bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2026–08–23
sixteen papers selected by
Xiao Qin, University of Oxford



  1. Cell Syst. 2026 Aug 17. pii: S2405-4712(26)00185-7. [Epub ahead of print] 101703
      Cell-cell communication modulates cell fate decisions by relaying information across tissues and inducing intracellular responses mediated by gene regulatory networks. Although the inference of cell-cell communication from high-throughput data is gaining popularity, studying how communication pathways operate across biological scales and influence cell fate decisions remains challenging. Here, we present scRICH (robust identification of cell-cell communication heterogeneity in single cells), a computational framework that leverages single-cell and spatial transcriptomics data to unravel the heterogeneity of communication behavior within cell types, link cell-cell communication to cell fate decisions by incorporating dynamical information on RNA splicing, and connect cell-cell interactions with intracellular responses by constructing multilayer regulatory networks. We validate scRICH with new experiments on epidermal growth factor (EGF) ligand/receptor co-expression in keratinocytes, comparing these predictions against those of existing communication inference methods. Applying scRICH to multiple biological scenarios demonstrates its ability to capture relationships between distinct communication pathways and emerging trends along cell differentiation lineages and in space. A record of this paper's transparent peer review process is included in the supplemental information.
    Keywords:  cell-cell communication; gene regulatory network; multiscale; phenotype heterogeneity; single-cell RNA sequencing
    DOI:  https://doi.org/10.1016/j.cels.2026.101703
  2. Mol Syst Biol. 2026 Aug 17.
      Transcription factors (TFs) are central to gene regulation and play critical roles in development, cellular homeostasis and disease. The ability to accurately measure TF activity is essential to understanding how TFs respond to signals and regulate target genes. In one commonly used approach, activities of TFs are computationally inferred from genome-wide chromatin accessibility data (ATAC-seq). However, it has remained unclear how well these inferences reflect actual regulatory activity of TFs. An alternative approach employs a collection of synthetic reporters that are designed to each probe the regulatory activity of a single TF. In this study, we systematically compared TF activities as inferred by ATAC-seq with those measured by multiplexed reporters, across diverse perturbations known to alter specific TF activities. We observed considerable overlap between the two methods, but also notable discrepancies. Our findings suggest that reporter assays and chromatin-based inference capture distinct aspects of TF function: reporter assays are more sensitive to signal-responsive TFs, while ATAC-seq better detects chromatin-modifying TFs.
    DOI:  https://doi.org/10.1038/s44320-026-00240-7
  3. Trends Cancer. 2026 Aug 21. pii: S2405-8033(26)00165-2. [Epub ahead of print]
      Tumors represent a heterogeneous set of neoplastic diseases, each composed of an intricate network of cancer cells residing in multiple alternative phenotypic states. Transitions between these phenotypic states, often termed 'phenotypic plasticity', enable them to execute specific steps in tumor progression and to develop therapeutic resistance. The phenotypic plasticity of tumor cells is mediated, in part, by cellular processes that orchestrate normal embryonic development and are hijacked by tumors. In this review, we discuss the contributions of these developmental programs to cancer cell phenotypic plasticity. We focus on epithelial-mesenchymal transition and ciliogenesis programs and discuss new insights into the mechanistic roles of these cellular processes in cancer progression and response to treatment.
    Keywords:  cancer cell plasticity; ciliogenesis; epithelial–mesenchymal transition; intratumor heterogeneity
    DOI:  https://doi.org/10.1016/j.trecan.2026.07.009
  4. bioRxiv. 2026 Aug 07. pii: 2026.08.06.743310. [Epub ahead of print]
      Colorectal cancer develops through a normal-adenoma-carcinoma sequence, yet only 5-10% of adenomas progress to malignancy, and the cellular programs governing that sequence remain poorly defined. Here we generate a spatial multi-omics atlas of human colon adenomas, combining Visium CytAssist and protein co-detection across 24 nonadvanced and advanced tubular adenomas with single-cell resolution Xenium Prime 5K profiling of 101 patient-matched normal, adenoma, and carcinoma cores from 16 patients. Integrating whole-transcriptome and 31-plex protein data identifies nine spatial clusters and two dysplastic epithelial populations that co-express stemness, proliferation, and senescence programs. These programs occupy a shared, spatially confined epithelial niche that expands from adenoma to carcinoma. Spatial analysis revealed GDF15, a senescence-associated secretory factor, mediated the coupling between senescence and stemness in advanced adenomas, and that GDF15-high epithelium locally excludes CD8+ T cells in adenoma and, more broadly, in carcinoma. These findings position senescence as a spatially instructive rather than merely tumor-suppressive program during colorectal carcinogenesis and suggest GDF15 might be a potential candidate target for cancer prevention and interception in the colon.
    DOI:  https://doi.org/10.64898/2026.08.06.743310
  5. Cell. 2026 Aug 17. pii: S0092-8674(26)00802-0. [Epub ahead of print]
      Generative AI (Gen-AI) has shown a remarkable impact in several biological research areas, from protein folding and de novo design to pathogenic mutation prediction. However, it remains unclear whether these molecular-level successes can translate to cellular and multicellular insights relevant to fields ranging from immunology to cancer and neurodegeneration. This arises from the intricate nature of the molecular mechanisms that determine cellular and organismal behavior, the lack of sufficient training data, and the multicellular nature of most pathophysiologic phenotypes. Novel Gen-AI frameworks are likely needed to integrate prior biological knowledge, such as molecular interaction networks, as well as guiding principles focusing the community's attention on solving biologically and translationally relevant problems. Drawing inspiration from Hilbert's list of 23 mathematical problems that have focused the mathematical community's attention for more than a century, we propose fifteen grand AI challenges to focus the biomedical community's attention on critically relevant questions, most of which still lack effective predictive methodologies.
    Keywords:  generative AI; large language models; predictive biology; systems biology; systems immunology
    DOI:  https://doi.org/10.1016/j.cell.2026.07.004
  6. Curr Oncol Rep. 2026 Aug 20. pii: 80. [Epub ahead of print]28(1):
       PURPOSE OF REVIEW: Early-onset colorectal cancer (EOCRC), conventionally defined as colorectal cancer diagnosed before the age of 50 years, has become one of the most important and unsettling epidemiologic shifts in gastrointestinal oncology. This review critically synthesizes recent evidence on EOCRC epidemiology, risk architecture, life-course carcinogenesis, molecular and microbiome-associated mechanisms, diagnostic delay, screening limitations, treatment considerations, and survivorship needs, with the aim of reframing EOCRC as an age-attuned clinical and biological challenge rather than a simple early presentation of conventional colorectal cancer.
    RECENT FINDINGS: Recent population-based analyses confirm that EOCRC incidence is increasing across multiple countries and birth cohorts, with a disproportionate contribution of distal colon and rectal cancers. These data suggest that the rise of EOCRC is unlikely to be explained by improved detection alone and instead points toward changing generational exposures. Contemporary studies have moved the field beyond hereditary predisposition as the dominant explanatory model: although germline syndromes remain essential to identify, most EOCRC is sporadic or incompletely explained by known inherited risk. Recent literature increasingly implicates metabolic dysfunction, obesity, westernized dietary patterns, early-life exposures, inflammation, antibiotic-associated microbial disruption, and host-microbiome disequilibrium. Particularly important are emerging genomic data linking colibactin-associated mutational signatures to younger-onset disease, supporting the hypothesis that microbial genotoxicity may imprint early driver events long before clinical diagnosis. In parallel, recent clinical studies show that EOCRC is frequently symptomatic, yet diagnosis is commonly delayed because alarm features such as rectal bleeding, abdominal pain, altered bowel habits, and anaemia are often underestimated in younger adults. EOCRC is best understood as a heterogeneous, life-course disease shaped by the convergence of inherited susceptibility, environmental and metabolic exposures, microbiome-mediated biology, tumour site, diagnostic-system factors, and survivorship context. Lowering the average-risk screening age to 45 years is necessary but insufficient, because many cases still occur below routine screening thresholds. A modern EOCRC strategy must therefore combine risk-adapted prevention, improved family-history capture, timely investigation of red-flag symptoms, systematic germline and tumour profiling, and treatment planning that accounts for decades of survivorship. Future progress will depend on moving beyond age alone toward integrated models that connect epidemiology, exposome biology, microbial mutagenesis, precision early detection, and age-specific care.
    Keywords:  Ccolorectal cancer screening; Colibactin; Diagnostic delay; Eearly-onset colorectal cancer; Hereditary predisposition; Life-course carcinogenesis; Microbiome; Precision prevention; Survivorship; Young-onset colorectal cancer
    DOI:  https://doi.org/10.1007/s11912-026-01815-1
  7. Cell Rep Methods. 2026 Aug 17. pii: S2667-2375(26)00267-5. [Epub ahead of print] 101566
      Lineage hierarchies and plasticity regulate development and tissue homeostasis, while diverted lineage dynamics and aberrant phenotypic plasticity are among the causes of incomplete drug response and resistance in cancer. Knowing the dynamics of phenotypically heterogeneous populations is therefore central to understanding growth regulation principles and to rationally design therapeutic approaches anticipating drug-tolerant states. While lineage inference can be addressed by barcoding technologies, these approaches often yield average clonal behaviors that neglect the underlying phenotypic plasticity of individual cells. Directly observing single-ancestor pedigrees in multi-type populations remains an experimental challenge. To address these difficulties, we developed a method to infer active phenotypic transitions in a multi-type tumor or clone and to quantify them, solely relying on counting cell-type abundances. We demonstrate the effectiveness of our approach to address cancer phenotypic heterogeneity and drug tolerance in silico. We then perform experiments on cancer cell populations and infer growth mechanisms and transition probabilities.
    Keywords:  Bayesian inference; CP: computational biology; CP: systems biology; Monte Carlo expectation maximization; branching processes; cancer; drug tolerance; inference; lineage hierarchies; patient-derived tumoroids; phenotypic plasticity; population dynamics
    DOI:  https://doi.org/10.1016/j.crmeth.2026.101566
  8. Curr Opin Genet Dev. 2026 Aug 15. pii: S0959-437X(26)00097-3. [Epub ahead of print]100 102530
      Stem cells must accurately balance self-renewal with the generation of specialized cells that each adopt the type of metabolism facilitating their specific function. However, recent advances demonstrate that metabolism can regulate decisions between self-renewal and differentiation, in addition to being a downstream outcome of transcriptional programs of differentiation. Here we discuss how metabolism influences mammalian stem cells, focusing on the conundrum of how cell fate determination can be accurately controlled if the endpoint product - the specialized cellular metabolism - can influence the process. We propose that most stem cells are guided by intrinsic and extrinsic metabolic cues, creating dynamic metabolic states that may differ in lineage preferences and activity but do not pose a deterministic impact on stem cell potency. Such metabolic plasticity safeguards tissue maintenance and regeneration from modest metabolic fluctuations, but disruptions beyond the limits of metabolic plasticity can impair stem cell function and fate potential.
    DOI:  https://doi.org/10.1016/j.gde.2026.102530
  9. Front Immunol. 2026 ;17 1823134
      Colorectal cancer (CRC) is a major global health burden, whereas small intestinal cancers are rare despite arising within the same gastrointestinal tract. This disparity suggests that segment-specific epithelial programmes may influence carcinogenesis. NLRP6 is an inflammasome-forming sensor with established roles in epithelial homeostasis, barrier maintenance, mucosal immune surveillance, and host-microbiota interactions. Public human tissue resources, an exploratory reanalysis of currently available single-cell data, and our local colonic cohort, provide hypothesis-generating observations compatible with segmental differences in NLRP6 expression, including very low bulk transcript abundance in human colonic samples. However, the currently available human evidence remains limited and heterogeneous, and does not yet support a simple binary model of presence in the small intestine and absence from the colon. Murine studies nevertheless support biological plausibility, as Nlrp6 deficiency exacerbates inflammation-driven colonic tumourigenesis and impairs epithelial repair. In addition, independent human studies indicate protein-level and clinicopathological relevance of NLRP6 in colonic disease, suggesting that its expression may vary according to segment, cell type, inflammatory context, and disease state. We therefore propose that NLRP6 may function as one candidate component of a segment-restricted epithelial defence and mucosal immune surveillance network in the human gut, potentially shaping CRC-relevant inflammatory and barrier conditions rather than acting as an established human tumour-suppressive mechanism. This model should now be tested through orthogonal human validation, including protein-based assays, spatial and single-cell analyses, and correlation with inflammatory status and clinical outcome, before any biomarker-guided intervention strategies are considered.
    Keywords:  NLRP6; colorectal cancer; human gut; inflammasome; mucosal immune surveillance; tumour microenvironment
    DOI:  https://doi.org/10.3389/fimmu.2026.1823134
  10. Cancer Cell. 2026 Aug 18. pii: S1535-6108(26)00356-9. [Epub ahead of print]
      In a Nature Medicine study, Tian et al. identify larger biological age gaps associated with early-onset lung, colorectal, and uterine cancers across birth cohorts. These findings position biological age as an integrative marker of physiological dysregulation. Future work combining aging clocks and mutational signatures could distinguish tumor-promoting states from tumor-initiating exposures.
    DOI:  https://doi.org/10.1016/j.ccell.2026.07.018
  11. Nat Commun. 2026 Aug 17. pii: 8410. [Epub ahead of print]17(1):
      Live cells in tissue are plastic, phenotypically dynamic, and modify their function in response to genetic and environmental perturbations. To unleash the power of live-cell imaging to identify phenotype-genotype-function coupling over time, we report the development of a standardized Shape-Appearance-Motion (SAM) "phenome" and SAM-Phenotype-Observation-Tool (SPOT), that act as an image-"transcriptome" and image-"transcriptome analyzer" respectively, and provide an unbiased and comprehensive description of morpho-dynamic phenotypes without prior knowledge. We apply SAM-SPOT to our simulated organoids database with known ground-truth and >1.6 million mouse and human organoid instances with defined genetic and chemical perturbations. SAM-SPOT can effectively and robustly characterize 3D morpho-dynamics from 2D projection videos. Combined with single-cell RNA sequencing, SAM-SPOT reveals that altered WNT signaling, but not mutant RAS or p53, predisposes intestinal organoids to irregular morphogenesis. SAM-SPOT advances biomedical discovery by empowering live-cell imaging to identify phenotype-genotype-function relationships through large-scale and cost-effective label-free live-cell imaging.
    DOI:  https://doi.org/10.1038/s41467-026-75506-7
  12. Sci Transl Med. 2026 Aug 19. 18(863): eadv6871
      For metastatic colonization to occur, disseminated tumor cells must survive, adapt to, and remodel distant microenvironments in an organ-specific manner. We established a human multitissue model of cancer spread, with engineered bone and lung linked by vascular flow containing circulating cancer cells. Parental MDA-MB-231 cells extravasated toward both tissues, remodeled their niches, and acquired transcriptional programs reflecting adaptation to the local microenvironment, particularly upon homing to bone. Tissue-specific colonization by the bone- and lung-tropic MDA-MB-231 derivatives was quantified in independently perfused bone or lung platforms. Consistent with in vivo behavior, bone-tropic cells showed stronger bone colonization than lung-tropic cells and induced more pronounced osteolysis. In contrast, lung-tropic cells caused greater epithelial disruption in lung tissue and only modest colonization of bone. Distinct patterns of tissue colonization and secreted factors demonstrate that this device recapitulates key features of organ-specific metastasis observed in vivo for this family of cell lines.
    DOI:  https://doi.org/10.1126/scitranslmed.adv6871
  13. Cell Syst. 2026 Aug 19. pii: S2405-4712(26)00181-X. [Epub ahead of print] 101699
      Embryonic development builds tissues and organs through the self-organization of heterogeneous cells across spatial and temporal scales, analogous to an ecosystem. Although ecological systems are often stochastic and multistable, embryogenesis is remarkably reproducible. We argue that this contrast is not a contradiction. Developmental robustness arises from evolutionarily filtered ecological interactions embedded within hierarchically organized, multiscale architectures that restrict accessible collective states. Competition, cooperation, niche construction, and density-dependent coupling are not metaphors but core interaction dynamics that shape tissues in vivo. In vitro systems frequently lack these multiscale constraints, allowing more permissive ecological dynamics and increased variability. We propose "synthetic tissue ecology" as a conceptual and engineering framework that treats development as a stabilized regime of ecological organization. By shifting focus to interaction architectures and constraints that direct cross-scale self-organization, this framework enables the decoding of mesoscale modules and tissue-coupling principles while supporting the engineering of robust organoids, embryoids, and regenerative systems.
    Keywords:  development; ecology; embryogenesis; embryoids; mammalian cells; multicellular systems; organoids; stem cells; synthetic biology
    DOI:  https://doi.org/10.1016/j.cels.2026.101699
  14. iScience. 2026 Aug 21. 29(8): 116756
      The development of preclinical models that recapitulate the physiological and pathological features of human tumors remains a central challenge in cancer research. Advances in cell biology have enabled the generation of three-dimensional tumor organoids, which closely mirror patient-specific therapeutic responses and facilitate the study of disease mechanisms. However, the trend of these models necessitates a shift from traditional, invasive analytical methods toward non-invasive, high-throughput imaging approaches. Here, we review the current state of tumor organoid culture and the emerging application of artificial intelligence (AI) in their evaluation. We discuss how AI-driven technologies are revolutionizing the analysis of fluorescence imaging, viability assessments, and dynamic cell tracking, thereby overcoming the limitations of manual interpretation. Finally, we provide a perspective on how integrating deep learning with organoid technology will enhance the precision and efficiency of drug discovery and personalized oncology.
    Keywords:  artificial intelligence; cancer; deep learning; image analysis; tumor organoid
    DOI:  https://doi.org/10.1016/j.isci.2026.116756