveal dynamic, cardiac-specific gene regulatory networks (GRNs) and transcriptional regulators during human cardiomyocyte development. Interrogating developmental trajectories reconstructed from single-cell data unexpectedly reveal divergent cardiomyocyte lineages with distinct gene programs based on developmental signaling pathways. High-throughput functional genomic screens identify key transcription factors from inferred GRNs that are functionally relevant for cardiomyocyte lineages derived from each pathway. Notably, we discover a critical heat shock transcription factor 1 (HSF1)-mediated cardiometabolic GRN controlling cardiac mitochondrial/metabolic function and cell survival, also observed in fetal human cardiomyocytes. Overall, these multi-modal genomic studies enable the systematic discovery and validation of coordinated GRNs and transcriptional regulators controlling the development of distinct human cardiomyocyte populations.
    Keywords:  CRISPR-based functional genomics screening; cardiac development; directed differentiation; gene regulatory networks; multi-omics
    DOI:  https://doi.org/10.1016/j.xgen.2024.100680
  3. Stem Cell Rev Rep. 2024 Oct 21.
    Patient-Derived Organoids: A Game-Changer in Personalized Cancer Medicine.
    Mohammad Hadi Abbasian, Navid Sobhani, Mahsa Mollapour Sisakht, Alberto D'Angelo, Marianna Sirico, Raheleh Roudi.
      Research on cancer therapies has benefited from predictive tools capable of simulating treatment response and other disease characteristics in a personalized manner, in particular three-dimensional cell culture models. Such models include tumor-derived spheroids, multicellular spheroids including organotypic multicellular spheroids, and tumor-derived organoids. Additionally, organoids can be grown from various cancer cell types, such as pluripotent stem cells and induced pluripotent stem cells, progenitor cells, and adult stem cells. Although patient-derived xenografts and genetically engineered mouse models replicate human disease in vivo, organoids are less expensive, less labor intensive, and less time-consuming, all-important aspects in high-throughput settings. Like in vivo models, organoids mimic the three-dimensional structure, cellular heterogeneity, and functions of primary tissues, with the advantage of representing the normal oxygen conditions of patient organs. In this review, we summarize the use of organoids in disease modeling, drug discovery, toxicity testing, and precision oncology. We also summarize the current clinical trials using organoids.
    Keywords:  Adult stem cells; Embryonic stem cells; Personalized cancer medicine; Pluripotent stem cells; Tumor-derived organoids
    DOI:  https://doi.org/10.1007/s12015-024-10805-4
  4. Nat Methods. 2024 Oct 21.
    Measuring multiple intracellular biochemical properties of proteins with next-generation sequencing.
      
    DOI:  https://doi.org/10.1038/s41592-024-02461-w
  5. Front Oncol. 2024 ;14 1420687
    Key characteristics of carcinogens meet hallmarks for prevention-cutting the Gordian knot.
    Sasi S Senga, William H Bisson, Annamaria Colacci.
      The complexity of cancer requires a comprehensive approach to understand its diverse manifestations and underlying mechanisms. Initially outlined by Hanahan and Weinberg in 2000 and updated in 2010, the hallmarks of cancer provide a conceptual basis for understanding inherent variability in cancer biology. Recent expansions have further elucidated additional hallmarks, including phenotypic plasticity and senescent cells. The International Agency for Research on Cancer (IARC) has identified the key characteristics of carcinogens (KCCs) to evaluate their carcinogenic potential. We analyzed chemicals of concern for environmental exposure that interact with specific receptors to induce genomic instability, epigenetic alterations, immune suppression, and receptor-mediated effects, thereby contributing to chronic inflammation. Despite their varying degrees of carcinogenicity, these chemicals have similar KCC profiles. Our analysis highlights the pivotal role of receptor binding in activating most other KCCs, underscoring their significance in cancer initiation. Although KCCs are associated with early molecular or cellular events, they do not encompass processes directly linked to full cellular malignancy. Thus, there is a need to integrate clear endpoints that anchor KCCs to the acquisition of a complete malignant phenotype into chemical testing. From the perspective of toxicology and cancer research, an all-encompassing strategy that incorporates both existing and novel KCCs and cancer hallmarks is essential to enable the targeted identification of prevalent carcinogens and facilitate zone-specific prevention strategies. To achieve this goal, collaboration between the KCC and cancer hallmarks communities becomes essential.
    Keywords:  KCCs; cancer hallmarks; cancer process; chemical carcinogens; environmental exposure; key carcinogens characteristics; precise toxicology; regulatory toxicology
    DOI:  https://doi.org/10.3389/fonc.2024.1420687
  6. Front Oncol. 2024 ;14 1474157
    Editorial: Hereditary colorectal cancer syndromes and risk assessment in the era of precision medicine.
    Kevin McDonnell, Gad Rennert, Gregory E Idos.
      
    Keywords:  chemoprevention; colorectal cancer; genetic testing; hereditary; precision medicine
    DOI:  https://doi.org/10.3389/fonc.2024.1474157
  7. Br J Cancer. 2024 Oct 22.
    Spatial analysis by current multiplexed imaging technologies for the molecular characterisation of cancer tissues.
    Takashi Semba, Takatsugu Ishimoto.
      Tumours are composed of tumour cells and the surrounding tumour microenvironment (TME), and the molecular characterisation of the various elements of the TME and their interactions is essential for elucidating the mechanisms of tumour progression and developing better therapeutic strategies. Multiplex imaging is a technique that can quantify the expression of multiple protein markers on the same tissue section while maintaining spatial positioning, and this method has been rapidly developed in cancer research in recent years. Many multiplex imaging technologies and spatial analysis methods are emerging, and the elucidation of their principles and features is essential. In this review, we provide an overview of the latest multiplex imaging techniques by type of imaging and staining method and an introduction to image analysis methods, primarily focusing on spatial cellular properties, providing deeper insight into tumour organisation and spatial molecular biology in the TME.
    DOI:  https://doi.org/10.1038/s41416-024-02882-6
  8. PLoS Comput Biol. 2024 Oct 23. 20(10): e1011971
    On the identification of differentially-active transcription factors from ATAC-seq data.
    Felix Ezequiel Gerbaldo, Emanuel Sonder, Vincent Fischer, Selina Frei, Jiayi Wang, Katharina Gapp, Mark D Robinson, Pierre-Luc Germain.
      ATAC-seq has emerged as a rich epigenome profiling technique, and is commonly used to identify Transcription Factors (TFs) underlying given phenomena. A number of methods can be used to identify differentially-active TFs through the accessibility of their DNA-binding motif, however little is known on the best approaches for doing so. Here we benchmark several such methods using a combination of curated datasets with various forms of short-term perturbations on known TFs, as well as semi-simulations. We include both methods specifically designed for this type of data as well as some that can be repurposed for it. We also investigate variations to these methods, and identify three particularly promising approaches (a chromVAR-limma workflow with critical adjustments, monaLisa and a combination of GC smooth quantile normalization and multivariate modeling). We further investigate the specific use of nucleosome-free fragments, the combination of top methods, and the impact of technical variation. Finally, we illustrate the use of the top methods on a novel dataset to characterize the impact on DNA accessibility of TRAnscription Factor TArgeting Chimeras (TRAFTAC), which can deplete TFs-in our case NFkB-at the protein level.
    DOI:  https://doi.org/10.1371/journal.pcbi.1011971
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