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Single cell transcriptomic analysis reveals molecular mechanisms of chemoresistance and immune microenvironment remodeling in ovarian cancer.
BACKGROUND: Chemotherapy resistance remains a major clinical challenge in ovarian cancer treatment, limiting therapeutic efficacy and patient survival. Understanding the molecular mechanisms underlying chemoresistance at the single-cell level is crucial for developing targeted therapeutic strategies. METHODS: We performed comprehensive single-cell RNA sequencing analysis on primary and chemoresistant ovarian cancer samples to characterize cellular heterogeneity and identify resistance-associated molecular signatures. Cell type identification, differential gene expression analysis, functional enrichment analysis, and immune microenvironment characterization were conducted to elucidate chemoresistance mechanisms. Computational predictions were validated by RT-qPCR analysis of four key resistance genes (BIRC5, ABCB1A, ABCG2, BCL2) in SKOV3 and SKOV3-CDDP cell lines. RESULTS: Our analysis identified nine distinct cell populations within the ovarian cancer microenvironment, revealing extensive transcriptional reprogramming in chemoresistant tumors. Key chemoresistance genes including Abcb1a, Abcg2, Bcl2, Birc5, Nek2, Inhba, Irs1, and Prc1 showed differential expression patterns across cell types. Epithelial cells and proliferating cells exhibited elevated expression of multiple resistance markers, particularly Birc5. Functional analysis revealed enrichment of ribosome biogenesis, protein synthesis machinery, and amoeboid-type cell migration pathways in resistant cells. Macrophage polarization states were significantly altered, and immune checkpoint molecules showed coordinated upregulation, indicating comprehensive immune microenvironment reprogramming. RT-PCR validation confirmed single-cell predictions with significant upregulation in resistant cells: BIRC5 (4.2-fold, p < 0.001), ABCB1A (3.8-fold, p < 0.001), ABCG2 (2.9-fold, p < 0.01), and BCL2 (2.1-fold, p < 0.05). CONCLUSIONS: This study provides a comprehensive single-cell atlas of chemoresistance in ovarian cancer, revealing cell type-specific resistance mechanisms and immune evasion strategies. The identified molecular signatures offer potential therapeutic targets for overcoming chemotherapy resistance and improving patient outcomes.
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Comprehensive analysis of KLF2 as a prognostic biomarker associated with fibrosis and immune infiltration in advanced hepatocellular carcinoma.
PURPOSE: Most Hepatocellular carcinoma (HCC) patients are in advanced or metastatic stage at the time of diagnosis. Prognosis for advanced HCC patients is dismal. This study was based on our previous microarray results, and aimed to explore the promising diagnostic and prognostic markers for advanced HCC by focusing on the important function of KLF2. METHODS: The Cancer Genome Atlas (TCGA), Cancer Genome Consortium database (ICGC), and the Gene Expression Comprehensive Database (GEO) provided the raw data of this study research. The cBioPortal platform, CeDR Atlas platform, and the Human Protein Atlas (HPA) website were applied to analyze the mutational landscape and single-cell sequencing data of KLF2. Basing on the results of single-cell sequencing analyses, we further explored the molecular mechanism of KLF2 regulation in the fibrosis and immune infiltration of HCC. RESULTS: Decreased KLF2 expression was discovered to be mainly regulated by hypermethylation, and indicated a poor prognosis of HCC. Single-cell level expression analyses revealed KLF2 was highly expressed in immune cells and fibroblasts. The function enrichment analysis of KLF2 targets indicated the crucial association between KLF2 and tumor matrix. 33-genes related with cancer associated fibroblasts (CAFs) were collected to identify the significant association of KLF2 with fibrosis. And SPP1 was validated as a promising prognostic and diagnostic marker for advanced HCC patients. CXCR6 CD8+ T cells were noted as a predominant proportion in the immune microenvironment, and T cell receptor CD3D was discovered to be a potential therapeutic biomarker for HCC immunotherapy. CONCLUSION: This study identified that KLF2 is an important factor promoting HCC progression by affecting the fibrosis and immune infiltration, highlighting its great potential as a novel prognostic biomarker for advanced HCC.
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Transcriptomic analysis of the ocular posterior segment completes a cell atlas of the human eye.
Although the visual system extends through the brain, most vision loss originates from defects in the eye. Its central element is the neural retina, which senses light, processes visual signals, and transmits them to the rest of the brain through the optic nerve (ON). Surrounding the retina are numerous other structures, conventionally divided into anterior and posterior segments. Here, we used high-throughput single-nucleus RNA sequencing (snRNA-seq) to classify and characterize cells in six extraretinal components of the posterior segment: ON, optic nerve head (ONH), peripheral sclera, peripapillary sclera (PPS), choroid, and retinal pigment epithelium (RPE). Defects in each of these tissues are associated with blinding diseases-for example, glaucoma (ONH and PPS), optic neuritis (ON), retinitis pigmentosa (RPE), and age-related macular degeneration (RPE and choroid). From ~151,000 single nuclei, we identified 37 transcriptomically distinct cell types, including multiple types of astrocytes, oligodendrocytes, fibroblasts, and vascular endothelial cells. Our analyses revealed a differential distribution of many cell types among distinct structures. Together with our previous analyses of the anterior segment and retina, the data presented here complete a "Version 1" cell atlas of the human eye. We used this atlas to map the expression of >180 genes associated with the risk of developing glaucoma, which is known to involve ocular tissues in both anterior and posterior segments as well as the neural retina. Similar methods can be used to investigate numerous additional ocular diseases, many of which are currently untreatable.
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Single-Cell Atlas of the Peripheral Immune Response in Patients With Chronic Hepatitis B.
Cellular immune responses are crucial in determining outcomes of the hepatitis B virus (HBV) infection. Ineffective immune responses enable persistent HBV infection and contribute to progressive liver disease. Understanding the mechanisms underlying immunological HBV tolerance and restoring functional adaptive immune responses is essential for successful chronic hepatitis B (CHB) treatment. This study examined the dysregulated immune responses and immunopathological cell states associated with CHB using single-cell RNA sequencing of peripheral blood mononuclear cells to investigate immune cell composition and transcriptional differences between patients with CHB and healthy donors. Phenotypic alterations in the lymphoid and myeloid compartments were observed following HBV infection. T cell immune profiling in patients with CHB showed enrichment of exhausted CD8+ T cells, impaired cytotoxicity of effector CD8+ T cells, and increased regulatory T cell (Treg) suppressive activity. Immature neutrophils and a unique CD14+ monocyte subset (myeloid-derived suppressor cells) exhibited potent immunosuppressive abilities. A novel population of CD14+CD163+VSIG4+ M2-like macrophages with immunosuppressive and anti-inflammatory phenotypes was enriched in a patient with severe CHB and liver failure, indicating a potential contribution to dysfunctional immune responses. Our study demonstrated immune exhaustion and evasion in chronic HBV infection, elucidating its immunopathological features and suggesting new therapeutic strategies for immune-mediated disorders and unresolved chronic HBV infection.
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Integrating single-cell and bulk RNA sequencing to develop a cancer-associated fibroblast-related signature for immune infiltration prediction and prognosis in lung adenocarcinoma.
BACKGROUND: An accumulating amount of studies are highlighting the impacts of cancer-associated fibroblasts (CAFs) on the initiation, metastasis, invasion, and immune evasion of lung cancer. However, it is still unclear how to tailor treatment regimens based on the transcriptomic characteristics of CAFs in the tumor microenvironment of patients with lung cancer. METHODS: Our study examined single-cell RNA-sequencing data from the Gene Expression Omnibus (GEO) database to identify expression profiles for CAF marker genes and constructed a prognostic signature of lung adenocarcinoma using these genes in The Cancer Genome Atlas (TCGA) database. The signature was validated in 3 independent GEO cohorts. Univariate and multivariate analyses were used to confirm the clinical significance of the signature. Next, multiple differential gene enrichment analysis methods were used to explore the biological pathways related to the signature. Six algorithms were used to assess the relative proportion of infiltrating immune cells, and the relationship between the signature and immunotherapy response of lung adenocarcinoma (LUAD) was explored based on the tumor immune dysfunction and exclusion (TIDE) algorithm. RESULTS: The signature related to CAFs in this study showed good accuracy and predictive capacity. In all clinical subgroups, the high-risk patients had a poor prognosis. The univariate and multivariate analyses confirmed that the signature was an independent prognostic marker. Moreover, the signature was closely associated with particular biological pathways related to cell cycle, DNA replication, carcinogenesis, and immune response. The 6 algorithms used to assess the relative proportion of infiltrating immune cells indicated that a lower infiltration of immune cells in the tumor microenvironment was associated with high-risk scores. Importantly, we found a negative correlation between TIDE, exclusion score, and risk score. CONCLUSIONS: Our study constructed a prognostic signature based on CAF marker genes useful for prognosis and immune infiltration estimation of lung adenocarcinoma. This tool could enhance therapy efficacy and allow individualized treatments.
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Identification and validation of anoikis-related genes to clarify the prognosis and immune mechanisms of patients with low-grade glioma.
BACKGROUND: Low-grade glioma (LGG) has an extremely poor prognosis, and the mechanism leading to malignant development has not been determined. The aim of our study was to clarify the function and mechanism of anoikis and TIMP1 in the malignant progression of LGG. METHODS: We screened 7 anoikis-related genes from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to construct a prognostic-predicting model. The study assessed the clinical prognosis, pathological characteristics, and immune cell infiltration in both high- and low-risk groups. Additionally, the potential modulatory effects of TIMP1 on proliferation, migration, and anoikis in LGG were investigated both in vivo and in vitro. RESULTS: In this study, we identified seven critical genes, namely, PTGS2, CCND1, TIMP1, PDK4, LGALS3, CDKN1A, and CDKN2A. Kaplan‒Meier (K‒M) curves demonstrated a significant correlation between clinical features and overall survival (OS), and single-cell analysis and mutation examination emphasized the heterogeneity and pivotal role of hub gene expression imbalances in LGG development. Immune cell infiltration and microenvironment analysis further elucidated the relationships between key genes and immune cells. In addition, TIMP1 promoted the malignant progression of LGG in both in vitro and in vivo models. CONCLUSIONS: This study confirmed that TIMP1 promoted the malignant progression of LGG by inhibiting anoikis, providing insights into LGG pathogenesis and potential therapeutic targets.
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Single-cell transcriptome analysis of human skin identifies novel fibroblast subpopulation and enrichment of immune subsets in atopic dermatitis.
BACKGROUND: Atopic dermatitis (AD) is a prevalent inflammatory skin disease with a complex pathogenesis involving immune cell and epidermal abnormalities. Despite whole tissue biopsy studies that have advanced the mechanistic understanding of AD, single cell-based molecular alterations are largely unknown. OBJECTIVE: Our aims were to construct a detailed, high-resolution atlas of cell populations and assess variability in cell composition and cell-specific gene expression in the skin of patients with AD versus in controls. METHODS: We performed single-cell RNA sequencing on skin biopsy specimens from 5 patients with AD (4 lesional samples and 5 nonlesional samples) and 7 healthy control subjects, using 10× Genomics. RESULTS: We created transcriptomic profiles for 39,042 AD (lesional and nonlesional) and healthy skin cells. Fibroblasts demonstrated a novel COL6A5+COL18A1+ subpopulation that was unique to lesional AD and expressed CCL2 and CCL19 cytokines. A corresponding LAMP3+ dendritic cell (DC) population that expressed the CCL19 receptor CCR7 was also unique to AD lesions, illustrating a potential role for fibroblast signaling to immune cells. The lesional AD samples were characterized by expansion of inflammatory DCs (CD1A+FCER1A+) and tissue-resident memory T cells (CD69+CD103+). The frequencies of type 2 (IL13+)/type 22 (IL22+) T cells were higher than those of type 1 (IFNG+) in lesional AD, whereas this ratio was slightly diminished in nonlesional AD and further diminished in controls. CONCLUSION: AD lesions were characterized by expanded type 2/type 22 T cells and inflammatory DCs, and by a unique inflammatory fibroblast that may interact with immune cells to regulate lymphoid cell organization and type 2 inflammation.
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Single cell RNA sequencing reveals ferritin as a key mediator of autoimmune pre-disposition in a mouse model of systemic lupus erythematosus.
Systemic lupus erythematosus (SLE) is a devastating autoimmune disorder characterized by failure of self-tolerance with resultant production of autoreactive antibodies. The etiology of this syndrome is complex, involving perturbations in immune cell signaling and development. The NZBWF1 mouse spontaneously develops a lupus-like syndrome and has been widely used as a model of SLE for over 60 years. The NZBWF1 model represents the F1 generation of a cross between New Zealand Black (NZB) and New Zealand White (NZW) mice. In order to better understand the factors that contribute to the development of autoimmunity, single cell RNA sequencing was conducted using the bone marrow from female NZBWF1 mice prior to the development of overt disease. The results were contrasted with single cell RNA sequencing results from the two parental strains. The expected findings of B cell abundance and upregulation, and evidence of interferon signaling were validated in this model. In addition, several novel areas of inquiry were identified. Most notably, the data showed a marked upregulation of the ferritin light chain across all cell types in the NZBWF1 mice compared to parental controls. This data can serve as a gene expression atlas of all hematopoietic cells in the NZBWF1 bone marrow prior to the development of autoimmunity.
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Integration of 117 machine learning algorithms and single-cell transcriptomics identifies macrophage polarization and ER stress signatures for cancer prognosis and precision therapy.
BACKGROUND: Macrophage polarization and endoplasmic reticulum (ER) stress play critical yet incompletely understood roles in cancer progression and therapeutic resistance. METHODS: Here, we conduct a systematic pan-cancer analysis of macrophage polarization and ER stress-related genes (MPERSRGs) by integrating multi-omics data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and single-cell RNA sequencing datasets across 33 cancer types. RESULTS: We identify distinct expression patterns of seven core MPERSRGs (CEBPB, NUPR1, ATF3, CASP3, TNFSF10, BRSK2, NOD2) that correlate significantly with tumor stage, immune infiltration, and patient prognosis. Employing 117 machine learning algorithm combinations, we develop a robust five-gene prognostic signature (FAM83A, RHOV, CPS1, STRIP2, SLC2A1) for lung adenocarcinoma (LUAD) with area under the curve values of 0.692, 0.688, and 0.614 for 1-, 3-, and 5-year overall survival, respectively. Single-cell transcriptomic analysis of 86,378 cells reveals three functionally distinct fibroblast subpopulations (MFAP5+, MATK+, HP+) with differential MPERSRG expression profiles, with MFAP5 + fibroblasts showing the highest enrichment in epithelial-mesenchymal transition and angiogenesis pathways. Cell-cell communication analysis identifies fibroblasts and epithelial cells as the most interactive populations, with the CLEC2C-KLRB1 ligand-receptor pair mediating the strongest signaling between mast cells and NK cells. Drug sensitivity predictions across multiple databases identify vorinostat, nilotinib, olaparib, and paclitaxel as potential therapeutic agents showing differential efficacy based on MPERSRG expression stratification. CONCLUSIONS: These findings establish MPERSRGs as key determinants of tumor-immune interactions and provide actionable biomarkers for risk stratification and precision therapy selection in cancer.
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Dissecting the dynamic cellular transcriptional atlas of adult teleost testis development throughout the annual reproductive cycle.
Teleost testis development during the annual cycle involves dramatic changes in cellular compositions and molecular events. In this study, the testicular cells derived from adult black rockfish at distinct stages - regressed, regenerating and differentiating - were meticulously dissected via single-cell transcriptome sequencing. A continuous developmental trajectory of spermatogenic cells, from spermatogonia to spermatids, was delineated, elucidating the molecular events involved in spermatogenesis. Subsequently, the dynamic regulation of gene expression associated with spermatogonia proliferation and differentiation was observed across spermatogonia subgroups and developmental stages. A bioenergetic transition from glycolysis to mitochondrial respiration of spermatogonia during the annual developmental cycle was demonstrated, and a deeper level of heterogeneity and molecular characteristics was revealed by re-clustering analysis. Additionally, the developmental trajectory of Sertoli cells was delineated, alongside the divergence of Leydig cells and macrophages. Moreover, the interaction network between testicular micro-environment somatic cells and spermatogenic cells was established. Overall, our study provides detailed information on both germ and somatic cells within teleost testes during the annual reproductive cycle, which lays the foundation for spermatogenesis regulation and germplasm preservation of endangered species.