AUTHOR=Schweer David , Anand Namrata , Anderson Abigail , McCorkle J. Robert , Neupane Khaga , Nail Alexandra N. , Harvey Brock , Hill Kristen S. , Ueland Frederick , Richards Christopher , Kolesar Jill TITLE=Human macrophage-engineered vesicles for utilization in ovarian cancer treatment JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2023 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1042730 DOI=10.3389/fonc.2022.1042730 ISSN=2234-943X ABSTRACT=Background

Ovarian cancer is a deadly female malignancy with a high rate of recurrent and chemotherapy-resistant disease. Tumor-associated macrophages (TAMs) are a significant component of the tumor microenvironment and include high levels of M2-protumor macrophages that promote chemoresistance and metastatic spread. M2 macrophages can be converted to M1 anti-tumor macrophages, representing a novel therapeutic approach. Vesicles engineered from M1 macrophages (MEVs) are a novel method for converting M2 macrophages to M1 phenotype-like macrophages.

Methods

Macrophages were isolated and cultured from human peripheral blood mononuclear cells. Macrophages were stimulated to M1 or M2 phenotypes utilizing LPS/IFN-γ and IL-4/IL-13, respectively. M1 MEVs were generated with nitrogen cavitation and ultracentrifugation. Co-culture of ovarian cancer cells with macrophages and M1 MEVs was followed by cytokine, PCR, and cell viability analysis. Murine macrophage cell line, RAW264.7 cells were cultured and used to generate M1 MEVs for use in ovarian cancer xenograft models.

Results

M1 MEVs can effectively convert M2 macrophages to an M1-like state both in isolation and when co-cultured with ovarian cancer cells in vitro, resulting in a reduced ovarian cancer cell viability. Additionally, RAW264.7 M1 MEVs can localize to ovarian cancer tumor xenografts in mice.

Conclusion

Human M1 MEVs can repolarize M2 macrophages to a M1 state and have anti-cancer activity against ovarian cancer cell lines. RAW264.7 M1 MEVs localize to tumor xenografts in vivo murine models.