New insights into the role of the CHI3L2 protein in invasive ductal breast carcinoma: the CHI3L1 protein has a different role

doi:10.21203/rs.3.rs-3884958/v1

Purpose

Chitinase-like proteins have multiple biological functions that promote tumor growth, angiogenesis and metastasis. Expression of CHI3L2, which is similar in structure to CHI3L1, is detected in glioma cells and tumor-associated macrophages (TAMs) in glioma and breast cancer. However, its exact role remains unclear.

Methods

We analyzed the expression of CHI3L2 in 74 invasive ductal breast carcinoma (IDC) tumors, breast cancer and macrophages cell cultures using immunohistochemistry, immunofluorescence, Western blot and PCR methods. Clinicopathologic data were included in the analysis.

Results

The results obtained show that CHI3L2 expression decreases with increasing degree of tumor grade and negative status of estrogen (ER) and progesterone receptors (PR). Furthermore, CHI3L2 is significantly and positively correlated with phosphorylation of STAT-3 and ERK1/2 signaling pathways, but negatively correlated with macrophage infiltration. Furthermore, CHI3L2 is expressed both in the cytoplasm of cancer cells and in macrophages. Analysis of the clinicopathologic data revealed that CHI3L2 levels had no effect on patient survival.

Discussion

CHI3L2 expression may be specific for cancer cells in IDC and involved in cross-talk with the tumor microenvironment. Our study has shown that IDC cancer cells express the CHI3L2 protein, possibly indicating a novel function of this protein.

chitinase-like proteins

CHI3L2

CHI3L1

invasive ductal breast carcinoma

ERK1/2

STAT-3

CHI3L2 (chitinase 3-like 2 protein; YKL-39) is a 39 kDa lectin that belongs to the chitinase-like protein family and shows high homology and structural similarity to CHI3L1. Of the chitinases found in human tissues, only mammalian acid chitinase and chitotriosidase exhibit chitinase activity. However, chitinase-like proteins, including CHI3L1, CHI3L2 and SI-CLP (stabilin-1 interacting chitinase-like protein), have biological functions that contribute to stimulation of cell proliferation, support of angiogenesis and tumor invasion, cell interactions and immunomodulation [1–7]. The best-known protein in this family is undoubtedly CHI3L1, also known as YKL-40. Its established role in promoting angiogenesis and involvement in development of various cancers, such as breast cancer, colorectal cancer and glioblastoma is well documented [8–11]. In addition, it is involved in bypassing the cancer immune system and in pathological inflammation in various diseases, including Alzheimer's and Parkinson's disease, multiple sclerosis and even asthma [12–18].

Elevated levels of the CHI3L1 protein have been detected in the serum of cancer patients, including those with gliomas, colorectal, lung and breast cancer as well as leukemia. These elevated levels are usually associated with poor prognosis, tumor growth and metastasis [6]. In our previous study, we have shown that increased CHI3L1 expression in IDC tumors can promote angiogenesis and be associated with the growth of triple-negative tumors [19]. Furthermore, our results show a correlation between the expression of CHI3L1 and Nogo-A in IDC and their involvement in angiogenesis in this cancer subtype [20]. Recent studies also indicate increased levels of CHI3L1 in bronchoalveolar lavage fluid and serum of critical COVID-19 patients, suggesting the possible involvement of this protein in the pathogenesis of the disease and its importance as a biomarker [21–23].

The significance of CHI3L2 in breast cancer is still largely unknown. There are only a limited number of articles pointing to its importance in the expression of TAMs. Recent studies emphasize the central role of this protein in promoting angiogenesis and supporting distant metastasis [3], [24]. In fact, it is more likely that the source of CHI3L2 protein in breast tumor tissue is macrophages.

In this article, the expression of CHI3L2 in the cytoplasm of IDC and breast cancer cell lines is presented for the first time, and the influence of CHI3L2 protein on the phosphorylation of STAT-3 and ERK1/2 signaling pathways is discussed. Furthermore, the correlation between CHI3L2 expression and clinicopathological data of patients diagnosed with IDC was analyzed. Our results reveal a novel role for chitinase-like proteins. CHI3L2 may have a protective function against tumors that differs from CHI3L1 despite the structural similarity of the two proteins.

Cell lines

Human cancer cell lines were cultured from various clinicopathological breast tumors, including MCF-7, SK-BR-3, T-47D, BT-474, B-T549, MDA-MB-231, MDA-MB-436, MDA-MB-468, and BO2 (all from ATCC, American Type Culture Collection ATCC, Old Town Manassas, VA, USA) [25], [26]. The MCF10A cell line, which is derived from fibrocystic breast disease, and the HME1-hTERT (Me16C) (ATCC) cell line, which is normal mammary epithelial cells immortalized with hTERT, were also used. Cells were cultured in appropriate media: α-MEM (Sigma-Aldrich) for MCF-7, BO2 and BT-474, L-15 medium (ATCC) for MDA-MB-231 and MDA-MB-468, EMEM (Lonza) for SK-BR-3, L-15 (ATCC) supplemented with 10 µg/ml insulin and 16 µg/ml glutathione (both from Sigma-Aldrich) for MDA-MB-436, RPMI-1640 (Gibco, Thermo-Fisher Scientific) supplemented with 0.1% insulin (Sigma-Aldrich) for BT-549.The human acute monocytic leukemia cell line THP-1 (ATCC) was cultured in RPMI-1640 medium (Gibco, ThermoFisher Scientific, Wilmington, DE, USA). All media were supplemented with fetal bovine serum (FBS) up to 10% (Sigma-Aldrich) and penicillin-streptomycin solution up to 1% of the final volume (Sigma-Aldrich). For MCF10A and hTERT (Me16C), the MEGM ^TM bullet kit (Lonza) was used for cell culture. Cell passaging was performed with TrypLE (Gibco, ThermoFisher Scientific) at a maximum confluence of 70%. The media were changed twice a week. Cell culture was performed under standard conditions in a humidified atmosphere with 5% CO2. The molecular characteristics of the individual breast cancer lines according to Kao et al. [27] are listed in Table 1.

Monocyte differentiation

THP-1 cells were cultured for 24 hours in complete RPMI-1640 medium (Gibco), supplemented with 100 nM PMA (phorbol 12-myristate 13-acetate) (Sigma-Aldrich) [28], [7]. Subsequently, adherent macrophages were identified at the bottom of the vessel.

Co-cultures

Macrophages were cultured for one week in conditioned media of MCF-7, MDA-MB-468, MCF 10A and MDA-MB-231 cells. Macrophage pellets were then harvested and frozen at -80°C for protein expression analysis.

Patients and tumors

The 74 samples of IDC used in this study were archival material from patients diagnosed and operated on at the Lower Silesian Oncology Center (Wroclaw, Poland) between 1999 and 2009. As a control, 12 non-malignant breast tissue lesions (NBTL) were included in the study. Breast cancer samples were graded according to the WHO system [29], [30] and tissue samples were either embedded in paraffin or stored at -80ºC.

Immunohistochemical reactions

Immunohistochemistry was performed on 4 µm sections of paraffin-embedded tissue samples using the Dako Autostainer Link48 (Dako, Glostrup, Denmark). Paraffin removal and antigen retrieval were performed in PT-Link (Dako) with basic EnVision FLEX Target Retrieval Solution (97°C, 20 min; Dako) for immunostaining of CHI3L2, CD68 and CD206, CHI3L1, VEGFA, VEGFD, CD31, CD34, estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER-2). The VEGFC and Ki-67 antibodies were treated with Dako's acidic EnVision FLEX Target Retrieval Solution. Dako's EnVision FLEX Peroxidase Blocking Reagent was used to block endogenous peroxidase for 5 minutes. The EnVision FLEX+ Mouse, High pH System (Dako) was used to visualize IHC reactions by mouse monoclonal antibodies: CHI3L2 (1:100 with linker, MAB5116, R&D, Minneapolis, Minnesota, USA), CD206 (1:100, MAB25341, R&D), CD31 (RTU, Dako; 20 minutes), CD34 (RTU, Dako; 20 minutes), VEGFA (1:50, Dako 18 hours, 4°C), Ki-67 (RTU, Dako, 20 minutes), ER (RTU, Dako, 20 minutes) and PR (RTU, Dako, 20 minutes).

The LSAB+ detection system (Dako) was used to visualize IHC reactions obtained with goat polyclonal antibodies against CHI3L1 (1:100, AF2599, 20 min; R&D Systems, Minneapolis, MN USA), VEGFC (1:100, 18 hours, 4°C; ReliaTech GmbH, Braunschweig, Germany) and VEGFD (1:100, 18 hours, 4°C; ReliaTech GmbH). HER-2 expression was measured using the HercepTest kit (Dako). Counterstaining with hematoxylin (5 minutes) was performed (EnVision FLEX Hematoxylin). The visualization systems were used according to the manufacturer's instructions. A secondary HRP-conjugated rat antibody was applied at a dilution of 1:400 (Jackson ImmunoResearch) and incubated for 1 hour at room temperature (RT). EnVision FLEX/HRP was also applied and incubated for 1 hour at RT (Dako). EnVisionFLEX Substrate Buffer was then added and incubated for 10 minutes at RT (Dako) [19], [20], [26], [31], [32].

Evaluation of the immunohistochemical reactions

The immunohistochemical reactions for CHI3L2, CHI3L1, VEGFA, VEGFC and VEGFD were evaluated using the 12-point immunoreactive score (IRS) developed by Remmele and Stegner [33] (Table 2). For the evaluation of the pan-macrophage marker CD68 and the anti-inflammatory macrophage CD206, the positively tested cells were counted in five hotspots with a x200 magnification and the average value was given. The Chalkley's ophthalmoscope (Pyser Inc., Edenbridge, UK) was used to score CD31- and CD34-positive blood vessels based on the number of grid points (n=1-25) and to estimate the relative microvessel count (MVC) [34] [35] [36]. Methodologically, the basis for the relative microvessel density (MVD) was determined by taking the mean of the three hotspots with the highest vascularization (magnification ×200), according to the approach of Fox and Harris [36]. A semi-quantitative scale from 0 to 4 was used for Ki-67 expression: 0 for 0% of positive cells, 1 for 1-10% of positive cells, 2 for 11-25% of positive cells, 3 for 26-50% of positive cells and 4 for 51-100% of positive cells [37]. For this marker, high expression was defined as values > 25% of positive cells, while low expression was considered ≤25%. For estrogen (ER), progesterone (PR) and human epidermal growth factor receptor 2 (HER-2), a semi-quantitative scale of 0-3 was used: 0 means 0% of positive cells, 1 means 1-10% of positive cells, 2 means 11-50% of positive cells and 3 means 51-100% of positive cells. For HER-2, a positive response was detected when more than 10% of cancer cells showed an intense membrane response (score of 3) [38]. CHI3L2 protein expression and its correlation with the clinicopathological data of the patients are shown in Table 3. For the markers CHI3L1, CHI3L2, VEGFA, VEGFC, VEGFD, CD31, CD34, CD68 and CD206, the median expression values were used as cut-off points for the analysis of low and high expression (Table 4). The immunohistochemical reactions were analyzed using a BX41 light microscope (Olympus, Tokyo, Japan).

Immunofluorescence reactions

Immunofluorescence reactions were performed on 4 µm thick tissue sections. Deparaffinization was performed with a graded alcohol series at room temperature, and epitope retrieval was performed at 90ºC for 15 minutes at pH=9.0. For blocking, a 1% BSA solution in PBS/0.1% Tween 20 was used for 30 minutes at RT. Slides were then incubated overnight at 4ºC with anti-CHI3L2 anti-rat antibody (1:5, #18H10) [24] and mouse monoclonal antibody (1:500, MAB5116, R&D). Incubation with secondary anti-rat and anti-mouse antibodies conjugated to the fluorochromes Alexa568 (Jackson ImmunoResearch) and Alexa 488 (ab150113, Abcam, Cambridge, UK) was performed for 1 hour at RT (dilution 1:2000 in 1% BSA in PBS/0.1% Tween20). Slides were coverslipped with FluoroShield mounting medium with DAPI (Abcam, Cambridge, UK, ab104139). A confocal microscope (Olympus Fluoview FV3000, Tokyo, Japan) and imaging software (Olympus Cell Sense) were used to analyze the immunofluorescence reactions [39], [26].

Western blot

Tissue samples were digested in T-PER Tissue Protein Extraction Reagent using a TissueRuptor homogenizer (Qiagen, Hilden, Germany), while cell lysates were homogenized in RIPA buffer. 0.For protein isolation, 5 mM PMSF (phenylmethanesulfonyl fluoride), EDTA and Heat™ Protease Inhibitor Coctail ×100 (all Thermo Scientific, Wilmington, DE, USA) were added. The bicinchoninic acid assay (Pierce BCA Protein Assay Kit) was used to determine total protein content, which was measured using the NanoDrop1000 (Thermo Fisher). Samples were denatured in a buffer consisting of 250 mM TRIS at pH 6.8, 40% glycerol, 20% (v/v) β-mercaptoethanol, 0.33 mg/ml bromophenol blue and 8% sodium dodecyl sulfate (SDS) for 10 minutes at 95°C. To perform SDS-PAGE, a Mini Protean 3 instrument (Bio-Rad, Hercules, CA, USA) was used with a 10% polyacrylamide gel for total protein and 12% for VEGFA and VEGFC; 30 μg of protein [40], [41] was applied per lane. We then performed a wet transfer in Tris-glycine buffer containing 20% methanol and 0.05% SDS onto a PVDF 0.45 µm (polyvinylidene difluoride membrane) (Immobilon, Millipore, Bedford, MA, USA) for a 1-h transfer at 140 V to nearly separate the proteins. For VEGFA and VEGFC proteins, 0.20 µm nitrocellulose membranes (Bio-Rad) were used at transfer conditions of 0.5 hours at 70 V. The blocker used was 5% skim milk in 0.05% TBST or 5% BSA in 0.05% TBST for CHI3L1.

Incubation with primary antibodies was performed overnight at 4ºC at the following concentrations: CHI3L2 (mouse monoclonal antibody, MAB5116, R&D, 1:1000 in 5% milk in 0.05% TBST), STAT-3 (rabbit polyclonal antibody, 1:1000 in 0.1%, A11185, ABclonal, Woburn, MA, USA), p-STAT-3 (rabbit monoclonal antibody, 1:1000 in 5% milk in TBST 0.05%, ab76315, Abcam). E-cadherin (mouse monoclonal, 1:1000, sc-8426, Santa Cruz), N-cadherin (mouse monoclonal, 1:1000, sc-8424, Santa Cruz), β-tubulin (rabbit polyclonal, 1:1000, ab6046, in 0.1% BSA in 0. 1% TBST, ab6046, Abcam, Cambridge, UK), VEGFA (mouse monoclonal, 1:1000, M7273, Dako, Glostrup, Denmark), VEGFC (mouse monoclonal, 101-M90, ReliaTech, Wolfenbüttel, Germany), VEGFD (mouse monoclonal, MAB286, R&D) [7].

For the secondary HRP-conjugated antibodies, incubation was performed for 1 hour at RT. Donkey anti-mouse (1:3000), donkey anti-rabbit (1:6000), both in 5% milk in 0.05% TBST (Jackson ImmunoResearch, Suffolk, UK) or donkey anti-goat (1:10000 in TBST, Jackson ImmunoResearch) were used. Super-Signal West Femto chemiluminescence substrate from ThermoFisher was used for the chemiluminescence reaction. Visualization was performed using Bio-Rad's ChemiDocTM MP system with Bio-Rad's ImageLab software (exposure time from 1 second to 3 minutes). Densitometric analysis was based on independent triplicates using ImageLab software (Bio-Rad). Reference protein was β-tubulin, except for pSTAT-3 and pERK1/2, where STAT-3 and ERK1/2 levels, respectively, served as reference [42] .

mRNA expression profile

For the transcriptomic analysis we used the database GSE3494 of the Gene Expression Omnibus Portal. This database contains clinical data and a complete microarray evaluation of gene expression for 251 breast cancer cases (G1: N=67, G2: N=128, G3: N=54) and uses the GPL96 [HG-U133A] Affymetrix Human Genome U133A Array (Thermo Fischer) (Miller et al., 2005). Patients underwent surgery in Sweden between 1987 and 1989. The raw gene expression data were normalized using the global mean approach, where the logarithmic signal values were transformed and scaled with log 500 as the target signal value. In our study, we examined CHI3L2 expression data from breast cancer tumors with different tumor grades (G1, G2, G3) and estrogen (ER) and progesterone receptor (PR) expression.

The normal distribution was analyzed using the Shapiro-Wilk test. As the variables had a non-normal distribution, a non-parametric test was used for the statistical analysis. The expression of the markers was analyzed using Spearman's and Kendall's tau -b correlation, the Kruskal-Wallis test with post-hoc Dunn test and the Mann-Whitney U test. The Breslow, Kaplan-Meier and Cox hazard regression models were used to examine the survival rates. The proportionality assumption was met for all predictors except pT, which was converted to a categorical variable in the results. Statistically significant p-values were defined at a level ≤0.05. Statistical analyzes were performed using Statistica 13.3 (Tibco, Palo Alto, CA, USA).

CHI3L2 expression in cancer cells is higher in lower tumors grade ER+ and PR+ and is not associated with angiogenesis and macrophage infiltration

The clinicopathologic data and the results of the immunohistochemical reactions are shown in Table 3. Cytoplasmic expression of CHI3L2 in cancer cells in IDC was detected by immunohistochemistry. Low expression of this protein occurred in 52.7% of cases, while high expression occurred in 47.3% of cases (Table 4). The differentiation of the expression levels of CHI3L2 and other markers detected by immunohistochemical reactions is shown in Figure 1. The expression level of CHI3L2 was highest in non-malignant breast tissue lesions (NBTLs) and decreased significantly with higher tumor grades. Conversely, the expression of CD68, indicative of macrophage infiltration, and CD206 (specific for an anti-inflammatory macrophage phenotype) increased with malignancy grade (Figure 2). The angiogenesis markers VEGFA, VEGFC and VEGFD were expressed in the cytoplasm of the cancer cells. No significant Spearman correlations were found between CHI3L2 expression and angiogenesis markers, including CD31 (r=-0.094, p=0.42), VEGFC (r=0.02, p=0.9) and VEGFD (r=-0.12, p=0.98) (data not shown). CHI3L2 showed an almost statistically significant correlation with CD34 (T=0.14, p=0.064) and VEGFA (T=0.14, p=0.082), while there were no correlations with CHI3L1 (Figure 3A), as shown by the Kendall's Tau-b correlations. Spearman correlation showed a significant negative association between CHI3L2 and CD68 expression (Figure 3B), but no significant correlation was found between CHI3L2 and CD206 expression. The expression of CD68 and CD206 showed a significant moderate positive correlation (Figure 3B). The cases with the highest CHI3L2 expression showed positive ER and PR expression, which was significantly correlated, while the lowest CHI3L2 expression was associated with positive HER-2 expression (Figure 4).

The immunofluorescence reaction proves the presence of CHI3L2 in the cytoplasm of cancer cells in IDC tumors. In addition, CHI3L2 expression was also observed in CD206-positive TAMs (Figure 5).

CHI3L2 is not a prognostic factor for patient survival

The analysis of patient survival using the proportional Cox hazards model showed no influence of CHI3L2 expression on the survival of patients with IDC (p=0.52, Cox parameter=0.11). However, an association was found with pT status (tumor size) and PR status (p=0.011, Cox parameter=-1.5 and p=0.0098, Cox parameter=1.2, respectively) (Table 5). Other investigated clinicopathologic factors, such as ER, HER-2 status, pN, Ki-76, age at treatment initiation, menopausal status and G, showed no significant associations. However, overall patient survival was found to be significantly influenced by pT, which had an unfavorable prognostic value, and PR, which had a favorable prognostic value. Table 5 shows the results of the Cox proportional hazard analysis.

Expression of CHI3L2 positively correlates with the phosphorylation of ERK1/2 and STAT-3 in IDC tumors

In tumor material, the highest expression of CHI3L2 was observed in G1 IDC tumors, and it decreased with the progression of tumor grades (see Figure 6A,B). Immunoblotting also showed negative cases for CHI3L2 expression. No correlation was found between CHI3L2 expression and CHI3L1, VEGFA, VEGFC and VEGFD (data not shown). The highest level of CHI3L2 showed a positive and significant correlation with the phosphorylation of STAT-3 and ERK1/2 (Figure 6C).

Breast cancer cell lines produce CHI3L2 and may stimulate macrophages to express CHI3L2

Expression of CHI3L2 protein was observed in breast cancer cell lines BT-549, MDA-MB-436 and BO2, as well as in normal breast epithelium and cells with fibrocystic disease: HME1-hTERT (Me16C) and MCF10A (Figure 7). All analyzed cell lines expressing CHI3L2 were negative for ER, PR and HER-2 and are considered representative of the basal subtype of breast cancer, except for the BO2 cell line with metastatic adenocarcinoma features, as shown in Table 1. Macrophages expressed CHI3L2 at low levels, but the expression of this protein was higher in macrophage cocultures with conditioned medium from CHI3L2-negative cancer cells (MCF-7 and MDA-MB-468), as shown in Figure 7. In addition, the levels of pSTAT-3 and pERK1/2 in breast cancer cell lines and macrophages were not dependent on CHI3L2 expression (Figure 7).

CHI3L2 mRNA expression was not significantly different in non-specific breast cancers

Transcriptome analysis performed in breast cancer cases revealed that mRNA levels of CHI3L2 were highest in G3, although there were no significant differences between tumors with different tumor grades. A tendency for the highest CHI3L2 mRNA level was observed in tumors without ER or PR expression. This correlation was not significant, but a trend was observed (Figure 8).

In fact, few papers have reported the expression of CHI3L2 in breast cancer, suggesting a possible role of this protein in carcinogenesis. Previous studies have demonstrated the expression of CHI3L2 in cancer cells, including glioblastoma tumors and cell lines such as U-87 MG and HEK293 [43], [44].

Indeed, CHI3L2 was expressed in glioblastoma tumors in cancer cells and microglia, and its expression was associated with poor patient prognosis [24], [44]. The presence of this protein in macrophages infiltrating nonspecific breast cancer tumors and its highest levels in developing metastases were reported by Liu and colleagues [24]. In addition, the authors show that the highest concentration of CHI3L2 after neoadjuvant therapy is an unfavorable indicator of treatment efficacy and also stimulates angiogenesis [24].

In contrast, our team's results clearly show that CHI3L2 is expressed in breast cancer cell lines and in vitro cultures as well as in cancer cells in tumor material from patients with IDC. In our study, we found evidence that CHI3L2 expression in cancer cells is specific for this type of breast tumor.

In our studies performed on commercially available cancer cell lines, the expression of CHI3L2 was detected in triple negative cells lacking ER, PR and HER-2, indicating a basal breast cancer subtype. This finding could have clinical implications. It is worth noting that patients with triple-negative breast cancer have a poorer prognosis compared to those with other forms of breast cancer. However, the results from the monolayer model of cancer cell lines may not reflect the complex system that occurs in tumors, where interactions between cancer cells, macrophages and stromal cells play a role. This difference in the expression pattern of CHI3L2 between in vitro models and patient material could be due to the above-mentioned interaction.

In contrast to breast cancer cell lines, the expression of CHI3L2 in tumors was highest in tumors positive for estrogen receptor (ER) and progesterone receptor (PR) and lowest in HER-2 positive tumors. Although the differences in CHI3L2 mRNA levels were insignificant, this analysis was performed in breast cancer tumors without distinguishing between cancer subtype diagnoses. Analysis of clinicopathologic data showed that CHI3L2 expression had no effect on patient survival or event-free survival. Our analysis of tumor material also showed a decrease in CHI3L2 expression with higher tumor grades (G). It is possible that the overexpression of CHI3L2 in low-grade malignant tumors suggests that the protein may be involved in inhibiting tumor growth or promoting tumor growth only at early stages. Our results differ from those of previous studies, such as Liu et al. and Kzhyshkowska[3] [24] ,which suggest that CHI3L2 is rather an unfavorable prognostic factor in cancer cells. In our opinion, these discrepancies could be related to different forms of breast cancer, which might differ in terms of CHI3L2 expression. Therefore, it is worth investigating the role of CHI3L2 protein in different types of breast cancer.

Our hypothesis about the positive role of CHI3L2 in patient prognosis is noteworthy, especially considering that CHI3L1 plays a significant role as a poor prognostic factor in various cancers such as glioma and breast cancer [44]. Our previous study in IDC tumors [19] shows that CHI3L1 supports VEGFD-mediated angiogenesis in this type of cancer [45]. Hovewer in these studies, no significant correlations were found between CHI3L2 and angiogenesis markers even with CHI3L1, suggesting that CHI3L2 is not involved in angiogenesis in IDC and this similar protein: CHI3L1 and CHI3L2 appear to differ significantly in their function.

Activation of the ERK1/2 kinase pathway, a component of the mitogen-activated protein kinase pathway (MAPK), usually promotes tumor growth, metastasis and angiogenesis. High concentrations of pERK1/2 are observed in various types of cancer such as breast, colon and lung cancer. The combination of RAF-ERK inhibitors may have anti-cancer effects [46] [47]. On the other hand, the anti-apoptotic function of pERK1/2 has also been documented in tumor suppressive mechanisms [46]. Certain anticancer drugs such as cisplatin, etoposide or paclitaxel and other sources of damage such as γ-irradiation, UV radiation and natural plant substances can trigger the anti-apoptotic function of pERK1/2.

From this perspective, CHI3L2 could serve as a promising subject to investigate its influence on ERK pathway activation in IDC [46], [48], [49]. Mechanistically, CHI3L2 has been found to activate ERK1/2 [44], [43]. Consistent with these reports, our results also suggest that CHI3L2 increases pERK1/2 and pSTAT-3 in IDC tissue. Interestingly, opposite roles of pERK1/2 are possible and have been described by Areshkov and team. For example, CHI3L1 leads to a proliferation of cancer cells, while CHI3L2 appears to inhibit the cell cycle [43]. The exact role of CHI3L2-mediated activation of the ERK1/2 signaling pathway remains to be investigated.

The signal transducer and activator of transcription, STAT-3, in turn plays a multifaceted role in carcinogenesis. The promotion of migration, invasion, metastasis, angiogenesis and immune escape of tumors characterizes the tumor-promoting effect of STAT-3 phosphorylation. Conversely, the antitumor effect of pSTAT3 is mediated in part by the reduced efficacy of IL-8 observed in glioblastomas [50], [51]. In breast cancer, activation of pSTAT-3 could contribute to cancer cell survival. In the review publication by Tolomeo and Cascio [51], the importance of STAT-3 activation for the mechanisms of carcinogenesis is analyzed in detail. Currently, the investigation of the role of CHI3L2 in the effects of pSTAT-3 in IDC is an interesting question to be explored.

In addition, we observed the expression of CHI3L2 in TAMs, which is consistent with the results of another study on breast cancer and glioma tumors [44]. CHI3L2 was expressed at low levels in macrophage cells in vitro, but its expression was enhanced in co-cultures designed to mimic the tumor microenvironment. Interestingly, in our simple co-culture model, CHI3L2-negative cancer cells were found to stimulate macrophage production of this protein. Our results help to clarify previous observations by Liu and colleagues, who detected CHI3L2 expression exclusively in TAMs and not in cancer cells [24]. Furthermore, we observed a negative correlation between CHI3L2 expression in tumor cells and infiltration of macrophages, but not TAMs. These results suggest that CHI3L2 may be involved in communication between cancer cells and immune cells, but further studies are needed to confirm this hypothesis. The specific function of CHI3L2 in the interaction between cancer cells and macrophages remains unclear. It is also conceivable that CHI3L2 expression in breast cancer cells and macrophages could promote different pathways of tumor growth. Our team will focus on this question in the future to clarify the mechanism of the role of CHI3L2 in the communication between TAMs and cancer cells in breast tumors, which could be a key factor in IDC tumor progression [52]. This interaction could be important for predicting breast cancer treatment and categorizing breast cancer types; however, it is crucial to substantiate this hypothesis.

The expression of CHI3L2 was detected for the first time in cancer cells in IDC. Previously, CHI3L2 expression in breast tumors had only been observed in TAMs. Higher expression of CHI3L2 was observed in tumors with lower malignancy grade or in non-malignant lesions. A correlation with pSTAT-3 and pERK1/2 was observed. Elevated levels of CHI3L2 protein were detected in ER + and PR + tumors. A negative significant correlation was observed between CHI3L2 and CD68, a pan-macrophage marker, but the expression of CHI3L2 in TAMs was confirmed. Our study suggests that CHI3L2 protein is not involved in angiogenesis and has a different function than CHI3L1. In vitro experiments showed that CHI3L2-negative breast cancer cells can induce macrophages to produce CHI3L2 protein. These results suggest a potential role of CHI3L2 protein in IDC, possibly contributing to tumor-microenvironment cross-talk, as well as an antitumor protective function.

Study limitation

This study analyzed 74 tumor samples from patients IDC diagnosed with and followed their progress over time. A larger study with complete treatment data will validate these results and evaluate the significance of CHI3L2 protein as a predictor of IDC outcome.

Author Contributions

Conceptualization: AR; Methodology: AR; Investigation: AR, EK, TG, AP, CS, AW; Resources: AR, PD, JK; Validation: AR; Visualization AR, AK, KRW, AP; Formal Analysis: AR, KK; Writing – Original Draft: AR; Writing – Review & Editing: AR, PD, JK; Supervision: PD, JK; Project Administration: AR; Funding Acquisition: AR. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partially funded by the National Science Center, Poland (NCN), under the Miniatura 5 grant (grant number 2021/05/X/NZ2/01698) to Agnieszka Rusak entitled "CHI3L1 and CHI3L2 as Proteins with Potential Prognostic and Therapeutic Significance in Breast Carcinoma and Glioblastoma". In addition, the Wroclaw Medical University received a promoter scholarship (grant number: STM.A110.17.025) entitled "The Role of YKL-39 (CHI3L2) in Breast Cancer".

For the purpose of open access, the author has applied a CC-BY public copyright license to any Author Accepted Manuscript (AAM) version resulting from this submission.

Institutional Review Board Statement: The study was conducted in compliance with the Declaration of Helsinki and was approved by the Bioethics Committee of WROCLAW MEDICAL UNIVERSITY (No. KB-517/2017, approved on July 22, 2017; KB-217/2022 and No. KB-216/2022, both approved on March 15, 2022).

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets [GENERATED/ANALYZED] for this study can be found in the [POLISH PLATFORM FOR MEDICAL RESEARCH] [ https://ppm.umw.edu.pl/info/researchdata/UMWd123852dab8646519ffc6b773ac9e2b9/]

[ https://ppm.umw.edu.pl/info/researchdata/UMW45fd930aadc44e9face13b51618e810d/]

Acknowledgments

The authors would like to thank Bożena Przygodzka, Elżbieta Połejko and Agnieszka Barańska for their fantastic technical assistance in the preparation of tissue sections at the Wroclaw Medical University, Poland. Special thanks to Helena Rusak.

Conflicts of interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

J. Kzhyshkowska, a Gratchev, S. Goerdt, Human chitinases and chitinase-like proteins as indicators for inflammation and cancer, Biomark Insights, 2 (2007) 128–146.
V. Riabov, A. Gudima, N. Wang, A. Mickley, A. Orekhov, J. Kzhyshkowska, Role of tumor associated macrophages in tumor angiogenesis and lymphangiogenesis, Front. Physiol., 5 MAR (2014) 1–13.
J. Kzhyshkowska, I. Larionova, T. Liu, YKL-39 as a Potential New Target for Anti-Angiogenic Therapy in Cancer, Front. Immunol., 10 (2020) 1–10.
S. Yin, N. Wang, V. Riabov, D.M. Mossel, I. Larionova, K. Schledzewski, O. Trofimova, T. Sevastyanova, A. Zajakina, C. Schmuttermaier, A. Gratchev, A. Flatley, E. Kremmer, M. Zavyalova, N. Cherdyntseva, K. Simon-Keller, A. Marx, H. Klüter, S. Goerdt, J. Kzhyshkowska, SI-CLP inhibits the growth of mouse mammary adenocarcinoma by preventing recruitment of tumor-associated macrophages, Int. J. Cancer, 146 (2020) 1396–1408.
Y. Zheng, M.B. Graeber, Microglia and Brain Macrophages as Drivers of Glioma Progression, Int. J. Mol. Sci., 23 (2022).
T. Zhao, Z. Su, Y. Li, X. Zhang, Q. You, Chitinase-3 like-protein-1 function and its role in diseases, Signal Transduct. Target. Ther., (2020) 1–20.
A. Rusak, I. Buzalewicz, M. Mrozowska, B. Wiatrak, K. Haczkiewicz-Leśniak, M. Olbromski, A. Kmiecik, E. Krzyżak, A. Pietrowska, J. Moskal, M. Podhorska-Okołów, H. Podbielska, P. Dzięgiel, Multimodal study of CHI3L1 inhibition and its effect on angiogenesis, migration, immune response and refractive index of cellular structures in glioblastoma, Biomed. Pharmacother., 161 (2023).
C. Cintin, J.S. Johansen, I.J. Christensen, P. a. Price, S. Sørensen, H.J. Nielsen, High serum YKL-40 level after surgery for colorectal carcinoma is related to short survival, Cancer, 95 (2002) 267–274.
Y.W. Shao R, Hamel K, Petersen L, Qing Cao J, Arenas RB, Bigelow C, Bentley B, YKL-40, a secreted glycoprotein, promotes tumor angiogenesis, Oncogene, 28 (2009) 4456–4468.
R. a. Francescone, S. Scully, M. Faibish, S.L. Taylor, D. Oh, L. Moral, W. Yan, B. Bentley, R. Shao, Role of YKL-40 in the angiogenesis, radioresistance, and progression of glioblastoma, J. Biol. Chem., 286 (2011) 15332–15343.
A. Rusak, K. Jabłońska, P. Dzięgiel, The role of YKL-40 in a cancerous process, Postepy Hig. Med. Dosw. (Online), 70 (2016) 1286–1299.
N. Xu, Q. Bo, R. Shao, J. Liang, Y. Zhai, S. Yang, F. Wang, X. Sun, Chitinase-3-like-1 promotes M2 macrophage differentiation and induces choroidal neovascularization in neovascular age-related macular degeneration, Investig. Ophthalmol. Vis. Sci., 60 (2019) 4596–4605.
J. Johansen, High serum YKL-40 level in patients with small cell lung cancer is related to early death, Lung Cancer, 46 (2004) 333–340.
C.G. Lee, J. a. Elias, Role of breast regression protein-39/YKL-40 in asthma and allergic responses, Allergy, Asthma Immunol. Res., 2 (2010) 20–27.
K. Tizaoui, J.W. Yang, K.H. Lee, J.H. Kim, M. Kim, S. Yoon, Y. Jung, J.B. Park, K. An, H. Choi, D. Song, H. Jung, S. Ahn, T. Yuh, H.M. Choi, J.H. Ahn, Y. Kim, S. Jee, H. Lee, S. Jin, et al., The role of YKL-40 in the pathogenesis of autoimmune diseases: a comprehensive review, Int. J. Biol. Sci., 18 (2022) 3731–3746.
C. Russo, M.S. Valle, A. Casabona, L. Malaguarnera, Chitinase Signature in the Plasticity of Neurodegenerative Diseases, Int. J. Mol. Sci., 24 (2023).
F. Li, A. Liu, M. Zhao, L. Luo, Astrocytic Chitinase-3-like protein 1 in neurological diseases: Potential roles and future perspectives, J. Neurochem., 165 (2023) 772–790.
J.-S. Kim, Protein biomarkers in multiple sclerosis, Encephalitis, 3 (2023) 54–63.
A. Rusak, K. Jablonska, A. Piotrowska, J. Grzegrzolka, A. Nowak, A. Wojnar, P. Dziegiel, The role of CHI3L1 expression in angiogenesis in invasive ductal breast carcinoma, Anticancer Res., 38 (2018) 3357–3366.
A. Rusak, K. Jablonska, A. Piotrowska, J. Grzegrzolka, A. Wojnar, P. Dziegiel, Correlation of expression of CHI3L1 and Nogo-A and their role in angiogenesis in invasive ductal breast carcinoma, Anticancer Res., 39 (2019) 2341–2350.
H.L. Zeng, D. Chen, J. Yan, Q. Yang, Q.Q. Han, S.S. Li, L. Cheng, Proteomic characteristics of bronchoalveolar lavage fluid in critical COVID-19 patients, FEBS J., 288 (2021) 5190–5200.
T. Ebihara, T. Matsubara, Y. Togami, H. Matsumoto, J. Tachino, H. Matsuura, T. Kojima, F. Sugihara, S. Seno, D. Okuzaki, H. Hirata, H. Ogura, Combination of WFDC2, CHI3L1, and KRT19 in Plasma Defines a Clinically Useful Molecular Phenotype Associated with Prognosis in Critically Ill COVID-19 Patients, J. Clin. Immunol., (2022).
Emine Parlak and Esra Laloğlu, Analysis of Chitinase-3-Like Protein 1, IL-1-Alpha, and IL-6 as Novel Inflammatory Biomarkers for COVID-19, J. Interf. Cytokine Res., 42 (2022) 536–541.
T. Liu, I. Larionova, N. Litviakov, V. Riabov, M. Tsyganov, M. Buldakov, B. Song, K. Moganti, P. Kazantseva, E. Slonimskaya, E. Kremmer, A. Flatley, H. Klüter, N. Cherdyntseva, J. Kzhyshkowska, T. Liu, I. Larionova, N. Litviakov, V. Riabov, M. Tsyganov, et al., Tumor-associated macrophages in human breast cancer produce new monocyte attracting and pro- angiogenic factor YKL-39 indicative for increased metastasis after neoadjuvant chemotherapy, Oncoimmunology, 7 (2018) 1–17.
T. Górnicki, J. Lambrinow, M. Mrozowska, H. Romanowicz, B. Smolarz, A. Piotrowska, A. Gomułkiewicz, M. Podhorska-Okołów, P. Dzięgiel, J. Grzegrzółka, Expression of RBMS3 in Breast Cancer Progression, Int. J. Mol. Sci., 24 (2023).
E. Kątnik, A. Gomułkiewicz, A. Piotrowska, J. Grzegrzółka, A. Rusak, A. Kmiecik, K. Ratajczak-Wielgomas, P. Dzięgiel, BCL11A Expression in Breast Cancer, Curr. Issues Mol. Biol., 45 (2023) 2681–2698.
J. Kao, K. Salari, M. Bocanegra, Y. La Choi, L. Girard, J. Gandhi, K.A. Kwei, T. Hernandez-Boussard, P. Wang, A.F. Gazdar, J.D. Minna, J.R. Pollack, Molecular profiling of breast cancer cell lines defines relevant tumor models and provides a resource for cancer gene discovery, PLoS One, 4 (2009).
K. Balon, B. Wiatrak, Pc12 and thp-1 cell lines as neuronal and microglia model in neurobiological research, Appl. Sci., 11 (2021) 1–17.
S.Sj. al. Lakhani SR, Ellis IO, WHO Classification of tumors Editorial Board, 5th ed., IARC, Lyon, France, 2022.
F. Pareja, T.M. D’Alfonso, Neuroendocrine neoplasms of the breast: A review focused on the updated World Health Organization (WHO) 5th Edition morphologic classification, Breast J., 26 (2020) 1160–1167.
A. Popiel-Kopaczyk, J. Grzegrzolka, A. Piotrowska, M. Olbromski, B. Smolarz, H. Romanowicz, A. Rusak, M. Mrozowska, P. Dziegiel, M. Podhorska-Okolow, C. Kobierzycki, The Expression of Testin, Ki-67 and p16 in Cervical Cancer Diagnostics, Curr. Issues Mol. Biol., 45 (2023) 490–500.
D.P. Zadka L, Kram P, Koscinski J, Jankowski R, Kaczmarek M, Piatek K, Kulus M, Gomułkiewicz A, Piotrowska A, Association Between Interleukin-10 Receptors and the CD45-Immunophenotype of Central Nervous System Tumors: A Preliminary Study, Anticancer Res., 37 (2017) 5777–5783.
Wolfgang Remmele and H. E. Stegner, Recommendation for uniform definition of an immunoreactive score (IRS) for immunohistochemical estrogen receptor detection (ER-ICA) in breast cancer tissue, Pathologe, 8 (1987) 138–40.
M.G. P.B. Vermeulen, G. Gasparini, S.B. Foxc, C. Colpaert, L.P. Marsond, N.W. J.A.M. Belie¨nf, R.M.W. de Waalg, E. Van Marcka, E. Magnanib, L.Y.D. A.L. Harrisi, Second international consensus on the methodology and criteria of evaluation of angiogenesis quantification in solid human tumours, Eur. J. Cancer, 38 (2002) 1564–1579.
I. Van der Auwera, Y. Cao, J.C. Tille, M.S. Pepper, D.G. Jackson, S.B. Fox, a L. Harris, L.Y. Dirix, P.B. Vermeulen, First international consensus on the methodology of lymphangiogenesis quantification in solid human tumours, Br. J. Cancer, 95 (2006) 1611–1625.
S.B. Fox, A.L. Harris, Histological quantitation of tumour angiogenesis, Apmis, 112 (2004) 413–430.
A. Królicka, C. Kobierzycki, B. PuŁa, M. Podhorska-OkoŁów, A. Piotrowska, M. Rzeszutko, W. Rzeszutko, J. Rabczyński, P. Domoslawski, B. Wojtczak, J. Dawiskiba, P. Dziegiel, Comparison of metallothionein (MT) and Ki-67 antigen expression in benign and malignant thyroid tumours, Anticancer Res., 30 (2010) 4945–4950.
A.C. Wolff, M. Elizabeth Hale Hammond, K.H. Allison, B.E. Harvey, P.B. Mangu, J.M.S. Bartlett, M. Bilous, I.O. Ellis, P. Fitzgibbons, W. Hanna, R.B. Jenkins, M.F. Press, P.A. Spears, G.H. Vance, G. Viale, L.M. McShane, M. Dowsett, Human epidermal growth factor receptor 2 testing in breast cancer: American society of clinical oncology/ college of American pathologists clinical practice guideline focused update, J. Clin. Oncol., 36 (2018) 2105–2122.
A.M. Kmiecik, B. Pula, J. Suchanski, M. Olbromski, A. Gomulkiewicz, T. Owczarek, A. Kruczak, A. Ambicka, J. Rys, M. Ugorski, M. Podhorska-Okolow, P. Dziegiel, Metallothionein-3 increases triple-negative breast cancer cell invasiveness via induction of metalloproteinase expression, PLoS One, 10 (2015) 1–25.
U.K. Laemmli, Cleavage of Structural Proteins during the Assembly of the Head of Bacteriophage T4, Nature, 227 (1970) 680–685.
M. Olbromski, J. Grzegrzolka, A. Jankowska-Konsur, W. Witkiewicz, M. Podhorska-Okolow, P. Dziegiel, MicroRNAs modulate the expression of the SOX18 transcript in lung squamous cell carcinoma, Oncol. Rep., 36 (2016) 2884–2892.
Y. Sun, L. Liu, Y. Wang, A. He, H. Hu, J. Zhang, M. Han, Y. Huang, Curcumin inhibits the proliferation and invasion of MG-63 cells through inactivation of the p-JAK2/ p-STAT3 pathway, Onco. Targets. Ther., 12 (2019) 2011–2021.
P.O. Areshkov, S.S. Avdieiev, O. V. Balynska, D. LeRoith, V.M. Kavsan, Two closely related human members of chitinase-like family, CHI3L1 and CHI3L2, activate ERK1/2 in 293 and U373 cells but have the different in-fluence on cell proliferation, Int. J. Biol. Sci., 8 (2011) 39–48.
L. Liu, Y. Yang, H. Duan, J. He, L. Sun, W. Hu, J. Zeng, CHI3L2 Is a Novel Prognostic Biomarker and Correlated With Immune Infiltrates in Gliomas, Front. Oncol., 11 (2021) 1–13.
S.M.Z. Bokhari, P. Hamar, Vascular Endothelial Growth Factor-D (VEGF-D): An Angiogenesis Bypass in Malignant Tumors, Int. J. Mol. Sci., 24 (2023) 1–19.
R. Sugiura, R. Satoh, T. Takasaki, Erk: A double-edged sword in cancer erk-dependent apoptosis as a potential therapeutic strategy for cancer, Cells, 10 (2021).
M. Morante, A. Pandiella, P. Crespo, Immune Checkpoint Inhibitors and RAS – ERK Pathway-Targeted Drugs as Combined Therapy for the Treatment of Melanoma, (2022).
M.H. Nissan, N. Rosen, D.B. Solit, VIEWS IN THE SPOTLIGHT ERK Pathway Inhibitors : How Low Should We Go ?, (2013) 719–721.
I. Smalley, K.S.M. Smalley, VIEWS eRK Inhibition : A new front in the War against MAPK Pathway – Driven Cancers ?, (2018) 140–142.
A.C. Guanizo, C.D. Fernando, D.J. Garama, D.J. Gough, STAT3: a multifaceted oncoprotein, Growth Factors, 36 (2018) 1–14.
M. Tolomeo, A. Cascio, The multifaced role of stat3 in cancer and its implication for anticancer therapy, Int. J. Mol. Sci., 22 (2021) 1–25.
Ł. Zadka, D.J. Grybowski, P. Dzięgiel, Modeling of the immune response in the pathogenesis of solid tumors and its prognostic significance, Cell. Oncol., (2020).

Table 1. Expression of CHI3L2 in breast cancer cell lines. The characteristics of the human breast cancer cell lines used in the study are described according to Kao et al. [27]

	Cell line ER PR HER-2 tumor type subtype CHI3L2
HME1-hTERT (Me16C)		-	NA	-	NA	basal B	+
MCF-7		+	+	-	metastatic adenocarcinoma	luminal	-
MCF10A		-	-	-	fibrcoystic disease	basal B	+
SK-BR-3		-	-	+	adenocarcinoma	luminal	-
T-47D		+	+	-	invasive ductal breast carcinoma	luminal	-
BT-474		+	+	+	invasive ductal breast carcinoma	luminal	-
BT-549		-	-	-	invasive ductal breast carcinoma	basal B	+
MDA-MB-231		-	-	-	metastatic adenocarcinoma	basal B	+
MDA-MB-436		-	-	-	adenocarcinoma	basal B	-
MDA-MB-468		-	-	-	metastatic adenocarcinoma	basal A	-
BO2		-	-	-	metastatic adenocarcinoma	NA	+

ER: estrogen receptor, PR: progesterone receptor, HER-2: human epidermal growth factor receptor 2

Table 2. Semi-quantitative immunoreactive scale (IRS) according to Remmele and Stegner [33], in which the result of the multiplication of the percentage of positively stained cells (A) and the intensity of the immunohistochemical reaction (B), (AxB) gives a score.

Points (AxB)	Percentage of positive cells (A)	Intensity of immunohistochemical reaction (B)
0	0%	0: no color reaction
1	≤10%	1: weak reaction
2	11-50%	2: moderate reaction
3	51-80%	3: intense reaction
4	>80%

Table 3. The expression of the protein chitinase 3-like 2 (CHI3L2) was measured using the immunoreactive score (IRS) (Remmele and Stegner, 1987) and its correlation with the clinicopathological data of patients diagnosed with IDC was analyzed. The cut-off point was determined using the median value.

		Total		IRS (0-6)		IRS (8-12)
Clinicopathological data		N 74	% 100	N 39	% 52.7	N 35	% 47.3
Age	>50	21	28.4	13	17.6	8	10.8
	≤50	53	71.6	27	36.5	26	35.1
Menopausal status	pre-	22	29.7	12	16.2	10	43.3
	post-	44	59.5	23	31.1	21	28.4
	unknown	8	10.8	4	5.4	4	5.4
ER status	positive	45	60.8	20	27.0	25	33.8
	negative	21	28.4	16	21.6	5	6.8
	unknown	8	10.8	3	4.0	5	6.8
PR status	positive	40	54.1	17	23.0	23	31.1
	negative	26	35.1	19	25.7	7	9.4
	unknown	8	10.8	3	4.0	5	6.8
HER-2 status	positive	15	20.3	12	16.2	3	4.1
	negative	51	68.9	24	32.4	27	35.6
	unknown	8	10.8	3	4.0	5	6.8
Triple negative (TN)	yes	10	13.5	7	9.4	3	4.1
	no	50	67.6	25	33.8	25	33.8
	unknown	14	18.9	7	9.4	7	9.4
Tumor grade (G)	1	7	9.5	1	1.4	6	8.1
	2	38	51.3	21	28.4	17	22.9
	3	27	36.5	17	23.0	10	13.5
	unknown	2	2.7	0	0	2	2.7
Stage	I	19	25.7	10	13.5	9	12.2
	II	37	50.0	19	25.7	18	24.3
	III	9	12.2	6	8.1	3	4.1
	IV	1	1.3	0	0	1	1.3
	unknown	8	10.8	4	5.4	4	5.4
Tumor size (pT)	pT0	12	16.2	7	9.4	5	6.8
	pT1	29	39.2	14	19.0	15	20.2
	pT2	21	28.4	10	13.5	11	14.9
	pT3	6	8.1	5	6.8	1	1.3
	pT4	4	5.4	2	2.7	2	2.7
	unknown	2	2.7	1	1.3	1	1.3
Lymph node (pN)	pN0	42	56.8	24	32.4	18	24.3
	pN1	16	21.6	7	9.4	9	12.2
	pN2	5	6.8	3	4.0	2	2.7
	pN3	3	4.0	1	1.3	2	2.7
	unknown	8	10.8	4	5.4	4	5.4
Ki-67	low ≤25%	29	39.2	15	20.3	14	18.9
	High >25%	9	12.2	8	10.8	1	1.3
	unknown	36	48.6	16	21.6	20	27.0

ER: estrogen receptor; PR: progesteron receptor; HER-2: human epidermal growth factor receptor 2; TN: triple negative (no expression of ER, PR and HER-2 receptor).

Table 4. Immunohistochemical analysis was performed using the IRS scale according to Remmele and Stegner [33] to evaluate the expression of the markers. Microvessel density (MVC) was assessed using the Chalkley ocular [34]. The number of macrophages was assessed in the field of view under 200x magnification. The median value was used as the cut-off value.

		Low expresion		High expression
IHC marker	Cut-off value	N	%	N	%
CHI3L2	IRS 0-6 vs. 8-12	39	52.7	35	47.3
CHI3L1	IRS 0-3 vs. 4-12	49	66.2	25	33.8
VEGFA	IRS 0-4 vs. 6-12	47	63.5	27	36.5
VEGFC	IRS 0-4 vs. 6-12	48	64.9	26	35.1
VEGFD	IRS 0-4 vs. 6-12	42	56.8	32	43.2
CD31	MVC ≤8 vs >8	43	50.0	43	50.0
CD34	MVC ≤9 vs >9	44	59.5	30	40.5
CD68	≤86.4>	38	51.4	36	48.6
CD206	≤43.75>	38	51.4	36	48.6

CHI3L1: chitinase-3 like 1; CHI3L2: chitinase-3 like 2; VEGFA: vascular endothelial growth factor A; VEGFC: vascular endothelial growth factor C; VEGFD: vascular endothelial growth factor D

Table 5. The results of the proportional Cox hazard analysis of the clinicopathologic patient data showed statistically significant P-values at a level of < 0.05 (indicated by red marking).

factor	level effect	parameter	p-value
age		-0,03	0,65
premenopausal status	1	-0,84	0,12
ER		-0,51	0,29
PR		1,19	0,01
HER-2		0,73	0,06
Triple negative	TN	1,47	0,05
Tumor size (pT)	2	-1,48	0,01
Lymph node (pN)		0,14	0,79
Grade (G)	2	-0,77	0,16
Grade (G)	3	-0.13	0.81
Ki-67		0,04	0,09
CHI3L2		0,11188	0,517875

No competing interests reported.

New insights into the role of the CHI3L2 protein in invasive ductal breast carcinoma: the CHI3L1 protein has a different role

Status:

Version 1

Abstract

Purpose

Methods

Results

Discussion

Figures

1. Introduction

2. Materials and methods

3. Statistical analysis

4. Results

5. Discussion

Conclusions

Declarations

References

Tables

Additional Declarations

Status:

Version 1