Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 1948 2022-11-23 11:04:11 |
2 format correct Meta information modification 1948 2022-11-24 02:44:55 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Amer, H.T.;  Stein, U.;  Tayebi, H.M.E. Monocyte in the Tumor Microenvironment of Breast Cancer. Encyclopedia. Available online: https://encyclopedia.pub/entry/36102 (accessed on 27 May 2024).
Amer HT,  Stein U,  Tayebi HME. Monocyte in the Tumor Microenvironment of Breast Cancer. Encyclopedia. Available at: https://encyclopedia.pub/entry/36102. Accessed May 27, 2024.
Amer, Hoda T., Ulrike Stein, Hend M. El Tayebi. "Monocyte in the Tumor Microenvironment of Breast Cancer" Encyclopedia, https://encyclopedia.pub/entry/36102 (accessed May 27, 2024).
Amer, H.T.,  Stein, U., & Tayebi, H.M.E. (2022, November 23). Monocyte in the Tumor Microenvironment of Breast Cancer. In Encyclopedia. https://encyclopedia.pub/entry/36102
Amer, Hoda T., et al. "Monocyte in the Tumor Microenvironment of Breast Cancer." Encyclopedia. Web. 23 November, 2022.
Monocyte in the Tumor Microenvironment of Breast Cancer
Edit

Breast cancer (BC) is well-known for being a leading cause of death worldwide. It is classified molecularly into luminal A, luminal B HER2−, luminal B HER2+, HER2+, and triple-negative breast cancer (TNBC). These subtypes differ in their prognosis; thus, understanding the tumor microenvironment (TME) makes new treatment strategies possible. The TME contains populations that exhibit anti-tumorigenic actions such as tumor-associated eosinophils. Moreover, it contains pro-tumorigenic populations such as tumor-associated neutrophils (TANs), or monocyte-derived populations. The monocyte-derived populations are tumor-associated macrophages (TAMs) and MDSCs. Thus, a monocyte can be considered a maestro within the TME. 

monocytes tumor microenvironment tumor-associated macrophages breast cancer immunotherapy immunoncology immune checkpoints triple negative breast cancer tumor associated macrophages TAMs TME

1. Breast cancer 

Breast cancer (BC) is one of the most commonly diagnosed cancers in women. It is not only a leading cause of cancer-related death, but also a leading cause of disease-associated death among women worldwide [1]. The number of death cases due to BC was 685,000 in 2020, making it the fifth leading cause of cancer mortality worldwide [2]. Although surgeries or chemotherapies are chances of recovery, the recovery chance decreases as cancer progresses [3]. The prognosis of BC depends on many factors, including traditional clinicopathological variables such as tumor grade, tumor size, and nodal involvement, and it has been shown to possess distinct behavior according to each molecular subtype. It was noted that each molecular subtype has different histopathological and biological features which lead to different and unique treatment responses and strategies [4].
The subtypes of BC are divided molecularly according to the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) with the percentage of the proliferating index (Ki67). With this in mind, BC is classified accordingly into five different subtypes: luminal A, luminal B HER2-negative, luminal B HER2-positive, HER2-positive, and triple-negative BC (TNBC) (basal-like) [5]. Luminal A subtype is characterized by expression of ER and/or PR with no expression of HER2 and with Ki67 < 14%. Moreover, the luminal A subtype expresses BCL-2 cytokeratin CK 8/18 and GATA 3 marker, which is expressed with its highest levels in this subtype [6]. Luminal A is considered the most prevalent with a prevalence of 50–60% among BC patients and is characterized by the best prognosis with a relapse rate of 27.8% [7]. Luminal B abundance is 10–20% among BC patients; it has a more aggressive diagnostic profile than luminal A and a worse prognosis. In addition, it has about 30% bone recurrency and 13.8% liver recurrency [6]. Despite the possible treatment of luminal B with tamoxifen, it responds more to chemotherapy [6]. Luminal B is further classified into two subgroups: luminal B HER2-negative subtype and luminal B HER2-positive. Luminal B HER2-negative is characterized by the expression of ER and/or PR with no expression of HER2 and with Ki67 ≥ 14%. Luminal B HER2-positive is ER- and/or PR-positive and HER2-positive with the expression of any Ki67 percentage [8]. Furthermore, the HER2-positive (enriched) subtype is hormonal-receptor-negative, and only HER2 receptors are expressed with any Ki67 percentage. The HER2-enriched subtype suffers from a worse prognosis than luminal subtypes, although anti-HER2 treatment, e.g., trastuzumab, is possible. It has lower survival rates (10-year survival rate of 12%) in comparison to luminal subgroups (10-year survival rates of 50–55%) [9]. Finally, TNBC (basal-like) is ER-, PR-, and HER2-negative. The TNBC subtype expresses cytokeratins (e.g., CK5, CK17) and epidermal growth factor receptor (EGFR) [10]. This subtype is characterized by high p53 and BRCA1 mutations. BRCA1 is very important and critical in DNA repair [11]. The TNBC subtype is more common in early age, African origin, and increased tumor size with node involvement. It has the highest relapse rate of all subgroups, and relapse usually happens in the first 3 years [12]. Some papers classify the TNBC as not only basal-like but also normal-breast-like and claudin-low. Normal-breast-like is also TNBC but not basal-like as it does not express CK5 and EGFR [13]. The claudin-low subtype is characterized by low expression of genes involved in intercellular adhesion and tight junctions, including claudin-3, -4, and -7; cingulin; occludin; and E-cadherin, and therefore the name of this subtype is claudin-low [14]. This subtype is usually positioned in the hierarchical clustering near the basal-like tumor. Thus, both subtypes share some common gene expression characteristics such as low expression of both HER2 and hormonal receptors, as mentioned before. In contrast to the basal-like subtype, this subtype overexpresses a set group of 40 genes that are related to the immune response, resulting in a high infiltration of tumor immune system cells [14]. The claudin-low subtype has a poor prognosis with a very rare subset of tumors (12–14%) and with high-grade infiltrating ductal carcinomas [14]. Not all claudin-low tumors are negative for hormone receptors (TNBC), as 20% of claudin-low tumors were found to be positive for hormone receptors. Claudin-low tumors in general show poor response to neoadjuvant chemotherapy with relatively intermediate prognosis values between basal and luminal tumors [15].
Generally, gene expression profiling has become a useful tool for breast cancer classification treatment. Although, as previously mentioned, the treatment of HER2-enriched and TNBC is well-defined for anti-HER2 and chemotherapy treatment, respectively, the hormonal subgroup still faces a clinical challenge. Briefly, all luminal tumors are candidates for anti-hormonal therapy. However, unexpectedly, some tumors within the luminal subclass have a more proliferative profile with poorer outcomes and thus are considered for additional therapy. In this context, the common classification which is only based on the molecular intrinsic subtypes as proposed in some papers might not be enough as it only divides the luminal tumors into the luminal A subtype and luminal B. Indeed, this classification is not sufficient for clinical decisions because the luminal tumors present a prognostic range rather than an exact clinical outcome for either group. Accordingly, in a recent study, the RNA-Seq expression profiles split the luminal A samples into two subgroups, namely LumA-R1 and LumA-R2. The lobular-enriched LumA-R2 sample group is characterized by a distinct gene overexpression pattern. This category was associated with significantly reduced recurrence risk compared with the more proliferative LumA-R1 subgroup. Interestingly and most importantly, overexpressed genes were significantly enriched for functions related to the immune system, including genes of upstream T-cell-receptor signaling pathways. The study concluded that the elevated mRNA levels of immune-related genes in LumA-R2 samples indicate increased levels of infiltration of immune system cells into the tumors [16].
Another study investigated the link between neurogenesis, tertiary lymphoid structures, plasma cells, and B lymphocytes in different samples of the basal-like subtype. Accordingly, the study further categorized the basal-like tumors into two subgroups, namely C2 and C3. These two basal-like enriched clusters showed a major biological discrepancy relative to immune response. Briefly, this discrepancy was characterized by a decreasing anti-tumorigenic immune gradient from C3 to C2. Additionally, high neurogenesis activity was found for C2 tumors. Furthermore, the upregulation of immune checkpoints characterized C3 more than C2. However, VTCN1 (B7-H4) was upregulated in C2 more than in the C3 profile [17]. VTZN1 gene codes for a B7 immunoregulatory protein, which possesses an immunosuppressive activity through the inhibition of T-cell activation and clonal expansion [18]. In ovarian carcinoma and glioma, it was observed that macrophages expressing VTCN1 have been directly correlated to the inhibition of T-cell immune response [19]. Accordingly, VTNC1 might actively participate in the C2 immunosuppressive phenotype. It is worth mentioning that the study suggested that tumor-associated macrophages are crucial actors of tumor fate and therefore represent promising immunotherapeutic targets [20]. Consequently, numerous macrophage-directed therapeutic approaches are under investigation and should be considered in the C2 subtype [17].

2. Tumor Microenvironment (TME)

Tumors have the ability to recruit stromal cells (e.g., fibroblasts), immune cells, and vascular cells through the secretion of growth factors, cytokines, and chemokines. Consequently, tumors build a tumor microenvironment (TME) by releasing growth-promoting signals as well as remodeling tissue structure affecting initiation, progression, metastasis, vascularization, and therapy responses [17]. Many treatments focus only on the cancer cell itself and ignore the TME, which is actually a key player in BC progression and development [21]. Tumors not only try to escape from the host immune system but also benefit from the infiltrating cells by modifying their functions to create a microenvironment that is favorable to its progression [22]. Within the TME, different stromal, immune, and regulatory cells may stimulate or inhibit tumor growth. For example, fibroblasts that represent the majority of stromal cells present in the TME inhibit the early stages of tumor progression. This inhibition happens through the production of various fibroblast factors and IL-6. However, it was reported that cancer cells have been associated with the alteration of fibroblasts into cancer-associated fibroblasts (CAFs) [23]. CAFs secrete various growth factors and cytokines, including fibroblast growth factor, human growth factor, tenascin, thrombospondin-1, TGF-β, and stromal cell-derived factor 1 SDF-1 or CXCL12. These factors promote BC proliferation and metastasis. Moreover, TGF-β and PDGF are secreted by tumor cells, causing the migration of fibroblasts to the TME and initiating their transdifferentiation to CAFs. Basically, fibroblasts are well known to be attracted to the wound site, where they undergo fibroblast-to-myofibroblast transdifferentiation under the impact of some platelet-derived cytokines, namely TGFβ1 and PDGF. The presence of TGFβ1 and PDGF at the wound site guarantees a proper wound-healing process through the maintenance of an activated myofibroblast network. The recruitment of the myofibroblast cohort during wound healing is mimicked by most solid cancers during growth and migration. In the presence of tumors, TGF-β1 and PDGF production is accomplished by the cancer cells [24]. CAFs are also known to promote angiogenesis and remodel the extracellular matrix (ECM) [23]. In addition to CAFs, neutrophils are abundantly found not only in human blood but also within the TME and have either pro- or anti-tumorigenic properties. According to cytokines in the TME, tumor-associated neutrophils (TANs) are polarized either into pro-inflammatory/anti-tumorigenic (N1 phenotype) or anti-inflammatory/pro-tumorigenic (N2 phenotype). Moreover, their migration from the blood circulation into the TME is triggered by IL-8 (CXCL8-CXCR1/2 axis) expressed by tumor cells [25]. Normally, neutrophils do not secrete oncostatin M. However, it was found that on interaction with cancer cells, oncostatin M becomes highly expressed in TANs. Commonly, oncostatin M has an inhibitory effect on cell proliferation of BC cell lines having a pro-inflammatory response by inducing chemotaxis and adhesion of neutrophils [23]. Despite its pro-inflammatory response, oncostatin M has also been shown to promote tumor progression by enhancing angiogenesis and metastasis in BC cell lines (MDA-MB-23 and T47D) [26], suggesting that TANs predominate in TNBC in comparison to non-TNBC.
Besides CAFs and TANs, tumor-associated eosinophils play a role in TME. Eosinophils are well known for parasitic and bacterial infections and inflammatory diseases such as allergic asthma and chronic obstructive pulmonary disease, in addition to the high secretion of IL-5 and other eosinophilia granules [27]. However, recent data showed that in the human breast, eosinophils’ presence is critical for mammary gland development. Of interest, eosinophils have been observed at the edge of BC biopsy wounds; this finding suggests that BC biopsies can trigger the recruitment of eosinophils and other inflammatory cells [28]. Basically, a low eosinophil count in the peripheral blood of BC patients is considered a major risk factor for BC relapse. These data suggest a positive correlation between improved prognosis and tumor-associated eosinophils [28]. It was noted that eosinophils were not present within the TME of BC but were present in the TME of other cancers such as colon and lung. In Hodgkin’s lymphoma, their presence in the TME indicates a poor prognosis [29]. Further studies must be conducted to determine whether tumor-associated eosinophils contribute to immune suppression or immune stimulation within the TME. Additionally, a lack of tumor-associated eosinophils was observed in the invasive BC TME [30]. In addition to the previously mentioned immune cells, monocytes play a very critical role in the TME either by themselves or by polarization to different cells such as dendritic cells, myeloid-derived suppressor cells (MDSCs), and macrophages. 

References

  1. Ding, J.; Guo, C.; Hu, P.; Chen, J.; Liu, Q.; Wu, X.; Cao, Y.; Wu, J. CSF1 Is Involved in Breast Cancer Progression through Inducing Monocyte Differentiation and Homing. Int. J. Oncol. 2016, 49, 2064–2074.
  2. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249.
  3. Zhou, L.; Tian, Y.; Guo, F.; Yu, B.; Li, J.; Xu, H.; Su, Z. LincRNA-P21 Knockdown Reversed Tumor-Associated Macrophages Function by Promoting MDM2 to Antagonize* P53 Activation and Alleviate Breast Cancer Development. Cancer Immunol. Immunother. 2020, 69, 835–846.
  4. Blows, F.M.; Driver, K.E.; Schmidt, M.K.; Broeks, A.; van Leeuwen, F.E.; Wesseling, J.; Cheang, M.C.; Gelmon, K.; Nielsen, T.O.; Blomqvist, C.; et al. Subtyping of Breast Cancer by Immunohistochemistry to Investigate a Relationship between Subtype and Short and Long Term Survival: A Collaborative Analysis of Data for 10,159 Cases from 12 Studies. PLoS Med. 2010, 7, e1000279.
  5. Kondov, B.; Milenkovikj, Z.; Kondov, G.; Petrushevska, G.; Basheska, N. Presentation of the Molecular Subtypes of Breast Cancer Detected by Immunohistochemistry in Surgically Treated Patients. Open Access Maced. J. Med. Sci. 2018, 6, 961–967.
  6. Kennecke, H.; Yerushalmi, R.; Woods, R.; Cheang, M.C.U.; Voduc, D.; Speers, C.H.; Nielsen, T.O.; Gelmon, K. Metastatic Behavior of Breast Cancer Subtypes. J. Clin. Oncol. 2010, 28, 3271–3277.
  7. Perou, C.M.; Sùrlie, T.; Eisen, M.B.; Van De Rijn, M.; Jeffrey, S.S.; Rees, C.A.; Pollack, J.R.; Ross, D.T.; Johnsen, H.; Akslen, L.A.; et al. Molecular Portraits of Human Breast Tumours. Letters to Nature 748. Nature 2000, 533, 747–752.
  8. Cheang, M.C.U.; Chia, S.K.; Voduc, D.; Gao, D.; Leung, S.; Snider, J.; Watson, M.; Davies, S.; Bernard, P.S.; Parker, J.S.; et al. Ki67 Index, HER2 Status, and Prognosis of Patients with Luminal B Breast Cancer. J. Natl. Cancer Inst. 2009, 101, 736–750.
  9. Staaf, J.; Ringnér, M.; Vallon-Christersson, J.; Jönsson, G.; Bendahl, P.O.; Holm, K.; Arason, A.; Gunnarsson, H.; Hegardt, C.; Agnarsson, B.A.; et al. Identification of Subtypes in Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer Reveals a Gene Signature Prognostic of Outcome. J. Clin. Oncol. 2010, 28, 1813–1820.
  10. Bosch, A.; Eroles, P.; Zaragoza, R.; Viña, J.R.; Lluch, A. Triple-Negative Breast Cancer: Molecular Features, Pathogenesis, Treatment and Current Lines of Research. Cancer Treat. Rev. 2010, 36, 206–215.
  11. Sørlie, T.; Tibshirani, R.; Parker, J.; Hastie, T.; Marron, J.S.; Nobel, A.; Deng, S.; Johnsen, H.; Pesich, R.; Geisler, S.; et al. Repeated Observation of Breast Tumor Subtypes in Independent Gene Expression Data Sets. Proc. Natl. Acad. Sci. USA 2003, 100, 8418–8423.
  12. Eroles, P.; Bosch, A.; Pérez-fidalgo, J.A.; Lluch, A. Molecular Biology in Breast Cancer: Intrinsic Subtypes and Signaling Pathways. Cancer Treat. Rev. 2012, 38, 698–707.
  13. Mozdarani, H.; Ezzatizadeh, V.; Parvaneh, R.R. The Emerging Role of the Long Non-Coding RNA HOTAIR in Breast Cancer Development and Treatment. J. Transl. Med. 2020, 18, 152.
  14. Prat, A.; Guo, H.; Ganesan, P.; Parker, J.S.; Gao, M.; Moulder, S.; Karginova, O.; Lu, Y.; Lee, J.J.; Fan, C.; et al. Phenotypic and Molecular Characterization of the Claudin-Low Intrinsic Subtype of Breast Cancer. Breast Cancer Res. 2010, 12, 68–86.
  15. Prat, A.; Perou, C.M. Deconstructing the Molecular Portraits of Breast Cancer. Mol. Oncol. 2011, 5, 5–23.
  16. Netanely, D.; Avraham, A.; Ben-Baruch, A.; Evron, E.; Shamir, R. Expression and Methylation Patterns Partition Luminal-A Breast Tumors into Distinct Prognostic Subgroups. Breast Cancer Res. 2016, 18, 74.
  17. Jézéquel, P.; Kerdraon, O.; Hondermarck, H.; Guérin-Charbonnel, C.; Lasla, H.; Gouraud, W.; Canon, J.L.; Gombos, A.; Dalenc, F.; Delaloge, S.; et al. Identification of Three Subtypes of Triple-Negative Breast Cancer with Potential Therapeutic Implications. Breast Cancer Res. 2019, 21, 65.
  18. MacGregor, H.L.; Ohashi, P.S. Molecular Pathways: Evaluating the Potential for B7-H4 as an Immunoregulatory Target. Clin. Cancer Res. 2017, 23, 2934–2941.
  19. Kryczek, I.; Zou, L.; Rodriguez, P.; Zhu, G.; Wei, S.; Mottram, P.; Brumlik, M.; Cheng, P.; Curiel, T.; Myers, L.; et al. B7-H4 Expression Identifies a Novel Suppressive Macrophage Population in Human Ovarian Carcinoma. J. Exp. Med. 2006, 203, 871–881.
  20. de Palma, M.; Lewis, C.E. Macrophage Regulation of Tumor Responses to Anticancer Therapies. Cancer Cell 2013, 23, 277–286.
  21. Pollard, J.W. Tumour-Educated Macrophages Promote Tumour Progression and Metastasis. Nat. Rev. Cancer 2004, 4, 71–78.
  22. Whiteside, T.L. The Tumor Microenvironment and Its Role in Promoting Tumor Growth. Oncogene 2008, 27, 5904–5912.
  23. Barriga, V.; Kuol, N.; Nurgali, K.; Apostolopoulos, V. The Complex Interaction between the Tumor Micro-Environment and Immune Checkpoints in Breast Cancer. Cancers 2019, 11, 1205.
  24. Karagiannis, G.S.; Poutahidis, T.; Erdman, S.E.; Kirsch, R.; Riddell, R.H.; Diamandis, E.P. Cancer-Associated Fibroblasts Drive the Progression of Metastasis through Both Paracrine and Mechanical Pressure on Cancer Tissue. Mol. Cancer Res. 2015, 10, 1403–1418.
  25. Treffers, L.W.; Hiemstra, I.H.; Kuijpers, T.W.; van den Berg, T.K.; Matlung, H.L. Neutrophils in Cancer. Immunol. Rev. 2016, 273, 312–328.
  26. Queen, M.M.; Ryan, R.E.; Holzer, R.G.; Keller-Peck, C.R.; Jorcyk, C.L. Breast Cancer Cells Stimulate Neutrophils to Produce Oncostatin M: Potential Implications for Tumor Progression. Cancer Res. 2005, 65, 8896–8904.
  27. Perret, J.; McDonald, C.; Apostolopoulos, V. Elevated Serum Interleukin-5 Levels in Severe Chronic Obstructive Pulmonary Disease. Acta Biochim. Biophys. Sin. 2017, 49, 560–563.
  28. Szalayova, G.; Ogrodnik, A.; Spencer, B.; Wade, J.; Bunn, J.; Ambaye, A.; James, T.; Rincon, M. Human Breast Cancer Biopsies Induce Eosinophil Recruitment and Enhance Adjacent Cancer Cell Proliferation. Breast Cancer Res. Treat. 2016, 157, 461–474.
  29. Sakkal, S.; Miller, S.; Apostolopoulos, V.; Nurgali, K. Eosinophils in Cancer: Favourable or Unfavourable? Curr. Med. Chem. 2016, 23, 650–666.
  30. Varricchi, G.; Galdiero, M.R.; Loffredo, S.; Lucarini, V.; Marone, G.; Mattei, F.; Marone, G.; Schiavoni, G. Eosinophils: The Unsung Heroes in Cancer? Oncoimmunology 2018, 7, e1393134.
More
Information
Subjects: Oncology
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : , ,
View Times: 578
Entry Collection: Biopharmaceuticals Technology
Revisions: 2 times (View History)
Update Date: 24 Nov 2022
1000/1000
Video Production Service