Heterogeneity of primary and metastatic CAFs: From differential treatment outcomes to treatment opportunities (Review)
- Authors:
- Published online on: April 4, 2024 https://doi.org/10.3892/ijo.2024.5642
- Article Number: 54
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Copyright: © Kou et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
1. Introduction
The simultaneous treatment of both primary and metastatic tumors is the main treatment option following tumor metastasis. However, the treatment for the primary tumor often has limited efficacy on the metastasis (1), resulting in different responses. Metastatic and primary tumors show varying degrees of resistance after several treatments (2,3). Compared with the metastatic sites of the primary tumors, they often exhibit a more malignant progression state (4). Accompanying this is the rapid loss of patient symptom management and the failure of antitumor treatment. The differential response of primary tumors and metastases to the treatment may be related to the heterogeneity in their tumor microenvironments (TMEs) (5,6).
The TMEs are the internal and external micro-landscape of tumor cells formed by the response of normal organs to evolving cancer cells, mainly composed of tumor cells, infiltrating immune cells, cancer-associated stromal cells, such as cancer-associated fibroblasts (CAFs), endothelial cells and lipocytes, along with the extracellular matrix (ECM) and multiple signaling molecules (7). These environmental factors play a key role in both the development of tumors and their response to therapy (5). CAFs, as key components of the tumor microenvironment, have been found to be closely associated with the heterogeneity between primary tumors and metastases. This heterogeneity may affect the drug resistance of primary and metastatic sites (8).
CAFs promote tumor proliferation, therapeutic resistance and immune rejection by secreting growth factors, inflammatory ligands and ECM proteins (9-11). Previously, CAFs were considered cell populations that were not single but complex subclusters with different functions (9). Significant heterogeneity in the subsets of CAFs associated with primary tumors and metastases (pCAFs and mCAFs, respectively) have been shown to exhibit different sensitivities to treatment (8). The heterogeneity of pCAFs and mCAFs may be the key to the different treatment responses of primary tumors and metastases.
Compared with pCAFs, mCAFs generally have a stronger ability to shape the ECM, and in immunosuppression and angiogenesis (12-16). The results of preclinical studies suggest that targeting mCAFs can alleviate the progression of metastatic cancer and mitigate therapeutic resistance, indicating that mCAFs are a promising target for metastatic cancer (17). Therefore, comparing the heterogeneity between mCAFs and pCAFs from the biological characteristics is necessary to find opportunities to target mCAFs. Among them, the identification of the cells of origin in CAF subtypes is a central question, as it may partially determine the functions of distinct CAF populations (18) (Fig. 1A). Furthermore, fibroblasts heterogeneity can be partly explained by variable activation levels of the resident fibroblasts (RFs) with organ-specific features (19). The phenotypic heterogeneity of activated CAFs can be manifested by a wide range of biological markers with selective expression patterns in the context of specific TMEs (10) (Fig. 1B). Moreover, the biological heterogeneity of CAFs is also reflected in secreted molecules, exosomes, transcriptional features and matreotypes (20,21) (Fig. 1C). The present study attempted to make sense of the different treatment outcomes between primary tumors and metastases from the perspective of heterogeneity and treatment resistance of pCAFs and mCAFs, identifying treatment opportunities for metastases.
2. Heterogeneity of mCAFs and pCAFs
Lineage-dependent heterogeneity of CAFs
Any cell with properties associated with 'activated' fibroblasts, myofibroblasts and mesenchymal stem cells (MSCs) can be defined as fibroblasts (21). In several experimental models of human tumors, validation at the transcriptional and protein levels revealed that differences in the spatial separation of CAF subclasses could be attributed to their respective sources (22,23), which is called lineage-dependent heterogeneity (18). In tumors, various cells, such as RFs, MSCs, including bone marrow-derived MSCs (BM-MSCs), pancreatic stellate cells (PSCs), hepatic stellate cells (HSCs), smooth muscle cells, pericytes, adipocytes, monocytes, mesothelial cells, epithelial cells and endothelial cells, are activated into CAFs through different mechanisms (24-31).
The present study summarized the functional convergence of CAFs from the perspective of their sources and CAFs from different sources may also have functional synergy (Table I). HSCs and PSCs share homology and have similar morphologies and functions (32), CAFs derived from HSCs and PSCs are prone to stromal deposition (33-35), similar to their function in mediating tissue fibrosis in non-malignant diseases (36,37). Tumor-resident MSCs also function in ECM production and remodeling after activation as CAFs and could partially promote angiogenesis (38-40). CAFs derived from BM-MSCs may be involved in angiogenesis and the maintenance of an inflammatory environment in tumors (41,42). Pericytes are cells embedded between the capillary basement membrane and endothelial cells that physiologically regulate vasoconstriction and source of neovascular walls (43), CAFs from this source may be predominantly involved in tumor angiogenesis (44). CAFs undergoing mesenchymal transformation change their adhesion properties, which is closely related to the enhancement of tumor aggressiveness (45); due to differences in organ anatomy and physiology, RFs activate CAFs in different ways via different pathways, differentiating into elusive functional phenotypes (46-49).
Pancreatic cancer (PDAC), colorectal cancer (CRC), breast cancer (BC) and lung cancer are malignant tumors characterized by high enrichment of CAFs and stromal hyperplasia and they have received a great deal of attention in the field of CAF research (50). Here, we take these several types of cancer as examples to compare the heterogeneity of pCAFs (Fig. 2A) and mCAFs (Fig. 2B) sources. It is of great significance in describing the overall picture of CAF composition and understanding the microenvironment heterogeneity between primary and metastatic tumors. The screening and ablation of CAF precursor cells of specific origins may be an effective means of improving the sensitivity of secondary tumors to drugs (17).
Main sources of pCAFs and liver mCAFs in PDAC and CRC
CRC: The main sources of pCAFs in CRC include RFs and intestinal MSCs (51). CRC cells secrete transforming growth factor-β (TGF-β) to activate RFs, which are then converted into smooth muscle actin-α (α-SMA)+ CAFs (52). Different mouse lineage traces show that most proliferating α-SMA+ CAFs originate from leptin receptor+ resident cells during the development of CRC (53). Shinagawa et al (54) injected PKH-labeled MSCs into the tail vein of CRC-bearing mice and detected MSCs in the stroma of both primary tumor and liver metastases (LMs). By contrast, MSCs were not detected in non-cancerous tissues, such as normal colon mucosa and liver, which proves that MSCs are specifically recruited into the CRC stroma and play an important role in tumor growth and metastasis (54). In addition, some studies have shown that epithelial cells, smooth muscle cells and pericytes are also part of the pCAFs pool in CRC (44,51,55).
PDAC: PSCs produce most of the ECM in PDAC (56) and were previously considered the main source of myofibroblasts in PDAC (57). Öhlund et al (58) identified myofibroblastic CAFs (myCAFs) as responsible for ECM deposition close to tumors and inflammatory CAFs (iCAFs) responsible for secreting inflammatory and chemokines factors far from tumors in KPC mouse models and human PDAC tissue. Subsequently, through a three-dimensional co-culture platform of mouse-derived PSCs and PDAC cells, they found that PSCs can differentiate into myCAFs and iCAFs in vitro. Moreover, Elyada et al (59) then corroborated the gene signatures of these two cell types via single-cell RNA sequencing (scRNA-seq). They identified antigen-presenting tumor-associated fibroblasts (apCAFs) in addition to these two cell subtypes, which were specifically labeled with serum amyloid A3 (Saa3) and expressed MHC-II class molecules but not co-stimulatory molecules (59). It has been proposed that apCAFs act as a direct positive regulator of the adaptive immune system to activate T cells (60). Dominguez et al (61) analyzed apCAFs derived from mesothelial cells by mouse PDAC RNA-seq data, which Huang et al confirmed via lineage tracing (62).
LMs: Mouse experiments have shown that 95% of liver myCAFs originate from HSCs and portal fibroblasts (PFs) (63). In some benign liver diseases, HSCs and PFs are the main sources of myofibroblasts (64). HSCs play a critical role in hepatic fibrosis (65), while PFs are the first responders in biliary fibrosis (66). Through gene tracking, scRNA-seq and Cre-lox mediated gene deletion methods, Bhattacharjee et al (35) showed that the CAFs of PDAC LMs mainly originate from HSCs. Xie et al (67) found the exosomal CD44v6/C1QBP complex is delivered to the plasma membrane of HSCs, resulting in the phosphorylation of insulin-like growth factor 1 (IGF-1), leading to HSC activation and liver fibrosis. In another RNA-Seq analysis of CRC LMs mCAFs, comparing ECM-CAFs subtypes functioning in ECM remodeling and collagen (COL) production with fibroblast gene features in the normal or cirrhotic liver, found that ECM-CAFs significantly overlap with scar-associated MSCs (SAMes), which express PFs markers. The Ctr-CAF-I subtype (with contractile function), which expresses PLN and variants of actin gamma 2, may originate from vascular smooth muscle cells (VSMCs); while the Ctr-CAF-II subtype (the average CAF phenotype) may originate from HSCs (68).
The most common metastatic site for PDAC and CRC is the liver and some studies have found that the fate of this directed metastasis appears to be mediated by fibroblasts before the metastatic event occurs (34,69-71). When genome-wide transcription data on the heterogeneity of human fibroblasts between organs were acquired through cDNA microarray analysis of human skin fibroblast cultures from different ages and anatomical locations, the fibroblasts were clustered next to other fibroblasts from the same site rather than cells from the same individual, which indicates that fibroblasts have positional memory characterized by gene expression patterns (72). LMs have unique and similar morphological characteristics in PDAC and CRC (35). This may be largely attributed to liver RFs, including HSCs (73), which have conserved transcriptional programs in different tumors and upon tumor progression (18). These persistent TMEs builders ultimately construct microenvironments that differ from the primary tumor in LMs.
Lineage-dependent heterogeneity of CRC pCAFs and LMs mCAFs is easily observable, however, in PDAC; PSCs and HSCs are known to be homologous and the primary tumors are characterized by abundant desmoplasia, constituting up to 90% of the total tumor volume (58), exceeding the proportion of stroma in LMs (74). One explanation for this is the presence of other stroma-producing cells in the pancreas (32). Helms et al (75). conducted fluorescence tracing on PSCs and found that they only produced a small portion of myCAFs and PSC ablation still generated a high abundance of α-S-adenosylmethionine (SAM) + CAFs, suggesting that PSCs are not the only source of myCAFs They speculated that other myCAFs in PDAC may originate from other RFs or the bone marrow (75). Through lineage tracing, Garcia et al (76) found that resident Gli1+ fibroblasts, which are distinct from PSCs in healthy pancreas, may a source of myCAF populations, providing clues for this hypothesis.
Main sources of pCAFs and mCAFs in lung cancer
The lung cancer pCAFs mainly originate from lung RFs and MSCs. Enhancing the expression of hypoxia inducible factor-1 in fibroblasts via hypoxia induced the conversion of normal fibroblasts into CAFs (77). Research indicates that fibroblasts activated by lung cancer cell conditioned media lead to an increase in interleukin (IL)-6 production, inducing epithelial-mesenchymal transition and cisplatin resistance in non-small cell lung cancer (NSCLC) cells (78). Treatment with NSCLC-derived factors induce a CAF phenotype in both normal lung resident MSCs and lung cancer-associated MSCs (79). One of the most common sites of metastasis in lung cancer is intrapulmonary metastasis to the ipsilateral or contralateral lung (80). A study showed that CAF extracellular vesicles (EVs) can activate lung fibroblasts and induce the formation of pre-metastatic niches in the lungs (81). Another study shows that the metastatic cells can bring stromal components from the primary site to the lungs (82).
Main sources of pCAFs and mCAFs in BC
BC CAFs have a wide range of sources, primarily including RFs, BM-fibroblasts, MSCs (including BM-MSCs) and adipocytes (83,84). RFs and BM-MSCs are two more important sources of CAFs in BC. RNA-seq of pCAFs extracted from a mouse orthotopic transplantation model showed that podoplanin+ CAFs had a transcription pattern similar to normal mammary fat pad fibroblasts, while fibroblast-specific protein 1 (FSP1) was not expressed in normal fibroblasts. Therefore, FPS1+ CAFs may have been recruited from the periphery (85). A previous study on adoptive bone marrow transplantation confirmed that BC recruits large numbers of MSCs that do not express platelet-derived growth factor (PDGFRα) from the bone marrow into the primary tumor and lung metastases and found that CAFs derived from resident CAFs and BM-MSCs had different abilities in inducing angiogenesis and recruiting macrophages (41).
BC bone metastasis mCAFs are mainly derived from BM-MSCs and primary tumor pCAFs. Specifically, pCAFs from triple-negative BC (TNBC) produce stromal cell-derived factor 1 (SDF-1) and IGF-1 to induce bone metastasis of cancer cells with high Src activity (86), where pCAFs are transferred to bone marrow together with BC cells under the mediation of osteopontin (OPN) (87). Tumor cells continue to evolve after metastasis, but they no longer depend on the primary tumor. They maintain a state of reduced information exchange due to physical and chemical barriers, especially in organs such as the brain and bone (88). The influence of the bone marrow microenvironment on bone metastasis is undoubtedly great. BM-MCSs, as the most important stromal cells in the bone marrow, differentiate into different cell subsets such as osteoblasts, adipocytes, fibroblasts and pericytes (89), playing a key role in tumor cell homing, bone marrow colonization and tumor cell dormancy (90). The deleting of Rictor gene reduces the secretion of IL-6, receptor activator of nuclear factor-kappa B ligand (RANKL) and TGF-β and inhibits the transition from BM-MCSs to CAFs, resulting in lower chemotaxis and less proliferation in TM40D cells (42).
CAFs in BC lung metastases are mainly derived from lung RFs and BM-MSCs. One study found that the expression patterns of specific genes in the lung CAFs of mice with transgenic BC dynamically changed at different metastatic stages (91). Houthuijzen et al (71) reported that a RF population only found in the lungs was transformed into CAFs, promoting the lung metastasis of BC cells. Raz et al (41) used β-actin-GFP-PyMT double transgenic mice generated via adoptive bone marrow transplantation as donors, transplanted their bone marrow into non-transgenic control mice and found that GFP-labeled CAFs were specifically recruited in the primary BC tumors and lung metastases.
Lymph nodes are transit stations for tumor metastasis, but there have been few reports on the source of CAFs during lymph node metastasis (Met-LNs). Immunohistochemistry (IHC) assays showed that pCAFs in BC has similar biomarkers with mCAFs in matching Met-LNs (92) and only small differences were found in their transcription profiles (93,94). Such results suggest that Met-LN mCAFs were derived directly from pCAFs.
The experiments of Helms et al (75) revealed that different CAF precursor cells can differentiate into CAF cell lines of the same functional type under the action of multiple activation pathways. Notably, Han et al (95) had the opposite view, reporting that Tomato-labeled ISL1+ mesenchymal cells in mouse models of PDAC gradually expanded as the tumor progressed and eventually developed into a vast majority of CAFs. They hypothesized that CAFs in the PDAC stroma are more likely to have a single origin and their diversity comes from acquired stimulation from their complex microenvironment (95). This may pose a great challenge to the lineage-dependent heterogeneity of CAFs. Nonetheless, metastatic heterogeneity can still be explained by organ-specific microenvironments.
Differential activation patterns of pCAFs and mCAFs
CAFs exist in the TEMs as quiescent precursor cells and are abnormally activated to serve tumor proliferation, migration and drug resistance (Table II). In addition to lineage-dependent heterogeneity, the heterogeneity between pCAFs and mCAFs is also reflected in their mode of activation. First, fibroblasts in metastatic sites can be activated differently from CAFs in primary tumors (18). For example, macrophages promote the activation of HSCs into αSMA+ myCAFs which secrete high levels of periosteal proteins in the LMs of PDAC by producing granulin (96). CRC exosomal HSPC111 regulates the lipid metabolism of HSCs and promotes the formation of pre-metastatic liver niches (97). Furthermore, even identical CAF subtypes may exhibit different activation levels in primary and secondary sites. For example, the liver colonization of tumors is extremely dependent on TGF-β signaling in the liver stroma (98), which is compatible with the high ECM stress of the liver. This is because TGF-β is present in the ECM and binds to latent TGF binding proteins; its activation and release require mechanical forces acting on integrin-specific domains (99). TGF-β released under the high ECM stress in LMs participates in ECM remodeling and EMT through classical and non-classical pathways and plays a decisive role in cancer cell migration and invasion (100,101). The positive feedback loop of TGF-β secretion is established by TGF-β-activated CAFs through the SDF-1/C-X-C chemokine receptor 4 (CXCR4) signaling pathway (69,102). Some studies have shown that LMs express more CXCR4 than the primary tumor (103,104), which confirms the differential activation of pCAFs and mCAFs.
Notably, while the differences in activation modes between primary and metastatic CAFs are constantly being discovered, different CAF activation methods within the same site are also found in the complex microenvironment. In PDAC, IL-1 induces leukemia inhibitory factor expression and activates the downstream JAK/STAT pathway to transform PSCs into iCAFs, while TGF-β antagonizes this process by downregulating IL-1R1 expression and promoting myCAF generation (105). This indicates that there may be mutual antagonistic between different activation modes for CAFs, which may be the reason for the differential spatial distribution of these CAF subtypes in PDAC. The ability to dynamically change with different environmental stimuli reflects the extremely strong plasticity of CAFs, which may be one of the reasons why the source of CAFs so far remains elusive (106).
Differential expression levels of biomarkers in pCAFs and mCAFs
In most cases, CAF markers used are not considered to be representative of their functional heterogeneity and this is because CAFs lack unique markers, as most of them are also expressed in other cells (107). The classification of CAFs with known markers only compensates for the current lack of understanding on this topic, although combinatorial labeling improves the sorting accuracy of CAFs in complex environments (20). It should be noted that the classification of functional CAF subsets using markers is not as clear as that of immune cells. Additionally, due to the presence of different functional subtypes of CAFs, a single marker is not sufficient to distinguish them effectively. When attempting to generalize the prognostic value of the complete CAF population without distinguishing the effects of the heterogeneous CAF subgroups, contradictory results may be obtained (106). Nevertheless, a number of studies have investigated the prognostic value of commonly used CAF biomarkers in various types of cancer (108). Similarly, the differential expression of common markers in mCAFs and pCAFs has also been reported (8,109,110).
Different in fibroblast activation protein (FAP)
FAP is a type II transmembrane serine protease with both dipeptidyl peptidase and endopeptidase activity. It is expressed in ~90% of CAFs and is a hallmark of CAF activation (111). Studies have shown that FAP+ CAFs promote tumor progression, ECM degradation, tumor invasion, angiogenesis and immune suppression (112,113). Brain metastases from multiple types of primary tumors uniformly show high levels of FAP expression and no association of histological type (114), therefore, FAP may serve as a broad therapeutic target for brain metastasis.
As the most promising therapeutic target and radiotracer, FAP has become the focus of CAFs research in recent years (115,116). FAP inhibitors (FAPi) based on quinoline have been used as tracers for positron emission tomography and computerized tomography (PET-CT) diagnosis. FAPi can specifically bind to FAP and be internalized by CAFs. 68Ga, 177LU or 18F can chelate it and be fed back as image information through imaging systems for the diagnosis and identification of tumors (111). FAPi is characterized by high intratumoral uptake and rapid in vivo clearance. Various types of FAPi have since been developed and compared head-to-head with fluorodeoxyglucose (FDG) PET-CT, showing that FAPi tracers are more advantageous in discovering some primary, lymph node, or metastatic tumors (112,115,117). However, the sample sizes of these studies are very limited and there is still no convincing evidence of which tumor types or which metastatic organs are more appropriate to FAPi. However, it is important to improve the detection rate of early tumors and accurately determine the tumor stage to positively influence clinical decisions. Serfling et al (118) established a positive correlation and significance between FAP targeted expression and FAPi PET standardized uptake values (SUVs). In their study, 15 patients underwent 68Ga-FAPi-46 PET-CT scans to determine the biodistribution of 68Ga-FAPi-46 in various tissues (117). After subsequent surgical treatment, FAP expression was scored on the excised samples and the results showed a positive correlation between FAP IHC scores and the 68Ga-FAPi-46 SUVmax and SUVmean (119). In addition, Serfling et al (118) suggested that FAPα Met-LNs expression was correlated with lesion size. Sollini et al (120) reasoned that the relatively low performance of 68Ga-FAPi in detecting Met-LNs reported in some studies may be related to the low enrichment of CAFs within the lymph nodes. The SUVs of FAPi PET/CT reflects the expression of FAP in CAFs to a certain extent. This is an important means to compare marker heterogeneity between pCAFs and mCAFs. Data on the SUVs of primary tumors and metastatic tumors regarding FAPi PET-CT were collected and compared in order to find partial correlations. Disappointingly, research on FAPi tracers is still in its infancy. Moreover, factors such as their wide variety, insufficient sample size and the majority of studies being pan-cancer samples prevent the comparison of the data comprehensively. Although some meta-analyses have demonstrated the diagnostic advantages of FAPi tracers (120), this is not the focus of the present study. However, the present study still showed some results suggesting the possibility of differential expression of FAP between pCAFs and mCAFs (Table III).
Differences in α-SMA
α-SMA is a marker used to distinguish activated fibroblasts (95). Fibroblasts are activated to express α-SMA under inflammatory conditions, exhibit a hypercontractile phenotype and play a central role in wound healing (121). CAFs express high levels of α-SMA and are considered to be 'wounds that do not heal'. In tumors, α-SMA+ CAFs have been proven to be the main players in ECM modification, which is closely related to the integrin signaling cascade (9). Although previous studies have reported α-SMA+ CAFs secretion as a key regulator of cancer progression, therapeutic resistance and immunosuppression (83,122,123), the deletion of α-SMA-related genes and the targeted pharmacological inhibition can lead to a low reduction in survival and tumor differentiation and to an increase in angiogenesis and cachexia in mouse model of PDAC (18). Gui et al (8) found that BC metastases have a high expression of α-SMA. This is consistent with the results reported by Kwak et al (124), who found that patients with a high expression of CAF markers in their primary tumors also showed an tendency of higher of it in metastases, suggesting the possibility that mCAFs came from pCAFs. Notably, similar to the report of Serfling et al (118) on FAP, Itou et al (125) found that the distribution of α-SMA is also related to the size of LNs in Met-LN samples of intrahepatic cholangiocarcinoma, which is rare in micro-Met-LNs α-SMA, conversely, abundant α-SMA+ cells were found in macro-Met-LNs (118).
Differences in FPS1, PDPN and PDGFR
FPS1, PDPN and PDGFR are also commonly used as markers of CAFs (84). FSP1, also known as S100A4, is a common CAF marker. αFAP+ FSP1+ CAFs in human neuroblastoma were associated with M2-type macrophage, which enhances the proliferation and survival of neuroblastoma cells in vitro and stimulates implantation and growth of neuroblastoma tumor in vivo (126). FSP1+ fibroblasts accumulate around the carcinogen where they produce COLs, encapsulating carcinogen methylcholanthrene and protecting epithelial cells from DNA damage (127). Compared with FSP1, the expression of PDPN in various tumors is more consistent, as PDPN+ CAFs predict unfavorable prognosis in patients with various types of solid tumors, including stage IV lung cancer, bladder cancer and PDAC (128-130). PDGFRα/β+CAFs are able to induce polarization of M2 macrophages (29) and a PDGFR inhibitor called crenolanib has been shown to inhibit the growth of lung cancer cells in vivo (131). Research on PDGFR as a possible target for cancer therapy continues.
Among 64 patients with lung squamous cell carcinoma, 47 had a high level of PDPN expression in the primary stroma but 27 patients had a high level of PDPN in Met-LNs; univariate analysis found that only high PDPN expression in Met-LNs was significantly associated with prognosis (132). Koo et al performed immunohistochemical staining on different metastatic sites of BC and observed that FSP1 expression was significantly elevated in bone metastases while it was significantly reduced in LMs. The expression of PDPN was significantly elevated in bone metastasis and PDGFR expression was elevated in bone and lung metastases, but significantly reduced in LMs (109). These results prove that markers are expressed in different proportions in different metastatic sites. In one study, TNBC 4T1 cells were injected in situ into the breast fat pad of immunocompetent BALB/c mice, at week 4, it was observed that the proportion of PDPN+ CAFs, which originally accounted for 70% of the total CAFs, was reduced to 23% in the primary tumor, while FSP1+ CAFs, which originally accounted for 30%, increased to 77%. Notably, two FSP1+ CAF subtypes that were not observed in the primary tumor appeared in lung metastases and were shown to express IL6 and CXC chemokine ligand 1 (CXCL1), respectively (85).
The heterogeneity of CAFs from the perspective of scRNA-seq CAFs subtypes distinguished by transcriptional characteristics
Recent advances in scRNA-seq have allowed for a comprehensive profiling of the complexity and heterogeneity within the CAF subpopulations across various tumor entities (Table IV). Some reviews have examined the organ-specific features of CAFs and summarized the transcriptomic information of CAFs in different organs with ECM-remodeling, inflammation and immunity and antigen presentation (133,134). However, CAF subtypes do not exhibit universality across different tumor types, even though the classical myCAF and iCAF subtypes have been described in PDAC, BC and cervical cancer (59,135,136). scRNA-seq technology has the drawback of losing spatial information, resulting in incomplete information on the correlation between different CAF subtypes and the anatomical location of tumors. At the same time, the loss of temporal information makes it difficult to present the evolutionary trajectory of CAF subtypes. The integration of scRNA-seq and microarray-based spatial transcriptomics methods and pseudotime inference might be able to partially solve these issues (137,138). It is hypothesized that a more comprehensive understanding of the heterogeneity of CAFs will provide innovative solutions for cancer treatment and enable clinical applications.
Heterogeneity in the transcriptional features between pCAFs and mCAFs
The differences in transcriptional levels between mCAFs and pCAFs are being described as RNA-seq technology matures (23,139). The transcription profiles of MSCs obtained from bone metastases in BC are significantly different from those of CAFs obtained from the primary site (93). RNA-Seq for BC primary tumors and paired brain metastases yielded 48 differential gene expression signatures, most of which were those of immunity and fibroblasts (139). Similarly, another study noted the differential upregulation of genes associated with ECM remodeling and BM-derived cell recruitment in lung mCAFs compared with BC pCAFs (41). Within PDAC samples, Liu et al (140) found large changes in fibroblast subclasses at succeeding stages of PDAC progression, with the emergence of specific subclasses when cancer trespasses stroma to metastasize to proximal lymph nodes (stage IIA to IIB) and gene expression analysis showed increased expression of cytoskeletal protein and inflammatory cytokines when transition to IIB, indicating that tumor growth and metastasis are strictly regulated by genes.
Heterogeneity in microRNA profiles between pCAFs and mCAFs
MicroRNAs (miRNAs or miRs) are non-coding RNAs which can disrupt mRNA expression (141). Tumor cells can deliver miRNAs to CAFs through exosomes, promoting the malignant phenotype of CAFs (142). As expected, there are also differences between the miRNA profiles of pCAFs and mCAFs. Upon exposure to estrogen, the number of miRNAs upregulated or downregulated in skin mCAFs in BC is three times that in pCAFs (143), but the biological effects of these differentially expressed miRNAs need further verification. In advanced CRC, the differential expression of miR-21 between the center of the primary tumor and distant metastases is common (144). There were five upregulated and six downregulated miRNAs in the exosomes of mCAFs with peritoneal metastasis in ovarian cancer, among which miR-29c-3p downregulation was the most significant and positively correlated with patient overall survival (OS) (145).
Different secretomes of pCAFs and mCAFs
CAFs continuously release soluble molecules into the ECM to provide information feedback and functionally regulate the microenvironment (18,20). The biological characteristics of primary tumors and metastases are inseparable from cytokines secreted by pCAFs and mCAFs. CXCR4 is a G-protein-coupled receptor, which is little expressed if at all in normal cells, but dysregulated and aberrant in a number of tumors (146). The best characterized ligand that binds and activates CXCR4 is stromal SDF-1 (147). SDF-1/CXCR4 signaling has serious consequences on cancer cell differentiation, proliferation, invasion, metastasis and angiogenesis (148). Several studies have found that high expression of SDF-1/CXCR4 signaling is associated with high density of CAFs in tumor stroma (103,149). Tan et al (69) observed that there were more CXCR4+ cells at the LMs tissues Compared with the CRC primary sites. Maintenance of the SDF-1 gradient by the BC primary tumor is independently controlled by both miR-126 and miR-126*, which show a significantly lower expression in metastatic tissue compared with primary tumor tissue (150). Dai et al (149) detected a higher CAFs density in metastatic lesions than those in primary tumor site from human ovarian cancer tissues, however, no significant difference of SDF-1α production from CAFs was found between primary and metastatic lesions. This may require further validation of CXCR4 expression and regulation through methylation and acetylation (146). CAFs secrete leucine-rich α-2-glycoprotein 1 (LRG1) through the IL-6/Janus tyrosine kinase 2/signal transducer and activator of transcription 3 (IL-6/JAK2/STAT3) pathway (151). The expression of LRG1 is significantly upregulated in CRC LMs, making LMs more aggressive (151). In another study, increased aggressiveness was also found to be associated with high phosphoribosyltransferase expression in LMs (152). The secretome of mCAFs in peritoneal metastases of CRC mainly comprises insulin-like growth factor binding protein 2, CXCL2 and SDF-1, while pCAFs secrete higher levels of matrix metalloproteinases (MMP), chemokine (c-c motif) ligand 8 (CCL8) and CCL11 (153). Proteomic analysis showed that, compared with primary ovarian cancer tumors, 62 proteins in omentum metastases were significantly up- or downregulated, among which the expression of N-methyltransferase (NNMT) was significantly altered (104). NNMT transfers an active methyl group from SAM to nicotinamide to produce S-adenosylhomocysteine, the loss of which leads to decreased histone methylation, which affects gene expression (104). In another experiment, the difference between ovarian cancer primary tumors and metastases was also validated, where mCAFs were hypothesized to express higher levels of Jagged1 and cause peritoneal metastases to produce more vascular endothelial growth factor (VEGFA) and cyclin-dependent kinase inhibitor p21 (CDKN1A) (154). The methylation of metabolic genes NQO1 and ALDH1a3 induced in LMs downregulate the mRNA expression of metabolic genes in CAFs, however, compared with normal lung fibroblasts, the gene methylation levels of NQO-1 and ALDH1a3 in fibroblasts isolated from lung metastases remained at baseline levels (155).
Heterogeneity in the matreotype of pCAFs and mCAFs
In a cross-comparison analysis conducted via RNA-seq, the differential expression of ECM-related genes is the main feature of transcriptome heterogeneity in inter-organ fibroblasts (156). Different types of COL and glycoproteins crosslink with each other to form a stable ECM network. The post-translational modification of matrix components in various organs via hydroxylation, glycosylation, transglutamination, sulfation, crosslinking, cleavage and degradation further modulates these features (14), such changes happen dynamically on a time scale from seconds to minutes. In this way, the various matrix components expressed through time and space are called the matreotype of the tissue (157). In the PDAC mouse model, after the fibrogenic gene Sonic hedgehog was deleted, the tumor stroma was significantly reduced, but the tumor acquired enhanced angiogenesis and invasive capabilities (158). This suggests that in early stages of tumorigenesis, fibroblastic reactions orchestrated by CAFs within the TMEs envelop the tumor cells, inhibiting their growth and spread. However, as tumor stromal components continue to evolve during the course of tumorigenesis, the further modification of the behavior of CAFs helps their tumor-promoting properties (159). Notably, the tumor-promoting and tumor-restraining abilities of CAF at different stages of tumor progression can both be induced by TGF-β (9). In the early stages of tumors, TGF-β primarily promotes fibroblast proliferation to inhibit metastasis and as CAFs evolve, TGF-β can also induce CAFs to promote metastatic events such as EMT (160).
CAFs modify ECM differently in different metastatic organs (161), For example, pyruvate has previously been shown to promote hydroxylation in the ECM by enhancing the activity of the enzyme COL prolyl-4-hydroxylase, promoting the stability of the matrix in lung metastases of BC (162). Peptidylarginine deiminase 4 (PAD4) can modify arginine residues into citrulline in the presence of Ca2+ and proteomic analysis shows that PAD4 is more abundant in the LMs matrix, enhancing the colonization of CRC cells in the liver (163). In addition, tumor ECM drives the positive feedback of matrix deposition and hardening through TGF-β-mediated COL enrichment, lysine oxidase (LOX)-mediated COL hyper-cross-linking and the CAFs contraction-induced activation of the Yes-associated protein/WW domain containing transcription regulator 1 (YAP/TAZ) and myocardin-related transcription factor A (MRTF-A) pathways to transform the compliance, stiffness, porosity, viscoelasticity and biochemical properties of the ECM (14,164,165). Shen et al (12) used atomic force microscopy and observed that the tissue hardness of LMs was higher than that of CRC primary lesions. Large RNA-seq data show that CAFs were more abundant in primary CRC tumors than in LMs, but contractile cluster 3 was only expressed in LMs (166). Furthermore, some independent laboratories have obtained significantly different results in the determination of hyaluronic acid (HA) content in PDAC primary tumors and metastases (167,168).
However, several experiments by Ueno et al (169) and Ao et al (170,171) revealed similarities in the desmoplastic reaction of CRC primary tumors, LMs and Met-LNs and they are equivalent in prognostic evaluation. These studies yielded different results, possibly due to differences in the sample size, staining methods and the selection of different metastatic sites. A technique called in situ tissue decellularization of tissues may help eliminate systematic errors and more objectively evaluate the ECM in various biological contexts. This method preserves the structural ECM of tissues while efficiently removing cells, preventing tissue collapse and using natural tissue and organ vasculature (172). Furthermore, the authors verify that the ECM obtained using this technique does not differ from that of fresh tissue in terms of distribution and orientation, fiber gaps, fiber integrity and fiber diameter (172). Using this technology, Mayorca-Guiliani et al (172) constructed a natural lung metastasis ECM structure map and reproduced the whole process of lung metastasis ECM remodeling in a mouse model.
The heterogeneity between pCAFs and mCAFs in the plasma membrane, cytoplasm, exosomes and the nucleus has been extensively characterized, deepening our understanding of the differences in the microenvironments of primary tumors and metastases. However, most of the data collected focused on the differences between NFs and CAFs or CAFs in metastatic and nonmetastatic primary tumors (85,173-175), which is conducive to highlighting metastasis-inducing factors. Pseudo-time RNA-seq analysis using matched normal tissue around the tumor, primary tumor and metastatic tumor to simulate pre-tumorigenesis, early-stage tumors and advanced-stage tumors, respectively, has shortcomings in effectively simulating the dynamic changes of CAFs during tumor evolution (18). However, it is an excellent model to describe the spatial heterogeneity of pCAFs and mCAFs after metastasis occurs, which helps to explore more about this in the future.
3. Differential therapeutic response mediated by pCAFs and mCAFs
Molecular mechanisms underlying the differential treatment outcomes
We have previously discussed the differences between pCAFs and mCAFs from multiple aspects of their biological characteristics and their abilities in shaping the microenvironment of primary and metastatic tumors. When facing treatment pressure, the microenvironment of metastatic tumors provides more efficient protection for the survival of tumor cells (8). mCAFs may make metastatic tumors relatively more drug-resistant through EMT or sustaining cancer stemness (Fig. 3B). Gui et al (8) isolated eight CAFs from normal tissues, primary tumors and multiple metastatic tumors of patients with BC Co-culture in vitro has shown that mCAFs can enhance the proliferation, migration and invasion of BC cell lines. The team further verified the resistance of mCAFs to treatment and their results showed that tumor cells co-cultured with mCAFs exhibited stronger doxorubicin resistance than pCAFs and observed that mCAFs induced tumor cells to undergo EMT and express more tumor stem cell markers (8), which may be one of the mechanisms underlying the stronger drug resistance in metastases (176,177). Comparison of the gene expression profiles of pCAFs and mCAFs revealed multiple significantly differentially expressed genes, of which IGF2 was the most significantly enriched (8). The overexpression of IGF2 was shown to play a key role in chemotherapy resistance (178). Mukherjee et al (154) discovered that when CAFs differentially overexpressing Jagged1 were co-cultured with ovarian cancer cells, the Notch3 signal increased with the increase in the expression level of Jagged1. Peritoneal metastasis mCAFs obtained from ascites have been shown to express higher levels of Jagged1 than the primary tumor (154). Further experiments show that CAFs affect the expression of VEGFA and CDKN1A through Jagged1/Notch3, increasing the proportion of tumor stem cells and resistance to cisplatin (154).
In addition, CAFs and immune cells are the main supporting cell populations in solid tumors and there is extensive functional interaction between them (7). Although pCAFs and mCAFs can crosstalk with immune cells in various ways, affecting their chemotaxis and polarization, and regulating the immune response in the TMEs (60,179), mCAFs may achieve protective effects against metastases through stronger immunosuppressive effects (Fig. 3C). A RF population that highly expresses cyclooxygenase-2 has been shown to exist only in the lung, where it promotes the lung metastasis of BC cells and inhibits the antigen presentation function of BM dendritic cells (71). CRC peritoneal metastasis mCAFs have a different secretome from pCAFs as the macrophages displayed expression profiles associated with T cell biology with a pronounced shift to a type 2 immune response and T cell tolerance (153). Similarly, peritoneal metastases mCAFs have been found in mouse models of gastric cancer to induce macrophage M2 polarization, resulting in low infiltration of CD8+ T cells (16).
Heterogeneity of matreotype affects the drug response
Most anti-tumor resistance studies focus on exploring the underlying molecular mechanisms. However, the limited distribution of drugs in tumors is often ignored. Drug penetration efficiency directly can affect drug efficacy and its influencing factors involve the ECM, vascular structure and hemodynamics (180). It is well known that the ECM forms a physical barrier that greatly impedes drug delivery (180). Some studies have described the heterogeneity in physical properties between the primary and metastatic stroma and the difference in the matreotype may be the key to the differences in the response of different metastatic organs to anti-tumor treatment (12,74,181) (Fig. 3A).
Studies have proven that stromal mechanical stress can guide the directed differentiation of naïve MSCs (182). For example, vascular progenitor cells with low and high stiffness differentiate into endothelial and smooth muscle cells, respectively, under the mediation of integrin (181). In another study, the effects of load initiation time, magnitude and mode of mechanical force on the formation of microvascular networks were also simulated (183). This means that primary tumors and metastases produce different the microvascular system in different matreotypes. For example, despite tumor vascularization, irregular vascular networks enhance blood fluid resistance in mouse models of LMs, leading to capillary collapse within metastases and limiting the tumor perfusion of drugs (13). Furthermore, stromal hyperplasia and a lack of blood supply have been shown to lead to a series of malignant events, such as hypoxia, in the deep tumor (182). Hypoxia has been previously found to be an important cause of treatment resistance (184).
In addition, the deposition of ECM traps immune cells in the tumor stroma and increases their resistance to infiltration into the tumor parenchyma (14). Gertych et al (15) observed that there was a difference in the proportion of CAFs in primary tumors and metastases and the differences in the matreotypes between the two were determined by COL11A1+ CAFs, although there is high CD8+ T cell infiltration in metastases, they are excluded by the proliferating ECM, resulting in a lower survival rate.
Notably, some studies have found that high intratumoral drug concentrations do not improve anti-tumor efficiency (185,186). Hence, the role of the TMEs as a physical barrier for drug delivery becomes worth re-examining. Hessmann et al (74) observed that KPC tumors had more CAFs and stromal hyperplasia than LMs and they found that CAFs captured 2′,2′-difluorodeoxycytidine-5′-triphosphate (dFdCTP), an active metabolic component of gemcitabine, thereby reducing the chance of gemcitabine contact with tumors, resulting in PDAC primary tumors with lower sensitivity to chemotherapy than matched LMs. This demonstrates that the response of CAFs to the highly selective pressure exerted by chemotherapy is pluralistic, which may explain why successful treatments targeting the ECM are difficult.
4. Potential therapeutic opportunities targeting mCAFs
Metastases are almost incurable and are the underlying cause of mortality in most patients with cancer (10). The fact that mCAFs cause metastasis treatment resistance makes it a promising therapeutic target (17). Eliminating or balancing the differences between mCAFs and pCAFs may be an effective treatment method (8,154). As aforementioned, most of the differences between primary tumors and metastases are 'more and less' rather than 'presence or absence', which means that treatments targeting the differences between them not only improve the sensitivity of metastases also benefit primary tumors. Although targeting mCAFs in mouse models or cell experiments is emphasized, when these drugs are used in human trials, there is more hope of achieving simultaneous remission of both the primary and metastatic tumors. Therefore, the present study did not emphasize whether the new therapeutic agents of clinical trials are mCAFs or pCAFs.
Restoration quiescence or apoptosis induction of mCAF precursor
Different metastatic organs have specific sources of CAF precursor cells; therefore, directly killing these precursor cells or restoration of their quiescence in the target organ can eliminate or attenuate their malignant effect on the metastatic microenvironment (10,187) (Fig. 4B). Bhattacharjee et al (35) depleted HSCs in triple transgenic mice through the injection of diphtheria toxin (DT) and the TdTomato reporter gene showed that 97% of the HSCs were depleted. In the PDAC and CRC mouse models, the depletion of HSCs led to a significant reduction in the area of LMs. The natural compound curcumin induces HSC senescence by activating peroxisome proliferator-activated receptor γ and promoting P53 expression (188). In a recent study, the targeted biomimetic nanoparticle-based delivery of all-trans-retinoic acid in resting HSCs improved artificially induced liver fibrosis in mice (189). Although numerous chemicals, herbs and their bioactive extracts have been proven to promote the apoptosis of HSCs, at present, no recognized HSC-depletion drugs have been approved for clinical use (187). Hence, there is still a long way to go in developing mCAF-derived treatments for metastases.
Targeting differentially expressed markers in mCAFs
Identifying the proportional expression of markers in primary tumors and metastases is a prerequisite for accurately targeting metastases. However, sufficient epidemiological evidence or clear molecular mechanisms regarding independent prognostic markers are necessary. FAP is probably the most reliable marker, as large studies have shown that the high expression of FAP is an independent prognostic marker for poor prognosis in ovarian cancer, lung cancer, PDAC, hepatocarcinoma and CRC (113,190). Therapeutic strategies for FAP, including FAP-activating drugs, DNA vaccines, anti-FAP chimeric antigen receptor redirected T cells, radionuclide-based approaches and FAP antibodies conjugated with toxins, have been reported to be effective in clinical and preclinical studies (111,113,115,191) (Fig. 4A). FAP-4-1BBL has bispecific antibody activity that can act on both FAP and the co-stimulatory molecule 4-1BBL and has been designed to provide costimulatory signals to immune effector cells selectively within the tumor (192). FAP-4-1BBL co-stimulates T cells in ex vitro in patient-derived tumor tissues, additionally the combination of carcinoembryonic antigen-targeted T cell bispecific antibody and FAP-4-1BBL in mouse models can induce the infiltration of CD8+ T cells and tumor regression (192). Subsequently, the first-in-human study of the FAP-4-1BB agonist RO7122290 was initiated in patients with advanced solid tumors, however, the study was not designed to demonstrate differences between single-agent and combination therapy (193). A case report described a patient with BC and brain metastases who experienced a decrease in the intensity of headaches after 4 weeks of FAPi targeted radiotherapy (194). In other studies, radiotherapy strategies based on the high expression of FAP and FAPi may create a new integrated tumor diagnosis/treatment model in the future. High FAPi expression on FAPi-46 PET-CT was a criterion of consideration for peptide-targeted radionuclide therapy following two cycles of 177Lu-FAPi-46 targeted therapy. In the selected patients, 12 of the 18 advanced patients were stable disease with no significant change in clinical condition but the remaining six progressed (195). Another group conducted a similar study (196). Unfortunately, these studies did not provide the information on local response status in each patient, so it is unknown whether the therapeutic benefit was correlated to the SUVs and whether low FAP expression implies resistance to FAP-targeting therapy.
Targeting the matrix of metastases
The penetration efficiency of drugs in tumors directly affects the drug concentration in contact with tumors. The means of targeting the ECM mainly include adjusting the modification state to inhibit ECM deposition, reducing the production of COL to soften tumors and directly shearing the ECM (Fig. 4C). For example, inhibiting citrullination can reduce LMs growth in CRC (163). As an important active enzyme for ECM crosslinking, LOX can also achieve tumor anti-fibrosis by inhibiting it (197). Hepatic fibroblasts express angiotensin II (AngII), a component of the RAS system. AngII activates the AngII type I receptor (AT1R) to undergo liver fibrosis through downstream JAK2 signaling (198). Using patient samples and atomic force microscopy, Shen et al (12) found that tissue stiffness is higher in LMs than in primary CRC. Highly activated mCAFs increase tissue stiffness, which enhances angiogenesis and anti-angiogenic therapy resistance. Drugs targeting the LMs mCAFs RAS system inhibit fibroblast contraction and ECM deposition, thereby reducing LMs stiffening and increasing the anti-angiogenic effects of bevacizumab (12). The use of valsartan in the treatment of spontaneous lung metastases of BC in mouse models inhibits the production of fibronectin and vimentin and reduces the occurrence of lung metastases (199). Another phase II clinical trial of FOLFIRINOX in combination with losartan has also achieved promising results as a neoadjuvant therapy for locally advanced unresectable PDAC (200). These studies demonstrate the anti-tumor efficacy of reduction of ECM stiffness, however, there seems to be little therapeutic breakthrough in clinical trials involving the direct degradation of the ECM. PEGPH20, is a polyethylene glycol hyaluronidase and early research has found that it can increase the distribution concentration of antitumor drugs in primary and metastatic tumors by degrading HA in the ECM (201). However, PEGPH20 combined with standard regimens for advanced PDAC has failed in multiple clinical trials. Some hypothesize that using only one ECM-degrading enzyme may be the reason for not meeting the expected clinical outcomes (202). However, this does not explain the negative results of the phase IB/II trial of PEGPH20 in combination with FOLFIRINOX in patients with metastatic PDAC (203). This is more likely due to the fact that ECM degradation products have a similar structure to some growth factors and they can bind to the corresponding receptors and activate downstream signaling pathways (14). Another clinical trial investigated AG in combination with PEGPH20 in the treatment of advanced PDAC. Although the combination group showed an increased objective response rate, it did not show improved OS or progression-free survival (204). Meanwhile, it was shown to increase the risk of thromboembolism, which requires prophylaxis with heparin. Hence, from a number of perspectives, PEGPH20 is not an optimum treatment choice.
Therapies targeting the matrix can also enhance the invasion of immune cells in metastases, which can be achieved by blocking the SDF-1/CXCR4 signaling axis in the case of BC metastasis (103) (Fig. 4D). Through modifications, some drugs with direct tissue penetration have also been developed (205), including lipophilic liposomes, albumin preparations, water-soluble prodrug preparations and nanocrystals (206). These modifications have been shown to enhance the precise delivery of drugs in the complex ECM environment of metastases.
Other treatment strategies
Directly targeting the up- or downstream pathways of mCAFs is another method to relieve the drug tolerance of metastases, which is related to the crosstalk between mCAFs and metastatic tumor cells (Fig. 4A). Gene silencing or receptor blocking of IGF2 can effectively inhibit the promoting effect of mCAFs on the growth of metastatic tumors (8). CXCR4 is highly expressed in LMs from BC and CRC and the CXCR4 inhibitor AMD3100 has been shown to alleviate desmoplasia in metastases (69,103). CXCR4 blocking has also been observed to sensitize the mBC tumors to immune checkpoint blockers (103). Similarly, silencing LRG1, which is highly expressed in LMs, can significantly reduce tumor migration and invasion (151). IL-1R knockout mice have demonstrated that IL-1β secreted by tumors can induce bone mCAFs to secrete SDF-1, promoting bone metastasis and this effect can be blocked by the IL-1 inhibitor anakinra (207). ECM-CAFs make up a high proportion in LMs, especially at the center of LMs, and promote vascular growth and tumor proliferation by secreting LTBP2; siRNA-mediated silencing of LTBP2 expression can regulate the phenotype of ECM-CAFs (68). Tranilast inhibits the production of SDF-1 in the myCAF cell line LmcMF in a mouse peritoneal metastasis model of gastric cancer, reducing the infiltration of M2 macrophages and leading to apoptosis of cancer cells by an immune response (208). However, the LmcMF cell line used in that study completed peritoneal implantation via intraperitoneal injection and may not represent the true source of mCAFs in peritoneal metastases. Although a large number of positive results have been obtained in laboratory studies, large-scale clinical trials are needed to provide direct evidence for blocking the upstream and downstream signals of mCAFs to improve the control rate of metastases and reveal a new avenue for advanced treatment in various tumors.
5. Conclusion
The reason why the present study emphasized the heterogeneity of pCAF and mCAF is because CAFs are the main cellular components in ECM and the frequent information exchange between different 'personalities'. CAFs with tumor cells result in great differences between metastasic and primary TMEs, ultimately showing different resistance in treatment. The present study described these differences in terms of origin, activation patterns, markers, matreotype, cytokines and transcriptome profiles.
In fact, there are a number of differences between pCAFs and mCAFs that may explain the low treatment responsiveness of metastases and some studies eliminated these differences to enhance the sensitivity of metastases to treatment options (8,12). However, one should pay attention to the fact that differences in the distribution of various CAF subsets exist even within the primary tumor, the best examples being the tumor center and the invasion front (124). Furthermore, CAFs have a very clear stage-dependent heterogeneity and the identity and prevalence of the various CAF subtypes present in a tumor or metastatic site change in response to normal, inflammatory, precancerous and malignant states, including anticancer treatment (18). These characteristics of CAFs also change as tumor growth progresses (85). The heterogeneity of pCAFs and mCAFs presented in the present review is only a cross-section at a certain point in time. Therefore, it is necessary to rely on new culture methods and observation methods to comprehensively and clearly describe the succession process and role of CAFs in the progression of the entire tumor.
Therapies targeting CAFs are currently being developed, including methods such as blocking ECM deposition and remodeling, directly targeting tumor-promoting CAFs, or using the plasticity of CAFs to engineer them into tumor-suppressing phenotypes (10). Most of these treatment strategies have failed because the heterogeneity of CAFs in different cancer types, tumor stages and metastasis sites makes these treatment methods one-sided (106), requiring a more comprehensive understanding of the role of CAFs within tumors. Future treatment options for advanced tumors may not only consider the molecular type of the tumor but also comprise more elaborate individualized treatment strategies which consider the heterogeneity of pCAFs and mCAFs. Some challenging questions lie ahead, such as the criteria for identifying the heterogeneity between mCAFs and pCAFs. Additional treatment for metastases will inevitably increase patient intolerance, so that screening for highly effective, low-toxicity sensitizers becomes particularly important. In addition, the timing of metastasis treatment and the choice of local or systemic treatment still needs to be solved urgently.
In conclusion, considering the biological heterogeneity of pCAFs and mCAFs, the present study provided a new perspective on the differential outcomes of primary and metastasis tumor treatment, revealing their key role in shaping different TMEs. It also explored possible means to improve the clinical treatment of metastases, providing new ideas for advanced anti-tumor treatments.
Availability of data and materials
Not applicable.
Authors' contributions
CS and QZ conceived and designed the present study. ZK and CL contributed to data analysis and wrote the manuscript. WZ was responsible for the figures. LL supervised the study, aided by QZ and CS. Data authentication is not applicable. All authors read and approved the final manuscript.
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:
|
CAFs |
cancer-associated fibroblasts |
|
mCAFs |
metastatic CAFs |
|
pCAFs |
primary CAFs |
|
RFs |
resident fibroblasts |
|
ECM |
the extracellular matrix |
|
MSCs |
mesenchymal stem cells |
|
BM-MSCs |
bone marrow-derived MSCs |
|
NFs |
Normal fibroblasts |
|
PSCs |
pancreatic stellate cells |
|
HSCs |
hepatic stellate cells |
|
LMs |
liver metastases |
|
myCAFs |
myofibroblastic CAFs |
|
iCAFs |
inflammatory CAFs |
|
PFs |
portal fibroblasts |
|
apCAFs |
antigen-presenting CAFs |
|
scRNA-seq |
single-cell RNA sequencing |
|
αSMA |
smooth muscle actin-α |
|
TGF-β |
transforming growth factor-β |
|
Met-LNs |
lymph node metastasis |
|
EMT |
epithelial-mesenchymal transition |
|
FSP1 |
fibroblast-specific protein 1 |
|
FAP |
fibroblast activation protein |
|
FAPi |
FAP inhibitor |
|
PDGF |
platelet-derived growth factor |
|
PDGFR |
PDGF receptor |
|
SDF-1 |
stromal cell-derived factor 1 |
|
OPN |
osteopontin |
|
COL |
collagen |
|
CXCR |
C-X-C chemokine receptor |
|
IL |
interleukin |
|
SUVs |
standardized uptake values |
|
LRG1 |
leucine-rich ɑ-2-glycoprotein 1 |
|
SAM |
S-adenosyl methionine |
|
LOX |
lysyl oxidases |
|
HA |
hyaluronan |
Acknowledgments
Not applicable.
Funding
The present study was supported by grants from the National Natural Science Foundation of China (grant nos. 82305000, 81973677 and 82174222), Natural Science Foundation of Shandong Province (grant no. ZR2021LZY015), Traditional Chinese Medicine Science and Technology Project of Shandong Province (grant no. Q-2023205) and Weifang Science and Technology Development Plan (grant no. 2022GX008).
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