Identification of FPR3 as a Unique Biomarker for Targeted Therapy in the Immune Microenvironment of Breast Cancer

Jian Qi; Yu Liu; Jiliang Hu; Li Lu; Zhen Dou; Haiming Dai; Hongzhi Wang; Wulin Yang

doi:10.3389/fphar.2020.593247

Identification of FPR3 as a Unique Biomarker for Targeted Therapy in the Immune Microenvironment of Breast Cancer

Front Pharmacol. 2021 Feb 11:11:593247. doi: 10.3389/fphar.2020.593247. eCollection 2020.

Authors

Jian Qi^{1

2

3}, Yu Liu^{1

2

3}, Jiliang Hu⁴, Li Lu⁵, Zhen Dou⁶, Haiming Dai^{1

3}, Hongzhi Wang^{1

3}, Wulin Yang^{1

3}

Affiliations

¹ Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.
² Scinece Island Branch, Graduate School of USTC, Hefei, China.
³ Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, China.
⁴ Department of Neurosurgery, The Shenzhen People's Hospital (The Second Clinical Medical College of Jinan University), Shenzhen, China.
⁵ Department of Anatomy, Shanxi Medical University, Taiyuan, China.
⁶ Hefei National Science Center for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, China.

Abstract

Although research into immunotherapy is growing, its use in the treatment of breast cancer remains limited. Thus, identification and evaluation of prognostic biomarkers of tissue microenvironments will reveal new immune-based therapeutic strategies for breast cancer. Using an in silico bioinformatic approach, we investigated the tumor microenvironmental and genetic factors related to breast cancer. We calculated the Immune score, Stromal score, Estimate score, Tumor purity, TMB (Tumor mutation burden), and MATH (Mutant-allele tumor heterogeneity) of Breast cancer patients from the Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm and Maftools. Significant correlations between Immune/Stromal scores with breast cancer subtypes and tumor stages were established. Importantly, we found that the Immune score, but not the Stromal score, was significantly related to the patient's prognosis. Weighted correlation network analysis (WGCNA) identified a pattern of gene function associated with Immune score, and that almost all of these genes (388 genes) are significantly upregulated in the higher Immune score group. Protein-protein interaction (PPI) network analysis revealed the enrichment of immune checkpoint genes, predicting a good prognosis for breast cancer. Among all the upregulated genes, FPR3, a G protein-coupled receptor essential for neutrophil activation, is the sole factor that predicts poor prognosis. Gene set enrichment analysis analysis showed FRP3 upregulation synergizes with the activation of many pathways involved in carcinogenesis. In summary, this study identified FPR3 as a key immune-related biomarker predicting a poor prognosis for breast cancer, revealing it as a promising intervention target for immunotherapy.

Keywords: ESTIMATE algorithm; FPR3; breast cancer; immune checkpoint; immune microenvironment.