Macrophages Promote Ovarian Cancer-Mesothelial Cell Adhesion by Upregulation of ITGA2 and VEGFC in Mesothelial Cells

Cells. 2023 Jan 20;12(3):384. doi: 10.3390/cells12030384.

Abstract

Ovarian cancer is a metastatic disease that frequently exhibits extensive peritoneal dissemination. Recent studies have revealed that noncancerous cells inside the tumor microenvironment, such as macrophages and mesothelial cells, may play a role in ovarian cancer metastasis. In this study, we found that human ovarian cancer cells (A2780 and SKOV3) adhered more to human mesothelial Met5A cells stimulated by macrophages (M-Met5A) in comparison to unstimulated control Met5A cells. The mRNA sequencing revealed that 94 adhesion-related genes, including FMN1, ITGA2, COL13A1, VEGFC, and NRG1, were markedly upregulated in M-Met5A cells. Knockdown of ITGA2 and VEGFC in M-Met5A cells significantly inhibited the adhesion of ovarian cancer cells. Inhibition of the JNK and Akt signaling pathways suppressed ITGA2 and VEGFC expression in M-Met5A cells as well as ovarian cancer-mesothelial cell adhesion. Furthermore, increased production of CC chemokine ligand 2 (CCL2) and CCL5 by macrophages elevated ovarian cancer-mesothelial cell adhesion. These findings imply that macrophages may play a significant role in ovarian cancer-mesothelial cell adhesion by inducing the mesothelial expression of adhesion-related genes via the JNK and Akt pathways.

Keywords: ITGA2; VEGFC; adhesion; macrophage; mesothelial cells; ovarian cancer.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Adhesion / physiology
  • Cell Line, Tumor
  • Female
  • Humans
  • Macrophages / metabolism
  • Ovarian Neoplasms* / pathology
  • Proto-Oncogene Proteins c-akt / metabolism
  • Tumor Microenvironment
  • Up-Regulation / genetics
  • Vascular Endothelial Growth Factor C / metabolism

Substances

  • Proto-Oncogene Proteins c-akt
  • Vascular Endothelial Growth Factor C
  • VEGFC protein, human
  • ITGA2 protein, human

Grants and funding

This research was funded by the National Research Foundation of Korea (NRF) (2017R1A5A2014768, NRF-2019R1A2C2011213, and NRF-2022R1A2C1003498).