β common (βc) cytokines are produced by various cell types in the human body and can exert their effects either locally—in the vicinity of cells that produce them—or at distant sites in the body. The colony-stimulating factor 2 receptor subunit beta (CSF2RB) gene encodes CD131, the common beta chain of the heterodimeric receptors for β common cytokines: granulocyte–macrophage colony-stimulating factor (GM-CSF), interleukin 3 (IL-3), and interleukin 5 (IL-5). These receptors are heterodimers composed of a common beta chain and distinct alpha chains, with the alpha chains conferring cytokine specificity. The ligand-specific alpha chain (CSF2RA) forms a receptor complex with the common beta chain (CSF2RB) and its ligand (GM-CSF), creating a dodecameric complex. Within this structure, the close presence of CSF2RB subunits enables the associated JAK2 kinases to trans-phosphorylate. Ligand binding to the cell surface receptors for GM-CSF, IL-3, and IL-5 activates these receptors and triggers functional responses, including cellular proliferation, differentiation, survival, and maturation. Although the exact process of receptor activation remains unclear, ligand-induced dimerization of receptor subunits appears to be a crucial step in the signaling process. Pleiotropic cytokines such as IL-3, IL-5, and GM-CSF are known to promote hematopoiesis and regulate the growth and activity of immune cells (Freeburn et al., 1998; Hercus et al., 2018; Côrte-Real et al., 2022; Watanabe-Smith et al., 2016).

Multiple signaling pathways are initiated when the cytokine–receptor complex assembles in a specific stoichiometry, which is triggered by cytokine binding. These include interactions with various receptor systems and activation of the Janus kinase (JAK) family and STAT5 pathway, the mitogen-activated protein kinase (MAPK), and the phosphoinositide 3-kinase (PI3K) pathways. These signaling cascades lead to numerous biological responses, such as cell survival, proliferation, differentiation, migration, and the effector functions of mature leukocytes (Côrte-Real et al., 2022).

There are differences between GM-CSF, IL-3, and IL-5. GM-CSF is secreted by multiple cell types, including macrophages, fibroblasts, and epithelial cells, while IL-3 and IL-5 are secreted by T-cells. Cytokines play various roles in innate and adaptive immune responses and inflammatory diseases. It is becoming more widely acknowledged that the common beta chain CSF2RB cytokines are involved in the pathogenesis of various types of leukemia. GM-CSF functions as a growth and survival factor in human myeloid leukemia and improves the prognosis of chronic myeloid leukemia (CML) (Hercus et al., 2018). Acute myeloid leukemia (AML) patients’ blast cells exhibit increased GM-CSF receptor expression and proliferation. Additionally, IL-3 modulates megakaryocytes and hemopoietic stem cells, and it serves as a growth and survival factor for several lineages of both normal and malignant hemopoietic cells. Based on a recent article (Watanabe-Smith et al., 2016), a patient with T-cell acute lymphoblastic leukemia (T-ALL) presented a germline mutation in the CSF2RB gene, which can induce cell proliferation in vitro. Early evidence establishing the role of CSF2RB mutations in hematological cell lines and malignancies appeared at the end of the 20th century (D'Andrea et al., 1994; Jenkins et al., 1996; Jenkins et al., 1995).

Charlet et al. (2022) investigated the role of CSF2RB in FMS-like tyrosine kinase 3 receptor (FLT3)-internal tandem duplication (ITD)-positive AML through in vitro and in vivo studies and confirmed CSF2RB/FLT3-ITD interaction in human primary leukemic cells and cell lines with FLT3-ITD mutation. The ITD mutation found in one-third of AML cases is a mutation of FLT3 leading to receptor activation and downstream signal transduction. Binding of CSF2RB to FLT3-ITD contributes to FLT3-dependent STAT5 activation, promoting oncogenic signaling and the transformation of AML in vitro and in vivo. FLT3 forms a complex with CSF2RB, leading to its phosphorylation and activation. Activated CSF2RB leads to STAT5 phosphorylation, which then mediates the oncogenic transformation of AML. Charlet et al. (2022) knocked down CSF2RB in AML cell lines with FLT3-ITD mutation and also transfected CSF2RB-deficient mice with FLT3-ITD mutation. The result was decreased STAT5 phosphorylation, reduced cell proliferation, and increased FLT3 inhibition sensitivity. In addition, the onset of the disease was delayed in the transfected mice, and there was an increase in the survival rate. They concluded that CSF2RB can be used to treat AML with FLT3-ITD mutation by discovering therapeutic peptides to target and interfere with FLT3-ITD-dependent CSF2RB activation (Charlet et al., 2022).

Interest in the function of βc cytokines outside the hematopoietic lineages has grown in recent years. It has been found that the expression of GM-CSF is linked to some tumors, such as colorectal cancer (Li et al., 2016), neuroblastoma (Agarwal et al., 2015), and breast cancer (Park et al., 2011). Moreover, it has been shown to induce angiogenesis and local tumor invasion in head and neck cancer (Lopes-Santos et al., 2023). Numerous investigations have also revealed that myeloid-derived suppressor cells (MDSCs), which are activated by GM-CSF, play a role in the metastasis of glioma, pancreatic, and liver malignancies. In addition, IL-3 could potentially play a pathogenic role in some solid tumors. Endothelial cells, endothelial progenitor cells, and tumor-derived endothelial cells all express IL-3 receptors, which promote angiogenesis and tumor progression. A study (C Bonder and Lopez, unpublished) implied that IL-3 and its receptor may be targeted to inhibit the growth and activity of some breast cancer cells (Hercus et al., 2018).

Breast cancer accounts for one in eight cancer cases and is the leading cause of cancer-related deaths among women, with its incidence dramatically increasing in recent years. The World Health Organization (WHO) and the International Agency for Research on Cancer (IARC) reported 2.26 million new cases of breast cancer and 684,996 cases of breast cancer-related deaths in women worldwide in 2020. Furthermore, it is estimated that by 2040, there will be more than 3 million new cases diagnosed and 1 million deaths due to breast cancer (Sung et al., 2021; Arnold et al., 2022). Currently, radiographic scanning, clinical/pathological testing, physical examination, and histological data are used to classify and diagnose breast cancer. Molecular diagnostics are not frequently used in clinical settings, although they provide an accurate, equitable, and effective means of classifying breast cancer. The use of gene expression profiling to detect variations in gene activity offers a novel and accurate approach to diagnosing breast cancer (Mirza et al., 2023). Subsequently, an array of gene expression signatures has been documented for diverse cancers, serving to categorize tumors, tumor types, and stages and predict the prognosis of the cancer. Breast cancer is a very heterogeneous disease; it is still difficult to identify a single set of biomarkers or a gene signature that is common to all molecular subtypes (Mirza et al., 2023).

Rashid et al. (2021) identified a somatic, potentially transforming, and oncogenic CSF2RB mutation (S230I) in a patient with breast cancer using exome sequencing of the breast tumor and adjacent normal tissue. CSF2RB and seven other immune-related hub genes were identified to be molecular signatures in the subtype of triple-negative breast cancer (TNBC), which may be used as therapeutic targets to treat breast cancer. Huang et al. (2020) estimated the prognostic value of colony-stimulating factors (CSFs) and colony-stimulating factor receptors (CSFRs) through studies across 24 solid cancer types. These studies revealed that in nine (53%) cancer types, one of which is breast invasive carcinoma (BRCA), the high expression of CSF2RB is associated with a favorable prognosis (Huang et al., 2020). Analysis of IL-3 and IL-3 receptor subunits (IL-3RA + CSF2RB) showed their elevated expression in basal-like and luminal A breast cancers. IL-3, but not IL-3RA or CSF2RB, was found to be associated with a poor prognosis in basal-like breast cancer, which supports the role of IL-3 in promoting cancer progression (Thompson et al., 2024). Moreover, histological analysis of IL-3, IL-3RA, and CSF2RB expression in healthy breast tissue, primary tumor tissue, and metastatic tissue suggested their potential use as biomarkers in TNBC (Koni et al., 2022). Upregulation of CSF2RB—among other genes in basal-like breast cancer with RYR2 and AHNAK mutations—has been associated with a good prognosis and correlated with immune infiltrations within tumors (Cimas et al., 2020).

The present study is an attempt to understand the role of CSF2RB in breast cancer by collecting omics data from cancer genomic databases such as The Cancer Genome Atlas (TCGA), cBioPortal, TIMER2.0, GEPIA, and UALCAN. The data include gene expression profiles, mutations, methylation patterns, survival outcomes, and immune infiltration related to CSF2RB, specifically in breast cancer, and are compared to acute myeloid leukemia as a control since the role of CSF2RB in AML is well-established.

The significance of bioinformatics methods and tools has become increasingly evident with advances in technology and the accumulation of genome-scale, high-throughput data from genomics, transcriptomics, and proteomics. To analyze the data obtained from experiments of cancer research, bioinformatics scientists have developed different types of computational tools, algorithms, and data structures (Mayakonda et al., 2018; Huang et al., 2024). Moreover, several databases and web-based interactive portals have been developed to access, explore, and analyze the vast amount of cancer genomic and clinical data collected from large-scale studies (TCGA, cBioPortal, TIMER, GEPIA, and UALCAN). These databases and web-portals have been extensively used in the current manuscript; therefore, they are described in more detail below.

GEPIA (https://gepia.cancer-pku.cn/) was developed by Zefang Tang, Chenwei Li, and Boxi Kang of Zhang Lab, Peking University. It is an interactive web server that uses a standard processing pipeline to analyze the RNA sequencing expression data of 8,587 normal samples and 9,736 tumor samples from the TCGA and GTEx projects. Tumor/normal differential expression analysis, cancer type or pathological stage-specific profiling, patient survival analysis, comparable gene detection, and correlation analysis are some of the customizable features offered by GEPIA. We used GEPIA to compare the CSF2RB gene expression between breast invasive carcinoma and acute myeloid leukemia and analyze the correlation between the pathological stage of breast invasive cancer and the expression of the CSF2RB gene. We carried out a heatmap of the overall survival of the CSF2RB gene in breast invasive carcinoma and acute myeloid leukemia.

Analyses of the cancer genomics data related to the CSF2RB gene/protein from different databases revealed some striking results that need to be discussed in order to draw the right conclusion from this study. The CSF2RB gene is expressed in tumors across all cancer types available from the TCGA study (Figure 7). In addition, the expression data are available for normal and matched tumor samples from all cancer types (Figures 3, 6). In BRCA, the median expression of the CSF2RB gene is higher in normal samples than in the matched tumor samples (Figures 1, 3, 6). These results were obtained from GEPIA, TIMER2.0, and UALCAN databases, respectively. The result from GEPIA (Figure 1) was not statistically significant. In contrast, the result (Figure 3) obtained from the TIMER2.0 database (hosting only TCGA data) showed that BRCA normal samples had significantly higher expression of CSF2RB than BRCA tumor samples (Figure 3). However, in all these results (Figures 1, 3, 6), CSF2RB gene expression is higher in normal than in the tumor tissues in the context of BRCA. This observation is also supported by other studies. Analysis of the mutational effect of CSF2RB on its expression revealed no statistically significant difference between the expression levels of the wild-type and mutated CSF2RB gene (Figure 4). Moreover, the expression of this gene is not associated with the pathological stages of BRCA tumor samples (Figure 2). However, the expression differs across different subtypes of breast cancer, with luminal and HER2+ subtypes expressing lower and TNBC expressing higher than normal samples (Figure 5). This observation is not surprising because of the heterogeneous nature of the breast cancer histological/molecular subtypes. Together, these results indicate that the CSF2RB gene potentially plays i) a protective or tumor-suppressive role in luminal and HER2+ subtypes and ii) an oncogenic role in triple-negative breast cancers (TNBC). In contrast, the CSF2RB gene is significantly more highly expressed in tumors than in normal samples in AML (Figure 1). In addition, the highest expression of this gene was observed in AML and diffuse large B-cell lymphoma (DLBC), among other cancer types (Figures 3, 7). These results suggest the potential oncogenic role of CSF2RB in hematological cancer. Moreover, this association has been recently established and published in various research articles.

Mining TCGA data using the “protein paint tool” for coding mutations in the CSF2RB gene resulted in a total of nine mutations, including five missense, three nonsense, and one silent mutation (Figure 8). Exploring cBioPortal (hosting TCGA data across 1,108 samples/1,101 patients) resulted in a total of four somatic mutations in the CSF2RB gene, with a frequency of approximately 0.4% among all samples (Figure 9). Among different subtypes of breast cancer, invasive ductal carcinoma showed higher alteration frequency than invasive lobular carcinoma (Figure 10). Across different cancer types, the mutation frequency of the CSF2RB gene is the highest in skin cutaneous melanoma (11.5%) and ranges from 0.38% to 1.26% in breast cancer subtypes (Figure 11). In summary, somatic mutations in CSF2RB are not abundant in BRCA, suggesting a limited or inconsistent role as a driver in the tumor progression of breast carcinoma.

The study of CSF2RB mRNA expression and its DNA methylation revealed a negative correlation, with a Pearson correlation coefficient of −0.29 and a Spearman correlation coefficient of −0.44 (Figure 12). DNA methylation impacts the gene expression pattern, and this phenomenon was discovered half a century ago (McGhee and Ginder, 1979; Jones and Taylor, 1980). The negative correlation between mRNA expression and DNA methylation has been instrumental in identifying several key genes in different diseases, such as obesity (Chen et al., 2021). DNA methylation plays a profound role in mammalian development (Smith and Meissner, 2013) and is also implicated in various diseases (Robertson, 2005). As expected, the promoter of the CSF2RB gene is hypermethylated in tumor tissues, and the methylation level is higher than that in normal tissues (Figure 13). This methylation difference explains the reason behind the higher gene expression of CSF2RB in normal tissues than that in tumor tissues, as shown in Figure 1. Promoter methylation of CSF2RB across different BRCA subtypes varies greatly, with luminal and HER2+ being hypermethylated and TNBC not being hypermethylated (Figure 14), which explains the gene expression pattern of this gene across different subtypes, as shown in Figure 5. Promoter methylation across different ethnic populations shows that the CSF2RB promoter is hypermethylated in breast tumors of Caucasian, African-American, and Asian populations (Figure 15). Figure 16 shows no difference in promoter methylation across BRCA stages, and this result explains the gene expression behavior across stages, as shown in Figure 2. In conclusion, the methylation pattern of the CSF2RB gene promoter across different breast cancer subtypes, stages, and ethnicities agrees very well with the gene expression pattern in an inverse manner.

Survival analyses have concluded that overall and disease-free survival probabilities are not significantly different between BRCA patients with or without CSF2RB genetic alteration (Figure 17). It means that CSF2RB does not have a significant impact on the pathobiology of breast carcinoma. However, the disease-free survival probability of patients with the altered CSF2RB gene remains lower than that of patients with the unaltered gene (Figure 17B). Comparison of overall survival between CSF2RB-altered and unaltered patient groups in BRCA and AML showed that the CSF2RB alterations are associated with a poorer prognosis in the case of AML but with a favorable prognosis in BRCA (Figure 18). Survival analysis based on CSF2RB expression levels shows similar results (Figure 19), where differences in CSF2RB expression do not significantly impact cumulative survival in BRCA patients (Figure 19A) groups but do have an impact in AML cases (Figure 19B). This conclusion is drawn on the basis of the log-rank p-value, which is 0.197 (non-significant) in the case of BRCA and 0.045 (significant) in the case of AML. However, a separate survival analysis of BRCA patients using the UALCAN database indicates that a statistically significantly difference in survival probability between groups with high and low CSF2RB expression (Figure 20). At first glance, the results from Figures 19, 20 appear to be contradictory. The reasons could be minor differences in the extent of data, such as i) the number of patients, ii) follow-up time, and iii) the expression variations across different assay platforms. At the end, the correlation analysis of CSF2RB expression and immune infiltration levels shows that there is a positive correlation of CD8 T-cell infiltration level and CSF2RB expression, stating the positive prognostic value of CSF2RB in BRCA patients and different subtypes (Figure 21). In general, BRCA patients have a positive correlation between CSF2RB expression and CD8⁺ T-cell infiltration level from different sources, with a p-value <0.05. However, we observe some insignificant (p > 0.05) positive correlations when samples are stratified into BRCA subtypes. The possible explanations for these discrepancies could be divergent data sources and their differences in data processing across different platforms.

The role of CSF2RB and other similar receptors in hematological or blood cancers was established in recent decades through several scientific research studies using hematological cell lines, primary cells, animal models, and human patients (Watanabe-Smith et al., 2016; Liongue and Ward, 2014; Maxson et al., 2013). CSF2RB mutations or alterations in signaling pathways and expression can contribute to cancer progression (Watanabe-Smith et al., 2016; Watanabe-Smith et al., 2015; Kassem et al., 2018). Other studies have shown that high CSF2RB expression is associated with an unfavorable prognosis in bladder and esophageal cancers, whereas it is related to a favorable prognosis in breast cancer, cervical squamous cell carcinoma and endo-cervical adenocarcinoma (CESC), and colon adenocarcinoma (Huang et al., 2020). The expression of CSF2RB in lung adenocarcinoma was lower in the tumor sample than in the normal sample, and low expression was related to poor survival (Zhu et al., 2022). CSF2RB expression level was also positively related to the levels of infiltrating CD4⁺ T cells, macrophages, NK cells, and monocytes in LUAD (Zhu et al., 2022). Similarly, our results showed that CSF2RB expression was correlated to CD8 cell infiltration levels in BRCA and its subtypes, and it could be associated with the immune response in the tumor microenvironment and may lead to immune cell activation or recruitment, which makes it a potential target for breast cancer therapy. CSF2RB has a low somatic mutation rate in breast cancer samples/patients, with a frequency of approximately 0.4%. The CSF2RB promoter methylation level in tumor samples of breast carcinoma and its subtypes and normal samples revealed that tumor samples are hypermethylated, which can explain the low expression of CSF2RB in tumor samples. Normal tissue and triple-negative breast cancer have normal levels of methylation. DNA methylation, an important epigenetic factor, is known to regulate gene expression (Moore et al., 2013).

In conclusion, CSF2RB is generally downregulated in breast tumor tissues, but its expression varies across different subtypes. Luminal and HER2+ subtypes exhibit lower expression and TNBC shows higher expression than that of normal tissues (Figure 5). CSF2RB does not seem to be a somatic mutational hot spot since the frequency of mutation in samples is very low. Moreover, promoter methylation patterns correspond well with the gene expression profiles across different subtypes of BRCA (Figure 14). The prognostic value of CSF2RB is not very clear and statistically significant in the current study (Figures 17–19), except in one experiment using the UALCAN database (Figure 20). Therefore, we find it difficult to conclude that CSF2RB could be a prognostic biomarker for BRCA. One of the possible explanations for the ambiguous prognostic effect could be heterogeneity of data sources, and we need to study these effects in each subtype separately. However, functional studies are required to claim CSF2RB as a breast cancer hallmark gene or a potential therapeutic and prognostic candidate for breast cancer treatment. Studies involving gene expression, DNA methylation, and integration with survival data for each of the BRCA subtype samples are highly recommended.

The major limitation of the current study is the integration of data from different sources, study designs, assay platforms, and bioinformatics analysis pipelines. These factors might contribute to the visible discrepancies in terms of statistical significance, particularly p-values.