Role of mast cells activation in the tumor immune microenvironment and immunotherapy of cancers

Guo, Xinxin; Sun, Mingjun; Yang, Peiyan; Meng, Xingchen; Liu, Ran

doi:10.1016/j.ejphar.2023.176103

Cited by 8 publications

(1 citation statement)

References 143 publications

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“…A deeper analysis on the altered gene expression profile between abemaciclib-treated and control mice revealed a massive increase in neutrophils and mast cells in our study. These latter cells secrete a variety of pro-inflammatory molecules and are involved in intercellular communication with other immune or stromal cells to modulate the immune status or promote tumor progression [ 43 ]. Thus, they may play a dual role in cancer regulation.…”

Section: Discussionmentioning

confidence: 99%

Prophylaxis with abemaciclib delays tumorigenesis in dMMR mice by altering immune responses and reducing immunosuppressive extracellular vesicle secretion

Wolff,

Krone,

Maennicke

et al. 2024

Translational Oncology

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Section: Discussionmentioning

confidence: 99%

Prophylaxis with abemaciclib delays tumorigenesis in dMMR mice by altering immune responses and reducing immunosuppressive extracellular vesicle secretion

Wolff,

Krone,

Maennicke

et al. 2024

Translational Oncology

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Prediction of clinical prognosis and drug sensitivity in hepatocellular carcinoma through the combination of multiple cell death pathways

Chen,

Zhang,

Meng

et al. 2024

Cell Biology International

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Hepatocellular carcinoma (HCC) is the sixth most common malignant tumor, highlighting a significant need for reliable predictive models to assess clinical prognosis, disease progression, and drug sensitivity. Recent studies have highlighted the critical role of various programmed cell death pathways, including apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, NETotic cell death, parthanatos, lysosome‐dependent cell death, autophagy‐dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis, in tumor development. Therefore, by investigating these pathways, we aimed to develop a predictive model for HCC prognosis and drug sensitivity. We analyzed transcriptome, single‐cell transcriptome, genomic, and clinical information using data from the TCGA‐LIHC, GSE14520, GSE45436, and GSE166635 datasets. Machine learning algorithms were used to establish a cell death index (CDI) with seven gene signatures, which was validated across three independent datasets, showing that high CDI correlates with poorer prognosis. Unsupervised clustering revealed three molecular subtypes of HCC with distinct biological processes. Furthermore, a nomogram integrating CDI and clinical information demonstrated good predictive performance. CDI was associated with immune checkpoint genes and tumor microenvironment components using single‐cell transcriptome analysis. Drug sensitivity analysis indicated that patients with high CDI may be resistant to oxaliplatin and cisplatin but sensitive to axitinib and sorafenib. In summary, our model offers a precise prediction of clinical outcomes and drug sensitivity for patients with HCC, providing valuable insights for personalized treatment strategies.

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H2 antihistamines: May be useful for combination therapies in cancer?

Mohamad,

Galarza,

Martín

2024

Biochemical Pharmacology

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Role of mast cells activation in the tumor immune microenvironment and immunotherapy of cancers

Cited by 8 publications

References 143 publications

Prophylaxis with abemaciclib delays tumorigenesis in dMMR mice by altering immune responses and reducing immunosuppressive extracellular vesicle secretion

Prophylaxis with abemaciclib delays tumorigenesis in dMMR mice by altering immune responses and reducing immunosuppressive extracellular vesicle secretion

Prediction of clinical prognosis and drug sensitivity in hepatocellular carcinoma through the combination of multiple cell death pathways

H2 antihistamines: May be useful for combination therapies in cancer?

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