FGFR‑related phenotypic and functional profile of CAFs in prognostication of breast cancer (Review)
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- Published online on: August 26, 2024 https://doi.org/10.3892/ijo.2024.5682
- Article Number: 94
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Copyright: © Solek et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Fibroblast growth factor (FGF) receptor (FGFR)-mediated interactions between tumour microenvironment (TME) and breast cancer (BC) cells in progression and response to therapy are well documented (1,2). While preclinical studies consistently implicate FGFR signalling in BC development, clinical evidence to support its pro-tumorigenic role is still missing (3,4). One of the possible reasons for the discordance between mechanistic and clinical findings as well as disappointing results of clinical trials with FGFR inhibitors in BC (5,6) may be an inability of in vitro models to truly represent an in vivo setting and biological complexity of the TME. As FGFR-pathway is regulated by TME-derived stimuli, the clinical value of FGFR in BC ought to be analysed in the context of the stromal component, activating or repressing its function, in particular, cancer-associated fibroblasts (CAFs), that either directly (cognate ligands; FGFs) or indirectly (various factors enhancing CAFs' paracrine activity), may affect FGFR signalling (7,8).
CAFs, the most abundant cellular component of the TME present a highly heterogenous population, whose remarkable phenotypic and functional diversity is due mostly to distinct cellular origins, such as resident fibroblasts, bone marrow-derived mesenchymal stem cells, pericytes, endothelial or cancer cell (9). Various factors produced by cancer cells, host immune or other stromal cells, for example tumour growth factor β (TGF-β), platelet-derived growth factor (PDGF), sonic hedgehog (HH), interleukin 6 (IL-6), and a wide array of chemokines (9-18), induce differentiation and activation of CAFs. CAFs participate in various aspects of carcinogenesis, interacting directly and/or indirectly with tumour cells as well as various components of TME including myeloid cells. They have been most extensively investigated in the context tumour immunosuppressive microenvironment and its potential clinical significance (19,20). In BC, CAFs have been shown to promote cancer cell proliferation, remodelling of the extracellular matrix (ECM), angiogenesis and metastasis as well as modulate immune responses and drug resistance (19). This suggests that the overall impact of CAFs on tumour progression, and hence disease prognosis, is determined by the spatio-temporal pattern of their distribution and activation. A series of excellent recent reviews discuss various aspects of CAFs' biology, their impact on progression and responsiveness to therapy in several solid tumours, including BC.
Unequivocal documentation of CAFs is notoriously difficult, as none of the available phenotypic markers are entirely specific or exclusive. Inherent plasticity between CAFs subtypes further conceals their true phenotypic identity (20-23). Most commonly, CAFs are being detected on the basis of their morphology, positivity for mesenchymal biomarkers, for example alpha-smooth muscle actin (αSMA), fibroblast-activating protein (FAP), fibroblast-specific protein (FSP/S100A4) and platelet-derived growth factor receptor-β (PDGFRβ) as well as lack of expression of lineages markers for epithelial, endothelial or hematopoietic cells (20,21,23). However, because of their dynamic interactions with the tumour and other TME components, not a single marker, but a panel of phenotypically- and functionally-related features, so-called 'a stromal signature', is better positioned to define CAFs with regards to patients' prognosis (24). And indeed, several molecular stromal signatures have already been shown to have a prognostic and predictive value, complementary to that of phenotypic markers of the BC epithelial compartment (25,26).
There is growing evidence to suggest that through their secretome, encompassing a range of biologically active molecules such as growth factors, chemokines and cytokines, CAFs influence the course of BC development (1,27). In particular, being a source of FGF ligands, they act as paracrine upstream regulators of FGFR likely to affect BC evolution and development of therapy resistance (1,28-31).
Based on the reported data, a panel of stroma-derived factors was selected, called henceforth an 'FGFR-related CAFs' profile', that enables identification of a subpopulation of CAFs [phenotypic markers: αSMA, S100A4/fibroblast-specific protein 1 (FSP-1), PDGFR, podoplanin (PDPN), FAP (20,21)], with characteristics indicative of their potential regulatory effect on the FGF/FGFR axis [factors inducing CAFs paracrine activity: transforming growth factor (TGF)-β1, HDGF, PDGF, CXCL8, C-C motif chemokine ligand (CCL) 5, CCL2, IL-6, HH and EGF (32,33) and 3 CAFs-derived cognate FGF ligands: FGF2, FGF5 and FGF17 (34-38)] (Table I).
In the present study, existing data on the prognostic and, where available, predictive significance of the individual components of the so designed 'CAFs' profile' were summarized. To the best of our knowledge this is the first attempt to define the traits of CAFs specifically relevant to the activity of FGFR. Such a profile may represent a 'missing link' in the translation between mechanistic and clinical studies, thus supporting an evaluation of the true value of FGFR in BC prognostication (Fig. 1 and Table II).
Table IIReported associations between components of FGFR-related CAFs' profile, clinicopathological and prognostic variables. |
The data have been organized into distinct paragraphs based on the tissue of origin of specific marker/s, whether expressed in the tissue (including the cytosol) or circulating in the blood (a substantial and easily accessible portion of the CAFs secretome). Details regarding the literature search, including a flowchart, are provided in Fig. 2.
Tissue proteins
Phenotypic markers αSMA
αSMA, a general marker of mesenchymal cells, is the most reliable marker of CAFs with a myofibroblast morphology (39). Alpha SMA can exist in a globular (G-actin) or filamentous (F-actin) form. The incorporation of αSMA into stress fibres, associated with the transition between G and F actin states, enhances the contractile properties of CAFs as well as the tension of the surrounding ECM (30). Via a mechanical feedback loop, αSMA-containing stress fibres participate in multiple cellular functions, ranging from the maintenance of cell shape and polarity to endosome dynamics and secretory pathways (39,40). Phenotypic transition into myofibroblasts and acquisition of the contractile features is one of the central traits of the activated stroma. It can be induced through several mechanisms, including auto- and paracrine stimulation by growth factors or cytokines (41). Activated myofibroblasts, in turn, secrete a number of soluble modulators, which contribute to ECM remodelling and, in cancer, promote invasiveness (39).
In BC, overexpression of αSMA in the stroma is consistently shown to be associated with unfavourable prognosis-an increased risk of metastases, shorter overall survival (OS) and disease-free survival (DFS) (28,42-47). Upregulation of αSMA was found to correlate with tumour high grade and positive nodal status (44,47,48). In human epidermal growth factor receptor 2 (HER2)-enriched BC, co-expression of αSMA, FGF5 and FGFR2, associated with upregulated c-Src, correlated with poor response to treatment (28), implicating the CAF (αSMA+)-FGF5-FGFR2-c-Src axis in development of resistance to HER2-targeted therapies. This was further supported by a demonstration of a link between αSMA overexpression in the stromal compartment and resistance to trastuzumab in patients with BC (45).
S100A4/FSP-1
S100A4 protein or FSP-1, localized in the cytoplasm and/or nucleus, is involved in the regulation of a number of cellular processes including cell cycle progression and differentiation. S100A4 is a polypeptide with two calcium-binding motifs, known to regulate, in a calcium-dependent manner, various cytoplasmic proteins, including the cytoskeletal components. The structural conformation of S100A4 upon calcium binding facilitates its interaction with RAGE on fibroblasts, activating intracellular signalling cascades such as the MAPK/ERK pathway (49). Furthermore, being secreted to the TME by activated stromal cells such as fibroblasts and immune cells, S100A4 supports growth factors release and angiogenesis, thus promoting tumour progression and metastasis (50). In macrophages, S100A4 binds to several intracellular proteins, which through the changes in cytoskeletal dynamics, promotes their recruitment to the tumour vicinity. In addition, S100A4 contributes to the pro-tumour macrophage polarization (51).
S100A4+ CAFs derive from adipocytes, post-epithelialmesenchymal transition (EMT) cancer cells or mesenchymal stem cells (52). S100A4+ CAFs play a tumour-protecting role in immune surveillance. In S100A4-deficient mice, mammary tumours do not metastasize (52). Furthermore, through secretion of vascular endothelial growth factor and tenascin C, S100A4+ CAFs participate in setting-up a pre-metastatic niche in the lung (53).
In patients with BC, S100A4 is an unfavourable prognostic factor and its upregulation correlates with tumour high grade and shorter OS (47,54-58). S100A4 expression varies between BC molecular subtypes and histologic features of the stroma (59). Upregulation of S100A4 in stromal cells was found to be associated with estrogen receptor (ER)-negativity and nodal metastases (54,56).
PDGFRα/β
PDGFR plays a critical role in tissue remodelling, scarring and fibrosis (60). It exists in two isoforms (PDGFRα and PDGFRβ) and is expressed in normal fibroblasts, pericytes, vascular smooth muscle cells, myocardiocytes and CAFs (21,61). Both PDGFRα and PDGFRβ are receptor tyrosine kinases with an extracellular ligand-binding domain, a single transmembrane helix, and an intracellular tyrosine kinase domain. Binding of PDGF ligands to PDGFRα/β expressed on CAFs, induces receptor dimerization, autophosphorylation and its subsequent activation. This promotes secretion of collagen and other ECM components, that by enhancing the formation of the fibrotic stroma, support tumour development (30). PDGFR-mediated signalling induces transformation of pericytes into CAFs with enhanced secretory and inflammatory features (61,62). In particular, through FGF2 and FGF7, PDGFR+ CAFs promote neo-angiogenesis and cancer cell proliferation (63).
In BC, stromal PDGRFβ overexpression is associated with unfavourable clinicopathological characteristics such as high histological grade, larger tumour size (T), ER-negativity, upregulated HER2, as well as shorter DFS, recurrence-free survival (RFS) and OS (64-66). Expression of stromal PDGRβ was found prognostically significant particularly in tumours from premenopausal patients (67). Furthermore, randomized clinical studies of two BC cohorts identified stromal PDGFRβ as a marker of a therapeutic benefit of tamoxifen in early BC (65).
PDPN
PDPN, a mucin-type glycoprotein, promotes cancer cell migration and invasiveness and is expressed on fibroblasts, macrophages and tumour cells (20). PDPN is a transmembrane mucin-type glycoprotein with an extracellular domain rich in O-glycosylation sites. The single transmembrane helix anchors PDPN in the cell membrane and plays a role in transmitting signals from the extracellular environment to the intracellular activation of the RhoA/ROCK signalling pathway, which is involved in cytoskeletal dynamics, cell contractility and motility (68). Several studies demonstrated a positive association between increased levels of stromal PDPN, tumour grade, size (T), nodal status, ER- and progesterone receptor (PR)-negativity as well as shorter DFS and OS (47,52,69-73). Friedman et al (52) showed that, together with S100A4, PDPN may be instrumental in identification of CAF subpopulations, the ratio of which, having clinical implications across BC subtypes, is particularly correlated with BRCA mutations in triple-negative BC (TNBC). It was also demonstrated that the phenotypic composition of CAF population tends to fluctuate over time of cancer development. This supports the concept of CAFs' plasticity, as a key trait of a dynamic TME, co-evolving with the tumour, to nurture and provide a permissive microenvironment for its continuous growth (52).
FAP
FAP is a transmembrane serine protease with both dipeptidyl peptidase and endopeptidase activities. FAP's proteolytic activity allows it to degrade components of the ECM, such as gelatin, collagen and fibronectin. By ECM lysis, FAP generates bioactive fragments that can activate pro-tumorigenic signalling pathways in CAFs (74). FAP is a surface marker of activated fibroblasts in >90% of cancers (21). FAP-expressing CAFs are involved in various cancer-related processes, for example ECM-remodelling, but their key pro-tumorigenic role is ascribed to an impact on immune cell polarization and development of immunosuppressive TME (21). A number of FAP+ CAF-derived soluble effector molecules, such as stromal-derived factor 1 and CCL2, have been implicated in creation of an environment facilitating tumour development (75). In particular, FAP+ CAF-mediated activation of the uPAR-FAK-c-Src-JAK2-STAT3-CCL2 cascade enables recruitment of circulating myeloid-derived stem cells expressing CCR2, a cognate CCL2 receptor (21). Lo et al (76) demonstrated a correlation between FAP overexpression in CAFs and regulatory T cell-dependent immunosuppression. Accordingly, in BC, increased FAP+ CAFs were associated with features of poor prognosis, such as distant metastases and decreased RFS (77-79). By contrast, Ariga et al (78) has found high density of FAP+ CAFs prognostic of a longer OS and DFS (78), suggesting that FAP overexpression may also be related to extensive tissue remodelling and ECM turnover.
Activating factors
TGF-β1
The TGF-β, a large family of structurally related cytokines and growth factors, are involved in a vast number of cellular processes in development and homoeostasis of most human tissues. TGF-β1, in particular, a key regulator of the synthesis and expression of collagen, elastin and MMPs, acts through the canonical Smad-dependent and non-Smad pathways, that involve a number of receptors and interacting networks, and is strongly implicated in the pathogenesis of fibrosis (80,81). The major targets of TGF-β1 are fibroblasts, but other cell types, including macrophages, epithelial and vascular cells are also affected. In tumours, expressed at high level, TGF-β1 mediates EMT, promotes angiogenesis, and together with IL-1β, induces expression of FAP in fibroblasts (20). It is widely acknowledged, that an overall outcome of TGF-β1 activity depends on a type of a cell and its microenvironment. TGF-β1 was demonstrated to significantly affect both the fibroblast-myofibroblast transition and the rate of invasion (82). Koumoundourou et al (83) has also shown that downregulation of TGF-β1 in BC tissue was a marker of poor prognosis and recurrence. Using immunohistochemistry for TGF-β1, pSmad2/3 and Smad4, the authors demonstrated an inverse association between TGF-β1 and PR, as well as between Smad4 and ER, but not with any other clinicopathological features. Interestingly, although neither TGF-β1 nor pSmad2/3 were related to ER, loss of pSmad2/3 expression was prognostic of a shorter DFS in all patients, including those with ER-positive BC (83). Tissue expression of TGF-β1 and survivin was evaluated in BC samples by Liu et al (84), who found that, although none of them, separately, had an independent prognostic value, increased TGF-β1/survivin co-expression was associated with shorter OS and PFS in patients with TNBC (84).
HDGF
Heparin binding growth factor or hepatoma-derived growth factor (HDGF) shares homology with the high mobility group 1 protein and was first purified from a human hepatoma-derived cell line (85). Widely expressed in normal tissues, HDGF promotes proliferation of various cells, including fibroblasts, as both a DNA-binding nuclear factor and a secreted protein via a receptor-mediated pathway (86). In BC, Chen et al (87) demonstrated that strong expression of nuclear HDGF was associated with high tumour grade, high stage, high proliferation index (Ki-67 index >20%), lymph node metastases and shorter RFS. This was confirmed by Qiu et al (88), who reported a negative correlation between high expression of HDGF and DFS.
PDGF
PDGF is a growth factor that is secreted by cancer cells and induces activation of fibroblasts (89). There are five PDGF isoforms (A-D) but only PDGF-A and -B can form functional heterodimers, that stimulate their cognate receptors (90). In most tumours, populations of PDGF-expressing cancer cells are markedly denser than those positive for PDGFR, which indicates that PDFG plays a role as a mediator of paracrine activity of cancer cells towards the neighbouring stroma (90). The primary effect of PDGF on fibroblasts is their recruitment and stimulation of proliferation with, unlike TGF-β, no influence on the phenotypic switch into myofibroblasts (90). In BC, high expression of PDGF (AA and BB) was found to be correlated with high grade, high Ki67, young age (<50 years), tumour size, triple negativity and shorter DFS (91). Moreover, confirmed to be associated with poor prognosis in stage IV BC, PDGF (AA, BB, CC) was also shown to be predictive of a low response rate to chemotherapy (92).
Cytokines
The role of CAFs in orchestration of inflammation in immune TME is well recognized (62). Both target and source of a number of immune-modulatory and chemo-attractive mediators such as Chemokine (C-X-C motif) ligand 8 (CXCL8), CCL5, CCL2 and IL-6, CAFs participate in the recruitment of suppressive myeloid and regulatory T cells, polarization of M2 macrophages, suppression of cytotoxic lymphocytes and dendritic cells, that contribute to the modulation of TME towards tumour-promoting immunosuppressive environment (62,93).
CXCL8, CCL2 and CCL5, essential components of the tumour-stroma-inflammatory network, are associated with aggressive BC phenotype and increased risk of recurrence. Produced mostly by macrophages, these pro-inflammatory chemokines attract and activate resident immune cells (93), induce EMT (94), promote tumour metastasis (95) as well as modify tumour response to therapy (96). Higher levels of these three chemokines were shown to be associated predominantly with basal BC (93). Several studies have demonstrated an association between high expression of CCL2, high grade, lymph node metastases and HER2-negativity as well as shorter DFS and RFS (97,98). CCL5 was analysed by Yamaguchi et al (99), who found that stromal CCL5 was negatively associated with tumour size, as well as ER and PR expression. CCL5 levels significantly correlated with the aggressive phenotype and this was noted particularly in the CCR3-positive tumours (99). Moreover, in another study, expression of CCL5 was prognostic of shortened RFS, suggesting that CCL5 promotes BC progression and contributes to the worse disease outcome (100).
Hedgehog (HH)
The HH-signalling pathway plays a fundamental role in embryonic development of various organs and its dysregulation has been associated with several malignancies. In mammary gland, overactivation of HH-signalling has been suggested to stimulate self-renewal of normal and tumorigenic stem cells, thus promoting BC formation (101). However, prognostic and predictive value of HH pathway in BC still remains largely understudied. In a single study comprising 36 patients with TNBC, activation of HH combined with Wnt pathway identified patients at risk for early recurrence (102).
Cognate ligands-FGFs
FGFs are a family of signalling proteins, which in humans comprises 23 members, with paracrine (FGF1-10, FGF 16-18, FGF 20 and FGF22) or endocrine (FGF19, FGF21 and FGF23) mode of action. FGFs bind with different affinity to one or several of the four transmembrane FGF receptors (FGFR1-4) (103), activation of which, through the Ras-dependent MAPK, PI3K/AKT or STATs-dependent pathways, influences cell proliferation, differentiation and survival (Fig. 1) (104). Cellular responses induced by FGF/FGFR vary between biological contexts, which are determined by a number of factors, including cell type-specific adaptor molecules, signal transduction enhancers, transcription factors and co-activators, as well as interacting other signalling networks (34). Whereas translational significance of FGFRs' alterations in human cancer is being analysed by numerous research groups, albeit with conflicting results, available data on the clinical value of their ligands (FGFs) in BC are scarce, often inconclusive, and restricted only to: FGF2, FGF5 and FGF17. For example, while downregulation of FGF2 was found a marker of poor prognosis (105), its upregulation was associated with both shorter and longer RFS and OS (34,106-108). In a study by Colomer et al (105), downregulation of FGF2 was associated with longer OS and RFS; whereas Granato et al (109) reported that an association with survival parameters was not significant. Moreover, although upregulation of FGF2 correlated with small tumour size and decreased incidence of nodal metastases, it was inconsistently (both low and high) linked to tumour grade (106,107,110,111). Predictive value of FGF2 was reported by Shee et al (34), who demonstrated that its upregulation in ER+ BC was significantly predictive of anti-estrogen resistance and shorter RFS and OS. Upregulation of FGF5 was found to be associated with shorter OS and RFS (28). The only existing study of a prognostic value of FGF17 in BC demonstrated that its upregulation inversely correlated with tumour grade and nodal status (112).
Circulating proteins
aSMA, FAP, PDGFR, S100A4/FSP-1, PDPN, TGF-β1, IL-6
In most studies, increased serum (or plasma) level of aSMA, FAP, PDGFR, S100A4/FSP-1, PDPN, TGF-β1, IL-6 markers have been found to be linked to unfavorable disease indicators such as high grade, metastases and shorter OS (41,92,113-120).
By contrast, for TGF-b1 and IL-6, several studies documented their association with a good disease outcome. For example, Panis et al (121), showed that an early presentation of TNBC (<45 years of age) was associated with high levels of circulating TGF-β1, while in metastatic BC, TGF-β1 plasma concentration was lower than in non-metastatic disease. In a 40-month follow-up, women with low TGF-β1 levels (<20 pg/ml) were shown to have a tendency for a reduced OS and doxorubicin induced decrease in TGF-β1 concentration, promptly after drug infusion. Interestingly, levels of plasma TGF-β1 were not affected by surgical removal of the primary tumour and did not differ between patients with responsive and resistant disease (121). Milovanović et al (122) has found serum concentration of IL-6 as the independent prognostic factor of a good disease outcome.
The discrepancies between the studies are, at least partially, due to the well documented pleiotropy of both cytokines that, via either proor anti-inflammatory activity, may differently affect tumour progression.
CXCL8
Low level of serum CXCL8 was associated with higher pathological complete response of patients with TNBC in response to neoadjuvant chemotherapy (123).
Cytokine clusters
In an attempt to identify the cluster/s that would support the prognostic significance of longitudinal serum cytokine analysis, Paccagnella et al (124) have recently shown in patients with BC treated with eribulin that, after four courses of therapy, low levels of TGF-β, IL-4, IL-6, IL-8, IL-10, CCL-2 and CCL-4 (out of 18 cytokines evaluated) were associated with the best patient survival. This novel approach to design a kind of a prognostic 'serum signature', if validated, may prove very valuable in decision making related to the type and time course of applied therapy (124).
EGF
Known as the main ligand of the epidermal growth factor (EGF) receptor, a dominant oncogenic driver in numerous cancers, EGF plays also an important role in fibroblast differentiation and activation. Signalling from EGF downregulates Rho-GTP levels, which gives permissive signals for Rac1 activation and fibroblast polarization (125). This leads to fibroblast transformation into myofibroblasts which, together with growth-promoting action of TGF-β1, reciprocally promotes cancer cell invasion (125). However, at the clinical level, there is no evidence to demonstrate any translation value of stromal EGF in BC. Results of the only existing study evaluating EGF plasma level have demonstrated no significant associations with clinicopathological features or disease prognosis (126).
FGF2
The data on FGF2 showed that in a parallel evaluation in the serum and tissue, there was no correlation between its tumour expression and the corresponding serum level (105).
In summary, although determination of biomarkers obtainable by liquid biopsy appears to be very attractive for minimally invasive and inexpensive diagnosis and prognostication, the level of a secreted and/or shredded protein in the plasma, being not cell- or tissue-specific, does not faithfully reflect the expression in the analysed organ, and hence its role in the mechanisms of disease development. This implies that a more complex approach combining evaluation of a panel of both serum and histological biomarkers with imaging-based metrics may provide a more efficient tool for clinical practice.
Conclusion and perspectives
Available evidence clearly demonstrates that CAFs contain a valuable prognostic information in BC. While presented studies of single markers (for example αSMA, S100A4, PDGFR or PDPN) identify promising candidates, analyses combining several stromal, either CAFs-specific or CAF-derived features (for example S100A4/PDPN (52), αSMA/FGF5 (28), or PDGFR/FGF2/FGF7 (63) reveal the traits of clinically more significant implications. This indicates that comprehensive analyses of CAFs in relation to other components of the stroma might improve an assessment of CAFs involvement in the tumorigenic process and their value as prognostic and predictive biomarkers.
CAFs are not currently used in routine histopathological practice. The challenge is to design biologically meaningful signatures that would capture essential molecular profiles and could be exploited in prognostication. Given CAFs' heterogeneity, plasticity and an intricate cross-talk with other TEM components, it appears that this could be achieved by profiling the chosen (for example micro-dissected) area of the stroma towards carefully selected panel of makers relevant to specific aspects of BC biology. In particular, the proposed 'FGFR-related stromal profile of CAFs' might provide (after a necessary further clinical validation) the context for an assessment of the true FGFR's clinical value as well as the criteria for further classification of patients with BC for the FGFR-targeted therapy.
Availability of data and materials
Not applicable.
Authors' contributions
JS designed the framework, performed the literature search, prepared the figure and the tables, and wrote the manuscript. MB supervised the research and selection of the literature. RS provided substantive support and critical review. HMR provided the concept and edited the manuscript. All authors have read and approved the final version of the manuscript. Data authentication is not applicable.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Abbreviations:
BC |
breast cancer |
CAFs |
cancer-associated fibroblasts |
DFS |
disease-free survival |
ER |
estrogen receptor |
FGF |
fibroblast growth factor |
FGFR |
fibroblast growth factor receptor |
HER2 |
human epidermal growth factor receptor 2 |
OS |
overall survival |
PR |
progesterone receptor |
RFS |
recurrence-free survival |
TME |
tumour microenvironment |
Acknowledgments
Not applicable.
Funding
The present study was supported by the National Science Centre (grant no. UMO-2020/39/B/NZ4/02696).
References
Santolla MF and Maggiolini M: The FGF/FGFR system in breast cancer: Oncogenic features and therapeutic perspectives. Cancers (Basel). 12:30292020. View Article : Google Scholar : PubMed/NCBI | |
Servetto A, Formisano L and Arteaga CL: FGFR signaling and endocrine resistance in breast cancer: Challenges for the clinical development of FGFR inhibitors. Biochim Biophys Acta Rev Cancer. 1876:1885952021. View Article : Google Scholar : PubMed/NCBI | |
Braun M, Piasecka D, Tomasik B, Mieczkowski K, Stawiski K, Zielinska A, Kopczynski J, Nejc D, Kordek R, Sadej R and Romanska HM: Hormonal receptor status determines prognostic significance of FGFR2 in invasive breast carcinoma. Cancers (Basel). 12:27132020. View Article : Google Scholar : PubMed/NCBI | |
Mieczkowski K, Kitowska K, Braun M, Galikowska-Bogut B, Gorska-Arcisz M, Piasecka D, Stawiski K, Zaczek AJ, Nejc D, Kordek R, et al: FGF7/FGFR2-JunB signalling counteracts the effect of progesterone in luminal breast cancer. Mol Oncol. 16:2823–2842. 2022. View Article : Google Scholar : PubMed/NCBI | |
Meric-Bernstam F, Bahleda R, Hierro C, Sanson M, Bridgewater J, Arkenau HT, Tran B, Kelley RK, Park JO, Javle M, et al: Futibatinib, an irreversible FGFR1-4 inhibitor, in patients with advanced solid tumors harboring FGF/FGFR aberrations: A phase I dose-expansion study. Cancer Discov. 12:402–415. 2022. View Article : Google Scholar | |
Coombes RC, Badman PD, Lozano-Kuehne JP, Liu X, Macpherson IR, Zubairi I, Baird RD, Rosenfeld N, Garcia-Corbacho J, Cresti N, et al: Results of the phase IIa RADICAL trial of the FGFR inhibitor AZD4547 in endocrine resistant breast cancer. Nat Commun. 13:32462022. View Article : Google Scholar : PubMed/NCBI | |
De Luca A, Frezzetti D, Gallo M and Normanno N: FGFR-targeted therapeutics for the treatment of breast cancer. Expert Opin Investig Drugs. 26:303–311. 2017. View Article : Google Scholar : PubMed/NCBI | |
Chew NJ, Lim Kam Sian TCC, Nguyen EV, Shin SY, Yang J, Hui MN, Deng N, McLean CA, Welm AL, Lim E, et al: Evaluation of FGFR targeting in breast cancer through interrogation of patient-derived models. Breast Cancer Res. 23:822021. View Article : Google Scholar : PubMed/NCBI | |
Ronnov-Jessen L, Petersen OW, Koteliansky VE and Bissell MJ: The origin of the myofibroblasts in breast cancer. Recapitulation of tumor environment in culture unravels diversity and implicates converted fibroblasts and recruited smooth muscle cells. J Clin Invest. 95:859–873. 1995. View Article : Google Scholar : PubMed/NCBI | |
Elenbaas B and Weinberg RA: Heterotypic signaling between epithelial tumor cells and fibroblasts in carcinoma formation. Exp Cell Res. 264:169–184. 2001. View Article : Google Scholar : PubMed/NCBI | |
Erez N, Truitt M, Olson P, Arron ST and Hanahan D: Cancer-associated fibroblasts are activated in incipient neoplasia to orchestrate tumor-promoting inflammation in an NF-kappaB-dependent manner. Cancer Cell. 17:135–147. 2010. View Article : Google Scholar : PubMed/NCBI | |
Tejada ML, Yu L, Dong J, Jung K, Meng G, Peale FV, Frantz GD, Hall L, Liang X, Gerber HP and Ferrara N: Tumor-driven paracrine platelet-derived growth factor receptor alpha signaling is a key determinant of stromal cell recruitment in a model of human lung carcinoma. Clin Cancer Res. 12:2676–2688. 2006. View Article : Google Scholar : PubMed/NCBI | |
Tian H, Callahan CA, DuPree KJ, Darbonne WC, Ahn CP, Scales SJ and de Sauvage FJ: Hedgehog signaling is restricted to the stromal compartment during pancreatic carcinogenesis. Proc Natl Acad Sci USA. 106:4254–4259. 2009. View Article : Google Scholar : PubMed/NCBI | |
Aggarwal V, Tuli HS, Varol A, Thakral F, Yerer MB, Sak K, Varol M, Jain A, Khan MA and Sethi G: Role of reactive oxygen species in cancer progression: Molecular mechanisms and recent advancements. Biomolecules. 9:7352019. View Article : Google Scholar : PubMed/NCBI | |
Direkze NC, Hodivala-Dilke K, Jeffery R, Hunt T, Poulsom R, Oukrif D, Alison MR and Wright NA: Bone marrow contribution to tumor-associated myofibroblasts and fibroblasts. Cancer Res. 64:8492–8495. 2004. View Article : Google Scholar : PubMed/NCBI | |
Kidd S, Spaeth E, Watson K, Burks J, Lu H, Klopp A, Andreeff M and Marini FC: Origins of the tumor microenvironment: Quantitative assessment of adipose-derived and bone marrow-derived stroma. PLoS One. 7:e305632012. View Article : Google Scholar : PubMed/NCBI | |
Abe R, Donnelly SC, Peng T, Bucala R and Metz CN: Peripheral blood fibrocytes: Differentiation pathway and migration to wound sites. J Immunol. 166:7556–7562. 2001. View Article : Google Scholar : PubMed/NCBI | |
Zeisberg EM, Potenta S, Xie L, Zeisberg M and Kalluri R: Discovery of endothelial to mesenchymal transition as a source for carcinoma-associated fibroblasts. Cancer Res. 67:10123–10128. 2007. View Article : Google Scholar : PubMed/NCBI | |
Timperi E, Gueguen P, Molgora M, Magagna I, Kieffer Y, Lopez-Lastra S, Sirven P, Baudrin LG, Baulande S, Nicolas A, et al: Lipid-associated macrophages are induced by cancer-associated fibroblasts and mediate immune suppression in breast cancer. Cancer Res. 82:3291–3306. 2022. View Article : Google Scholar : PubMed/NCBI | |
Nurmik M, Ullmann P, Rodriguez F, Haan S and Letellier E: In search of definitions: Cancer-associated fibroblasts and their markers. Int J Cancer. 146:895–905. 2020. View Article : Google Scholar | |
Chen X and Song E: Turning foes to friends: Targeting cancer-associated fibroblasts. Nat Rev Drug Discov. 18:99–115. 2019. View Article : Google Scholar | |
Costa A, Kieffer Y, Scholer-Dahirel A, Pelon F, Bourachot B, Cardon M, Sirven P, Magagna I, Fuhrmann L, Bernard C, et al: Fibroblast heterogeneity and immunosuppressive environment in human breast cancer. Cancer Cell. 33:463–479.e410. 2018. View Article : Google Scholar : PubMed/NCBI | |
Glabman RA, Choyke PL and Sato N: Cancer-associated fibroblasts: Tumorigenicity and targeting for cancer therapy. Cancers (Basel). 14:39062022. View Article : Google Scholar : PubMed/NCBI | |
Paulsson J and Micke P: Prognostic relevance of cancer-associated fibroblasts in human cancer. Semin Cancer Biol. 25:61–68. 2014. View Article : Google Scholar : PubMed/NCBI | |
Marchini C, Montani M, Konstantinidou G, Orrù R, Mannucci S, Ramadori G, Gabrielli F, Baruzzi A, Berton G, Merigo F, et al: Mesenchymal/stromal gene expression signature relates to basal-like breast cancers, identifies bone metastasis and predicts resistance to therapies. PLoS One. 5:e141312010. View Article : Google Scholar : PubMed/NCBI | |
Frings O, Augsten M, Tobin NP, Carlson J, Paulsson J, Pena C, Olsson E, Veerla S, Bergh J, Ostman A and Sonnhammer EL: Prognostic significance in breast cancer of a gene signature capturing stromal PDGF signaling. Am J Pathol. 182:2037–2047. 2013. View Article : Google Scholar : PubMed/NCBI | |
Lappano R, Rigiracciolo DC, Belfiore A, Maggiolini M and De Francesco EM: Cancer associated fibroblasts: Role in breast cancer and potential as therapeutic targets. Expert Opin Ther Targets. 24:559–572. 2020. View Article : Google Scholar : PubMed/NCBI | |
Fernández-Nogueira P, Mancino M, Fuster G, López-Plana A, Jauregui P, Almendro V, Enreig E, Menéndez S, Rojo F, Noguera-Castells A, et al: Tumor-associated fibroblasts promote HER2-targeted therapy resistance through FGFR2 activation. Clin Cancer Res. 26:1432–1448. 2020. View Article : Google Scholar | |
Palmieri C, Roberts-Clark D, Assadi-Sabet A, Coope RC, O'Hare M, Sunters A, Hanby A, Slade MJ, Gomm JJ, Lam EW and Coombes RC: Fibroblast growth factor 7, secreted by breast fibroblasts, is an interleukin-1beta-induced paracrine growth factor for human breast cells. J Endocrinol. 177:65–81. 2003. View Article : Google Scholar : PubMed/NCBI | |
Kalluri R: The biology and function of fibroblasts in cancer. Nat Rev Cancer. 16:582–598. 2016. View Article : Google Scholar : PubMed/NCBI | |
Cerliani JP, Guillardoy T, Giulianelli S, Vaque JP, Gutkind JS, Vanzulli SI, Martins R, Zeitlin E, Lamb CA and Lanari C: Interaction between FGFR-2, STAT5, and progesterone receptors in breast cancer. Cancer Res. 71:3720–3731. 2011. View Article : Google Scholar : PubMed/NCBI | |
Mao Y, Keller ET, Garfield DH, Shen K and Wang J: Stromal cells in tumor microenvironment and breast cancer. Cancer Metastasis Rev. 32:303–315. 2013. View Article : Google Scholar | |
Louault K, Li RR and DeClerck YA: Cancer-associated fibroblasts: Understanding their heterogeneity. Cancers (Basel). 12:31082020. View Article : Google Scholar : PubMed/NCBI | |
Shee K, Yang W, Hinds JW, Hampsch RA, Varn FS, Traphagen NA, Patel K, Cheng C, Jenkins NP, Kettenbach AN, et al: Therapeutically targeting tumor microenvironment-mediated drug resistance in estrogen receptor-positive breast cancer. J Exp Med. 215:895–910. 2018. View Article : Google Scholar : PubMed/NCBI | |
Clayton NS, Wilson AS, Laurent EP, Grose RP and Carter EP: Fibroblast growth factor-mediated crosstalk in cancer etiology and treatment. Dev Dyn. 246:493–501. 2017. View Article : Google Scholar : PubMed/NCBI | |
Zhou Z, Wu B, Tang X, Ke R and Zou Q: Comprehensive analysis of fibroblast growth factor receptor (FGFR) family genes in breast cancer by integrating online databases and bioinformatics. Med Sci Monit. 26:e9235172020. View Article : Google Scholar : PubMed/NCBI | |
Suh J, Kim DH, Lee YH, Jang JH and Surh YJ: Fibroblast growth factor-2, derived from cancer-associated fibroblasts, stimulates growth and progression of human breast cancer cells via FGFR1 signaling. Mol Carcinog. 59:1028–1040. 2020. View Article : Google Scholar : PubMed/NCBI | |
Xie Y, Su N, Yang J, Tan Q, Huang S, Jin M, Ni Z, Zhang B, Zhang D, Luo F, et al: FGF/FGFR signaling in health and disease. Signal Transduct Target Ther. 5:1812020. View Article : Google Scholar : PubMed/NCBI | |
Otranto M, Sarrazy V, Bonte F, Hinz B, Gabbiani G and Desmouliere A: The role of the myofibroblast in tumor stroma remodeling. Cell Adh Migr. 6:203–219. 2012. View Article : Google Scholar : PubMed/NCBI | |
Chakrabarti R, Lee M and Higgs HN: Multiple roles for actin in secretory and endocytic pathways. Curr Biol. 31:R603–R618. 2021. View Article : Google Scholar : PubMed/NCBI | |
Ao Z, Shah SH, Machlin LM, Parajuli R, Miller PC, Rawal S, Williams AJ, Cote RJ, Lippman ME, Datar RH and El-Ashry D: Identification of cancer-associated fibroblasts in circulating blood from patients with metastatic breast cancer. Cancer Res. 75:4681–4687. 2015. View Article : Google Scholar : PubMed/NCBI | |
Kim S, You D, Jeong Y, Yu J, Kim SW, Nam SJ and Lee JE: TP53 upregulates α-smooth muscle actin expression in tamoxifen-resistant breast cancer cells. Oncol Rep. 41:1075–1082. 2019. | |
Wang T, Srivastava S, Hartman M, Buhari SA, Chan CW, Iau P, Khin LW, Wong A, Tan SH, Goh BC and Lee SC: High expression of intratumoral stromal proteins is associated with chemotherapy resistance in breast cancer. Oncotarget. 7:55155–55168. 2016. View Article : Google Scholar : PubMed/NCBI | |
Yamashita M, Ogawa T, Zhang X, Hanamura N, Kashikura Y, Takamura M, Yoneda M and Shiraishi T: Role of stromal myofibroblasts in invasive breast cancer: Stromal expression of alpha-smooth muscle actin correlates with worse clinical outcome. Breast Cancer. 19:170–176. 2012. View Article : Google Scholar | |
Vathiotis IA, Moutafi MK, Divakar P, Aung TN, Qing T, Fernandez A, Yaghoobi V, El-Abed S, Wang Y, Guillaume S, et al: Alpha-smooth muscle actin expression in the stroma predicts resistance to trastuzumab in patients with early-stage HER2-positive breast cancer. Clin Cancer Res. 27:6156–6163. 2021. View Article : Google Scholar : PubMed/NCBI | |
Busch S, Rydén L, Stål O, Jirström K and Landberg G: Low ERK phosphorylation in cancer-associated fibroblasts is associated with tamoxifen resistance in pre-menopausal breast cancer. PLoS One. 7:e456692012. View Article : Google Scholar : PubMed/NCBI | |
Hu G, Wang S, Xu F, Ding Q, Chen W, Zhong K, Huang L and Xu Q: Tumor-infiltrating podoplanin+ fibroblasts predict worse outcome in solid tumors. Cell Physiol Biochem. 51:1041–1050. 2018. View Article : Google Scholar : PubMed/NCBI | |
Yazhou C, Wenlv S, Weidong Z and Licun W: Clinicopathological significance of stromal myofibroblasts in invasive ductal carcinoma of the breast. Tumour Biol. 25:290–295. 2004. View Article : Google Scholar | |
Bresnick AR, Weber DJ and Zimmer DB: S100 proteins in cancer. Nat Rev Cancer. 15:96–109. 2015. View Article : Google Scholar : PubMed/NCBI | |
D'Ambrosi N, Milani M and Apolloni S: S100A4 in the physiology and pathology of the central and peripheral nervous system. Cells. 10:7982021. View Article : Google Scholar : PubMed/NCBI | |
Liu S, Zhang H, Li Y, Zhang Y, Bian Y, Zeng Y, Yao X, Wan J, Chen X, Li J, et al: S100A4 enhances protumor macrophage polarization by control of PPAR-γ-dependent induction of fatty acid oxidation. J Immunother Cancer. 9:e0025482021. View Article : Google Scholar | |
Friedman G, Levi-Galibov O, David E, Bornstein C, Giladi A, Dadiani M, Mayo A, Halperin C, Pevsner-Fischer M, Lavon H, et al: Cancer-associated fibroblast compositions change with breast cancer progression linking the ratio of S100A4+ and PDPN+ CAFs clinical outcome. Nat Cancer. 1:692–708. 2020. View Article : Google Scholar : PubMed/NCBI | |
Grum-Schwensen B, Klingelhofer J, Berg CH, El-Naaman C, Grigorian M, Lukanidin E and Ambartsumian N: Suppression of tumor development and metastasis formation in mice lacking the S100A4(mts1) gene. Cancer Res. 65:3772–3780. 2005. View Article : Google Scholar : PubMed/NCBI | |
Park CK, Jung WH and Koo JS: Expression of cancer-associated fibroblast-related proteins differs between invasive lobular carcinoma and invasive ductal carcinoma. Breast Cancer Res Treat. 159:55–69. 2016. View Article : Google Scholar : PubMed/NCBI | |
de Silva Rudland S, Martin L, Roshanlall C, Winstanley J, Leinster S, Platt-Higgins A, Carroll J, West C, Barraclough R and Rudland P: Association of S100A4 and osteopontin with specific prognostic factors and survival of patients with minimally invasive breast cancer. Clin Cancer Res. 12:1192–1200. 2006. View Article : Google Scholar : PubMed/NCBI | |
Pedersen KB, Nesland JM, Fodstad O and Maelandsmo GM: Expression of S100A4, E-cadherin, alphaand beta-catenin in breast cancer biopsies. Br J Cancer. 87:1281–1286. 2002. View Article : Google Scholar : PubMed/NCBI | |
Li WL, Zhang Y, Liu BG, Du Q, Zhou CX and Tian XS: Correlation between the expression of S100A4 and the efficacy of TAC neoadjuvant chemotherapy in breast cancer. Exp Ther Med. 10:1983–1989. 2015. View Article : Google Scholar : PubMed/NCBI | |
McKiernan E, McDermott EW, Evoy D, Crown J and Duffy MJ: The role of S100 genes in breast cancer progression. Tumour Biol. 32:441–450. 2011. View Article : Google Scholar | |
Park SY, Kim HM and Koo JS: Differential expression of cancer-associated fibroblast-related proteins according to molecular subtype and stromal histology in breast cancer. Breast Cancer Res Treat. 149:727–741. 2015. View Article : Google Scholar : PubMed/NCBI | |
Donovan J, Shiwen X, Norman J and Abraham D: Platelet-derived growth factor alpha and beta receptors have overlapping functional activities towards fibroblasts. Fibrogenesis Tissue Repair. 6:102013. View Article : Google Scholar : PubMed/NCBI | |
Claesson-Welsh L, Ronnstrand L and Heldin CH: Biosynthesis and intracellular transport of the receptor for platelet-derived growth factor. Proc Natl Acad Sci USA. 84:8796–8800. 1987. View Article : Google Scholar : PubMed/NCBI | |
Lavie D, Ben-Shmuel A, Erez N and Scherz-Shouval R: Cancer-associated fibroblasts in the single-cell era. Nat Cancer. 3:793–807. 2022. View Article : Google Scholar : PubMed/NCBI | |
Pietras K, Pahler J, Bergers G and Hanahan D: Functions of paracrine PDGF signaling in the proangiogenic tumor stroma revealed by pharmacological targeting. PLoS Med. 5:e192008. View Article : Google Scholar : PubMed/NCBI | |
Paulsson J, Sjöblom T, Micke P, Pontén F, Landberg G, Heldin CH, Bergh J, Brennan DJ, Jirström K and Ostman A: Prognostic significance of stromal platelet-derived growth factor beta-receptor expression in human breast cancer. Am J Pathol. 175:334–341. 2009. View Article : Google Scholar : PubMed/NCBI | |
Paulsson J, Rydén L, Strell C, Frings O, Tobin NP, Fornander T, Bergh J, Landberg G, Stål O and Östman A: High expression of stromal PDGFRβ is associated with reduced benefit of tamoxifen in breast cancer. J Pathol Clin Res. 3:38–43. 2017. View Article : Google Scholar : PubMed/NCBI | |
Hu G, Huang L, Zhong K, Meng L, Xu F, Wang S and Zhang T: PDGFR-β+ fibroblasts deteriorate survival in human solid tumors: a meta-analysis. Aging (Albany NY). 13:13693–13707. 2021. View Article : Google Scholar : PubMed/NCBI | |
Yam C, Murthy RK, Rauch GM, Murray JL, Walters RS, Valero V, Brewster AM, Bast RC Jr, Booser DJ, Giordano SH, et al: A phase II study of imatinib mesylate and letrozole in patients with hormone receptor-positive metastatic breast cancer expressing c-kit or PDGFR-b. Invest New Drugs. 36:1103–1109. 2018. View Article : Google Scholar : PubMed/NCBI | |
Wicki A, Lehembre F, Wick N, Hantusch B, Kerjaschki D and Christofori G: Tumor invasion in the absence of epithelial-mesenchymal transition: Podoplanin-mediated remodeling of the actin cytoskeleton. Cancer Cell. 9:261–272. 2006. View Article : Google Scholar : PubMed/NCBI | |
Niemiec J, Adamczyk A, Harazin-Lechowska A, Ambicka A, Grela-Wojewoda A, Majchrzyk K, Kruczak A, Sas-Korczyńska B and Ryś J: Podoplanin-positive cancer-associated stromal fibroblasts in primary tumor and synchronous lymph node metastases of HER2-overexpressing breast carcinomas. Anticancer Res. 38:1957–1965. 2018.PubMed/NCBI | |
Schoppmann SF, Berghoff A, Dinhof C, Jakesz R, Gnant M, Dubsky P, Jesch B, Heinzl H and Birner P: Podoplanin-expressing cancer-associated fibroblasts are associated with poor prognosis in invasive breast cancer. Breast Cancer Res Treat. 134:237–244. 2012. View Article : Google Scholar : PubMed/NCBI | |
Tanaka Y, Ohno T, Kadonaga T, Kidokoro Y, Wakahara M, Nosaka K, Sakabe T, Suzuki Y, Nakamura H and Umekita Y: Podoplanin expression in cancer-associated fibroblasts predicts unfavorable prognosis in node-negative breast cancer patients with hormone receptor-positive/HER2-negative subtype. Breast Cancer. 28:822–828. 2021. View Article : Google Scholar : PubMed/NCBI | |
Pula B, Jethon A, Piotrowska A, Gomulkiewicz A, Owczarek T, Calik J, Wojnar A, Witkiewicz W, Rys J and Ugorski M, et al: Podoplanin expression by cancer-associated fibroblasts predicts poor outcome in invasive ductal breast carcinoma. Histopathology. 59:1249–1260. 2011. View Article : Google Scholar : PubMed/NCBI | |
Pula B, Wojnar A, Werynska B, Ambicka A, Kruczak A, Witkiewicz W, Ugorski M, Podhorska-Okolow M and Dziegiel P: Impact of different tumour stroma assessment methods regarding podoplanin expression on clinical outcome in patients with invasive ductal breast carcinoma. Anticancer Res. 33:1447–1455. 2013.PubMed/NCBI | |
Liu R, Li H, Liu L, Yu J and Ren X: Fibroblast activation protein: A potential therapeutic target in cancer. Cancer Biol Ther. 13:123–129. 2012. View Article : Google Scholar : PubMed/NCBI | |
Sarkar M, Nguyen T, Gundre E, Ogunlusi O, El-Sobky M, Giri B and Sarkar TR: Cancer-associated fibroblasts: The chief architect in the tumor microenvironment. Front Cell Dev Biol. 11:10890682023. View Article : Google Scholar : PubMed/NCBI | |
Lo A, Wang LCS, Scholler J, Monslow J, Avery D, Newick K, O'Brien S, Evans RA, Bajor DJ, Clendenin C, et al: Tumor-promoting desmoplasia is disrupted by depleting FAP-expressing stromal cells. Cancer Res. 75:2800–2810. 2015. View Article : Google Scholar : PubMed/NCBI | |
Tashireva LA, Denisov EV, Gerashchenko TS, Pautova DN, Bulda kov MA, Zavyalova MV, Kzhysh kowska J, Cherdyntseva NV and Perelmuter VM: Intratumoral heterogeneity of macrophages and fibroblasts in breast cancer is associated with the morphological diversity of tumor cells and contributes to lymph node metastasis. Immunobiology. 222:631–640. 2017. View Article : Google Scholar | |
Ariga N, Sato E, Ohuchi N, Nagura H and Ohtani H: Stromal expression of fibroblast activation protein/seprase, a cell membrane serine proteinase and gelatinase, is associated with longer survival in patients with invasive ductal carcinoma of breast. Int J Cancer. 95:67–72. 2001. View Article : Google Scholar : PubMed/NCBI | |
Bonneau C, Eliès A, Kieffer Y, Bourachot B, Ladoire S, Pelon F, Hequet D, Guinebretière JM, Blanchet C, Vincent-Salomon A, et al: A subset of activated fibroblasts is associated with distant relapse in early luminal breast cancer. Breast Cancer Res. 22:762020. View Article : Google Scholar : PubMed/NCBI | |
Biernacka A, Dobaczewski M and Frangogiannis NG: TGF-β signaling in fibrosis. Growth Factors. 29:196–202. 2011. View Article : Google Scholar : PubMed/NCBI | |
Shi X, Young CD, Zhou H and Wang X: Transforming growth factor-β signaling in fibrotic diseases and cancer-associated fibroblasts. Biomolecules. 10:16662020. View Article : Google Scholar | |
Casey TM, Eneman J, Crocker A, White J, Tessitore J, Stanley M, Harlow S, Bunn JY, Weaver D, Muss H and Plaut K: Cancer associated fibroblasts stimulated by transforming growth factor beta1 (TGF-beta 1) increase invasion rate of tumor cells: A population study. Breast Cancer Res Treat. 110:39–49. 2008. View Article : Google Scholar | |
Koumoundourou D, Kassimatis T, Zolota V, Tzorakoeleftherakis E, Ravazoula P, Vassiliou V, Kardamakis D and Varakis J: Prognostic significance of TGFbeta-1 and pSmad2/3 in breast cancer patients with T1-2,N0 tumours. Anticancer Res. 27:2613–2620. 2007.PubMed/NCBI | |
Liu N, Qi D, Jiang J, Zhang J and Yu C: Significance of combined TGF-β1 and survivin expression on the prognosis of patients with triple-negative breast cancer. Oncol Lett. 23:1932022. View Article : Google Scholar | |
Nakamura H, Kambe H, Egawa T, Kimura Y, Ito H, Hayashi E, Yamamoto H, Sato J and Kishimoto S: Partial purification and characterization of human hepatoma-derived growth factor. Clin Chim Acta. 183:273–284. 1989. View Article : Google Scholar : PubMed/NCBI | |
Enomoto H, Nakamura H, Liu W and Nishiguchi S: Hepatoma-derived growth factor: Its possible involvement in the progression of hepatocellular carcinoma. Int J Mol Sci. 16:14086–14097. 2015. View Article : Google Scholar : PubMed/NCBI | |
Chen X, Yun J, Fei F, Yi J, Tian R, Li S and Gan X: Prognostic value of nuclear hepatoma-derived growth factor (HDGF) localization in patients with breast cancer. Pathol Res Pract. 208:437–443. 2012. View Article : Google Scholar : PubMed/NCBI | |
Qiu L, Ma Y, Chen X, Zhou L, Zhang H, Zhong G, Zhang L and Tang J: Heparin-binding growth factor (HDGF) drives radioresistance in breast cancer by activating the STAT3 signaling pathway. J Transl Med. 19:3442021. View Article : Google Scholar : PubMed/NCBI | |
Anderberg C and Pietras K: On the origin of cancer-associated fibroblasts. Cell Cycle. 8:1461–1462. 2009. View Article : Google Scholar : PubMed/NCBI | |
Kuzet SE and Gaggioli C: Fibroblast activation in cancer: When seed fertilizes soil. Cell Tissue Res. 365:607–619. 2016. View Article : Google Scholar : PubMed/NCBI | |
Jansson S, Aaltonen K, Bendahl PO, Falck AK, Karlsson M, Pietras K and Rydén L: The PDGF pathway in breast cancer is linked to tumour aggressiveness, triple-negative subtype and early recurrence. Breast Cancer Res Treat. 169:231–241. 2018. View Article : Google Scholar : PubMed/NCBI | |
Seymour L, Dajee D and Bezwoda WR: Tissue platelet derived-growth factor (PDGF) predicts for shortened survival and treatment failure in advanced breast cancer. Breast Cancer Res Treat. 26:247–252. 1993. View Article : Google Scholar : PubMed/NCBI | |
Liubomirski Y, Lerrer S, Meshel T, Rubinstein-Achiasaf L, Morein D, Wiemann S, Körner C and Ben-Baruch A: Tumor-stroma-inflammation networks promote pro-metastatic chemokines and aggressiveness characteristics in triple-negative breast cancer. Front Immunol. 10:7572019. View Article : Google Scholar : PubMed/NCBI | |
Lin S, Sun L, Lyu X, Ai X, Du D, Su N, Li H, Zhang L, Yu J and Yuan S: Lactate-activated macrophages induced aerobic glycolysis and epithelial-mesenchymal transition in breast cancer by regulation of CCL5-CCR5 axis: A positive metabolic feedback loop. Oncotarget. 8:110426–110443. 2017. View Article : Google Scholar | |
Qian BZ, Li J, Zhang H, Kitamura T, Zhang J, Campion LR, Kaiser EA, Snyder LA and Pollard JW: CCL2 recruits inflammatory monocytes to facilitate breast-tumour metastasis. Nature. 475:222–225. 2011. View Article : Google Scholar : PubMed/NCBI | |
Zhou B, Sun C, Li N, Shan W, Lu H, Guo L, Guo E, Xia M, Weng D, Meng L, et al: Cisplatin-induced CCL5 secretion from CAFs promotes cisplatin-resistance in ovarian cancer via regulation of the STAT3 and PI3K/Akt signaling pathways. Int J Oncol. 48:2087–2097. 2016. View Article : Google Scholar : PubMed/NCBI | |
Yao M, Yu E, Staggs V, Fan F and Cheng N: Elevated expression of chemokine C-C ligand 2 in stroma is associated with recurrent basal-like breast cancers. Mod Pathol. 29:810–823. 2016. View Article : Google Scholar : PubMed/NCBI | |
Heiskala M, Leidenius M, Joensuu K and Heikkilä P: High expression of CCL2 in tumor cells and abundant infiltration with CD14 positive macrophages predict early relapse in breast cancer. Virchows Arch. 474:3–12. 2019. View Article : Google Scholar | |
Yamaguchi M, Takagi K, Narita K, Miki Y, Onodera Y, Miyashita M, Sasano H and Suzuki T: Stromal CCL5 promotes breast cancer progression by interacting with CCR3 in tumor cells. Int J Mol Sci. 22:19182021. View Article : Google Scholar : PubMed/NCBI | |
Yaal-Hahoshen N, Shina S, Leider-Trejo L, Barnea I, Shabtai EL, Azenshtein E, Greenberg I, Keydar I and Ben-Baruch A: The chemokine CCL5 as a potential prognostic factor predicting disease progression in stage II breast cancer patients. Clin Cancer Res. 12:4474–4480. 2006. View Article : Google Scholar : PubMed/NCBI | |
Liu S, Dontu G, Mantle ID, Patel S, Ahn NS, Jackson KW, Suri P and Wicha MS: Hedgehog signaling and Bmi-1 regulate self-renewal of normal and malignant human mammary stem cells. Cancer Res. 66:6063–6071. 2006. View Article : Google Scholar : PubMed/NCBI | |
Arnold KM, Pohlig RT and Sims-Mourtada J: Co-activation of Hedgehog and Wnt signaling pathways is associated with poor outcomes in triple negative breast cancer. Oncol Lett. 14:5285–5292. 2017.PubMed/NCBI | |
Beenken A and Mohammadi M: The FGF family: Biology, pathophysiology and therapy. Nat Rev Drug Discov. 8:235–253. 2009. View Article : Google Scholar : PubMed/NCBI | |
Babina IS and Turner NC: Advances and challenges in targeting FGFR signalling in cancer. Nat Rev Cancer. 17:318–332. 2017. View Article : Google Scholar : PubMed/NCBI | |
Colomer R, Aparicio J, Montero S, Guzmán C, Larrodera L and Cortés-Funes H: Low levels of basic fibroblast growth factor (bFGF) are associated with a poor prognosis in human breast carcinoma. Br J Cancer. 76:1215–1220. 1997. View Article : Google Scholar : PubMed/NCBI | |
Linderholm BK, Lindh B, Beckman L, Erlanson M, Edin K, Travelin B, Bergh J, Grankvist K and Henriksson R: Prognostic correlation of basic fibroblast growth factor and vascular endothelial growth factor in 1307 primary breast cancers. Clin Breast Cancer. 4:340–347. 2003. View Article : Google Scholar | |
Surowiak P, Murawa D, Materna V, Maciejczyk A, Pudelko M, Ciesla S, Breborowicz J, Murawa P, Zabel M, Dietel M and Lage H: Occurence of stromal myofibroblasts in the invasive ductal breast cancer tissue is an unfavourable prognostic factor. Anticancer Res. 27:2917–2924. 2007.PubMed/NCBI | |
Yiangou C, Gomm JJ, Coope RC, Law M, Luqmani YA, Shousha S, Coombes RC and Johnston CL: Fibroblast growth factor 2 in breast cancer: Occurrence and prognostic significance. Br J Cancer. 75:28–33. 1997. View Article : Google Scholar : PubMed/NCBI | |
Granato AM, Nanni O, Falcini F, Folli S, Mosconi G, De Paola F, Medri L, Amadori D and Volpi A: Basic fibroblast growth factor and vascular endothelial growth factor serum levels in breast cancer patients and healthy women: Useful as diagnostic tools? Breast Cancer Res. 6:R38–R45. 2004. View Article : Google Scholar : | |
Faridi A, Rudlowski C, Biesterfeld S, Schuh S, Rath W and Schröder W: Long-term follow-up and prognostic significance of angiogenic basic fibroblast growth factor (bFGF) expression in patients with breast cancer. Pathol Res Pract. 198:1–5. 2002. View Article : Google Scholar : PubMed/NCBI | |
Smith K, Fox SB, Whitehouse R, Taylor M, Greenall M, Clarke J and Harris AL: Upregulation of basic fibroblast growth factor in breast carcinoma and its relationship to vascular density, oestrogen receptor, epidermal growth factor receptor and survival. Ann Oncol. 10:707–713. 1999. View Article : Google Scholar : PubMed/NCBI | |
Meijer D, Sieuwerts AM, Look MP, van Agthoven T, Foekens JA and Dorssers LCJ: Fibroblast growth factor receptor 4 predicts failure on tamoxifen therapy in patients with recurrent breast cancer. Endocr Relat Cancer. 15:101–111. 2008. View Article : Google Scholar : PubMed/NCBI | |
Ivanović V, Demajo M, Krtolica K, Krajnović M, Konstantinović M, Baltić V, Prtenjak G, Stojiljković B, Breberina M, Nesković-Konstantinović Z, et al: Elevated plasma TGF-beta1 levels correlate with decreased survival of metastatic breast cancer patients. Clin Chim Acta. 371:191–193. 2006. View Article : Google Scholar | |
El-Abd E, El-Tahan R, Fahmy L, Zaki S, Faid W, Sobhi A, Kandil K and El-Kwisky F: Serum metastasin mRNA is an important survival predictor in breast cancer. Br J Biomed Sci. 65:90–94. 2008. View Article : Google Scholar : PubMed/NCBI | |
Tripsianis G, Papadopoulou E, Romanidis K, Katotomichelakis M, Anagnostopoulos K, Kontomanolis E, Botaitis S, Tentes I and Kortsaris A: Overall survival and clinicopathological characteristics of patients with breast cancer in relation to the expression pattern of HER-2, IL-6, TNF-α and TGF-b1. Asian Pac J Cancer Prev. 14:6813–6820. 2013. View Article : Google Scholar | |
Zhu X, Xu M, Zhao X, Shen F, Ruan C and Zhao Y: The detection of plasma soluble podoplanin of patients with breast cancer and its clinical signification. Cancer Manag Res. 12:13207–13214. 2020. View Article : Google Scholar : | |
Tripsianis G, Papadopoulou E, Anagnostopoulos K, Botaitis S, Katotomichelakis M, Romanidis K, Kontomanolis E, Tentes I and Kortsaris A: Coexpression of IL-6 and TNF-α: Prognostic significance on breast cancer outcome. Neoplasma. 61:205–212. 2014. View Article : Google Scholar | |
Cai S, Zheng J, Song H, Wu H and Cai W: Relationship between serum TGF-β 1, MMP-9 and IL-1β and pathological features and prognosis in breast cancer. Front Genet. 13:10953382023. View Article : Google Scholar | |
Al-Ashkar N and Zetoune AB: S100A14 serum level and its correlation with prognostic factors in breast cancer. J Egypt Natl Canc Inst. 32:372020. View Article : Google Scholar : PubMed/NCBI | |
Yahia S, Tahari Z, Medjdoub A, Tahari FZ, Bessaih N, Messatfa M, Deblaoui F, Raiah M, Ouldcadi H, Seddiki S and Sahraoui T: Expression profile of interleukin-6, 4-hydroxy-2-nonenal, and hypoxia-inducible factor 1-α in women with breast cancer and their association with clinicopathological parameters. Contemp Oncol (Pozn). 27:14–21. 2023. | |
Panis C, Herrera AC, Victorino VJ, Aranome AM and Cecchini R: Screening of circulating TGF-β levels and its clinicopathological significance in human breast cancer. Anticancer Res. 33:737–742. 2013.PubMed/NCBI | |
Milovanović J, Todorović-Raković N and Radulovic M: Interleukin-6 and interleukin-8 serum levels in prognosis of hormone-dependent breast cancer. Cytokine. 118:93–98. 2019. View Article : Google Scholar | |
Wang RX, Ji P, Gong Y, Shao ZM and Chen S: Value of CXCL8-CXCR1/2 axis in neoadjuvant chemotherapy for triple-negative breast cancer patients: A retrospective pilot study. Breast Cancer Res Treat. 181:561–570. 2020. View Article : Google Scholar : PubMed/NCBI | |
Paccagnella M, Abbona A, Michelotti A, Geuna E, Ruatta F, Landucci E, Denaro N, Vanella P, Lo Nigro C, Galizia D, et al: Circulating cytokines in metastatic breast cancer patients select different prognostic groups and patients who might benefit from treatment beyond progression. Vaccines (Basel). 10:782022. View Article : Google Scholar : PubMed/NCBI | |
Denys H, Derycke L, Hendrix A, Westbroek W, Gheldof A, Narine K, Pauwels P, Gespach C, Bracke M and De Wever O: Differential impact of TGF-beta and EGF on fibroblast differentiation and invasion reciprocally promotes colon cancer cell invasion. Cancer Lett. 266:263–274. 2008. View Article : Google Scholar : PubMed/NCBI | |
Kjær IM, Olsen DA, Brandslund I, Bechmann T, Jakobsen EH, Bogh SB and Madsen JS: Prognostic impact of serum levels of EGFR and EGFR ligands in early-stage breast cancer. Sci Rep. 10:165582020. View Article : Google Scholar : PubMed/NCBI |