Chrome Extension
WeChat Mini Program
Use on ChatGLM

Colorectal Cancer-Derived Extracellular Vesicles Containing HSP70 Enhance Macrophage Phagocytosis by Up-Regulating MARCO Expression

EXPERIMENTAL CELL RESEARCH(2023)

Sun Yat Sen Univ | Gannan Med Univ | 628 Zhenyuan Rd

Cited 5|Views24
Abstract
In recent years, we have realized that extracellular vesicles (EVs) play a critical role in regulating the intercellular communication between tumor and immune cells in the tumor microenvironment (TME). Tumor-derived extracellular vesicles (TDEVs) profoundly affect the functional changes of tumor-associated macrophages (TAMs) and promote their M2 polarization. Meanwhile, macrophages have a strong phagocytic ability in phagocytosing apoptotic cells. Especially in the course of chemotherapy or radiotherapy, TAMs can phagocytose and remove apoptotic tumor cells, showing anti-inflammatory and pro-tumor effects. However, the underlying mechanisms by which TDEVs regulate macrophage phagocytosis of apoptotic tumor cells have not been fully elucidated. In this study, we focused on the effect of colorectal cancer-derived extracellular vesicles (CRC-EVs) on macrophages. We demonstrated that CRC-EVs enhanced macrophage phagocytosis of apoptotic CRC cells. We then determined that heat shock protein 70 (HSP70) carried in CRC-EVs was responsible for this effect by using mass spectrometry-based proteomic analysis and the CRISPR-Cas9 system. Through transcriptome sequencing of macrophages, we found that the enhanced phagocytosis of macrophages was mainly due to the up-regulation of the macrophage receptor with collagenous structure (MARCO). In addition, we confirmed that the up-regulation of MARCO was mediated by the AKT-STAT3 signaling pathway. Taken together, this study revealed a novel EVs-mediated macrophage phagocytosis mechanism involved in the clearance of apoptotic tumor cells in the TME. Targeting TDEVs may have potential therapeutic applications in tumor treatment.
More
Translated text
Key words
Colorectal cancer,Extracellular vesicles,HSP70,MARCO,Macrophage,Phagocytosis
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined