bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2026–01–04
ten papers selected by
Xiao Qin, University of Oxford
  1. Spatial omics at the forefront: emerging technologies, analytical innovations, and clinical applications.
  2. Pertpy: an end-to-end framework for perturbation analysis.
  3. Let the data speak - single-cell analysis with CellWhisperer.
  4. Interpretation, extrapolation and perturbation of single cells.
  5. ApCAFs: spatial niches and therapeutic insights across cancers.
  6. Quantifying host-microbe interactions with bacterial lineage tracing.
  7. Science in 2026: what to expect this year.
  8. Cancer cell death: Cell-autonomous and immunogenic dimensions.
  9. FOCAS: Transcriptome-wide screening of individual m6A sites functionally dissects epitranscriptomic control of gene expression in cancer.
  10. Developing New Immunotherapy Approaches for Colorectal Cancer.
  1. Cancer Cell. 2025 Dec 31. pii: S1535-6108(25)00543-4. [Epub ahead of print]
    Spatial omics at the forefront: emerging technologies, analytical innovations, and clinical applications.
    Yunhe Liu, Yibo Dai, Linghua Wang.
      Spatial omics transforms our understanding of cancer by revealing how tumor cells and the microenvironment are organized, interact, and evolve within tissues. Here, we synthesize advances in spatial technologies that map tumor ecosystems with unprecedented fidelity. We highlighted analytical breakthroughs-including multimodal integration and emerging spatial foundation models-that resolve functional niches and spatial communities, converting spatial patterns into mechanistic insights. We summarize how spatially organized features, from immune hubs to microbiota and neural interfaces, shape tumor evolution and clinical outcomes. We then outline how spatial approaches illuminate precancer biology, metastatic adaptation, and therapy response. Bridging discovery and translation, we provide a practical roadmap for incorporating spatial readouts into clinically oriented study design. We conclude by discussing persistent challenges in standardization and scalability and how high-plex spatial discoveries may be distilled into scalable, AI-enabled, clinically deployable assays, positioning spatial omics as a cornerstone of next-generation predictive and precision oncology.
    Keywords:  AI; ML; TME; artificial intelligence; cell-cell interaction; cellular neighborhood; computational pathology; machine learning; molecular imaging; multi-omics; multimodal data integration; proteomics; spatial biomarkers; spatial heterogeneity; spatial niche; spatial omics; transcriptomics; tumor microenvironment
    DOI:  https://doi.org/10.1016/j.ccell.2025.12.009
  2. Nat Methods. 2025 Dec 31.
    Pertpy: an end-to-end framework for perturbation analysis.
    Lukas Heumos, Yuge Ji, Lilly May, Tessa D Green, Stefan Peidli, Xinyue Zhang, Xichen Wu, Johannes Ostner, Antonia Schumacher, Karin Hrovatin, Michaela Müller, Faye Chong, Gregor Sturm, Alejandro Tejada, Emma Dann, Mingze Dong, Gonçalo Pinto, Mojtaba Bahrami, Ilan Gold, Sergei Rybakov, Altana Namsaraeva, Amir Ali Moinfar, Zihe Zheng, Eljas Roellin, Isra Mekki, Chris Sander, Mohammad Lotfollahi, Herbert B Schiller, Fabian J Theis.
      Advances in single-cell technology have enabled the measurement of cell-resolved molecular states across a variety of cell lines and tissues under a plethora of genetic, chemical, environmental or disease perturbations. Current methods focus on differential comparison or are specific to a particular task in a multi-condition setting with purely statistical perspectives. The quickly growing number, size and complexity of such studies require a scalable analysis framework that takes existing biological context into account. Here we present pertpy, a Python-based modular framework for the analysis of large-scale single-cell perturbation experiments. Pertpy provides access to harmonized perturbation datasets and metadata databases along with numerous fast and user-friendly implementations of both established and novel methods, such as automatic metadata annotation or perturbation distances, to efficiently analyze perturbation data. As part of the scverse ecosystem, pertpy interoperates with existing single-cell analysis libraries and is designed to be easily extended.
    DOI:  https://doi.org/10.1038/s41592-025-02909-7
  3. Nat Rev Genet. 2026 Jan 02.
    Let the data speak - single-cell analysis with CellWhisperer.
    Moritz Schaefer.
      
    DOI:  https://doi.org/10.1038/s41576-025-00927-x
  4. Nat Rev Genet. 2026 Jan 02.
    Interpretation, extrapolation and perturbation of single cells.
    Daniel Dimitrov, Stefan Schrod, Martin Rohbeck, Oliver Stegle.
      Single-cell analyses have transitioned from descriptive atlasing towards inferring causal effects and mechanistic relationships that capture cellular logic. Technological advances and the growing scale of observational and interventional datasets have fuelled the development of machine learning methods aimed at identifying such dependencies and extrapolating perturbation effects. Here, we review and connect these approaches according to their modelling concepts (including representation learning, causal inference, mechanistic discovery, disentanglement and population tracing), underlying assumptions and downstream tasks. We propose a unifying ontology to guide practitioners in selecting the most suitable methods for a given biological question, with detailed technical descriptions provided in an online resource . Finally, we identify promising computational directions and underexplored data properties that could pave the way for future developments.
    DOI:  https://doi.org/10.1038/s41576-025-00920-4
  5. Trends Cancer. 2025 Dec 30. pii: S2405-8033(25)00312-7. [Epub ahead of print]
    ApCAFs: spatial niches and therapeutic insights across cancers.
    Wenlong Li, Gideon Nsubuga, Giulia Biffi.
      Although interest in antigen-presenting cancer-associated fibroblasts (apCAFs) is increasing, their therapeutic potential remains poorly understood. In a recent study, Chen et al. reveal two osteopontin-expressing apCAF populations present across malignancies and distinct in origin and location: mesothelial-like (M-)apCAFs, which are found near cancer cells, and fibrocyte-like (F-)apCAFs, which associate with lymphocyte-enriched niches.
    Keywords:  Antigen-presenting cancer-associated fibroblasts; fibrocytes; mesothelial cells; spatial niches
    DOI:  https://doi.org/10.1016/j.trecan.2025.12.005
  6. Science. 2026 Jan;391(6780): 34-40
    Quantifying host-microbe interactions with bacterial lineage tracing.
    Ian W Campbell, Karthik Hullahalli, Matthew K Waldor.
      Using genomic barcodes to trace bacterial lineages within a host reveals previously unobservable dynamics of infection, including the impact of infection bottlenecks, routes of bacterial dissemination, and patterns of within-host evolution. Barcoding introduces trackable diversity to otherwise isogenic bacterial populations. Comparing the barcodes within an inoculum to those within the host quantifies the "founding population," which reveals the magnitude of population collapse caused by host bottlenecks. Furthermore, comparisons of the founders between tissues can reveal the patterns of pathogen dissemination. On longer timescales, the emergence of dominant barcoded lineages can also be used to detect within-host evolution. Collectively, barcoding studies quantify the hidden parameters that underlie bacterial colonization and create a quantitative framework for modeling and preventing infectious disease.
    DOI:  https://doi.org/10.1126/science.adx5362
  7. Nature. 2026 Jan 01.
    Science in 2026: what to expect this year.
    Nick Petrić Howe, Miryam Naddaf.
      
    Keywords:  Astronomy and astrophysics; Gene therapy; Machine learning; Policy
    DOI:  https://doi.org/10.1038/d41586-025-04114-0
  8. Cancer Cell. 2025 Dec 31. pii: S1535-6108(25)00539-2. [Epub ahead of print]
    Cancer cell death: Cell-autonomous and immunogenic dimensions.
    Lorenzo Galluzzi, Oliver Kepp, Laurence Zitvogel, Daolin Tang, Guido Kroemer.
      Regulated cell death (RCD) shapes neoplastic transformation, tumor progression, and response to treatment. While apoptosis was long viewed as the only RCD variant, additional modalities, including necroptosis, pyroptosis, and ferroptosis, have been characterized. These interconnected pathways operate in a context-dependent manner to influence the dynamic interplay between malignant and non-malignant cells that governs disease progression or regression, both naturally and during therapy. Major advances stemmed from recognizing immunogenic cell death (ICD) as an RCD type defined by the emission of immunomodulatory damage-associated molecular patterns (DAMPs) from dying cancer cells. The balance between immunostimulatory and immunosuppressive DAMPs dictates whether neoplastic cells undergoing RCD effectively activate adaptive immunity. Thus, ICD provides mechanistic grounds for the durable efficacy of certain cancer therapeutics, and underpins their synergy with immune checkpoint inhibitors. Understanding the molecular determinants of RCD and ICD is reshaping oncology, allowing for an increasingly refined integration between cytotoxicity and durable anticancer immune responses.
    Keywords:  PD-1; STING; autophagy; cellular senescence; persister cells; type I interferon
    DOI:  https://doi.org/10.1016/j.ccell.2025.12.005
  9. Cell. 2025 Dec 31. pii: S0092-8674(25)01372-8. [Epub ahead of print]
    FOCAS: Transcriptome-wide screening of individual m6A sites functionally dissects epitranscriptomic control of gene expression in cancer.
    Xinning Zhang, Yifan Zhang, Xinyu Liu, Chang Liu, Ying Liu, Yuan He, Yuhang Qiu, Lida Sun, Jing Hu, Yawei Gao, Wensheng Wei, Jun Liu.
      Although N6-methyladenosine (m6A) is a pervasive RNA modification essential for gene regulation, dissecting the functions of individual m6A sites remains technically challenging. To overcome this, we developed functional m6A sites detection by CRISPR-dCas13b-FTO screening (FOCAS), a CRISPR-dCas13b-based platform enabling high-throughput, site-specific functional screening of m6A. Applying FOCAS to four human cancer cell lines identified 4,475 m6A-regulated genes influencing cell fitness via both mRNAs and non-coding RNAs (ncRNAs), many of which are newly linked to cancer and exhibit dynamic developmental expression. FOCAS uncovered context-dependent and reader-specific effects of m6A within the same gene, revealing its intricate regulatory logic. We further uncovered universal and cell-type-specific m6A patterns, with unique sites enriched in ncRNAs and universal ones in transcription-related genes. In SMMC-7721 cells, we identified m6A-regulated transcriptional networks that demonstrated extensive epitranscriptome-transcriptome crosstalk. Overall, this study established a powerful, unbiased approach for the functional dissection of m6A, advancing the understanding of its complexity and therapeutic relevance in cancers.
    Keywords:  FOCAS; RNA m(6)A modification; cell fitness; transcriptional-related network; universal and unique FiGenes
    DOI:  https://doi.org/10.1016/j.cell.2025.11.037
  10. Cancers (Basel). 2025 Dec 09. pii: 3929. [Epub ahead of print]17(24):
    Developing New Immunotherapy Approaches for Colorectal Cancer.
    Gregory Kelly, Bianca Nowlan, Simon Manuel Tria, Afshin Nikkhoo, Catherine Bond, Vicki Whitehall.
      Immunotherapy represents a groundbreaking approach for treating colorectal cancer (CRC), harnessing the body's own immune system to target tumour cells more precisely than conventional chemotherapy. Immune checkpoint inhibitors, such as antibodies against PD-1, PD-L1, or CTLA-4, have shown remarkable efficacy in certain patients, leading to durable responses and improved survival. However, the majority of CRC cases have limited benefit from a single agent checkpoint blockade. There is a growing need to identify biomarkers that will improve the selection of patients who will best respond to therapy, as well as new targets to sensitise cancers to an immune checkpoint blockade. Unfortunately, the search for reliable biomarkers has been limited by our incomplete understanding of how immunotherapies modify the already complex immune response to cancer. Revolutionary techniques, such as genome-wide CRISPR/Cas9 screening combined with the appropriate validation systems such as in vivo mouse models and/or 3D organoid co-culture systems, are being used to address this knowledge gap. This review will focus on the use of immunotherapies in CRC, discuss why most CRC patients do not respond, and highlight in vitro, in vivo, and novel techniques for discovery of new targets for combination treatment.
    Keywords:  CRISPR/Cas9 screens; co-culture models; colorectal cancer; immunotherapy; in vivo models; organoids
    DOI:  https://doi.org/10.3390/cancers17243929
This page is being maintained by Thomas Krichel. It was last updated on 2026‒01‒04 at 14:45.