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Integrated Single-Cell RNA-Sequencing Analysis of Gastric Cancer Identifies FABP1 as a Novel Prognostic Biomarker.
Gastric cancer (GC) is usually diagnosed in an advanced stage at the first visit due to the atypical clinical symptoms. The low surgical resection rate and chemotherapy sensitivity result in dismal survival. Therefore, it is urgent to develop novel biomarkers with high sensitivity and specificity to accurately assess the prognosis of GC patients. In the present study, 3385 differentially expressed genes (DEGs) were obtained from the single-cell RNA sequencing data of GC specimens. Using the unsupervised dimensionality reduction, we further found 3 subsets of cells including gastric cells, plasmacytoid dendritic cells, and memory T cells. Based on the cell clustering, we explored the key regulatory genes for GC progression by pseudo-time analysis and functional enrichment analysis. According to the results, the significant differentially expressed fatty acid-binding protein 1 (FABP1) verified by pseudo-time analysis was identified as the hub gene of GC progression. FABP1 was shown to be closely related to the long-term survival and the age at diagnosis of patients with GC in analysis based on the TCGA (The Cancer Genome Atlas) database. To further verify the role of FABP1 in GC, we performed immunohistochemical (IHC) analysis using the GC tissue microarray and found that the expression level of FABP1 was higher in GC tissues than in the adjacent tissues. Moreover, GC patients with higher expression of FABP1 had a worse clinical outcome. In summary, our study revealed that FABP1 is a potential effective biomarker for the prognosis of GC, and high expression of FABP1 predicts unsatisfactory survival.
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Single-nucleus profiling reveals age-associated remodeling opposed by parity in the postmenopausal human ovary.
The postmenopausal ovary is commonly viewed as a passive organ, and its biology and cell composition remain incompletely characterized. Here, we generated a single-nucleus atlas of the aging postmenopausal human ovary comprising 439,011 nuclei across 64 ovarian samples from 28 donors. We resolved 37 fine cell states, revealing extensive stromal, vascular, and immune heterogeneity in the postmenopausal ovary. Aging was associated with stromal stress-state expansion, vascular and immune depletion, and enrichment of steroidogenic programs consistent with ovarian androgenization. Several major age-associated compositional shifts were supported in an independent GTEx ovary bulk RNA-seq cohort. Notably, the number of live births broadly opposed age-associated transcriptional and compositional remodeling. Together, our findings show that the postmenopausal ovary remains an actively remodeled aging tissue and that reproductive history leaves durable molecular and cellular imprints on ovarian aging.
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Diverse Landscape of Group 1 Innate Lymphoid Cells Predicts the Prognosis in Patients with Head and Neck Squamous Cell Carcinoma.
Objectives: Innate lymphoid cells (ILCs) and natural killer (NK) cells represent a diverse group of innate immune populations that modulate immune responses and tissue equilibrium across various diseases, including cancer. In the present study, we analyzed single-cell RNA sequencing (scRNA-seq) data to explore the landscape and functional status of ILC subsets in patients with head and neck squamous cell carcinoma (HNSCC). Methods: The GSE164690 dataset, which includes preprocessed scRNA-seq and clinical data, was acquired from the Gene Expression Omnibus database. The Cancer Genome Atlas database was used to develop the survival prediction model. Results: A total of 95,809 immune cells were clustered into 16 immune cell clusters, among which 7278 NK cells were further subdivided into 11 clusters. Among the 11 clusters, eight NK cell clusters, two intraepithelial ILC1 (ieILC1) clusters, and one ieILC1-NK-intermediate (ieILC1-NK-int) cluster were identified. Among the ieILC1/NK clusters, ieILC1-1 exhibited the highest immunological activity and was mainly derived from human papillomavirus-positive samples. Further, ieILC1s showed higher enrichment of pathways related to inflammation and effector functions-such as inflammatory response, interferon-gamma response, and interferon-alpha response-compared to the other clusters. Moreover, we developed prognostic prediction models based on differentially expressed genes in the ieILC1/NK clusters. Risk scores of the ieILC1-1, ieILC1-NK-int, and NK clusters were identified as independent prognostic factors for shorter overall survival (OS) and progression-free survival (PFS). Recursive partitioning revealed that combining ieILC1-1 and the NK clusters strongly predicted shorter OS and PFS. Conclusions: Our findings highlight the diverse landscape and prognostic significance of ieILC1/NK cells in patients with HNSCC.
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Single-cell Transcriptomic Profiling Reveals Novel Stem Cell Markers for Corneal Limbal Epithelium Homeostasis.
Sox9 is a well-established marker of skin epithelial hair follicle stem cells and has been observed in the corneal limbus of Sox9-EGFP transgenic mice. Using Sox9-EGFP as a reference marker, this study characterized the transcriptomic atlas of corneal limbal epithelial cells during homeostasis and identified novel markers of limbal stem cells (LSCs) by single-cell RNA sequencing (scRNA-seq). A total of 21,066 viable cells were profiled, revealing 13 distinct cell clusters with unique molecular signatures. The cluster enriched with EGFP-positive cells was identified as the putative LSCs population during corneal epithelial homeostasis. Comparative analysis of corneal LSCs and early differentiated cells revealed several differentially expressed genes (DEGs) strongly associated with stemness-related pathways, including Gabrp, Fmo1, Fmo2, and Alcam, which were identified as potential novel LSC markers. These genes were exclusively expressed in the limbus, as confirmed by quantitative PCR (qPCR), Western blotting, and immunofluorescence staining. This study delineated the heterogeneous cellular composition of the limbal epithelium and uncovered several novel candidate markers that may be critical for maintaining corneal epithelial homeostasis.
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Optimized GLORI-Seq of Chromatin-Associated RNAs.
N6-methyladenosine (m6A) is a prevalent endogenous modification in mammalian mRNAs as well as chromatin-associated RNAs (caRNAs). Recently developed GLORI-seq, which chemically converts unmodified adenosine to inosine, enables absolute quantification of single-base-resolution m6A sites on mRNAs. However, since GLORI-seq generates short-transited reads with mainly three kinds of nucleotides, applying it to caRNAs with a large fraction of intronic and intergenic regions poses additional challenges. In our recent study, we simply optimized the library construction of GLORI-seq to enrich long cDNA fragments for subsequent sequencing, resulting in significantly promoted read length and mapping accuracy of GLORI-seq on caRNAs. Here, we describe the detailed protocol of optimized GLORI-seq of caRNAs to facilitate studies on m6A in caRNAs.
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Single-cell and machine learning approaches uncover intrinsic immune-evasion genes in the prognosis of hepatocellular carcinoma.
BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) is a tumor of high heterogeneity and complexity, which poses significant challenges to effective treatment and patient prognosis because of its immune evasion characteristics. To address these issues, single-cell technology and machine learning methods have emerged as a promising approach to identify genes associated with immune escape in HCC. This study aimed to develop a prognostic risk score model for HCC by identifying intrinsic immune-evasion genes (IIEGs) through single-cell technology and machine learning, providing insights into immune infiltration, enhancing predictive accuracy, and facilitating the development of more effective treatment strategies. MATERIALS AND METHODS: The study utilized data from The Cancer Genome Atlas database to analyze gene expression profiles and clinical data related to intrinsic immune evasion in patients with HCC. Various tools, including the Human Protein Atlas, cBioPortal, single-cell analysis, machine learning, and Kaplan-Meier plot, were used to analyze IIEGs. Functional enrichment analysis was conducted to explore potential mechanisms. In addition, the abundance of infiltrating cells in the tumor microenvironment was investigated using single-sample gene set enrichment analysis, CIBERSORT, xCELL, and tumor immunophenotype algorithms. The expression of glycosylphosphatidylinositol anchor attachment 1 (GPAA1) was examined in the clinical sample of HCC by quantitative real-time polymerase chain reaction, Western blotting, and immunohistochemical staining. RESULTS: Univariate Cox analysis identified 63 IIEGs associated with the prognosis of HCC. Using random forest, least absolute shrinkage and selection operator regression analysis, and support vector machine, a risk score model consisting of six IIEGs (carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD), phosphatidylinositol glycan anchor biosynthesis class U (PIGU), endoplasmic reticulum membrane protein complex subunit 3 (EMC3), centrosomal protein 55 (CEP55), autophagy-related 10 (ATG10), and GPAA1) developed, which was validated using 10 pairs of HCC and adjacent non-cancerous samples. Based on the calculated median risk score, HCC samples were categorized into high- and low-risk groups. The Kaplan-Meier curve analysis showed that the high-risk group had a worse prognosis compared with the low-risk group. Time-dependent receiver operating characteristic analysis demonstrated the accurate predictive capability of the risk score model for HCC prognosis. Furthermore, immune infiltration analysis showed a positive correlation between the risk score model and 40 immune checkpoint genes as well as Th2 cells. CONCLUSIONS: A prognostic risk score model was formulated by six IIEG signatures and showed promise in predicting the prognosis of patients diagnosed with HCC. The utilization of the IIEG risk score as a novel prognostic index, together with its significance as a valuable biomarker for immunotherapy in HCC, provides benefit for patients with HCC in determining therapeutic strategies for clinical application.
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Microenvironmental niches dictate divergent fibroblast fates in reversible versus progressive lung fibrosis.
BACKGROUND: Fibroblast behaviour is a key determinant of outcomes in interstitial lung diseases (ILDs), yet mechanisms governing the switch between reversible repair and progressive fibrosis remain unclear. How disease-specific cellular niches shape fibroblast fate across ILD phenotypes has not been compared in situ. METHODS: We profiled peripheral lung tissues from controls, organising pneumonia (OP), connective tissue disease-associated ILD (CTD-ILD), and idiopathic pulmonary fibrosis (IPF) using High-Definition Visium spatial transcriptomics. A matched single-cell RNA-seq atlas was integrated via robust cell-type deconvolution to map cellular neighbourhoods. Differential expression and pathway activity were validated by immunofluorescence. Predicted ligand-receptor mechanisms and fibroblast responses were tested in vitro under glucocorticoid (GC), TGF-β1, and B-cell/MIF perturbations with receptor blockade. FINDINGS: Disease-specific niches were tightly coupled to fibroblast states. OP exhibited B-cell-AT2-myofibroblast-enriched niches with high GC responsiveness and apoptosis. IPF was dominated by bronchiolised epithelium, alongside myofibroblasts exhibiting glucocorticoid resistance and strong matrix programmes. CTD-ILD exhibited macrophage-rich niches with multinucleated giant cells. In vitro, GC induced NR3C1-mediated apoptosis in fibroblasts, whereas TGF-β1 drove a senescent, GC-resistant phenotype. IgD + B-cell-derived MIF enhanced fibroblast migration via CD74, an effect blunted by TGF-β1. Thus, niche composition dictates fibroblast fate, distinguishing GC-sensitive resolution from apoptosis-resistant fibrosis. INTERPRETATION: A GC-sensitive, apoptosis-prone myofibroblast niche in OP may underpin reversibility, whereas CTD-ILD and IPF follow distinct trajectories driven by immune dysregulation and epithelial-stromal maladaptation. These spatial microenvironmental signatures nominate therapeutic targets and may inform precision therapy for fibrotic lung disease. FUNDING: The National Natural Science Foundation of China (82172109 to L.X., 82570001 to H.C.), the Ministry of Science and Technology of the People's Republic of China (2023YFC3502605, 2024YFA1108906) (H.C.), the Natural Science Foundation of Tianjin, China (25JCZDJC01260) (H.C.); the Key Laboratory of Medical Rescue Key Technology and Equipment, Ministry of Emergency Management (Open Fund Project No. YJBKFKT202410).
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Revealing the Organ-Specific Expression of SPTBN1 using Single-Cell RNA Sequencing Analysis.
Despite the recent technological advances in single-cell RNA sequencing, it is still unknown how three marker genes (SPTBN1, EPDR1, and PKDCC), which are associated with bone fractures and highly expressed in the muscle tissue, are contributing to the development of other tissues and organs at the cellular level. This study aims to analyze three marker genes at the single-cell level using 15 organ tissue types of adult human cell atlas (AHCA). The single-cell RNA sequencing analysis used three marker genes and a publicly available AHCA data set. AHCA data set contains more than 84,000 cells from 15 organ tissue types. Quality control filtering, dimensionality reduction, clustering for cells, and data visualization were performed using the Seurat package. A total of 15 organ types are included in the downloaded data sets: Bladder, Blood, Common Bile Duct, Esophagus, Heart, Liver, Lymph Node, Marrow, Muscle, Rectum, Skin, Small Intestine, Spleen, Stomach, and Trachea. In total, 84,363 cells and 228,508 genes were included in the integrated analysis. A marker gene of SPTBN1 is highly expressed across all 15 organ types, particularly in the Fibroblasts, Smooth muscle cells, and Tissue stem cells of the Bladder, Esophagus, Heart, Muscle, Rectum, Skin, and Trachea. In contrast, EPDR1 is highly expressed in the Muscle, Heart, and Trachea, and PKDCC is only expressed in Heart. In conclusion, SPTBN1 is an essential protein gene in physiological development and plays a critical role in the high expression of fibroblasts in multiple organ types. Targeting SPTBN1 may prove beneficial for fracture healing and drug discovery.
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Delineating the dynamic evolution from preneoplasia to invasive lung adenocarcinoma by integrating single-cell RNA sequencing and spatial transcriptomics.
The cell ecology and spatial niche implicated in the dynamic and sequential process of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) have not yet been elucidated. Here, we performed an integrative analysis of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to characterize the cell atlas of the invasion trajectory of LUAD. We found that the UBE2C + cancer cell subpopulation constantly increased during the invasive process of LUAD with remarkable elevation in IAC, and its spatial distribution was in the peripheral cancer region of the IAC, representing a more malignant phenotype. Furthermore, analysis of the TME cell type subpopulation showed a constant decrease in mast cells, monocytes, and lymphatic endothelial cells, which were implicated in the whole process of invasive LUAD, accompanied by an increase in NK cells and MALT B cells from AIS to MIA and an increase in Tregs and secretory B cells from MIA to IAC. Notably, for AIS, cancer cells, NK cells, and mast cells were colocalized in the cancer region; however, for IAC, Tregs colocalized with cancer cells. Finally, communication and interaction between cancer cells and TME cell-induced constitutive activation of TGF-β signaling were involved in the invasion of IAC. Therefore, our results reveal the specific cellular information and spatial architecture of cancer cells and TME subpopulations, as well as the cellular interaction between them, which will facilitate the identification and development of precision medicine in the invasive process of LUAD from AIS to IAC.
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A single-cell atlas of the developing Drosophila ovary identifies follicle stem cell progenitors.
Addressing the complexity of organogenesis at a system-wide level requires a complete understanding of adult cell types, their origin, and precursor relationships. The Drosophila ovary has been a model to study how coordinated stem cell units, germline, and somatic follicle stem cells maintain and renew an organ. However, lack of cell type-specific tools have limited our ability to study the origin of individual cell types and stem cell units. Here, we used a single-cell RNA sequencing approach to uncover all known cell types of the developing ovary, reveal transcriptional signatures, and identify cell type-specific markers for lineage tracing. Our study identifies a novel cell type corresponding to the elusive follicle stem cell precursors and predicts subtypes of known cell types. Altogether, we reveal a previously unanticipated complexity of the developing ovary and provide a comprehensive resource for the systematic analysis of ovary morphogenesis.