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Dynamic increase of M2 macrophages is associated with disease progression of colorectal cancers following cetuximab-based treatment

Cited 5 time in Web of Science Cited 6 time in Scopus
Authors

Kim, Hyung-Don; Kim, Sun Young; Kim, Jihun; Kim, Jeong Eun; Hong, Yong Sang; Han, Buhm; Tak, Eunyoung; Ryu, Yeon-Mi; Kim, Sang-Yeob; Kim, Tae Won

Issue Date
2022-01
Publisher
Nature Publishing Group
Citation
Scientific Reports, Vol.12 No.1, p. 1678
Abstract
We aimed to investigate the dynamic changes of gene expression profiles and immune microenvironment linked to resistance to cetuximab-based treatments in patients with metastatic colorectal cancer (mCRC). A total of 106 patients with RAS-wild type mCRC who were treated with cetuximab-based treatments were included as the study population. RNA-sequencing and multiplexed immunohistochemistry were performed using paired or unpaired pre-treatment and post-treatment tumor tissues. Differentially expressed gene analysis of paired pre-treatment and post-treatment tumor tissues that develop acquired resistance (AR) identified the AR signature. Gene ontology analysis of the AR signature indicated enrichment of immune-related pathway genes. Among the immune subsets whose abundance was estimated by CIBERSORT, M2 macrophages showed the most prominent positive correlation with the expression of the AR signature. Among the post-treatment samples, progressive disease (PD) tumors showed a significantly higher abundance of M2 macrophages compared to non-PD tumors. These findings were validated by multiplexed immunohistochemistry analysis: the density of CD68(+)CD206(+) M2 macrophages significantly increased at the time of PD following cetuximab-based treatment, whereas it did not consistently change in the tumor pairs of non-PD. In conclusion, a dynamic increase of M2 macrophages is associated with disease progression during cetuximab-based treatment of mCRCs. Targeting M2 macrophages is a promising immunotherapeutic strategy in this clinical context.
ISSN
2045-2322
URI
https://hdl.handle.net/10371/191469
DOI
https://doi.org/10.1038/s41598-022-05694-x
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  • College of Medicine
  • Department of Medicine
Research Area Bioinformatics, Computational Biology, Genomics, Human Leukocyte Antigen, Statistical Genetics

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