Examining the influence of tumor-infiltrating macrophages on breast cancer outcomes and identifying relevant genes for diagnostic purposes

Abstract

Objective: The purpose of this research was to investigate how different types of immune cells impact the outlook of individuals with breast cancer, as well as identify the essential genes associated with immune cell subtype enrichment.

Methods: The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database were used to obtain global transcriptome sequencing data sets of breast tissue. The study utilized the CIBERSORT algorithm to determine the presence of 22 different types of immune cells in both breast cancer tissue and normal breast tissue.Immune cell infiltration content was utilized to conduct univariate COX analysis in order to identify risk factors linked to breast cancer prognosis.

Results: Univariate COX analysis indicates that Macrophages M1 and B cells naive are beneficial factors for the outlook of individuals with breast cancer (P < 0.05), while Macrophages M2 and Monocytes are detrimental factors for the prognosis of breast cancer patients (P < 0.05). The high infiltration group of macrophage M2 had a poorer prognosis compared to the low infiltration group (P < 0.001); Conversely, the high infiltration group of macrophage M1 had a better prognosis than the low infiltration group (P = 0.002).

Conclusion: The study provided an overview of immune cell infiltration in breast cancer tissues, identifying macrophage M1 and macrophage M2 as potential factors in breast cancer development and progression. Additionally, genes associated with macrophage phenotype were analyzed, offering insights into macrophage polarization mechanisms.

Keywords: Breast cancer; Immune cells; Prognosis.

Fig. 1

Histogram of the proportion of different immune cell subtypes in each sample

Fig. 2

Differences in immune cell infiltration levels between normal breast tissue and breast cancer tissue

Fig. 3

Illustrates the correlation of immune cells in breast cancer samples. The red color indicates positive correlation, while the blue color represents negative correlation

Fig. 4

Analysis of immune cell infiltration and survival

Fig. 5

Gene set associated with Macrophages M1 and Macrophages M2. A Macrophages M1; B Macrophages M2

Fig. 6

Intersection of gene sets associated with Macrophages M1 and Macrophages M2. There are 15 common genes, namely TCL1A, GFI1, CD8B, OR2I1P, GPR171, MS4A1, CD27, CCL19, SPIB, CCR7, SPOCK2, LAMP3, UBD, LCK, PRKCQ

Fig. 7

Protein–protein interaction network among common genes. Thicker lines represent stronger correlations