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Single-cell transcriptomic analyses of tumor microenvironment and molecular reprograming landscape of metastatic laryngeal squamous cell carcinoma.
Laryngeal squamous cell carcinoma (LSCC) is a malignant tumor with a high probability of metastasis. The tumor microenvironment (TME) plays a critical role in cancer metastasis. To gain insights into the TME of LSCC, we conducted single-cell RNA-seq (scRNA-seq) on samples collected from LSCC patients with or without lymphatic metastasis. The stem and immune cell signatures in LSCC suggest their roles in tumor invasion and metastasis. Infiltration of a large number of regulatory T cells, dysplastic plasma cells, and macrophages that are at the early development stage in the cancerous tissue indicates an immunosuppressive state. Abundant neutrophils detected at the cancer margins reflect the inflammatory microenvironment. In addition to dynamic ligand-receptor interactions between the stromal and myeloid cells, the enhanced autophagy in endothelial cells and fibroblasts implies a role in nutrient supply. Taken together, the comprehensive atlas of LSCC obtained allowed us to identify a complex yet unique TME of LSCC, which may help identify potential diagnostic biomarkers and therapeutic targets for LSCC.
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Integrative single cell transcriptomic analysis reveals 3p deletion associated tumor microenvironment and chemoresistance in head and neck squamous cell carcinoma.
Head and neck squamous cell carcinoma (HNSCC) remains a prevalent and lethal malignancy, with a five-year survival rate of just 50% for cases of locally advanced disease. Chromosomal aberrations, particularly the deletion of the short arm of chromosome 3 (3p), have been strongly associated with poor prognosis and more aggressive tumor phenotypes. The tumor microenvironment (TME) plays a pivotal role in tumor progression and resistance to therapy. This study aims to elucidate the impact of 3p deletion on the TME, immune cell infiltration, and treatment response in HNSCC, to identify novel therapeutic targets to improve patient outcomes. We analyzed single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) and bulk transcriptome data from The Cancer Genome Atlas (TCGA). Pseudo-time trajectory and cell-cell communication analyses were performed with the Monocle and CellChat packages. The Wilcoxon test was used to evaluate the differential gene expression between wild-type (wt) and mutant (mut) groups. Prognostic models were developed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Cox regression analyses to find the genes related to survival, with survival analysis conducted via Kaplan-Meier curves. Gene set enrichment analysis (GSEA) was employed to investigate pathway dysregulation, and immune cell infiltration was assessed using various immune scoring methodologies to explore the differences immune environment. The Tumor Immune Dysfunction and Exclusion (TIDE) database was utilized to predict the potential efficacy of immune checkpoint inhibitors. mRNA and protein expression levels of SPP1 were examined by RT-qPCR and Western blotting, while cell proliferation was assessed using the CCK8 assay. The mut group demonstrated significant alterations in cellular composition, characterized by increased endothelial cells and macrophages and decreased fibroblasts and CD8 + T cells, indicative of an immunosuppressive TME. Differential expression analysis revealed downregulation of immune pathways, including antigen processing and presentation, T cell receptor signaling, and B cell receptor signaling pathways in the mut group, along with enhanced metabolic activity in glycolysis and lipid metabolism. The prognostic model identified nine key genes associated with poor survival in HNSCC. The mut group exhibited poorer overall survival and a more immunosuppressive microenvironment compared to the wt group, which correlated with the outcomes observed in high-risk versus low-risk groups. High-risk patients also showed a diminished response to immunotherapy compared to low-risk patients. Additionally, SPP1 emerged as a critical gene associated with chemotherapy resistance and macrophage M2 polarization. This study demonstrates that 3p deletion significantly reshapes the TME, contributing to poor prognosis in HNSCC by fostering an immunosuppressive environment and enhancing chemoresistance. These findings highlight the potential for developing targeted therapies that address the genetic and immunological landscape of HNSCC.
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Single-cell-resolution transcriptome map revealed novel genes involved in testicular germ cell progression and somatic cells specification in Chinese tongue sole with sex reversal.
Female-to-male sex reversals (pseudomales) are common in lower vertebrates and have been found in natural populations, which is a concern under rapid changes in environmental conditions. Pseudomales can exhibit altered spermatogenesis. However, the regulatory mechanisms underlying pseudomale spermatogenesis remain unclear. Here, we characterized spermatogenesis in Chinese tongue sole (Cynoglossus semilaevis), a species with genetic and environmental sex determination, based on a high-resolution single-cell RNA-seq atlas of cells derived from the testes of genotypic males and pseudomales. We identified five germ cell types and six somatic cell types and obtained a single-cell atlas of dynamic changes in gene expression during spermatogenesis in Chinese tongue sole, including alterations in pseudomales. We detected decreased levels of Ca2+ signaling pathway-related genes in spermatogonia, insufficient meiotic initiation in spermatocytes, and a malfunction of somatic niche cells in pseudomales. However, a cluster of CaSR genes and MAPK signaling factors were upregulated in undifferentiated spermatogonia of pseudomales. Additionally, we revealed that Z chromosome-specific genes, such as piwil2, dhx37, and ehmt1, were important for spermatogenesis. These results improve our understanding of reproduction after female-to-male sex-reversal and provide new insights into the adaptability of reproductive strategies in lower vertebrates.
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Single-Cell Atlases as Meta-Analytic Compasses for Developmental Biology: A Case Study Using the Arabidopsis Root.
Plant development arises from the coordinated execution of gene regulatory programs across diverse cell types. While classical genetic and genomic approaches have revealed many of the genes required for plant growth and patterning, these methods often average signals across heterogeneous tissues, thereby obscuring how regulatory programs operate within individual cells. Resolving gene expression at cellular resolution is therefore essential for understanding how developmental decisions are made, integrated, and propagated during organ growth. The Arabidopsis root, with its simple anatomy and invariant cell lineages, provides an ideal system for addressing these questions. Recent advances in single-cell and single-nucleus transcriptomics have enabled the construction of comprehensive cellular atlases that capture gene expression dynamics across cell identities and developmental trajectories. In this Expert Views article, we highlight recent conceptual and technical developments that illustrate how single-cell atlases have transformed studies of root development. We emphasize how these atlases both serve as community resources to inform the interpretation of new datasets, including those generated from mutants and in response to perturbation, as well as provide a platform for meta-analysis to initiate new studies. Using auxin signaling as a meta-analysis case study, we demonstrate how legacy transcriptomic data can be reinterpreted within a cell lineage-resolved framework. Finally, we highlight how spatial transcriptomics and rigorous data-sharing practices will extend cellular atlases across tissues and species, thereby enabling increasingly precise strategies for understanding and engineering plant growth and resilience.
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CART-GPT: A T Cell-Informed AI Linguistic Framework for Interpreting Neurotoxicity and Therapeutic Outcomes in CAR-T Therapy.
Chimeric antigen receptor (CAR) T cell therapy holds transformative potential for hematologic malignancies, yet predicting patient-specific treatment efficacy and neurotoxicity remains a major clinical challenge due to the complex and heterogeneous nature of the infused CAR-T cell populations. Here, we introduce CART-GPT, a transformer-based model fine-tuned on a curated atlas of 1.12 million CAR-T single-cell RNA-seq profiles annotated with clinical outcomes. CART-GPT is the first AI model developed for CAR-T therapy that predicts both treatment response and the risk of immune effector cell-associated neurotoxicity syndrome (ICANS), achieving state-of-the-art performance (AUC ~0.8) and marking a significant advance in the field. The model provides interpretable insights, revealing that neither therapeutic efficacy nor neurotoxicity is driven by individual cell types alone, but by the combined influence of discrete, distinct subsets across diverse T cell states and transcriptional programs. A novel cell aggregation strategy links single-cell predictions to patient-level metrics, enhancing both accuracy and biological relevance. As a contribution to this ever-evolving field, we also release a comprehensive, annotated single-cell CAR-T atlas as a community resource to facilitate future research in immunotherapy. These advances demonstrate the potential of foundation models in single-cell biology to inform precision CAR-T treatment planning and facilitate the rational design of next-generation cell therapies.
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Tumor-Infiltrating PD-1hiCD8+-T-Cell Signature as an Effective Biomarker for Immune Checkpoint Inhibitor Therapy Response Across Multiple Cancers.
BACKGROUND: Stratification of patients who could benefit from immune checkpoint inhibitor (ICI) therapy is of much importance. PD-1hiCD8+ T cells represent a newly identified and effective biomarker for ICI therapy response biomarker in lung cancer. Accurately quantifying these T cells using commonly available RNA sequencing (RNA-seq) data may extend their applications to more cancer types. METHOD: We built a transcriptome signature of PD-1hiCD8+ T cells from bulk RNA-seq and single-cell RNA-seq (scRNA-seq) data of tumor-infiltrating immune cells. The signature was validated by flow cytometry and in independent datasets. The clinical applications of the signature were explored in non-small-cell lung cancer, melanoma, gastric cancer, urothelial cancer, and a mouse model of breast cancer samples treated with ICI, and systematically evaluated across 21 cancer types in The Cancer Genome Atlas (TCGA). Its associations with other biomarkers were also determined. RESULTS: Signature scores could be used to identify the PD-1hiCD8+ T subset and were correlated with the fraction of PD-1hiCD8+ T cells in tumor tissue (Pearson correlation, R=0.76, p=0.0004). Furthermore, in the scRNA-seq dataset, we confirmed the capability of PD-1hiCD8+ T cells to secrete CXCL13, as well as their interactions with other immune cells. In 581 clinical samples and 204 mouse models treated with ICIs, high signature scores were associated with increased survival, and the signature achieved area under the receiver operating characteristic curve scores of 0.755 (ranging from 0.61 to 0.91) in predicting therapy response. In TCGA pan-cancer datasets, our signature scores were consistently correlated with therapy response (R=0.78, p<0.0001) and partially explained the diverse response rates among different cancer types. Finally, our signature generally outperformed other mRNA-based predictors and showed improved predictive performance when used in combination with tumor mutational burden (TMB). The signature score is available in the R package "PD1highCD8Tscore" (https://github.com/Liulab/PD1highCD8Tscore). CONCLUSION: Through estimating the fraction of the PD-1hiCD8+ T cell, our signature could predict response to ICI therapy across multiple cancers and could serve as a complementary biomarker to TMB.
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Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia.
Peripheral sensory neurons in the dorsal root ganglion (DRG) and trigeminal ganglion (TG) are specialized to detect and transduce diverse environmental stimuli including touch, temperature, and pain to the central nervous system. Recent advances in single-cell RNA-sequencing (scRNA-seq) have provided new insights into the diversity of sensory ganglia cell types in rodents, non-human primates, and humans, but it remains difficult to compare transcriptomically defined cell types across studies and species. Here, we built cross-species harmonized atlases of DRG and TG cell types that describe 18 neuronal and 11 non-neuronal cell types across 6 species and 19 studies. We then demonstrate the utility of this harmonized reference atlas by using it to annotate newly profiled DRG nuclei/cells from both human and the highly regenerative axolotl. We observe that the transcriptomic profiles of sensory neuron subtypes are broadly similar across vertebrates, but the expression of functionally important neuropeptides and channels can vary notably. The new resources and data presented here can guide future studies in comparative transcriptomics, simplify cell type nomenclature differences across studies, and help prioritize targets for future pain therapy development.
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SHMT2: a Metabolic and Immune Biomarker of Aggressive Lung Adenocarcinoma.
Serine/glycine-one-carbon (SGOC) metabolism is frequently altered in lung adenocarcinoma (LUAD), but its relationship to tumor behavior and predicted immunotherapy responsiveness remains incompletely defined. Metabolomic profiling of 23 paired LUAD and adjacent normal lung tissues was performed using internal extractive electrospray ionization mass spectrometry. Transcriptomic and clinical data from The Cancer Genome Atlas LUAD cohort (TCGA-LUAD) were analyzed to assess SHMT2 expression, prognosis, differentially expressed genes, and immune-related features. Predicted response to immune checkpoint blockade was evaluated using Tumor Immune Dysfunction and Exclusion (TIDE) and The Cancer Immunome Atlas (TCIA), and drug sensitivity was inferred using oncoPredict. Single-cell RNA-seq data were used to examine the cellular distribution of SHMT2. Experimental validation included quantitative reverse-transcription PCR (RT-qPCR), western blotting, Human Protein Atlas (HPA) immunohistochemistry, and short hairpin RNA (shRNA)-mediated SHMT2 knockdown followed by proliferation, wound-healing and colony formation assays. Metabolomic analysis identified glycine, serine, and threonine metabolism as a prominently altered pathway in LUAD. SHMT2 was upregulated in LUAD and associated with worse overall survival and adverse clinicopathological features. SHMT2-high tumors displayed enrichment of cell-cycle and SGOC-related transcriptional programs, lower immune and stromal scores, and reduced predicted responsiveness to immunotherapy. Single-cell analysis showed relative enrichment of SHMT2 expression in B cell populations. In vitro, SHMT2 was overexpressed in LUAD cells, and its knockdown suppressed proliferation, migration, and clonogenic growth. Collectively, SHMT2 is associated with SGOC metabolic reprogramming, aggressive tumor phenotypes, and an immune-disadvantaged state in LUAD, supporting its potential relevance as a biomarker; therapeutic targeting requires additional pharmacologic and in vivo validation.
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Cardiac SARS-CoV-2 infection is associated with pro-inflammatory transcriptomic alterations within the heart.
AIMS: Cardiac involvement in COVID-19 is associated with adverse outcome. However, it is unclear whether cell-specific consequences are associated with cardiac SARS-CoV-2 infection. Therefore, we investigated heart tissue utilizing in situ hybridization, immunohistochemistry, and RNA-sequencing in consecutive autopsy cases to quantify virus load and characterize cardiac involvement in COVID-19. METHODS AND RESULTS: In this study, 95 SARS-CoV-2-positive autopsy cases were included. A relevant SARS-CoV-2 virus load in the cardiac tissue was detected in 41/95 deceased (43%). Massive analysis of cDNA ends (MACE)-RNA-sequencing was performed to identify molecular pathomechanisms caused by the infection of the heart. A signature matrix was generated based on the single-cell dataset 'Heart Cell Atlas' and used for digital cytometry on the MACE-RNA-sequencing data. Thus, immune cell fractions were estimated and revealed no difference in immune cell numbers in cases with and without cardiac infection. This result was confirmed by quantitative immunohistological diagnosis. MACE-RNA-sequencing revealed 19 differentially expressed genes (DEGs) with a q-value <0.05 (e.g. up: IFI44L, IFT3, TRIM25; down: NPPB, MB, MYPN). The upregulated DEGs were linked to interferon pathways and originate predominantly from endothelial cells. In contrast, the downregulated DEGs originate predominately from cardiomyocytes. Immunofluorescent staining showed viral protein in cells positive for the endothelial marker ICAM1 but rarely in cardiomyocytes. The Gene Ontology (GO) term analysis revealed that downregulated GO terms were linked to cardiomyocyte structure, whereas upregulated GO terms were linked to anti-virus immune response. CONCLUSION: This study reveals that cardiac infection induced transcriptomic alterations mainly linked to immune response and destruction of cardiomyocytes. While endothelial cells are primarily targeted by the virus, we suggest cardiomyocyte destruction by paracrine effects. Increased pro-inflammatory gene expression was detected in SARS-CoV-2-infected cardiac tissue but no increased SARS-CoV-2 associated immune cell infiltration was observed.
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An age-and sex-matched postoperative therapy should be required in thyroid papillary carcinoma.
BACKGROUND AND PURPOSE: Thyroid papillary carcinoma (PTC) had a high possibility of recurrence after surgery, and thyroid stimulating hormone (TSH) suppression and radioactive iodine (131I) were used for postoperative therapy. This study explored the potential mechanism of lymph node metastasis (LNM) and aimed to develop differentiated treatments for PTC. METHOD: This study explored the risk factors of lymph node metastasis in PTC by analyzing the clinical information of 2073 cases. The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) and the Gene Expression Omnibus (GEO) databases of gene expression were analyzed to identify the interrelationships between gene expression to phenotype. RESULTS: Analyzing clinical data, we found that male gender, younger age, larger tumor size, and extra-thyroidal extension (ETE) were risk significant risk factors for lymph node metastasis(P<0.05). Conversely, thyroid function parameters such as TSH, FT3, FT4, TSH/FT3, and TSH/FT4 didn't correlate with LNM(P>0.05), and TSH levels were observed to be higher in females(P<0.05). Gene expression analysis revealed that SLC5A5 was down-regulated in males, younger individuals, and those with lymph node metastasis, and a lower level of SLC5A5 was associated with a worse disease-free survival(P<0.05). Additionally, our examination of single-cell RNA sequencing (scRNA-seq) data indicated that SLC5A5 expression was reduced in tumors and lymph node metastasis samples, correlating positively with the expression of TSHR. CONCLUSION: The impact of TSH on PTC behavior remained unclear, while the capacity for absorbing 131I in dependence on SLC5A5 showed variations across different genders and ages. We conclude that postoperative treatment of PTC should take into account the differences caused by gender and age.