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A single-cell transcriptomic atlas reveals senescence and inflammation in the post-tuberculosis human lung.
Patients with a history of Mycobacterium tuberculosis infection often suffer from irreversible and progressive pulmonary damage, yet the underlying mechanisms are not fully understood. Here we conducted single-cell transcriptomic analysis of human lung tissues including 19 post-tuberculosis lung tissues and 13 matched normal lung samples as controls, focusing on areas within and surrounding tuberculosis lesions. We identified tuberculosis-associated molecular signatures across various cell types, including gene expression patterns associated with senescence, inflammation, fibrosis and apoptosis. We observed increased vascular inflammation as a key feature of lung tissues following tuberculosis. Signatures of decreased FOXO3 signalling and increased NF-κB-dependent thromboinflammation were validated by showing that small interfering RNA silencing of FOXO3 and thrombin treatment exacerbated senescence and inflammation in pulmonary endothelial cells. These findings provide insight into the mechanisms contributing to post-tuberculosis pulmonary damage and suggest potential therapeutic targets for alleviating lung impairment in these patients.
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Prediction of the Survival Status, Immunotherapy Response, and Medication of Lung Adenocarcinoma Patients Based on Hypoxia- and Apoptosis-Related Genes.
To predict patient survival prognosis, we aimed to establish a novel set of gene features associated with hypoxia and apoptosis. RNA-seq and clinical data of LUAD were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, while hypoxia and apoptosis-related genes were obtained from the Molecular Signatures Database (MsigDB). A 13-gene-prognostic model incorporating hypoxia and apoptosis genes was developed using univariate/multivariate Cox regression, Nonnegative Matrix Factorization (NMF) clustering, and LASSO regression. Patients were divided into high-risk (HR) and low-risk (LR) groups according to the median risk score. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed distinct biological processes between HR and LR groups, including hormone regulation and lipid metabolism pathways. Single sample gene set enrichment analysis (ssGSEA) indicated elevated cell infiltration levels of Neutrophils and T_helper_cells in the LR group, while NK cells and Th1cells were higher in the HR group. Immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) analyses suggested potential benefits of immunotherapy for LR group patients. In conclusion, this prognostic feature integrating hypoxia- and apoptosis-related genes offers insights into predicting survival, immune status, and treatment response in LUAD patients, paving the way for personalized treatment strategies.
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Blockade of TREM2 ameliorates pulmonary inflammation and fibrosis by modulating sphingolipid metabolism.
Pulmonary fibrosis is a chronic interstitial lung disease involving systemic inflammation and abnormal collagen deposition. Dysregulations in lipid metabolism, such as macrophage-dependent lipid catabolism, have been recognized as critical factors for the development of pulmonary fibrosis. However, little is known about the signaling pathways involved and the key regulators. Here we found that triggering receptor expressed on myeloid cells 2 (TREM2) plays a pivotal role in regulating the lipid handling capacities of pulmonary macrophages and triggering fibrosis. By integrating analysis of single-cell and bulk RNA sequencing data from patients and mice with pulmonary fibrosis, we revealed that pulmonary macrophages consist of heterogeneous populations with distinct pro-fibrotic properties, and found that both sphingolipid metabolism and the expression of chemotaxis-related genes are elevated in fibrotic lungs. TREM2, a sensor recognizing multiple lipid species, is specifically upregulated in a subset of monocyte-derived macrophages. Blockade of TREM2 by conventional/conditional knock-out or soluble TREM2 administration can attenuate bleomycin-induced pulmonary fibrosis. By utilizing scRNA Seq and lipidomics, we found that Trem2 deficiency downregulates the synthesis of various sphingomyelins, and inhibits the expression of chemokines such as Ccl2. Together, our findings not only reveal the alterations in lipidomic profiles and the atlas of pulmonary macrophages during pulmonary fibrosis, but also suggest that targeting TREM2, the crucial regulator affecting both pulmonary sphingolipid metabolism and the chemokines secretion, can benefit pulmonary fibrosis patients in the future.
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Hypothyroidism reduces the risk of lung cancer through oxidative stress response and the PI3K/Akt signaling pathway: An RNA-seq and Mendelian randomization study.
Hypothyroidism has been suggested to play a role in tumor progression. However, the causal association between hypothyroidism and lung cancer remains unknow. To elucidate the potential association between hypothyroidism and lung cancer risk, we employ a Mendelian randomization (MR) approach. MR was performed to analyze pooled data from the International Lung Cancer Consortium (11,348 cases and 15,861 controls; European ancestry) to determine the causal relationship between hypothyroidism and lung cancer. We used 36, 83, and 14 single nucleotide polymorphisms as instrumental variables for hypothyroidism/myxoedema, hypothyroidism, and exercise, respectively. We further investigated the mechanisms involved in transcriptome analysis using data from The Cancer Genome Atlas and Genotype-Tissue Expression database. We conducted an initial validation of intermediary factor using a two-step MR analysis. Genetically predicted hypothyroidism was significantly related to the risk of overall lung cancer, specifically the risk of lung squamous cell cancer (LSCC) but not with the risk of lung adenocarcinoma (LUAD) as assessed using the inverse-variance weighted (IVM) method. A similar causal association was found between hypothyroidism/myxoedema and the risk of lung cancer, LSCC, and LUAD. Transcriptome analysis showed that genes associated with hypothyroidism, lung cancer, and LSCC were enriched in the PI3K/Akt signaling pathway and oxidative stress response. However, genes related to hypothyroidism and LUAD did not exhibit enrichment in these pathways. Hypothyroidism was significantly associated with strenuous sports or other exercises. Moreover, genetically predicted exercise was significantly related to the risk of overall lung cancer, and LSCC, but not LUAD. We detected no horizontal pleiotropy using the MR-PRESSO and MR Egger regression intercept. Hypothyroidism was causally associated with a lower risk of lung cancer, and these effects might be mediated by the oxidative stress response and the PI3K/Akt signaling pathway. Therefore, our study suggests that the potential factors and viable etiologies of hypothyroidism that contributed to lung cancer risk deserve further investigation.
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iSoMAs: Finding isoform expression and somatic mutation associations in human cancers.
Aberrant alternative splicing, prevalent in cancer, impacts various cancer hallmarks involving proliferation, angiogenesis, and invasion. Splicing disruption often results from somatic point mutations rewiring functional pathways to support cancer cell survival. We introduce iSoMAs (iSoform expression and somatic Mutation Association), an efficient computational pipeline leveraging principal component analysis technique, to explore how somatic mutations influence transcriptome-wide gene expression at the isoform level. Applying iSoMAs to 33 cancer types comprising 9,738 tumor samples in The Cancer Genome Atlas, we identified 908 somatically mutated genes significantly associated with altered isoform expression across three or more cancer types. Mutations linked to differential isoform expression occurred through both cis- and trans-acting mechanisms, involving well-known oncogenes/suppressor genes, RNA binding protein and splicing factor genes. With wet-lab experiments, we verified direct association between TP53 mutations and differential isoform expression in cell cycle genes. Additional iSoMAs genes have been validated in the literature with independent cohorts and/or methods. Despite the complexity of cancer, iSoMAs attains computational efficiency via dimension reduction strategy and reveals critical associations between regulatory factors and transcriptional landscapes.
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Multiomic Analysis of Subtype Evolution and Heterogeneity in High-Grade Serous Ovarian Carcinoma.
Multiple studies have identified transcriptome subtypes of high-grade serous ovarian carcinoma (HGSOC), but their interpretation and translation are complicated by tumor evolution and polyclonality accompanied by extensive accumulation of somatic aberrations, varying cell type admixtures, and different tissues of origin. In this study, we examined the chronology of HGSOC subtype evolution in the context of these factors using a novel integrative analysis of absolute copy-number analysis and gene expression in The Cancer Genome Atlas complemented by single-cell analysis of six independent tumors. Tumor purity, ploidy, and subclonality were reliably inferred from different genomic platforms, and these characteristics displayed marked differences between subtypes. Genomic lesions associated with HGSOC subtypes tended to be subclonal, implying subtype divergence at later stages of tumor evolution. Subclonality of recurrent HGSOC alterations was evident for proliferative tumors, characterized by extreme genomic instability, absence of immune infiltration, and greater patient age. In contrast, differentiated tumors were characterized by largely intact genome integrity, high immune infiltration, and younger patient age. Single-cell sequencing of 42,000 tumor cells revealed widespread heterogeneity in tumor cell type composition that drove bulk subtypes but demonstrated a lack of intrinsic subtypes among tumor epithelial cells. Our findings prompt the dismissal of discrete transcriptome subtypes for HGSOC and replacement by a more realistic model of continuous tumor development that includes mixtures of subclones, accumulation of somatic aberrations, infiltration of immune and stromal cells in proportions correlated with tumor stage and tissue of origin, and evolution between properties previously associated with discrete subtypes. SIGNIFICANCE: This study infers whether transcriptome-based groupings of tumors differentiate early in carcinogenesis and are, therefore, appropriate targets for therapy and demonstrates that this is not the case for HGSOC.
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SUMOylation substrate encoding genes as prognostic biomarkers in pancreatic ductal adenocarcinoma with functional assessment of SAF-B2.
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is highly malignant with a poor prognosis, posing significant clinical challenges. SUMOylation, a reversible post-translational modification, plays a critical role in tumor progression, yet its prognostic significance in PDAC remains unclear. METHODS: We assessed SUMOylation expression patterns and function in PDAC using Western blot and the SUMOylation inhibitor TAK-981. Differentially expressed SUMOylation substrate encoding genes (DE-SSEGs) were identified from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Project (GTEx) datasets. A SUMOylation-based prognostic model, Sscore, was constructed using LASSO and Cox regression. Additional analyses included somatic mutation, immune infiltration, TIDE, drug sensitivity, and single-cell RNA sequencing. The role of SAFB2 in PDAC was validated in vitro. RESULTS: PDAC cells showed elevated SUMOylation, and its inhibition reduced cell proliferation. The Sscore model, based on DE-SSEGs (CDK1, AHNAK2, SAFB2), predicted overall survival and correlated with genome variation, immune infiltration, and drug sensitivity. Single-cell analysis further confirmed a link between high Sscore and malignancy. SAFB2, identified as a pivotal gene within the Sscore model, was significantly downregulated in PDAC tissues and cell lines; its overexpression was shown to inhibit PDAC cell proliferation, migration, and invasion by suppressing the Wnt/β-Catenin signaling pathway. CONCLUSION: This study underscores the role of SUMOylation in PDAC and introduces the Sscore as a prognostic tool. SAFB2 is identified as a potential tumor suppressor, offering new therapeutic targets for PDAC.
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Construction and Validation of a Prognostic Model Based on Novel Senescence-Related Genes in Non-Small Cell Lung Cancer Patients with Drug Sensitivity and Tumor Microenvironment.
Cellular senescence contributes to cancer pathogenesis and immune regulation. Using the LASSO Cox regression, we developed a 12-gene prognostic signature for lung adenocarcinoma (LUAD) from The Cancer Genome Atlas (TCGA) and a Gene Expression Omnibus (GEO) dataset. We assessed gene expression, drug sensitivity, immune infiltration, and conducted cell line experiments. High-risk LUAD patients showed increased mortality risk and shorter survival (P < 0.001). Senescence-related gene analysis indicated differences in protein phosphorylation and DNA methylation between normal individuals and LUAD patients. The high-risk group showed a positive association with PD-L1 expression (P = 0.003). Single-cell sequencing data suggested PEBP1 might significantly impact T cell infiltration. We predicted potential sensitive compounds for 12 senescence genes and found GAPDH promoted cell line proliferation. We established a novel prognostic system based on a newly identified senescence gene. High-risk patients had elevated immunosuppressive markers, and PEBP1 might influence T cell infiltration significantly. GAPDH, expressed at higher levels in tumors, could affect cancer progression. Our drug prediction model may guide treatment selection.
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TGF-β-mediated activation of fibroblasts in cervical cancer: implications for tumor microenvironment and prognosis.
BACKGROUND: Cervical cancer (CC) is a prevalent female malignancy strongly influenced by the tumor microenvironment (TME). This study focuses on the role of TGF-β signaling in cancer-associated fibroblasts (CAFs) and its interaction with immune cells, aiming to elucidate its impact on CC progression. METHODS: The TME of CC patients was analyzed using scRNA-seq data and we identified the major cell types in the TME with a focus on the activation of the TGF-β signaling pathway in fibroblasts. Gene modules related to the TGF-β signaling pathway were identified by Weighted correlation network analysis (WGCNA). Using The Cancer Genome Atlas Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (TCGA-CESC) dataset, a prognostic gene model was constructed by univariate Cox, LASSO Cox and multivariate Cox regression analyses. For cellular validation, the mRNA level of prognostic model-related genes was tested via quantitative real-time real-time polymerase chain reaction (PCR). Thereafter, the following assays, including cell counting kit-8, scratch and wound healing assays, were applied to assess the viability, migration and invasion of CC cells. RESULTS: Analysis at single-cell resolution identified nine major cell types in the TME, and significant activation of the TGF-β signaling pathway in fibroblasts was correlated with tumor proliferation and differentiation. Strong TGF-β signaling communication between fibroblasts and macrophages and NK/T cells suggested a crucial role in the shaping of the immunosuppressive microenvironment. WGCNA analysis identified gene modules significantly associated with the TGF-β signaling pathway. The prognostic model constructed based on three genes, ITGA5, SHF and SNRPN, demonstrated good predictive ability in multiple datasets, validating its potential for clinical application. Meanwhile, the cellular validation assays have revealed the higher expression of ITGA5 and SNRPN and lower expression of SHF in CC cells. Further, ITGA5 knockdown suppressed the viability, migration and invasion of CC cells. CONCLUSION: This study confirmed the important role of the TGF-β signaling pathway in CC, especially in fibroblasts on tumor microenvironment and tumor progression. The current model could effectively evaluate the prognosis of CC, providing a theoretical foundation for developing CC therapies according to the TGF-β signaling pathway. The present results provide new perspectives for further research on the pathological mechanisms and clinical management of CC.
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EMP1 as a Potential Biomarker in Liver Fibrosis: A Bioinformatics Analysis.
Liver fibrosis is a wound-healing response to chronic injury, which may result in cirrhosis and liver failure. Studies have been carried on the mechanisms and pathogenesis of liver fibrosis. However, the potential cell-specific expressed marker genes involved in fibrotic processes remain unknown. In this study, we combined a publicly accessible single-cell transcriptome of human liver with microarray datasets to evaluate the cell-specific expression patterns of differentially expressed genes in the liver. We noticed that EMP1 (epithelial membrane protein 1) is significantly active not only in CCl4 (carbon tetrachloride)-treated mouse liver fibrosis but also in BDL (bile duct ligation)-induced liver fibrosis and even in human fibrotic liver tissues such as alcoholic hepatitis, NASH (nonalcoholic steatohepatitis), and advanced stage liver fibrosis. Furthermore, we demonstrated that EMP1 is a specific fibrotic gene expressed in HSCs (hepatic stellate cells) and endothelial cells using the Protein Atlas single-cell transcriptome RNA-sequencing clustering. Its expression was significantly elevated in fibrotic HSCs or CCl4 and NASH-induced fibroblasts. Previous research revealed that EMP1 plays a role in proliferation, migration, metastasis, and tumorigeneses in different cancers via a variety of mechanisms. Because HSC activation and proliferation are two important steps following liver injury, it would be interesting to investigate the role of EMP1 in these processes. All of this information suggested that EMP1 could be used as a novel fibrotic liver marker and a possible target in the future.