ISSN 1866-8836
Клеточная терапия и трансплантация

Biomarkers and potential targets for immune and cellular therapy in triple negative breast cancer

Oleg E. Molchanov1, Dmitrii A. Maistrenko1, Dmitrii A. Granov1, Lubov V. Vasina2, Alena A. Popova1, Irina V. Vasilevskaya1, Olga V. Mikolaichuk1,2,3, Olga S. Shemchuk2,3, Elena A. Popova1,2, Alexandra V. Protas1,2, Vladimir V. Sharoyko1,2,3, Konstantin N. Semenov1,2,3

1 A.M. Granov Russian Research Centre for Radiology and Surgical Technologies, St. Petersburg, Russia
2 Pavlov University, St. Petersburg, Russia
3 Institute of Chemistry, St. Petersburg State University, St. Petersburg, Russia


Correspondence:
Prof. Dr. Konstantin N. Semenov, Head, Department of General and Bioorganic Chemistry Pavlov University, 6-8 L. Tolstoy St., 197022, St. Petersburg, Russia
Phone: +7 (952) 215-19-05
E-mail: knsemenov@gmail.com


Citation: Molchanov OE, Maistrenko DA, Granov DA, et al. Biomarkers and potential targets for immune and cellular therapy in triple negative breast cancer. Cell Ther Transplant 2022; 11(2): 16-30.

doi 10.18620/ctt-1866-8836-2022-11-2-16-30
Submitted 05 April 2022
Accepted 24 June 2022

Summary

Triple negative breast cancer (TNBC) is the most aggressive variant of breast malignancies, being a heterogeneous group with various molecular abnormalities that require differentiated approach to diagnosis and treatment. The article contains current data on modern molecular classifications of triple negative breast cancer and appropriate defects in signaling pathways as well as their assignment to distinct immunological and metabolic biomarkers. The data on the prognostic and predictive role of the tumor molecular biomarkers, as well as on clinically used and cellular therapy approaches and developing targeted drugs are presented, and the prospects for the future research are outlined. We also present the data of our own research concerning evaluation of the prognostic role of cytokines and lymphocyte subpopulations in peripheral blood of the TNBC patients.

Keywords

Breast cancer, triple negative, molecular subtypes, mutational burden, tumor stem cells, circulating tumor cells, cellular microenvironment, lymphocyte subpopulations, interleukins, molecular targets, cellular therapy.


Introduction

Breast cancer (BC) is a malignant disease with heterogeneous biological characteristics and different clinical course. It ranks first in the world (about 25%) in terms of morbidity and mortality among other tumors in women. According to the global cancer database (GLOBOCAN), 34650951 cases of breast cancer were detected in the world in 2020, and 11210413 patients died from this disease [1, 2]. 66,990 new cases of breast cancer were diagnosed in Russian Federation in 2019 (489.6 cases per 100,000 people) [3].

Combined chemo- and hormone therapy is, generally, efficient in breast cancer treatment, in terms of overall and disease-free survival. Special advances are achieved in HER-positive tumors using targeted therapy with drugs which suppress the tumor cell growth factors (trastuzumab, herceptin).

A number of protein markers could be used as diagnostic and therapeutic targets in BC, as follows:
1) estrogen receptors (α-subunit, ERα);
2) progesterone receptors (PR);
3) epidermal growth factor receptors of the second type (HER2/new);
4) epidermal growth factor receptors (EGFR);
5) vascular endothelial growth factor (VEGF);
6) cytokeratins (CK5/6, CK14, CK17);
7) nuclear protein reflecting the level of proliferative activity (Ki-67) [4, 5].

Moreover, novel molecular biology approaches, first introduced by Perou et al., using DNA microarray technology, have discerned 4 molecular subtypes of breast cancer, which, in part, corresponded to the previously accepted immunohistochemical (IHC) markers, i.e., luminal A (PR+, ER+, Her-2-), luminal B (PR±, ER+, Her-2+), with Her-2 overexpression (PR-, ER-, Her-2 overexpression), basal-like or triple negative cancer (PR-, ER-, Her-2 -, as well as CK5/6+, CK14+, CK17+, EGFR+). Subsequent works revealed some other molecular variants of breast cancer [6-10].

Basal-like triple-negative breast cancer (TNBC) makes up 12-20% among other histological types, displaying a number of clinicopathological and molecular features that affect treatment strategy. It occurs in women under 50 years of age being characterized by a high recurrence rate, low differentiation levels, and high risk of metastases to parenchymal organs and brain. Molecular defects are often represented by hereditary BRCA (Breast cancer gene) mutations leading to altered DNA repair, thus presuming higher efficiency of DNA-damaging agents, such as platinum drugs and poly-ADP-ribose polymerase (PARP) inhibitors. Moreover, somatic mutations in the P53 gene are detected in 60-80% of cases [11]

The relatively low immunogenicity of this type of tumor seems to be the main obstacle in cellular and immune therapy for breast cancer, compared with many other types of solid malignancies. At the present time, specific TNBC markers are required to determine molecular targets for personalized therapy, e.c., monoclonal antibodies or antigen-oriented immune cells (for example, CAR- T cells). Meanwhile, there exist a lot of molecular markers for diagnostics and therapy [12]. Recent meta-analysis of available data from clinical trials [13] highlighted some potential TNBC biomarkers and therapeutically relevant protein factors on the surface of tumor cells, as well as some blood biomarkers in the patients at different clinical risk. The informative markers of tumor cells were selected, i.e., EGFR, IGF -binding protein, c-Kit, c-Met, and PD-L1. Plasma markers included PIK3CA, pAKT/S6/p4E-BP1, PTEN, ALDH 1 and metabolites of the regulatory pathway PIK3CA/AKT/mTOR, as well as nuclear biomarkers (BRCA1, glucocorticoid receptors, TP53 and Ki-67).

Clinical significance of the TNBC molecular subtypes

To date, several classifications of TNBC have been proposed. They are based on histological signs, characteristic mutations or RNA expression in tumor tissues (Table 1).

Table 1. Molecular classifications of triple negative breast cancer

Molchanov-tab01-01.jpg Molchanov-tab01-02.jpg

The clinically oriented classifications based on the gene expression profiles offer an advanced tool for the disease prognosis and prediction, in addition to the common IHC approaches. E.g., in 2012 Curtis C. et al. developed a classification based on the assessment of the frequency of point mutations and duplications of several genes in 997 primary tumors [14]. The authors identified 10 integrative transcriptional clusters that differ in dominant mode of gene expression. Tumors of the basal-like type, mainly (80% of the cases), have the characteristics of integrative clusters 4 and 10, with pronounced lymphoid infiltration in cases of cluster 4 transcriptional profile, and multiple chromosomal aberrations in the patients with cluster 10 expression [14].

In 2014, Lehmann et al. analyzed the expression profiles of 2188 genes in 587 patients and identified 6 types of tumors that differ in biological properties: basal-like 1, 2 (BL 1, BL 2); mesenchymal (M), mesenchymal-stem (MSL), immunomodulatory (IM), androgen receptor (LAR). The rest of the variants were classified as Unstable Type (UNS). Moreover, the authors divided these triple negative breast cancer cell types using this classification [15].

In 2013, Masuda et al. analyzed the prognostic significance of molecular subtypes of breast cancer [18]. The following conclusions were drawn: 1) molecular subtypes clearly correlate with the rate of complete responses during chemotherapy with anthracycline antibiotics and taxanes (BL1, 52%; BL2, 0%; LAR, 10%; MSL, 23%); 2) molecular subtype is an independent predictor of complete response (p=0.043); 3) molecular subtypes have greater prognostic value compared to PAM 50 (Prediction Analysis of Microarray 50). This parameter tests a sample of the tumor for a group of 50 genes to predict the chance of progression.

The study by Burstein et al. (2015) aimed at modifying the criteria and clarifying the number of molecular subtypes in triple negative breast cancer in accordance with expression profiles of 80 genes [16]. The workers have identified 4 molecular subgroups determined by overexpression of different genes, and specific biomarkers were shown for each of them: 1) luminal AR (LAR): androgen receptors, mucin (MUC 1); 2) mesenchymal (MES): IGF -1, ADRB 2, EDBRB, PTGER 3/4, PTGFR, PTGFRA; 3) basal-like immunosuppressive (BLIS): VTCN 1; 4) basal-like immunoactivated (BLIA): CTLA-4. The subgroups proved to be predictive for the relapse-free (p=0.019) and tumor-specific survival (p=0.07). The group-specific biomarkers can be considered as targets in the development of treatment for triple-negative breast cancer [17].

At the same time, it should be noted that the molecular typing of breast cancer tissues do not always correlate with spectrum and amount of appropriate proteins, i.e, with results of immunohistochemical studies. Hence, the existing classifications require further improvement.

Altered signaling pathways in breast cancer stem cells

Over recent decades, there has been increasing evidence that the characteristics of cancer stem cells (CSC) may determine high risk of metastases and drug resistance. Hence, the CSCs are one of the promising biomarkers for TNBC prognosis. Their quantitative and functional evaluation may inform about degree of tumor aggressiveness, whereas defective signaling pathways could be affected by targeted therapy.

Compared to other tumors, the TNBC clinical samples and cell lines show much higher contents of the cells with a CD 44+/CD 24-/ phenotype and high ALDH 1 expression. Clinical studies have shown that the expression of CD 44+/CD 24-/ is associated with decreased efficacy of chemotherapy, high incidence of distant metastasis, lymph node involvement, and recurrence, whereas ALDH 1 is an independent prognostic factor for long-term treatment outcomes. Detectable markers of the epithelial-mesenchymal transition (EMT) combined with high CSC concentration are also associated with resistance to chemotherapy and, in particular, to PARP inhibitors [19].

Self-renewal of malignant stem cells and other features providing invasiveness, resistance to therapy, and high metastatic potential, are associated with hyperactivation of several key signaling pathways, e.g., Notch, Wnt/β-catenin, Hedgehog, STAT 3. Thus, the Notch signaling cascade includes a family of transmembrane ligands and their receptors, which are critical for the processes of cell proliferation and differentiation. Disturbances of this cascade are detected in patients with lung cancer, prostate cancer, colorectal cancer, breast cancer and leukemia, thus regarded as prospective targets for anticancer drugs [20, 21].

To date, a lot of experimental and clinical data has been obtained confirming that dysregulation of the classical Wnt/β-catenin signaling pathway leads to increased incidence of distant metastases. The members of non-canonical Wnt-signaling pathway (FZD6 and FZD8) are also associated with aggressive behavior of the tumor and its chemoresistance [22, 23]. These molecules are considered potential targets for the newly developed drugs [24].

HH (Hedgehog) is a signaling pathway that promotes self-renewal of the CSC population. The HH family includes three secretory ligands: SHH (Sonic), expressed in embryonic cells; IHH (Indian), found predominantly in hematopoietic stem cells; DHH (Desert) found in cells of the peripheral nervous system and testicles. Overexpression of HH components (SHH, GLI 1/2, SMO) is associated with tumor invasion, angiogenesis, and chemoresistance and, therefore, with poor clinical prognosis. The components of this signaling pathway, especially SMO and GLI, are considered targets for the novel anticancer drugs [25].

TGF-β is a member of the cytokine superfamily, which includes more than 30 functionally related growth factors, including 3 TGF-β isoforms (TGF-β1-3) involved in the regulation of cell growth, adhesion, apoptosis, differentiation and immunoregulation. It inhibits the secretion and regulation of the functions of a number of cytokines, including IFN-γ, TNF-α, IL-2. The role of TGF-β in carcinogenesis is to promote proliferation, angiogenesis, metastasis, chemoresistance, immunosuppression. In addition, the presence of TGF-β is critical for CSC. TGF-β is secreted by the cells from tumor microenvironment which supports CSC population, and, in turn, promotes alternative polarization of immunocompetent cell precursors. In clinical practice, overexpression of TGF-β is a marker of chemoresistance and poor prognosis. TGF-β receptors are considered targets for some prospective drugs [26].

JAK/STAT signaling pathway plays an important role in a number of carcinogenesis-associated events, including proliferation, inflammation, and the pathological changes of microenvironment. E.g., JAK is a family of non-receptor tyrosine kinases that includes 4 components: JAK 1, JAK 2, JAK 3 and TYK 2. JAK 1, JAK 2 and TYK 2 are expressed in many cell types, whereas JAK 3 is specific to hematopoietic stem cells. Under the influence of cytokines and growth factors (IL-6, IL-8, TGF-β, IGF, EGF), the JAK/STAT 3 complex is activated causing overexpression of the genes providing synthesis of growth factors and cytokines (TGF-β, IL-6) which stimulate proliferation of TNBC cells. Experimental and clinical studies have shown that expression of IL-6, IL-8, and STAT 3 is associated with poor prognosis and chemoresistance [27-29].

Circulating tumor cells

Circulating tumor cells (CTC) are considered a potential biomarker associated with prognosis, prediction of efficacy, and treatment monitoring in TNBC. CellSearch technology is the conventional approach to CTCs isolation offered by Menarini Silicon Biosystems, based on recognition of EpCAM adhesion molecules [30]. In 2004, Cristofanilli et al. have shown that detection of >5 CTCs per 7.5 ml of blood is an independent predictor of overall and relapse-free survival of the patients with metastatic breast cancer. In 2019, the prognostic role of this marker was proven in the study in 1944 TNBC patients stratified into two large groups: indolent, for which standard treatment is adequate, and aggressive course, for which new, including experimental, methods of treatment were required [31].

However, the data on significance of CTC as a prognostic factor in TNBC patients still remain contradictory. E.g., Munzone E. et al., in retrospective analysis of data from 203 patients, showed that the number of CTCs correlated with overall survival, but not with progression-free survival. Meanwhile, in the SWOG study S0500, the CTC scores were found to be predictive of overall survival and predictive of chemotherapy efficacy [32]. At present, the most promising areas of CTC research are their molecular biology characterization, cluster studies, and combined assays with other biomarkers. The study which involved 360 TNBC cases has shown that occurrence of CTC clusters correlated with the median time to progression [33].

Genetic biomarkers

Molecular markers of TNBC include gene mutations affecting DNA repair systems, signaling molecules, growth factors and their receptors, as well as microsatellite instability and general mutation load. Among the mutated or overexpressed genes, specific targets are searched for the recently used and novel immunotherapeutic drugs. A separate group consists of immunological biomarkers. These indexes reflect the state of tumor microenvironment, peripheral immunological components, and tertiary lymphoid structures.

Mutations in genes associated with DNA repair

Finding the relationships between BRCA 1/2 gene mutations and inherited ovarian and breast tumors was a key discovery in clinical oncology, opening up new opportunities for screening and prevention. Detailed studies of appropriate mechanisms has led to the development of new treatment options. BRCA 1 and BRCA 2 are autosomal dominant genes that are critical in DNA repair by homologous recombination (homologus recombination repair, HRR). Mutations of BRCA 1 and BRCA 2 (gBRCAm) occur in a small part of the population (approximately 0.25%), whereas in women with TNBC their frequency varies from 11% to 31%. The risk of developing breast cancer with hereditary BRCA mutations is 65% and 45%, respectively [34]. These mutations may trigger an alternative DNA repair mechanism, i.e., a non-homologous end joining (NHEJ). This process depends on poly-ADP-ribose polymerase activity (PARP), and its inactivation leads to cell death. Currently, a number of PARP-blocking drugs entered the clinical practice, e.g., Olaparib, Talazoparib, Niraparib, Rucaparib, Veliparib [35].

In 2015, Domogala P. et al. studied the distribution of 36 mutations in genes involved in homologous recombination. They were found in 22% (35 out of 158) of the patients with TNBC [36], thus suggesting usage of PARP inhibitors and other DNA damaging agents for defects in other genes associated with HRD (homologus recombination deficiency) [37, 38]. Microsatellite instability (MSI) is an additional feature of malignant disease progression сaused by deficient DNA mismatch repair (dMMR). MSI is associated with highly frequent neoantigen production, thus affecting sensitivity to immunooncological drugs. Some tumor variants (colorectal cancer, endometrial cancer) are characterized by increased MSI rates (20%-30% of the cases).

Immunological markers for TNBC

Mutual interactions between the tumor and host immune system were studied for decades. In the mid-20th century, animal experiments on tumor xenotransplantation showed that effective antitumor immune response is possible only at high levels of tumor-specific antigens. Based on these data, in 1957 M. Burnet formulated the "clonal selection theory" and coined the term "immunological surveillance" [39]. In particular, it was suggested that the transformed cells expressing foreign antigens permanently occur in the body, being normally eliminated by the host immune system. This immune response is similar to classic "immunological surveillance" as described by M. Bernet. Over this period, the tumor cells are recognized and eliminated by factors of innate and adaptive immunity. Both immune cells of tumor microenvironment and peripheral blood may be of prognostic and predictive value. In both cases, quantitative characteristics and ratios of different populations, as well as concentration and production of cytokines (spontaneous and induced) should be assessed.

Lymphocytes and mononuclear cells in peripheral blood

In several studies concerning prognostic cellular markers in TNBC, an assessment was made of lymphocytes or peripheral blood mononuclear cells, as well as the ratios of different leukocyte subpopulations. E.g., a prognostic significance of lymphocytosis, monocytosis, and lymphocyte: monocyte ratio (LMR ≥ 4.7; p <0.001) was shown by He et al. (2016) in 230 patients with local and locally advanced forms of TNBC. Moreover, LMR correlated with tumor size (p <0.005) and disease stage (p=0.013) [40]. Losada B. et al., when studying a group of older BC patients have revealed by univariate analysis that еру platelet-lymphocyte ratio (PLR) is the only independent predictor of disease-free (p=0.04) and overall three-year survival (p=0.03), whereas, among the 3-year survivors (n=69), whereas only ALC has predictive properties in a multivariate analysis at the marginal significance level (p=0.04) [41].

Evaluation of myeloid and lymphoid cell subpopulations, either in peripheral blood, or in tumor microenvironment is a more accurate method for assessing the prognosis. Among lymphoid cells, the role of lymphocytes (CTL, Treg, B-lymphocytes), myeloid cells – monocytes/macrophages (M 1.2), dendritic cells (DC), and suppressor cells of myeloid origin (MDSC) have been studied [42].

Monocyte/macrophage cell lineage

To date, monocytes and macrophages (MFs) are shown to be associated with carcinogenesis in breast cancer, as well as with prognosis and efficiency of various treatment approaches. There are two macrophage subpopulations, M1 and M2, discerned in the tumor microenvironment and peripheral blood of the patients. M1 represents classical activated MFs, that develop from their precursors under the action of lipopolysaccharide, IFN-γ and TNF-α. M2 is the collective name for the macrophages induced via IL-4, IL-13, IL-10, TGF-β, Fc receptors, complement and glucocorticoids. M2 are derived from peripheral blood monocytes recruited to the affected site by chemokine ligands (CCL – 2, MCP – 1), colony-stimulating factors (M – CSF, CSF – 1) and vascular endothelial growth factor (VEGF), due to their higher concentration in the areas with low oxygenation. Under the chronic local hypoxia, the macrophages produce hypoxia-induced factors (HIF-1 and HIF-2) which derepress the synthesis of several proteins that increase angiogenic potential (VEGF, bFGF, PDGF), invasive and metastatic ability of tumor cells (MMP, CCL 2, CCL 18). Moreover, they promote arginase (Arg) and IDO expression, thus reducing local contents of arginine and tryptophan, which are essential to the normal functioning of T-lymphocytes and NK cells [43].

Concentration of M2 cells in peripheral blood is significantly higher compared to M1 population, thus correlating with a short relapse-free period in TNBC patients. The M2 macrophages are more common in the blood of patients with distant metastases. The ratio of monocyte subpopulations in TNBC differs from other types of breast cancer, i.e., the alternative polarization variant (CD 14+CD 16+) dominates over the classical one (CD 14hi CD 16-). High concentration of monocytes (CD 14+) is a predictor of good response to high-dose systemic therapy with cyclophosphamide and taxanes [44-46].

Dendritic cells (DCs) comprise a highly specialized subpopulation which performs uptake, processing, and antigen presentation within major MHC I and II histocompatibility complexes, along in combination with co-stimulatory Th molecules (CD 4+), acting with CTL in direct and indirect manner. They are activated by the "danger signals" from the tumor cells, including chemokines and neoantigens. The DC maturation, along with antigen-presenting functions includes expression of costimulatory molecules (CD40, ICAM I, CD80/86, CD 83), secretion of numerous cytokines (IFN-γ, IL-4, IL-5, IL-6, IL-10, IL-13), and migration to the lymph nodes, where the T-cell activation program is launched. In humans, two subpopulations of DC are morphologically and functionally distinguished. I.e., myeloid DC (mDCs) comprise classical DCs of the CD11c+ CD4+ CD45RO+ phenotype expressing MHC I, II which trigger the immune response upon contact with soluble antigens.

Plasmacytoid DCs (pDCs) display the CD11c- CD4+ CD45RA+ CD123+ phenotype and MHC I expression, being reactive for the cell-associated antigens. The DCs in TNBC patients showed reduced expression of cytokines (IL-12), co-stimulatory molecules (CD 80, CD 86), activation markers (HLA-DR), and lower ability to present antigens [47].

There are some controversial data on prognostic and predictive role of DC in the patients with TNBC. Despite conflicting data on the role of dendritic cells, considerable attention is paid to this cell population, in terms of vaccine therapy for cancer, in particular, breast cancer. According to several studies, their high levels may be a favorable prognostic factor for overall survival [48, 49]. However, further research is needed to determine their therapeutic potential in TNBC.

The populations of natural killer cells (NKs) are formed from a common lymphoid precursor in the bone marrow, from where they further spread to the primary and secondary lymphoid organs, as well as to the lungs, liver, and blood. Two NK subpopulations are identified in humans: CD56bright CD 16- (cytokine-producing) and CD56dim CD16+ (cytotoxic). In addition, there are several groups of NK depending on the degree of maturity, determined by the expression of CD 27 and CD11b surface markers which are not expressed by the immature NKs. In the course of maturation, CD 27 appears first, followed by CD11b. NK with the CD 27+ phenotype show the best ability for cytokine secretion, whereas the NK cells with CD11b+ CD27 phenotype demonstrate maximal cytolytic activity. NK can eliminate cells that do not express MHC I, and this mechanism is used by malignant cells and CSCs to prevent attack by CTLs. Potentially, NK cells are the most effective cells against the tumor, but they may acquire the CD56bright CD16- phenotype under the influence of microenvironmental factors (TGF-β, adenosine), and express pro-angiogenic factors (MMP 9, VEGF), thus increasing the invasive potential, leading to T-cell depletion [59]. Low blood levels of NKs seem to predict low efficacy of neoadjuvant chemotherapy in TNBC. Expression of CD 163 and CXCR 4 in the NK microenvironment is a marker of early relapse [50, 51].

Tumor microenvironment

The study of the tumor microenvironment in TNBC is an important component of assessing the prognosis of the disease. From a clinical point of view, the cellular microenvironment can be assessed both quantitatively and qualitatively, taking into account the population profile, by the presence of a specific "immunological signature". Moreover, it is currently possible to assess the contents and production levels of cytokines by lymphoid cells of peripheral blood and tumor microenvironment. The lymphoid component, which makes up to 50-60% of the stromal volume in all molecular subtypes of TNBC, as a rule, suggests good prognosis and potential sensitivity to immuno-oncological drugs and chemotherapy [52, 53].

In 2020 He L. et al. conducted a meta-analysis of randomized trials with assessment of tumor-infiltrating lymphocytes (TIL) which reflected the results of treatment in 15,676 patients with breast cancer, including 3847 TNBC cases. The results of multivariate analysis showed that any 10% increase in TIL density was associated with increase in overall survival and complete morphological response rates for all molecular subtypes. High TIL density (≥50%) leads to a 2.7-fold increase in the complete response rates in TNB [54].

A similar study was done by Mao et al. [55]. They analyzed data from 25 works (22964 patients) concerning the major TIL subsets: CD 8+, Foxp 3+, PD-1+, γδ T cells, CD3+, CD4+. CD8+ TIL in the infiltrate proved to be a favorable prognostic factor for disease-free and tumor-specific survival in all subgroups. Foxp3+ TILs seem to be a dismal unfavorable prognostic factor for relapse-free and overall survival in all the subgroups except of TNBC. PD-1+ TIL and γδT TILs are poor prognostic factors for overall survival in all subgroups, whereas CD3+ TIL and CD4+ TIL did not show any predictive potential [55]. Thus, in most behavioral studies, the authors conclude that the formation of tertiary lymphoid organs is a favorable prognostic factor for TNBC.

Local and systemic concentrations of cytokines

Cytokines are currently considered universal regulators of homeostasis for many cell types. In TNBC, they are involved in regulation of angiogenesis, arrangement of immunosuppressive networks, tumor metastasis, and metabolic processes associated with obesity, chronic inflammation, and carcinogenesis. Involvement in carcinogenesis enables usage of the cytokines as prognostic markers. Cytokines can be measured in blood or in tumor microenvironment. Their contents, as well as spontaneous and induced production, may be assessed in these samples. IL-1, -6, -8, -10, -11, -17, -19, -20, -23, like as TNF-α; TGF-β, adipokines (leptin, adiponectin) are involved in TNBC carcinogenesis. Many of them have predictive potential (Table 2).

Table 2. Prognostic role of functional overexpression in microenvironment, or increased levels of cytokines in blood plasma in patients with triple-negative breast cancer

Molchanov-tab02.jpg

IL-6, 8, 10, TNF-α and TGF-β are the most studied cytokines associated with carcinogenesis and prognosis of TNBC. IL-6 is a cytokine that functionally integrates the immune and neuroendocrine systems, being produced by T cells, macrophages, myocytes, endotheliocytes, fibroblasts, and tumor cells. IL-6 promotes cell proliferation and synthesis of antibodies by B-lymphocytes, CTL proliferation, stimulates the granulocytic hematopoietic lineage, and induces the expression of acute phase proteins in the liver. Overexpression of IL-6 in malignant tumor and increased concentration in peripheral blood is considered an unfavorable prognostic factor in terms of overall and disease-free survival [67-69].

Interleukin-8 (IL -8) belongs to the chemokine family, being produced by the MF and endothelial cells. In the course of carcinogenesis, IL -8 can act as an autocrine growth factor and stimulate angiogenesis. Serum IL -8 is not a favorable prognostic factor for overall and disease-free survival [70-72].

IL-10 is a key regulator of the antitumor immune response. Treg, Th0, Th1, Th2, CTL, monocytes, MF, tumor cells, TAM and NK are the main producers of IL-10 in humans. Maturation by reducing MHC expression II, adhesion molecules and cytokines (IL-12), as well as reducing the sensitivity of receptors that respond to "danger signals". IL-10 inhibits proliferative activity and production of Th 1 cytokines, T-dependent activation of CTL and CD 19 [73]. The main biological effects of TNF – α in carcinogenesis are associated with the maintenance of the peritumoral inflammation, increased capillary permeability and stimulation of angiogenesis. The role of TNF-α in TNBC is twofold. On the one hand, it promotes EMT, on the other hand, it activates antitumor CTLs [74-76].

Recently, the workers at A.M.Granov Research Centre for Radiology and Surgical Technologies and Pavlov University have performed a pilot study to assess prognostic significance of subpopulations of lymphocytes and cytokines which involved 29 TNBC patients. Before and after neoadjuvant chemotherapy, the amounts of lymphocyte subpopulations and cytokine contents were measured in peripheral blood, as follows: CD3+CD8+ (cytotoxic lymphocytes); CD3+CD4+ (T helpers); CD4+CD8+ (double positive T cells); CD16+CD56+HLADR+ (activated natural killers); CD3+CD16+CD56+ (TNK cells); CD4+CD25+FoxP3 (T-regulatory cells); CD3+HLA DR+ (activated T cells); αβ T cells (alpha/beta T cells); γδ T cells (gamma/delta T cells); interleukin-1β (IL-1); interleukin-2 (IL-2); interleukin-4 (IL-4); interleukin-6 (IL-6); interleukin-8 (IL-8); interleukin-10 (IL-10); interleukin-12 (IL-12); interferon-α (IFN-α); interferon-γ (IFN-γ); tumor necrosis factor-α (TNF-α). The assays were carried out at Laboratory of Immunology, A.M. Nikiforov Center for Emergency and Radiation Medicine (St. Petersburg) using the Cytomics laser flow cytometer FC 500 (BECKMAN COULTER, USA). As a result of multivariate analysis, we have revealed that, among these parameters, the concentrations of T regulatory cells in peripheral blood (CD4+CD25+FoxP3) (p=0.045), as well as spontaneous production of IL-6 (p <0.005) and IL-10 (p <0.005) proved to be independent predictors of early relapse in triple-negative breast cancer.

The use of monoclonal antibodies in TNBC treatment

As already noted, specific tumor target antigens for immunotherapy have not yet been identified in breast cancer. Therefore, in recent years, much attention has been paid to the mobilization of immune surveillance of cells in the microenvironment. For example, many cancers are undergoing extensive clinical trials of immune checkpoint (ICT) inhibitors. These drugs relieve the state of local immunosuppression in these patients and enhance the activity of antitumor immunity. Reviewed by [77] Radoza et al. (2020) provide results from the IMpassion 130 program and other trials where therapy with antibodies to the programmed death receptor or its ligand (PD-1/PD-L1) and paclitaxel was used as first-line therapy for PDL 1-positive metastatic TNBC. Other ICT trials have used carboplatin or other cytotoxic drugs. The biological meaning of such combined schemes is the death of malignant cells and, which leads to the appearance of neoantigens – additional targets for activated immune cells of the patient. Along with this, within the framework of the generally accepted concept of targeted therapy for malignant neoplasms, programs of clinical trials of monoclonal antibodies are being carried out, against EGFR2 (epidermal growth factor receptor 2).

Potential targets for immunoconjugates of anticancer antibodies

A separate group of biomarkers is regarded as potential targets for a new group of drugs – conjugates of monoclonal antibodies with cytotoxic agents. Monoclonal antibodies bind to the target, and the complex is internalized into the tumor cell, realizing selective cytotoxicity. The target molecule for the conjugate must be overexpressed on the cell surface and have the property of internalization upon interaction with the ligand. Currently, several molecules have been identified in TNBC cells with the following properties: 1) non-metastatic glycoprotein b (GPNMB); 2) surface trophoblastic antigen-2 (Trop -2); 3) zinc-containing transport protein (LIV-1); 4) sialoglycomucin (CA 6).

GPNMB is involved in several processes associated with carcinogenesis, including cell migration, invasion, angiogenesis, and EMT. In addition, it is a biomarker of poor prognosis [90]. GPNMB is a target for Glematumumab vedotin (CDX -011), a conjugate containing a microtubule-destroying chemical agent, monomethyl auristatin E (MMAE), as an effector. Phase II data from the EMERGE study demonstrated that CDX -011 is more effective and less toxic than chemotherapy in TNBC patients with GPNMB overexpression [78, 79].

Trop -2 is a transmembrane glycoprotein involved in the processes of migration and proliferation, which is a target for Saccituzumab govitecan (IMMU -132), which contains a topoisomerase I inhibitor as an active agent. SN -38. Results of a phase II study of 33.3% objective responses in patients with TNBC in the third line of therapy [80, 81].

LIV -1 is involved in the regulation of STAT -3 expression, cell adhesion, and EMT. Preclinical studies have demonstrated the efficacy of Ladiratuzumab vedotin, which binds to the extracellular domain of LIV -1 [82].

CA 6 is selectively expressed on many solid tumor cells. It is a target for SAR 566658, which contains microtubule-destroying DM 4 as an active component [83].

Immune response inhibitors: PD1/PDL

Biomarkers that predict the effectiveness of immunotherapy in patients with TNBC include co-inhibitory molecules – targets of immunooncological drugs, microsatellite instability, mutation load, and tumor-infiltrating lymphocytes.

PD-1 is a co-inhibitory molecule that regulates the functions of components of the innate and adaptive immune response. It is expressed on the surface of T-lymphocytes, B-lymphocytes, MF, monocytes, DC. Under physiological conditions, it contributes to the formation of tolerance to autoantigens; in the tumor microenvironment, it promotes tumor immunological tolerance [84]. The PD-1 ligand (PD-L1) is a transmembrane protein that is expressed both on tumor and immunocompetent cells (T, B-lymphocytes, DC, MF). The interaction of PD-1/PD-L1 leads to deactivation of T-lymphocytes, activation of T-regulatory cells, and persistence of tumor cells [85, 86].

PD-L1 is expressed in 20% of TNBC cases. PD-L1 is expressed in about 10% on tumor cells, and 40-65% on cells of the tumor microenvironment. Expression of PD-L1 on tumor cells is a predictor of a favorable prognosis and a marker of sensitivity to chemotherapy [87]. Expression of PD-L1 on lymphocytes in the microenvironment is a marker of sensitivity to blockers of co-inhibiting molecules [88].

PD-1 and PD-L1 blockers are currently the standard treatment for TNBC. Atezolizumab (anti-PD-L1) was the first approved drug in this group for the treatment of its metastatic forms. The Phase III study IMPASSION 130 evaluated the efficacy and safety of atezolizumab and included 451 participants. The median overall survival in the group where the expression of PD-L1 ≥ 1% on the cells of the lymphoid infiltrate was significantly higher in the group where patients received atezolizumab in combination with nab-paclitaxel (25 and 18 months). To assess the expression of PD-L1 in the study, the test system VENTATA was used [89]. The efficacy and safety of pembrolizumab (anti-PD-1) in previously untreated patients in phase III was assessed in the KEYNOTE -355 protocol. The study included 847 patients who received various chemotherapy regimens (paclitaxel, nab-paclitaxel, platinum drugs and gemcitabine) in combination with placebo or pembrolizumab. Expression of PD-L1 was assessed in points using the 22С3 test system (DAKO PharmaDx), which considered the ratio of PD-L1 on tumor cells, lymphocytes and macrophages to the total number of detected tumor cells, multiplied by 100 (CPS, combined positive score). Significant differences in median relapse-free survival were found only at CPS ≥ 10 (9.7 months in the pembrolizumab group and 5.6 months in the placebo group). PD-1 and PD-L1 in patients with TNBC are associated with prognosis. PD-L1, in addition, plays the role of a predictive factor in relation to the effectiveness of blockers of co-inhibitory molecules [90, 91].

Cellular and immunotherapy of breast cancer

Early attempts of hematopoietic stem cell transplantation (HSCT)

In the 1980s, with the development of cytostatic therapy for solid tumors, it became necessary to maintain and restore hematopoiesis in patients with intensification of chemotherapy regimens. Therefore, methods of bone marrow transplantation taken from the patient himself (autologous BMT) before the start of intensive chemotherapy, in combination with hematopoiesis stimulation factors, were proposed. At the same time, the main problem was the purification of the harvested bone marrow of patients from metastatic tumor cells. At that time, there were no sufficiently effective immunological markers for the detection of malignant cells and their elimination in transplants. However, the first clinical studies of the 90s according to the use of auto-TKM in breast cancer, an increase in overall and recurrence-free survival was revealed in some patients [92]. However, later these positive results were not confirmed in larger samples and in randomized trials [93].

Subsequently, with the development of transplantation of hematopoietic and immune cells from HLA -compatible donors (allo-HSCT), there were proposals to use allogeneic cells to implement the immune effect "graft-versus-tumor", by analogy with the "graft-versus-leukemia" reaction in oncohematological diseases [94]. A positive effect of allo-HSCT was noted in some patients with solid neoplasms, including breast cancer. In general, the clinical response here was associated with the development of acute and chronic graft-versus-host disease. The authors pointed to low specificity and pronounced undesirable effects in this type of treatment.

The use of individual fractions of donor immune cells (primarily lymphocytes) for the adoptive therapy of solid cancers is considered. However, the authors express doubts about the duration of the therapeutic effects of adoptive immunotherapy [95]. It is possible that adoptive immunotherapy will find its place in combined regimens for the treatment of solid tumors, along with targeted drugs.

Current opportunities of cell therapy of breast cancer

One of the long-standing methods of biotherapy is the use of individual cell-based vaccines that have a therapeutic effect in breast cancer. Their clinical development is in the 2nd-3rd phases. Early work in this area consisted of short-term incubation of the patient's tumor tissues with his lymphocytes/monocytes with the addition of several cytokines to induce the presentation of these antigens and activate the response of immune cells (both T-lymphocytes and macrophages) to tumor antigens, after which these stimulated, the cells were returned to the patient. More modern approaches involve targeting antigens that are expressed mainly in malignant tumors and, to a much lesser extent, on normal cells. Typically, T-lymphocytes targeting these antigens are eliminated by the tolerance system. However, in this clinical situation, cell-based vaccines must be immunogenic enough to activate, among other things, T cells with low affinity for these antigens. Here it becomes expedient to use ICT to activate these cell populations. In addition, there is currently a search for individual mutations in the genome of cancer cells, based on which it is supposed to create cell-based vaccines for specific patients with cancer [96].

A few works [97] consider the possibility of using activated populations of natural killer (NK) cells of malignant killer T cells in oncological diseases. Most often, peripheral blood mononuclear cells are used for this and stimulated with interferon gamma and/or IL-2 for 2-3 days. In particular, Sommaggio et al. (2020), cytokine-induced killer cells (CECs) in combination with cetuximab (an EGFR inhibitor) showed good antitumor and antimetastatic efficacy in NOD/SCID (NSG) mice with human breast transplants [98].

One of the latest trends is the development of CAR-T cells as a selective means of eliminating malignant cells that carry a specific antigen.

Thus, some authors are considering the possibility of using CAR-T cells against the MAGE-A4 antigen, which is considered a promising target for the treatment of lung cancer and TNBC [99]. The main objective of this work was to select T cells directed against a small MAGE-A4 region recognized by the corresponding HLA-A2 allele. These TCR-T cells with CD4 markers showed a direct selective cytotoxic effect in vitro and in vivo (in mice with xenografts) against various human malignant tumors expressing the antigen MAGE-A4.

Epidermal growth factor receptor (EGFR) is one of the most promising targets in cell therapy for breast cancer, against which effective T-cell products with a chimeric antigen receptor have been developed. Chinese authors have created EGFR lines using a lentiviral vector. CAR-T cells against TNTC, which was tested on cells in vitro. The 3rd-generation drugs caused a pronounced and specific suppression of the growth of tumor cells. At the same time, only minimal toxicity was noted in relation to normal breast cells. The antitumor effect was confirmed and in vivo in mice with transplanted human tumors. It is hypothesized that EGFR stimulation CAR T cells cause this population to proliferate and support their growth. Transcriptome studies have shown that the effect of CAR T cells consists in the activation of systems of ќ≥-interferon, granzyme-perforin, and enzymes of apoptosis of tumor cells.

Another possible target antigen for immunotherapy is the so-called ROR1 (tyrosine kinase-like orphan receptor 1). A group of German authors developed ROR 1-specific CARs T cells [100]. Their biological activity was assessed in 3D models of lung and breast tumors based on the corresponding cell lines similar in structure and phenotype to primary tumors. ROR 1- CAR T cells in this model had a pronounced antitumor effect, actively inhabiting the tumor tissue and destroying its cell layers. Thus, the fundamental possibility of bioeffects of these genetically modified T cells under conditions close to the situation in vivo was shown.

At the same time, the action of CAR T cells against tumors may be defective. Thus, the suppression of the cellular immune response under the influence of the widespread factor TGF-β is supposed. The already mentioned group of German authors [101] studied the issue of this pronounced immune suppression, and the ways of neutralizing this effect. For this purpose, the lines CD 8 + and CD 4 + were prepared. ROR 1- CAR T cells from healthy blood donors, and their antitumor activity was determined on TNBC cells (MDA-MB-231) in vitro and in 3D models. It turned out that adding TGF-β led to decreased viability, cytolytic activity, cytokine production, and ROR 1 – CAR proliferation. T cells in mixed culture with tumor cells. Blockade of the TGF-β receptor with a specific inhibitor SD-208 protected CD 8+ and CD 4+ ROR 1- CAR T cells from this inhibitory effect and maintained the antitumor properties of CAR T cells. Thus, to preserve the effects of CAR T cells may need combined exposure, in particular – and in subsequent testing of these cell products. Among the factors of tumor resistance is called immunosuppression, which may develop with the introduction of CAR T cells against EGFR, as shown by the same group of authors in experiments on mice with TNBC [102]. This negative effect of CAR T cell therapy is associated with the induction of interferons, suppression of the activity of a number of immune response genes and can be overcome with epigenesis inhibitors (for example, inhibitors of the CDK7 gene).

In addition to the generally accepted cell therapy for oncological diseases, additional means of enhancing the effects of chemotherapy on the tumor are also possible. Thus, it is known that the system of macrophages and other phagocytic cells is able to capture and inactivate most of the drug when it is administered in a free form. To solve this problem, various means are proposed for its microencapsulation and targeted delivery to the tumor tissue. Chinese authors proposed preparations of the so-called "analogs of apoptotic bodies" (AAT) prepared from malignant cells containing CD47 and adhesion molecules [103]. These artificial structures, according to the authors, combine antiphagocytic properties and, at the same time, can be used for more efficient delivery of chemotherapy drugs to the tumor. An increased accumulation of AAT and, accordingly, increased efficiency of encapsulated drugs has been shown in an experimental model of metastasis.

Conclusions

1. The search for new biomarkers of TNBC, as well as the assessment of their prognostic and therapeutic potential, is currently one of the main tasks in the development of effective individualized treatment programs.

2. Several lines of research seem to be the most promising. The first (diagnostic) is associated with the development of "liquid biopsy" technology and evaluation of biomarkers in the blood, including subpopulations of lymphocytes, spontaneous and induced production of cytokines.

3. To address these standardization issues, an international working group on tumor immunological biomarkers has now been established, as well as analytical centers for immunological monitoring, whose tasks include identification, assessment of prognostic and predictive potential, and validation of biomarkers.

4. Another direction is related to the improvement of the technology of 3D tumor models, which allow modeling the microenvironment and selecting the most specific effects on the tumor, in accordance with the individual biomarkers of a given patient.

5. In the field of TNBC cell therapy, the data of numerous clinical trials are gradually accumulating. The results obtained so far make it possible to determine the dosage, the frequency of administration and the possibility of combination with conventional cytostatic anticancer drugs. To date, EGFR may be a suitable target for cellular immunotherapy in TNBC, and appropriate CAR-T cell products may be promising in the future in the clinical setting.

Conflicting interests

Not declared.

Funding

The research was supported financially by Ministry of Health of the Russian Federation. State assignment 37.15-2021; 121040200135-3.

References

  1. Hwang S-Y, Park S, Kwon Y. Recent therapeutic trends and promising targets in triple negative breast cancer. Pharmacol Ther. 2019;199: 30-57. doi: 10.1016/j.pharmthera.2019.02.006
  2. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021; caac.21660. doi: 10.3322/caac.21660
  3. Kaprin A, Starinsky V, Shakhzadova A. State of oncological care for Russian population in 2019. P.A. Herzen Moscov Res Inst Oncol. 2020, 239 p. (In Russian).
  4. Gucalp A, Traina TA. Triple-Negative Breast Cancer: Adjuvant Therapeutic Options. Chemother Res Pract. 2011;2011: 1-13.
    doi: 10.1155/2011/696208
  5. Zhang MH, Man HT, Zhao XD, Dong N, Ma SL. Estrogen receptor-positive breast cancer molecular signatures and therapeutic potentials (Review). Biomed Reports. 2014;2: 41-52. doi: 10.3892/br.2013.187
  6. Perou CM, Sørlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406: 747-752. doi: 10.1038/35021093
  7. Penault-Llorca F, Viale G. Pathological and molecular diagnosis of triple-negative breast cancer: a clinical perspective. Ann Oncol. 2012;23: vi19-vi22. doi: 10.1093/annonc/mds190
  8. Yeh I-T, Mies C. Application of Immunohistochemistry to Breast Lesions. Arch Pathol Lab Med. 2008;132: 349-358.
    doi: 10.5858/2008-132-349-AOITBL
  9. Prat A, Parker JS, Karginova O, Fan C, Livasy C, Herschkowitz JI, et al. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res. 2010;12: R68. doi: 10.1186/bcr2635
  10. Prat A, Perou CM. Deconstructing the molecular portraits of breast cancer. Mol Oncol. 2011;5: 5-23. doi: 10.1016/j.molonc.2010.11.003
  11. Sharma P. Biology and management of patients with triple-negative breast cancer. Oncologist. 2016;21: 1050-1062. doi: 10.1634/theoncologist.2016-0067
  12. Fleisher B, Clarke C, Ait-Oudhia S. Current advances in biomarkers for targeted therapy in triple-negative breast cancer. Breast Cancer. 2016;8: 183-197. doi: 10.2147/BCTT.S114659
  13. https://clinicaltrials.gov/
  14. Curtis C, Shah SP, Chin S-F, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012;486: 346-352. doi: 10.1038/nature10983
  15. Lehmann BD, Pietenpol JA. Identification and use of biomarkers in treatment strategies for triple-negative breast cancer subtypes. J Pathol. 2014;232: 142-150. doi: 10.1002/path.4280
  16. Burstein MD, Tsimelzon A, Poage GM, Covington KR, Contreras A, Fuqua SAW, et al. Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer. Clin Cancer Res. 2015;21: 1688-1698. doi: 10.1158/1078-0432.CCR-14-0432
  17. Liu Y-R, Jiang Y-Z, Xu X-E, Yu K-D, Jin X, Hu X, et al. Comprehensive transcriptome analysis identifies novel molecular subtypes and subtype-specific RNAs of triple-negative breast cancer. Breast Cancer Res. 2016;18: 33. doi: 10.1186/s13058-016-0690-8
  18. Masuda H, Baggerly KA, Wang Y, Zhang Y, Gonzalez-Angulo AM, Meric-Bernstam F, et al. Differential Response to Neoadjuvant Chemotherapy Among 7 Triple-Negative Breast Cancer Molecular Subtypes. Clin Cancer Res. 2013;19: 5533-5540. doi: 10.1158/1078-0432.CCR-13-0799
  19. Talukdar Y, Rashkow JT, Lalwani G, Kanakia S, Sitharaman B. The effects of graphene nanostructures on mesenchymal stem cells. Biomaterials. 2014;35: 4863-4877. doi: 10.1016/j.biomaterials.2014.02.054
  20. Speiser JJ, Erşahin Ç, Osipo C. The functional role of notch signaling in triple-negative breast cancer. Vitamins & Hormones. 2013; 93: 277-306. doi: 10.1016/B978-0-12-416673-8.00013-7
  21. Miele L, Espinoza I, Pochampally, Watabe, Xing F. Notch signaling: targeting cancer stem cells and epithelial-to-mesenchymal transition. Onco Targets Ther. 2013; 1249. doi: 10.2147/OTT.S36162
  22. Corda G, Sala G, Lattanzio R, Iezzi M, Sallese M, Fragassi G, et al. Functional and prognostic significance of the genomic amplification of frizzled 6 ( FZD6 ) in breast cancer. J Pathol. 2017;241: 350-361. doi: 10.1002/path.4841
  23. Yin S, Xu L, Bonfil RD, Banerjee S, Sarkar FH, Sethi S, et al. Tumor-Initiating Cells and FZD8 Play a Major Role in Drug Resistance in Triple-Negative Breast Cancer. Mol Cancer Ther. 2013;12: 491-498. doi: 10.1158/1535-7163.MCT-12-1090
  24. Li W, Yang H, Li X, Han L, Xu N, Shi A. Signaling pathway inhibitors target breast cancer stem cells in triple-negative breast cancer. Oncol Rep. 2018. doi: 10.3892/or.2018.6805
  25. Bhateja P, Cherian M, Majumder S, Ramaswamy B. The hedgehog signaling pathway: a viable target in breast cancer? Cancers (Basel). 2019;11: 1126. doi: 10.3390/cancers11081126
  26. Xu X, Zhang L, He X, Zhang P, Sun C, Xu X, et al. TGF-β plays a vital role in triple-negative breast cancer (TNBC) drug-resistance through regulating stemness, EMT and apoptosis. Biochem Biophys Res Commun. 2018;502: 160-165. doi: 10.1016/j.bbrc.2018.05.139
  27. He L, Gu J, Lim LY, Yuan Z, Mo J. Nanomedicine-mediated therapies to target breast cancer stem cells. Front Pharmacol. 2016;7.
    doi: 10.3389/fphar.2016.00313
  28. Guanizo AC, Fernando CD, Garama DJ, Gough DJ. STAT3: a multifaceted oncoprotein. Growth Factors. 2018;36: 1-14. doi: 10.1080/08977194.2018.1473393
  29. Moreira MP, da Conceição Braga L, Cassali GD, Silva LM. STAT3 as a promising chemoresistance biomarker associated with the CD44 +/high /CD24 -/low /ALDH + BCSCs-like subset of the triple-negative breast cancer (TNBC) cell line. Exp Cell Res. 2018;363: 283-290. doi: 10.1016/j.yexcr.2018.01.018
  30. Cristofanilli M, Hayes DF, Budd GT, Ellis MJ, Stopeck A, Reuben JM, et al. Circulating tumor cells: a novel prognostic factor for newly diagnosed metastatic breast cancer. J Clin Oncol. 2005;23: 1420-1430. doi: 10.1200/JCO.2005.08.140
  31. Cristofanilli M, Pierga J-Y, Reuben J, Rademaker A, Davis AA, Peeters DJ, et al. The clinical use of circulating tumor cells (CTCs) enumeration for staging of metastatic breast cancer (MBC): International expert consensus paper. Crit Rev Oncol Hematol. 2019;134: 39-45. doi: 10.1016/j.critrevonc.2018.12.004
  32. Munzone E, Botteri E, Sandri MT, Esposito A, Adamoli L, Zorzino L, et al. Prognostic value of circulating tumor cells according to immunohistochemically defined molecular subtypes in advanced breast cancer. Clin Breast Cancer. 2012;12: 340-346. doi: 10.1016/j.clbc.2012.07.001
  33. Smerage JB, Barlow WE, Hortobagyi GN, Winer EP, Leyland-Jones B, Srkalovic G, et al. Circulating tumor cells and response to chemotherapy in metastatic breast cancer: SWOG S0500. J Clin Oncol. 2014;32: 3483-3489. doi: 10.1200/JCO.2014.56.2561
  34. Qin J-J, Yan L, Zhang J, Zhang W-D. STAT3 as a potential therapeutic target in triple negative breast cancer: a systematic review.
    J Exp Clin Cancer Res. 2019;38: 195. doi: 10.1186/s13046-019-1206-z
  35. Evans DG, Howell A, Ward D, Lalloo F, Jones JL, Eccles DM. Prevalence of BRCA1 and BRCA2 mutations in triple negative breast cancer. J Med Genet. 2011;48: 520-522. doi: 10.1136/jmedgenet-2011-100006
  36. Kuroda H, Sakamoto G, Ohnisi K, Itoyama S. Clinical and pathological features of glycogen-rich clear cell carcinoma of the breast. Breast Cancer. 2005;12: 189-195. doi: 10.2325/jbcs.12.189
  37. Domagala P, Jakubowska A, Jaworska-Bieniek K, Kaczmarek K, Durda K, Kurlapska A, et al. Prevalence of germline mutations in genes engaged in dna damage repair by homologous recombination in patients with triple-negative and hereditary non-triple-negative breast cancers. PLoS One. 2015;10: e0130393. doi: 10.1371/journal.pone.0130393
  38. Sun K, Mikule K, Wang Z, Poon G, Vaidyanathan A, Smith G, et al. A comparative pharmacokinetic study of PARP inhibitors demonstrates favorable properties for niraparib efficacy in preclinical tumor models. Oncotarget. 2018;9: 37080-7096. doi: 10.18632/oncotarget.26354
  39. Burnet M. Cancer. A Biological Approach: I. The Processes Of Control. II. The Significance of Somatic Mutation. BMJ. 1957;1: 779-786. doi: 10.1136/bmj.1.5022.779
  40. He J, Lv P, Yang X, Chen Y, Liu C, Qiu X. Pretreatment lymphocyte to monocyte ratio as a predictor of prognosis in patients with early-stage triple-negative breast cancer. Tumor Biol. 2016;37: 9037-9043. doi: 10.1007/s13277-016-4793-8
  41. Losada B, Guerra JA, Malón D, Jara C, Rodriguez L, Del Barco S. Pretreatment neutrophil/lymphocyte, platelet/lymphocyte, lymphocyte/monocyte, and neutrophil/monocyte ratios and outcome in elderly breast cancer patients. Clin Transl Oncol. 2019;21: 855-863. doi: 10.1007/s12094-018-1999-9
  42. Batalha S, Ferreira S, Brito C. The Peripheral immune landscape of breast cancer: clinical findings and in vitro models for biomarker discovery. Cancers (Basel). 2021;13: 1305. doi: 10.3390/cancers13061305
  43. Hung C-H, Chen F-M, Lin Y-C, Tsai M-L, Wang S-L, Chen Y-C, et al. Altered monocyte differentiation and macrophage polarization patterns in patients with breast cancer. BMC Cancer. 2018;18: 366. doi: 10.1186/s12885-018-4284-y
  44. Zhang B, Cao M, He Y, Liu Y, Zhang G, Yang C, et al. Increased circulating M2-like monocytes in patients with breast cancer. Tumor Biol. 2017;39: 101042831771157. doi: 10.1177/1010428317711571
  45. Lafrenie RM, Speigl L, Buckner CA, Pawelec G, Conlon MS, Shipp C. Frequency of immune cell subtypes in peripheral blood correlates with outcome for patients with metastatic breast cancer treated with high-dose chemotherapy. Clin Breast Cancer. 2019;19: 433-442. doi: 10.1016/j.clbc.2019.05.002
  46. Holl EK, Frazier VN, Landa K, Beasley GM, Hwang ES, Nair SK. Examining peripheral and tumor cellular immunome in patients with cancer. Front Immunol. 2019;10. doi: 10.3389/fimmu.2019.01767
  47. Wculek SK, Cueto FJ, Mujal AM, Melero I, Krummel MF, Sancho D. Dendritic cells in cancer immunology and immunotherapy. Nat Rev Immunol. 2020;20: 7-24. doi: 10.1038/s41577-019-0210-z
  48. Lee H, Lee HJ, Song IH, Bang WS, Heo S-H, Gong G, et al. CD11c-positive dendritic cells in triple-negative breast cancer. In Vivo. 2018;32: 1561-1569. doi: 10.21873/invivo.11415
  49. Kini Bailur J, Gueckel B, Pawelec G. Prognostic impact of high levels of circulating plasmacytoid dendritic cells in breast cancer.
    J Transl Med. 2016;14: 151. doi: 10.1186/s12967-016-0905-x
  50. Verma C, Kaewkangsadan V, Eremin JM, Cowley GP, Ilyas M, El-Sheemy MA, et al. Natural killer (NK) cell profiles in blood and tumour in women with large and locally advanced breast cancer (LLABC) and their contribution to a pathological complete response (PCR) in the tumour following neoadjuvant chemotherapy (NAC): differential rest. J Transl Med. 2015;13: 180. doi: 10.1186/s12967-015-0535-8
  51. Foulds GA, Vadakekolathu J, Abdel-Fatah TMA, Nagarajan D, Reeder S, Johnson C, et al. Immune-phenotyping and transcriptomic profiling of peripheral blood mononuclear cells from patients with breast cancer: identification of a 3 gene signature which predicts relapse of triple negative breast cancer. Front Immunol. 2018;9. doi: 10.3389/fimmu.2018.02028
  52. Bates JP, Derakhshandeh R, Jones L, Webb TJ. Mechanisms of immune evasion in breast cancer. BMC Cancer. 2018;18: 556. doi: 10.1186/s12885-018-4441-3
  53. Adams S, Gray RJ, Demaria S, Goldstein L, Perez EA, Shulman LN, et al. Prognostic value of tumor-infiltrating lymphocytes in triple-negative breast cancers from two Phase III randomized adjuvant breast cancer trials: ECOG 2197 and ECOG 1199. J Clin Oncol. 2014;32: 2959-2966. doi: 10.1200/JCO.2013.55.0491
  54. He L, Wang Y, Wu Q, Song Y, Ma X, Zhang B, et al. Association between levels of tumor-infiltrating lymphocytes in different subtypes of primary breast tumors and prognostic outcomes: a meta-analysis. BMC Womens Health. 2020;20: 194.
    doi: 10.1186/s12905-020-01038-x
  55. Mao Y, Qu Q, Chen X, Huang O, Wu J, Shen K. The prognostic value of tumor-infiltrating lymphocytes in breast cancer: a systematic review and meta-analysis. Tagliabue E, editor. PLoS One. 2016;11: e0152500. doi: 10.1371/journal.pone.0152500
  56. Salimi M, Wang R, Yao X, Li X, Wang X, Hu Y, et al. Activated innate lymphoid cell populations accumulate in human tumour tissues. BMC Cancer. 2018;18: 341. doi: 10.1186/s12885-018-4262-4
  57. Onesti CE, Josse C, Boulet D, Thiry J, Beaumecker B, Bours V, et al. Blood eosinophilic relative count is prognostic for breast cancer and associated with the presence of tumor at diagnosis and at time of relapse. Oncoimmunology. 2020;9. doi: 10.1080/2162402X.2020.1761176
  58. Varricchi G, Galdiero MR, Loffredo S, Lucarini V, Marone G, Mattei F, et al. Eosinophils: The unsung heroes in cancer? Oncoimmunology. 2018;7: e1393134. doi: 10.1080/2162402X.2017.1393134
  59. Aponte-López A, Fuentes-Pananá EM, Cortes-Muñoz D, Muñoz-Cruz S. Mast Cell, the Neglected Member of the Tumor Microenvironment: Role in Breast Cancer. J Immunol Res. 2018;2018: 1-11. doi: 10.1155/2018/2584243
  60. Rajput AB, Turbin DA, Cheang MC, Voduc DK, Leung S, Gelmon KA, et al. Stromal mast cells in invasive breast cancer are a marker of favourable prognosis: a study of 4,444 cases. Breast Cancer Res Treat. 2008;107: 249-257. doi: 10.1007/s10549-007-9546-3
  61. Yu X, Zhang Z, Wang Z, Wu P, Qiu F, Huang J. Prognostic and predictive value of tumor-infiltrating lymphocytes in breast cancer: a systematic review and meta-analysis. Clin Transl Oncol. 2016;18: 497-506. doi: 10.1007/s12094-015-1391-y
  62. Mahmoud SMA, Paish EC, Powe DG, Macmillan RD, Grainge MJ, Lee AHS, et al. Tumor-infiltrating CD8+ lymphocytes predict clinical outcome in breast cancer. J Clin Oncol. 2011;29: 1949-1955. doi: 10.1200/JCO.2010.30.5037
  63. Irshad S, Flores-Borja F, Lawler K, Monypenny J, Evans R, Male V, et al. RORγt+ Innate lymphoid cells promote lymph node metastasis of breast cancers. Cancer Res. 2017;77: 1083-1096. doi: 10.1158/0008-5472.CAN-16-0598
  64. Iwamoto M, Shinohara H, Miyamoto A, Okuzawa M, Mabuchi H, Nohara T, et al. Prognostic value of tumor-infiltrating dendritic cells expressing CD83 in human breast carcinomas. Int J Cancer. 2003;104: 92-97. doi: 10.1002/ijc.10915
  65. Brown JR, Wimberly H, Lannin DR, Nixon C, Rimm DL, Bossuyt V. Multiplexed Quantitative analysis of CD3, CD8, and CD20 predicts response to neoadjuvant chemotherapy in breast cancer. Clin Cancer Res. 2014;20: 5995-6005. doi: 10.1158/1078-0432.CCR-14-1622
  66. Gu-Trantien C, Loi S, Garaud S, Equeter C, Libin M, de Wind A, et al. CD4+ follicular helper T cell infiltration predicts breast cancer survival. J Clin Invest. 2013;123: 2873-2892. doi: 10.1172/JCI67428
  67. Oshi M, Newman S, Tokumaru Y, Yan L, Matsuyama R, Endo I, et al. Inflammation is associated with worse outcome in the whole cohort but with better outcome in triple-negative subtype of breast cancer patients. J Immunol Res. 2020;2020: 1-17. doi: 10.1155/2020/5618786
  68. Martínez-Pérez C, Kay C, Meehan J, Gray M, Dixon JM, Turnbull AK. The IL6-like cytokine family: Role and biomarker potential in breast cancer. J Pers Med. 2021;11: 1073. doi: 10.3390/jpm11111073
  69. Ma Y, Ren Y, Dai Z-J, Wu C-J, Ji Y-H, Xu J. IL-6, IL-8 and TNF-α levels correlate with disease stage in breast cancer patients. Adv Clin Exp Med. 2017;26: 421-426. doi: 10.17219/acem/62120
  70. Zuccari DAP de C, Leonel C, Castro R, Gelaleti GB, Jardim BV, Moscheta MG, et al. An immunohistochemical study of interleukin-8 (IL-8) in breast cancer. Acta Histochem. 2012;114: 571-576. doi: 10.1016/j.acthis.2011.10.007
  71. Singh JK, Simões BM, Howell SJ, Farnie G, Clarke RB. Recent advances reveal IL-8 signaling as a potential key to targeting breast cancer stem cells. Breast Cancer Res. 2013;15: 210. doi: 10.1186/bcr3436
  72. Todorović-Raković N, Milovanović J. Interleukin-8 in breast cancer progression. J Interf Cytokine Res. 2013;33: 563-570.
    doi: 10.1089/jir.2013.0023
  73. Chang C-M, Lam HP, Hsu H-J, Jiang S-J. Interleukin-10: A double-edged sword in breast cancer. Tzu Chi Med J. 2021;33: 203.
    doi: 10.4103/tcmj.tcmj_162_20
  74. Gao W, Wen H, Liang L, Dong X, Du R, Zhou W, et al. IL20RA signaling enhances stemness and promotes the formation of an immunosuppressive microenvironment in breast cancer. Theranostics. 2021;11: 2564-2580. doi: 10.7150/thno.45280
  75. Li C-J, Chu P-Y, Yiang G-T, Wu M-Y. The Molecular Mechanism of Epithelial-Mesenchymal Transition for Breast Carcinogenesis. Biomolecules. 2019;9: 476. doi: 10.3390/biom9090476
  76. Yu Y, Wang Y, Ren X, Tsuyada A, Li A, Liu LJ, et al. Context-dependent bidirectional regulation of the MutS homolog 2 by transforming growth factor β contributes to chemoresistance in breast cancer cells. Mol Cancer Res. 2010;8: 1633-1642.
    doi: 10.1158/1541-7786.MCR-10-0362
  77. Radosa JC, Stotz L, Müller C, Kaya AC, Solomayer E-F, Radosa MP. Clinical data on immunotherapy in breast cancer. Breast Care. 2020;15: 450-469. doi: 10.1159/000511788
  78. Yardley DA, Weaver R, Melisko ME, Saleh MN, Arena FP, Forero A, et al. EMERGE: A randomized Phase II study of the antibody-drug conjugate glembatumumab vedotin in advanced glycoprotein NMB-expressing breast cancer. J Clin Oncol. 2015;33: 1609-1619.
    doi: 10.1200/JCO.2014.56.2959
  79. Wolska-Washer A, Robak T. Safety and tolerability of antibody-drug conjugates in cancer. Drug Saf. 2019;42: 295-314.
    doi: 10.1007/s40264-018-0775-7
  80. Goldenberg DM, Sharkey RM. Antibody-drug conjugates targeting TROP-2 and incorporating SN-38: A case study of anti-TROP-2 sacituzumab govitecan. MAbs. 2019;11: 987-995. doi: 10.1080/19420862.2019.1632115
  81. Bardia A, Mayer IA, Vahdat LT, Tolaney SM, Isakoff SJ, Diamond JR, et al. Sacituzumab Govitecan-hziy in refractory metastatic triple-negative breast cancer. N Engl J Med. 2019;380: 741-751. doi: 10.1056/NEJMoa1814213
  82. Nejadmoghaddam M-R, Minai-Tehrani A, Ghahremanzadeh R, Mahmoudi M, Dinarvand R, Zarnani A-H. Antibody-Drug conjugates: Possibilities and challenges. Avicenna J Med Biotechnol. 11: 3-23. Available: http://www.ncbi.nlm.nih.gov/pubmed/30800238
  83. Gomez-Roca CA, Boni V, Moreno V, Morris JC, Delord J-P, Calvo E, et al. A phase I study of SAR566658, an anti CA6-antibody drug conjugate (ADC), in patients (Pts) with CA6-positive advanced solid tumors (STs)(NCT01156870). J Clin Oncol. 2016;34: 2511-2511. doi: 10.1200/JCO.2016.34.15_suppl.2511
  84. Ahmadzadeh M, Johnson LA, Heemskerk B, Wunderlich JR, Dudley ME, White DE, et al. Tumor antigen-specific CD8 T cells infiltrating the tumor express high levels of PD-1 and are functionally impaired. Blood. 2009;114: 1537-1544. doi: 10.1182/blood-2008-12-195792
  85. Salmaninejad A, Khoramshahi V, Azani A, Soltaninejad E, Aslani S, Zamani MR, et al. PD-1 and cancer: molecular mechanisms and polymorphisms. Immunogenetics. 2018;70: 73-86. doi: 10.1007/s00251-017-1015-5
  86. Boussiotis VA. Molecular and biochemical aspects of the PD-1 checkpoint pathway. Longo DL, editor. N Engl J Med. 2016;375: 1767-1778. doi: 10.1056/NEJMra1514296
  87. Van Berckelaer C, Rypens C, van Dam P, Pouillon L, Parizel M, Schats KA, et al. Infiltrating stromal immune cells in inflammatory breast cancer are associated with an improved outcome and increased PD-L1 expression. Breast Cancer Res. 2019;21: 28.
    doi: 10.1186/s13058-019-1108-1
  88. Bertucci F, Gonçalves A. Immunotherapy in breast cancer: the emerging role of PD-1 and PD-L1. Curr Oncol Rep. 2017;19: 64.
    doi: 10.1007/s11912-017-0627-0
  89. Stover DG, Parsons HA, Ha G, Freeman SS, Barry WT, Guo H, et al. Association of cell-free DNA tumor fraction and somatic copy number alterations with survival in metastatic triple-negative breast cancer. J Clin Oncol. 2018;36: 543-553. doi: 10.1200/JCO.2017.76.0033
  90. Schmid P, Rugo HS, Adams S, Schneeweiss A, Barrios CH, Iwata H, et al. Atezolizumab plus nab-paclitaxel as first-line treatment for unresectable, locally advanced or metastatic triple-negative breast cancer (IMpassion130): updated efficacy results from a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol. 2020;21: 44-59. doi: 10.1016/S1470-2045(19)30689-8
  91. Cortes J, Cescon DW, Rugo HS, Nowecki Z, Im S-A, Yusof MM, et al. Pembrolizumab plus chemotherapy versus placebo plus chemotherapy for previously untreated locally recurrent inoperable or metastatic triple-negative breast cancer (KEYNOTE-355): a randomised, placebo-controlled, double-blind, phase 3 clinical trial. Lancet. 2020;396: 1817-1828. doi: 10.1016/S0140-6736(20)32531-9
  92. Myers SE, Williams SF. Role of high-dose chemotherapy and autologous stem cell support in treatment of breast cancer. Hematol Oncol Clin North Am. 1993;7: 631-645. PMID: 8102137
  93. Hamilton RF, Tsuruoka S, Wu N, Wolfarth M, Porter DW, Bunderson-Schelvan M, et al. Length, but not reactive edges, of cup-stack MWCNT is responsible for toxicity and acute lung inflammation. Toxicol Pathol. 2018;46: 62-74. doi: 10.1177/0192623317732303
  94. Demirer T, Barkholt L, Blaise D, Pedrazzoli P, Aglietta M, Carella AM, et al. Transplantation of allogeneic hematopoietic stem cells: an emerging treatment modality for solid tumors. Nat Clin Pract Oncol. 2008;5: 256-67. doi: 10.1038/ncponc1104
  95. Mondino A, Manzo T. To Remember or to Forget: The Role of good and bad memories in adoptive T cell therapy for tumors. Front Immunol. 2020;11: 1915. doi: 10.3389/fimmu.2020.01915
  96. Sahin U, Derhovanessian E, Miller M, Kloke B-P, Simon P, Löwer M, et al. Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer. Nature. 2017;547: 222-226. doi: 10.1038/nature23003
  97. Davari K, Holland T, Prassmayer L, Longinotti G, Ganley KP, Pechilis LJ, et al. Development of a CD8 co-receptor independent T-cell receptor specific for tumor-associated antigen MAGE-A4 for next generation T-cell-based immunotherapy. J Immunother cancer. 2021;9. doi: 10.1136/jitc-2020-002035
  98. Sommaggio R, Cappuzzello E, Dalla Pietà A, Tosi A, Palmerini P, Carpanese D, et al. Adoptive cell therapy of triple negative breast cancer with redirected cytokine-induced killer cells. Oncoimmunology. 2020;9. doi: 10.1080/2162402X.2020.1777046
  99. Xia L, Zheng Z-Z, Liu J-Y, Chen Y-J, Ding J-C, Xia N-S, et al. EGFR-targeted CAR-T cells are potent and specific in suppressing triple-negative breast cancer both in vitro and in vivo. Clin Transl Immunol. 2020;9: e01135. doi: 10.1002/cti2.1135
  100. Wallstabe L, Göttlich C, Nelke LC, Kühnemundt J, Schwarz T, Nerreter T, et al. ROR1-CAR T cells are effective against lung and breast cancer in advanced microphysiologic 3D tumor models. JCI insight. 2019;4. doi: 10.1172/jci.insight.126345
  101. Stüber T, Monjezi R, Wallstabe L, Kühnemundt J, Nietzer SL, Dandekar G, et al. Inhibition of TGF-β-receptor signaling augments the antitumor function of ROR1-specific CAR T-cells against triple-negative breast cancer. J Immunother Cancer. 2020;8: e000676.
    doi: 10.1136/jitc-2020-000676
  102. Xia L, Zheng Z, Liu J, Chen Y, Ding J, Hu G, et al. Targeting Triple-Negative Breast Cancer with Combination Therapy of EGFR CAR T Cells and CDK7 Inhibition. Cancer Immunol Res. 2021;9: 707-722. doi: 10.1158/2326-6066.CIR-20-0405
  103. Zhang K, Fu H, Xing C, Luo Y, Cheng F, Fu Q, et al. "Don’t eat me/eat me" – combined apoptotic body analogues for efficient targeted therapy of triple-negative breast cancer. J Mater Chem B. 2021;9: 8472-8479. doi: 10.1039/d1tb01116b

Volume 11, Number 2
06/30/2022

Download PDF version

doi 10.18620/ctt-1866-8836-2022-11-2-16-30
Submitted 05 April 2022
Accepted 24 June 2022

Back to the list