Classification and characterisation of extracellular vesicles‐related tuberculosis subgroups and immune cell profiles

Zhou, Peipei; Shen, Jie; Ge, Xijin; Ding, Fang; Zhou, Hong; Huang, Xin-Lin; Zhao, Chao; Li, Meng; Li, Z Y

doi:10.1111/jcmm.17836

Cited by 3 publications

(1 citation statement)

References 59 publications

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“…The EVs' ability to encapsulate hydrophobic compounds, lipids, proteins, and glycolipids allows for distant interactions with the host that may play a vital role in the pathogenesis of TB [15,16]. In addition, they also function in various processes such as inhibition of antigen presentation, vaccination, TB biomarkers, recruitment of immune cells, and activation of macrophages [17]. Therefore, EVs and exosomes offer excellent biomarkers for TB prediction and prognosis, efficacy evaluation, etc.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Role of Extracellular Vesicles in the Pathogenesis of Tuberculosis

Arya,

Shakya,

Chaurasia

et al. 2024

Genes

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Tuberculosis (TB) remains a significant global health concern, necessitating accurate diagnosis and treatment monitoring. Extracellular vesicles (EVs), including exosomes, play crucial roles in disease progression, with their associated genes serving as potential biomarkers and therapeutic targets. Leveraging publicly available RNA-Seq datasets of TB patients and healthy controls (HCs), to identify differentially expressed genes (DEGs) and their associated protein–protein interaction networks and immune cell profiles, the common EV-related DEGs were identified and validated in the GSE42830 and GSE40553 datasets. We have identified nine common EV-related DEGs (SERPINA1, TNFAIP6, MAPK14, STAT1, ITGA2B, VAMP5, CTSL, CEACAM1, and PLAUR) upregulated in TB patients. Immune cell infiltration analysis revealed significant differences between TB patients and HCs, highlighting increased proportions of various immune cells in TB patients. These DEGs are involved in crucial cellular processes and pathways related to exocytosis and immune response regulation. Notably, VAMP5 exhibited excellent diagnostic performance (AUC—0.993, sensitivity—93.8%, specificity—100%), with potential as a novel biomarker for TB. The EV-related genes can serve as novel potential biomarkers that can distinguish between TB and HCs. VAMP5, which functions in exosome biogenesis and showed significant upregulation in TB, can be targeted for therapeutic interventions and treatment outcomes.

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Section: Introductionmentioning

confidence: 99%

Exploring the Role of Extracellular Vesicles in the Pathogenesis of Tuberculosis

Arya,

Shakya,

Chaurasia

et al. 2024

Genes

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Single‐cell sequencing: Current applications in various tuberculosis specimen types

Zeng,

Ma,

Chen

et al. 2024

Cell Proliferation

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Tuberculosis (TB) is a chronic disease caused by Mycobacterium tuberculosis (M.tb) and responsible for millions of deaths worldwide each year. It has a complex pathogenesis that primarily affects the lungs but can also impact systemic organs. In recent years, single‐cell sequencing technology has been utilized to characterize the composition and proportion of immune cell subpopulations associated with the pathogenesis of TB disease since it has a high resolution that surpasses conventional techniques. This paper reviews the current use of single‐cell sequencing technologies in TB research and their application in analysing specimens from various sources of TB, primarily peripheral blood and lung specimens. The focus is on how these technologies can reveal dynamic changes in immune cell subpopulations, genes and proteins during disease progression after M.tb infection. Based on the current findings, single‐cell sequencing has significant potential clinical value in the field of TB research. Next, we will focus on the real‐world applications of the potential targets identified through single‐cell sequencing for diagnostics, therapeutics and the development of effective vaccines.

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Machine learning-based approach for efficient prediction of diagnosis, prognosis and lymph node metastasis of papillary thyroid carcinoma using adhesion signature selection

Sun,

Cai,

Shao

et al. 2023

MBE

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<abstract> <p>The association between adhesion function and papillary thyroid carcinoma (PTC) is increasingly recognized; however, the precise role of adhesion function in the pathogenesis and prognosis of PTC remains unclear. In this study, we employed the robust rank aggregation algorithm to identify 64 stable adhesion-related differentially expressed genes (ARDGs). Subsequently, using univariate Cox regression analysis, we identified 16 prognostic ARDGs. To construct PTC survival risk scoring models, we employed Lasso Cox and multivariate + stepwise Cox regression methods. Comparative analysis of these models revealed that the Lasso Cox regression model (LPSRSM) displayed superior performance. Further analyses identified age and LPSRSM as independent prognostic factors for PTC. Notably, patients classified as low-risk by LPSRSM exhibited significantly better prognosis, as demonstrated by Kaplan-Meier survival analyses. Additionally, we investigated the potential impact of adhesion feature on energy metabolism and inflammatory responses. Furthermore, leveraging the CMAP database, we screened 10 drugs that may improve prognosis. Finally, using Lasso regression analysis, we identified four genes for a diagnostic model of lymph node metastasis and three genes for a diagnostic model of tumor. These gene models hold promise for prognosis and disease diagnosis in PTC.</p> </abstract>

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Classification and characterisation of extracellular vesicles‐related tuberculosis subgroups and immune cell profiles

Cited by 3 publications

References 59 publications

Exploring the Role of Extracellular Vesicles in the Pathogenesis of Tuberculosis

Exploring the Role of Extracellular Vesicles in the Pathogenesis of Tuberculosis

Single‐cell sequencing: Current applications in various tuberculosis specimen types

Machine learning-based approach for efficient prediction of diagnosis, prognosis and lymph node metastasis of papillary thyroid carcinoma using adhesion signature selection

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