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Immunosuppression of HMOX1 contributes to metastasis and poor prognosis in glioma.
BACKGROUND: Glioma is the most prevalent form of brain cancer, characterized by immunosuppression and heterogeneity. Recently, numerous genes associated with immunosuppression have been identified in glioma. Nevertheless, the molecular mechanisms underlying this immunosuppression remain unclear. In this study, we aim to delineate the relationship between HMOX1 and cancer-related immunosuppression in glioma. METHODS: Two GEO datasets were selected for assessment the expression of HMOX1. The Chinese Glioma Genome Atlas (CGGA, 693 patients) and the Cancer Genome Atlas (TCGA, 702 patients) were analyzed using R software. Additionally, single-cell RNA sequencing (scRNA-seq) data from CGGA were also analyzed. Cell experiments and xenograft model were carried out to validate the role of HMOX1 in glioma metastasis. RESULTS: Two GEO datasets revealed a significantly increased expression of HMOX1 in glioma. This upregulation of HMOX1 was associated with WHO grade 4, IDH wild-type, 1p/19q non-codeletion, and poor survival in both CGGA and TCGA datasets. GO, KEGG, and GSVA analyses indicated that immune-related pathways were the most dysregulated processes. We observed infiltration of M2 macrophages and activation of checkpoint genes in HMOX1-upregulated glioma. ScRNA-seq analysis showed that HMOX1 was upregulated in M2 macrophages, indicating the association between HMOX1 upregulation and polarization of M2 macrophages. Knockdown HMOX1 reduced the growth and metastasis of glioma cells in vitro and in vivo. Co-cultured HMOX1-inhibited M2 macrophages with glioma cells decreased the invasive ability of glioma cells. CONCLUSION: In glioma, high expression of HMOX1 was associated with cancer-related immunosuppression through polarization of M2 macrophages. Moreover, knockdown HMOX1 reduced the growth and metastasis of tumor cells in vitro and in vivo. These findings suggested that HMOX1 could serve as a prognostic factor for glioma.
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Molecular subtyping and prognostic modeling of non-small cell lung cancer based on disulfidptosis-related genes.
BACKGROUND: Non-small cell lung cancer (NSCLC) shows substantial molecular and immune heterogeneity, and prognosis varies widely even among patients with similar clinicopathologic stage, highlighting the need for biologically grounded biomarkers. Disulfidptosis is a newly described form of regulated cell death triggered by disulfide stress and linked to tumor metabolic vulnerability, but its molecular patterns and prognostic relevance in NSCLC remain unclear. This study aimed to define disulfidptosis-related molecular subtypes in NSCLC, construct and externally validate a disulfidptosis-based prognostic gene signature, and investigate its associations with the tumor immune microenvironment (TIME) and potential immunotherapy response. METHODS: We analyzed NSCLC gene expression and clinical follow-up data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Initial unsupervised clustering identified disulfidptosis-related molecular subtypes. Further analysis used weighted gene co-expression network analysis (WGCNA), univariate and least absolute shrinkage and selection operator (LASSO)-COX regression, and stepwise Cox regression to identify disulfidptosis-related prognostic genes, which were then validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) in surgically resected NSCLC tumor specimens in our center. A Disulfidptosis Score-based risk model was built and evaluated with Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves. Single-cell RNA sequencing (RNA-seq) data characterised gene-expression patterns in the TIME. RESULTS: Two molecular subtypes (C1 and C2) based on 16 disulfidptosis genes were identified, among which subtype C2 had a lower immune infiltration score and poorer prognosis. Furthermore, eight disulfidptosis-related prognostic genes were identified and validated through our local cohort by RT-PCR. The Disulfidptosis Score-based on these eight genes effectively stratified patients into high- and low-risk categories. Kaplan-Meier analysis demonstrated that disulfidptosis-related genes were significantly associated with survival outcomes. A prognostic model based on the Disulfidptosis Score and Stage was validated using independent datasets, and the area under the curve (AUC) was 0.728, 0.763, and 0.73 at one, three and five years respectively. Single-cell analysis revealed the expression of disulfidptosis-related prognostic genes across various immune cell types, particularly in plasma cells. CONCLUSIONS: This study identified disulfidptosis-related gene characteristics and their correlation with tumor microenvironment and prognosis in NSCLC. These findings could provide new insights into NSCLC heterogeneity and offer potential biomarkers for prognosis and therapeutic strategies.
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Identification of estrogen response-associated STRA6+ granulosa cells within high-grade serous ovarian carcinoma by single-cell sequencing.
BACKGROUND: High-grade serous ovarian carcinoma (HGSOC) is a pathologic subtype of ovarian cancer (OC) with a more lethal prognosis. Extensive heterogeneity results in HGSOC being more susceptible to treatment resistance and adverse treatment effects. Revealing the heterogeneity involved is crucial. METHODS: We downloaded the single-cell RNA-seq (scRNA) data from GEO database and performed a scRNA analysis for cell landscape of HGSOC by using the Seurat package. The highly expressed genes were uploaded into the DAVID and KEGG database for enrichment analysis, and the AUCell package was used to calculate cancer-associated hallmark score. The SCENIC analysis was used for key regulons, the estrogen response enrichment scores in TCGA-OV RNA-seq dataset were calculated by using the GSVA package. Besides, the expression of STRA6 and IRF1 and the cell invasion and migration in si-STRA6 OC cells were detected by using the quantitative reverse transcription (qRT)-PCR method and Transwell assay respectively. RESULTS: We successfully constructed a single-cell atlas of HGSOC and delineated the heterogeneity of epithelial cells therein. There were five epithelial cell subpopulations, GLDC + Epithelial cells, PEG3+ leydig cells, STRA6+ granulosa cells, POLE2+ Epithelial cells, and AURKA + Epithelial cells. STRA6+ granulosa cells have the potential to promote tumor growth as well as the highest estrogen response early activity through the biological pathways analysis of highly expressed genes and estrogen response score of ssGSEA. We found that IRF1 and STRA6 expression was remarkably upregulated in the OC cancer cell line HEY. Silencing of STRA6 markedly decreased the invasion and migration ability of the OC cancer cell line HEY. CONCLUSION: There is extreme heterogeneity of epithelial cells in HGSOC, and STRA6+ granulosa cells may be able to promote cancer progression. Our findings are benefit to the heterogeneity identification of HGSOC and develop targeted therapy strategy for HGSOC patients.
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Genome-wide identification of long non-coding RNAs in pigs and their roles in muscle development.
OBJECTIVE: Long non-coding RNAs (lncRNAs) regulates complex traits in pigs and the systematic annotation and functional roles of these genes remain poorly understood. This study aimed to construct a comprehensive porcine lncRNA atlas and explore the regulatory role of lncRNAs in muscle development. METHODS: We used 8,871 strand-specific RNA-seq datasets to identify porcine lncRNAs. Their transcriptional characteristics, tissue specificity, evolutionary conservation, and expression quantitative trait locus (eQTL)-supported regulatory relationships were esamined. Single-cell RNA-seq, Hi-C, H3K27ac ChIP-seq, and population differentiation analyses were further incorporated to investigate candidate lncRNAs involved in muscle development. RESULTS: We identified 50,203 porcine lncRNA genes with greater tissue specificity and lower expression levels than protein-coding genes. A subset of lncRNAs showed sequence conservation across mammals. Integration with pigGTEx data identified extensive eQTLsupported lncRNA-mRNA candidate regulatory pairs enriched in active promoter and enhancer chromatin states. Single-cell and multi-omics analyses highlighted PRANCR as a candidate regulator of postnatal muscle growth in Laiwu pigs. A highly distinct enhancer variation (chr5:g.34155013T>C; Sscrofa11.1) could affect SOX8 binding and regulate PRANCR expression in satellite stem cells. CONCLUSION: The current study provides the most comprehensive porcine lncRNA resource currently available and proposes a potential enhancer-lncRNA regulatory mechanism that contributes to muscle development in pigs.
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DIAPH3 is upregulated in high-grade gliomas and linked to chromosomal instability.
ABSTRACT: BackgroundDiaphanous-related formin 3 (DIAPH3) is a member of the formin family, a group of proteins that regulate actin and microtubule dynamics. During mitosis, DIAPH3 localizes specifically to the centrosome. Its loss destabilizes microtubules and disrupts mitotic spindle polarity, leading to multipolar mitoses and abnormal chromosome segregation, which ultimately causes aneuploidy in daughter cells. METHODS: We investigated DIAPH3 expression in glioma samples-including low-grade and high-grade gliomas-using publicly available datasets (The Cancer Genome Atlas and a single-cell RNA-seq study). We also explored the impact of DIAPH3 expression on aneuploidy in cultured glioblastoma cells. RESULTS: DIAPH3 expression was specifically increased in grade 4 gliomas. However, its prognostic value did not surpass that of the WHO CNS5 glioma classification. DIAPH3 was predominantly expressed in mitotic cells and showed strong coexpression with genes involved in cell division, particularly those regulating mitotic progression and chromosome segregation. Several transcription factors known to drive proliferation and cancer progression may regulate DIAPH3 expression. In glioblastoma cell lines, we confirmed that DIAPH3 is upregulated during mitosis and that its knockdown increases aneuploidy. CONCLUSIONS: These findings confirm the role of DIAPH3 in chromosome segregation in clinical glioma samples and demonstrate its association with high-grade, poor-prognosis gliomas.
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Pinpointing Cell Identity in Time and Space.
Mammalian cells display a broad spectrum of phenotypes, morphologies, and functional niches within biological systems. Our understanding of mechanisms at the individual cellular level, and how cells function in concert to form tissues, organs and systems, has been greatly facilitated by centuries of extensive work to classify and characterize cell types. Classic histological approaches are now complemented with advanced single-cell sequencing and spatial transcriptomics for cell identity studies. Emerging data suggests that additional levels of information should be considered, including the subcellular spatial distribution of molecules such as RNA and protein, when classifying cells. In this Perspective piece we describe the importance of integrating cell transcriptional state with tissue and subcellular spatial and temporal information for thorough characterization of cell type and state. We refer to recent studies making use of single cell RNA-seq and/or image-based cell characterization, which highlight a need for such in-depth characterization of cell populations. We also describe the advances required in experimental, imaging and analytical methods to address these questions. This Perspective concludes by framing this argument in the context of projects such as the Human Cell Atlas, and related fields of cancer research and developmental biology.
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Multiomics Analysis Reveals CTHRC1+ CAFs Drive Immunosuppressive Niches and Predict Immunotherapy Resistance in Gastric Cancer.
Cancer-associated fibroblasts (CAFs) orchestrate immune-excluded tumor microenvironment (TME), but the CAF heterogeneity remains incompletely understood in gastric cancer (GC). In this study, we integrated multicohort single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and bulk transcriptomic data to construct a comprehensive atlas of the GC TME. Unsupervised clustering identified eight transcriptionally distinct CAF subpopulations, among which CTHRC1+ CAFs were selectively enriched in tumors and showed the strongest association with T cell exclusion. Pseudotemporal trajectory analysis, gene regulatory network inference, and cell-cell communication analysis revealed that basic helix-loop-helix family member e41 (BHLHE41) serves as a key transcription factor driving CTHRC1+ CAF differentiation, whereas spatial analyses demonstrated these fibroblasts contribute to fibrotic niches at the tumor-stroma interface through macrophage migration inhibitory factor (MIF)-mediated signaling. Finally, we developed and validated a CTHRC1+ cancer-associated fibroblast-related risk signature (CRS) that accurately predicts immunotherapy response across independent cohorts. These findings establish CTHRC1+ CAFs as a critical stromal determinant of immune exclusion in GC, suggesting that targeting the CTHRC1+ CAF-MIF axis or applying CRS-guided patient stratification may enhance immunotherapy efficacy.
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Integrative multi-omics analysis identifies stromal-immune crosstalk as a determinant of immunotherapy efficacy and establishes a prognostic signature in gastric cancer.
Immune checkpoint inhibitors like pembrolizumab exhibit variable efficacy in metastatic gastric cancer (GC). This study aimed to identify molecular drivers of pembrolizumab response, explore mechanisms of immune checkpoint inhibitors (ICIs) efficacy, and develop a prognostic signature. Transcriptomic analysis of pembrolizumab-treated GC (TIGER database) identified 165 response-associated differentially expressed genes (DEGs). Functional annotation and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) revealed that responder-upregulated genes (R-DEGs) were enriched in immune activation pathways and mainly localized to CD8 + T/NK cells. In contrast, non-responder-upregulated genes (D-DEGs) were linked to extracellular matrix (ECM) remodeling and mainly expressed in fibroblasts/endothelial cells. CellChat analysis demonstrated that key DEGs mediate immune-stromal crosstalk via MHC-I and collagen/laminin signaling. A prognostic signature (Lasso-StepCox[forward] Riskscore; LSR: APOD, APOH, BATF2, GJA1, MAGED1, SLC5A1, SLCO2A1, VWF, VCAN) was derived and validated in four independent GC cohorts from the GEO and Cancer Genome Atlas (TCGA) database. Multi-omics analyses showed that LSR-high tumors exhibited aggressive clinicopathological features, increased stromal components, reduced cytotoxic immune infiltration, diminished tumor mutational burden (TMB), and poorer prognosis. Immunohistochemistry (IHC) and spatial transcriptomics in GC showed that stromal VWF/VCAN expression correlates with reduced CD8⁺ T cell granzyme B expression, suggesting T cell dysfunction. High VWF expression in GC predicted poor survival, and a combined VWF/VCAN score showed enhanced prognostic stratification. This study highlights stromal-immune crosstalk as a driver of pembrolizumab resistance and provides a signature as a clinical tool for prognosis and personalized therapy in metastatic GC.
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Construction of molecular subtype and prognostic model for gastric cancer based on nucleus-encoded mitochondrial genes.
Gastric cancer (GC) is a common digestive system cancer, characterized by a significant mortality rate. Mitochondria is an indispensable organelle in eukaryotic cells. It was previously revealed that a series of nucleus-encoded mitochondrial genes (NMG) mutations and dysfunctions potentially contribute to the initiation and progression of GC. However, the correlation between NMG mutations and survival outcomes for GC patients is still unclear. In this study, NMG expression profile and clinical information in GC samples were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Through consistent clustering and functional enrichment analysis, we have identified three NMG clusters and three gene clusters that are associated with patterns of immune cell infiltration. Prognostic genes were identified through Univariate Cox regression analysis. The principal component analysis was conducted to set up a scoring system. Subsequently, the Single‑cell RNA sequencing (scRNA-seq) data of GC patients and cancer cell drug sensitivity data were retrieved from the GEO database. Patients with high NMG scores exhibited increased microsatellite instability status and a heightened tumor mutation rate compared to those with low NMG scores. Survival analysis revealed that GC samples with high NMG scores could achieve a better prognosis. Additionally, These patients were observed to be more responsive to immunotherapy. Moreover, we delved into prognostic genes at the level of single cells, revealing that MRPL4 and MRPL37 exhibit high expression in epithelial cells, while TPM1 demonstrates high expression in tissue stem cells. Utilizing cancer cell drug sensitivity data from the Drug Sensitivity in Cancer (GDSC) database, we noted a heightened sensitivity to chemotherapy in the high NMG group. Furthermore, we discovered a significant enrichment of cuproptosis-related genes in clusters with high NMG scores. Consequently, employing the scoring system could facilitate the prediction of GC patients' sensitivity to cuproptosis-induced therapy. Our study confirmed the potency of this scoring system as a therapeutic response biomarker for gastric cancer, potentially informing clinical treatment strategies.
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Single-cell RNA-seq reveals the communications between extracellular matrix-related components and Schwann cells contributing to the earlobe keloid formation.
Keloid is a major type of skin fibrotic disease, with one prominent feature of extensive accumulation of extracellular matrix (ECM) components, and another feature of pain/itching, which is closely related to the peripheral nervous system (PNS). However, the molecular pathogenesis of these two prominent features still needs to be further explored. In the present study, we performed single-cell RNA sequencing (scRNA-seq) on clinical earlobe keloid samples and adjacent normal skin samples and constructed a keloid atlas of 31,379 cells. All cells were clustered into 13 major cell types using cell-type-specific markers. Among them, fibroblast, vascular endothelial cells, and smooth muscle cells were defined as the ECM-related populations according to their ECM-associated functions. Also, we found that Schwann cells (SCs) were the main neuron cells of PNS in the skin. Interestingly, the cell proportions of ECM-related populations, as well as SC were increased significantly in the earlobe keloid compared to the adjacent normal tissues, suggesting an important role of these cell types in the development of the earlobe keloid. Comprehensive cell-cell interaction analysis at the single-cell level revealed a strong interaction between SC and ECM-related subgroups which might be mediated by SEMA3C signaling pathways and MK/PTN gene family, which are found to be mainly involved in promoting cell proliferation and migration. Moreover, further exploration of the interactions of ECM-related populations and SC in different keloids, including earlobe keloid, back keloid, and chest keloid revealed an increasing amount of TGFβ-TGFβ receptor interactions in chest/back keloids as compared to earlobe keloid, which suggested the anatomic site-specific pathogenesis in different keloids. Altogether, these findings suggested the interactions between ECM-related populations and SC contributing to the earlobe keloid formation and helped us to better understand the pathogenesis of keloids.