IMD expression is significantly increased in breast cancer samples
We first evaluated the expression level of IMD in a tissue microarray, which contained 142 breast cancer samples and 88 adjacent nontumor tissue samples (Fig. 1A and 1B). The immunohistochemical (IHC) staining results showed that the breast cancer tissues exhibited significantly increased levels of IMD expression compared with the adjacent nontumor tissues (Fig. 1C). Based on the tissue microarray data, we selected 67 paired samples (that is, tumor tissue and adjacent tissue samples from the same patient) for comparison and found that the expression of IMD in the tumor tissues of most patients was significantly higher than that in the normal tissues adjacent to the cancerous tissues (Fig. 1D). In addition, stepwise binary regression analysis showed a significant association between the IMD levels and both lymph node metastasis and Ki67 expression in the breast cancer tissues (Table 1).
IMD facilitates the malignancy of breast cancer cells
The elevated expression of IMD in breast cancer tissues suggests that it may play a role in the growth and invasion of breast cancer cells. We investigated this hypothesis using a murine breast cancer model established with 4T1 cells. The 4T1 breast cancer can produce highly metastatic solid tumors that can spontaneously metastasize to the lung, which closely mimics that of highly metastatic human breast cancer [17, 18]. The cell viability assay showed that treatment with an anti-IMD monoclonal antibody had an inhibitory effect on the growth of 4T1 cells (Fig. 2A). Anchorage-independent growth refers to the ability of cancer cells to grow independently on a solid surface and is considered a hallmark of cancer malignancy. The soft agar colony formation assay showed that IMD slightly increased the colony-forming ability of 4T1 cells, whereas the treatment with the anti-IMD antibody significantly decreased the number of cell colonies (Fig. 2B and 2C).
Cancer cell migration and invasion are highly integrated, multistep processes that play an important role in local invasion and metastasis. The wound healing assay showed that IMD promoted but the anti-IMD antibody significantly decreased the migration of 4T1 cells (Fig. 2D and 2E). The invasive ability of cancer cells, which indicates their ability to travel through the extracellular matrix into neighboring tissues, can be assessed by the Transwell assay. As shown in Fig. 2F-G, compared to the Vehicle-treated group, the number of cells crossing through the membrane in the IMD-treated group was higher; in contrast, treatment with the anti-IMD antibody significantly decreased the number of 4T1 cells that invaded into the lower chambers.
Blockade of IMD reduces in situ tumor growth and lung metastasis of 4T1 breast cancer
The elevated expression of IMD in breast cancer tissue and its effect on the malignancy of breast cancer cells suggest that blockade of IMD activity may inhibit breast cancer growth and metastasis. We tested this hypothesis in a 4T1 orthotopic breast cancer model. A total of 2.5×106 4T1 cells were injected under the mammary fat pads of 6-week-old female BALB/c mice. Seven days after cancer cell injection, the mice were treated with the mature IMD peptide (0.25 mg/kg/day, 2 weeks, 14 times in total, subcutaneous injection), the anti-IMD monoclonal antibody (2.5 mg/kg, twice weekly, 3 times in total, intravenous injection), or vehicle (100 ml of 0.9% saline, twice weekly, 3 times in total, intravenous injection). On the final day of the experiment, tumor growth curves were plotted (Fig. 3A). Compared with the vehicle group, IMD increased, whereas the anti-IMD antibody inhibited the orthotopic tumor growth, and the pro- or anti-tumor effects were not due to the body weight loss (Fig. 3B).
The most important feature of 4T1 tumors is not their in situ tumor growth but rather their spontaneous metastasis, particularly lung metastasis [17, 18]. Five weeks after inoculation of 4T1 cancer cells, lungs from the tumor-bearing mice in the vehicle group and the anti-IMD antibody treatment group were removed for analysis (Fig. 3C-E). Statistical analysis performed by calculating the number of metastatic colonies and the metastatic area on the surface of the lungs (including the ventral and dorsal sides) showed that anti-IMD antibody treatment reduced the number of lung metastases to approximately 1/3 of that in the vehicle group (Fig. 3F and 3G). The analysis of H&E-stained pathologic images of the whole lungs confirmed the tumor metastasis within the lungs (Fig. 4A-C). According to the results, IMD increased, whereas the anti-IMD antibody significantly inhibited lung metastasis.
Blockade of IMD significantly inhibits ribosome biogenesis and protein synthesis
To obtain a more comprehensive understanding of the influence of IMD on breast cancer cells, we analyzed the transcriptional profiles of 4T1 cells via RNA sequencing (RNA-seq) analysis. Biological replicates are necessary when performing biological experiments to ensure that the results are reliably reproducible. Herein, we analyzed two parallel samples per group (treated with vehicle, IMD, or the anti-IMD antibody). The correlation of gene expression levels between samples is an important indicator for assessing the reliability of experiments and the rationality of sample selection. The closer the correlation coefficient is to 1, the higher the similarity of the expression patterns between samples is. The Encyclopedia of DNA Elements (ENCODE) Project recommends that the square of the Pearson correlation coefficient (R2) be greater than 0.92 (under ideal sampling and experimental conditions). Quality control (QC) analysis showed that the R2 value of each sample was greater than 0.97, indicating good reliability of the experimental results and high similarity of expression patterns between samples (Fig. 5A).
After gene expression is quantified, statistical analysis must be performed on the expression data to screen samples for genes whose expression levels are significantly different under various treatment conditions. This analysis is generally divided into three steps [19-21]: (1) normalization of the original read counts to correct for the sequencing depth; (2) calculation of the probability value (p-value) by hypothesis testing; and (3) performance of multiple hypothesis testing and calculation of the FDR (adjusted p, or p-adj) value. A volcano plot was generated to visually show the distribution of differentially expressed genes for each comparison (Fig. 5B and 5C). The abscissa indicates the gene expression fold change (log2 Fold Change) values, and the ordinate indicates the significance level of the gene expression difference (-log10 p-adj or -log10 p-value) between the treatment and control groups. The red dots indicate upregulated genes, and the green dots indicate downregulated genes. The volcano plot showed that IMD treatment affected gene transcriptional profiles only slightly; only 43 genes were upregulated and 41 were downregulated. The relatively small number of changed genes may be due to 4T1 cells expressing high levels of endogenous IMD; thus, supplementation with exogenous IMD may cause relatively mild effects on these cells. However, treatment with the anti-IMD antibody caused drastic changes in gene transcription; 1913 genes were significantly upregulated, and 2156 were significantly downregulated (Fig. 5C). The result suggests that inhibiting the activity of IMD may induce changes in multiple signaling pathways in breast cancer cells.
Gene Ontology (GO) analysis utilizes a comprehensive database describing gene functions that can be divided into three categories: biological processes, cellular components, and molecular functions. The most significantly enriched GO terms are displayed as scatter plots (Fig. 5D). The abscissa shows the ratio of the number of differentially expressed genes to the total number of genes in the GO term, and the ordinate shows the GO terms. The size of a dot represents the number of genes annotated to the specific GO term, and the color represents the significance of enrichment. The GO categories with significant changes (p-adj <0.05) were shown in Additional file 1. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis utilizes another database for systematic analysis of biochemical pathways, metabolic pathways, and signal transduction pathways, including differentially expressed genes. The KEGG pathway enrichment results are shown in Fig. 5E, and KEGG pathways with significant changes (p-adj <0.05) are shown in Additional file 2.
The terms with the most significant differences and the largest number of down-regulated genes were as follows: Ribonucleoprotein complex biogenesis, Ribosome biogenesis, rRNA processing, mRNA metabolic process et al. in GO terms; and Ribosome biogenesis in eukaryotes, Protein export, Spliceosome et al. in KEGG terms. Analysis of these two databases showed that anti-IMD antibody treatment had the greatest impact on ribosome biogenesis and protein synthesis.
Ribosomes are macromolecular machines that exist in almost all living cells and can perform mRNA translation and protein synthesis; they are categorized by their localization as either cytoplasmic or mitochondrial. Ribosomes consist of two major components: the small and large ribosomal subunits (S and L subunits). Each subunit consists of ribosomal RNA (rRNA) molecules and ribosomal proteins (RPs). After treatment with the anti-IMD antibody, among genes related to components of cytoplasmic ribosomes, 53 were downregulated and 6 were upregulated; among genes related to components of mitochondrial ribosomes, 25 were downregulated and only 3 were upregulated (Fig. 5F; the red box indicates gene upregulation, and the green box indicates gene downregulation; detailed differential gene expression (DEG) data are shown in Additional file 3).
IMD up-regulates the expression of ribosomal component genes by activating the Src/c-Myc signaling pathway
Cancer cells undergo uncontrolled, indefinite proliferation and persistent invasion, which requires increased production of ribosomes to support increased protein translation. The transcription of both cytoplasmic and mitochondrial ribosome components was significantly suppressed by treatment with the anti-IMD antibody, suggesting that cancer cell translation and protein production were significantly inhibited. Therefore, we sought to identify the mechanism through which IMD regulates ribosome biogenesis. KEGG pathway analysis of the “breast cancer” pathway (Fig. 6A) showed that treatment with the anti-IMD antibody suppressed the cell cycle (at the G1/S phase transition) by downregulating c-Myc and cyclin D1 (CCND1). The read count values from the original RNA-Seq data showed that IMD significantly increased the transcription levels of c-Myc and cyclin D1, whereas the anti-IMD antibody treatment significantly down-regulated the two genes (Fig. 6B-C).
c-Myc and cyclin D1 are two key genes that affect the cell cycle, cell growth and invasion. c-Myc is a major oncoprotein controlling the expression of almost 15% of all human genes, many of which are involved in ribosome biogenesis and protein translation [22]. As one of the most frequently studied oncoproteins that regulates ribosome biogenesis, c-Myc was reported to promote cell proliferation and invasion by enhancing ribosome biogenesis and protein translation largely via its key function in stimulating the transcription of numerous genes encoding proteins essential for ribosomal biogenesis [23]. As shown in Supplementary Table 3, the magnitude of the anti-IMD antibody-caused reduction in the transcription of ribosome-related genes was consistent with the magnitude of the reduction in c-Myc, which may explain the extensive inhibitory effect of the anti-IMD antibody on ribosome biogenesis-related genes.
Cyclin D1 has long been noted to play an important role in breast cancer [24]. Cyclin D1 overexpression has been reported in more than 50% of human breast cancers, and dysregulation of its expression contributes to loss of normal G1/S transition control during tumorigenesis [25]. Interestingly, Cyclin D1 was not the only cyclin-related gene affected by the anti-IMD antibody. As shown in Fig. 6D, the transcription levels of 3 genes encoding cyclin-dependent kinase inhibitors (CDKNs) were increased, whereas those of 5 genes encoding cyclin-dependent kinases (CDKs) and 8 genes encoding cyclins (D/E/G/L) were decreased. In general, CDKs and cyclins promote cell cycle progression from G1 to S phase, whereas CDKNs inhibit this process. The promotion of cell cycle progression is a major oncogenic mechanism of c-Myc, which not only activates the expression of cyclins and CDKs but also suppresses the expression of a set of proteins that act as cell cycle brakes [26]. These results indicate that c-Myc may be the key effector molecule in the IMD-regulated signaling cascade.
The activation of tyrosine kinase Src is believed to initiate expression of c-Myc for cell cycle progression in breast cancer cells [27-29]. IMD shares a G protein-coupled receptor (GPCR), CRLR (calcitonin receptor-like receptor), with its family members [6]. We have reported that IMD can induce the formation of a signaling complex containing CRLR and Src and promote subsequent Src phosphorylation in endothelial cells [16]. Based on these results, we hypothesized that IMD may regulate the expression of c-Myc by activating Src, thereby affecting ribosome biogenesis and the cell cycle in breast cancer cells.
We tested this hypothesis using 4T1 cells. Western blot (WB) analysis showed that IMD induced a significant increase in Src phosphorylation, and this effect could be blocked by treatment with an siRNA that can specifically inhibit Src transcription (siR-Src) (Fig. 6E-G). The rescue of Src expression by transfection of Lv.Src (lentiviral vector expressing Src) restored the ability of IMD to induce Src phosphorylation (Fig. 6E-F). To determine whether the IMD-induced Src phosphorylation and c-Myc expression was causally related, we performed Real-time PCR and found that the IMD-induced c-Myc up-regulation was blocked when Src was knocked down by siR-Src (Fig. 6H). On the other hand, after Src expression was rescued by transfection of Lv.Src, the c-Myc mRNA level was restored accordingly (Fig. 6H). The results suggest that IMD up-regulates c-Myc expression via inducing Src phosphorylation.
We then asked how Src is activated by IMD. IMD has been reported to be a ligand of CRLR, a class B GPCR [6]. In our previous study, we have identified an IMD/CRLR/β-arrestin 1/Src signaling cascade in endothelial cells [16]. β-arrestin 1 is a scaffold protein that mediates the agonist-dependent recruitment of Src kinase to GPCRs [30, 31]. We have shown that in endothelial cells, after IMD binds to its receptor CRLR, with the help of β-arrestin 1, Src is recruited to CRLR and form a signaling protein complex. This Src/CRLR complex is subsequently internalized into cytoplasm, resulting in Src phosphorylation [16]. Herein, we sought to determine whether this signaling pathway exists in breast cancer cells.
We performed the immunoprecipitation (IP) assay to detect the protein interactions. We found that after exposure to IMD, the binding of Src to CRLR increased by more than 3 folds (Fig. 6I and 6J). This result suggested that IMD did promote the recruitment of Src to CRLR in 4T1 breast cancer cells. The siRNA that can specifically knockdown b-arrestin 1 transcription (siR-b-arr1) could inhibit the IMD-induced binding of Src and CRLR, and transfection of Lv.b-arr1 (lentiviral vector expressing b-arrestin 1) restored the ability of IMD to induce Src binding to CRLR (Fig. 6K-M). In addition, the IP-IB assay showed that the Src phosphorylation occurred on the Src/CRLR complex; b-arrestin 1 knockdown significantly inhibited the IMD-induced Src phosphorylation, and rescue of b-arrestin 1 expression restored the Src phosphorylation (Fig. 6N and 6O). According to these results, we may say that IMD upregulates c-Myc expression by recruiting Src to CRLR and inducing Src phosphorylation, thereby enhancing ribosome assembly and driving cell cycle progression.