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Published on: November 28, 2019
Reprogramming tumour-associated macrophages in breast cancer via si-FOXM1-loaded lipid nanoparticles enhances immune
Yali Gao1, Jiayi Li1, Mengying Xu1
1School of Clinical Medicine, Ningxia Medical University, Yinchuan, P. R. China.
Background And Purpose:
The polarization state of tumour-associated macrophages (TAMs) plays a crucial role in breast cancer treatment outcomes, particularly in enhancing the efficacy of immune checkpoint inhibitors by transitioning TAMs from the M2 to M1 phenotype. This study aims to investigate whether delivering si-Forkhead Box M1 (FOXM1) efficiently into tumour cells via lipid nanoparticles (LNPs) can silence FOXM1 expression, up-regulate Kruppel-like factor 15 (KLF15) and thereby modulate TAM polarization to enhance the antitumor immune response against breast cancer.
Experimental Approach:
Transcriptomic data from TCGA and GEO were analysed using Weighted Gene Co-expression Network Analysis (WGCNA) and CIBERSORT for immune infiltration. Cell culture, gene expression, and functional assays assessed the impact of FOXM1 silencing on TAM polarization and breast cancer cell behaviour. si-FOXM1-loaded LNPs were characterized and evaluated both in vitro and in vivo xenograft models.
Key Results:
The study identified KLF15 as a key player associated with breast cancer prognosis and showed that FOXM1 silencing promoted KLF15 expression, leading to reduced M2 macrophage infiltration and inhibited breast cancer progression. LNPs loaded with si-FOXM1 efficiently reprogrammed TAMs to the M1 phenotype, inhibiting breast cancer cell proliferation and invasion.
Conclusions And Implications:
LNPs loaded with si-FOXM1 act on tumour cells to silence FOXM1 expression and up-regulate KLF15, thereby promoting the reprogramming of tumour-associated macrophages towards the M1 phenotype within the tumour microenvironment. This process effectively inhibits breast cancer progression and enhances the antitumor efficacy of immune checkpoint inhibitors against breast cancer cells.
