CCL2-CCR2 axis recruits tumor associated macrophages to induce immune evasion through PD-1 signaling in esophageal carcinogenesis

Abstract

Background: The poor prognosis of esophageal squamous cell carcinoma (ESCC) highlights the need for novel strategies against this disease. Our previous study suggested the involvement of CCL2 and tumor associated macrophages (TAMs) in esophageal carcinogenesis. Despite the recognition of TAMs as a promising target for cancer treatment, mechanisms underlying its infiltration, activation and tumor-promotive function in ESCC remain unknown. Methods: Human esophageal tissue array and TCGA database were used to evaluate the clinical relevance of CCL2 and TAMs in ESCC. F344 rats and C57BL/6 mice were treated with N-nitrosomethylbenzylamine (NMBA) to establish orthotopic models of esophageal carcinogenesis. CCL2/CCR2 gene knockout mice and macrophage-specific PPARG gene knockout mice were respectively used to investigate the role of infiltration and polarization of TAMs in ESCC. CCL2-mediated monocyte chemotaxis was estimated in malignantly transformed Het-1A cells. THP-1 cells were used to simulate TAMs polarization in vitro. RNA-sequencing was performed to uncover the mechanism. Results: Increasing expression of CCL2 correlated with TAMs accumulation in esophageal carcinogenesis, and they both predicts poor prognosis in ESCC cohort. Animal studies show blockade of CCL2-CCR2 axis strongly reduces tumor incidence by hindering TAMs recruitment and thereby potentiates the antitumor efficacy of CD8 + T cells in the tumor microenvironment. More importantly, M2 polarization increases PD-L2 expression in TAMs, resulting in immune evasion and tumor promotion through PD-1 signaling pathway. Conclusion: This study highlights the role of CCL2-CCR2 axis in esophageal carcinogenesis. Our findings provide new insight into the mechanism of immune evasion mediated by TAMs in ESCC, suggesting the potential of TAMstargeted strategies for ESCC prevention and immunotherapy.

RETRACTED ARTICLE: Immune landscape of periodontitis unveils alterations of infiltrating immunocytes and molecular networks-aggregating into an interactive web-tool for periodontitis related immune analysis and visualization

“…At present, there is a lack of such systematic and comprehensive bioinformatics analysis in the periodontal research, and there are few studies on immune cells using high-throughput data, and a huge amount of information hidden behind these data were left unexplored. However, in other fields, particularly oncology, bioinformatics analysis and the use of high-throughput data have become the norm [ 30 , 31 ], which help researchers identify research targets and predict results. In our study, we a series of bioinformatic analysis were conducted from which abundant results were generated that couldinspire other researchers.…”

Immune landscape of periodontitis unveils alterations of infiltrating immunocytes and molecular networks-aggregating into an interactive web-tool for periodontitis related immune analysis and visualization

“…At present, there is a lack of such systematic and comprehensive bioinformatics analysis in the periodontal research, and there are few studies on immune cells using high-throughput data, and a huge amount of information hidden behind these data were left unexplored. However, in other elds, particularly oncology, bioinformatics analysis and the use of high-throughput data have become the norm [30,31], which help researchers identify research targets and predict results. In our study, we a series of bioinformatic analysis were conducted from which abundant results were generated that couldinspire other researchers.…”

Immune Landscape of Periodontitis Unveils Alterations of Infiltrating Immunocytes and Molecular Networks-Aggregating into an Interactive Web-Tool for Periodontitis Related Immune Analysis and Visualization

“…At present, there is a lack of such systematic and comprehensive bioinformatics analysis in the periodontal research eld, and there are few studies on immune cells using high-throughput data, so many data cannot fully play their role. However, in other elds, particularly oncology, bioinformatics analysis and the use of high-throughput data have become the norm [25,26], which help researchers identify research targets and predict results. In our study, we made a lot of bioinformatic analysis and generated abundant results that can well inspire other researchers.…”