Open Access

CXCR4 and CXCR3 are two distinct prognostic biomarkers in breast cancer: Database mining for CXCR family members

  • Authors:
    • Kaibo Guo
    • Guan Feng
    • Qingying Yan
    • Leitao Sun
    • Kai Zhang
    • Fengfei Shen
    • Minhe Shen
    • Shanming Ruan
  • View Affiliations

  • Published online on: October 30, 2019     https://doi.org/10.3892/mmr.2019.10784
  • Pages: 4791-4802
  • Copyright: © Guo et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

CXC chemokine receptors (CXCRs) and chemokines are involved in tissue development and homeostasis, including in cancer development and progression. To date, seven CXCRs have been identified. However, the expression of CXCRs and their influence on the occurrence and development of breast cancer (BC) requires further investigation. In the present study, mRNA expression levels of the seven CXCRs were compared between normal tissues and several cancer types using the Oncomine database. Highly expressed CXCRs were selected and the expression levels of these CXCRs were examined in different subtypes of BC using the Gene Expression‑Based Outcome for Breast Cancer database. Finally, the prognostic value of these CXCRs was examined using Kaplan‑Meier plotter. It was found that, compared with normal controls, transcripts of CXCR4 and CXCR3 were significantly overexpressed in BC samples compared with other CXCRs. Survival analysis showed that high expression of CXCR4 promoted the recurrence of BC but had no impact on overall survival (OS), while a high level of CXCR3 transcript expression was significantly associated with increased survival in patients with BC. With regards to different subtypes of BC, the present study revealed that high CXCR4 transcript expression was significantly associated with both longer relapse‑free survival and OS only in basal‑like BC. Furthermore, CXCR4 promoted chemosensitivity in patients with basal‑like BC and induced resistance against endocrine therapy for patients with luminal A BC. Thus, CXCR4 and CXCR3 are two distinct prognostic biomarkers and further studies are required.

Introduction

In 2018, breast cancer (BC) was expected to account for 30% of all new cancer diagnoses in women, and remains the principal cause of mortality from cancer in women worldwide (1). Recently, emphasis has been on the tumorigenesis of the immune system and immunotherapy for BC (2).

Chemokines, known as chemotactic cytokines, are a family of small molecular weight proteins (6–14 kDa) of the immune system, which bind to G protein-coupled receptors and participate in tissue maintenance and development, and in pathological conditions. Chemokines can be divided into four types according to their structural differences: CC, CXC, XC, and CX3C (3). Increasing evidence shows that CXCRs and their ligands affect some cancer-associated processes, including tumor cell activation, proliferation, invasion and migration (4,5).

CXCR1-CXCR7 have been identified (6). CXCR1/2 share ~76% sequence homology and bind to CXC ligand 8 (CXCL8) with similar affinities (79). CXCR1/2 and CXCL8 play important roles in the initiation and transfer of inflammatory mediators, as well as in the related tumor growth and metastasis (10). The CXCL9, −10, −11/CXCR3 axis contributes to tumor suppression by regulating immune cell development, differentiation and activation through paracrine signaling. However, the axis also promotes tumor progression and metastasis through autocrine signaling (11). CXCR4, which is widely expressed on the surface of epithelial and endothelial cells (12), is activated by CXCL12. This generates signals for a number of processes leading to tissue remodeling, including the homeostasis and development of normal tissues, hemopoiesis and angiogenesis. These roles make CXCR4 an important player in tumorigenesis (13). CXCR5 is specifically expressed in Burkitt lymphoma and lymphoid tissues, and is important for B cell migration through its binding to CXCL13 (14). It was reported that increased CXCR5 expression may result in increased survival and migration of MCF-7 BC cells that lack functional cellular tumor antigen p53 (TP53) (15). CXCR6-positive cells are cancer stem cells that can generate tumors through the process of self-renewal and their ability to differentiate into multiple cell types, which may also play a role in the mechanism of CXCR6 in tumor progression (16). CXCR7 is also expressed in different types of cancer and on tumor-associated vasculature. Emerging evidence also reveals its participation in metastasis and tumor progression (16).

Individual CXCRs have discrete roles in cancer development and progression. Nevertheless, the contributions of distinct CXCRs to BC tumorigenesis need to be explored. Thus, in the present study, large databases were mined for transcription expression information about CXCR family members in BC and normal tissues. Finally, the expression levels of CXCR family members were analyzed in diverse subtypes of BC and the prognostic value of CXCR family members in BC was assessed.

Materials and methods

Oncomine database analysis

The transcript expression levels of different CXCRs in a variety of cancers were analyzed using the publicly available cancer microarray database Oncomine (http://www.oncomine.org), which contains numerous datasets, including The Cancer Genome Atlas (TCGA) dataset. In the present study, the thresholds were set as follows: Data type, mRNA; gene rank, all; fold change, 2; P-value, 0.01. The differences in expression between cancer specimens and normal control datasets for CXCR family members were compared.

Gene expression-based outcome for breast cancer (GOBO) database analysis

The transcript levels of specific CXCRs in BC subtypes were analyzed using the GOBO database (http://co.bmc.lu.se/gobo). The GOBO database contains gene expression data about 1,881 BC samples and 51 BC cell lines from experiments conducted using Affymetrix microarrays (17).

Survival analysis using the Kaplan-Meier (KM) plotter

The KM plotter tool (http://kmplot.com/analysis/) can be used to evaluate the influence of the expression of 54,675 genes on survival in 10,461 cancer samples, including relapse-free survival (RFS) and overall survival (OS), to determine the prognostic values of CXCRs in 5,143 BC patients.

The effects of specific CXCRs on the prognosis of BC were studied, according to the following criteria: All patients with BC; the four molecular subtypes of BC, according to the 2013 St. Gallen criteria (18), were basal-like [estrogen receptor (ER) and progesterone receptor (PR) absent, human epidermal growth factor receptor-2 (HER2) negative], luminal A [ER and PR positive, HER2 negative, Ki-67 ‘low’ (<14%)], luminal B [ER positive, HER2 negative and at least one of the following: Ki-67 ‘high’ (≥20%), PR ‘negative or low’ (<20%) or ER positive, HER2 over-expressed or amplified, any Ki-67, any PR], HER2 (HER2 over-expressed or amplified, ER and PR absent); other characteristic molecular markers; related optimal treatment for different BC molecular subtypes, for example, basal-like BC with chemotherapy, luminal A BC with endocrine therapy and luminal B BC with both chemotherapy and endocrine therapy. The results are presented using KM curves, with the hazard ratio (HR) with 95% confidence intervals (95% CI) and the P-value for the log-rank test displayed.

Results

CXCR4 and CXCR3 are significantly overexpressed in BC

To date, it has been determined that there are seven CXCR family members expressed in a variety of human cancer types (Fig. 1). Utilizing the Oncomine database for gene expression analysis in BC, 15 out of 50 analyses met the threshold for CXCR4 in 9 out of 13 datasets, while 6 out of 43 analyses met the threshold for CXCR3 in 5 out of 10 datasets. No fold change >2 was found between BC samples and normal tissues for the transcript expression of CXCR1 (fold change=1.074; P=0.163; Fig. 2A), CXCR2 (fold change=−1.095; P=0.795; Fig. 2B), CXCR5 (fold change=1.119; P=1.87×10−4; Fig. 2G), CXCR6 (fold change=1.713; P=7.19×105; Fig. 2H) and CXCR7 (fold change=−2.448; P=1.000; Fig. 2I).

The analysis showed that the CXCR3 transcript was significantly elevated in BC samples compared with normal tissues. The CXCR3 transcript level was 2.200-fold (P=1.52×10−9) higher in BC samples in a large-sample dataset from TCGA database (Fig. 2C). Similarly, in a previous study by Curtis et al (19), CXCR3 was elevated by 2.857-fold (P=4.20×10−11) in BC compared with normal samples (Fig. 2D).

The transcript level of CXCR4 was 2.079-fold (P=2.69×10−10) higher in BC compared with normal samples in a 593-sample dataset from TCGA database (Fig. 2E). Furthermore, in a 59 sample dataset from a previous study by Finak et al (20), CXCR4 mRNA expression was increased by 7.230-fold (P=8.95×10−19) in BC tissues compared with normal samples (Fig. 2F).

In different breast cancer cell lines, the Neve (21) expression and intensity of CXCR3 and CXCR4 differ (Figs. 3E and 4E), which may provide a reference to the selection of cell lines for basic experiments.

Expression of CXCR4 and CXCR3 in different molecular subtypes of BC

In the present study, CXCR4 and CXCR3 were identified as being overexpressed in BC. To further explore the expression of CXCR4 and CXCR3, their expression levels were analyzed in different molecular subtypes of BC. The dataset from a previous study by Farmer et al (22) revealed that CXCR4 was increased by 1.496-fold (P=5.75×10−4) in basal-like BC samples compared to luminal-like BC samples (Fig. 3A), while CXCR3 showed no significant difference between these two subtypes of BC (P=0.18; Fig. 4A).

Basal-like subtype can be classified as basal A and basal B. In GOBO analysis, CXCR4 expression in luminal-like BC was statistically higher (P=0.01784) than in the basal A or basal B subtypes of BC, and the basal-like subtype of BC expressed higher levels of CXCR4 (P<0.00001) than in the luminal A or luminal B subtype (Fig. 3B-D). The hormone receptor sensitive subtype of BC was not significantly different (P=0.12853) than the triple negative BC (TNBC) or HER2 subtypes in terms of CXCR4 expression (Fig. 3D). But, CXCR3 showed no significant difference in expression among the different molecular subtypes of BC (Fig. 4B-D).

CXCR4 expression predicts better survival in patients with ER-negative/TP53-mutated basal-like BC, in patients with basal-like BC treated with chemotherapy and in patients with luminal A BC not treated with endocrine therapy

The prognostic value of CXCR4 in BC was evaluated and indicated that high expression of CXCR4 was significantly associated with a poorer RFS (HR=1.18; P=0.0028) in all patients with BC (Fig. 5A). In Fig. 6A, a high CXCR4 transcript level was not significantly correlated with better OS (HR=1.01; P=0.9) in all patients with BC.

Subtype analysis showed that a high level of CXCR4 transcript expression was positively correlated with a longer RFS in both TP53-mutated (HR=0.5; P=0.0048) and basal-like BC (HR=0.77; P=0.043), while no statistical significance was found in TP53 wild-type or other molecular subtypes of BC (Fig. 5B-F and G). Similarly, the analysis also revealed that high transcript levels of CXCR4 were statistically correlated with better OS in patients with basal-like BC (HR=0.52; P=0.01) and in ER-negative BC (HR=0.65; P=0.034; Fig. 6B-F and G).

High CXCR4 mRNA expression was statistically associated with a better RFS (HR=0.42; P=0.00095) and OS (HR=0.4; P=0.035) in patients with basal-like BC treated with chemotherapy (Figs. 5H and I, and 6H and I). However, high expression of CXCR4 was significantly correlated with a poorer RFS (HR=1.44; P=0.045) in patients with luminal A BC treated with endocrine therapy (Fig. 5J and K).

High CXCR3 mRNA expression is correlated with a longer survival in patients with TP53-mutated/basal-like BC

High CXCR3 mRNA expression was statistically correlated with a better RFS (HR=0.74; P=9.7×10−8) and OS (HR=0.71; P=0.0015) in all patients with BC (Figs. 7A and 8A). Subtype analysis also showed that high CXCR3 mRNA expression was significantly associated with a longer RFS (HR=0.55; P=2.6×10−6) and OS (HR=0.51; P=0.0073) in basal-like BC (Figs. 7B and 8B). Consistently, patients with mutated TP53 and with high levels of CXCR3 transcript expression were found to have longer RFS (HR=0.46; P=0.0014) and OS (HR=0.43; P=0.032) (Figs. 7G and I, and 8J and K). However, high levels of CXCR3 transcript had a different effect on RFS and OS for some characteristic markers. The analysis predicted a better RFS in patients with luminal A BC (HR=0.8; P=0.01) and luminal B BC (HR=0.7; P=0.00024; Fig. 7C-F and I), as well as a longer OS in patients with ER-negative BC (HR=0.59; P=0.0078) and lymph node positive BC (HR=0.66; P=0.04; Fig. 8C-I).

Discussion

In the present study, the expression of CXCR family members was examined in different tumors, and it was indicated that CXCR4 and CXCR3 were highly expressed in BC. Subsequent analyses were performed to determine whether a correlation was present between the expression of CXCR4 and CXCR3 in the different molecular subtypes of BC, and the survival rates associated with their expression. The results indicated that the mRNA expression of CXCR4 was statistically higher in patients with basal-like BC than in other subtypes, which is consistent with a previous report (23), and may explain why basal-like BC has a poorer prognosis than other subtypes. Survival analysis showed that high CXCR4 mRNA expression in BC promoted the recurrence of BC, but did not have an impact on OS. There are many confounding factors influencing OS, including non-cancer-related mortality and participation in clinical trials. Two previous meta-analyses (24,25) demonstrated that low CXCR4 mRNA expression in patients with BC is associated with better survival, including progression-free survival, disease-free survival and OS. In the present study, it was found that the impact of low CXCR4 mRNA expression on RFS is consistent with these previous studies (24,25), while the results showed no difference in OS. The heterogeneity in OS between the combined meta-analysis studies is high (I2=70% and P<0.00001; I2=84.2% and P<0.001) (24,25). There is a discrepancy in the OS rates among the present study and previous studies (24,25). Therefore, larger sample-sizes and high-quality trials are needed to show significance. In the present study, CXCR4 was found to be involved in BC tumorigenesis and to act as a prognostic biomarker for BC, based on its high expression and correlation with survival.

A stratified analysis revealed that high CXCR4 levels in basal-like BC predicted a good clinical outcome, both in terms of RFS and OS. Basal-like BC accounts for >70% of TNBC cases. Previous studies using small-sample sizes found the opposite result and support a negative role of CXCR4 in TNBC (26,27) CXCR4 is thought to play an important role in promoting the proliferation, recurrence and metastasis of BC, and may contribute to an adverse prognosis (28). However, a recent study reported that CXCR4 inhibitors were not efficient at inhibiting the growth of TNBC and even promoted the metastatic spread in 25% of cases (29). Therefore, this previous study indirectly supports the hypothesis that high CXCR4 expression predicts a favorable prognosis in TNBC. High CXCR4 mRNA expression does not always promote migration. For example, Ierano et al (30) found that histone deacetylase inhibitors induced CXCR4 mRNA expression but antagonized CXCR4-mediated migration by inhibiting CXCR4 protein. In addition, the present study revealed that, as in patients with basal-like BC, high expression of CXCR4 predicted a better RFS and OS in patients with ER-negative and TP53-mutated BC, respectively. This may be because an ER-negative status and TP53 mutation are features of TNBC (31). However, not all basal-like BC is TNBC (32), and as such, there may be discrepancies in the comparison between previous studies and the present study. Thus, more studies are required to clarify the relationship between CXCR4 expression and basal-like BC (or TNBC), and to understand the underlying molecular mechanism.

Next, the relationship between CXCR4 expression in different subtypes of BC was examined. Patients with basal-like BC are predominantly treated with chemotherapy. The results of the present study indicated that patients with basal-like BC and with high CXCR4 expression after chemotherapy have a more favorable prognosis, indicating that high expression of CXCR4 may increase the sensitivity of chemotherapy in basal-like BC. At present, few studies have reported on the relationship between the expression level of CXCR4 and the efficacy of chemotherapy, and these studies have used animal models or cell lines. For example, researchers found that CXCR4 induces chemoresistance in acute myeloid leukemia cells (OCI-AML3) and in colon cancer cells (HT-29 and SW480) (33,34). Furthermore, Liang et al (35) reported that the silencing of CXCR4 sensitized TNBC cells to cisplatin. However, chemotherapy for basal-like BC typically consists of paclitaxel and anthracyclines. Another previous study showed that patients with BC have decreased expression of CXCR4 and HER2 after neoadjuvant chemotherapy, indicating that these two genes may be a part of the mechanism of chemotherapy in BC (36). These previous studies may not support the results of the present study; therefore, more clinical trials are required to elucidate the role of CXCR4 in the efficacy of different chemotherapy regimens in basal-like BC. Furthermore, more experiments are required to understand the underlying molecular mechanism. To the best of our knowledge, the present study was the first to show that patients with luminal A BC and with high levels of CXCR4 expression after endocrine therapy have a shorter RFS than those with a low level of CXCR4 expression. Therefore, the present study indicated that CXCR4 may be a cause of resistance to endocrine therapy. Rhodes et al (37) found that the effects of CXCR4 overexpression were correlated with stromal cell-derived factor-1-mediated activation of downstream signaling through ERK1/2 and p38 MAPK. CXCR4 overexpression was also associated with increased ER-mediated gene expression, indicating that increased CXCR4 signaling is sufficient to drive ER-positive breast cancer to a metastatic and endocrine therapy-resistant phenotype through enhanced MAPK signaling. As patients with luminal A BC are usually only treated with adjuvant endocrine therapy (38), the efficacy of treatment can be predicted using CXCR4 expression.

The number of studies about CXCR3 in BC is fewer than that for CXCR4. CXCR3 has three isoforms, CXCR3-A, CXCR3-B and CXCR3-alt. CXCR3-A and CXCR3-B are the predominant isoforms and have different roles in BC; signaling through CXCR3-A promotes tumor growth while CXCR3-B prevents cancer cell proliferation (39). A previous study found that CXCR3 inhibition is effective in both BC and host compartments (40), while another previous study revealed that CXCR3 deficiency induced cancer development by promoting macrophage M2 polarization in a murine BC model (41). Thus, CXCR3 has multifaceted roles; it mediates the recruitment of tumor-infiltrating lymphocytes into the cancer microenvironment, resulting in a favorable clinical outcome by inhibiting tumor development and metastasis, and high expression of CXCR3 can promote tumor cell proliferation, migration and invasion, contributing to poor survival rates for patients (42). In the present study, it was found that CXCR3 is a favorable factor in several subtypes of BC, this is especially the case in basal-like BC.

In conclusion, CXCR4 and CXCR3 are significantly highly expressed in BC in comparison with normal samples. CXCR4 was found to be an adverse prognostic factor in BC; however, for basal-like BC, CXCR4 predicted a better prognosis. CXCR3 was found to be a favorable predictive factor in patients with BC. Furthermore, CXCR4 promoted chemosensitivity in patients with basal-like BC and induced resistance to endocrine therapy in patients with luminal A BC.

Acknowledgements

Not applicable.

Funding

The present study was supported by the Program for the Cultivation of Youth talents in China Association of Chinese Medicine (SR; grant no. QNRC2-C08; http://www.cacm.org.cn/), the Zhejiang Provincial Program for the Cultivation of High-Level Innovative Health Talents (SR; grant no. 2015-43; http://www.zjwjw.gov.cn/) and the Zhejiang Provincial Program for the Cultivation of the Young and Middle-Aged Academic Leaders in Colleges and Universities (SR; grant no. 2017-248; http://www.zjedu.gov.cn/).

Availability of data and materials

The datasets generated and analyzed during the current study are available in the Oncomine database (http://www.oncomine.org), the GOBO database (http://co.bmc.lu.se/gobo) and the KM plotter tool (http://kmplot.com/analysis/).

Authors' contributions

SR, KG and MS contributed to the study design. KZ and FS conducted the data collection. QY and LS performed the statistical analysis. KG and GF interpreted the data. KG, SR and GF prepared the manuscript. KG and GF performed the literature search. SR and MS were responsible for funds collection.

Ethics approval and consent to participate

Not applicable.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References

1 

Siegel RL, Miller KD and Jemal A: Cancer statistics, 2018. CA Cancer J Clin. 68:7–30. 2018. View Article : Google Scholar : PubMed/NCBI

2 

Nakasone ES, Hurvitz SA and McCann KE: Harnessing the immune system in the battle against breast cancer. Drugs Context. 7:2125202018. View Article : Google Scholar : PubMed/NCBI

3 

Balkwill FR: The chemokine system and cancer. J Pathol. 226:148–157. 2012. View Article : Google Scholar : PubMed/NCBI

4 

Zlotnik A, Burkhardt AM and Homey B: Homeostatic chemokine receptors and organ-specific metastasis. Nat Rev Immunol. 11:597–606. 2011. View Article : Google Scholar : PubMed/NCBI

5 

Zhu Q, Han X, Peng J, Qin H and Wang Y: The role of CXC chemokines and their receptors in the progression and treatment of tumors. J Mol Histol. 43:699–713. 2012. View Article : Google Scholar : PubMed/NCBI

6 

Vandercappellen J, Van Damme J and Struyf S: The role of CXC chemokines and their receptors in cancer. Cancer Lett. 267:226–244. 2008. View Article : Google Scholar : PubMed/NCBI

7 

Holmes WE, Lee J, Kuang WJ, Rice GC and Wood WI: Structure and functional expression of a human interleukin-8 receptor. Science. 253:1278–1280. 1991. View Article : Google Scholar : PubMed/NCBI

8 

Murphy PM and Tiffany HL: Cloning of complementary DNA encoding a functional human interleukin-8 receptor. Science. 253:1280–1283. 1991. View Article : Google Scholar : PubMed/NCBI

9 

Kunsch C and Rosen CA: NF-kappa B subunit-specific regulation of the interleukin-8 promoter. Mol Cell Biol. 13:6137–6146. 1993. View Article : Google Scholar : PubMed/NCBI

10 

Ha H, Debnath B and Neamati N: Role of the CXCL8-CXCR1/2 axis in cancer and inflammatory diseases. Theranostics. 7:1543–1588. 2017. View Article : Google Scholar : PubMed/NCBI

11 

Tokunaga R, Zhang W, Naseem M, Puccini A, Berger MD, Soni S, McSkane M, Baba H and Lenz HJ: CXCL9, CXCL10, CXCL11/CXCR3 axis for immune activation-A target for novel cancer therapy. Cancer Treat Rev. 63:40–47. 2018. View Article : Google Scholar : PubMed/NCBI

12 

Gupta SK, Lysko PG, Pillarisetti K, Ohlstein E and Stadel JM: Chemokine receptors in human endothelial cells. Functional expression of CXCR4 and its transcriptional regulation by inflammatory cytokines. J Biol Chem. 273:4282–4287. 1998. View Article : Google Scholar : PubMed/NCBI

13 

Coke CJ, Scarlett KA, Chetram MA, Jones KJ, Sandifer BJ, Davis AS, Marcus AI and Hinton CV: Simultaneous activation of induced heterodimerization between CXCR4 chemokine receptor and cannabinoid receptor 2 (CB2) reveals a mechanism for regulation of tumor progression. J Biol Chem. 291:9991–10005. 2016. View Article : Google Scholar : PubMed/NCBI

14 

Forster R, Mattis AE, Kremmer E, Wolf E, Brem G and Lipp M: A putative chemokine receptor, BLR1, directs B cell migration to defined lymphoid organs and specific anatomic compartments of the spleen. Cell. 87:1037–1047. 1996. View Article : Google Scholar : PubMed/NCBI

15 

Mitkin NA, Hook CD, Schwartz AM, Biswas S, Kochetkov DV, Muratova AM, Afanasyeva MA, Kravchenko JE, Bhattacharyya A and Kuprash DV: p53-dependent expression of CXCR5 chemokine receptor in MCF-7 breast cancer cells. Sci Rep. 5:93302015. View Article : Google Scholar : PubMed/NCBI

16 

Szpakowska M, Meyrath M, Reynders N, Counson M, Hanson J, Steyaert J and Chevigné A: Mutational analysis of the extracellular disulphide bridges of the atypical chemokine receptor ACKR3/CXCR7 uncovers multiple binding and activation modes for its chemokine and endogenous non-chemokine agonists. Biochem Pharmacol. 153:299–309. 2018. View Article : Google Scholar : PubMed/NCBI

17 

Ringner M, Fredlund E, Hakkinen J, Borg A and Staaf J: GOBO: Gene expression-based outcome for breast cancer online. PLoS One. 6:e179112011. View Article : Google Scholar : PubMed/NCBI

18 

Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thurlimann B and Senn HJ; Panel members, : Personalizing the treatment of women with early breast cancer: Highlights of the St Gallen international expert consensus on the primary therapy of early breast cancer 2013. Ann Oncol. 24:2206–2223. 2013. View Article : Google Scholar : PubMed/NCBI

19 

Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, Speed D, Lynch AG, Samarajiwa S, Yuan Y, et al: The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 486:346–352. 2012. View Article : Google Scholar : PubMed/NCBI

20 

Finak G, Bertos N, Pepin F, Sadekova S, Souleimanova M, Zhao H, Chen H, Omeroglu G, Meterissian S, Omeroglu A, et al: Stromal gene expression predicts clinical outcome in breast cancer. Nat Med. 14:518–527. 2008. View Article : Google Scholar : PubMed/NCBI

21 

Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, Clark L, Bayani N, Coppe JP, Tong F, et al: A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell. 10:515–527. 2006. View Article : Google Scholar : PubMed/NCBI

22 

Farmer P, Bonnefoi H, Becette V, Tubiana-Hulin M, Fumoleau P, Larsimont D, Macgrogan G, Bergh J, Cameron D, Goldstein D, et al: Identification of molecular apocrine breast tumours by microarray analysis. Oncogene. 24:4660–4671. 2005. View Article : Google Scholar : PubMed/NCBI

23 

Zhang M, Liu HX, Teng XD, Wang HB, Cui J, Jia SS, Gu XY and Li ZG: The differences in CXCR4 protein expression are significant for the five molecular subtypes of breast cancer. Ultrastruct Pathol. 36:381–386. 2012. View Article : Google Scholar : PubMed/NCBI

24 

Xu TP, Shen H, Liu LX and Shu YQ: The impact of chemokine receptor CXCR4 on breast cancer prognosis: A meta-analysis. Cancer Epidemiol. 37:725–731. 2013. View Article : Google Scholar : PubMed/NCBI

25 

Wang F, Li S, Zhao Y, Yang K, Chen M, Niu H, Yang J, Luo Y, Tang W and Sheng M: Predictive role of the overexpression for CXCR4, C-Met, and VEGF-C among breast cancer patients: A meta-analysis. Breast. 28:45–53. 2016. View Article : Google Scholar : PubMed/NCBI

26 

Chen HW, Du CW, Wei XL, Khoo US and Zhang GJ: Cytoplasmic CXCR4 high-expression exhibits distinct poor clinicopathological characteristics and predicts poor prognosis in triple-negative breast cancer. Curr Mol Med. 13:410–416. 2013. View Article : Google Scholar : PubMed/NCBI

27 

Chu QD, Panu L, Holm NT, Li BD, Johnson LW and Zhang S: High chemokine receptor CXCR4 level in triple negative breast cancer specimens predicts poor clinical outcome. J Surg Res. 159:689–695. 2010. View Article : Google Scholar : PubMed/NCBI

28 

Dayer R, Babashah S, Jamshidi S and Sadeghizadeh M: Upregulation of CXC chemokine receptor 4-CXC chemokine ligand 12 axis ininvasive breast carcinoma: A potent biomarker predicting lymph node metastasis. J Cancer Res Ther. 14:345–350. 2018.PubMed/NCBI

29 

Lefort S, Thuleau A, Kieffer Y, Sirven P, Bieche I, Marangoni E, Vincent-Salomon A and Mechta-Grigoriou F: CXCR4 inhibitors could benefit to HER2 but not to triple-negative breast cancer patients. Oncogene. 36:1211–1222. 2017. View Article : Google Scholar : PubMed/NCBI

30 

Ierano C, Basseville A, To KK, Zhan Z, Robey RW, Wilkerson J, Bates SE and Scala S: Histone deacetylase inhibitors induce CXCR4 mRNA but antagonize CXCR4 migration. Cancer Biol Ther. 14:175–183. 2013. View Article : Google Scholar : PubMed/NCBI

31 

Duffy MJ, Synnott NC and Crown J: Mutant p53 in breast cancer: Potential as a therapeutic target and biomarker. Breast Cancer Res Treat. 170:213–219. 2018. View Article : Google Scholar : PubMed/NCBI

32 

Rakha EA, Elsheikh SE, Aleskandarany MA, Habashi HO, Green AR, Powe DG, El-Sayed ME, Benhasouna A, Brunet JS, Akslen LA, et al: Triple-negative breast cancer: Distinguishing between basal and nonbasal subtypes. Clin Cancer Res. 15:2302–2310. 2009. View Article : Google Scholar : PubMed/NCBI

33 

Chen Y, Jacamo R, Konopleva M, Garzon R, Croce C and Andreeff M: CXCR4 downregulation of let-7a drives chemoresistance in acute myeloid leukemia. J Clin Invest. 123:2395–2407. 2013. View Article : Google Scholar : PubMed/NCBI

34 

Heckmann D, Maier P, Laufs S, Wenz F, Zeller WJ, Fruehauf S and Allgayer H: CXCR4 expression and treatment with SDF-1α or plerixafor modulate proliferation and chemosensitivity of colon cancer cells. Transl Oncol. 6:124–132. 2013. View Article : Google Scholar : PubMed/NCBI

35 

Liang S, Peng X, Li X, Yang P, Xie L, Li Y, Du C and Zhang G: Silencing of CXCR4 sensitizes triple-negative breast cancer cells to cisplatin. Oncotarget. 6:1020–1030. 2015. View Article : Google Scholar : PubMed/NCBI

36 

Yang SX, Loo WT, Chow LW, Yang XH, Zhan Y, Fan LJ, Zhang F, Chen L, Wang QL, Xiao HL, et al: Decreased expression of C-erbB-2 and CXCR4 in breast cancer after primary chemotherapy. J Transl Med. 10 (Suppl 1):S32012. View Article : Google Scholar : PubMed/NCBI

37 

Rhodes LV, Short SP, Neel NF, Salvo VA, Zhu Y, Elliott S, Wei Y, Yu D, Sun M, Muir SE, et al: Cytokine receptor CXCR4 mediates estrogen-independent tumorigenesis, metastasis, and resistance to endocrine therapy in human breast cancer. Cancer Res. 71:603–613. 2011. View Article : Google Scholar : PubMed/NCBI

38 

Park S, Lee SK, Paik HJ, Ryu JM, Kim I, Bae SY, Yu J, Kim SW, Lee JE and Nam SJ: Adjuvant endocrine therapy alone in patients with node-positive, luminal A type breast cancer. Medicine. 96:e67772017. View Article : Google Scholar : PubMed/NCBI

39 

Ma B, Khazali A and Wells A: CXCR3 in carcinoma progression. Histol Histopathol. 30:781–792. 2015.PubMed/NCBI

40 

Zhu G, Yan HH, Pang Y, Jian J, Achyut BR, Liang X, Weiss JM, Wiltrout RH, Hollander MC and Yang L: CXCR3 as a molecular target in breast cancer metastasis: Inhibition of tumor cell migration and promotion of host anti-tumor immunity. Oncotarget. 6:43408–43419. 2015. View Article : Google Scholar : PubMed/NCBI

41 

Oghumu S, Varikuti S, Terrazas C, Kotov D, Nasser MW, Powell CA, Ganju RK and Satoskar AR: CXCR3 deficiency enhances tumor progression by promoting macrophage M2 polarization in a murine breast cancer model. Immunology. 143:109–119. 2014. View Article : Google Scholar : PubMed/NCBI

42 

Bronger H, Karge A, Dreyer T, Zech D, Kraeft S, Avril S, Kiechle M and Schmitt M: Induction of cathepsin B by the CXCR3 chemokines CXCL9 and CXCL10 in human breast cancer cells. Oncol Lett. 13:4224–4230. 2017. View Article : Google Scholar : PubMed/NCBI

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December-2019
Volume 20 Issue 6

Print ISSN: 1791-2997
Online ISSN:1791-3004

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Copy and paste a formatted citation
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Spandidos Publications style
Guo K, Feng G, Yan Q, Sun L, Zhang K, Shen F, Shen M and Ruan S: CXCR4 and CXCR3 are two distinct prognostic biomarkers in breast cancer: Database mining for CXCR family members. Mol Med Rep 20: 4791-4802, 2019.
APA
Guo, K., Feng, G., Yan, Q., Sun, L., Zhang, K., Shen, F. ... Ruan, S. (2019). CXCR4 and CXCR3 are two distinct prognostic biomarkers in breast cancer: Database mining for CXCR family members. Molecular Medicine Reports, 20, 4791-4802. https://doi.org/10.3892/mmr.2019.10784
MLA
Guo, K., Feng, G., Yan, Q., Sun, L., Zhang, K., Shen, F., Shen, M., Ruan, S."CXCR4 and CXCR3 are two distinct prognostic biomarkers in breast cancer: Database mining for CXCR family members". Molecular Medicine Reports 20.6 (2019): 4791-4802.
Chicago
Guo, K., Feng, G., Yan, Q., Sun, L., Zhang, K., Shen, F., Shen, M., Ruan, S."CXCR4 and CXCR3 are two distinct prognostic biomarkers in breast cancer: Database mining for CXCR family members". Molecular Medicine Reports 20, no. 6 (2019): 4791-4802. https://doi.org/10.3892/mmr.2019.10784