A large-scale screening and functional sorting of tumour microenvironment prognostic genes for breast cancer patients

Bo Xiao; Mingwei Li; Mingxuan Cui; Chengliang Yin; Bo Zhang

doi:10.3389/fendo.2023.1131525

A large-scale screening and functional sorting of tumour microenvironment prognostic genes for breast cancer patients

Front Endocrinol (Lausanne). 2023 Mar 1:14:1131525. doi: 10.3389/fendo.2023.1131525. eCollection 2023.

Authors

Bo Xiao¹, Mingwei Li¹, Mingxuan Cui¹, Chengliang Yin², Bo Zhang¹

Affiliations

¹ Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Cellular and Molecular Immunology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
² Faculty of Medicine, Macau University of Science and Technology, Macau, Macau SAR, China.

Abstract

Purpose: The aim of this study was to systematically establish a comprehensive tumour microenvironment (TME)-relevant prognostic gene and target miRNA network for breast cancer patients.

Methods: Based on a large-scale screening of TME-relevant prognostic genes (760 genes) for breast cancer patients, the prognostic model was established. The primary TME prognostic genes were selected from the constructing database and verified in the testing database. The internal relationships between the potential TME prognostic genes and the prognosis of breast cancer patients were explored in depth. The associated miRNAs for the TME prognostic genes were generated, and the functions of each primary TME member were investigated in the breast cancer cell line.

Results: Compared with sibling controls, breast cancer patients showed 55 differentially expressed TME prognostic genes, of which 31 were considered as protective genes, while the remaining 24 genes were considered as risk genes. According to the lambda values of the LASSO Cox analysis, the 15 potential TME prognostic genes were as follows: ENPEP, CCDC102B, FEZ1, NOS2, SCG2, RPLP2, RELB, RGS3, EMP1, PDLIM4, EPHA3, PCDH9, VIM, GFI1, and IRF1. Among these, there was a remarkable linear internal relationship for CCDC102B but non-linear relationships for others with breast cancer patient prognosis. Using the siRNA technique, we silenced the expression of each TME prognostic gene. Seven of the 15 TME prognostic genes (NOS2, SCG2, RGS3, EMP1, PDLIM4, PCDH9, and GFI1) were involved in enhancing cell proliferation, destroying cell apoptosis, promoting cell invasion, or migration in breast cancer. Six of them (CCDC102B, RPLP2, RELB, EPHA3, VIM, and IRF1) were favourable for maintaining cell invasion or migration. Only two of them (ENPEP and FEZ1) were favourable for the processes of cell proliferation and apoptosis.

Conclusions: This integrated study hypothesised an innovative TME-associated genetic functional network for breast cancer patients. The external relationships between these TME prognostic genes and the disease were measured. Meanwhile, the internal molecular mechanisms were also investigated.

Keywords: breast cancer; cell proliferation; miRNA; prognostic model; tumor microenvironment.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Breast Neoplasms* / genetics
Early Detection of Cancer
Female
Humans
MicroRNAs*
Prognosis
Tumor Microenvironment / genetics

Substances

MicroRNAs

Grants and funding

This study was funded by the National Natural Science Foundation of China (Grant No. 82070687 to Bo Zhang).