Paclitaxel promotes <scp>mTOR</scp> signaling‐mediated apoptosis in esophageal cancer cells by targeting <scp>MUC20</scp>

Li, Meng; Feng, Zhen; Han, Rui; Hu, Benchuang; Zhang, Renfeng; Wang, Hui

doi:10.1111/1759-7714.15091

Cited by 3 publications

(2 citation statements)

References 27 publications

(46 reference statements)

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“…MUC20 is a transmembrane mucin located on chromosome locus 3q29 close to MUC4 [18]. The functional importance of MUC20 has been demonstrated in several cancers [111][112][113], but its role in gliomas remains to be further elucidated. In a similar study on different tumors, JONCKHEERE and VAN SEUNINGEN (2018) [114], through bioinformatics analysis, evaluated genes correlated with MUC4 expression in epithelial cancers and found a close correlation between MUC16 and MUC20.…”

Section: Discussionmentioning

confidence: 99%

MUC1andMUC4expression are inversely correlated and trigger immunological response and transport pathways in gliomas

Machado,

Ferrer

2024

Preprint

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Diffuse gliomas are tumors that arise from glial or glial progenitor cells. They are currently classified as astrocytoma isocitrate dehydrogenase (IDH)-mutant or oligodendroglioma IDH-mutant, and chromosome arms 1p/19q-codeleted, both slower-growing tumors, or glioblastoma (GBM), a more aggressive tumor. Despite advances in the diagnosis and treatment of gliomas, the median survival time after diagnosis of GBM remains low, approximately 15 months, with a 5-year overall survival rate of only 6.8%. Therefore, new biomarkers and therapy targets that could support better prognosis of these tumors would be of great value. MUC1 and MUC4, membrane-bound mucins, has been identified as a potential biomarker in several tumors. However, the role of these mucins in adult gliomas has not yet been well explored. Here, we show for the first time, in a retrospective study and byin silicoanalysis, the relevance and correlation of these genes in adult gliomas. Analysis of adult diffuse glioma patient cohorts revealed differential methylation and expression patterns of MUC1 and MUC4 across GBM and non-GBM subtypes. GBM patients exhibited decreased MUC1 methylation and elevated expression (r-0.25, p < 0.0001) whereas increased MUC4 methylation and its lower expression (r-0.13, p = 0.1344). Conversely, in non-GBM patients, MUC1 showed higher methylation levels and low expression (r-0.27, p < 0.0001) whereas MUC4 showed lower methylation levels and high expression (r-0.32, p < 0.0001). The expression levels of these genes influenced overall survival (OS) in gliomas patients (p = 0.0344), with high MUC1 and low MUC4 expression associated with worse OS. MUC1 and MUC4 correlated with MUC20 in both GBM (r = 0.54) and non-GBM (r = 0.53) patients (p < 0.0001). Functional enrichment analysis revealed distinct biological roles for co-expressed genes with MUC1 involvement in innate immunity, antigen processing, pro-inflammatory responses in both non-GBM and GBM cohorts, and integrin-based signaling pathways in GBM patients. MUC4 co-expressed genes were involved in ion transport in GBM patients. Using molecular docking, we observed that MUC1 has domains that are physically capable of interacting with immune response-related proteins such as Receptor for Advanced Glycation End-products (RAGE), Major Histocompatibility Complex II (MHCII), and extracellular matrix receptor integrin alpha 2 (ITGA2). These findings shed light on the molecular mechanisms underlying glioma progression and highlight MUC1 and MUC4 as potential prognostic markers and therapeutic targets in glioma management.

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Section: Discussionmentioning

confidence: 99%

MUC1andMUC4expression are inversely correlated and trigger immunological response and transport pathways in gliomas

Machado,

Ferrer

2024

Preprint

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“…The following supporting information can be downloaded at: , Table S1: Gene ontology information on the 11 genes identified as described in the text; Table S2: Gene ontology information on the six overlapping genes. References [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 ] are cited in the Supplementary Materials.…”

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confidence: 99%

An Exercise Immune Fitness Test to Unravel Disease Mechanisms—A Proof-of-Concept Heart Failure Study

Bondar,

Mahapatra,

Bao

et al. 2024

JCM

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Background: Cardiorespiratory fitness positively correlates with longevity and immune health. Regular exercise may provide health benefits by reducing systemic inflammation. In chronic disease conditions, such as chronic heart failure and chronic fatigue syndrome, mechanistic links have been postulated between inflammation, muscle weakness, frailty, catabolic/anabolic imbalance, and aberrant chronic activation of immunity with monocyte upregulation. We hypothesize that (1) temporal changes in transcriptome profiles of peripheral blood mononuclear cells during strenuous acute bouts of exercise using cardiopulmonary exercise testing are present in adult subjects, (2) these temporal dynamic changes are different between healthy persons and heart failure patients and correlate with clinical exercise-parameters and (3) they portend prognostic information. Methods: In total, 16 Heart Failure (HF) patients and 4 healthy volunteers (HV) were included in our proof-of-concept study. All participants underwent upright bicycle cardiopulmonary exercise testing. Blood samples were collected at three time points (TP) (TP1: 30 min before, TP2: peak exercise, TP3: 1 h after peak exercise). We divided 20 participants into 3 clinically relevant groups of cardiorespiratory fitness, defined by peak VO2: HV (n = 4, VO2 ≥ 22 mL/kg/min), mild HF (HF1) (n = 7, 14 < VO2 < 22 mL/kg/min), and severe HF (HF2) (n = 9, VO2 ≤ 14 mL/kg/min). Results: Based on the statistical analysis with 20–100% restriction, FDR correction (p-value 0.05) and 2.0-fold change across the three time points (TP1, TP2, TP3) criteria, we obtained 11 differentially expressed genes (DEG). Out of these 11 genes, the median Gene Expression Profile value decreased from TP1 to TP2 in 10 genes. The only gene that did not follow this pattern was CCDC181. By performing 1-way ANOVA, we identified 8/11 genes in each of the two groups (HV versus HF) while 5 of the genes (TTC34, TMEM119, C19orf33, ID1, TKTL2) overlapped between the two groups. We found 265 genes which are differentially expressed between those who survived and those who died. Conclusions: From our proof-of-concept heart failure study, we conclude that gene expression correlates with VO2 peak in both healthy individuals and HF patients, potentially by regulating various physiological processes involved in oxygen uptake and utilization during exercise. Multi-omics profiling may help identify novel biomarkers for assessing exercise capacity and prognosis in HF patients, as well as potential targets for therapeutic intervention to improve VO2 peak and quality of life. We anticipate that our results will provide a novel metric for classifying immune health.

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Artesunate-loaded solid lipid nanoparticles resist esophageal squamous cell carcinoma by inducing Ferroptosis through inhibiting the AKT/mTOR signaling

Xia,

Tang,

Huang

et al. 2024

Cellular Signalling

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Paclitaxel promotes mTOR signaling‐mediated apoptosis in esophageal cancer cells by targeting MUC20

Cited by 3 publications

References 27 publications

MUC1andMUC4expression are inversely correlated and trigger immunological response and transport pathways in gliomas

MUC1andMUC4expression are inversely correlated and trigger immunological response and transport pathways in gliomas

An Exercise Immune Fitness Test to Unravel Disease Mechanisms—A Proof-of-Concept Heart Failure Study

Artesunate-loaded solid lipid nanoparticles resist esophageal squamous cell carcinoma by inducing Ferroptosis through inhibiting the AKT/mTOR signaling

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