bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2024–12–22
fifteen papers selected by
Xiao Qin, University of Oxford
  1. Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome.
  2. Mini colons to study cancer ex vivo.
  3. Beyond the hype of AI in cancer R&D.
  4. Toward clinical applications of spatial-omics in cancer research.
  5. GraphVelo allows inference of multi-modal single cell velocities and molecular mechanisms.
  6. Molecular glue-based RAS-MAPK targeting.
  7. How AI agents will change cancer research and oncology.
  8. Endosomal pH is an evolutionarily conserved driver of phenotypic plasticity in colorectal cancer.
  9. CRISPR-StAR enables high-resolution genetic screening in complex in vivo models.
  10. Closing Editorial: Colorectal Cancer-A Molecular Genetics Perspective.
  11. Latent spaces for tumour transcriptomes.
  12. Systems Biology of the Cancer Cell.
  13. Multiplexing strategies to scale up brain organoid modeling.
  14. Deep profiling of gene expression across 18 human cancers.
  15. Functional heterogeneity of fibroblasts in primary tumors and metastases.
  1. Cell Syst. 2024 Dec 14. pii: S2405-4712(24)00366-1. [Epub ahead of print]
    Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome.
    Eli Metzner, Kaden M Southard, Thomas M Norman.
      Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here, we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Modeling of perturbation-induced heterogeneity connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  CRISPRi; Perturb-seq; chromatin accessibility; functional genomics; gene regulatory networks; multiome; single-cell genomics
    DOI:  https://doi.org/10.1016/j.cels.2024.12.002
  2. Nat Cancer. 2024 Dec 17.
    Mini colons to study cancer ex vivo.
    Ioanna Pavlaki.
      
    DOI:  https://doi.org/10.1038/s43018-024-00832-y
  3. Nat Cancer. 2024 Dec 17.
    Beyond the hype of AI in cancer R&D.
    Melanie Senior.
      
    DOI:  https://doi.org/10.1038/s43018-024-00857-3
  4. Nat Cancer. 2024 Dec 17.
    Toward clinical applications of spatial-omics in cancer research.
    Cameron Walker, Michael Angelo.
      
    DOI:  https://doi.org/10.1038/s43018-024-00868-0
  5. bioRxiv. 2024 Dec 07. pii: 2024.12.03.626638. [Epub ahead of print]
    GraphVelo allows inference of multi-modal single cell velocities and molecular mechanisms.
    Yuhao Chen, Yan Zhang, Jiaqi Gan, Ke Ni, Ming Chen, Ivet Bahar, Jianhua Xing.
      RNA velocities and generalizations emerge as powerful approaches for exacting dynamical information from high-throughput snapshot single-cell data. Several inherent limitations restrict applying the approaches to genes not suitable for RNA velocity inference due to complex transcriptional dynamics, low expression, or lacking splicing dynamics, and data of non-transcriptomic modality. Here, we present GraphVelo, a graph-based machine learning procedure that uses RNA velocities inferred from existing methods as input and infer velocity vectors lie in the tangent space of the low-dimensional manifold formed by the single cell data. GraphVelo preserves vector magnitude and direction information during transformations across different data representations. Tests on multiple synthetic and experimental scRNA-seq data, as well as multi-omics datasets demonstrate that GraphVelo, together with downstream Dynamo analyses, extends RNA velocities to multi-modal data and reveals quantitative nonlinear regulation relations between genes, different layers of gene regulation, and between virus and host cells.
    DOI:  https://doi.org/10.1101/2024.12.03.626638
  6. Nat Cancer. 2024 Dec 17.
    Molecular glue-based RAS-MAPK targeting.
    Eleni Skourti.
      
    DOI:  https://doi.org/10.1038/s43018-024-00835-9
  7. Nat Cancer. 2024 Dec 17.
    How AI agents will change cancer research and oncology.
    Yongju Lee, Dyke Ferber, Jennifer E Rood, Aviv Regev, Jakob Nikolas Kather.
      
    DOI:  https://doi.org/10.1038/s43018-024-00861-7
  8. NPJ Syst Biol Appl. 2024 Dec 19. 10(1): 149
    Endosomal pH is an evolutionarily conserved driver of phenotypic plasticity in colorectal cancer.
    Hari Prasad, Harshavardhan Bv, Ayalur Raghu Subbalakshmi, Susmita Mandal, Mohit Kumar Jolly, Sandhya S Visweswariah.
      Dysregulated pH is now recognised as a hallmark of cancer. Recent evidence has revealed that the endosomal pH regulator Na+/H+ exchanger NHE9 is upregulated in colorectal cancer to impose a pseudo-starvation state associated with invasion, highlighting an underexplored mechanistic link between adaptive endosomal reprogramming and malignant transformation. In this study, we use a model that quantitatively captures the dynamics of the core regulatory network governing epithelial mesenchymal plasticity. The model recapitulated NHE9-induced calcium signalling and the emergence of migratory phenotypes in colorectal cancer cells. Model predictions were compared with patient data and experimental results from RNA sequencing analysis of colorectal cancer cells with stable NHE9 expression. Mathematical analyses identified that tumours leverage elevated NHE9 levels to delay the transition of cells to a mesenchymal state and allow for metastatic progression. Ectopic expression of NHE9 is sufficient to induce loss of epithelial nature but does not fully couple with gain of mesenchymal state, resulting in a hybrid epithelial-mesenchymal population with increased aggressiveness and metastatic competence. Higher NHE9 expression is associated with cancer cell migration, and the effect appears to be independent of hypoxia status. Our data suggests that alterations in endosomal pH, an evolutionarily conserved starvation response, may be hijacked by colorectal cancer cells to drive phenotypic plasticity and invasion. We propose that cancer cells rewire their endosomal pH not only to meet the demands of rapid cell proliferation, but also to enable invasion, metastasis, and cell survival. Endosomal pH may be an attractive therapeutic target for halting tumour progression.
    DOI:  https://doi.org/10.1038/s41540-024-00463-0
  9. Nat Biotechnol. 2024 Dec 16.
    CRISPR-StAR enables high-resolution genetic screening in complex in vivo models.
    Esther C H Uijttewaal, Joonsun Lee, Annika Charlotte Sell, Naomi Botay, Gintautas Vainorius, Maria Novatchkova, Juliane Baar, Jiaye Yang, Tobias Potzler, Sophie van der Leij, Christopher Lowden, Julia Sinner, Anais Elewaut, Milanka Gavrilovic, Anna Obenauf, Daniel Schramek, Ulrich Elling.
      Pooled genetic screening with CRISPR-Cas9 has enabled genome-wide, high-resolution mapping of genes to phenotypes, but assessing the effect of a given genetic perturbation requires evaluation of each single guide RNA (sgRNA) in hundreds of cells to counter stochastic genetic drift and obtain robust results. However, resolution is limited in complex, heterogeneous models, such as organoids or tumors transplanted into mice, because achieving sufficient representation requires impractical scaling. This is due to bottleneck effects and biological heterogeneity of cell populations. Here we introduce CRISPR-StAR, a screening method that uses internal controls generated by activating sgRNAs in only half the progeny of each cell subsequent to re-expansion of the cell clone. Our method overcomes both intrinsic and extrinsic heterogeneity as well as genetic drift in bottlenecks by generating clonal, single-cell-derived intrinsic controls. We use CRISPR-StAR to identify in-vivo-specific genetic dependencies in a genome-wide screen in mouse melanoma. Benchmarking against conventional screening demonstrates the improved data quality provided by this technology.
    DOI:  https://doi.org/10.1038/s41587-024-02512-9
  10. Int J Mol Sci. 2024 Nov 24. pii: 12604. [Epub ahead of print]25(23):
    Closing Editorial: Colorectal Cancer-A Molecular Genetics Perspective.
    Ehsan Gharib.
      Colorectal cancer (CRC) remains a significant global health challenge, ranking third in incidence and second in mortality among all cancers [...].
    DOI:  https://doi.org/10.3390/ijms252312604
  11. Nat Biomed Eng. 2024 Dec 17.
    Latent spaces for tumour transcriptomes.
    Adriana Ivich, Casey S Greene.
      
    DOI:  https://doi.org/10.1038/s41551-024-01322-3
  12. Annu Rev Biomed Eng. 2024 Dec 17.
    Systems Biology of the Cancer Cell.
    Kevin A Janes, Matthew J Lazzara.
      Questions in cancer have engaged systems biologists for decades. During that time, the quantity of molecular data has exploded, but the need for abstractions, formal models, and simplifying insights has remained the same. This review brings together classic breakthroughs and recent findings in the field of cancer systems biology, focusing on cancer-cell pathways for tumorigenesis and therapeutic response. Cancer cells mutate and transduce information from their environment to alter gene expression, metabolism, and phenotypic states. Understanding the molecular architectures that make each of these steps possible is a long-term goal of cancer systems biology pursued by iterating between quantitative models and experiments. We argue that such iteration is the best path to deploying targeted therapies intelligently so that each patient receives the maximum benefit for their cancer.
    DOI:  https://doi.org/10.1146/annurev-bioeng-103122-030552
  13. Nat Methods. 2024 Dec 18.
    Multiplexing strategies to scale up brain organoid modeling.
      
    DOI:  https://doi.org/10.1038/s41592-024-02556-4
  14. Nat Biomed Eng. 2024 Dec 17.
    Deep profiling of gene expression across 18 human cancers.
    Wei Qiu, Ayse B Dincer, Joseph D Janizek, Safiye Celik, Mikael J Pittet, Kamila Naxerova, Su-In Lee.
      Clinical and biological information in large datasets of gene expression across cancers could be tapped with unsupervised deep learning. However, difficulties associated with biological interpretability and methodological robustness have made this impractical. Here we describe an unsupervised deep-learning framework for the generation of low-dimensional latent spaces for gene-expression data from 50,211 transcriptomes across 18 human cancers. The framework, which we named DeepProfile, outperformed dimensionality-reduction methods with respect to biological interpretability and allowed us to unveil that genes that are universally important in defining latent spaces across cancer types control immune cell activation, whereas cancer-type-specific genes and pathways define molecular disease subtypes. By linking latent variables in DeepProfile to secondary characteristics of tumours, we discovered that mutation burden is closely associated with the expression of cell-cycle-related genes, and that the activity of biological pathways for DNA-mismatch repair and MHC class II antigen presentation are consistently associated with patient survival. We also found that tumour-associated macrophages are a source of survival-correlated MHC class II transcripts. Unsupervised learning can facilitate the discovery of biological insight from gene-expression data.
    DOI:  https://doi.org/10.1038/s41551-024-01290-8
  15. Trends Cancer. 2024 Dec 13. pii: S2405-8033(24)00260-7. [Epub ahead of print]
    Functional heterogeneity of fibroblasts in primary tumors and metastases.
    Priscilla S W Cheng, Marta Zaccaria, Giulia Biffi.
      Cancer-associated fibroblasts (CAFs) are abundant components of the tumor microenvironment (TME) of most solid malignancies and have emerged as key regulators of cancer progression and therapy response. Although recent technological advances have uncovered substantial CAF molecular heterogeneity at the single-cell level, defining functional roles for most described CAF populations remains challenging. With the aim of bridging CAF molecular and functional heterogeneity, this review focuses on recently identified functional interactions of CAF subtypes with malignant cells, immune cells, and other stromal cells in primary tumors and metastases. Dissecting the heterogeneous functional crosstalk of specific CAF populations with other components is starting to uncover candidate combinatorial strategies for therapeutically targeting the TME and cancer progression.
    Keywords:  cancer-associated fibroblasts; fibroblast heterogeneity; metastases; primary tumors; tumor microenvironment
    DOI:  https://doi.org/10.1016/j.trecan.2024.11.005
This page is being maintained by Thomas Krichel. It was last updated on 2024‒12‒23 at 14:28.