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Integrating single-cell atlases and machine learning to construct 'in silico patients' for predicting individualized drug responses.
Intratumoral cellular heterogeneity is a core challenge that drives drug resistance and hinders the advancement of precision oncology. Single-cell RNA sequencing (scRNA-seq) has revealed the complexity of the tumor ecosystem at unprecedented resolution, offering new opportunities for predicting therapeutic responses. This review synthesizes the emerging concept of the "in silico patient", a predictive framework that integrates multi-source data. This framework leverages large-scale single-cell atlases as references for cellular identity, combines massive pharmacogenomic databases to train models, and incorporates patient-specific scRNA-seq data to achieve individualized predictions. Artificial intelligence (AI), particularly deep learning and transfer learning algorithms, acts as the core driver of this framework, effectively applying knowledge gained from cell line data to clinically relevant patient single-cell data. By integrating the impact of the tumor microenvironment (TME) and using advanced preclinical models that preserve tissue architecture (such as acute tissue slice cultures) for rapid experimental validation, a critical "prediction-validation-optimization" closed loop is being formed. This review systematically outlines the data foundations, core computational strategies, current challenges, and future directions, including multi-omics and spatial information integration, necessary to construct "in silico patients", aiming to provide a comprehensive conceptual blueprint for developing the next generation of individualized drug response prediction tools.
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Deciphering the Cellular and Metabolic Landscape of Lymph Node Metastasis in Breast Cancer Using Single-Cell and Spatial Multi-Omics.
Metastasis is a major threat in breast cancer, often involving lymph node (LN) dissemination. However, the cellular composition and signaling networks within the metastatic microenvironment remain incompletely characterized, resulting in limited understanding of the molecular mechanisms driving LN metastasis. In this study, a comprehensive single-cell atlas of metastatic niches was constructed using single-cell RNA-sequencing data from 78 primary breast tumors and their paired LN metastatic samples. Among the epithelial cell subpopulations, distinct clusters representing early-disseminated cancer cells were identified. Notably, profound metabolic reprogramming and immune modulation was observed during the malignant transformation of epithelial cells, which may contribute to the invasive and metastatic phenotype of early-disseminated cancer cells. Furthermore, the communication network within the metastatic microenvironment has also been delineated systematically, where crosstalk among lymphocyte, macrophage, and epithelial cells drove immunosuppressive features of LN metastasis. To explore potential therapeutic interventions, computational drug repositioning was conducted and four tyrosine kinase receptor inhibitors were identified that may target key interactions within this crosstalk. These results were validated using spatial transcriptomics data of four metastatic LN tissue sections from an integrated single-cell RNA-sequencing cohort. Collectively, this study discussed the cellular architecture and regulatory interplay underlying LN metastasis in breast cancer, offering novel insights that may inform targeted therapeutic strategies for patients with metastatic disease.
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Single-cell RNA-seq and pathological phenotype reveal the functional atlas and precise roles of Sox30 in testicular cell development and differentiation.
Sox30 has recently been demonstrated to be a key regulator of spermatogenesis. However, the precise roles of Sox30 in the testis remain largely unclear. Here, the specific functions of Sox30 in testicular cells were determined by single-cell sequencing and confirmed via pathological analyses. Sox30 loss appears to damage all testicular cells to different extents. Sox30 chiefly drives the differentiation of primary spermatocytes. Sox30 deficiency causes spermatocyte arrest at the early phase of meiosis I, with nearly no normally developing second spermatocytes and three new spermatocyte -subclusters emerging. In addition, Sox30 seems to play important roles in the mature phenotypes of Sertoli and Leydig cells, and the proliferation and differentiation of spermatogonia. The developmental trajectory of germ cells begins with spermatogonia and splits into two different spermatocyte branches, with Sox30-null spermatocytes and wild-type spermatocytes placed at divergent ends. An opposite developmental trajectory of spermatocyte subclusters is observed, followed by incomplete development of spermatid subclusters in Sox30-null mice. Sox30 deficiency clearly alters the intercellular cross-talk of major testicular cells and dysregulates the transcription factor networks primarily involved in cell proliferation and differentiation. Mechanistically, Sox30 appears to have similar terminal functions that are involved mainly in spermatogenic development and differentiation among major testicular cells, and Sox30 performs these similar crucial roles through preferential regulation of different signalling pathways. Our study describes the exact functions of Sox30 in testicular cell development and differentiation and highlights the primary roles of Sox30 in the early meiotic phase of germ cells.
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A single-donor proof-of-concept single-cell analysis maps heterogeneous differentiation trajectories toward cartilage-like states in human urine-derived stem cells.
BACKGROUND: Urine-derived stem cells (USCs) represent an accessible and non-invasive cell source with reported chondrogenic differentiation potential. However, the cellular heterogeneity and transcriptional dynamics underlying USC differentiation remain incompletely understood, limiting their translational interpretation. METHODS: We combined functional differentiation assays with single-cell RNA sequencing to characterize USC differentiation at both phenotypic and transcriptional levels. Chondrogenic and osteogenic differentiation were assessed using histological staining, quantitative PCR, and three-dimensional spheroid cultures. Single-cell transcriptomic analysis was performed on integrated datasets of undifferentiated and differentiated USCs, followed by pseudotime trajectory inference and mapping to a human cartilage reference atlas. RESULTS: Chondrogenic induction resulted in reproducible acquisition of cartilage-associated features, including glycosaminoglycan-rich extracellular matrix deposition, increased expression of SOX9, and formation of aggrecan-positive spheroids. In this donor, single-cell analysis mapped an inferred differentiation trajectory from proliferative states towards differentiated populations, although the fine-grained pseudotemporal ordering was sensitive to analytical choices and is therefore interpreted qualitatively. Along this inferred trajectory, we identified a candidate transient transcriptional state associated with elevated CDH1 expression and epithelial-like aggregation features. Probabilistic mapping to a human cartilage reference atlas indicated that overall mapping confidence was low (median prediction score 0.34) and that only a minority of cells showed confident transcriptional similarity (prediction score ≥ 0.5) to mature/articular cartilage-associated reference states (7.8% of all cells and 17.6% of chondrogenically induced cells). This confident similarity was concentrated in a few clusters at the differentiated end of the trajectory rather than representing the bulk of the culture, and label-transfer confidence was not equated with chondrocyte identity. Despite this enrichment, differentiated populations exhibited transcriptional heterogeneity, including subsets of cells associated with hypertrophic, fibrocartilage-like, and contractile gene programmes, indicating the presence of multiple differentiation trajectories. CONCLUSIONS: This single-donor proof-of-concept study suggests that USC differentiation may involve a candidate transient, aggregation-associated transcriptional state accompanied by CDH1 expression and gives rise to heterogeneous lineage-associated outcomes, with only a minority of cells acquiring confident transcriptional similarity to mature cartilage. Because these observations derive from one donor, they should be interpreted as hypothesis-generating and require validation across independent donors before donor-independent or translational conclusions for cartilage regeneration can be drawn. These findings nonetheless provide a single-cell resolution framework for future multi-donor validation of USC differentiation and its inherent transcriptional heterogeneity.
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Single-nucleus multiple-organ chromatin accessibility landscape in the adult rat.
BACKGROUND: Chromatin accessibility landscape is the basis of cell-specific gene expression and reflects the regulatory logic underlying cellular identity and function. However, a systematic multi-organ chromatin accessibility atlas in the rat (Rattus norvegicus), an important biomedical model organism, has been lacking. RESULTS: We generated a multi-organ single-nucleus chromatin accessibility landscape of Rattus norvegicus using snATAC-seq. For this single-cell atlas, we constructed 25 libraries via snATAC-seq from 9 organs in the adult rat, with a total of over 110,000 cells. Cell classification integrating gene activity scores with known marker genes identified 77 cell types, which were strongly correlated with those in published mouse single-cell transcriptome atlases. We further investigated the enrichment of cell-type- and organ-specific transcription factors, shared and organ-specific features of endothelial and stromal cells, as well as cross-organ macrophage regulatory states, and the conservation and specificity of gene regulatory programs across species. CONCLUSION: This single-nucleus chromatin accessibility landscape provides a valuable foundation for dissecting tissue-specific regulatory mechanisms in the rat and facilitates cross-organ and cross-species cell type annotation and functional inference, supporting broader applications of rat model in systems biology and biomedical research.
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Molecular and immune signatures, and pathological trajectories of fatal COVID-19 lungs defined by in situ spatial single-cell transcriptome analysis.
Despite intensive studies during the last 3 years, the pathology and underlying molecular mechanism of coronavirus disease 2019 (COVID-19) remain poorly defined. In this study, we investigated the spatial single-cell molecular and cellular features of postmortem COVID-19 lung tissues using in situ sequencing (ISS). We detected 10 414 863 transcripts of 221 genes in whole-slide tissues and segmented them into 1 719 459 cells that were mapped to 18 major parenchymal and immune cell types, all of which were infected by SARS-CoV-2. Compared with the non-COVID-19 control, COVID-19 lungs exhibited reduced alveolar cells (ACs) and increased innate and adaptive immune cells. We also identified 19 differentially expressed genes in both infected and uninfected cells across the tissues, which reflected the altered cellular compositions. Spatial analysis of local infection rates revealed regions with high infection rates that were correlated with high cell densities (HIHD). The HIHD regions expressed high levels of SARS-CoV-2 entry-related factors including ACE2, FURIN, TMPRSS2 and NRP1, and co-localized with organizing pneumonia (OP) and lymphocytic and immune infiltration, which exhibited increased ACs and fibroblasts but decreased vascular endothelial cells and epithelial cells, mirroring the tissue damage and wound healing processes. Sparse nonnegative matrix factorization (SNMF) analysis of niche features identified seven signatures that captured structure and immune niches in COVID-19 tissues. Trajectory inference based on immune niche signatures defined two pathological routes. Trajectory A primarily progressed with increased NK cells and granulocytes, likely reflecting the complication of microbial infections. Trajectory B was marked by increased HIHD and OP, possibly accounting for the increased immune infiltration. The OP regions were marked by high numbers of fibroblasts expressing extremely high levels of COL1A1 and COL1A2. Examination of single-cell RNA-seq data (scRNA-seq) from COVID-19 lung tissues and idiopathic pulmonary fibrosis (IPF) identified similar cell populations consisting mainly of myofibroblasts. Immunofluorescence staining revealed the activation of IL6-STAT3 and TGF-β-SMAD2/3 pathways in these cells, likely mediating the upregulation of COL1A1 and COL1A2 and excessive fibrosis in the lung tissues. Together, this study provides a spatial single-cell atlas of cellular and molecular signatures of fatal COVID-19 lungs, which reveals the complex spatial cellular heterogeneity, organization, and interactions that characterized the COVID-19 lung pathology.
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Alterations of sphingosine-1-phosphate and its receptors in type 1 diabetes mellitus: an integrated clinical and single-cell transcriptomic study.
BACKGROUND: Type 1 diabetes (T1DM) is a T cell-mediated autoimmune disease. The sphingosine-1-phosphate (S1P) signaling pathway regulates lymphocyte trafficking, but its status in T1DM remains poorly characterized. This study investigated S1P and sphingosine-1-phosphate receptor 1(S1PR1) alterations in T1DM through integrated single-cell transcriptomic and clinical analysis. MAIN METHODS: We performed single-cell RNA sequencing (scRNA-seq)on colonic tissues from T1DM patients and healthy controls, complemented by analysis in non-obese diabetic (NOD) mice at pre-diabetic (4 weeks) and disease stages (12 weeks).Serum total S1P, HDL-bound S1P, and apolipoprotein M (ApoM) were quantified, and transcriptomic functional enrichment of intestinal T cell subsets was further performed. RESULTS: scRNA-seq showed differences in S1P receptor expression in intestinal immune cells between T1DM patients and healthy controls. S1PR1 expression was lower in T cell subsets, particularly CD8+ effector T cells, in T1DM patients. In NOD mice, S1PR1 expression showed a clustered pattern at 4 weeks and was more diffuse with lower levels in lymphocytes at 12 weeks. Clinically, serum total S1P was significantly elevated in T1DM and independently increased T1DM risk, while high-density lipoprotein-bound (HDL-bound) sphingosine-1-phosphate (HDL-S1P) was decreased with unchanged apolipoprotein M (ApoM) levels. Serum S1P positively correlated with glycated hemoglobin (HbA1c) and interleukin-6 (IL-6), and was inversely associated with hypoglycemic episodes. Transcriptomic enrichment indicated functional reprogramming of intestinal CD8+ effector T and regulatory T cells. CONCLUSION: T1DM is associated with alterations in the S1P-S1PR1 pathway, characterized by reduced intestinal S1PR1 expression, elevated circulating total S1P, and decreased functional HDL-bound S1P despite stable ApoM.S1P is independently associated with T1DM status and correlates with glycemic control and inflammation, suggesting its potential as a disease-related biomarker.
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Rudolf Buchheim Award 2026: Toward a ToxAtlas of carbon-based nanomaterials: single-cell RNA sequencing reveals initiating cell circuits in pulmonary inflammation.
The Rudolf Buchheim Award of the German Society for Experimental and Clinical Pharmacology and Toxicology (DGPT) honors outstanding contributions by early-career scientists in pharmacology and toxicology. The 2026 award recognizes research that advances mechanistic understanding of the initiation of respiratory inflammation by carbon-based nanomaterials (CBN). While pulmonary inflammation is recognized as an early adverse but generic response to inhaled particles, only little is known about the initiating events and involved cell types. Carola Voss systematically dissected cell type-specific responses to soot-like carbon nanoparticles, flexible double-walled carbon nanotubes, and needle-like multi-walled carbon nanotubes known for their asbestos-like toxicity at single-cell resolution in the lab of Dr. Tobias Stoeger at Helmholtz Munich. Using advanced single-cell transcriptomics of CBN-exposed mouse lungs, this research establishes a toxicological atlas that links physicochemical CBN properties to cell-specific inflammatory initiation, cellular stress responses, and immune cell recruitment. The findings provide a conceptual framework for mode of action-based hazard assessment and support the rational design of safer nanomaterials along with the development of specific in vitro assays.
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Oyster cellular architecture and innate immune programs resolved by single-cell RNA sequencing.
Barrier mucosal tissues in marine invertebrates coordinate filtration, gas exchange, and frontline innate immunity, yet their cellular organization and division of functions remain poorly resolved. This study generated a tissue-resolved single-cell atlas in a marine invertebrate Crassostrea hongkongensis, defining twenty cell types. The framework revealed a diversified phagocyte lineage composed by five phagocytic cells with three terminal strategies: rapid extracellular containment, deep intracellular clearance, and a resolution program that couples degradation with matrix restoration. We also identified three humoral immune populations with complementary recognition and effector roles that collaborated with phagocytes and epithelial cells. Barrier epithelium supports acted as organizers rather than redundant producers of soluble effectors, and shaped immune activity through defined communication and adhesion programs that coordinated proliferation, survival, and migration. A neural-related compartment comprised of neural progenitor-like, neuron-like, and neuroendocrine cells, and exhibited predominantly sender roles toward epithelial and immune targets consistent with transmitter and peptide-mediated control of ciliary flow, secretory activity, as well as the priming of phagocytic and humoral effectors. Ligand receptor inference highlighted adhesion modules centering on neural cell adhesion molecule (NCAM) and the receptor type protein tyrosine phosphatase (PTPRM) as the key pathways of communication between neural, epithelial, and immune populations. Our finding present a compact taxonomy to map immune programs with precise cellular contexts, and further our understanding of resilience and health in variable coastal environments.
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Single cell RNAseq signatures refined with combiroc enhance identification of NK cells in blood and solid tissues.
Cytotoxic CD8 T lymphocytes (CTLs) and natural killer (NK) cells share the common objective of controlling infections and detecting and removing tumor cells, albeit through distinct target recognition mechanisms. Although CTLs belong to the adaptive immune system and NK cells are innate lymphoid cells, they frequently exhibit considerable overlap in their molecular phenotypes. This overlap, as with many others in cell biology, poses challenges for distinguishing cells in the context of single cell transcriptomics. Building on a previous ROC-driven combinatorial approach, we developed a new computational framework for single-cell RNA-seq with the combiroc R package, and in this study we showed that it can identify non-canonical marker combinations for NK cells in Peripheral Blood Mononuclear Cell datasets. These combinatorial markers were in line with the Human Protein Atlas and we validated them through cytometry staining and functional assays. Markers selected with combiroc exhibit exceptional discriminatory power for identifying NK cells, both in blood and solid tumoral tissues. Besides this finding, we showed that our approach vastly optimizes standard differential expression signatures: it reduces dimensionality while improving interpretability and transferability to diagnostic applications, offering a practical solution for refining immune cell identities in complex transcriptomic datasets.