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. 2023 Dec 18;10(1):e23917.
doi: 10.1016/j.heliyon.2023.e23917. eCollection 2024 Jan 15.

MFG-E8 promotes M2 polarization of macrophages and is associated with poor prognosis in patients with gastric cancer

Yang Li  1 , Jianda Qiu  1 , Ziyu Meng  1 , Shiyuan Yin  1 , Mingxuan Ruan  1 , Wenbiao Zhang  1 , Zhiwei Wu  1 , Tao Ding  1 , Fei Huang  2 , Wenbin Wang  1
Affiliations

MFG-E8 promotes M2 polarization of macrophages and is associated with poor prognosis in patients with gastric cancer

Yang Li et al. Heliyon. .

Abstract

Background: Milk Fat Globule-Epidermal Growth Factor 8 (MFG-E8) has been reported to play an oncogenic role in a variety of tumors. However, its involvement in gastric cancer (GC) development has not been described.

Methods: The cancer genome atlas (TCGA) and the gene expression omnibus database (GEO) databases were used to analyze the expression of MFG-E8 in GC. These findings were further validated using immunohistochemistry (IHC) and western blotting assay (WB). Kaplan-Meier method, univariate logistic regression, and Christopher Cox regression were used to study the relationship between MFG-E8 and clinical pathology. In addition, the potential signaling pathways involved in MFG-E8 and its potential correlation with levels of immune cell infiltration were investigated. Finally, the biological function of MFG-E8 in GC cells was revealed.

Results: MFG-E8 was highly expressed in GC patients and cells, and the high level of MFG-E8 was associated with poor overall survival (OS). KEGG analysis indicated that MFG-E8 may play an important role in the cAMP signaling pathway. The expression of MFG-E8 was positively correlated with the infiltration of M2 macrophages. The patients with high MFG-E8 were easy to develop chemotherapy resistance. Furthermore, the knockdown of MFG-E8 significantly inhibited the proliferation and invasion of GC cells.

Conclusion: MFG-E8 in GC may serve as a prognostic marker and a potential immunotherapy target for GC.

Keywords: Bioinformatics; Gastric cancer; Immune infiltration; MFG-E8; Prognosis.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Expression of MFG-E8 in GC tissues and cells. (A) Expression levels of MFG-E8 in pan-carcinomas based on the TCGA database. (B) Comparison between GC and paired normal tissues in the TCGA database. (C) Comparison between GC and unpaired normal tissues in the TCGA database. (D) Comparison between GC and unpaired normal tissues in GSE54129. (E) Comparison between GC and paired normal tissues in GSE79973. (F, G) WB assay was used to detect the protein level of MFG-E8 in GC cells. *p < 0.05, **p < 0.01, ***p < 0.001, ###p < 0.001.
Fig. 2
Fig. 2
Localization of MFG-E8 in cells and expression in GC tissues. (A) The localization of MFG-E8 in AGS cells was determined by immunofluorescence. (B, C) Expression of MFG-E8 in 40 tumors and adjacent tissues as determined by IHC (The nucleus was colored blue, MFG-E8 was labeled with green fluorescence, the cell morphology was colored red, and the merged result is shown in yellow; Magnification, × 200). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3
Fig. 3
Expression and prognosis of MFG-E8 in different subgroups of GC patients. (A) The relationship between high and low MFG-E8 expression and age, T classification, N classification, and M classification. (B) OS survival curves for high and low MFG-E8 with age >65 years, T1 and T4, N1 and N3, M0 and M1.
Fig. 4
Fig. 4
Prognostic analysis of MFG-E8 expression in GC patients and construction and validation of nomograms. (A, B) Overall survival and disease-specific survival of GC patients with high versus low MFG-E8. (C) The Receiver operating characteristic (ROC) curve of MFG-E8 expression. (D, E) Forest plots for univariate and multivariate Cox regression analysis based on overall survival. (E) Nomograms predicting 1-, 3-, and 5-year OS in GC patients. (F) The calibration curve of nomograms for predicting 1-, 3-, and 5-year overall survival in patients with breast cancer. HR, hazard ratio; CI, confidence interval.
Fig. 5
Fig. 5
Identification and functional enrichment analysis of differentially expressed genes (DEGs) related to MFG-E8 in GC. (A) Volcano map of DEGs. (B) Co-expression heatmap of DEGS. (C) GO and KEGG enrichment analysis of MFG-E8-related DEGs in GC. BP, biological Process; CC, cellular compositions; MF, molecular functions. ***p < 0.001.
Fig. 6
Fig. 6
The relationship between MFG-E8 and immune infiltration of GC. (A) The relative proportion of high and low MFG-E8 immune infiltrates. (B) The StromalScore, ImmuneScore, and ESTIMATEScore of TME differed between high and low MFG-E8 expression groups. (C) Correlation between MFG-E8 and the relative abundance of 24 immune cells in GC. (D) Comparison of immune infiltration levels of macrophages between high and low MFG-E8 expression groups. (E) Correlation between relative enrichment score of macrophages and MFG-E8 expression. (F, G) Relationship between MFG-E8 expression and macrophage subtypes. (H) OS survival curves of macrophages between high and low MFG-E8 expression groups. **p < 0.01, ***p < 0.001.
Fig. 7
Fig. 7
Correlation of MFG-E8 expression with immune infiltration cell markers. (A) The correlation between MFG-E8 and TAM. (B) The correlation between MFG-E8 and M1 macrophages. (C) The correlation between MFG-E8 and M2 macrophages.. (CXCL8, also known as IL8; RFX5, also referred to as MHC II; NOS2, alternatively named INOS; IFNG, also recognized as IFN gamma; and MRC1, also commonly referred to as CD206.)
Fig. 8
Fig. 8
Relationship between MFG-E8 expression in GC and chemotherapeutic drugs. (A) Low and high expression MFG-E8 pairs Box plots of IC50 for Dihydrorotenone, AZD1332, Dasatinib. (B) The relationship between MFG-E8 expression and drug sensitivity.
Fig. 9
Fig. 9
Knockdown of MFG-E8 inhibited cell proliferation, migration, and invasion. (A, B) Expression levels of MFG-E8 in AGS and MKN45 after siRNA transfection. (C, D) EDU proliferation assay was used to detect the effect of siRNA transfection on cell proliferation. (E, F) After siRNA transfection, scratches were performed, and the healing area was recorded at 0 and 24 h, showing the effect on migration ability. (G, H) After the knockdown of MFG-E8, the effect of MFG-E8 on cell migration and invasion was examined by Transwell assay. **p < 0.01, ***p < 0.001.
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