Open Access

Potential of blood exosomal ENAH, SEPT9, EGF, MMP‑9 and CXCL8 for the early screening of breast cancer

  • Authors:
    • Zijing Zhang
    • Hongying Wang
    • Yiting Jin
    • Chengyu Chu
    • Jinsong Bai
    • Juntian Huang
    • Lemei Yang
    • Feng Tang
    • Liping Zou
    • Shuyang Wang
    • Qiang Zou
  • View Affiliations

  • Published online on: November 3, 2022     https://doi.org/10.3892/ol.2022.13580
  • Article Number: 460
  • Copyright: © Zhang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Exosomal contents have been recognized as candidate biomarkers for cancer screening and prognosis. The current study aimed to evaluate the potential of the expression levels of exosomal enabled homolog (ENAH), septin 9 (SEPT9), epidermal growth factor (EGF), matrix metalloproteinase‑9 (MMP‑9) and C‑X‑C motif chemokine ligand 8 (CXCL8) in the blood for the early screening of breast cancer. Therefore, exosomes were extracted and purified from the peripheral blood of 47 patients with breast cancer, 63 disease controls (DCs) and 33 healthy controls (HCs). Subsequently, the exosomal mRNA expression levels of ENAH, SEPT9, EGF, MMP‑9 and CXCL8 were detected by reverse transcription‑quantitative polymerase chain reaction. The results showed that the exosomal levels of ENAH and EGF were significantly higher in patients with breast cancer compared with DCs and HCs (both P<0.001). In addition, receiver operating characteristic curves revealed that exosomal ENAH was able to discriminate patients with breast cancer from DCs [area under the curve (AUC), 0.841] and HCs (AUC, 0.859). However, exosomal EGF was only able to discriminate patients with breast cancer from HCs (AUC, 0.776). Furthermore, the levels of exosomal SEPT9 were lower in patients with breast cancer compared with DCs and HCs (P=0.021), and exosomal SEPT9 expression levels exhibited good potential in the discrimination of patients with breast cancer from DCs (AUC, 0.717) and HCs (AUC, 0.830). However, no significant difference was detected in exosomal levels of MMP‑9 and CXCL8 among the three groups, and these RNAs showed no discriminative ability. In addition, in patients with breast cancer, the exosomal levels of ENAH were associated with molecular subtypes (P=0.010), while those of MMP‑9 were associated with a Ki‑67 index of ≥30% (P=0.011). In conclusion, the exosomal levels of ENAH, SEPT9 and EGF in blood samples were able to identify patients with breast cancer, thus providing a novel approach for the early screening of breast cancer.

Introduction

Breast cancer is the most prevalent type of cancer globally, and accounts for >648,000 cancer-associated deaths annually (1,2). In China, it is estimated that ~416,000 patients are diagnosed with breast cancer every year, which results in >117,000 deaths annually (3,4). Currently, the overall prognosis for patients with breast cancer is unsatisfactory, partially due to a significant proportion of patients being diagnosed with this cancer at an advanced stage (57). In response to this, the identification of novel biomarkers for the risk prediction and early screening of breast cancer is of great importance.

Exosomes are spherical particles released by cells that can carry a variety of molecules derived from the cells, including DNAs, RNAs and proteins (8). Due to their stability and ability to remain unaffected by the surrounding environment, it has been suggested that the contents of exosomes exhibit potential as biomarkers for breast cancer screening (911).

With the development of molecular biology, several specific genes involved in the pathogenesis and progression of breast cancer have been identified. For instance, previous studies showed that enabled homolog (ENAH), an actin regulatory protein of the enabled/vasodilator-stimulated phosphoprotein family, promoted the proliferation, invasion and epithelial-mesenchymal transition of breast cancer cells when overexpressed (12,13). Also, other studies showed that septin 9 (SEPT9), an oncogenic protein, was dysregulated in patients with breast cancer with lymph node metastases and regulated the migration of breast cancer cells via ras homolog family member A/focal adhesion kinase signaling (14,15). Additionally, epidermal growth factor (EGF) has been reported to interact with its receptor to regulate the carcinogenesis and malignant behavior of breast cancer cells (16,17). Moreover, matrix metalloproteinase-9 (MMP-9) has been revealed to critically increase the migration and invasion abilities of breast cancer cells, thus reflecting the aggressiveness of breast cancer (18,19). C-X-C motif chemokine ligand 8 (CXCL8) has also been shown to promote breast cancer progression and to be involved in the immunosuppressive tumor microenvironment. Therefore, CXCL8 is considered as a potential therapeutic target for breast cancer (2022). Accordingly, ENAH, SEPT9, EGF, MMP-9 and CXCL8 are critical genes for the pathogenesis and/or progression of breast cancer (1222). The aforementioned findings indicate that these genes could be used in the early screening of breast cancer.

The current study aimed to evaluate the association between the exosomal levels of ENAH, SEPT9, EGF, MMP-9 and CXCL8 in the blood and the risk of breast cancer, as well as the clinical characteristics of patients with breast cancer.

Materials and methods

Subjects

Blood samples from 31 (first batch; age range, 30–87 years) and 16 (second batch; age range, 32–68 years) female patients with breast cancer were collected between January 1 and June 30, 2021 at Huashan Hospital Affiliated to Fudan University (Shanghai, China). The inclusion criteria were as follows: i) Patients diagnosed with breast cancer based on pathological tissue and imaging examinations; ii) aged >18 years; and iii) willing to voluntarily participate in the study and provide peripheral blood (PB). The exclusion criteria were as follows: i) Patients with other primary solid tumors or malignant hematological disorders; and ii) female patients diagnosed with breast cancer during pregnancy or breastfeeding. During the same period, 36 (first batch; age range, 15–85 years) and 27 (second batch; age range, 23–85 years) patients with benign breast disease were also enrolled as disease controls (DCs). Additionally, a total of 14 (first batch; age range, 26–73 years) and 19 (second batch; age range, 28–70 years) healthy subjects were recruited as healthy controls (HCs). The present study was approved by the Ethics Committee of Huashan Hospital, Fudan University (Shanghai, China) and all patients or the guardian for the patient who was <18 years old provided written informed consent prior to enrollment.

Data documentation

The clinical data of patients with breast cancer, including age, menopause status, histological type, molecular subtype and tumor-node-metastasis (TNM) stage were recorded. The molecular subtype of each patient was determined according to the Chinese Anti-Cancer Association Breast Cancer Diagnosis and Treatment Guidelines and Standards (2021 edition) (23). The patients received the appropriate treatment based on disease stage, patient preferences and physician recommendations, which were not affected by the study. All treatments were also recorded.

Sample processing

A total of 4 ml PB was collected from each subject in an EDTA tube. Plasma was then isolated from each sample using Ficoll-Paque Plus Reagent (Cytiva) diluted with PBS at a ratio of 1:1, followed by centrifugation at 12,000 × g at 4°C for 15 min. Subsequently, bind-elute size exclusion chromatography columns (HiScreen Capto Core 700 column; Cytiva) connected to the ÄKTA Pure 25 chromatography system (Cytiva) were used to capture and purify exosomes from 1.5 ml plasma at room temperature. The columns were equilibrated with sterile PBS. The flow rate was 25 ml/min according to the manufacturer's instruction. Following exosome capture, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was carried out to assess the mRNA expression levels of ENAH and SEPT9 in the exosomes derived from the first batch of subjects (31 patients with breast cancer, 36 DCs and 14 HCs) and EGF, MMP-9 and CXCL8 in exosomes derived from the second batch of subjects (16 patients with breast cancer, 27 DCs and 19 HCs).

RT-qPCR

Total RNA was extracted from the exosomes using the RNeasy Micro Kit (Qiagen GmbH) and then reverse transcribed into cDNA using the ReverTra Ace® qPCR RT Kit (Toyobo Co., Ltd.). The conditions for reverse transcription comprised one cycle of 37°C for 15 min and 98°C for 5 min. Subsequently, qPCR was carried out using the KOD SYBR® qPCR Mix (Toyobo Co., Ltd.). The thermocycling conditions for qPCR comprised 1 cycle of 98°C for 2 min followed by 40 cycles of 98°C for 10 sec and 61°C for 30 sec. The relative mRNA expression levels were calculated by the 2−ΔΔCq method (24). The internal reference genes were β-actin for ENAH and SEPT9, and glyceraldehyde-3-phosphate dehydrogenase for EGF, MMP-9 and CXCL8. The primer sequences are listed in Table SI.

Statistical analysis

SPSS 26.0 (IBM Corp.) and GraphPad Prism 7.01 (GraphPad Software Inc.) software were used for statistical analysis and graph plotting, respectively. Differences among groups were compared by Kruskal-Wallis H rank-sum and Wilcoxon rank-sum tests. The ability of ENAH, SEPT9, EGF, MMP-9 or CXCL8 to distinguish individuals from different groups was assessed using receiver operating characteristic (ROC) curves. The normalized partial area under the curve (AUC) was calculated as previously described (25). Associations between exosomal genes and age, menopause, hormone receptor status, HER2 and Ki-67 were analyzed using Wilcoxon rank-sum tests. Associations between exosomal genes and histological type and molecular subtypes were analyzed using Kruskal-Wallis H rank-sum tests. Associations of exosomal genes with TNM stage were analyzed using Spearman's rank correlation test. Clinical characteristics between the two batches were compared using an unpaired Student's t-test for age and a Chi-square or Fisher's exact test for categorical data. P<0.05 was considered to indicate a statistically significant result.

Results

Characteristics of patients with breast cancer

The mean age of the patients with breast cancer was 54.6±11.5 years, including 2 (4.3%), 7 (14.9%), 10 (21.3%), 17 (36.2%) and 11 (23.4%) patients with triple-negative, luminal A, HER2-negative luminal B, HER2-positive luminal B and HER2-enriched breast cancer, respectively. In terms of tumor stage, 4 (8.5%), 13 (27.7%), 22 (46.8%), 6 (12.8%) and 2 (4.3%) patients were diagnosed with a TNM stage of 0, I, II, III and IV, respectively (Table I). Furthermore, comparative analyses revealed that there were no differences in the demographic and disease characteristics of patients with breast cancer between the two batches (all P>0.05; Table SII). In addition, the mean age of the DCs and HCs was 44.5±15.5 and 54.3±12.0 years, respectively (Table I).

Table I.

Clinical characteristics of the study participants.

Table I.

Clinical characteristics of the study participants.

ItemsHCs (n=33)DCs (n=63)Patients with breast cancer (n=47)
Age (years), mean±SD54.3±12.044.5±15.554.6±11.5
Menopause, n (%)
  No25 (75.8)23 (36.5)36 (76.6)
  Yes8 (24.2)40 (63.5)11 (23.4)
Histological type, n (%)
  Ductal carcinoma in situ--3 (6.4)
  Invasive ductal carcinoma--34 (72.3)
  Invasive lobular carcinoma--4 (8.5)
  Others--6 (12.8)
Molecular subtypes, n (%)
  Triple-negative--2 (4.3)
  Luminal A--7 (14.9)
  HER2-negative luminal B--10 (21.3)
  HER2-positive luminal B--17 (36.2)
  HER2-enriched--11 (23.4)
Hormone receptor status, n (%)
  ER negative and PR negative--13 (27.7)
  ER positive and/or PR positive--34 (72.3)
HER2, n (%)
  Negative--19 (40.4)
  Positive--28 (59.6)
Ki-67, n (%)
  <30%--34 (72.3)
  ≥30%--13 (27.7)
TNM stage, n (%)
  0--4 (8.5)
  I--13 (27.7)
  II--22 (46.8)
  III--6 (12.8)
  IV--2 (4.3)
Surgical type, n (%) 47 (100.0)
  Modified radical mastectomy--24 (51.1)
  Sentinel lymph node biopsy--18 (38.3)
  Radical mastectomy--15 (31.9)
  Breast-conserving surgery--5 (10.6)
Neoadjuvant therapy, n (%)--9 (19.1)
Adjuvant therapy, n (%)--44 (93.6)

[i] HCs, healthy controls; DCs, disease controls; SD, standard deviation; HER2, human epidermal growth factor receptor 2; ER, estrogen receptor; PR, progesterone receptor; TNM, tumor-node-metastasis.

Expression of exosomal ENAH, SEPT9, EGF, MMP-9 and CXCL8

The exosomal mRNA expression level of ENAH was the highest in patients with breast cancer, lower DCs and the lowest in HCs (P<0.001; Fig. 1A). Additionally, ROC curve analyses showed that exosomal ENAH exhibited the ability to discriminate between patients with breast cancer and the DCs (AUC, 0.841; Fig. 1B) and HCs (AUC, 0.859; Fig. 1C). However, it could not discriminate DCs from HCs (AUC, 0.523; Fig. 1D). By contrast, the mRNA expression levels of exosomal SEPT9 were lowest in patients with breast cancer, higher in DCs and the highest in HCs (P<0.001; Fig. 1E). ROC curve analyses revealed that exosomal SEPT9 was effectively able to differentiate patients with breast cancer from DCs (AUC, 0.717; Fig. 1F) and HCs (AUC, 0.830; Fig. 1G), but not DCs from HCs (AUC, 0.604; Fig. 1H). Furthermore, the exosomal mRNA expression level of EGF was the highest in patients with breast cancer, lower in DCs and the lowest in HCs (P=0.021; Fig. 2A). ROC curve analyses demonstrated that exosomal EGF failed to discriminate patients with breast cancer from DCs (AUC, 0.664; Fig. 2B). However, it showed an acceptable ability to differentiate between patients with breast cancer and HCs, with an AUC value of 0.776 (Fig. 2C), but not DCs from HCs (AUC, 0.607; Fig. 2D). Regarding the exosomal mRNA expression levels of MMP-9 and CXCL8, no differences were observed among the patients with breast cancer, DCs and HCs (both P>0.05; Fig. 2E and I). ROC curve analyses also revealed that exosomal MMP-9 and CXCL8 could not discriminate patients with breast cancer from DCs or HCs, or DCs from HCs (Fig. 2F-H and J-L).

Association of exosomal ENAH, SEPT9, EGF, MMP-9 and CXCL8 with the clinical characteristics of patients with breast cancer

Exosomal ENAH was differentially expressed among patients with different molecular subtypes of breast cancer (P=0.010). More specifically, its expression level was increased in patients with HER2-negative luminal B and HER2-enriched breast cancer and reduced in those with triple-negative, luminal A and HER2-positive luminal B breast cancer. Additionally, exosomal SEPT9 was not found to be associated with any of the clinical characteristics of patients with breast cancer (all P>0.05; Table II). Furthermore, the exosomal expression of MMP-9 was associated with a Ki-67 index of ≥30% (P=0.011), but not with other clinical characteristics of the patients with breast cancer (all P>0.05). Furthermore, the exosomal expression levels of EGF and CXCL8 were also not found to be associated with any of the clinical characteristics of the patients with breast cancer (all P>0.05; Table III).

Table II.

Association of exosomal ENAH and SEPT9 with the clinical characteristics of patients with breast cancer.

Table II.

Association of exosomal ENAH and SEPT9 with the clinical characteristics of patients with breast cancer.

Exosomal ENAH expressionaExosomal SEPT9 expressiona


ItemsMedian (IQR)Z/Χ2/ρ valueP-valueMedian (IQR)Z/Χ2/ρ valueP-value
Age (years) −0.4540.650 −0.1860.853
  <600.102 (0.035-0.128) 0.758 (0.437-0.976)
  ≥600.067 (0.001-0.133) 0.835 (0.232-1.395)
Menopause −0.7560.450 −0.0710.943
  No0.095 (0.006-0.126) 0.766 (0.437-1.079)
  Yes0.111 (0.074-0.129) 0.785 (0.293-1.197)
Histological type 2.7900.425 3.3530.340
  Ductal carcinoma in situ0.123 (0.104-NA) 1.197 (0.785-NA)
  Invasive ductal carcinoma0.074 (0.001-0.129) 0.763 (0.325-1.117)
  Invasive lobular carcinomaNA NA
  Others0.125 (0.031-0.139) 0.758 (0.682-0.818)
Molecular subtypes 13.1760.010 1.3860.847
  Triple-negative0.067 (0.000-NA) 0.956 (0.763-NA)
  Luminal A0.067 (0.001-0.085) 0.835 (0.607-1.256)
  HER2-negative luminal B0.125 (0.113-0.144) 0.758 (0.380-0.926)
  HER2-positive luminal B0.060 (0.001-0.103) 0.655 (0.335-0.976)
  HER2-enriched0.134 (0.090-0.145) 0.616 (0.284-1.939)
Hormone receptor status −1.7150.086 −0.2260.821
  ER negative and PR negative0.131 (0.047-0.140) 0.817 (0.334-1.687)
  ER positive and/or PR positive0.095 (0.001-0.123) 0.768 (0.429-0.979)
HER2 −0.3600.719 −0.6210.535
  Negative0.110 (0.034-0.130) 0.785 (0.588-1.133)
  Positive0.098 (0.017-0.129) 0.655 (0.317-1.201)
Ki-67 (%) −0.9930.321 −0.2480.804
  <300.095 (0.023-0.127) 0.763 (0.429-1.149)
  ≥300.118 (0.012-0.142) 0.802 (0.334-0.942)
TNM stage −0.0880.639 0.0070.970
  00.114 (0.026-0.140) 0.991 (0.691-2.225)
  I0.092 (0.025-0.121) 0.540 (0.214-0.898)
  II0.095 (0.034-0.129) 0.768 (0.445-1.133)
  III0.100 (0.001-NA) 0.763 (0.253-NA)
  IVNA NA

a Exosomal ENAH and SEPT9 were detected among the first batch patients with breast cancer (n=31). ENAH, enabled homolog; SEPT9, septin 9; IQR, interquartile range; HER2, human epidermal growth factor receptor 2; ER, estrogen receptor; PR, progesterone receptor; TNM, tumor-node-metastasis; NA, not applicable.

Table III.

Association of exosomal EGF, MMP-9 and CXCL8 with the clinical characteristics of patients with breast cancer.

Table III.

Association of exosomal EGF, MMP-9 and CXCL8 with the clinical characteristics of patients with breast cancer.

Exosomal EGF expressionaExosomal MMP-9 expressionaExosomal CXCL8 expressiona



ItemsMedian (IQR)Z/Χ2/ρ valueP-valueMedian (IQR)Z/Χ2/ρ valueP-valueMedian (IQR)Z/Χ2/ρ valueP-value
Age (years) −0.6230.533 −0.9630.336 −0.6230.533
  <600.092 (0.003-0.254) 0.003 (0.002-0.003) 0.092 (0.003-0.230)
  ≥600.144 (0.072-0.309) 0.002 (0.001-0.052) 0.186 (0.090-0.215)
Menopause −1.0910.275 −1.3340.182 −0.1210.903
  No0.145 (0.019-0.304) 0.003 (0.002-0.008) 0.136 (0.003-0.217)
  Yes0.073 (0.015-0.143) 0.002 (0.001-0.003) 0.114 (0.026-0.347)
Histological type 0.1810.913 3.2990.192 5.0000.082
  Ductal carcinoma in situNA NA NA
  Invasive ductal carcinoma0.092 (0.003-0.321) 0.003 (0.002-0.010) 0.102 (0.003-0.186)
  Invasive lobular carcinoma0.144 (0.142-NA) 0.001 (0.001-NA) 0.218 (0.212-NA)
  Others0.099 (0.053-NA) 0.003 (0.002-NA) 0.046 (0.000-NA)
Molecular subtypes 3.2870.349 2.5920.459 1.5220.677
  Triple-negativeNA NA NA
  Luminal A0.036 (0.003-NA) 0.006 (0.003-NA) 0.117 (0.048-NA)
  HER2-negative luminal B0.098 (0.015-0.155) 0.002 (0.001-0.003) 0.172 (0.032-0.370)
  HER2-positive luminal B0.145 (0.073-0.356) 0.003 (0.002-0.052) 0.179 (0.048-0.338)
  HER2-enriched0.160 (0.047-0.353) 0.002 (0.001-0.066) 0.003 (0.002-0.166)
Hormone receptor status −1.0760.282 −0.6230.533 −1.1900.234
  ER negative and PR negative0.160 (0.047-0.353) 0.002 (0.001-0.066) 0.003 (0.002-0.166)
  ER positive and/or PR positive0.142 (0.003-0.159) 0.003 (0.002-0.003) 0.179 (0.048-0.218)
HER2 −1.7350.083 −0.3250.745 −0.4340.664
  Negative0.061 (0.002-0.146) 0.002 (0.001-0.005) 0.156 (0.036-0.269)
  Positive0.153 (0.070-0.337) 0.003 (0.001-0.028) 0.097 (0.003-0.217)
Ki-67 (%) −0.7360.462 −2.5490.011 −0.7360.462
  <300.142 (0.053-0.159) 0.002 (0.001-0.003) 0.102 (0.002-0.212)
  ≥300.254 (0.002-0.421) 0.003 (0.003-0.115) 0.179 (0.003-0.347)
TNM stage −0.2480.354 0.0130.962 −0.2150.423
  0NA NA NA
  I0.159 (0.003-NA) 0.002 (0.001-NA) 0.230 (0.002-NA)
  II0.144 (0.036-0.320) 0.003 (0.002-0.055) 0.102 (0.026-0.182)
  III0.142 (0.002-NA) 0.001 (0.001-NA) 0.218 (0.001-NA)
  IVNA NA NA

a Exosomal EGF, MMP-9 and CXCL8 were detected among the second batch of patients with breast cancer (n=16). EGF, epidermal growth factor; MMP-9, matrix metalloproteinase-9; CXCL8, C-X-C motif chemokine ligand 8; IQR, interquartile range; HER2, human epidermal growth factor receptor 2; ER, estrogen receptor; PR, progesterone receptor; TNM, tumor-node-metastasis; NA, not applicable.

Discussion

Breast cancer screening is a currently focus of attention, since it can diagnose patients with breast cancer at an early stage of the disease, thus providing a satisfactory overall prognosis (6,26). Mammography is recommended for the screening of breast cancer in several countries. However, some subjects may be unwilling to undergo mammography due to concerns about radiation (27). Other screening modalities include ultrasound, magnetic resonance imaging and clinical breast examination. However, the above modalities may have one or more of the following limitations: Low sensitivity/specificity, increased cost and the potential influence of demographic characteristics including age and body weight on their effectiveness (28,29). Therefore, the exploration of novel screening modalities for breast cancer is of great importance. It has been recently reported that several RNAs and proteins exert a great ability in predicting the risk of breast cancer and, therefore, these molecules could be used in the early screening of breast cancer (3032). Among these biomarkers, exosomes and their contents are of great interest. Due to the robust bilayer lipid membrane of exosomes, their contents are protected from the surrounding environment and can therefore provide accurate information on the tumor (3335). Thus, exosomal contents could be considered as appropriate biomarkers for the early screening of breast cancer.

The dysregulation of ENAH, SEPT9, EGF, MMP-9 and CXCL8 in breast cancer tissues and/or cell lines is known to be of considerable importance. For example, a study used data from the ONCOMINE database to analyze the mRNA expression levels of ENAH in breast cancer tissues and the results showed that ENAH was upregulated in breast cancer tissues compared with normal tissues (36). Furthermore, another study revealed that a high level of SEPT9 methylation is present in breast cancer cell lines and tissues (37). Additionally, the dysregulation of EGF, MMP-9 and CXCL8 in breast cancer cell lines or tissues has also been previously reported (3840). However, to the best of our knowledge, the expression levels of the aforementioned genes in exosomes isolated from patients with breast cancer have not been previously investigated. The present study demonstrated that exosomal ENAH and EGF were notably upregulated, while exosomal SEPT9 was downregulated in patients with breast cancer. This finding suggests that high levels of ENAH and EGF as well as reduced levels of SEPT9 could facilitate the growth of breast cancer cells (12,14,16). Furthermore, breast cancer cells may encapsulate these genes into exosomes and release them into the circulatory system. This assumption is consistent with the enhanced exosomal levels of ENAH and EGF, and the reduced levels of exosomal SEPT9 observed in the current study. In addition, ROC curve analysis showed that exosomal ENAH exhibited good capacity for discriminating patients with breast cancer from DCs and HCs, whereas exosomal SEPT9 and EGF each had an acceptable capacity for this discrimination. These findings indicate the potential of these exosomal biomarkers in the early screening of breast cancer. A previous study demonstrated that ENAH was elevated in pancreatic cancer tissues compared with tissues from patients with pancreatitis or normal subjects (41). Additionally, another study revealed that the methylation of SEPT9 was increased in colorectal cancer tissues (42). Regarding MMP-9, a previous study showed that it was aberrantly expressed in osteosarcoma tissues, in which its expression was higher than that in paracancerous tissues (43). Furthermore, CXCL8 has been found to be significantly upregulated in prostate cancer tissues (44).

The results of the present study demonstrated that the exosomal levels of ENAH were partially associated with HER2-negative luminal B and HER2-enriched breast cancer A possible explanation for this could be that exosomal ENAH showed a tendency to associate with estrogen receptor (ER)- and progesterone (PR)-negative breast cancer, as well as with a Ki-67 index of ≥30%, although this tendency did not reach statistical significance. Based on the expression of ER, PR, HER2 and Ki-67, breast cancer is classified in different molecular subtypes, namely HER2-negative luminal B breast cancer, characterized by a lack of expression of PR and upregulated expression of Ki-67, and HER2-enriched breast cancer, characterized by the lack of PR and ER expression. Therefore, exosomal ENAH showed a tendency to correlate with the aforementioned breast cancer subtypes. The results of the current study also showed that exosomal MMP-9 was associated with a Ki-67 index of ≥30%. This could be due to the expression of Ki-67 reflecting the proliferation ability of breast cancer cells (45). Additionally, MMP-9 promotes the proliferation of breast cancer cells (18); therefore, it was also associated with a Ki-67 index of ≥30%.

However, the present study has some limitations. Firstly, the sample size was relatively small. Therefore, the association of the expression levels of exosomal ENAH, SEPT9, EGF, MMP-9 and CXCL8 with the risk of breast cancer should be further investigated using a larger sample size. Secondly, a validation cohort is required to verify the diagnostic value of exosomal ENAH, SEPT9 and EGF in the early screening of breast cancer. Thirdly, due to the single-center study design, there may be regional bias. Fourthly, the expression levels of exosomal ENAH and SEPT9 were detected in one batch of patients, while those of EGF, MMP-9 and CXCL8 were detected in a different batch of patients. However, the comparison of baseline characteristics revealed that the demographic and disease features were comparable between the two batches of patients, thus suggesting that there were no major confounding factors. Although the treatment strategy varied between batches, all samples were collected prior to treatment, i.e., before surgery or neoadjuvant therapy if the patients were due to receive it. Therefore, different treatment approaches could not significantly affect the main findings of the present study. Fifthly, the current study lacked follow-up, and thus the association between the expression levels of the aforementioned exosomal genes and the prognosis of patients with breast cancer requires investigation in further studies. Finally, further studies are also required to evaluate the value of the expression of other exosomal genes for the prediction of breast cancer risk.

In conclusion, the results of the present study suggest that the expression levels of exosomal ENAH, SEPT9 and EGF in blood possess the potential to identify patients with breast cancer. However, this potential was not observed for MMP-9 and CXCL8, possibly due to the small sample size. The results also indicate that detection of the exosomal levels of ENAH, SEPT9 and EGF in the blood could improve the early screening of breast cancer. However, further validation experiments are necessary. In addition, whether these exosomal genes could serve as potential indicators for the prognosis of breast cancer merits further investigation.

Supplementary Material

Supporting Data

Acknowledgements

Not applicable.

Funding

Funding: No funding was received.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors' contributions

QZ and SW substantially contributed to the conception and the design of the study. ZZ, HW and YJ were responsible for the acquisition and analysis of the data. CC, JB and JH contributed to interpretation of the data. FT, LY and LZ contributed to data interpretation and manuscript drafting. QZ, LY and SW confirm the authenticity of all the raw data. All authors read and approved the final version of the manuscript.

Ethics approval and consent to participate

The study was approved by Ethics Committee of Huashan Hospital, Fudan University (Shanghai, China). Each patient or guardian of the patient who was <18 years old signed a written informed consent form.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Glossary

Abbreviations

Abbreviations:

ENAH

enabled homolog

SEPT9

septin 9

EGF

epidermal growth factor

MMP-9

matrix metalloproteinase-9

CXCL8

C-X-C motif chemokine ligand 8

PB

peripheral blood

HCs

healthy controls

DCs

disease controls

TNM

tumor-node-metastasis

RT-qPCR

reverse transcription-quantitative polymerase chain reaction

GAPDH

glyceraldehyde-3-phosphate dehydrogenase

ROC

receiver operating characteristic

IQR

interquartile range

CI

confidence interval

AUC

area under the curve

HER2

human epidermal growth factor receptor 2

ER

estrogen receptor

PR

progesterone receptor

References

1 

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A and Bray F: Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 71:209–249. 2021. View Article : Google Scholar : PubMed/NCBI

2 

Smolarz B, Nowak AZ and Romanowicz H: Breast cancer-epidemiology, classification, pathogenesis and treatment (Review of Literature). Cancers (Basel). 14:25692022. View Article : Google Scholar : PubMed/NCBI

3 

Cao W, Chen HD, Yu YW, Li N and Chen WQ: Changing profiles of cancer burden worldwide and in China: A secondary analysis of the global cancer statistics 2020. Chin Med J (Engl). 134:783–791. 2021. View Article : Google Scholar : PubMed/NCBI

4 

Fan X, Zhang B, He Y, Zhou X, Zhang Y, Ma L, Li X and Wu J: Burden of disease due to cancer-China, 2000–2019. China CDC Wkly. 4:306–311. 2022. View Article : Google Scholar : PubMed/NCBI

5 

Mahanani MR, Valkov M, Agaeva A, Kaucher S, Pikalova LV, Grishchenko MY, Zhuikova LD, Jaehn P and Winkler V: Comparison of female breast cancer between Russia and Germany: A population-based study on time trends and stage at diagnosis. Cancer Epidemiol. 80:1022142022. View Article : Google Scholar : PubMed/NCBI

6 

Miller KD, Nogueira L, Devasia T, Mariotto AB, Yabroff KR, Jemal A, Kramer J and Siegel RL: Cancer treatment and survivorship statistics, 2022. CA Cancer J Clin. 72:409–436. 2022. View Article : Google Scholar : PubMed/NCBI

7 

Jani C, Salcicciol I, Rupal A, Al Omari O, Goodall R, Salciccioli JD, Marshall DC, Hanbury G, Singh H, Weissmann L and Shalhoub J: Trends in breast cancer mortality between 2001 and 2017: An observational study in the European Union and the United Kingdom. JCO Glob Oncol. 7:1682–1693. 2021. View Article : Google Scholar : PubMed/NCBI

8 

Yu W, Hurley J, Roberts D, Chakrabortty SK, Enderle D, Noerholm M, Breakefield XO and Skog JK: Exosome-based liquid biopsies in cancer: Opportunities and challenges. Ann Oncol. 32:466–477. 2021. View Article : Google Scholar : PubMed/NCBI

9 

Liu M, Mo F, Song X, He Y, Yuan Y, Yan J, Yang Y, Huang J and Zhang S: Exosomal hsa-miR-21-5p is a biomarker for breast cancer diagnosis. PeerJ. 9:e121472021. View Article : Google Scholar : PubMed/NCBI

10 

Wang X, Qian T, Bao S, Zhao H, Chen H, Xing Z, Li Y, Zhang M, Meng X, Wang C, et al: Circulating exosomal miR-363-5p inhibits lymph node metastasis by downregulating PDGFB and serves as a potential noninvasive biomarker for breast cancer. Mol Oncol. 15:2466–2479. 2021. View Article : Google Scholar : PubMed/NCBI

11 

Liu J, Peng X, Liu Y, Hao R, Zhao R, Zhang L, Zhao F, Liu Q, Liu Y and Qi Y: The diagnostic value of serum exosomal Has_circ_0000615 for breast cancer patients. Int J Gen Med. 14:4545–4554. 2021. View Article : Google Scholar : PubMed/NCBI

12 

Di Modugno F, DeMonte L, Balsamo M, Bronzi G, Nicotra MR, Alessio M, Jager E, Condeelis JS, Santoni A, Natali PG and Nisticò P: Molecular cloning of hMena (ENAH) and its splice variant hMena+11a: Epidermal growth factor increases their expression and stimulates hMena+11a phosphorylation in breast cancer cell lines. Cancer Res. 67:2657–2665. 2007. View Article : Google Scholar : PubMed/NCBI

13 

Ahuja N, Ashok C, Natua S, Pant D, Cherian A, Pandkar MR, Yadav P, Vishnu NSS, Mishra J, Samaiya A and Shukla S: Hypoxia-induced TGF-β-RBFOX2-ESRP1 axis regulates human MENA alternative splicing and promotes EMT in breast cancer. NAR Cancer. 2:zcaa0212020. View Article : Google Scholar : PubMed/NCBI

14 

Zeng Y, Cao Y, Liu L, Zhao J, Zhang T, Xiao L, Jia M, Tian Q, Yu H, Chen S and Cai Y: SEPT9_i1 regulates human breast cancer cell motility through cytoskeletal and RhoA/FAK signaling pathway regulation. Cell Death Dis. 10:7202019. View Article : Google Scholar : PubMed/NCBI

15 

Devlin L, Okletey J, Perkins G, Bowen JR, Nakos K, Montagna C and Spiliotis ET: Proteomic profiling of the oncogenic septin 9 reveals isoform-specific interactions in breast cancer cells. Proteomics. 21:e21001552021. View Article : Google Scholar : PubMed/NCBI

16 

Lu C, Zhao Y, Wang J, Shi W, Dong F, Xin Y, Zhao X and Liu C: Breast cancer cell-derived extracellular vesicles transfer miR-182-5p and promote breast carcinogenesis via the CMTM7/EGFR/AKT axis. Mol Med. 27:782021. View Article : Google Scholar : PubMed/NCBI

17 

Kavarthapu R, Anbazhagan R and Dufau ML: Crosstalk between PRLR and EGFR/HER2 signaling pathways in breast cancer. Cancers (Basel). 13:46852021. View Article : Google Scholar : PubMed/NCBI

18 

Hong OY, Jang HY, Lee YR, Jung SH, Youn HJ and Kim JS: Inhibition of cell invasion and migration by targeting matrix metalloproteinase-9 expression via sirtuin 6 silencing in human breast cancer cells. Sci Rep. 12:121252022. View Article : Google Scholar : PubMed/NCBI

19 

Cancemi P, Buttacavoli M, Roz E and Feo S: Expression of alpha-enolase (ENO1), Myc promoter-binding protein-1 (MBP-1) and matrix metalloproteinases (MMP-2 and MMP-9) reflect the nature and aggressiveness of breast tumors. Int J Mol Sci. 20:39522019. View Article : Google Scholar : PubMed/NCBI

20 

Mishra A, Suman KH, Nair N, Majeed J and Tripathi V: An updated review on the role of the CXCL8-CXCR1/2 axis in the progression and metastasis of breast cancer. Mol Biol Rep. 48:6551–6561. 2021. View Article : Google Scholar : PubMed/NCBI

21 

Ruffini PA: The CXCL8-CXCR1/2 axis as a therapeutic target in breast cancer stem-like cells. Front Oncol. 9:402019. View Article : Google Scholar : PubMed/NCBI

22 

Wang RX, Ji P, Gong Y, Shao ZM and Chen S: Value of CXCL8-CXCR1/2 axis in neoadjuvant chemotherapy for triple-negative breast cancer patients: A retrospective pilot study. Breast Cancer Res Treat. 181:561–570. 2020. View Article : Google Scholar : PubMed/NCBI

23 

Breast Cancer Committee of Chinese Anti-Cancer Association, . Chinese Anti-Cancer Association Breast Cancer Diagnosis and Treatment Guidelines and Standards (2021). China Oncology. 31:954–1040. 2021.

24 

Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) Method. Methods. 25:402–408. 2001. View Article : Google Scholar : PubMed/NCBI

25 

Han C, Bellone S, Siegel ER, Altwerger G, Menderes G, Bonazzoli E, Egawa-Takata T, Pettinella F, Bianchi A, Riccio F, et al: A novel multiple biomarker panel for the early detection of high-grade serous ovarian carcinoma. Gynecol Oncol. 149:585–591. 2018. View Article : Google Scholar : PubMed/NCBI

26 

Luo C, Wang L, Zhang Y, Lu M, Lu B, Cai J, Chen H and Dai M: Advances in breast cancer screening modalities and status of global screening programs. Chronic Dis Transl Med. 8:112–123. 2022.PubMed/NCBI

27 

Ren W, Chen M, Qiao Y and Zhao F: Global guidelines for breast cancer screening: A systematic review. Breast. 64:85–99. 2022. View Article : Google Scholar : PubMed/NCBI

28 

Ding R, Xiao Y, Mo M, Zheng Y, Jiang YZ and Shao ZM: Breast cancer screening and early diagnosis in Chinese women. Cancer Biol Med. 19:450–467. 2022. View Article : Google Scholar : PubMed/NCBI

29 

Mann RM, Hooley R, Barr RG and Moy L: Novel approaches to screening for breast cancer. Radiology. 297:266–285. 2020. View Article : Google Scholar : PubMed/NCBI

30 

Wang H, Shu L, Niu N, Zhao C, Lu S, Li Y, Wang H, Liu Y, Zou T, Zou J, et al: Novel lncRNAs with diagnostic or prognostic value screened out from breast cancer via bioinformatics analyses. PeerJ. 10:e136412022. View Article : Google Scholar : PubMed/NCBI

31 

Jia L, Li G, Ma N, Zhang A, Zhou Y, Ren L and Dong D: Soluble POSTN is a novel biomarker complementing CA153 and CEA for breast cancer diagnosis and metastasis prediction. BMC Cancer. 22:7602022. View Article : Google Scholar : PubMed/NCBI

32 

Veyssiere H, Bidet Y, Penault-Llorca F, Radosevic-Robin N and Durando X: Circulating proteins as predictive and prognostic biomarkers in breast cancer. Clin Proteomics. 19:252022. View Article : Google Scholar : PubMed/NCBI

33 

Na-Er A, Xu YY, Liu YH and Gan YJ: Upregulation of serum exosomal SUMO1P3 predicts unfavorable prognosis in triple negative breast cancer. Eur Rev Med Pharmacol Sci. 25:154–160. 2021.PubMed/NCBI

34 

Lakshmi S, Hughes TA and Priya S: Exosomes and exosomal RNAs in breast cancer: A status update. Eur J Cancer. 144:252–268. 2021. View Article : Google Scholar : PubMed/NCBI

35 

Zokaei E, Darbeheshti F and Rezaei N: Prospect of exosomal circular RNAs in breast cancer: Presents and future. Mol Biol Rep. 49:6997–7011. 2022. View Article : Google Scholar : PubMed/NCBI

36 

Li QL, Su YL, Zeng M and Shen WX: Enabled homolog shown to be a potential biomarker and prognostic indicator for breast cancer by bioinformatics analysis. Clin Invest Med. 41:E186–E195. 2019. View Article : Google Scholar : PubMed/NCBI

37 

Matsui S, Kagara N, Mishima C, Naoi Y, Shimoda M, Shimomura A, Shimazu K, Kim SJ and Noguchi S: Methylation of the SEPT9_v2 promoter as a novel marker for the detection of circulating tumor DNA in breast cancer patients. Oncol Rep. 36:2225–2235. 2016. View Article : Google Scholar : PubMed/NCBI

38 

Khambri D, Suyuthie HD, Hilbertina N, Yetti H and Purwanto DJ: Matrix metalloproteinase-9 as prognostic factor for the treatment of HER-2 enriched breast cancer. Asian Pac J Cancer Prev. 23:1013–1021. 2022. View Article : Google Scholar : PubMed/NCBI

39 

Yotsumoto F, Tokunaga E, Oki E, Maehara Y, Yamada H, Nakajima K, Nam SO, Miyata K, Koyanagi M, Doi K, et al: Molecular hierarchy of heparin-binding EGF-like growth factor-regulated angiogenesis in triple-negative breast cancer. Mol Cancer Res. 11:506–517. 2013. View Article : Google Scholar : PubMed/NCBI

40 

Fang QI, Wang X, Luo G, Yu M, Zhang X and Xu N: Increased CXCL8 expression is negatively correlated with the overall survival of patients with ER-Negative breast cancer. Anticancer Res. 37:4845–4852. 2017.PubMed/NCBI

41 

Melchionna R, Iapicca P, Di Modugno F, Trono P, Sperduti I, Fassan M, Cataldo I, Rusev BC, Lawlor RT, Diodoro MG, et al: The pattern of hMENA isoforms is regulated by TGF-β1 in pancreatic cancer and may predict patient outcome. Oncoimmunology. 5:e12215562016. View Article : Google Scholar : PubMed/NCBI

42 

Wasserkort R, Kalmar A, Valcz G, Spisak S, Krispin M, Toth K, Tulassay Z, Sledziewski AZ and Molnar B: Aberrant septin 9 DNA methylation in colorectal cancer is restricted to a single CpG island. BMC Cancer. 13:3982013. View Article : Google Scholar : PubMed/NCBI

43 

Bai C, Ma X, Wang X and Chen X: Correlation between pathological features and protein expressions of TfR1, VEGF and MMP-9 in patients with osteosarcoma. Am J Transl Res. 14:4562–4572. 2022.PubMed/NCBI

44 

Kong L, Qi R, Zhou G and Ding S: Correlation analysis of survivin, ING4, CXCL8 and VEGF expression in prostate cancer tissue. Am J Transl Res. 13:13784–13790. 2021.PubMed/NCBI

45 

Hacisalihoglu UP and Dogan MA: Expression of estrogen and progesterone receptors, HER2 protein and Ki-67 proliferation index in breast carcinoma in both tumor tissue and tissue microarray. Biotech Histochem. 97:298–305. 2022. View Article : Google Scholar : PubMed/NCBI

Related Articles

Journal Cover

December-2022
Volume 24 Issue 6

Print ISSN: 1792-1074
Online ISSN:1792-1082

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Zhang Z, Wang H, Jin Y, Chu C, Bai J, Huang J, Yang L, Tang F, Zou L, Wang S, Wang S, et al: Potential of blood exosomal ENAH, SEPT9, EGF, MMP‑9 and CXCL8 for the early screening of breast cancer. Oncol Lett 24: 460, 2022.
APA
Zhang, Z., Wang, H., Jin, Y., Chu, C., Bai, J., Huang, J. ... Zou, Q. (2022). Potential of blood exosomal ENAH, SEPT9, EGF, MMP‑9 and CXCL8 for the early screening of breast cancer. Oncology Letters, 24, 460. https://doi.org/10.3892/ol.2022.13580
MLA
Zhang, Z., Wang, H., Jin, Y., Chu, C., Bai, J., Huang, J., Yang, L., Tang, F., Zou, L., Wang, S., Zou, Q."Potential of blood exosomal ENAH, SEPT9, EGF, MMP‑9 and CXCL8 for the early screening of breast cancer". Oncology Letters 24.6 (2022): 460.
Chicago
Zhang, Z., Wang, H., Jin, Y., Chu, C., Bai, J., Huang, J., Yang, L., Tang, F., Zou, L., Wang, S., Zou, Q."Potential of blood exosomal ENAH, SEPT9, EGF, MMP‑9 and CXCL8 for the early screening of breast cancer". Oncology Letters 24, no. 6 (2022): 460. https://doi.org/10.3892/ol.2022.13580