Characterization of the relationship between FLI1 and immune infiltrate level in tumour immune microenvironment for breast cancer

Abstract

Breast cancer is the most common cancer and the leading cause of cancer death among women in the world. Tumour-infiltrating lymphocytes were defined as the white blood cells left in the vasculature and localized in tumours. Recently, tumour-infiltrating lymphocytes were found to be associated with good prognosis and response to immunotherapy in tumours. In this study, to examine the influence of FLI1 in immune system in breast cancer, we interrogated the relationship between the FLI1 expression levels with infiltration levels of 28 immune cell types. By splitting the breast cancer samples into high and low expression FLI1 subtypes, we found that the high expression FLI1 subtype was enriched in many immune cell types, and the up-regulated differentially expressed genes between them were enriched in immune system processes, immune-related KEGG pathways and biological processes. In addition, many important immune-related features were found to be positively correlated with the FLI1 expression level. Furthermore, we found that the FLI1 was correlated with the immune-related genes. Our findings may provide useful help for recognizing the relationship between tumour immune microenvironment and FLI1, and may unravel clinical outcomes and immunotherapy utility for FLI1 in breast cancer.

Keywords: FLI1; breast cancer; tumour immune microenvironment; tumour-infiltrating lymphocyte.

Figure 1

The immune infiltrate profile of BRCA. A, Heat map of 1095 breast cancer samples by using the ssGSEA scores from 28 immune cell types. Samples were arranged along the rows by two subtypes. Red‐green colour scale reflected magnitude. The barplot at the top indicated the percentages of 28 immune cell types which were significant. The barplot on the left indicated the percentages of BRCA samples which were significant. B, Volcano plot for the high FLI1 subtype that calculated from the GSEA when compared with the low FLI1 subtype. The visualization of (C) enriched immune system processes and (D) KEGG enriched pathways of the DEGs by using ClueGO (P‐value < .05). E, Top 10 statistically enriched biological processes by the DEGs

Figure 2

The relationship between the FLI1 and the immune‐related features in BRCA. A, Spearman's correlation between the ssGSEA scores of 28 immune cell types and the FLI1 expression level, LI signature score, TIL regional fraction, leucocyte fraction, stromal score, tumour purity, ESTIMATE score, immune score and CYT. Statistical significance at the level of null ≥ 0.05, * <0.05, ** <0.01 and *** <0.001. B, Spearman's correlation between the FLI1 expression level, LI signature score, TIL regional fraction, leucocyte fraction, stromal score, tumour purity, ESTIMATE score, immune score and CYT. The correlation coefficients were represented by red‐blue colour scale on the left. C, The violin plots of the CYT, immune score, ESTIMATE score, stromal score, tumour purity, TIL regional fraction, LI signature score and leucocyte fraction for two BRCA subtypes. D, Spearman's correlation between FLI1, PD‐1, PD‐L1 and CTLA4 expression level. E, The violin plots of the PD‐1, PD‐L1 and CTLA4 expression level for two BRCA subtypes

Figure 3

The relationship between the FLI1 and immunomodulators. A, Spearman's correlations between FLI1 expression levels and immunomodulators. Statistical significance at the level of null ≥ 0.05, *<0.05, **<0.01 and ***<0.001. B, The heat map for the expression levels of 75 immunomodulators. The immunomodulators were annotated by super category and immune checkpoint type

Figure 4

Identification of modules associated with the immune‐related features in BRCA by WGCNA. A, Heat map of the correlation between module eigengenes and immune‐related features in BRCA. B, Top 10 statistically enriched biological processes of turquoise module genes. The scatter plots between gene significance for FLI1 and module membership in (C) blue module, (D) brown module and (E) turquoise module. Each point corresponded to a gene in the module.

Figure 5

Prognostic significance of FLI1 in BRCA. Kaplan‐Meier survival curves by high and low FLI1 expression level for (A) BRCA (B) Basal (C) Her2 (D) Lum A (E) Lum B and (F) normal patients. G, Forest plot visualizing hazard ratios (HRs) with 95% CI and P‐values of 28 immune cell types in 1095 breast cancer patients. HR with 95% CI and P‐values was determined by univariate Cox proportional hazards regression analysis. H, Bubble plot for the hazard ratios and P‐values of 28 immune cell types in BRCA, Basal, Her2, Lum A, Lum B and normal patients

Figure 6

The evaluation of FLI1 expression level. A, Pairwise comparison of FLI1 expression level by normal and tumour tissues. The FLI1 expression level in human different tissues from (B) HPA data set, (C) GTEx data set and (D) FANTOM5 data set