bims-gerecp 2025-07-06 papers

Nat Commun. 2025 Jul 01. 16(1): 5970

Dissecting crosstalk induced by cell-cell communication using single-cell transcriptomic data.

During cell-cell communication (CCC), pathways activated by different ligand-receptor pairs may have crosstalk with each other. While multiple methods have been developed to infer CCC networks and their downstream response using single-cell RNA-seq data (scRNA-seq), the potential crosstalk between pathways connecting CCC with its downstream targets has been ignored. Here we introduce a machine learning-based method SigXTalk to analyze the crosstalk using scRNA-seq data by quantifying signal fidelity and specificity, two critical quantities measuring the effect of crosstalk. Specifically, a hypergraph learning method is used to encode the higher-order relations among receptors, transcription factors and target genes within regulatory pathways. Benchmarking of SigXTalk using simulation and real-world data shows the effectiveness, robustness, and accuracy in identifying key shared molecules among crosstalk pathways and their roles in transferring shared CCC information. Analysis of disease data shows SigXTalk's capability in identifying crucial signals, targets, regulatory networks, and CCC patterns that distinguish different disease conditions. Applications to the data with multiple time points reveals SigXTalk's capability in tracking the evolution of crosstalk pathways over time. Together our studies provide a systematic analysis of CCC-induced regulatory networks from the perspective of crosstalk between pathways.

DOI: https://doi.org/10.1038/s41467-025-61149-7

Nat Biotechnol. 2025 Jul 01.

Defining and benchmarking open problems in single-cell analysis.

Open Problems Jamboree Members

DOI: https://doi.org/10.1038/s41587-025-02694-w

Cell Res. 2025 Jul 04.

A patient-derived organoid model captures fetal-like plasticity in colorectal cancer.

Liang Xiong, Ying Xu, Zhaoya Gao, Jingyi Shi, Yunfan Wang, Xiaodong Wang, Wensheng Huang, Ming Li, Longteng Wang, Jun Xu, Cheng Li, Jin Gu, Hongkui Deng, Molong Qu.

Phenotypic plasticity is a hallmark feature driving cancer progression, metastasis, and therapy resistance. Fetal-like transcriptional programs have been increasingly implicated in promoting plastic cell states, yet their roles remain difficult to study due to limitations of existing culture models. Here, we establish a chemically defined patient-derived organoid system that enables long-term expansion of colorectal cancer (CRC) cells while preserving fetal-like features associated with phenotypic plasticity. Using this model, we identify an oncofetal state (OnFS) that is enriched in advanced tumors and linked to key features of plasticity, including epithelial-mesenchymal plasticity, as well as increased metastasis and treatment resistance. Mechanistically, we show that FGF2-AP-1 signaling maintains the OnFS program and associated phenotypic plasticity in CRC. This model offers a powerful platform for studying the fetal-like features underlying cancer cell plasticity and their role in tumor progression and treatment resistance in CRC.

DOI: https://doi.org/10.1038/s41422-025-01139-y

Sci Rep. 2025 Jul 04. 15(1): 23921

Pan-cancer immune and stromal deconvolution predicts clinical outcomes and mutation profiles.

Cancer Genome Atlas Analysis Network

Traditional gene expression deconvolution methods assess a limited number of cell types, therefore do not capture the full complexity of the tumor microenvironment (TME). Here, we integrate nine deconvolution tools to assess 79 TME cell types in 10,592 tumors across 33 different cancer types, creating the most comprehensive analysis of the TME. In total, we found 41 patterns of immune infiltration and stroma profiles, identifying heterogeneous yet unique TME portraits for each cancer and several new findings. Our findings indicate that leukocytes play a major role in distinguishing various tumor types, and that a shared immune-rich TME cluster predicts better survival in bladder cancer for luminal and basal squamous subtypes, as well as in melanoma for RAS-hotspot subtypes. Our detailed deconvolution and mutational correlation analyses uncover 35 therapeutic target and candidate response biomarkers hypotheses (including CASP8 and RAS pathway genes).

Keywords: Cell type estimation; Deconvolution; Immune cells; Integrated scores; Pan-cancer analysis; Somatic mutations; Stroma; Survival; Tumor microenvironment; Tumor progression; iScores

DOI: https://doi.org/10.1038/s41598-025-09075-y

Immunol Cell Biol. 2025 Jun 29.

Sketching T cell atlases in the single-cell era: challenges and recommendations.

Itana Bojović, António Gg Sousa, Sini Junttila, Laura L Elo.

Recent advances in single-cell technologies have enabled the creation of comprehensive cell atlases, reference maps of various cell types within organisms. Here we specifically focus on T cell atlases, which offer a detailed catalog of the adaptive immune system at single-cell resolution. As such, they capture cellular diversity, functional states, and spatial dynamics across tissues, developmental stages, and disease conditions. Given the central role of T cells in orchestrating immune responses, their dysregulation underpins autoimmune disorders, cancer progression and failed immunotherapies. Therefore, a unified T cell atlas is critical for decoding such disease mechanisms, identifying therapeutic targets, and advancing personalized treatments. In this article, we explore the latest advances in T cell atlases, describing breakthroughs in multi-omics technologies, spatial profiling and computational frameworks that resolve transcriptional, epigenetic and proteomic heterogeneity. We also address persistent challenges and highlight strategies to address these gaps. Finally, we discuss emerging frontiers set to reshape our understanding of T cell dynamics in both health and diseases. Together, these insights underscore the transformative potential of T cell atlases in reconstructing precision immunology and accelerating therapeutic innovation.

Keywords: T cells; atlas; integration; multi‐omics; single‐cell

DOI: https://doi.org/10.1111/imcb.70040

Nat Cancer. 2025 Jun 30.

Self-amplifying NRF2-EZH2 epigenetic loop converts KRAS-initiated progenitors to invasive pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) emerges from mutant KRAS-harboring but dormant low-grade pancreatic intraepithelial neoplasia (PanIN). To examine the role of oxidative stress, a putative PDAC risk factor, we established an organoid-based transformation system. Although the prototypic oxidant H2O2 induced organoid transformation, its effect was nonmutational and was mediated by the oxidant-responsive transcription factor NRF2, which induced the histone methyltransferase EZH2. Congruently, nonoxidizing NRF2 activators triggered organoid malignant conversion through NRF2 and EZH2, establishing a hitherto unknown epigenetic mechanism underlying PanIN-to-PDAC progression. While NRF2 induced EZH2 gene transcription in mouse and human PDAC, EZH2, a general repressor, coactivated transcription of NRF2-encoding NFE2L2 and interacted with other transcription factors to induce genes that sustain PDAC metabolic demands. The self-amplifying NRF2-EZH2 epigenetic loop also accounted for inflammation-driven PanIN-to-PDAC progression in vivo and was upregulated in established human PDAC, whose malignancy was maintained by NRF2 binding to the EZH2 promoter.

DOI: https://doi.org/10.1038/s43018-025-01003-3

Nat Rev Cancer. 2025 Jul 04.

Combining spatial transcriptomics and AI to enhance brain tumour diagnosis.

Yahaya A Yabo.

DOI: https://doi.org/10.1038/s41568-025-00851-6