Guanylate-binding protein-1 is a potential new therapeutic target for triple-negative breast cancer

Abstract

Background: Triple-negative breast cancer (TNBC) is characterized by a lack of estrogen and progesterone receptor expression (ESR and PGR, respectively) and an absence of human epithelial growth factor receptor (ERBB2) amplification. Approximately 15-20% of breast malignancies are TNBC. Patients with TNBC often have an unfavorable prognosis. In addition, TNBC represents an important clinical challenge since it does not respond to hormone therapy.

Methods: In this work, we integrated high-throughput mRNA sequencing (RNA-Seq) data from normal and tumor tissues (obtained from The Cancer Genome Atlas, TCGA) and cell lines obtained through in-house sequencing or available from the Gene Expression Omnibus (GEO) to generate a unified list of differentially expressed (DE) genes. Methylome and proteomic data were integrated to our analysis to give further support to our findings. Genes that were overexpressed in TNBC were then curated to retain new potentially druggable targets based on in silico analysis. Knocking-down was used to assess gene importance for TNBC cell proliferation.

Results: Our pipeline analysis generated a list of 243 potential new targets for treating TNBC. We finally demonstrated that knock-down of Guanylate-Binding Protein 1 (GBP1 ), one of the candidate genes, selectively affected the growth of TNBC cell lines. Moreover, we showed that GBP1 expression was controlled by epidermal growth factor receptor (EGFR) in breast cancer cell lines.

Conclusions: We propose that GBP1 is a new potential druggable therapeutic target for treating TNBC with enhanced EGFR expression.

Keywords: Breast cancer; Gene expression; RNA-Seq; Therapeutic target; Transcriptomics; Triple-negative breast cancer.

Fig. 1

DE genes in TNBC versus non-TNBC tissues and TNBC versus normal tissues from TCGA. Principal component analysis (a) and heatmap clustering (b) performed with the DE genes revealed a clear separation between TNBC, non-TNBC and normal tissues. Correlations were obtained through Pearson coefficient analysis; unsupervised clustering was conducted via a complete method, and both axis and log₂(RSEM + 1) values were scaled by line. c 3D Volcano plot showing non-DE (gray circles) and DE (blue circles, downregulated; red circles, upregulated) genes. Genes showing FC ≥ +2 and FC ≤ −2 with FDR ≥ 0.05 were considered up- and downregulated, respectively. On axis Z, −log₁₀(FDR). d Venn diagram showing that 1512 genes were equally DE when TNBC versus non-TNBC and TNBC versus normal tissues were compared

Fig. 2

Transcriptomics and proteomics druggability analysis generated a list of new potential protein targets for TNBC. a 3D correlation plot between FC of DE genes. Dark gray in 2D projections represents upregulated genes. Unifying DE genes exhibiting an FDR ≤ 0.05 and an FC ≥ +2; FDR ≤ 0.05 and FC ≤ −2; or an FDR > 0.05 are shown as purple, orange and green circles, respectively. b Venn diagrams showing that 134 genes (B, left) were equally downregulated, while 243 (b, right) were equally upregulated in all three comparisons. c Probes covering CpG islands were related to genes based on TSS proximity and their methylation status (values for different probes were averaged) were correlated to the gene expression FC (TNBC x Non-TNBC). d Circos plot comparing CpG islands methylation FC (green or pink lines) with gene expression FC (blue line) in the TNBC x Non-TNBC (outer circle) or TNBC x normal (inner circle) (chromosome ideogram denoted in the most outer circle). Values for both methylation and gene expression FC were averaged within every 5 Mbp. FC opposite spikes indicate that the higher the methylation FC, the lower the gene expression FC of the associated region, and vice-verse. e Protein level FC (MS dataset [64] performed with the same BRCA samples used in this work) and gene expression FC correlation in the comparison TNBC x Non-TNBC. f Pipeline used for new protein targets discovering. g Number of genes found in two or more publications (25) or in 0 or 1 publication (218) following the PubMed query “gene name + triple-negative breast cancer”. The genes that were non-cited or were cited only once were then evaluated in canSAR as either having available protein structure (67) or not (151), followed by a cutoff of being structurally druggable (42) or not (25). Among the 42 genes with a druggable structure, the top 10 based on the ligand-based druggability percentile are listed

Fig. 3

Multiple evidence sources makes GBP1 arise as potential target for TNBC. a GBP1 is more highly expressed in TNBC than in non-TNBC and normal tissues (left) and in TNBC versus non-TNBC cell lines (right). FDR values were obtained from the DESeq2 comparisons. b Cartoon representation of the human GBP1 protein structure (PDB ID 1DG3), displaying the 5 highest-scoring potential small molecule binding pockets according to PockDrug [54]. c MS evaluation of GBP1 protein level in Non-TNBC and TNBC samples. P-Value and FDR value were calculated with limma. d Seven microarray datasets external-to-our-pipeline analysis confirmed GBP1 upregulation in TNBC versus non-TNBC tissues. FDR values were derived from limma comparisons. (e, lower) GBP1 gene scheme denoting the open-sea probe cg12054698 location within the exon 1. (e, upper) Methylation status (as defined by M-values) for the cg12054698 in Normal, Non-TNBC and TNBC samples, showing hypomethylation in TNBC. FDR values calculated with limma. As for all the displayed box-plots, log₂-transformed upper-quantile values were used, with the whiskers extending to half of the interquartile range. Gray circles denote each sample. Notches, when present, denotes the 95% confidence intervals of the median

Fig. 4

TNBC are more sensitive to GBP1 knock-down than non-TNBC cells. EGFR drives GBP1 expression. a GBP1 mRNA levels were evaluated via quantitative PCR in different cell lines. b GBP1 knock-down (shGBP1) using pLKO.mKO2 for 96 h affected the growth of TNBC cells more effectively than that of non-TNBC cells, as assessed using two shRNA sequences. An shRNA targeting non-human gene luciferase (shLuc) was used as a control. Data were split between cells that died (left) and cells that proliferated less (right) after knock down. c Representative fluorescence microscopy images of MDA-MB-231 after 96 h of GBP1 knock-down compared with shLuc. DAPI staining of nuclei is shown in blue, and mKO2 fluorescence of cells positive for viral transduction is shown in yellow. d Cell proliferation assay (performed over 7 days) of cell lines selected to stably express the shGBP1 and shLuc sequences. e Propidum iodide incorporation assay was performed to evaluate the fraction of cells that are in apoptosis/late necrosis state. EGFR is more highly expressed in TNBC than non-TNBC tissues (f, top) and cell lines (f, down). The FDR value was absent in DESeq2 comparisons due to outlier removal. g GBP1 and EGFR expression levels are highly correlated in tissues (left) and cell lines (right). h GBP1 expression level positively correlates with EGFR total protein level. Log₂-transformed upper-quantile RSEM expression values were used, with whiskers extending to half of the interquartile range. Gray circles denote each sample Notches denote the 95% confidence interval of the median. (I) MDA-MB-231 cells were serum starved for 24 h and then stimulated with 50 ng/mL of EGF for six hours. Western blotting (right) confirmed that the treatment increased EGFR stimulation (increase of Tyr1068 phosphorylation). qPCR (left) showed that, with the exception of BT549, all tested cell lines responded to EGF stimulation by increasing GBP1 expression. Error bars denote one standard error of the experimental triplicates