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Article

Prognostic Significance of CSF-1R Expression in Early Invasive Breast Cancer

1
Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC V6T 1Z7, Canada
2
Centre for Regenerative Medicine and Stem Cell Research, Aga Khan University, Karachi 74800, Pakistan
*
Author to whom correspondence should be addressed.
Cancers 2021, 13(22), 5769; https://doi.org/10.3390/cancers13225769
Submission received: 27 September 2021 / Revised: 12 November 2021 / Accepted: 13 November 2021 / Published: 18 November 2021
(This article belongs to the Special Issue Biological Basis of Anti-tumor Therapies)

Abstract

:

Simple Summary

Experimental evidence suggests that CSF-1/CSF-1R signaling attracts immune cells called macrophages into the tumor microenvironment which promote the capacity of cancer cells to spread. In this study, we investigated CSF-1R protein expression on breast cancer cells and macrophages and their relationship with other immune cells and breast cancer survival. Our results show that cases with high CSF-1R expression on cancer cells, but not macrophages, are associated with inferior survival, particularly in the common hormone receptor-positive breast cancer group, which persists even in the presence of an active anti-tumor host immune response.

Abstract

Colony-stimulating factor-1 receptor (CSF-1R) signaling promotes an immune suppressive microenvironment enriched in M2 macrophages. Given that CSF-1R inhibitors are under investigation in clinical trials, including in breast cancer, CSF-1R expression and association with immune biomarkers could identify patients who derive greater benefit from combination with immunotherapies. TIMER2.0 and bc-GenExMiner v4.7 were used to assess the correlation of CSF1R mRNA with immune infiltrates and prognosis. Following a prespecified training–validation approach, an optimized immunohistochemistry assay was applied to assess CSF-1R on carcinoma cells and macrophages on breast cancer tissue microarray series representing 2384 patients, coupled to comprehensive clinicopathological, biomarker, and outcome data. Significant positive correlations were observed between CSF1R mRNA and immune infiltrates. High carcinoma CSF-1R correlated with grade 3 tumors >2 cm, hormone receptor negativity, high Ki67, immune checkpoint biomarkers, and macrophages expressing CSF-1R and CD163. High carcinoma CSF-1R was significantly associated with poor survival in univariate and multivariate analyses. Adverse prognostic associations were retained in ER+ cases regardless of the presence of CD8+ T cells. CSF-1R+ macrophages were not prognostic. High carcinoma CSF-1R is associated with aggressive breast cancer biology and poor prognosis, particularly in ER+ cases, and identifies patients in whom biomarker-directed CSF-1R therapies may yield superior therapeutic responses.

1. Introduction

Colony stimulating factor-1 receptor (CSF-1R) is a class III receptor tyrosine kinase that is encoded by the CSF1R gene, previously called the c-fms protooncogene [1]. CSF-1R is normally expressed in a wide range of cells derived from hematopoietic progenitors, including monocytes, tissue-resident macrophages, dendritic cells, and osteoclasts [1]. Engagement of CSF-1R with its ligands, CSF-1 or the more recently identified interleukin-34, causes receptor homodimerization and progressive autophosphorylation of the tyrosine residues on its cytoplasmic tail. The subsequent downstream signaling involves the activation of MEK, PIK3, and PLC-γ2 pathways that regulate the lineage commitment, survival, proliferation, and biological functions of a myriad of cells, including macrophages that constitute the mononuclear phagocyte system [1,2,3].
Preclinical studies have demonstrated a critical role of CSF-1 [4] and CSF-1R [5] in normal breast development. In clinical studies, it has been shown that compared to low expression in the normal breast epithelium, high expression of CSF-1 and CSF-1R is found in the lactating breast epithelium, supporting a potential role of this cytokine–receptor pair in ductal morphogenesis [4]. Aberrant expression of CSF-1 and CSF-1R has been linked with unfavorable outcomes in hematological and solid organ malignancies [6,7,8]. In breast cancer specifically, preclinical studies suggest that this could be attributed to oncogenic paracrine signaling, whereby tumor cell-derived CSF-1 facilitates the recruitment of CSF-1R expressing polarized macrophages into the tumor microenvironment, thereby promoting angiogenesis, tumor cell migration, and invasion [9,10,11,12,13]. Additionally, an autocrine signaling mechanism has also been described in xenograft models of the claudin-low subtype of breast cancer, where TGF-β-driven CSF-1R expression maintains the claudin-low phenotype but promotes invasive potential by suppressing junctional proteins; inhibition of CSF-1R signaling in the same model leads to the upregulation of luminal cytokeratins with a reduction in tumor cell invasiveness but enhanced proliferative capacity [14].
Immune checkpoint inhibitor therapy in combination with chemotherapy has emerged as a promising therapeutic modality for early and metastatic triple-negative breast cancer [15,16,17]. Clinical benefit has been demonstrated with regards to higher rates of pathological complete responses [15,18,19] and a modest increase in objective response rates [16], though improvement in progression-free survival and overall survival has been predominantly achieved in PD-L1-enriched, treatment-naïve metastatic tumors [16,17,20]. Durable responses with immune checkpoint blockade have been reported in diverse tumor types [21]; however, such evidence is limited in breast cancer [16,22]. Primary tumor refractiveness and acquired resistance contribute to inconsistent responses, even in histologically similar tumor types [23]. Factors enabling immune escape are complex and include mechanisms creating an immune-tolerant microenvironment consisting of but not limited to regulatory T cells, myeloid-derived suppressor cells, and tumor-associated macrophages [24].
Dense infiltration with tumor-associated macrophages portends aggressive disease biology and poor prognosis in breast cancer [25]. Tumor-associated macrophages enhance the metastatic potential of carcinoma cells and facilitate remodeling of the extracellular matrix [26]. Equally important is the modulation of the immune microenvironment that contributes to poor treatment responses. A substantial body of experimental evidence indicates that tumor-associated macrophages impair the cytotoxic function of T cells by several mechanisms that include depletion of the metabolic substrate L-arginine via expression of arginase-1, production of reactive oxygen species (which in turn induce expression of PD-L1 on macrophages), and recruiting regulatory T cells [27]. It has also been suggested that TGF-β produced by the macrophages promotes a desmoplastic response in the tumor stroma, which impedes the intratumoral recruitment of cytotoxic T cells [28]. In preclinical models, tumor-associated macrophages contribute to resistance to chemotherapy [29,30], endocrine therapy [31], radiation [32], anti-HER2 [33], and immune-targeted therapies [34,35]. Combination therapies to either deplete or repolarize tumor-associated macrophages have shown encouraging results [36]. In particular, small molecules and monoclonal antibodies targeting CSF-1/CSF-1R signaling have been found to decrease macrophage infiltration and the cancer stem cell pool, enabling the restoration of the antitumor activity of the cytotoxic T cells [37,38]; their clinical efficacy is under investigation in several ongoing clinical trials [36].
Previously, limited studies have reported the prognostic impact of CSF-1R expression in human breast cancers [39,40,41], and the significance of its expression on tumor-associated macrophages in clinical breast cancer specimens is not known. Except for a single study of moderate sample size (n = 581) [39], the remaining studies were inadequately powered (fewer than 70 clinical samples each), limiting statistical inferences [40,41]. Given that CSF-1R inhibitors are under active study in clinical trials, including in breast cancer, positive CSF-1R staining in clinical breast cancer specimens and its association with immune cells could help identify which patients might best benefit from combination with immunotherapies. Of particular interest are ER+ breast cancers, where emerging data are suggestive of the presence of a unique microenvironment characterized by tolerant, protumorigenic immune contexture that is rich in tumor-associated macrophages [42]. Hence, the present study was undertaken first to investigate the prognostic significance of CSF1R mRNA expression and its correlation with immune cell infiltrates. Subsequently, we applied an in-house optimized CSF-1R immunohistochemistry assay on a particularly large tissue microarray series linked to detailed biomarker and clinical data using a training–validation approach. We sought to test the hypothesis that the expression of CSF-1R protein on carcinoma cells will identify tumors with aggressive features and provide prognostic information in ER+ breast cancers, identifying a subgroup of patients associated with poor clinical outcome. Furthermore, we also determined the prognostic significance of CSF-1R+ tumor-associated macrophages and their association with lymphocytic infiltrates expressing immune checkpoint and CD163+ M2 macrophage biomarkers in the context of ER+ breast cancers.

2. Materials and Methods

2.1. Bioinformatic Analyses: Correlation of CSF1R mRNA with Stromal Immune Infiltrates, Tumor-Associated Macrophage Gene Signature, and Prognosis

Tumor IMmune Estimation Resource (TIMER) is a web-based portal comprised of three fundamental components, i.e., immune, exploration, and estimation [43,44]. Each of these components has different modules that provide an exhaustive approach for analyzing the tumor-immune interactions across 32 different cancer types from the TCGA database. We accessed the Gene_Corr module to investigate the correlation of CSF1R mRNA with the 37-gene set described for tumor-associated macrophages [26]. The purity-adjusted partial Spearman’s rho values and associated p-values were generated, representing the degree of the correlation. The Gene module was used for analyzing the correlation between the CSF1R mRNA and immune infiltrate levels through a statistical deconvolution method described previously [45], and the results were displayed as scatter plots with the purity-adjusted partial Spearman’s rho values and the associated p-values.
The Breast Cancer Gene-Expression Miner v4.7, an open-access, web-based tool [46], was utilized to explore the expression of CSF1R mRNA in the invasive breast cancer cases represented in the TCGA cohort (n = 1033) [47] and validated in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort (n = 1980) [48]. Targeted analysis was selected, prognostic significance of CSF1R mRNA was estimated by applying a univariate Cox proportional hazard model, and results were presented as Kaplan–Meier survival curves for disease-free survival. The median threshold was selected for classifying CSF1R mRNA expression levels as high versus low.

2.2. Breast Cancer Clinical Cohorts for Optimizing Immunohistochemistry Protocol and Hypothesis Testing

Assessment of CSF-1R protein was initially performed on a local population series called the UBC cohort to finalize the immunostaining protocol, interpretation, and optimal scoring criteria before applying to the larger BC Cancer cohort. The patients included in the UBC cohort (n = 330) were diagnosed with early invasive breast cancer at the University of British Columbia Hospital between 1989 and 2002. The clinicopathological features, surgical procedures, adjuvant radiation/systemic treatments, and clinical outcomes for a median follow up of 13 years have been described previously [49].
The BC cancer cohort represents our independent, main series (n = 2384). These patients were diagnosed with stage I–III invasive breast cancer between 1986 and 1992 at the British Columbia Cancer Agency, Vancouver. The adjuvant treatments recommended for these patients were in accord with the provincial guidelines at the time and preceded anti-HER2 and immune checkpoint inhibitor therapies. The median follow-up of the patients is 12.5 years. This cohort has been comprehensively profiled for several key biomarkers, [50] including those related to immune-oncology, i.e., stromal tumor-infiltrating lymphocytes (assessed on hematoxylin- and eosin-stained slides), CD8, FOXP3, TIM3, LAG-3, PD-1 (on intraepithelial tumor-infiltrating lymphocytes (iTILs)), PD-L1 (on carcinoma cells), and CD163 (on macrophages), and assessed by immunohistochemistry [51,52,53,54,55]. The patient population of the BC Cancer cohort has been split into internal training and validation sets as described previously [56]. For the purpose of this study, the training set (n = 1183) was used to perform correlative and prognostic analyses for testing our prespecified hypothesis for the biomarker under study. The significant findings were re-tested for confirmation in the validation set (n = 1201). Post-hoc analyses were then performed on a prespecified ER+ subgroup using the combined cohort (n = 2384) to explore the prognostic association of CSF-1R expression on carcinoma cells in the context of CSF-1R+ macrophages and other immune infiltrates. Patients diagnosed with bilateral breast cancers, ductal carcinoma in situ without an invasive component, and metastatic disease at presentation, or those who received neoadjuvant chemotherapy, were omitted from the analyses. Details about the clinicopathological characteristics, treatments, relapses, and survival have been described previously [50].
The Clinical Research Ethics Board of the University of British Columbia and the Breast Cancer Outcomes Unit of BC Cancer granted authorization for retrieving the archived tumor samples and the corresponding de-identified clinical information for this retrospective biomarker study, which was conducted in accordance with the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) guidelines [57]. A flow diagram illustrating the study design is presented as Supplementary Figure S1.

2.3. Tissue Microarrays and Immunohistochemistry

Archived formalin-fixed, paraffin-embedded tumor tissues from both the cohorts were utilized for construction of tissue microarrays with a 0.6-mm diameter core size, as described previously [49,58]. Briefly, the UBC cohort was represented in 3 tissue microarray blocks consisting of duplicate cores, while the tumors from the BC Cancer validation cohort were assembled into 17 blocks with one core per case. Sections were cut at 4 µm, and immunostaining was performed on a Ventana Discovery XT stainer. Following heat-induced epitope retrieval (Cell Conditioning 1, Ventana Medical Systems, Inc., Oro Valley, AZ, USA) in sodium citrate buffer (pH 6.0) for 10 min, the sections were incubated with anti-human CSF-1R monoclonal antibody (clone SP211; ab183316) at room temperature for 1 h at 1:500 dilution. Sections were then incubated with secondary antibody (UltraMap anti-Rb HRP) for 16 min, and immunoreactivity was visualized using a ChromoMap DAB detection kit (Ventana Medical Systems, Inc.). Human colonic tissue was used as a positive control; for the negative control, the primary antibody was replaced with phosphate-buffered saline. Tissue microarray slides were digitally scanned at 10X objective magnification on the BLISS system (Bacus Laboratories/Olympus America, Lombard, IL, USA) and were visually scored by a breast pathologist (DG) who was blinded to the clinical information. CSF-1R revealed a membranous/cytoplasmic staining pattern. The proportion of the carcinoma cells positively stained was recorded. High expression was defined when ≥10% carcinoma cells stained positive while staining of <10% was considered as low expression (Figure 1A). For tumor-associated macrophages, up to 100 positively stained cells were counted per core, and the threshold was set at 2 (low, <2 and high, ≥2) (Figure 1B). Cores with fewer than 50 invasive cells were excluded from evaluation. Duplicate cores were handled by estimating the mean of the positively stained cells. Images from these slides are available for public access via the website of the Genetic Pathology Evaluation Center (http://www.gpec.ubc.ca/csf1r (accessed on 27 September 2021)). The scoring methodologies for the immune biomarkers have been described previously [51,52,53,54,55].

2.4. Statistical Analyses

SPSS (IBM SPSS Statistic, Version 25.0) was used for statistical analyses. Descriptive statistics were estimated for categorical and continuous variables. A chi-square test or Fisher exact test was used to determine the correlations between CSF-1R expression and clinicopathological characteristics or immune cell infiltrates. The Kaplan–Meier method was applied for the evaluation of cumulative survival probabilities using breast cancer-specific survival (defined as the period between the date of diagnosis and the date of death due to breast cancer) as the predetermined main survival endpoint. All patients who were either alive at the end of the follow-up or died due to non-breast cancer-related causes were censored. Differences in the survival probabilities between the groups were estimated by the log-rank test. For our hypothesis testing using a training–validation approach, the assumptions for the Cox proportional hazard model were violated by the 20-year follow up data. Hence, these analyses were performed by limiting the breast cancer-specific survival time up to 10 years. For multivariate analysis, Cox proportional hazard models were developed for reporting hazard ratios with 95% confidence intervals after correction for traditional clinicopathological characteristics that included age, tumor size, grade, axillary lymph nodal status, and lymphovascular invasion. A p-value of <0.05 was regarded as statistically significant. The Bonferroni correction was applied to address the concerns of multiple comparisons during correlative analyses (involving 10 or more variables), making the criterion for statistical significance p < 0.005. Kaplan–Meier survival curves for exploratory analyses are presented on the combined cohort of n = 2384 patients, for whom 20-year follow-up data was available.

3. Results

3.1. Correlation of CSF1R mRNA Expression with Immune Cell Abundance and Prognosis

We first assessed the correlation of CSF1R mRNA expression in the tumor microenvironment with the level of immune infiltration using the TIMER2.0 web server [43,44]. Our results showed a significantly positive correlation of CSF1R mRNA expression with immune cell abundance comprising B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells (Figure 2A).
Higher expression of a recently described 37-gene tumor-associated macrophage gene signature, derived from whole-tumor RNA sequencing of 47 breast cancers, has been shown to associate with aggressive subtypes and poor clinical outcomes [26]. We correlated the expression of CSF1R with the tumor-associated macrophage gene set and observed a highly significant positive correlation for all 37 genes (Supplementary Table S1). These data support the role of CSF1R in regulating the biological functions of tumor-associated macrophages as has been shown in previous preclinical studies [12,59]
No significant prognostic association was observed between CSF1R mRNA expression in the bulk tumor tissue and clinical outcomes in the TCGA cohort. This lack of significant association was further validated in the METABRIC cohort of invasive breast cancers (Figure 2B,C).
The immune cell infiltration was also associated with significant positive correlation with CSF1 mRNA expression (Supplementary Figure S2A). However, no significant prognostic associations were observed for CSF1 mRNA in the TCGA and METABRIC cohorts (Supplementary Figure S2B,C).

3.2. Correlation of CSF-1R+ Carcinoma Cells with Clinicopathological Features, Immune Cell Infiltrates, and Prognosis in The BC Cancer Cohort

The locked down immunohistochemistry protocol was applied to the BC Cancer series. The selection of the optimal positivity threshold and the correlative and prognostic associations of CSF-1R on carcinoma cells and macrophages were first assessed in the training cohort (n = 1183) of the BC Cancer series (Supplementary Tables S2–S4 and Supplementary Figure S3) before confirming the results in the validation cohort, presented in this section.
In all, there were 1201 scorable cases in the validation set of the BC Cancer series, of which 23.1% (277/1201) were positive for CSF-1R expression on carcinoma cells, and high expression was significantly associated with tumor size > 2 cm, grade 3 histology, Ki67 index ≥ 14%, negative hormone receptor status, HER2 positivity, and non-luminal subtypes (Table 1). CSF-1R+ carcinoma cells are significantly associated with stromal tumor-infiltrating lymphocytes; intraepithelial lymphocytic infiltrates expressing CD8, FOXP3, TIM3, LAG3, and PD-1; and PD-L1+ carcinoma cells (p < 0.001) (Table 2). In addition, a significantly positive correlation (p < 0.001) is also observed between CSF-1R+ carcinoma cells and macrophages expressing CSF-1R and CD163 (Table 2), supporting the plausible existence of a CSF-1/CSF-1R paracrine signaling mechanism as has been suggested in the preclinical studies [9].
Breast cancers with high expressions of CSF-1R on carcinoma cells are associated with significantly poor breast cancer-specific survival compared to tumors with low expression (Figure 3A) (HR 1.63; 95% CI 1.26–2.09; p < 0.001). However, the expression of CSF-1R+ macrophages did not reveal any significant prognostic associations in either the training (Supplementary Figure S3B) or validation sets of the BC Cancer series (HR 1.0, 95% CI 0.80–1.27; p = 0.97) (Figure 3B).
We next performed a prespecified subgroup analysis to investigate the prognostic impact of CSF-1R+ carcinoma cells in cases stratified by ER status. We found that CSF-1R+ carcinoma cells are associated with significantly adverse outcome in patients with ER-positive status (HR 1.82, 95% CI 1.30–2.54; p < 0.001) but not in those with ER-negative status (HR 1.08, 95% CI 0.73–1.60; p = 0.71) (Figure 3C,D). The subsequent multivariate analysis confirms that high CSF-1R expression on carcinoma cells is independently associated with unfavorable outcome (HR 1.58; 95% CI 1.21–2.05; p = 0.001) (Table 3).

3.3. Exploratory Analyses: Prognostic Association of CSF-1R-Expressing Carcinoma Cells with Immune Infiltrates in ER-Positive Breast Cancers

In contrast to triple-negative breast cancers, immune-enriched ER-positive breast cancers are characterized by a distinctive immune profile which is dominated by TGF-β signaling, dysfunctional CD8+ T cells, and enrichment of M2 tumor-associated macrophages [42]. Clinical studies have shown that high levels of FOXP3- and CD8-positive lymphocytic subsets are linked with inferior clinical outcomes in ER-positive breast cancers [52,60]. Here, we performed an exploratory analysis to examine the prognostic impact of CSF-1R+ carcinoma cells in the context of iTIL subsets expressing CD8 or FOXP3 in ER-positive breast cancers in the combined cohort of the BC Cancer series with complete 20-year follow-up information (n = 1666). Our results show that high CSF-1R expression on carcinoma cells is associated with significantly inferior survival in cases harboring CD8+ iTILs (HR 1.65, 95% CI 1.21–2.26; p = 0.002) (Figure 4A). When analyzed for regulatory T cells, the cases with concurrent low CSF-1R+ carcinoma cells and low FOXP3 iTILs exhibit the best outcome (HR 0.71, 95% CI 0.60–0.86; p = 0.001) (Figure 4B). Together, these results suggest an association of CSF-1R+ carcinoma cells in supporting an immune-suppressed microenvironment.
We and others have previously shown that CD163+ M2 macrophages are associated with poor prognosis in breast cancer [25,54]. We performed an exploratory analysis to examine the relationship of carcinoma cells expressing CSF-1R in the context of tumor-associated macrophages stratified by ER expression. We observed that in ER-positive cases, concomitant high expression of CSF-1R on carcinoma cells and macrophages is associated with significantly poorer clinical outcome (HR 1.57, 95% CI 1.13–2.17; p = 0.006), compared to ER-negative cases (HR 1.09, 95% CI 0.75–1.57; p = 0.66) (Figure 5A,B). Similar results are observed when analysis is performed in CD163+ M2 macrophage-enriched ER-positive breast cancers (Figure 5C,D). Together, these results show a negative prognostic association linked with the concurrent expression of CSF-1R+ carcinoma cells and CSF-1R+ macrophages in ER-positive breast cancers.

4. Discussion

We report the prognostic significance of CSF-1R protein expression on carcinoma cells and tumor-associated macrophages in a large, well-characterized cohort of early breast cancer patients. Key findings of our study include (a) poor clinical outcome associated with high expression of CSF-1R+ carcinoma cells that was maintained in ER-positive breast cancers despite the presence of infiltrating lymphocytes expressing CD8 and (b) a significant positive correlation between CSF-1R+ carcinoma cells and tumor-associated macrophages in a manner that suggests that its expression on carcinoma cells could be a factor driving poor outcome in the ER-positive subgroup, whereas a lack of its expression on malignant epithelial cells corresponds with significantly improved outcome regardless of the presence of CSF-1R+ tumor-associated macrophages.
Our analysis of TCGA and METABRIC data sets in contrast did not reveal a significant prognostic association for CSF1R or CSF1 at the mRNA level. These observations are not necessarily surprising. Since bulk tumor-derived transcriptomic data quantify total gene expression from heterogenous cell types, CSF1R and CSF1 transcripts could be mostly derived from the stromal tumor-associated macrophages (which express this highly in comparison to relatively low expression in carcinoma cells); CSF1, in addition, is also expressed by several stromal cells such as fibroblasts, endothelial cells, and smooth muscle cells [61]. Our findings in this regard are important, as using immunohistochemistry, we were able to distinguish between carcinoma cell and macrophage cell CSF-1R expression. We believe that our data, showing a lack of prognostic association of CSF-1R on macrophages, are in agreement with the results of transcriptomic analysis on the TCGA and METABRIC data sets (Figure 2B,C).
Previously, few studies [39,40,41,62] have investigated CSF-1R expression in clinical samples showing prognostic relevance with regards to ipsilateral breast cancer recurrence [62] and nodal involvement [39]. However, these studies, being underpowered, either failed to show statistically meaningful results [40] or could not confirm the independent prognostic significance of CSF-1R beyond standard clinical factors [39].
The oncogenic role of CSF-1R has been described mostly in relation to its ligand, CSF-1. However, a ligand-independent protumorigenic role for CSF-1R has also been shown in preclinical models, where activating mutations in the c-fms protooncogene have shown transforming potential in NIH 3T3 cells independent of the CSF-1 ligand [63]. Likewise, using an MCF10A cell line model, it has been shown that constitutively active CSF-1R can alter acinar morphology by inducing destabilization of cell-to-cell adhesions via a mechanism that involves src kinases [64]. Together, these data suggest that constitutively active CSF-1R may potentially drive oncogenesis. However, these observations warrant further investigation in clinical breast cancer specimens.
Our immunohistochemistry results are particularly relevant in the context of ER-positive breast cancers, which comprise approximately 70% of all newly diagnosed invasive breast cancers [65]. Whether CSF-1R signaling predominantly regulates the luminal phenotype needs further investigation. However, preclinical studies do suggest that CSF-1R signaling may have a role in regulating luminal differentiation, as mice bearing homozygous mutations in CSF1R have defects in mammary ductal branching [5], and that hyperstimulation of CSF-1R disrupts the formation of ductal acini, inducing hyperproliferation in a non-malignant luminal cell line model [64].
Overall, ER-positive breast cancers represent indolent tumors that are generally considered less immunogenic on account of low tumor mutational burden [66], relatively lower expression of immune checkpoints [67], and generally low counts of tumor-infiltrating lymphocytes [68,69]. Emerging data challenge this paradigm and support the existence of distinct immune subsets in ER-positive breast cancers [70]. Recently, it has been shown that, in contrast to immune-rich triple-negative breast cancers, immune-rich ER-positive breast cancers are characterized by TGF-β signaling, which dampens host anti-tumor immune responses by promoting the exhaustion of CD8+ T cells, infiltration with FOXP3+ T regulatory subsets, and M2 macrophage polarization [42]. Together, these data provide some insight into the heterogenous responses of advanced stage ER-positive breast cancers to immune checkpoint inhibition in clinical trials [71,72,73,74]. Whilst prior treatments may possibly weigh heavily in producing sub-optimal responses, the use of immune checkpoint inhibitors in the neoadjuvant setting have yielded encouraging results in hormone receptor-positive/HER2-negative breast cancers [19].
Given the high frequency of M2 macrophages in ER-positive breast cancers [42] and their plausible role in inducing resistance to standard adjuvant and immune checkpoint inhibitor therapies [29,31,32,33,34], combination therapies, including those targeting tumor-associated macrophages in breast cancers, are an attractive concept. Preclinical studies have shown that targeting CSF-1/CSF-1R signaling depletes tumor-associated macrophages by inducing apoptotic death [75], inhibits their recruitment from circulating monocytes [76], and induces M2–M1 polarization [34]. The net result is a reprogrammed immune contexture with a switch from immune-suppressed to an immune-activated, tumoricidal microenvironment [34,59]. While results from trials testing combined targeting of PD-1/LI and CSF-1R are still pending [37], promising efficacy signals of CSF-1R inhibitors have been demonstrated in combination with chemotherapy in solid organ malignancies, including breast cancer [77]. Of note, despite their capacity to eliminate tumor-associated macrophages, limited anti-cancer activity has been observed with use of CSF-1R inhibitors alone or in combination with chemotherapeutic agents [78,79]. Indeed, these observations are in part supported by preclinical studies showing a significant impact of the timing of initiation of anti-CSF-1R therapies, showing diminished anti-tumor activity when CSF-1R inhibitors are administered in mice bearing established tumors versus when therapy is started concurrent with tumor implantation [80]. It has been shown that the carcinoma cells actively contribute to compensatory mechanisms that promote the survival of macrophages following CSF-1R inhibitor therapy [81].
Even though several biomarkers for tumor-associated macrophages have shown prognostic implications [25], at present, no companion diagnostic tests are available to predict benefit from macrophage-targeted interventional therapies. Our biomarker study demonstrates that CSF-1R expression on tumor-associated macrophages does not provide prognostic value; however, it is likely that in vivo CSF-1R expression on both the carcinoma cells and host macrophages contributes to the pharmacologic effects of inhibitors. Whether combined assessment of CSF-1R expression on both the carcinoma cells and immune cells demonstrates better predictive capacity needs further investigation in correlative studies linked to trials of CSF-1R-targeted therapies.
Strengths of our study include the utilization of a hypothesis-driven training–validation approach for evaluation of CSF-1R expression and the large size of the BC Cancer cohort, for there exist previously generated extensive data relevant to immune biomarkers. Our study has some limitations which must be acknowledged. Firstly, our study was designed to evaluate the expression of CSF-1R on carcinoma cells and tumor-associated macrophages using a single biomarker immunohistochemistry. However, the CSF-1R signaling axis also influences other immune and non-immune subsets, including dendritic cells, neutrophils, and cancer-associated fibroblasts, which may either augment or neutralize the effects of CSF-1R inhibition [80,82]. Comprehensive evaluation of the tumor microenvironment with multiplexed approaches might improve prognostic and predictive capacity, particularly in the context of immune checkpoint inhibitor therapies [83]. Secondly, we did not evaluate the immunohistochemical expression of CSF-1, a major ligand of CSF-1R that influences the recruitment and polarization of M2 tumor-associated macrophages. Thirdly, we assessed CSF-1R expression on morphologically assessed tumor-associated macrophages and did not perform multiplex immunohistochemistry to confirm co-expression with other macrophage biomarkers. Fourthly, our study was based on immunohistochemistry performed on formalin-fixed tissues assembled on tissue microarray cores which were sampled from a tumor-rich region and hence may not sufficiently capture the heterogeneity of the immune microenvironment [84]. Lastly, the patients included in our cohorts received treatments that were approved by provincial guidelines that date back to more than 30 years and do not reflect the more contemporary adjuvant treatments that are presently recommended.

5. Conclusions

Our results demonstrate that CSF1-R expression on carcinoma cells detected by immunohistochemistry provides prognostic information in breast cancers, particularly in a subset of ER-positive cases, and may represent an actionable target for patient selection in trials evaluating CSF-1R blockade. Findings from our exploratory analyses showing a negative association of CSF-1R+ carcinoma cells even in immune-rich ER-positive breast cancers require validation in independent clinical cohorts.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/cancers13225769/s1, Figure S1: Flow diagram illustrating the study design; Figure S2: Correlation of CSF1 mRNA expression with immune cell infiltrates and prognosis in breast cancer; Figure S3: Kaplan Meier survival curves showing breast cancer specific survival in the training set of BC Cancer series; Table S1: Correlation of CSF-1R mRNA with 37-gene tumor-associated macrophage signature; Table S2: BC Cancer series training set: correlation of CSF-1R+ carcinoma cells with clinicopathological features; Table S3: BC Cancer series training set: correlation of CSF-1R+ carcinoma cells with immune biomarkers; Table S4: Multivariate analysis for CSF-1R+ carcinoma cells in the training set of BC Cancer cohort.

Author Contributions

Conceptualization: S.B. and T.O.N.; methodology, N.R., S.B., A.S.C. and D.G.; formal analysis, N.R., S.B., A.S.C., D.G. and T.O.N.; investigation, N.R., D.G. and T.O.N.; resources, T.O.N.; data curation, S.C.Y.L. and T.O.N.; writing—original draft preparation, N.R., S.B., A.S.C. and T.O.N.; writing—review and editing, N.R. and T.O.N.; visualization, N.R. and T.O.N.; supervision, T.O.N.; project administration, T.O.N.; funding acquisition, T.O.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by an operating grant from the Canadian Cancer Society (#705463) to T.O.N.

Institutional Review Board Statement

The Clinical Research Ethics Board of the University of British Columbia and British Columbia Cancer Agency approved this research project and the access to the de-identified data. (Approval Code: H17-01385).

Informed Consent Statement

In accordance with the Canadian Tri-Council Policy Statement for ethical research involving human subjects, informed consent was waived, as anonymized archival specimens were utilized in this study.

Data Availability Statement

As per the institutional policy for protecting patient privacy, the clinical information included in this study is not publicly available. Requests or inquiries for accessing the clinical data files should be referred to the corresponding author. The data presented in this study can be made available to qualified researchers only if a satisfactory requisition is approved by the Breast Cancer Outcomes Unit of BC Cancer, subject to completion of a Data Transfer Agreement and confirmation of ethical approval. Images from the tissue microarray slides are available for public access via the website of Genetic Pathology Evaluation Center (http://www.gpec.ubc.ca/csf1r (accessed on 27 September 2021)).

Acknowledgments

We acknowledge the technical support provided by Monica Ta and Christine Chow at the Genetic Pathology Evaluation Centre for performing immunohistochemistry experiments.

Conflicts of Interest

Nielsen reports grants from the Canadian Cancer Society during the conduct of the study, personal fees from Bioclassifier LLC, and personal fees from NanoString Technologies, outside the submitted work; in addition, Nielsen has a patent gene expression profile (not involving CSF-1R) to predict breast cancer outcomes with royalties paid by licensee Veracyte. Other authors have nothing to disclose. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Stanley, E.R.; Chitu, V. CSF-1 Receptor Signaling in Myeloid Cells. Cold Spring Harb. Perspect. Biol. 2014, 6, a021857. [Google Scholar] [CrossRef] [Green Version]
  2. Pixley, F.; Stanley, E.R. CSF-1 regulation of the wandering macrophage: Complexity in action. Trends Cell Biol. 2004, 14, 628–638. [Google Scholar] [CrossRef]
  3. Bourette, R.P.; Rohrschneider, L.R. Early Events in M-CSF Receptor Signaling. Growth Factors 2000, 17, 155–166. [Google Scholar] [CrossRef] [PubMed]
  4. Pollard, J.W.; Hennighausen, L. Colony stimulating factor 1 is required for mammary gland development during pregnancy. Proc. Natl. Acad. Sci. USA 1994, 91, 9312–9316. [Google Scholar] [CrossRef] [Green Version]
  5. Dai, X.; Ryan, G.R.; Hapel, A.J.; Dominguez, M.G.; Russell, R.G.; Kapp, S.; Sylvestre, V.; Stanley, E.R. Targeted disruption of the mouse colony-stimulating factor 1 receptor gene results in osteopetrosis, mononuclear phagocyte deficiency, increased primitive progenitor cell frequencies, and reproductive defects. Blood 2002, 99, 111–120. [Google Scholar] [CrossRef]
  6. Baghdadi, M.; Endo, H.; Takano, A.; Ishikawa, K.; Kameda, Y.; Wada, H.; Miyagi, Y.; Yokose, T.; Ito, H.; Nakayama, H.; et al. High co-expression of IL-34 and M-CSF correlates with tumor progression and poor survival in lung cancers. Sci. Rep. 2018, 8, 1–10. [Google Scholar] [CrossRef]
  7. Yang, L.; Wu, Q.; Xu, L.; Zhang, W.; Zhu, Y.; Liu, H.; Xu, J.; Gu, J. Increased expression of colony stimulating factor-1 is a predictor of poor prognosis in patients with clear-cell renal cell carcinoma. BMC Cancer 2015, 15, 67. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Mo, H.; Hao, Y.; Lv, Y.; Chen, Z.; Shen, J.; Zhou, S.; Yin, M. Overexpression of macrophage-colony stimulating factor-1 receptor as a prognostic factor for survival in cancer: A systematic review and meta-analysis. Medicine (Baltimore) 2021, 100, e25218. [Google Scholar] [CrossRef]
  9. Wyckoff, J.; Wang, W.; Lin, E.Y.; Wang, Y.; Pixley, F.; Stanley, E.R.; Graf, T.; Pollard, J.W.; Segall, J.; Condeelis, J. A Paracrine Loop between Tumor Cells and Macrophages Is Required for Tumor Cell Migration in Mammary Tumors. Cancer Res. 2004, 64, 7022–7029. [Google Scholar] [CrossRef] [Green Version]
  10. Lin, E.Y.; Pollard, J.W. Tumor-Associated Macrophages Press the Angiogenic Switch in Breast Cancer. Cancer Res. 2007, 67, 5064–5066. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  11. Lin, E.Y.; Nguyen, A.V.; Russell, R.G.; Pollard, J.W. Colony-Stimulating Factor 1 Promotes Progression of Mammary Tumors to Malignancy. J. Exp. Med. 2001, 193, 727–740. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Patsialou, A.; Wyckoff, J.; Wang, Y.; Goswami, S.; Stanley, E.R.; Condeelis, J.S. Invasion of Human Breast Cancer Cells In Vivo Requires both Paracrine and Autocrine Loops Involving the Colony-Stimulating Factor-1 Receptor. Cancer Res. 2009, 69, 9498–9506. [Google Scholar] [CrossRef] [Green Version]
  13. Beck, A.H.; Espinosa, I.; Edris, B.; Li, R.; Montgomery, K.; Zhu, S.; Varma, S.; Marinelli, R.J.; Van De Rijn, M.; West, R.B. The Macrophage Colony-Stimulating Factor 1 Response Signature in Breast Carcinoma. Clin. Cancer Res. 2009, 15, 778–787. [Google Scholar] [CrossRef] [Green Version]
  14. Patsialou, A.; Wang, Y.; Pignatelli, J.; Chen, X.; Entenberg, D.; Oktay, M.; Condeelis, J.S. Autocrine CSF1R signaling mediates switching between invasion and proliferation downstream of TGFbeta in claudin-low breast tumor cells. Oncogene 2015, 34, 2721–2731. [Google Scholar] [CrossRef] [Green Version]
  15. Schmid, P.; Cortes, J.; Pusztai, L.; McArthur, H.; Kümmel, S.; Bergh, J.; Denkert, C.; Park, Y.H.; Hui, R.; Harbeck, N.; et al. Pembrolizumab for Early Triple-Negative Breast Cancer. N. Engl. J. Med. 2020, 382, 810–821. [Google Scholar] [CrossRef] [PubMed]
  16. Schmid, P.; Rugo, H.S.; Adams, S.; Schneeweiss, A.; Barrios, C.H.; Iwata, H.; Diéras, V.; Henschel, V.; Molinero, L.; Chui, S.Y.; et al. Atezolizumab plus nab-paclitaxel as first-line treatment for unresectable, locally advanced or metastatic triple-negative breast cancer (IMpassion130): Updated efficacy results from a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 2020, 21, 44–59. [Google Scholar] [CrossRef]
  17. Cortes, J.; Cescon, D.W.; Rugo, H.S.; Nowecki, Z.; Im, S.-A.; Yusof, M.M.; Gallardo, C.; Lipatov, O.; Barrios, C.H.; Holgado, E.; et al. Pembrolizumab plus chemotherapy versus placebo plus chemotherapy for previously untreated locally recurrent inoperable or metastatic triple-negative breast cancer (KEYNOTE-355): A randomised, placebo-controlled, double-blind, phase 3 clinical trial. Lancet 2020, 396, 1817–1828. [Google Scholar] [CrossRef]
  18. Loibl, S.; Untch, M.; Burchardi, N.; Huober, J.; Sinn, B.V.; Blohmer, J.-U.; Grischke, E.-M.; Furlanetto, J.; Tesch, H.; Hanusch, C.; et al. A randomised phase II study investigating durvalumab in addition to an anthracycline taxane-based neoadjuvant therapy in early triple-negative breast cancer: Clinical results and biomarker analysis of GeparNuevo study. Ann. Oncol. 2019, 30, 1279–1288. [Google Scholar] [CrossRef] [Green Version]
  19. Nanda, R.; Liu, M.C.; Yau, C.; Shatsky, R.; Pusztai, L.; Wallace, A.; Chien, A.J.; Forero-Torres, A.; Ellis, E.; Han, H.; et al. Effect of Pembrolizumab Plus Neoadjuvant Chemotherapy on Pathologic Complete Response in Women with Early-Stage Breast Cancer: An Analysis of the Ongoing Phase 2 Adaptively Randomized I-SPY2 Trial. JAMA Oncol. 2020, 6, 676–684. [Google Scholar] [CrossRef]
  20. Winer, E.P.; Lipatov, O.; Im, S.A.; Goncalves, A.; Muñoz-Couselo, E.; Seok Lee, K.; Nowecki, Z.; Schmid, P.; Tamura, K.; Testa, L.; et al. Abstract PD14-04: Contribution of tumor and immune cells to PD-L1 as a predictive biomarker in triple-negative breast cancer (TNBC): Analysis from KEYNOTE-119. Breast Cancer Res. Treat. 2021. [Google Scholar] [CrossRef]
  21. Pons-Tostivint, E.; Latouche, A.; Vaflard, P.; Ricci, F.; Loirat, D.; Hescot, S.; Sablin, M.-P.; Rouzier, R.; Kamal, M.; Morel, C.; et al. Comparative Analysis of Durable Responses on Immune Checkpoint Inhibitors Versus Other Systemic Therapies: A Pooled Analysis of Phase III Trials. JCO Precis. Oncol. 2019, 3, 1–10. [Google Scholar] [CrossRef]
  22. Schmid, P.; Adams, S.; Rugo, H.S.; Schneeweiss, A.; Barrios, C.H.; Iwata, H.; Diéras, V.; Hegg, R.; Im, S.-A.; Wright, G.S.; et al. Atezolizumab and Nab-Paclitaxel in Advanced Triple-Negative Breast Cancer. N. Engl. J. Med. 2018, 379, 2108–2121. [Google Scholar] [CrossRef]
  23. Fares, C.M.; Van Allen, E.M.; Drake, C.G.; Allison, J.P.; Hu-Lieskovan, S. Mechanisms of Resistance to Immune Checkpoint Blockade: Why Does Checkpoint Inhibitor Immunotherapy Not Work for All Patients? Am. Soc. Clin. Oncol. Educ. Book 2019, 39, 147–164. [Google Scholar] [CrossRef] [PubMed]
  24. O’Donnell, J.S.; Long, G.V.; Scolyer, R.A.; Teng, M.W.; Smyth, M.J. Resistance to PD1/PDL1 checkpoint inhibition. Cancer Treat. Rev. 2017, 52, 71–81. [Google Scholar] [CrossRef] [Green Version]
  25. Zhao, X.; Qu, J.; Sun, Y.; Wang, J.; Liu, X.; Wang, F.; Zhang, H.; Wang, W.; Ma, X.; Gao, X.; et al. Prognostic significance of tumor-associated macrophages in breast cancer: A meta-analysis of the literature. Oncotarget 2017, 8, 30576–30586. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Cassetta, L.; Fragkogianni, S.; Sims, A.; Swierczak, A.; Forrester, L.M.; Zhang, H.; Soong, D.Y.; Cotechini, T.; Anur, P.; Lin, E.Y.; et al. Human Tumor-Associated Macrophage and Monocyte Transcriptional Landscapes Reveal Cancer-Specific Reprogramming, Biomarkers, and Therapeutic Targets. Cancer Cell 2019, 35, 588–602. [Google Scholar] [CrossRef] [Green Version]
  27. DeNardo, D.G.; Ruffell, B. Macrophages as regulators of tumour immunity and immunotherapy. Nat. Rev. Immunol. 2019, 19, 369–382. [Google Scholar] [CrossRef] [PubMed]
  28. Mariathasan, S.; Turley, S.J.; Nickles, D.; Castiglioni, A.; Yuen, K.; Wang, Y.; Kadel, E.E., III; Koeppen, H.; Astarita, J.L.; Cubas, R.; et al. TGFbeta attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature 2018, 554, 544–548. [Google Scholar] [CrossRef]
  29. Olson, O.C.; Kim, H.; Quail, D.F.; Foley, E.A.; Joyce, J.A. Tumor-Associated Macrophages Suppress the Cytotoxic Activity of Antimitotic Agents. Cell Rep. 2017, 19, 101–113. [Google Scholar] [CrossRef]
  30. Shree, T.; Olson, O.; Elie, B.T.; Kester, J.C.; Garfall, A.; Simpson, K.; Bell-McGuinn, K.M.; Zabor, E.C.; Brogi, E.; Joyce, J.A. Macrophages and cathepsin proteases blunt chemotherapeutic response in breast cancer. Genes Dev. 2011, 25, 2465–2479. [Google Scholar] [CrossRef] [Green Version]
  31. Castellaro, A.M.; Rodriguez-Baili, M.C.; Di Tada, C.E.; Gil, G.A. Tumor-Associated Macrophages Induce Endocrine Therapy Resistance in ER+ Breast Cancer Cells. Cancers 2019, 11, 189. [Google Scholar] [CrossRef] [Green Version]
  32. Shiao, S.L.; Ruffell, B.; DeNardo, D.G.; Faddegon, B.A.; Park, C.C.; Coussens, L.M. TH2-Polarized CD4+ T Cells and Macrophages Limit Efficacy of Radiotherapy. Cancer Immunol. Res. 2015, 3, 518–525. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Xu, M.; Liu, M.; Du, X.; Li, S.; Li, H.; Li, X.; Li, Y.; Wang, Y.; Qin, Z.; Fu, Y.-X.; et al. Intratumoral Delivery of IL-21 Overcomes Anti-Her2/Neu Resistance through Shifting Tumor-Associated Macrophages from M2 to M1 Phenotype. J. Immunol. 2015, 194, 4997–5006. [Google Scholar] [CrossRef] [Green Version]
  34. Zhu, Y.; Knolhoff, B.L.; Meyer, M.; Nywening, T.M.; West, B.; Luo, J.; Wang-Gillam, A.; Goedegebuure, S.P.; Linehan, D.C.; DeNardo, D.G. CSF1/CSF1R Blockade Reprograms Tumor-Infiltrating Macrophages and Improves Response to T-cell Checkpoint Immunotherapy in Pancreatic Cancer Models. Cancer Res. 2014, 74, 5057–5069. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Wiehagen, K.R.; Girgis, N.M.; Yamada, D.H.; Smith, A.A.; Chan, S.R.; Grewal, I.; Quigley, M.; Verona, R.I. Combination of CD40 Agonism and CSF-1R Blockade Reconditions Tumor-Associated Macrophages and Drives Potent Antitumor Immunity. Cancer Immunol. Res. 2017, 5, 1109–1121. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Xiang, X.; Wang, J.; Lu, D.; Xu, X. Targeting tumor-associated macrophages to synergize tumor immunotherapy. Signal Transduct. Target. Ther. 2021, 6, 1–12. [Google Scholar] [CrossRef]
  37. Osipov, A.; Saung, M.T.; Zheng, L.; Murphy, A.G. Small molecule immunomodulation: The tumor microenvironment and overcoming immune escape. J. Immunother. Cancer 2019, 7, 224. [Google Scholar] [CrossRef] [Green Version]
  38. Mitchem, J.B.; Brennan, D.J.; Knolhoff, B.L.; Belt, B.A.; Zhu, Y.; Sanford, D.E.; Belaygorod, L.; Carpenter, D.; Collins, L.; Piwnica-Worms, D.; et al. Targeting tumor-infiltrating macrophages decreases tumor-initiating cells, relieves immunosuppression, and improves chemotherapeutic responses. Cancer Res. 2013, 73, 1128–1141. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Kluger, H.M.; Dolled-Filhart, M.; Rodov, S.; Kacinski, B.M.; Camp, R.L.; Rimm, D.L. Macrophage Colony-Stimulating Factor-1 Receptor Expression Is Associated with Poor Outcome in Breast Cancer by Large Cohort Tissue Microarray Analysis. Clin. Cancer Res. 2004, 10, 173–177. [Google Scholar] [CrossRef] [Green Version]
  40. Richardsen, E.; Uglehus, R.D.; Johnsen, S.H.; Busund, L.-T. Macrophage-colony stimulating factor (CSF1) predicts breast cancer progression and mortality. Anticancer Res. 2015, 35, 865–874. [Google Scholar]
  41. Tang, R.; Ojeda, M.; Pouillart, P.; Scholl, S.; Beuvon, F.; Mosseri, V. M-CSF (monocyte colony stimulating factor) and M-CSF receptor expression by breast tumour cells: M-CSF mediated recruitment of tumour infiltrating monocytes? J. Cell. Biochem. 1992, 50, 350–356. [Google Scholar] [CrossRef] [PubMed]
  42. O’Meara, T.; Marczyk, M.; Qing, T.; Yaghoobi, V.; Blenman, K.; Cole, K.; Pelekanou, V.; Rimm, D.L.; Pusztai, L. Immunological Differences Between Immune-Rich Estrogen Receptor–Positive and Immune-Rich Triple-Negative Breast Cancers. JCO Precis. Oncol. 2020, 4, 767–779. [Google Scholar] [CrossRef]
  43. Li, T.; Fu, J.; Zeng, Z.; Cohen, D.; Li, J.; Chen, Q.; Li, B.; Liu, X.S. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020, 48, W509–W514. [Google Scholar] [CrossRef]
  44. Li, T.; Fan, J.; Wang, B.; Traugh, N.; Chen, Q.; Liu, J.S. TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells. Cancer Res. 2017, 77, e108–e110. [Google Scholar] [CrossRef] [Green Version]
  45. Li, B.; Severson, E.; Pignon, J.-C.; Zhao, H.; Li, T.; Novak, J. Comprehensive analyses of tumor immunity: Implications for cancer immunotherapy. Genome Biol. 2016, 17, 1–16. [Google Scholar] [CrossRef] [Green Version]
  46. Jézéquel, P.; Campone, M.; Gouraud, W.; Guérin-Charbonnel, C.; Leux, C.; Ricolleau, G.; Campion, L. bc-GenExMiner: An easy-to-use online platform for gene prognostic analyses in breast cancer. Breast Cancer Res. Treat. 2011, 131, 765–775. [Google Scholar] [CrossRef]
  47. Koboldt, D.C.F.R.; Fulton, R.; McLellan, M.; Schmidt, H.; Kalicki-Veizer, J.; McMichael, J.; Fulton, L.; Dooling, D.; Ding, L.; Mardis, E.; et al. Comprehensive molecular portraits of human breast tumours. Nature 2012, 490, 61–70. [Google Scholar]
  48. Curtis, C.; Shah, S.P.; Chin, S.F.; Turashvili, G.; Rueda, O.M.; Dunning, M.J.; Speed, D.; Lynch, A.G.; Samarajiwa, S.; Yuan, Y.; et al. The genomic and transcriptomic architecture of 2000 breast tumours reveals novel subgroups. Nature 2012, 486, 346–352. [Google Scholar] [CrossRef]
  49. Bortnik, S.; Choutka, C.; Horlings, H.M.; Leung, S.; Baker, J.H.; Lebovitz, C.; Dragowska, W.H.; Go, N.E.; Bally, M.; Minchinton, A.I.; et al. Identification of breast cancer cell subtypes sensitive to ATG4B inhibition. Oncotarget 2016, 7, 66970–66988. [Google Scholar] [CrossRef]
  50. Cheang, M.C.U.; Voduc, D.; Bajdik, C.; Leung, S.; McKinney, S.; Chia, S.K.; Perou, C.; Nielsen, T.O. Basal-Like Breast Cancer Defined by Five Biomarkers Has Superior Prognostic Value than Triple-Negative Phenotype. Clin. Cancer Res. 2008, 14, 1368–1376. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  51. Liu, S.; Lachapelle, J.; Leung, S.; Gao, D.; Foulkes, W.D.; O Nielsen, T. CD8+ lymphocyte infiltration is an independent favorable prognostic indicator in basal-like breast cancer. Breast Cancer Res. 2012, 14, R48. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Liu, S.; Foulkes, W.D.; Leung, S.; Gao, D.; Lau, S.; Kos, Z.; Nielsen, T.O. Prognostic significance of FOXP3+ tumor-infiltrating lymphocytes in breast cancer depends on estrogen receptor and human epidermal growth factor receptor-2 expression status and concurrent cytotoxic T-cell infiltration. Breast Cancer Res. 2014, 16, 1–12. [Google Scholar] [CrossRef] [Green Version]
  53. Burugu, S.; Gao, D.; Leung, S.; Chia, S.; Nielsen, T. LAG-3+ tumor infiltrating lymphocytes in breast cancer: Clinical correlates and association with PD-1/PD-L1+ tumors. Ann. Oncol. 2017, 28, 2977–2984. [Google Scholar] [CrossRef]
  54. Chafe, S.; Riaz, N.; Burugu, S.; Gao, D.; Leung, S.; Lee, A.; Lee, C.-H.; Dedhar, S.; Nielsen, T. Granulocyte Colony Stimulating Factor Expression in Breast Cancer and Its Association with Carbonic Anhydrase IX and Immune Checkpoints. Cancers 2021, 13, 1022. [Google Scholar] [CrossRef]
  55. Burugu, S.; Gao, D.; Leung, S.; Chia, S.K.; Nielsen, T.O. TIM-3 expression in breast cancer. Oncoimmunology 2018, 7, e1502128. [Google Scholar] [CrossRef] [Green Version]
  56. Bortnik, S.; Tessier-Cloutier, B.; Leung, S.; Xu, J.; Asleh, K.; Burugu, S.; Magrill, J.; Greening, K.; Derakhshan, F.; Yip, S.; et al. Differential expression and prognostic relevance of autophagy-related markers ATG4B, GABARAP, and LC3B in breast cancer. Breast Cancer Res. Treat. 2020, 183, 525–547. [Google Scholar] [CrossRef]
  57. Sauerbrei, W.; Taube, S.E.; McShane, L.M.; Cavenagh, M.M.; Altman, D.G. Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): An Abridged Explanation and Elaboration. J. Natl. Cancer Inst. 2018, 110, 803–811. [Google Scholar] [CrossRef] [PubMed]
  58. Cheang, M.C.; Treaba, D.O.; Speers, C.H.; Olivotto, I.A.; Bajdik, C.D.; Chia, S.K.; Goldstein, L.C.; Gelmon, K.A.; Huntsman, D.; Gilks, C.B.; et al. Immunohistochemical Detection Using the New Rabbit Monoclonal Antibody SP1 of Estrogen Receptor in Breast Cancer Is Superior to Mouse Monoclonal Antibody 1D5 in Predicting Survival. J. Clin. Oncol. 2006, 24, 5637–5644. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  59. Strachan, D.C.; Ruffell, B.; Oei, Y.; Bissell, M.J.; Coussens, L.M.; Pryer, N.; Daniel, D. CSF1R inhibition delays cervical and mammary tumor growth in murine models by attenuating the turnover of tumor-associated macrophages and enhancing infiltration by CD8+T cells. OncoImmunology 2013, 2, e26968. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  60. Bates, G.J.; Fox, S.B.; Han, C.; Leek, R.D.; Garcia, J.F.; Harris, A.L.; Banham, A.H. Quantification of Regulatory T Cells Enables the Identification of High-Risk Breast Cancer Patients and Those at Risk of Late Relapse. J. Clin. Oncol. 2006, 24, 5373–5380. [Google Scholar] [CrossRef]
  61. Ushach, I.; Zlotnik, A. Biological role of granulocyte macrophage colony-stimulating factor (GM-CSF) and macrophage colony-stimulating factor (M-CSF) on cells of the myeloid lineage. J. Leukoc. Biol. 2016, 100, 481–489. [Google Scholar] [CrossRef]
  62. Maher, M.G.; Sapi, E.; Turner, B.; Gumbs, A.; Perrotta, P.L.; Carter, D.; Kacinski, B.M.; Haffty, B.G. Prognostic significance of colony-stimulating factor receptor expression in ipsilateral breast cancer recurrence. Clin. Cancer Res. 1998, 4, 1851–1856. [Google Scholar]
  63. Roussel, M.F.; Downing, J.R.; Rettenmier, C.W.; Sherr, C.J. A point mutation in the extracellular domain of the human CSF-1 receptor (c-fms proto-oncogene product) activates its transforming potential. Cell 1988, 55, 979–988. [Google Scholar] [CrossRef]
  64. Wrobel, C.N.; Debnath, J.; Lin, E.; Beausoleil, S.A.; Roussel, M.F.; Brugge, J.S. Autocrine CSF-1R activation promotes Src-dependent disruption of mammary epithelial architecture. J. Cell Biol. 2004, 165, 263–273. [Google Scholar] [CrossRef]
  65. Rosenberg, P.S.; Barker, K.A.; Anderson, W.F. Estrogen Receptor Status and the Future Burden of Invasive and In Situ Breast Cancers in the United States. J. Natl. Cancer Inst. 2015, 107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  66. Thomas, A.; Routh, E.; Pullikuth, A.; Jin, G.; Su, J.; Chou, J.W.; Hoadley, K.; Print, C.; Knowlton, N.; Black, M.A.; et al. Tumor mutational burden is a determinant of immune-mediated survival in breast cancer. OncoImmunology 2018, 7, e1490854. [Google Scholar] [CrossRef]
  67. Sobral-Leite, M.; Van de Vijver, K.; Michaut, M.; van der Linden, R.; Hooijer, G.K.; Horlings, H.M.; Severson, T.M.; Mulligan, A.M.; Weerasooriya, N.; Sanders, J.; et al. Assessment of PD-L1 expression across breast cancer molecular subtypes, in relation to mutation rate, BRCA1-like status, tumor-infiltrating immune cells and survival. OncoImmunology 2018, 7, e1509820. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Denkert, C.; Von Minckwitz, G.; Darb-Esfahani, S.; Lederer, B.; Heppner, B.I.; Weber, K.E.; Budczies, J.; Huober, J.; Klauschen, F.; Furlanetto, J.; et al. Tumour-infiltrating lymphocytes and prognosis in different subtypes of breast cancer: A pooled analysis of 3771 patients treated with neoadjuvant therapy. Lancet Oncol. 2018, 19, 40–50. [Google Scholar] [CrossRef]
  69. Stanton, S.E.; Adams, S.; Disis, M.L. Variation in the Incidence and Magnitude of Tumor-Infiltrating Lymphocytes in Breast Cancer Subtypes: A Systematic Review. JAMA Oncol. 2016, 2, 1354–1360. [Google Scholar] [CrossRef] [PubMed]
  70. Thorsson, V.; Gibbs, D.L.; Brown, S.; Wolf, D.; Bortone, D.S.; Ou Yang, T.-H.; Porta-Pardo, E.; Gao, G.F.; Plaisier, C.L.; Eddy, J.A.; et al. The Immune Landscape of Cancer. Immunity 2018, 48, 812–830. [Google Scholar] [CrossRef] [Green Version]
  71. Dirix, L.Y.; Takacs, I.; Jerusalem, G.; Nikolinakos, P.; Arkenau, H.T.; Forero-Torres, A.; Boccia, R.; Lippman, M.E.; Somer, R.; Smakal, M.; et al. Avelumab, an anti-PD-L1 antibody, in patients with locally advanced or metastatic breast cancer: A phase 1b JAVELIN Solid Tumor study. Breast Cancer Res. Treat. 2018, 167, 671–686. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Rugo, H.S.; Delord, J.-P.; Im, S.-A.; Ott, P.A.; Piha-Paul, S.; Bedard, P.; Sachdev, J.; Le Tourneau, C.; Van Brummelen, E.M.; Varga, A.; et al. Safety and Antitumor Activity of Pembrolizumab in Patients with Estrogen Receptor–Positive/Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer. Clin. Cancer Res. 2018, 24, 2804–2811. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Tolaney, S.M.; Kalinsky, K.; Kaklamani, V.G.; D’Adamo, D.R.; Aktan, G.; Tsai, M.L.; O’Regan, R.M.; Kaufman, P.A.; Wilks, S.T.; Andreopoulou, E.; et al. Eribulin Plus Pembrolizumab in Patients with Metastatic Triple-Negative Breast Cancer (ENHANCE 1): A Phase Ib/II Study. Clin. Cancer Res. 2021, 27, 3061–3068. [Google Scholar] [CrossRef]
  74. Shah, A.N.; Flaum, L.; Helenowski, I.; Santa-Maria, C.A.; Jain, S.; Rademaker, A.; Nelson, V.; Tsarwhas, D.; Cristofanilli, M.; Gradishar, W. Phase II study of pembrolizumab and capecitabine for triple negative and hormone receptor-positive, HER2−negative endocrine-refractory metastatic breast cancer. J. Immunother. Cancer 2020, 8, e000173. [Google Scholar] [CrossRef] [Green Version]
  75. Ries, C.H.; Cannarile, M.A.; Hoves, S.; Benz, J.; Wartha, K.; Runza, V.; Rey-Giraud, F.; Pradel, L.P.; Feuerhake, F.; Klaman, I.; et al. Targeting Tumor-Associated Macrophages with Anti-CSF-1R Antibody Reveals a Strategy for Cancer Therapy. Cancer Cell 2014, 25, 846–859. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. Lin, W.; Xu, D.; Austin, C.D.; Caplazi, P.; Senger, K.; Sun, Y.; Jeet, S.; Young, J.; Delarosa, D.; Suto, E.; et al. Function of CSF1 and IL34 in Macrophage Homeostasis, Inflammation, and Cancer. Front. Immunol. 2019, 10, 2019. [Google Scholar] [CrossRef]
  77. Wesolowski, R.; Sharma, N.; Reebel, L.; Rodal, M.B.; Peck, A.; West, B.L.; Marimuthu, A.; Severson, P.; Karlin, D.A.; Dowlati, A.; et al. Phase Ib study of the combination of pexidartinib (PLX3397), a CSF-1R inhibitor, and paclitaxel in patients with advanced solid tumors. Ther. Adv. Med. Oncol. 2019, 11, 1758835919854238. [Google Scholar] [CrossRef]
  78. Gomez-Roca, C.; Italiano, A.; Le Tourneau, C.; Cassier, P.; Toulmonde, M.; D’Angelo, S.; Campone, M.; Weber, K.; Loirat, D.; Cannarile, M.; et al. Phase I study of emactuzumab single agent or in combination with paclitaxel in patients with advanced/metastatic solid tumors reveals depletion of immunosuppressive M2-like macrophages. Ann. Oncol. 2019, 30, 1381–1392. [Google Scholar] [CrossRef]
  79. Papadopoulos, K.P.; Gluck, L.; Martin, L.P.; Olszanski, A.; Tolcher, A.W.; Ngarmchamnanrith, G.; Rasmussen, E.; Amore, B.M.; Nagorsen, D.; Hill, J.S.; et al. First-in-Human Study of AMG 820, a Monoclonal Anti-Colony-Stimulating Factor 1 Receptor Antibody, in Patients with Advanced Solid Tumors. Clin. Cancer Res. 2017, 23, 5703–5710. [Google Scholar] [CrossRef] [Green Version]
  80. O’Brien, S.A.; Orf, J.; Skrzypczynska, K.M.; Tan, H.; Kim, J.; DeVoss, J.; Belmontes, B.; Egen, J.G. Activity of tumor-associated macrophage depletion by CSF1R blockade is highly dependent on the tumor model and timing of treatment. Cancer Immunol. Immunother. 2021, 70, 2401–2410. [Google Scholar] [CrossRef]
  81. Swierczak, A.; Cook, A.; Lenzo, J.; Restall, C.M.; Doherty, J.P.; Anderson, R.L.; Hamilton, J.A. The Promotion of Breast Cancer Metastasis Caused by Inhibition of CSF-1R/CSF-1 Signaling Is Blocked by Targeting the G-CSF Receptor. Cancer Immunol. Res. 2014, 2, 765–776. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Kumar, V.; Donthireddy, L.; Marvel, D.; Condamine, T.; Wang, F.; Lavilla-Alonso, S.; Hashimoto, A.; Vonteddu, P.; Behera, R.; Goins, M.A.; et al. Cancer-Associated Fibroblasts Neutralize the Anti-tumor Effect of CSF1 Receptor Blockade by Inducing PMN-MDSC Infiltration of Tumors. Cancer Cell 2017, 32, 654–668.e5. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Lu, S.; Stein, J.E.; Rimm, D.L.; Wang, D.W.; Bell, J.M.; Johnson, D.B.; Sosman, J.A.; Schalper, K.A.; Anders, R.A.; Wang, H.; et al. Comparison of Biomarker Modalities for Predicting Response to PD-1/PD-L1 Checkpoint Blockade: A Systematic Review and Meta-analysis. JAMA Oncol. 2019, 5, 1195–1204. [Google Scholar] [CrossRef] [PubMed]
  84. Nederlof, I.; De Bortoli, D.; Bareche, Y.; Nguyen, B.; De Maaker, M.; Hooijer, G.K.J.; Buisseret, L.; Kok, M.; Smid, M.; Van den Eynden, G.; et al. Comprehensive evaluation of methods to assess overall and cell-specific immune infiltrates in breast cancer. Breast Cancer Res. 2019, 21, 1–13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1. Representative photomicrographs for immunohistochemical staining of CSF-1R expression in breast carcinoma tissue microarray cores. (A) Cytoplasmic/membranous expression of high CSF-1R showing ≥10% positivity on carcinoma cells; (B) cytoplasmic/membranous expression of CSF-1R on tumor-associated macrophages (red arrows) showing ≥2 positive macrophages; (C) negative expression on tumor cells and macrophages (images acquired at 10×). The inserts show CSF-1R+ carcinoma cells (A) and CSF-1R+ tumor-associated macrophages (B) at high magnification.
Figure 1. Representative photomicrographs for immunohistochemical staining of CSF-1R expression in breast carcinoma tissue microarray cores. (A) Cytoplasmic/membranous expression of high CSF-1R showing ≥10% positivity on carcinoma cells; (B) cytoplasmic/membranous expression of CSF-1R on tumor-associated macrophages (red arrows) showing ≥2 positive macrophages; (C) negative expression on tumor cells and macrophages (images acquired at 10×). The inserts show CSF-1R+ carcinoma cells (A) and CSF-1R+ tumor-associated macrophages (B) at high magnification.
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Figure 2. Correlation of CSF1R mRNA expression with immune cell infiltrates and prognosis in breast cancer. TIMER2.0 web server was used to evaluate the correlation between CSF1R mRNA expression and immune cell infiltrates. The left-most panel (A(i)) shows CSF1R mRNA expression against tumor purity (proportion of cancer cells in the sample), showing a significantly negative correlation. Scatter plots (A(ii–vii)) show the purity-adjusted partial Spearman’s rho value and statistical significance for positive correlation of CSF1R mRNA with immune cell types (Spearman’s rho: 0, no correlation; 0.1–0.3, weak; 0.4–0.6, moderate; 0.7–0.9, strong; 1, perfect; p-value < 0.05). Five-year Kaplan–Meier curves show an insignificant association of CSF1R mRNA with disease-free survival (DFS) in the TCGA (B) and METABRIC (C) invasive breast cancer cohorts. The p-value and hazard ratios (HR) with corresponding 95% confidence intervals were estimated by the log-rank test. The survival curves for TCGA and METABRIC cohorts were generated using Breast Cancer Gene-Expression Miner v4.7.
Figure 2. Correlation of CSF1R mRNA expression with immune cell infiltrates and prognosis in breast cancer. TIMER2.0 web server was used to evaluate the correlation between CSF1R mRNA expression and immune cell infiltrates. The left-most panel (A(i)) shows CSF1R mRNA expression against tumor purity (proportion of cancer cells in the sample), showing a significantly negative correlation. Scatter plots (A(ii–vii)) show the purity-adjusted partial Spearman’s rho value and statistical significance for positive correlation of CSF1R mRNA with immune cell types (Spearman’s rho: 0, no correlation; 0.1–0.3, weak; 0.4–0.6, moderate; 0.7–0.9, strong; 1, perfect; p-value < 0.05). Five-year Kaplan–Meier curves show an insignificant association of CSF1R mRNA with disease-free survival (DFS) in the TCGA (B) and METABRIC (C) invasive breast cancer cohorts. The p-value and hazard ratios (HR) with corresponding 95% confidence intervals were estimated by the log-rank test. The survival curves for TCGA and METABRIC cohorts were generated using Breast Cancer Gene-Expression Miner v4.7.
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Figure 3. Kaplan–Meier survival curves showing breast cancer-specific survival in the validation set of BC Cancer series stratified by CSF-1R+ carcinoma cells (A) and CSF-1R+ tumor-associated macrophages (B). Prespecified subgroup analysis for CSF-1R-expressing carcinoma cells in ER-positive cases (C) and ER negative cases (D).
Figure 3. Kaplan–Meier survival curves showing breast cancer-specific survival in the validation set of BC Cancer series stratified by CSF-1R+ carcinoma cells (A) and CSF-1R+ tumor-associated macrophages (B). Prespecified subgroup analysis for CSF-1R-expressing carcinoma cells in ER-positive cases (C) and ER negative cases (D).
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Figure 4. Kaplan–Meier survival curves for breast cancer-specific survival in ER-positive cases in the full BC Cancer cohort stratified by CSF-1R expression on carcinoma cells and intraepithelial tumor-infiltrating lymphocytes (iTILs) expressing CD8 (A) or FOXP3 (B).
Figure 4. Kaplan–Meier survival curves for breast cancer-specific survival in ER-positive cases in the full BC Cancer cohort stratified by CSF-1R expression on carcinoma cells and intraepithelial tumor-infiltrating lymphocytes (iTILs) expressing CD8 (A) or FOXP3 (B).
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Figure 5. Kaplan–Meier survival curves showing breast cancer-specific survival in combined BC Cancer series in the presence of CSF-1R+ macrophages stratified by CSF-1R+ carcinoma cells in ER-positive (A) and ER-negative cases (B). Kaplan–Meier curves in the presence of CD163+ macrophages stratified by CSF-1R+ carcinoma cells in ER-positive (C) and ER-negative cases (D).
Figure 5. Kaplan–Meier survival curves showing breast cancer-specific survival in combined BC Cancer series in the presence of CSF-1R+ macrophages stratified by CSF-1R+ carcinoma cells in ER-positive (A) and ER-negative cases (B). Kaplan–Meier curves in the presence of CD163+ macrophages stratified by CSF-1R+ carcinoma cells in ER-positive (C) and ER-negative cases (D).
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Table 1. Validation set of BC Cancer cohort: correlation of CSF-1R+ carcinoma cells with clinicopathological features.
Table 1. Validation set of BC Cancer cohort: correlation of CSF-1R+ carcinoma cells with clinicopathological features.
Clinicopathological VariablesCSF-1R Expression on Carcinoma Cellsp-Value
Low (<10%)
n = 924 (76.9%)
High (≥10%)
n = 277 (23.1%)
Age at diagnosis 0.57
<50307 (33.2)87 (31.4)
≥50617 (66.8)190 (68.6)
Tumor size (cm) 0.001 *
≤2484 (52.7)113 (41.1)
>2434 (47.3)162 (58.9)
Tumor grade <0.001 *
1 and 2404 (45.4)86 (31.9)
3486 (54.6)184 (68.1)
Axillary lymph node status 0.11
Negative 519 (56.2)140 (50.7)
Positive 404 (43.8)136 (49.3)
Lymphovascular invasion 0.37
Negative459 (51.2)144 (54.3)
Positive437 (48.8)121 (45.7)
ER expression <0.001 *
Negative201 (21.8)131 (47.3)
Positive720 (78.2)146 (52.7)
Progesterone receptor expression <0.001 *
Negative 392 (44.7)169 (63.5)
Positive484 (55.3)97 (36.5)
HER2 overexpression/amplification <0.001 *
Negative816 (89.9)203 (74.9)
Positive92 (10.1)68 (25.1)
Ki-67 proliferation index <0.001 *
<14%502 (58.3)92 (35.8)
≥14%359 (41.7)165 (64.2)
Breast cancer subtypes <0.001 *
Luminal NOS 37 (4.0)5 (1.8)
Luminal A438 (47.4)58 (20.9)
Luminal B/HER2-/Ki67+217 (23.5)64 (23.1)
Luminal/HER2+47 (5.1)20 (7.2)
HER2+44 (4.8)45 (16.2)
Basal 66 (7.1))53 (19.1)
Additional basal by TNP50 (5.4)18 (6.5)
Unassignable25 (2.7)14 (5.1)
* Denotes differences between low and high CSF-1R groups that are significant at the Bonferroni-corrected p-value of <0.005 (0.05/10); ER, estrogen receptor; HER2, human epidermal growth factor receptor; TNP, triple-negative phenotype.
Table 2. Validation set of BC Cancer cohort: correlation of CSF-1R+ carcinoma cells with immune biomarkers.
Table 2. Validation set of BC Cancer cohort: correlation of CSF-1R+ carcinoma cells with immune biomarkers.
VariablesCSF-1R Expression on Carcinoma Cells p-Value
Low (<10%)High (≥10%)
H&E sTIL count (%) <0.001
<10 723 (84.8)194 (73.8)
≥10130 (15.2)69 (26.2)
CD8 iTIL count 0.001
<1602 (67.7)149 (56.4)
≥1287 (32.3)115 (43.6)
PD-1 iTIL count <0.001
<1809 (91.7)219 (81.7)
≥173 (8.3)49 (18.3)
PD-L1+ carcinoma cells (%) <0.001
0814 (94.1)215 (81.4)
≥151 (5.9)49 (18.6)
FOXP3 iTIL count <0.001
<2624 (70.1)141 (52.8)
≥2266 (29.9)126 (47.2)
TIM3 iTIL count <0.001
<1804 (90.5)212 (78.5)
≥184 (9.5)58 (21.5)
LAG3 iTIL count <0.001
<1793 (89.5)208 (77)
≥193 (10.5)62 (23)
CD163+ M2 macrophages <0.001
≤5336 (40.5)61 (24.2)
>5493 (59.5)191 (75.8)
CSF-1R+ M2 macrophages <0.001
<2532 (61.2)108 (39.6)
≥2337 (38.8)165 (60.4)
H&E, hematoxylin- and eosin-stained; iTILs, intraepithelial tumor infiltrating lymphocytes; sTILs, stromal tumor-infiltrating lymphocytes; PD/L1, programmed cell death protein/ligand 1; FOXP3, forkhead box P3; TIM3, T cell immunoglobulin domain and mucin domain 3; LAG3, lymphocyte activation gene 3 protein; CSF-1R, colony-stimulating factor-1 receptor.
Table 3. Multivariate analysis for CSF-1R+ carcinoma cells in the validation set of BC Cancer cohort.
Table 3. Multivariate analysis for CSF-1R+ carcinoma cells in the validation set of BC Cancer cohort.
Co-Variates in the ModelBreast Cancer Specific Survival
Adjusted HR (95% CI)p-Value
Age at diagnosis (years) 0.70
<501
≥501.05 (0.81–1.36)
Tumor size (cm) <0.001
≤21
>21.65 (1.26–2.15)
Tumor grade <0.001
1 and 21
32.03 (1.52–2.71)
Axillary LN status <0.001
Negative1
Positive1.84 (1.38–2.44)
LVI 0.02
Negative1
Positive1.40 (1.05–1.88)
CSF-1R+ carcinoma cells 0.001
Low (<10%)1
High (≥10%)1.58 (1.22–2.05)
LN, lymph node; LVI, lymphovascular invasion; CSF-1R, colony-stimulating factor-1 receptor.
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Riaz, N.; Burugu, S.; Cheng, A.S.; Leung, S.C.Y.; Gao, D.; Nielsen, T.O. Prognostic Significance of CSF-1R Expression in Early Invasive Breast Cancer. Cancers 2021, 13, 5769. https://doi.org/10.3390/cancers13225769

AMA Style

Riaz N, Burugu S, Cheng AS, Leung SCY, Gao D, Nielsen TO. Prognostic Significance of CSF-1R Expression in Early Invasive Breast Cancer. Cancers. 2021; 13(22):5769. https://doi.org/10.3390/cancers13225769

Chicago/Turabian Style

Riaz, Nazia, Samantha Burugu, Angela S. Cheng, Samuel C. Y. Leung, Dongxia Gao, and Torsten O. Nielsen. 2021. "Prognostic Significance of CSF-1R Expression in Early Invasive Breast Cancer" Cancers 13, no. 22: 5769. https://doi.org/10.3390/cancers13225769

APA Style

Riaz, N., Burugu, S., Cheng, A. S., Leung, S. C. Y., Gao, D., & Nielsen, T. O. (2021). Prognostic Significance of CSF-1R Expression in Early Invasive Breast Cancer. Cancers, 13(22), 5769. https://doi.org/10.3390/cancers13225769

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