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Review

Cancer-Associated Fibroblasts: Understanding Their Heterogeneity

by
Kévin Louault
1,2,3,*,
Rong-Rong Li
4 and
Yves A. DeClerck
1,2,3,5,*
1
Division of Hematology, Oncology and Blood and Marrow Transplantation, Children’s Hospital Los Angeles, Los Angeles, CA 90027, USA
2
Department of Pediatrics, Keck School of Medicine of the University of Southern California, Los Angeles, CA 90027, USA
3
The Saban Research Institute, Children’s Hospital Los Angeles, Los Angeles, CA 90027, USA
4
Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA 90033, USA
5
Department of Biochemistry and Molecular Biology, Keck School of Medicine of the University of Southern California, Los Angeles, CA 90033, USA
*
Authors to whom correspondence should be addressed.
Cancers 2020, 12(11), 3108; https://doi.org/10.3390/cancers12113108
Submission received: 12 September 2020 / Revised: 12 October 2020 / Accepted: 21 October 2020 / Published: 24 October 2020
(This article belongs to the Special Issue Cancer-Associated Fibroblast)
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Abstract

:

Simple Summary

Cancer-associated fibroblasts (CAFs) play an important contributory role in the microenvironment of tumors. They originate from different cells, have multiple pro-and anti-tumorigenic functions in tumors and their presence is variable among cancer types. Recently, there has been evidence that CAFs represent a highly heterogeneous group of cells that can now be characterized and identified at the single cell level. This review article summarizes our recent understanding of the highly heterogeneous nature of the origin, phenotype and function of CAFs and how such understanding will lead to a more precise approach to target or use CAFs and their precursor cells in the treatment of cancer.

Abstract

The tumor microenvironment (TME) plays a critical role in tumor progression. Among its multiple components are cancer-associated fibroblasts (CAFs) that are the main suppliers of extracellular matrix molecules and important contributors to inflammation. As a source of growth factors, cytokines, chemokines and other regulatory molecules, they participate in cancer progression, metastasis, angiogenesis, immune cell reprogramming and therapeutic resistance. Nevertheless, their role is not fully understood, and is sometimes controversial due to their heterogeneity. CAFs are heterogeneous in their origin, phenotype, function and presence within tumors. As a result, strategies to target CAFs in cancer therapy have been hampered by the difficulties in better defining the various populations of CAFs and by the lack of clear recognition of their specific function in cancer progression. This review discusses how a greater understanding of the heterogeneous nature of CAFs could lead to better approaches aimed at their use or at their targeting in the treatment of cancer.

1. Introduction

Over the last few decades, scientific evidence in support of Paget’s "Seed and Soil" theory has been obtained through an improved understanding of the cellular and molecular hallmarks of cancer cells (the Seed) and an in-depth characterization of the highly complex tumor microenvironment (TME; the Soil) [1,2,3]. Four major components of the TME [4] have been identified: 1) an immune component known as the tumor immune microenvironment (TIME), composed of a large variety of innate immune cells such as tumor-associated macrophages (TAMs), natural killer (NK) cells, neutrophils, mast cells, dendritic cells (DCs), myeloid-derived suppressive cells (MDSCs) and of adaptative immune cells including CD4+ T helper lymphocytes (Th), CD8+ cytotoxic T cells, NK-T cells, γδT cells, regulatory T cells (Treg), and B cells [5,6,7,8]; 2) a vascular component consisting of micro-vascular and lymphatic endothelial cells (ECs) and pericytes [9,10]; 3) an extracellular matrix (ECM) component made of diverse collagen molecules, glycoproteins and proteoglycans [11,12]; and 4) a less well defined stromal component that includes non-immune cells of mesenchymal origin such as mesenchymal stromal cells (MSCs) and cancer-associated fibroblasts (CAFs), which are the focus of this review [13,14].
Fibroblasts are characterized by their contractile and ECM remodeling activities [15]. These cells become activated and proliferate during inflammation, wound repair and fibrosis, and during malignant progression where they were first reported to accelerate the growth of epithelial tumors by L.W. Chung et al. and were later designated as cancer-associated fibroblasts (CAFs) [14,16,17,18]. For some time, CAFs were considered a homogeneous population of ECM-producing stromal cells, responsible for the stiff 3-D architecture of a tumor. However, multiple studies over the last two decades have indicated that CAFs are not innocent bystanders in tumors and can have pro- or anti-tumorigenic functions [19,20,21]. These opposite activities raise the question of whether CAFs represent a homogeneous and well-defined population of stromal cells or rather are members of a heterogeneous group of stromal cells that differ in their origin, phenotype, function and presence in different types of cancers. Recent evidence indicates that it is the latter rather than the former situation. In this review, we discuss how these differences could explain the various and sometimes contradictory roles of CAFs in cancer progression, and how such heterogeneity makes their consideration in cancer therapy challenging.

2. Origins of CAF Heterogeneity

There is now strong experimental evidence that CAFs can originate from a variety of cells such as resident fibroblasts, a variety of precursor cells that differentiate, mature cells that de-differentiate or transdifferentiate, or even tumor cells (Figure 1) [22].
Resident fibroblasts are located in the tissue of origin of the primary tumor and are the main source of CAFs in a tumor. Transforming growth factor beta 1 (TGF-β1), secreted by stromal and tumor cells, is the main factor promoting the mobilization of resident fibroblasts and their activation into CAFs [23,24]. TGF-β1, through SMAD-dependent and independent pathways, activates fibroblasts into CAFs, expressing alpha-smooth muscle actin (α-SMA, a.k.a. ACTA2), periostin (POSTN), α-fibroblast activation protein (αFAP, a.k.a. dipeptidylpeptidase IV) and fibroblast specific protein-1 (FSP-1, a.k.a. S100A4), and produces type I collagen [25]. Other factors secreted by tumor cells such as platelet-derived growth factor (PDGF), fibroblast growth factor (FGF), sonic hedgehog (SHH) and interleukin (IL) 1-β promote the conversion of resident fibroblasts into CAFs through activation of signaling pathways such as the extracellular signal regulated kinase (ERK), Shh/Smo (smoothened), or nuclear factor kappa-B (NFκB) pathways [26,27,28,29]. CAFs are characterized not only by their expression of α-SMA, αFAP and FSP-1, but also by their production of vascular endothelial growth factor (VEGF) and cytokines like IL-6 and IL-8 [26,27]. Hypoxia is another factor that promotes the activation of resident fibroblasts into CAFs through the accumulation of reactive oxygen species (ROS) and activation of the hypoxia inducible factor (HIF)-1α-mediated signaling pathway [30,31,32]. In pancreatic cancer, vitamin A and D are responsible for reprogramming CAFs from a quiescent state into an active pro-tumorigenic state via activation of SMAD signaling or the renin-angiotensin system, increasing the proliferation and metabolism of CAFs [33,34,35] Moreover, activated fibroblasts secrete TGF-β1 and the C-X-C chemokine ligand-12 (CXCL-12; a.k.a. stromal-derived factor (SDF) -1), which both act through autocrine and paracrine mechanisms to initiate and maintain their myofibroblasts phenotype and their tumor-promoting function [36].
CAFs also originate from a variety of precursor cells recruited by tumor cells at the sites of primary growth or metastasis. Among these, MSCs are an important source of CAFs and can provide up to 20% of the CAF population in a tumor [37]. They express similar markers as the CAFs derived from resident fibroblasts, i.e., α-SMA, vimentin (VIM) and αFAP, along with MSC markers including CD90 (a.k.a. THY1), CD105 (endoglin) and CD73 (a.k.a. 5’-nucleotidase) [37,38]. The recruitment of MSCs and their activation into CAFs are stimulated by CXCL-12 and TGF-β secreted by tumor cells [39,40,41]. Furthermore, hepatoma-derived growth factor (HDGF) and IL-1β promote the secretion by MSCs of pro-tumorigenic cytokines that stimulate tumor progression [37,42,43].
CAFs can also derive from mature cells. Through TGF-β-mediated epithelial to mesenchymal transition (EMT), epithelial cells differentiate into functional CAFs expressing FSP-1 and αFAP [44,45]. ECs contribute to the pool of CAFs through a similar process known as EndoMT, driven by TGF-β and SMAD signaling [46]. Pericytes, adipocytes, fibrocytes and stellate cells are all sources of CAFs. They are recruited in tumors by TGF-β and CXCL-12, and activated into CAFs by TGF-β or PDGF via mechanisms similar to those activating resident fibroblasts [46,47,48,49,50,51,52]. It has also been demonstrated that cancer cells, in particular cancer stem cells, can be a source of CAFs under the action of TGF-β [22,53].

3. Phenotypic and Functional Heterogeneity

CAFs represent a heterogeneous population of cells. Major challenges in defining the sub-populations of CAFs have been the lack of consistency in identifying specific robust markers and difficulties in defining the association between subgroups and their specific function in cancer. However, a more comprehensive picture emerges based on a review of the most recent literature (Figure 2 and Table 1).

3.1. Phenotypic Markers Associated with Specific CAFs Activities

α-SMA has long been the main marker used to characterize CAFs [18], despite being expressed by most mesenchymal cells including normal fibroblasts, myo-fibroblasts, myocytes and pericytes [74,75]. CAFs were later defined by the absence of expression of epithelial markers (cytokeratin, E-cadherin), ECs marker (CD31) and myeloid marker (CD45), and by the expression of mesenchymal markers such as VIM, FSP-1, PDGF receptor beta (PDGFRβ) and αFAP [18,76,77]. Although highly expressed in CAFs, these proteins are also expressed by mesodermal cells (αFAP), myeloid cells (FSP-1), pericytes (PDGFRβ) and normal fibroblasts (FSP-1, PDGFRβ) [78,79], reflecting their lack of specificity.
However, more recent studies in a variety of murine cancer models and human tumors have now identified and characterized subpopulations of CAFs with specific functions based on surface markers, secreted proteins and transcriptome. R. Kalluri‘s laboratory was the first to bring attention to the heterogeneity among CAFs by describing two sub-populations of murine pro-tumorigenic CAFs in breast and pancreatic cancer models [54]. The first sub-population, labeled CAF-1, consists of CAF-expressing FSP-1, that promotes metastatic colonization by tumor cells [54,55,56]. In an orthotopic mouse model of breast cancer, they show that the production of tenascin by these FSP-1+ CAFs promotes VEGF-A-mediated angiogenesis and metastasis [55]. The second sub-population, called CAF-2, is characterized by the expression of α-SMA, neural/glial antigen 2 (NG2) and PDGFRβ [60]. This subtype of CAFs is a source of type I collagen, contributing to the formation of a fibrotic connective tissue barrier that prevents tumor infiltration by cytotoxic T lymphocytes [57]. Two different sub-populations of CAFs, designated CAF-N (normal) and CAF-D (divergent) were later described in human oral squamous cell carcinoma (OSCC). CAF-N secrete hyaluronic acid (HA) and matrix metalloproteinases (MMPs), promoting tissue invasion by cancer cells and by fibroblasts, and creating a HA-rich and immunosuppressive ECM, while CAF-D are a source of TGF-β that induces EMT in cancer cells and promotes cell migration [58,59]. In human colorectal tumors, two other sub-populations of CAFs were reported based on their transcriptome, CAF-A, rich in MMP2, αFAP and COL1A2 (type 1 collagen α−chain 2) mRNA, and CAF-B, rich in α-SMA, PDGF-A and TAGLN (transgelin) mRNA, but their function was not determined [60].
In human pancreatic ductal adenocarcinoma (PDAC) tumors and in transgenic mice engineered to carry KRas and p53 mutations under the control of the pancreatic specific Cre promoter (KPC), different subpopulations of CAFs were identified based on their expression of meflin, a glycosylphosphatidylinositol-anchored protein expressed by MSCs that maintains their undifferentiated state. Meflin-poor CAFs (pCAFs) have a pro-tumorigenic function, whereas meflin-rich CAFs (rCAFs) suppress PDAC progression by acting on ECM remodeling, hypoxia and cancer initiation [61,62]. The concept that some subpopulations of CAFs exert their function through the production of ECM proteins whereas other subpopulations of CAFs act as inflammatory cells is suggested by some recent reports. In mice xenotransplanted with PDAC tumors, pancreatic stellate cells (PSC) were shown to differentiate into α-SMA+ myofibroblasts, designated myCAFs, producing collagen and TGF-β, or into inflammatory CAFs having an immunomodulatory function, designated iCAFs secreting IL-6, IL-11 and leukemia inhibitory factor (LIF) that promote immune escape [63]. Using single cell RNA-sequencing analysis (scRNA-seq), a new powerful tool to further define CAF heterogeneity, it has been shown that iCAFs are characterized by the production of inflammatory cytokines and chemokines such as IL-6, IL-8, CXCL1, CXCL12 and other proteins like complement factor D (CFD), lamin A/C (LMNA), podoplanin (PDPN), and dermatopontin (DPT), whereas myCAFs are characterized by the expression of ACTA2, PDPN, TAGLN, tropomyosin 1 and 2 (TPM1, TPM2) and POSTN [64,65,66]. iCAFs promote metastasis, angiogenesis and have an immunomodulatory function through their production of cytokines and chemokines. iCAFs secrete CCL17 and CCL22 that recruit Treg cells in tumors, resulting in an immunosuppressive microenvironment [80], and CCL2 and CXCL12 that recruit monocytes and promote their maturation into MDSCs that inhibit CD8+ T lymphocytes [81,82]. In contrast, myCAFs through the production of ECM proteins and TGF-β induce EMT and promote tumor cell proliferation, invasion and metastasis. A specific subtype of myCAFs expressing leucine-rich repeat containing 15 (LRRC15) is associated with chemoresistance to therapy targeting programmed death ligand-1 (PD-L1) in patients [66]. Another subtype of CAFs with an important immunomodulatory function has recently been reported in PDAC. This subpopulation of CAFs, designated antigen presenting-CAFs (apCAFs), expresses PDPN and COL1A1 as iCAFs and myCAFs but also major histocompatibility complex (MHC) class II family of proteins such as histocompatibility 2, class II antigen A alpha and beta 1 (H2-Aa, H2-Ab1), and CD74 that present antigen epitopes to their receptor on CD4+/CD8+ T lymphocytes. This binding inhibits activation and proliferation of lymphocytes, with apCAFs acting as a decoy [64,67].
In tumor samples from human breast adenocarcinoma, Costa et al. identified four subtypes of CAFs, designated CAF-S1 to CAF-S4, based on the expression of six markers, including integrin β1 (ITGB1, a.k.a. CD29), αFAP, PDGFRβ, FSP-1, α-SMA and caveolin 1 (Cav1). They defined CAF-S1 as strongly positive for all six markers, CAF-S2 as negative for all markers, CAF-S3 as rich in ITGB1, FSP-1 and PDGFRβ, and CAF-S4 as expressing α-SMA in addition to the three markers present in CAF-S3 [68]. Whereas the tumorigenic functions of CAF-S2 and S3 have not been defined, CAF-S1 and CAF-S4 secrete TGF-β and CXCL12 that activate NOTCH signaling in tumor cells, promoting proliferation and invasion [69]. CAF-S1 also have an immunosuppressive activity through the secretion of IL-6, IL-17, IL-10 and CXCL12 that induce the inhibition of CD4+ T lymphocytes, as well as the activation and the proliferation of Treg lymphocytes [68,70]. A recent transcriptomic analysis by scRNA-seq from the same group indicates a further level of heterogeneity among CAF-S1, also suggestive of the highly diverse spectrum of CAF functions, as it identified eight new clusters, each expressing specific genes coding ECM proteins (cluster 0, ecm-myCAFs), detoxification pathway (cluster 1, detox-iCAFs), IL signaling (cluster 2, IL-iCAFs), TGFβ signaling pathway (cluster 3, TGFβ-myCAFs), wound healing (cluster 4, wound-myCAFs), IFNγ (cluster 5, IFNγ-iCAFs), IFNαβ (cluster 6, IFNαβ-myCAFs), and acto-myosin pathway (cluster 7, acto-myCAFs). Interestingly, CAFs from clusters 0 and 3, characterized by extracellular matrix proteins and TGFβ signaling respectively, are indicative of primary resistance to immunotherapies and act synergistically with ecm-myCAF upregulating PD-1 and CTLA4 protein levels in regulatory T lymphocytes (Tregs), which, in turn, increases TGFβ-myCAF cellular content. These observations in breast cancer were also validated in head, neck and lung cancers [71]. Moreover, Kieffer et al. have also shown correlations between the different clusters and PDAC subtypes. Clusters 0, 3, 4, 6 and 7 are associated with myCAFs, especially ecm-myCAFs with LRRC15-myCAFs; whereas clusters 1, 2 and 5 are associated with iCAFs, especially IFNγ-iCAFs with apCAFs. The subgrouping of CAF-S1 in different clusters can also explain the diversity of the CAF activities described earlier.
In patient-derived xenograft (PDX) tumors of breast adenocarcinoma, other investigators have described subpopulations of CAFs expressing the G protein-coupled C5a receptor 77 (GPR77, a.k.a. C5AR2) and membrane metallo-endopeptidase (MME, a.k.a. CD10) that promote tumor formation and chemoresistance by providing a survival niche for cancer stem cells. CD10+GPR77+ CAFs are driven by persistent NF-κB activation, which is maintained by complement signaling via GPR77. Furthermore, CD10+GPR77+ CAFs promote successful engraftment of PDXs, and targeting these CAFs with a neutralizing anti-GPR77 antibody abolishes tumor formation and restores tumor chemosensitivity via the production of IL-6 and IL-8 [72]. ScRNA-seq analysis in murine models of breast cancer and human samples also suggest that different subpopulations of CAFs are spatially separated. Following a negative selection strategy combined with scRNA-seq of mesenchymal cells from a genetically engineered mouse model of breast cancer, Bartoschek et al. [73] define three distinct subpopulations of CAFs: vascular (vCAFs), matrix (mCAFs) and development (dCAFs). vCAFs express EC markers and are located in the peri-vascular niche, whereas mCAFs express matricellular proteins and are descendants of resident fibroblasts and dCAFs express stem cells genes (Scgr1, Sox9 and Sox10) shared with the tumor epithelium. Gene profiles for each CAF subtype correlate to distinctive functional programs.
The summary above highlights the significant progress made in our understanding of the heterogeneity of the CAF population and in our ability to recognize specific subpopulations defined by their expression of specific surface markers, production and secretion of proteins and transcriptomic profiles. Whether there is an overlap among the different subpopulations reported by several laboratories in pancreatic cancer or breast cancer is uncertain and needs to be further investigated. Nevertheless, it is clear that these subpopulations of CAFs have different functions in cancer, which are far-reaching, extending from direct effect on tumor cell proliferation, survival, chemoresistance, invasion, and metastasis to effects mediated by changes in the ECM, the vasculature and in immune cells in the TME. Table 1 represents an attempt to link CAF subtypes with these specific functions based on the review of the recent literature.

3.2. Mechanisms of CAF Functions

In this section, we briefly summarize our current understanding of the mechanisms by which CAFs exert each of the six main recognized functions as depicted in Figure 2 (Table 2).

3.2.1. Effects of CAFs on Tumor Proliferation

CAFs secrete multiple factors such as TGF-β1, CXCL-12, FGF, POSTN, osteopontin (OPN), hepatocyte growth factor (HGF), IL-6 and IL-22 that directly stimulate the proliferation of tumor cells in vitro and tumor growth in vivo via activation of their respective signaling pathways, i.e., integrin/FAK-src (POSTN), Wnt/β-catenin (HGF and OPN), PI3K/mTOR (CXCL-12, HGF and IL-22), MAPK (IL-6, TGF-β and FGF) or Hippo (EVs) [83,84,85,86,87,88,89,90]. These factors also increase the survival of tumor cells via upregulation of anti-apoptotic proteins like B-cell lymphoma-2 (BCL-2) and myeloid cell leukemia-1 (MCL-1) or downregulation of pro-apoptotic proteins like BCL-2 Associated X protein (BAX) [83,84].

3.2.2. Chemoresistance

Several studies have indicated that CAFs play an important role in chemoresistance via different mechanisms such as secretion of cytokine and miRNAs, increase in cancer stem cells (CSCs), and decreased drug bioavailability via production of a stromal barrier [134]. In breast, colorectal and pancreatic tumors, CAFs increase the resistance of cells to chemotherapeutic agents like gemcitabine and doxorubicin and to combination chemotherapy like doxorubicin, 5-fluorouracil and cisplatin through the production of IL-6, IL-17A, PDGF and insulin like growth factor (IGF) that activate the NF-κB and ERK pathways in tumor cells, promoting the stabilization of anti-apoptotic proteins and the proliferation of cancer stem cells [91,92,93,94,95]. For example, IL-6 increases the survival of breast cancer cells via ERK signaling that stabilizes MCL-1 [38,91]. CAFs are also a source of extracellular vesicles (EVs) that contain regulatory microRNAs (miR) like CmiR-98-5p and miR-522. When EVs are captured by tumor cells, miRNAs can promote resistance to cisplatin by downregulating cyclin-dependent kinase inhibitor (CDKN)1A and ferroptosis, a newly described programmed cell death mechanism characterized by the accumulation of lipid peroxides and a lack of cellular anti-oxidant response [100,101]. In PDAC and breast cancer, the presence of a physical barrier, induced by secretion of hyaluronan and collagen by CAFs, reduces drug delivery. In particular, hyaluronan creates a high interstitial fluid pressure, limiting drug diffusion and causing vascular collapse [96,97,98,99].

3.2.3. Migration, pro-Invasive and Metastatic Activity of CAFs

CAFs directly stimulate tumor cell migration and invasion through the secretion of TGF-β, IL-32, PDGF and FGF that induce EMT, actin polymerization/depolymerization and cell motility [102,103,104,105]. In a model of breast cancer, IL-32 secreted by CAFs promotes metastasis in vivo via activation of β-integrin-mediated p38MAPK signaling in tumor cells, inducing loss of cell-cell adhesion and promoting cell migration [104]. In a similar model, the complement 3a (C3a) protein secreted by CAFs induces an autocrine loop that stimulates PI3K/Akt signaling and the secretion of TGF-β, HGF and PDGF that promote EMT, invasion and lung metastasis in tumor cells [103]. In an orthotopic murine model of hepatocellular carcinoma, the Hippo-Yes-associated protein (YAP) signaling pathway induced by CAFs in cancer cells increases EMT and stimulates actin cytoskeleton polymerization via the upregulation of Rho-GTPase activating proteins (ARHGAP29), both effects resulting in promotion of invasion and metastasis in cancer cells [106].

3.2.4. Activity of CAFs on Angiogenesis

CAFs secrete multiple angiogenic molecules like VEGF, PDGF, CXCL-12 or HGF that promote ECM remodeling, the proliferation of ECs and the recruitment of ECs and pericytes to the tumor [107,108,109]. PDGF and VEGF have also an autocrine effect on CAFs, further stimulating the production of additional pro-angiogenic factors such as IL-6, IL-8 and placental growth factor (PGF) [110,111]. In a murine hepatocellular carcinoma xenograft model, TGF-β and CXCL-12 secreted by CAFs induce the production of proteins such as VE-cadherin, MMP-2 and laminin-5γ2 that promote vascular mimicry [112,113].

3.2.5. Immunosuppressive Activity of CAFs

CAFs affect the recruitment, polarization and function of immune cells in the TIME [135,136]. They participate in the recruitment of several immune cells, in particular monocytes and myeloid cells, via the production of chemokines such as IL-1β, CCL22, CXCL-12 and CCL2. For example, CXCL1, CXCL5 and IL-8 secreted by FGF-activated CAFs induce the recruitment of macrophages to tumors [80,114,115]. CAFs can also affect the polarization of immune cells (TAMs, T cells and neutrophils) [116,117,118,119]. When co-cultured with CAFs, TAMs polarize from anti-tumorigenic M1 to pro-tumorigenic M2 via the production of IL-10 by CAFs or from M2 to M1 via IL-12, thereby regulating the inflammatory response [120]. TGF-β, CXCL1 and IL-10 secreted by CAFs inhibit the function of NK cells, CD8+ T lymphocytes, Th1 lymphocytes and DCs [121,137,138]. These cytokines upregulate the expression of transcription factors such as T-bet and NOX4 in tumor cells, contributing to immune escape [118,121,122,123,124]. CAFs also suppress immune cells through direct contact by expressing βig-h3, a TGFβ-induced RGD-containing surface protein that binds to the integrin β3 (CD61) present on CD8+ T lymphocytes, inhibiting their cytotoxic function [125].

3.2.6. Anti-Tumorigenic Activities of CAFs

Contrary to their pro-tumorigenic functions, CAFs can also have a negative impact on tumor progression. In mouse models of PDAC, the population of CAFs expressing α-SMA exhibit increased activation of Shh signaling that inhibits the production of VEGF, CXCL-12 and IL-8, which affects tumor growth, angiogenesis and immunosuppression [126,127]. In sarcoma and prostatic adenocarcinoma, CAFs secrete TGF-β, IL-6 and tumor necrosis factor-alpha (TNF-α) that activate YAP1/TAZ and NFκB signaling in tumor cells, resulting in inhibition of tumor cell proliferation [128,129,130,131]. In a murine model of OSCC, a sub-population of CAFs, characterized by low α-SMA expression and secretion of bone morphogenetic protein 4 (BMP4), was reported to decrease cell proliferation and inhibit cancer stem cells [132]. In intestinal tumors, overactivation of NFκB signaling in CAFs inhibits tumor growth and angiogenesis in vivo, and the depletion of this CAF sub-population induces the increased production of HGF, IL-6 and FGF and increased the recruitment and activity of Treg cells [133].

4. Heterogeneous Presence of CAFs in Human Cancers

Although CAFs have been reported to be present in most solid tumors, there is a significant degree of variability regarding their abundance among cancers, with pancreatic adenocarcinoma, breast carcinoma, lung adenocarcinoma and kidney renal clear cell carcinoma, being typically heavily infiltrated with CAFs, and leukemia, lymphoma and brain tumors being mostly devoid of CAFs. An in silico analysis of transcriptomics data obtained from the Gene Expression Profiling Interactive Analysis (GEPIA) databases (http://gepia.cancer-pku.cn) [139] for the mRNA expression of several CAF markers (VIM, ACTA2, S100A4, COL1A2, ITGB1, TNC, PDPN, POSTN, FAP, MFAP5 (microfibril associated protein 5, a.k.a. MAGP2), PDGFRβ, COL11A1 (collagen type 11 alpha chain 1), ITGA11 (integrin alpha 11), and NG2) performed by our group illustrates this point (Figure 3A). Vimentin was highly expressed in all types of cancers, including in acute myeloid leukemia, suggesting that it is not a specific marker of CAFs. In contrast, four transcripts, ACTA2, S100A4, COL1A2 and ITGB1, had the highest level of expression in cancers known to have a high proportion of CAFs, whereas low mRNA levels of these four genes were found in uveal melanoma, acute myeloid leukemia and low-grade brain glioma [79,140]. These data are consistent with other studies demonstrating that S100A4 and α-SMA (a.k.a. ACTA2) are overexpressed in most pancreatic adenocarcinoma and breast cancers [141,142]. We also found a positive correlation (r2 = 0.55) between the mRNA expression of S100A4, a gene that reflects the inflammatory function of CAFs [143] and COL1A2, a gene reflecting their effect on the stiffness of the tumor ECM [144], suggesting that these two functions of CAFs are closely associated (Figure 3B).
This analysis also points to other markers for tumor-specific functions (Figure 3A). POSTN is expressed more abundantly in invasive breast carcinoma, lung adenocarcinoma and squamous cell carcinoma, colon adenocarcinoma and head and neck squamous cell carcinoma (HNSCC). POSTN encodes for periostin, which was highly expressed in these cancers as demonstrated by immunohistohemistry (IHC) [145]. In contrast, CAF-poor tumors such as low-grade glioma and acute myeloid leukemia had low POSTN expression. Periostin was initially identified in osteoblasts, but is also secreted by CAFs. Present in the ECM, it promotes tumor cell adhesion, proliferation and migration through integrin binding and activation of the YAP signaling pathway, and through the secretion of cytokines such as IL-6 and TGF-β that promote immune escape and EMT [89,146,147]. Podoplanin (PDPN) is a mucin-type transmembrane glycoprotein and a lymphatic vessel marker. We found PDPN to be abundantly expressed in mesothelioma, HNSCC, lung squamous cell carcinoma and testicular germ cell tumors. This observation is consistent with an analysis of 662 tumors, examined by IHC for PDPN expression, which revealed that PDPN is expressed by stromal α−SMA+, VIM- myofibroblasts [148]. PDPN expression by CAFs may represent a predictive marker of lymphatic/vascular spread [148]. In breast cancer, high presence of PDPN+ CAFs is positively correlated with tumor size, invasive potential and poor prognosis in patients [149,150]. PDPN+ CAFs also have an unfavorable prognostic value in lung squamous cell carcinoma [151,152]. MFAP5 was strongly expressed in fibroblastic cancers such as breast, ovarian, sarcoma, pancreatic and lung cancers. MFAP5 is a 25-kD microfibril-associated glycoprotein present in the ECM that interacts with integrins such as αVβ3 expressed by ECs and with other ECM molecules such as collagen IV. MFAP5 promotes ECs motility and the rearrangement of their cytoskeleton via Notch signaling [153,154]. Recent studies show a correlation between MFAP5 and ACTA2 expression in CAFs, suggesting that they may identify a new subtype of CAFs [79,155]. In bladder cancer and oral squamous cell carcinoma, MFAP5 secreted by CAFs activates NOTCH2/HEY1, ERK and PI3K signaling pathways directly, promoting the proliferation, migration and invasion of cancer cells [155,156]. In murine xenografted models of ovarian cancer, MFAP5 secreted by CAFs upregulates lipoma-preferred partner (LPP) in ECs via FAK/ERK signaling, which promotes paclitaxel chemoresistance and angiogenesis [157]. In bladder and breast cancers, high expression of MFAP5 in CAFs correlated with high-grade malignancy, presence of metastasis and unfavorable clinical outcome [155]. In murine models of ovarian and PDAC cancers, inhibition of MFAP5 with monoclonal antibodies is associated with a decrease in the number of CAFs and microvessels, but also with increased sensitivity to paclitaxel [158].
Although this in silico transcriptomic analysis is informative, it does not take into consideration the potentially significant heterogeneity in CAF distribution within a single tumor where different sub-populations of CAFs with pro-and anti-tumorigenic function could co-exist. This aspect is well illustrated in the recent report by Bartocheck et al. discussed above [73], and by Öhlund et al. showing that myCAFs are located in close proximity to tumor cells, while iCAFs are distant [63]. A deeper understanding of the spatial heterogeneity of CAF in cancer will be obtained with further studies at the single cell level.

5. Challenges in Targeting CAF Activity

Evidence supporting a pro-tumorigenic role for CAFs summarized in this review suggests that targeting CAFs in human cancer could be a valuable, albeit challenging strategy. With the increased ability to further characterize subtypes of CAFs associated with specific functions, we can anticipate a more ‘precise’ approach to targeting CAFs in cancer therapy in combination with strategies targeting tumor cells. For example, specifically targeting immune-suppressive CAFs may be combined with cell-mediated immuno-therapies. Therapeutic strategies using CAFs can be categorized into three groups: 1. Strategies directly targeting CAFs by eliminating them or preventing their activation; 2. Strategies targeting CAF activity by inhibiting factors they produce and their impact on cancer cells and TME cells [20,33,159]; and 3. Strategies taking advantage of the tumor-tropism of MSCs (CAF precursors) to deliver anti-neoplastic molecules to tumors.

5.1. Strategies Directly Targeting CAFs

Strategies to eliminate CAFs have been limited by the need to identify a target molecule expressed on their surface and the lack of markers specific for CAFs as discussed earlier. Approaches targeting αFAP have been the most widely tested as this protein is expressed in 90% of CAFs [160]. In murine models of breast, colon and lung cancers, and in human xenograft models of lung, colon, PDAC and OSCC cancers, PT-630, a small molecule inhibiting the peptidyl peptidase activity of αFAP, and anti-αFAP monoclonal antibodies have been used. They induce apoptosis in CAFs, and subsequently promote Th1 lymphocyte polarization and cytotoxic T lymphocytes (CTL) infiltration in tumors, thereby decreasing metastasis and tumor growth [116,161,162,163,164]. Chimeric antigen receptor T-cells (CAR-T) engineered against αFAP have shown significant efficacy without any toxicity in murine models of lung, breast and colon cancers [165]. When tested in Phase I clinical trials in non-small cell lung carcinoma (NCT00243204, NCT02209727), melanoma (NCT00083252) and pancreatic carcinoma (NCT00116389), sibrotuzumab, a monoclonal antibody against αFAP, and PT-100, a small molecule peptidyl peptidase inhibitor, have shown feasibility in the absence of severe toxicity, but their efficacy in Phase II trials has been limited [166,167,168]. TRC-105, a monoclonal antibody against endoglin (CD105) present on the surface of ECs, CAFs and MSCs, enhances immunotherapy with NK cells in xenotransplanted human neuroblastoma tumors [123]. It has also been tested in multiple Phase I, II and III trials as an anti-angiogenic agent, often in combination with bevacizumab (anti-VEFG), but has not yet been tested specifically for its activity against CAFs [169].
Strategies to prevent or reverse CAFs activation have also been developed. PDGF and TGF-β are the two main growth factors that activate CAFs. Dasatinib, a broad receptor tyrosine kinase inhibitor with activity against PDGFRβ, induces a reversion from the activated phenotype of CAFs to a phenotype closer to that of normal fibroblasts, limiting their proliferation [170]. Evidence that CAF activation involves regulatory miRNAs such as miR-221-5p, miR-145 and miR-Let-7 and epigenetic mechanisms such as DNA methylation and histone acetylation [171,172] suggests other strategies to reverse CAF activation. One such strategy tested in breast, prostate and OSCC cancer xenograft models is to re-induce the expression of miRNAs (miR-145, miR-15, miR-16, Let-7b) that prevent CAF activation. Transfection of these miRs into CAFs inhibits TGF-β activation and their secretion of IL-8 and FGF, decreasing tumor growth in murine models [173,174,175]. Another strategy is to use a histone deacetylase (HDAC) inhibitor such as scriptaid, which acts as a repressor of TGF-β activity [176]. In a murine melanoma model, scriptaid inhibits the activation of α-SMA+ and COL1+ CAFs by repressing TGF-β signaling and inhibiting ECM production and tumor invasion in a 3D model of tumor/CAFs, and delaying tumor growth in vivo in murine model [177]. The drug was well-tolerated and could be used as an adjunct to improve chemotherapy [178]. LIF activates JAK/STAT-3 and upregulates DNA methyl transferase (DNMT), inducing epigenetic changes in CAFs that promote their activation and migration. Accordingly, the combination of a JAK inhibitor (ruxolitinib) and a DNMT inhibitor (5-azacytidine) has been shown to inhibit CAFs activation [179]. Ruxolitinib has been tested in multiple Phase I and II clinical trials in pancreatic and lung cancers in combination with other tyrosine kinase inhibitors such as capecitabine (pancreatic) and afatinib and erlotinib (lung) [180,181,182]. These trials show generally good tolerance of this combination, but the efficiency is mostly moderate. Ruxolitinib improves survival for patients with metastatic pancreatic cancer, whereas in lung cancer, combining ruxolitinib with other drugs does not improve efficiency over administering ruxolitinib alone (NCT01423604, NCT02145637, NCT02155465) [180,181,182].
Based on data demonstrating a difference in the dependence of CAFs on BCL-2 vs. MCL-1 for survival, studies have shown that CAFs in human breast cancer are sensitive to inhibitors targeting MCL-1 (A-1210477 and S63845) but not to those targeting BCL-2/BCL-XL (ABT-737 and navitoclax) [91]. However, illustrating the issue of heterogeneity, the opposite effect was reported in cholangiocarcinoma and ovarian cancer [183,184,185].

5.2. Inhibitors of CAF Activity

Targeting proteins secreted by CAFs when activated or the signaling pathways activated by these proteins in cancer or host cells in the TME is another line of research. Multiple small molecule inhibitors or blocking monoclonal antibodies against ECM molecules, cytokines, chemokines, growth factors and signaling pathways have been developed over the last several decades and have been tested in clinical trials, several with major success, others with disappointing results, especially when used alone. Resistance developed towards these molecules and pathways has been a major problem.
The stromal collagen barrier produced by CAFs may limit drug bioavailability. Inhibitors targeting different components of the ECM have been developed to decrease the impact of CAFs on chemoresistance. For example, the renin-angiotensin system affects the proliferation, metabolism and growth of tumors, and the activation of CAFs, inducing fibrosis. Angiotensin receptor blockers (ARB) such as losartan have been shown to improve the bioavailability of drugs such as doxorubicin and nanoparticles in xenotransplanted models of pancreatic cancer and melanoma by decreasing the percentage of α-SMA+ cells and the amount of collagen in the tumor stroma, and the tumor size in murine models [186,187]. Clinical trials with ARB in combination with bevacizumab or FOLFIRINOX in pancreatic and colorectal cancers have shown prolonged progression-free survival (PFS) and overall survival (OS) when used as adjuvant therapy [188,189]. For example, Phase II clinical trials (NCT01821729, NCT03563248) in pancreatic cancer using a combination of losartan and FOLFIRINOX recently showed extended patient prognosis and was associated with negative resection margin for 61% of patients [189]. The administration of nab-paclitaxel (abraxane) combined with gemcitabine decreases the production of type-I collagen and the secretion of CXCL10 and IL-6 in co-cultures of pancreatic cells and CAFs [190,191]. A recent Phase III clinical trial tested nab-paclitaxel in combination with atezolizumab, a monoclonal antibody against PD-L1, in unresectable and metastatic triple-negative breast cancer (NCT02425891) and metastatic lung cancer (NCT02367781), showing an increase in PFS and OS [192,193,194]. These inhibitors, which have an effect on ECM, could preferentially target CAF subtypes implicated in ECM production and remodeling such as CAF-N, CAF-A and myCAFs.
Multiple inhibitors of growth factors, cytokines and chemokines produced by CAFs in the TME have been tested in pre-clinical models and several have reached clinical trials [33,159]. For example, CXCL-12 and TGF-β are major factors secreted by CAFs that recruit immune cells and ECs into tumors and stimulate EMT and proliferation in cancer cells. Plerixafor (AMD3100), a small molecule inhibitor for CXCR4, the receptor for CXCL-12, has been tested in murine models of prostate cancers and PDAC. In the KPC murine model of PDAC, AMD3100 in combination with ipilimumab, a monoclonal antibody against the immune checkpoint, CTLA-4, inhibits αFAP+ CAFs and increases the recruitment of CTL [195,196,197]. Plerixafor is currently undergoing clinical trials for PDAC, colorectal and ovarian cancers (NCT03277209) [197]. Two clinical trials combining plerixafor with antibodies against PD-1, i.e., cemiplimab in metastatic PDAC (NCT04177810) and pembrolizumab in head and neck carcinoma (NCT04058145) are ongoing. Galunisertib (LY3200882), a small molecule targeting the TGF-β receptor has been the focus of multiple pre-clinical and clinical studies. In murine models of breast and liver cancers, treatment with galunisertib inhibits the growth of tumors by increasing the infiltration of CD8+ T lymphocytes, and their invasion by increasing the accumulation of collagen and by inhibiting EMT [198,199]. Treatment with galunisertib in combination with gemcitabine in a Phase Ib/II trial in patients with PDAC resulted in an increase in overall survival when compared to gemcitabine alone (NCT01373164) [200]. Other clinical trials testing galunisertib in combination with capecitabine, an anti-metabolite drug, in colorectal cancer (NCT04031872), or with enzalutamide, an androgen receptor inhibitor, in metastatic prostate cancer (NCT02452008) are ongoing. These inhibitors have the advantage of targeting both CAF activation and CAF activity.
Thus, we can begin to envision how targeting CAFs may become more precise (Table 1). For example, an inhibitor of cytokine-mediated signaling, such as ruxolitinib, may be used to more specifically block the activity of iCAFs whereas an inhibitor of TGF-β, such as galunisertib, will preferentially target myCAFs and TGFβ-myCAFs.

5.3. Strategies Using CAF Precursors as Delivery Tools

A third strategy is to take advantage of the tumor-tropism of CAFs, and in particular MSCs, to deliver anti-tumor molecules. MSCs are attracted to the sites of tissue repair in diseases such as chronic inflammatory diseases, ischemic stroke and cancers. Three strategies are presently explored: (1) the use of MSCs grown in vitro as producers of a large amount of EVs that can be collected and used to deliver drugs to tumors in vivo [201]; (2) the use of MSCs amplified ex vivo and administered in vivo as vehicles of anti-tumor drugs; (3) the use of MSCs genetically modified ex vivo to produce molecules that reduce tumor progression and are administered in vivo [202,203].
MSCs-derived EVs (called iExosomes), carrying siRNA or shRNA against KRASG12D, a mutation often found in cancers, have been tested in different murine models of PDAC, and shown to inhibit metastases and increase overall survival, particularly when administered in combination with an anti-CD47 (“don’t eat me” signal) monoclonal antibody that promotes RAS-dependent macropinocytosis of iExosomes. A clinical trial with these iExosomes is currently ongoing (NCT03608631) [204,205]. In melanoma and pancreatic cancers, MSCs delivering paclitaxel induce a decrease of the proliferation of tumor cells in vitro [206,207]. MSCs collected from patients and engineered ex-vivo can be safely and efficiently re-administered to the patient [208]. A clinical study in metastatic gastrointestinal cancer has shown that engineered MSCs are localized at the site of the primary cancer tumor [208]. In mouse prostate and metastasis lung models, MSCs engineered to overexpress IFNβ have an antitumorigenic effect by inducing cell death by apoptosis, stimulating the cytotoxic activity of NK cells, and inhibiting angiogenesis [209]. A clinical trial with IFNβ-MSCs is currently recruiting patients with ovarian cancer (NCT02530047).

6. Conclusions

Our understanding of the contribution of CAFs to cancer progression has dramatically changed since their initial description in the early 1990s. We now have a much better understanding of their heterogeneity and the complexity of their functions and phenotypes. As we have become more proficient at precisely identifying subgroups of CAFs with specific functions and localization in tumors, it may soon be possible to design “molecularly-informed clinical trials” that combine the targeting of tumor cells with the targeting of subpopulations of CAFs that specifically provide tumor cells with mechanisms for therapeutic escape.

Author Contributions

Conceptualization, K.L., and Y.A.D.; methodology, K.L., R.-R.L., and Y.A.D.; validation, writing-original draft preparation, K.L., R.-R.L., and Y.A.D.; writing-editing, K.L., and Y.A.D.; supervision, Y.A.D. All authors have read and agreed to be published version of the manuscript.

Funding

This work was supported in part by grant P01CA217959 from National Institutes of Health to Y.A.D.

Acknowledgments

The authors would like to thank Martine Torres, Ph.D. for her editorial assistance.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Paget, S. The Distribution of Secondary Growths in Cancer of the Breast. Cancer Metastasis Rev. 1989, 8, 98–101. [Google Scholar] [CrossRef] [Green Version]
  2. Radisky, D.; Hagios, C.; Bissell, M.J. Tumors Are Unique Organs Defined by Abnormal Signaling and Context. Semin. Cancer Biol. 2001, 11, 87–95. [Google Scholar] [CrossRef] [PubMed]
  3. Hanahan, D.; Weinberg, R.A. Hallmarks of Cancer: The Next Generation. Cell 2011, 144, 646–674. [Google Scholar] [CrossRef] [Green Version]
  4. Hui, L.; Chen, Y. Tumor Microenvironment: Sanctuary of the Devil. Cancer Lett. 2015, 368, 7–13. [Google Scholar] [CrossRef] [PubMed]
  5. Yang, F.; Wang, T.; Du, P.; Fan, H.; Dong, X.; Guo, H. M2 Bone Marrow-Derived Macrophage-Derived Exosomes Shuffle MicroRNA-21 to Accelerate Immune Escape of Glioma by Modulating PEG3. Cancer Cell Int. 2020, 20, 93. [Google Scholar] [CrossRef]
  6. Gajewski, T.F.; Schreiber, H.; Fu, Y.-X. Innate and Adaptive Immune Cells in the Tumor Microenvironment. Nat. Immunol. 2013, 14, 1014–1022. [Google Scholar] [CrossRef] [Green Version]
  7. Petty, A.J.; Yang, Y. Tumor-Associated Macrophages: Implications in Cancer Immunotherapy. Immunotherapy 2017, 9, 289–302. [Google Scholar] [CrossRef] [Green Version]
  8. Zhang, D.; Zheng, Y.; Lin, Z.; Liu, X.; Li, J.; Yang, H.; Tan, W. Equipping Natural Killer Cells with Specific Targeting and Checkpoint Blocking for Enhanced Adoptive Immunotherapy in Solid Tumors. Angew. Chem. Int. Ed. 2020. [Google Scholar] [CrossRef]
  9. Ruscetti, M.; Morris, J.P.; Mezzadra, R.; Russell, J.; Leibold, J.; Romesser, P.B.; Simon, J.; Kulick, A.; Ho, Y.; Fennell, M.; et al. Senescence-Induced Vascular Remodeling Creates Therapeutic Vulnerabilities in Pancreas Cancer. Cell 2020. [Google Scholar] [CrossRef]
  10. Viallard, C.; Larrivée, B. Tumor Angiogenesis and Vascular Normalization: Alternative Therapeutic Targets. Angiogenesis 2017, 20, 409–426. [Google Scholar] [CrossRef]
  11. Eble, J.A.; Niland, S. The Extracellular Matrix in Tumor Progression and Metastasis. Clin. Exp. Metastasis 2019, 36, 171–198. [Google Scholar] [CrossRef] [PubMed]
  12. Girard, C.A.; Lecacheur, M.; Ben Jouira, R.; Berestjuk, I.; Diazzi, S.; Prod’homme, V.; Mallavialle, A.; Larbret, F.; Gesson, M.; Schaub, S.; et al. A Feed-Forward Mechanosignaling Loop Confers Resistance to Therapies Targeting the MAPK Pathway in BRAF-Mutant Melanoma. Cancer Res. 2020. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Castells, M.; Thibault, B.; Delord, J.-P.; Couderc, B. Implication of Tumor Microenvironment in Chemoresistance: Tumor-Associated Stromal Cells Protect Tumor Cells from Cell Death. Int. J. Mol. Sci. 2012, 13, 9545–9571. [Google Scholar] [CrossRef] [PubMed]
  14. Kalluri, R.; Zeisberg, M. Fibroblasts in Cancer. Nat. Rev. Cancer 2006, 6, 392–401. [Google Scholar] [CrossRef]
  15. Gabbiani, G.; Ryan, G.B.; Majne, G. Presence of Modified Fibroblasts in Granulation Tissue and Their Possible Role in Wound Contraction. Experientia 1971, 27, 549–550. [Google Scholar] [CrossRef]
  16. Dvorak, H.F. Tumors: Wounds That Do Not Heal. Similarities Between Tumor Stroma Generation and Wound Healing. N. Engl. J. Med. 1986, 315, 1650–1659. [Google Scholar] [CrossRef]
  17. Camps, J.L.; Chang, S.M.; Hsu, T.C.; Freeman, M.R.; Hong, S.J.; Zhau, H.E.; von Eschenbach, A.C.; Chung, L.W. Fibroblast- Mediated Acceleration of Human Epithelial Tumor Growth In Vivo. Proc. Natl. Acad. Sci. USA 1990, 87, 75–79. [Google Scholar] [CrossRef] [Green Version]
  18. Desmoulière, A.; Guyot, C.; Gabbiani, G. The Stroma Reaction Myofibroblast: A Key Player in the Control of Tumor Cell Behavior. Int. J. Dev. Biol. 2004, 48, 509–517. [Google Scholar] [CrossRef] [Green Version]
  19. Schauer, I.G.; Sood, A.K.; Mok, S.; Liu, J. Cancer-Associated Fibroblasts and Their Putative Role in Potentiating the Initiation and Development of Epithelial Ovarian Cancer. Neoplasia 2011, 13, 393–405. [Google Scholar] [CrossRef] [Green Version]
  20. Öhlund, D.; Elyada, E.; Tuveson, D. Fibroblast Heterogeneity in the Cancer Wound. J. Exp. Med. 2014, 211, 1503–1523. [Google Scholar] [CrossRef]
  21. Kalluri, R. The Biology and Function of Fibroblasts in Cancer. Nat. Rev. Cancer 2016, 16, 582–598. [Google Scholar] [CrossRef] [PubMed]
  22. Haviv, I.; Polyak, K.; Qiu, W.; Hu, M.; Campbell, I. Origin of Carcinoma Associated Fibroblasts. Cell Cycle Georget. Tex. 2009, 8, 589–595. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Rønnov-Jessen, L.; Petersen, O.W.; Koteliansky, V.E.; Bissell, M.J. 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. Investig. 1995, 95, 859–873. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Zhang, J.; Liu, J. Tumor Stroma as Targets for Cancer Therapy. Pharmacol. Ther. 2013, 137, 200–215. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Bhowmick, N.A.; Chytil, A.; Plieth, D.; Gorska, A.E.; Dumont, N.; Shappell, S.; Washington, M.K.; Neilson, E.G.; Moses, H.L. TGF- Beta Signaling in Fibroblasts Modulates the Oncogenic Potential of Adjacent Epithelia. Science 2004, 303, 848–851. [Google Scholar] [CrossRef] [Green Version]
  26. Tejada, M.L.; Yu, L.; Dong, J.; Jung, K.; Meng, G.; Peale, F.V.; Frantz, G.D.; Hall, L.; Liang, X.; Gerber, H.-P.; et al. 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. Off. J. Am. Assoc. Cancer Res. 2006, 12, 2676–2688. [Google Scholar] [CrossRef] [Green Version]
  27. Erez, N.; Truitt, M.; Olson, P.; Arron, S.T.; Hanahan, D. Cancer-Associated Fibroblasts Are Activated in Incipient Neoplasia to Orchestrate Tumor-Promoting Inflammation in an NF-kappaB-Dependent Manner. Cancer Cell 2010, 17, 135–147. [Google Scholar] [CrossRef] [Green Version]
  28. Tian, H.; Callahan, C.A.; DuPree, K.J.; Darbonne, W.C.; Ahn, C.P.; Scales, S.J.; de Sauvage, F.J. Hedgehog Signaling Is Restricted to the Stromal Compartment During Pancreatic Carcinogenesis. Proc. Natl. Acad. Sci. USA 2009, 106, 4254–4259. [Google Scholar] [CrossRef] [Green Version]
  29. Elenbaas, B.; Weinberg, R.A. Heterotypic Signaling Between Epithelial Tumor Cells and Fibroblasts in Carcinoma Formation. Exp. Cell Res. 2001, 264, 169–184. [Google Scholar] [CrossRef]
  30. Costa, A.; Scholer-Dahirel, A.; Mechta-Grigoriou, F. The Role of Reactive Oxygen Species and Metabolism on Cancer Cells and Their Microenvironment. Semin. Cancer Biol. 2014, 25, 23–32. [Google Scholar] [CrossRef]
  31. Zou, B.; Liu, X.; Zhang, B.; Gong, Y.; Cai, C.; Li, P.; Chen, J.; Xing, S.; Chen, J.; Peng, S.; et al. The Expression of FAP in Hepatocellular Carcinoma Cells is Induced by Hypoxia and Correlates with Poor Clinical Outcomes. J. Cancer 2018, 9, 3278–3286. [Google Scholar] [CrossRef]
  32. Radisky, D.C.; Levy, D.D.; Littlepage, L.E.; Liu, H.; Nelson, C.M.; Fata, J.E.; Leake, D.; Godden, E.L.; Albertson, D.G.; Nieto, M.A.; et al. Rac1b and Reactive Oxygen Species Mediate MMP-3-Induced EMT and Genomic Instability. Nature 2005, 436, 123–127. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Liu, T.; Han, C.; Wang, S.; Fang, P.; Ma, Z.; Xu, L.; Yin, R. Cancer-Associated Fibroblasts: An Emerging Target of Anti-Cancer Immunotherapy. J. Hematol. Oncol. J. Hematol. Oncol. 2019, 12, 86. [Google Scholar] [CrossRef]
  34. Shany, S.; Sigal-Batikoff, I.; Lamprecht, S. Vitamin D and Myofibroblasts in Fibrosis and Cancer: At Cross-purposes with TGF-β/SMAD Signaling. Anticancer Res. 2016, 36, 6225–6234. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Sherman, M.H.; Yu, R.T.; Engle, D.D.; Ding, N.; Atkins, A.R.; Tiriac, H.; Collisson, E.A.; Connor, F.; Van Dyke, T.; Kozlov, S.; et al. Vitamin D Receptor-Mediated Stromal Reprogramming Suppresses Pancreatitis and Enhances Pancreatic Cancer Therapy. Cell 2014, 159, 80–93. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Kojima, Y.; Acar, A.; Eaton, E.N.; Mellody, K.T.; Scheel, C.; Ben-Porath, I.; Onder, T.T.; Wang, Z.C.; Richardson, A.L.; Weinberg, R.A.; et al. Autocrine TGF- Beta and Stromal Cell-Derived Factor-1 (SDF-1) Signaling Drives the Evolution of Tumor-Promoting Mammary Stromal Myofibroblasts. Proc. Natl. Acad. Sci. USA 2010, 107, 20009–20014. [Google Scholar] [CrossRef] [Green Version]
  37. Quante, M.; Tu, S.P.; Tomita, H.; Gonda, T.; Wang, S.S.W.; Takashi, S.; Baik, G.H.; Shibata, W.; Diprete, B.; Betz, K.S.; et al. Bone Marrow-Derived Myofibroblasts Contribute to the Mesenchymal Stem Cell Niche and Promote Tumor Growth. Cancer Cell 2011, 19, 257–272. [Google Scholar] [CrossRef] [Green Version]
  38. Borriello, L.; Nakata, R.; Sheard, M.A.; Fernandez, G.E.; Sposto, R.; Malvar, J.; Blavier, L.; Shimada, H.; Asgharzadeh, S.; Seeger, R.C.; et al. Cancer-Associated Fibroblasts Share Characteristics and Protumorigenic Activity with Mesenchymal Stromal Cells. Cancer Res. 2017, 77, 5142–5157. [Google Scholar] [CrossRef] [Green Version]
  39. Direkze, N.C.; Hodivala-Dilke, K.; Jeffery, R.; Hunt, T.; Poulsom, R.; Oukrif, D.; Alison, M.R.; Wright, N.A. Bone Marrow Contribution to Tumor-Associated Myofibroblasts and Fibroblasts. Cancer Res. 2004, 64, 8492–8495. [Google Scholar] [CrossRef] [Green Version]
  40. Mishra, P.J.; Mishra, P.J.; Humeniuk, R.; Medina, D.J.; Alexe, G.; Mesirov, J.P.; Ganesan, S.; Glod, J.W.; Banerjee, D. Carcinoma-Associated Fibroblast-Like Differentiation of Human Mesenchymal Stem Cells. Cancer Res. 2008, 68, 4331–4339. [Google Scholar] [CrossRef] [Green Version]
  41. Barcellos-de-Souza, P.; Comito, G.; Pons-Segura, C.; Taddei, M.L.; Gori, V.; Becherucci, V.; Bambi, F.; Margheri, F.; Laurenzana, A.; Del Rosso, M.; et al. Mesenchymal Stem Cells are Recruited and Activated into Carcinoma-Associated Fibroblasts by Prostate Cancer Microenvironment-Derived TGF-β1. Stem Cells 2016, 34, 2536–2547. [Google Scholar] [CrossRef]
  42. Liu, C.-J.; Wang, Y.-K.; Kuo, F.-C.; Hsu, W.-H.; Yu, F.-J.; Hsieh, S.; Tai, M.-H.; Wu, D.-C.; Kuo, C.-H. Helicobacter Pylori Infection-Induced Hepatoma-Derived Growth Factor Regulates the Differentiation of Human Mesenchymal Stem Cells to Myofibroblast-Like Cells. Cancers 2018, 10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Zhang, Q.; Chai, S.; Wang, W.; Wan, C.; Zhang, F.; Li, Y.; Wang, F. Macrophages Activate Mesenchymal Stem Cells to Acquire Cancer-Associated Fibroblast-Like Features Resulting in Gastric Epithelial Cell Lesions and Malignant Transformation In Vitro. Oncol. Lett. 2019, 17, 747–756. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Kahounová, Z.; Kurfürstová, D.; Bouchal, J.; Kharaishvili, G.; Navrátil, J.; Remšík, J.; Šimečková, Š.; Študent, V.; Kozubík, A.; Souček, K. The Fibroblast Surface Markers Fap, Anti-Fibroblast, and FSP Are Expressed by Cells of Epithelial Origin and May Be Altered During Epithelial-to-Mesenchymal Transition. Cytom. Part A J. Int. Soc. Anal. Cytol. 2018, 93, 941–951. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Iwano, M.; Plieth, D.; Danoff, T.M.; Xue, C.; Okada, H.; Neilson, E.G. Evidence that fibroblasts derive from epithelium during tissue fibrosis. J. Clin. Investig. 2002, 110, 341–350. [Google Scholar] [CrossRef] [PubMed]
  46. Zeisberg, E.M.; Potenta, S.; Xie, L.; Zeisberg, M.; Kalluri, R. Discovery of Endothelial to Mesenchymal Transition as a Source for Carcinoma-Associated Fibroblasts. Cancer Res. 2007, 67, 10123–10128. [Google Scholar] [CrossRef] [Green Version]
  47. Hosaka, K.; Yang, Y.; Seki, T.; Fischer, C.; Dubey, O.; Fredlund, E.; Hartman, J.; Religa, P.; Morikawa, H.; Ishii, Y.; et al. Pericyte-Fibroblast Transition Promotes Tumor Growth and Metastasis. Proc. Natl. Acad. Sci. USA 2016, 113, E5618–E5627. [Google Scholar] [CrossRef] [Green Version]
  48. Abe, R.; Donnelly, S.C.; Peng, T.; Bucala, R.; Metz, C.N. Peripheral Blood Fibrocytes: Differentiation Pathway and Migration to Wound Sites. J. Immunol. 2001, 166, 7556–7562. [Google Scholar] [CrossRef] [Green Version]
  49. Kidd, S.; Spaeth, E.; Watson, K.; Burks, J.; Lu, H.; Klopp, A.; Andreeff, M.; Marini, F.C. Origins of the Tumor Microenvironment: Quantitative Assessment of Adipose-Derived and Bone Marrow-Derived Stroma. PLoS ONE 2012, 7, e30563. [Google Scholar] [CrossRef] [Green Version]
  50. Jotzu, C.; Alt, E.; Welte, G.; Li, J.; Hennessy, B.T.; Devarajan, E.; Krishnappa, S.; Pinilla, S.; Droll, L.; Song, Y.-H. Adipose Tissue Derived Stem Cells Differentiate Into Carcinoma-Associated Fibroblast-Like Cells Under the Influence of Tumor Derived Factors. Cell. Oncol. 2011, 34, 55–67. [Google Scholar] [CrossRef]
  51. Omary, M.B.; Lugea, A.; Lowe, A.W.; Pandol, S.J. The Pancreatic Stellate Cell: A Star on the Rise in Pancreatic Diseases. J. Clin. Investig. 2007, 117, 50–59. [Google Scholar] [CrossRef] [Green Version]
  52. Yin, C.; Evason, K.J.; Asahina, K.; Stainier, D.Y.R. Hepatic Stellate Cells in Liver Development, Regeneration, and Cancer. J. Clin. Investig. 2013, 123, 1902–1910. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Nair, N.; Calle, A.S.; Zahra, M.H.; Prieto-Vila, M.; Oo, A.K.K.; Hurley, L.; Vaidyanath, A.; Seno, A.; Masuda, J.; Iwasaki, Y.; et al. A Cancer Stem Cell Model as the Point of Origin of Cancer-Associated Fibroblasts in Tumor Microenvironment. Sci. Rep. 2017, 7, 6838. [Google Scholar] [CrossRef] [PubMed]
  54. Sugimoto, H.; Mundel, T.M.; Kieran, M.W.; Kalluri, R. Identification of Fibroblast Heterogeneity in the Tumor Microenvironment. Cancer Biol. Ther. 2006, 5, 1640–1646. [Google Scholar] [CrossRef] [Green Version]
  55. O’Connell, J.T.; Sugimoto, H.; Cooke, V.G.; MacDonald, B.A.; Mehta, A.I.; LeBleu, V.S.; Dewar, R.; Rocha, R.M.; Brentani, R.R.; Resnick, M.B.; et al. VEGF-A and Tenascin-C Produced by S100A4+ Stromal Cells Are Important for Metastatic Colonization. Proc. Natl. Acad. Sci. USA 2011, 108, 16002–16007. [Google Scholar] [CrossRef] [Green Version]
  56. Jiao, J.; González, Á.; Stevenson, H.L.; Gagea, M.; Sugimoto, H.; Kalluri, R.; Beretta, L. Depletion of S100A4+ Stromal Cells Does Not Prevent HCC Development but Reduces the Stem Cell-Like Phenotype of the Tumors. Exp. Mol. Med. 2018, 50, e422. [Google Scholar] [CrossRef] [PubMed]
  57. Carstens, J.L.; Correa de Sampaio, P.; Yang, D.; Barua, S.; Wang, H.; Rao, A.; Allison, J.P.; LeBleu, V.S.; Kalluri, R. Spatial Computation of Intratumoral T Cells Correlates with Survival of Patients with Pancreatic Cancer. Nat. Commun. 2017, 8, 15095. [Google Scholar] [CrossRef]
  58. Costea, D.E.; Hills, A.; Osman, A.H.; Thurlow, J.; Kalna, G.; Huang, X.; Pena Murillo, C.; Parajuli, H.; Suliman, S.; Kulasekara, K.K.; et al. Identification of Two Distinct Carcinoma-Associated Fibroblast Subtypes With Differential Tumor-Promoting Abilities in Oral Squamous Cell Carcinoma. Cancer Res. 2013, 73, 3888–3901. [Google Scholar] [CrossRef] [Green Version]
  59. Hassona, Y.; Cirillo, N.; Heesom, K.; Parkinson, E.K.; Prime, S.S. Senescent Cancer-Associated Fibroblasts Secrete Active MMP-2 That Promotes Keratinocyte Dis-Cohesion and Invasion. Br. J. Cancer 2014, 111, 1230–1237. [Google Scholar] [CrossRef] [Green Version]
  60. Li, H.; Courtois, E.T.; Sengupta, D.; Tan, Y.; Chen, K.H.; Goh, J.J.L.; Kong, S.L.; Chua, C.; Hon, L.K.; Tan, W.S.; et al. Reference Component Analysis of Single-Cell Transcriptomes Elucidates Cellular Heterogeneity in Human Colorectal Tumors. Nat. Genet. 2017, 49, 708–718. [Google Scholar] [CrossRef]
  61. Mizutani, Y.; Kobayashi, H.; Iida, T.; Asai, N.; Masamune, A.; Hara, A.; Esaki, N.; Ushida, K.; Mii, S.; Shiraki, Y.; et al. Meflin-Positive Cancer-Associated Fibroblasts Inhibit Pancreatic Carcinogenesis. Cancer Res. 2019, 79, 5367–5381. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  62. Miyai, Y.; Esaki, N.; Takahashi, M.; Enomoto, A. Cancer-Associated Fibroblasts That Restrain Cancer Progression: Hypotheses and Perspectives. Cancer Sci. cas.14346. [CrossRef] [PubMed] [Green Version]
  63. Öhlund, D.; Handly-Santana, A.; Biffi, G.; Elyada, E.; Almeida, A.S.; Ponz-Sarvise, M.; Corbo, V.; Oni, T.E.; Hearn, S.A.; Lee, E.J.; et al. Distinct Populations of Inflammatory Fibroblasts and Myofibroblasts in Pancreatic Cancer. J. Exp. Med. 2017, 214, 579–596. [Google Scholar] [CrossRef]
  64. Elyada, E.; Bolisetty, M.; Laise, P.; Flynn, W.F.; Courtois, E.T.; Burkhart, R.A.; Teinor, J.A.; Belleau, P.; Biffi, G.; Lucito, M.S.; et al. Cross-Species Single-Cell Analysis of Pancreatic Ductal Adenocarcinoma Reveals Antigen-Presenting Cancer-Associated Fibroblasts. Cancer Discov. 2019, 9, 1102–1123. [Google Scholar] [CrossRef] [Green Version]
  65. Hosein, A.N.; Huang, H.; Wang, Z.; Parmar, K.; Du, W.; Huang, J.; Maitra, A.; Olson, E.; Verma, U.; Brekken, R.A. Cellular Heterogeneity During Mouse Pancreatic Ductal Adenocarcinoma Progression at Single-Cell Resolution. JCI Insight 2019, 5. [Google Scholar] [CrossRef] [Green Version]
  66. Dominguez, C.X.; Müller, S.; Keerthivasan, S.; Koeppen, H.; Hung, J.; Gierke, S.; Breart, B.; Foreman, O.; Bainbridge, T.W.; Castiglioni, A.; et al. Single-Cell RNA Sequencing Reveals Stromal Evolution into LRRC15+ Myofibroblasts as a Determinant of Patient Response to Cancer Immunotherapy. Cancer Discov. 2020, 10, 232–253. [Google Scholar] [CrossRef] [Green Version]
  67. Lakins, M.A.; Ghorani, E.; Munir, H.; Martins, C.P.; Shields, J.D. Cancer-Associated Fibroblasts Induce Antigen-Specific Deletion of CD8 + T Cells to Protect Tumour Cells. Nat. Commun. 2018, 9, 948. [Google Scholar] [CrossRef]
  68. 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 2018, 33, 463–479. [Google Scholar] [CrossRef] [Green Version]
  69. Pelon, F.; Bourachot, B.; Kieffer, Y.; Magagna, I.; Mermet-Meillon, F.; Bonnet, I.; Costa, A.; Givel, A.-M.; Attieh, Y.; Barbazan, J.; et al. Cancer-Associated Fibroblast Heterogeneity in Axillary Lymph Nodes Drives Metastases in Breast Cancer Through Complementary Mechanisms. Nat. Commun. 2020, 11, 404. [Google Scholar] [CrossRef] [Green Version]
  70. Givel, A.-M.; Kieffer, Y.; Scholer-Dahirel, A.; Sirven, P.; Cardon, M.; Pelon, F.; Magagna, I.; Gentric, G.; Costa, A.; Bonneau, C.; et al. miR200-regulated CXCL12β Promotes Fibroblast Heterogeneity and Immunosuppression in Ovarian Cancers. Nat. Commun. 2018, 9, 1056. [Google Scholar] [CrossRef]
  71. Kieffer, Y.; Hocine, H.R.; Gentric, G.; Pelon, F.; Bernard, C.; Bourachot, B.; Lameiras, S.; Albergante, L.; Bonneau, C.; Guyard, A.; et al. Single-Cell Analysis Reveals Fibroblast Clusters Linked to Immunotherapy Resistance in Cancer. Cancer Discov. 2020, 10, 1330–1351. [Google Scholar] [CrossRef] [PubMed]
  72. Su, S.; Chen, J.; Yao, H.; Liu, J.; Yu, S.; Lao, L.; Wang, M.; Luo, M.; Xing, Y.; Chen, F.; et al. CD10+GPR77+ Cancer-Associated Fibroblasts Promote Cancer Formation and Chemoresistance by Sustaining Cancer Stemness. Cell 2018, 172, 841–856. [Google Scholar] [CrossRef] [PubMed]
  73. Bartoschek, M.; Oskolkov, N.; Bocci, M.; Lövrot, J.; Larsson, C.; Sommarin, M.; Madsen, C.D.; Lindgren, D.; Pekar, G.; Karlsson, G.; et al. Spatially and Functionally Distinct Subclasses of Breast Cancer-Associated Fibroblasts Revealed by Single Cell RNA Sequencing. Nat. Commun. 2018, 9, 5150. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Hawinkels, L.J.A.C.; Paauwe, M.; Verspaget, H.W.; Wiercinska, E.; van der Zon, J.M.; van der Ploeg, K.; Koelink, P.J.; Lindeman, J.H.N.; Mesker, W.; ten Dijke, P.; et al. Interaction With Colon Cancer Cells Hyperactivates Tgf-β Signaling in Cancer-Associated Fibroblasts. Oncogene 2014, 33, 97–107. [Google Scholar] [CrossRef] [Green Version]
  75. Wendling, O.; Bornert, J.-M.; Chambon, P.; Metzger, D. Efficient Temporally-Controlled Targeted Mutagenesis in Smooth Muscle Cells of the Adult Mouse. Genes 2009, 47, 14–18. [Google Scholar] [CrossRef]
  76. Lazard, D.; Sastre, X.; Frid, M.G.; Glukhova, M.A.; Thiery, J.P.; Koteliansky, V.E. Expression of Smooth Muscle-Specific Proteins in Myoepithelium and Stromal Myofibroblasts of Normal and Malignant Human Breast Tissue. Proc. Natl. Acad. Sci. USA 1993, 90, 999–1003. [Google Scholar] [CrossRef] [Green Version]
  77. Tarin, D.; Croft, C.B. Ultrastructural Features of Wound Healing in Mouse Skin. J. Anat. 1969, 105, 189–190. [Google Scholar] [PubMed]
  78. Roberts, E.W.; Deonarine, A.; Jones, J.O.; Denton, A.E.; Feig, C.; Lyons, S.K.; Espeli, M.; Kraman, M.; McKenna, B.; Wells, R.J.B.; et al. Depletion of Stromal Cells Expressing Fibroblast Activation Protein-α From Skeletal Muscle and Bone Marrow Results in Cachexia and Anemia. J. Exp. Med. 2013, 210, 1137–1151. [Google Scholar] [CrossRef]
  79. Nurmik, M.; Ullmann, P.; Rodriguez, F.; Haan, S.; Letellier, E. In Search of Definitions: Cancer-Associated Fibroblasts and Their Markers. Int. J. Cancer 2020, 146, 895–905. [Google Scholar] [CrossRef] [Green Version]
  80. Zhao, X.; Ding, L.; Lu, Z.; Huang, X.; Jing, Y.; Yang, Y.; Chen, S.; Hu, Q.; Ni, Y. Diminished CD68+ Cancer-Associated Fibroblast Subset Induces Regulatory T-Cell (Treg) Infiltration and Predicts Poor Prognosis of Oral Squamous Cell Carcinoma Patients. Am. J. Pathol. 2020, 190, 886–899. [Google Scholar] [CrossRef]
  81. Xiang, H.; Ramil, C.P.; Hai, J.; Zhang, C.; Wang, H.; Watkins, A.A.; Afshar, R.; Georgiev, P.; Sze, M.A.; Song, X.S.; et al. Cancer-Associated Fibroblasts Promote Immunosuppression by Inducing ROS-Generating Monocytic MDSCs in Lung Squamous Cell Carcinoma. Cancer Immunol. Res. 2020, 8, 436–450. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Cheng, J.-T.; Deng, Y.-N.; Yi, H.-M.; Wang, G.-Y.; Fu, B.-S.; Chen, W.-J.; Liu, W.; Tai, Y.; Peng, Y.-W.; Zhang, Q. Hepatic Carcinoma-Associated Fibroblasts Induce IDO-Producing Regulatory Dendritic Cells Through IL-6-Mediated STAT3 Activation. Oncogenesis 2016, 5, e198. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Huang, C.; Wang, X.-L.; Qi, F.-F.; Pang, Z.-L. Berberine Inhibits Epithelial-Mesenchymal Transition and Promotes Apoptosis of Tumour-Associated Fibroblast-Induced Colonic Epithelial Cells Through Regulation of TGF-β Signalling. J. Cell Commun. Signal. 2020, 14, 53–66. [Google Scholar] [CrossRef] [PubMed]
  84. Wang, S.; Su, X.; Xu, M.; Xiao, X.; Li, X.; Li, H.; Keating, A.; Zhao, R.C. Exosomes Secreted by Mesenchymal Stromal/Stem Cell-Derived Adipocytes Promote Breast Cancer Cell Growth via Activation of Hippo Signaling Pathway. Stem Cell Res. Ther. 2019, 10, 117. [Google Scholar] [CrossRef] [Green Version]
  85. Ao, M.; Franco, O.E.; Park, D.; Raman, D.; Williams, K.; Hayward, S.W. Cross-Talk between Paracrine-Acting Cytokine and Chemokine Pathways Promotes Malignancy in Benign Human Prostatic Epithelium. Cancer Res. 2007, 67, 4244–4253. [Google Scholar] [CrossRef] [Green Version]
  86. Todaro, M.; Gaggianesi, M.; Catalano, V.; Benfante, A.; Iovino, F.; Biffoni, M.; Apuzzo, T.; Sperduti, I.; Volpe, S.; Cocorullo, G.; et al. CD44v6 is a Marker of Constitutive and Reprogrammed Cancer Stem Cells Driving Colon Cancer Metastasis. Cell Stem Cell 2014, 14, 342–356. [Google Scholar] [CrossRef] [Green Version]
  87. Han, D.; Wang, M.; Yu, Z.; Yin, L.; Liu, C.; Wang, J.; Liu, Y.; Jiang, S.; Ren, Z.; Yin, J. FGF5 Promotes Osteosarcoma Cells Proliferation via Activating MAPK Signaling Pathway. Cancer Manag. Res. 2019, 11, 6457–6466. [Google Scholar] [CrossRef] [Green Version]
  88. Li, H.; Zhang, Q.; Wu, Q.; Cui, Y.; Zhu, H.; Fang, M.; Zhou, X.; Sun, Z.; Yu, J. Interleukin-22 Secreted by Cancer-Associated Fibroblasts Regulates the Proliferation and Metastasis of Lung Cancer Cells via the PI3K-Akt-mTOR Signaling Pathway. Am. J. Transl. Res. 2019, 11, 4077–4088. [Google Scholar]
  89. Ma, H.; Wang, J.; Zhao, X.; Wu, T.; Huang, Z.; Chen, D.; Liu, Y.; Ouyang, G. Periostin Promotes Colorectal Tumorigenesis through Integrin-FAK-Src Pathway-Mediated YAP/TAZ Activation. Cell Rep. 2020, 30, 793–806. [Google Scholar] [CrossRef] [Green Version]
  90. Zhang, M.; Shi, R.; Guo, Z.; He, J. Cancer-Associated Fibroblasts Promote Cell Growth by Activating ERK5/PD-L1 Signaling Axis in Colorectal Cancer. Pathol. Res. Pract. 2020, 216, 152884. [Google Scholar] [CrossRef]
  91. Louault, K.; Bonneaud, T.L.; Séveno, C.; Gomez-Bougie, P.; Nguyen, F.; Gautier, F.; Bourgeois, N.; Loussouarn, D.; Kerdraon, O.; Barillé-Nion, S.; et al. Interactions Between Cancer-Associated Fibroblasts and Tumor Cells Promote MCL-1 Dependency in Estrogen Receptor-Positive Breast Cancers. Oncogene 2019, 38, 3261–3273. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  92. Zhang, L.; Yao, J.; Li, W.; Zhang, C. Micro-RNA-21 Regulates Cancer-Associated Fibroblast-Mediated Drug Resistance in Pancreatic Cancer. Oncol. Res. Featur. Preclin. Clin. Cancer Ther. 2018, 26, 827–835. [Google Scholar] [CrossRef] [PubMed]
  93. Lotti, F.; Jarrar, A.M.; Pai, R.K.; Hitomi, M.; Lathia, J.; Mace, A.; Gantt, G.A.; Sukhdeo, K.; DeVecchio, J.; Vasanji, A.; et al. Chemotherapy Activates Cancer-Associated Fibroblasts to Maintain Colorectal Cancer-Initiating Cells by IL-17A. J. Exp. Med. 2013, 210, 2851–2872. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  94. Kadel, D.; Zhang, Y.; Sun, H.-R.; Zhao, Y.; Dong, Q.-Z.; Qin, L. Current Perspectives of Cancer-Associated Fibroblast in Therapeutic Resistance: Potential Mechanism and Future Strategy. Cell Biol. Toxicol. 2019, 35, 407–421. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  95. Mutgan, A.C.; Besikcioglu, H.E.; Wang, S.; Friess, H.; Ceyhan, G.O.; Demir, I.E. Insulin/IGF- Driven Cancer Cell-Stroma Crosstalk as a Novel Therapeutic Target in Pancreatic Cancer. Mol. Cancer 2018, 17, 66. [Google Scholar] [CrossRef] [Green Version]
  96. Shiga, K.; Hara, M.; Nagasaki, T.; Sato, T.; Takahashi, H.; Takeyama, H. Cancer-Associated Fibroblasts: Their Characteristics and Their Roles in Tumor Growth. Cancers 2015, 7, 2443–2458. [Google Scholar] [CrossRef]
  97. Laklai, H.; Miroshnikova, Y.A.; Pickup, M.W.; Collisson, E.A.; Kim, G.E.; Barrett, A.S.; Hill, R.C.; Lakins, J.N.; Schlaepfer, D.D.; Mouw, J.K.; et al. Genotype Tunes Pancreatic Ductal Adenocarcinoma Tissue Tension to Induce Matricellular Fibrosis and Tumor Progression. Nat. Med. 2016, 22, 497–505. [Google Scholar] [CrossRef] [Green Version]
  98. Busch, S.; Acar, A.; Magnusson, Y.; Gregersson, P.; Rydén, L.; Landberg, G. TGF- Beta Receptor Type-2 Expression in Cancer-Associated Fibroblasts Regulates Breast Cancer Cell Growth and Survival and Is a Prognostic Marker in Pre-Menopausal Breast Cancer. Oncogene 2015, 34, 27–38. [Google Scholar] [CrossRef]
  99. Provenzano, P.P.; Cuevas, C.; Chang, A.E.; Goel, V.K.; Von Hoff, D.D.; Hingorani, S.R. Enzymatic Targeting of the Stroma Ablates Physical Barriers to Treatment of Pancreatic Ductal Adenocarcinoma. Cancer Cell 2012, 21, 418–429. [Google Scholar] [CrossRef] [Green Version]
  100. Guo, H.; Ha, C.; Dong, H.; Yang, Z.; Ma, Y.; Ding, Y. Cancer-Associated Fibroblast-Derived Exosomal MicroRNA-98-5p Promotes Cisplatin Resistance in Ovarian Cancer by Targeting CDKN1A. Cancer Cell Int. 2019, 19, 347. [Google Scholar] [CrossRef]
  101. Zhang, H.; Deng, T.; Liu, R.; Ning, T.; Yang, H.; Liu, D.; Zhang, Q.; Lin, D.; Ge, S.; Bai, M.; et al. CAF Secreted miR-522 Suppresses Ferroptosis and Promotes Acquired Chemo-Resistance in Gastric Cancer. Mol. Cancer 2020, 19, 43. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  102. Wang, R.; Sun, Y.; Yu, W.; Yan, Y.; Qiao, M.; Jiang, R.; Guan, W.; Wang, L. Downregulation of miRNA-214 in Cancer-Associated Fibroblasts Contributes to Migration and Invasion of Gastric Cancer Cells Through Targeting FGF9 and Inducing EMT. J. Exp. Clin. Cancer Res. 2019, 38, 20. [Google Scholar] [CrossRef] [Green Version]
  103. Shu, C.; Zha, H.; Long, H.; Wang, X.; Yang, F.; Gao, J.; Hu, C.; Zhou, L.; Guo, B.; Zhu, B. C3a-C3aR Signaling Promotes Breast Cancer Lung Metastasis via Modulating Carcinoma Associated Fibroblasts. J. Exp. Clin. Cancer Res. 2020, 39, 11. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  104. Wen, S.; Hou, Y.; Fu, L.; Xi, L.; Yang, D.; Zhao, M.; Qin, Y.; Sun, K.; Teng, Y.; Liu, M. Cancer-Associated Fibroblast (CAF)-Derived il32 Promotes Breast Cancer Cell Invasion and Metastasis via Integrin β3–p38 MAPK signalling. Cancer Lett. 2019, 442, 320–332. [Google Scholar] [CrossRef] [PubMed]
  105. Neri, S.; Miyashita, T.; Hashimoto, H.; Suda, Y.; Ishibashi, M.; Kii, H.; Watanabe, H.; Kuwata, T.; Tsuboi, M.; Goto, K.; et al. Fibroblast-Led Cancer Cell Invasion Is Activated by Epithelial–Mesenchymal Transition Through Platelet-Derived Growth Factor BB Secretion of Lung Adenocarcinoma. Cancer Lett. 2017, 395, 20–30. [Google Scholar] [CrossRef] [PubMed]
  106. Qiao, Y.; Chen, J.; Lim, Y.B.; Finch-Edmondson, M.L.; Seshachalam, V.P.; Qin, L.; Jiang, T.; Low, B.C.; Singh, H.; Lim, C.T.; et al. YAP Regulates Actin Dynamics through ARHGAP29 and Promotes Metastasis. Cell Rep. 2017, 19, 1495–1502. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  107. Wang, F.; Sun, W.; Zhang, J.; Fan, Y. Cancer-Associated Fibroblast Regulation of Tumor Neo-Angiogenesis as a Therapeutic Target in Cancer. Oncol. Lett. 2019. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  108. Inoue, K.; Kishimoto, S.; Akimoto, K.; Sakuma, M.; Toyoda, S.; Inoue, T.; Yoshida, K.; Shimoda, M.; Suzuki, S. Cancer-Associated Fibroblasts Show Heterogeneous Gene Expression and Induce Vascular Endothelial Growth Factor A (VEGFA) in Response to Environmental Stimuli. Ann. Gastroenterol. Surg. 2019. [Google Scholar] [CrossRef] [Green Version]
  109. San Martin, R.; Barron, D.A.; Tuxhorn, J.A.; Ressler, S.J.; Hayward, S.W.; Shen, X.; Laucirica, R.; Wheeler, T.M.; Gutierrez, C.; Ayala, G.E.; et al. Recruitment of CD34(+) Fibroblasts in Tumor-Associated Reactive Stroma: The Reactive Microvasculature Hypothesis. Am. J. Pathol. 2014, 184, 1860–1870. [Google Scholar] [CrossRef] [Green Version]
  110. Herrera, A.; Herrera, M.; Guerra-Perez, N.; Galindo-Pumariño, C.; Larriba, M.J.; García-Barberán, V.; Gil, B.; Giménez-Moyano, S.; Ferreiro-Monteagudo, R.; Veguillas, P.; et al. Endothelial Cell Activation on 3D-Matrices Derived From PDGF-BB-Stimulated Fibroblasts Is Mediated by snail1. Oncogenesis 2018, 7, 76. [Google Scholar] [CrossRef]
  111. Unterleuthner, D.; Neuhold, P.; Schwarz, K.; Janker, L.; Neuditschko, B.; Nivarthi, H.; Crncec, I.; Kramer, N.; Unger, C.; Hengstschläger, M.; et al. Cancer-Associated Fibroblast-Derived WNT2 Increases Tumor Angiogenesis in Colon Cancer. Angiogenesis 2020, 23, 159–177. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  112. Yang, J.; Lu, Y.; Lin, Y.-Y.; Zheng, Z.-Y.; Fang, J.-H.; He, S.; Zhuang, S.-M. Vascular Mimicry Formation Is Promoted by Paracrine TGF-β and SDF1 of Cancer-Associated Fibroblasts and Inhibited by miR-101 in Hepatocellular Carcinoma. Cancer Lett. 2016, 383, 18–27. [Google Scholar] [CrossRef] [PubMed]
  113. Tuxhorn, J.A.; McAlhany, S.J.; Yang, F.; Dang, T.D.; Rowley, D.R. Inhibition of Transforming Growth Factor-Beta Activity Decreases Angiogenesis in a Human Prostate Cancer-Reactive Stroma Xenograft Model. Cancer Res. 2002, 62, 6021–6025. [Google Scholar] [PubMed]
  114. Bordignon, P.; Bottoni, G.; Xu, X.; Popescu, A.S.; Truan, Z.; Guenova, E.; Kofler, L.; Jafari, P.; Ostano, P.; Röcken, M.; et al. Dualism of FGF and TGF-β Signaling in Heterogeneous Cancer-Associated Fibroblast Activation with ETV1 as a Critical Determinant. Cell Rep. 2019, 28, 2358–2372. [Google Scholar] [CrossRef] [Green Version]
  115. Vickman, R.E.; Broman, M.M.; Lanman, N.A.; Franco, O.E.; Sudyanti, P.A.G.; Ni, Y.; Ji, Y.; Helfand, B.T.; Petkewicz, J.; Paterakos, M.C.; et al. Heterogeneity of Human Prostate Carcinoma-Associated Fibroblasts Implicates a Role for Subpopulations in Myeloid Cell Recruitment. Prostate 2020, 80, 173–185. [Google Scholar] [CrossRef]
  116. Liao, D.; Luo, Y.; Markowitz, D.; Xiang, R.; Reisfeld, R.A. Cancer Associated Fibroblasts Promote Tumor Growth and Metastasis by Modulating the Tumor Immune Microenvironment in a 4T1 Murine Breast Cancer Model. PLoS ONE 2009, 4, e7965. [Google Scholar] [CrossRef] [Green Version]
  117. Kuen, J.; Darowski, D.; Kluge, T.; Majety, M. Pancreatic Cancer Cell/Fibroblast Co-Culture Induces M2 Like Macrophages That Influence Therapeutic Response in a 3D Model. PLoS ONE 2017, 12, e0182039. [Google Scholar] [CrossRef]
  118. Zhang, R.; Qi, F.; Zhao, F.; Li, G.; Shao, S.; Zhang, X.; Yuan, L.; Feng, Y. Cancer-Associated Fibroblasts Enhance Tumor-Associated Macrophages Enrichment and Suppress NK Cells Function in Colorectal Cancer. Cell Death Dis. 2019, 10, 273. [Google Scholar] [CrossRef] [Green Version]
  119. Fridlender, Z.G.; Sun, J.; Kim, S.; Kapoor, V.; Cheng, G.; Ling, L.; Worthen, G.S.; Albelda, S.M. Polarization of Tumor-Associated Neutrophil Phenotype by TGF-beta: “N1” versus “N2” TAN. Cancer Cell 2009, 16, 183–194. [Google Scholar] [CrossRef] [Green Version]
  120. Gok Yavuz, B.; Gunaydin, G.; Gedik, M.E.; Kosemehmetoglu, K.; Karakoc, D.; Ozgur, F.; Guc, D. Cancer Associated Fibroblasts Sculpt Tumour Microenvironment by Recruiting Monocytes and Inducing Immunosuppressive PD-1+ TAMs. Sci. Rep. 2019, 9, 3172. [Google Scholar] [CrossRef]
  121. Raker, V.K.; Domogalla, M.P.; Steinbrink, K. Tolerogenic Dendritic Cells for Regulatory T Cell Induction in Man. Front. Immunol. 2015, 6, 569. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  122. Comito, G.; Iscaro, A.; Bacci, M.; Morandi, A.; Ippolito, L.; Parri, M.; Montagnani, I.; Raspollini, M.R.; Serni, S.; Simeoni, L.; et al. Lactate Modulates CD4+ T-Cell Polarization and Induces an Immunosuppressive Environment, Which Sustains Prostate Carcinoma Progression via TLR8/miR21 Axis. Oncogene 2019, 38, 3681–3695. [Google Scholar] [CrossRef] [PubMed]
  123. Wu, H.-W.; Sheard, M.A.; Malvar, J.; Fernandez, G.E.; DeClerck, Y.A.; Blavier, L.; Shimada, H.; Theuer, C.P.; Sposto, R.; Seeger, R.C. Anti-CD105 Antibody Eliminates Tumor Microenvironment Cells and Enhances Anti-GD2 Antibody Immunotherapy of Neuroblastoma with Activated Natural Killer Cells. Clin. Cancer Res. 2019, 25, 4761–4774. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  124. Ford, K.; Hanley, C.J.; Mellone, M.; Szyndralewiez, C.; Heitz, F.; Wiesel, P.; Wood, O.; Machado, M.; Lopez, M.-A.; Ganesan, A.-P.; et al. NOX4 Inhibition Potentiates Immunotherapy by Overcoming Cancer-Associated Fibroblast-Mediated CD8 T-cell Exclusion from Tumors. Cancer Res. 2020. [Google Scholar] [CrossRef] [Green Version]
  125. Goehrig, D.; Nigri, J.; Samain, R.; Wu, Z.; Cappello, P.; Gabiane, G.; Zhang, X.; Zhao, Y.; Kim, I.-S.; Chanal, M.; et al. Stromal Protein βIg-h3 Reprogrammes Tumour Microenvironment in Pancreatic Cancer. Gut 2018. [Google Scholar] [CrossRef] [Green Version]
  126. Özdemir, B.C.; Pentcheva-Hoang, T.; Carstens, J.L.; Zheng, X.; Wu, C.-C.; Simpson, T.R.; Laklai, H.; Sugimoto, H.; Kahlert, C.; Novitskiy, S.V.; et al. Depletion of Carcinoma-Associated Fibroblasts and Fibrosis Induces Immunosuppression and Accelerates Pancreas Cancer with Reduced Survival. Cancer Cell 2014, 25, 719–734. [Google Scholar] [CrossRef] [Green Version]
  127. Rhim, A.D.; Oberstein, P.E.; Thomas, D.H.; Mirek, E.T.; Palermo, C.F.; Sastra, S.A.; Dekleva, E.N.; Saunders, T.; Becerra, C.P.; Tattersall, I.W.; et al. Stromal Elements Act to Restrain, Rather Than Support, Pancreatic Ductal Adenocarcinoma. Cancer Cell 2014, 25, 735–747. [Google Scholar] [CrossRef] [Green Version]
  128. Alkasalias, T.; Flaberg, E.; Kashuba, V.; Alexeyenko, A.; Pavlova, T.; Savchenko, A.; Szekely, L.; Klein, G.; Guven, H. Inhibition of Tumor Cell Proliferation and Motility by Fibroblasts Is Both Contact and Soluble Factor Dependent. Proc. Natl. Acad. Sci. USA 2014, 111, 17188–17193. [Google Scholar] [CrossRef] [Green Version]
  129. Alexeyenko, A.; Alkasalias, T.; Pavlova, T.; Szekely, L.; Kashuba, V.; Rundqvist, H.; Wiklund, P.; Egevad, L.; Csermely, P.; Korcsmaros, T.; et al. Confrontation of Fibroblasts With Cancer Cells In Vitro: Gene Network Analysis of Transcriptome Changes and Differential Capacity to Inhibit Tumor Growth. J. Exp. Clin. Cancer Res. CR 2015, 34, 62. [Google Scholar] [CrossRef] [Green Version]
  130. Degeorges, A.; Tatoud, R.; Fauvel-Lafeve, F.; Podgorniak, M.P.; Millot, G.; de Cremoux, P.; Calvo, F. Stromal Cells From Human Benign Prostate Hyperplasia Produce a Growth-Inhibitory Factor for LNCaP Prostate Cancer Cells, Identified as Interleukin -6. Int. J. Cancer 1996, 68, 207–214. [Google Scholar] [CrossRef]
  131. Paland, N.; Kamer, I.; Kogan-Sakin, I.; Madar, S.; Goldfinger, N.; Rotter, V. Differential Influence of Normal and Cancer-Associated Fibroblasts on the Growth of Human Epithelial Cells in an In Vitro Cocultivation Model of Prostate Cancer. Mol. Cancer Res. MCR 2009, 7, 1212–1223. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  132. Patel, A.K.; Vipparthi, K.; Thatikonda, V.; Arun, I.; Bhattacharjee, S.; Sharan, R.; Arun, P.; Singh, S. A Subtype of Cancer-Associated Fibroblasts With Lower Expression of Alpha-Smooth Muscle Actin Suppresses Stemness Through BMP4 in Oral Carcinoma. Oncogenesis 2018, 7, 78. [Google Scholar] [CrossRef] [PubMed]
  133. Pallangyo, C.K.; Ziegler, P.K.; Greten, F.R. IKKβ Acts as a Tumor Suppressor in Cancer-Associated Fibroblasts During Intestinal Tumorigenesis. J. Exp. Med. 2015, 212, 2253–2266. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  134. Chen, X.; Song, E. Turning Foes to Friends: Targeting Cancer-Associated Fibroblasts. Nat. Rev. Drug Discov. 2019, 18, 99–115. [Google Scholar] [CrossRef] [PubMed]
  135. Ziani, L.; Chouaib, S.; Thiery, J. Alteration of the Antitumor Immune Response by Cancer-Associated Fibroblasts. Front. Immunol. 2018, 9, 414. [Google Scholar] [CrossRef]
  136. Poltavets, V.; Kochetkova, M.; Pitson, S.M.; Samuel, M.S. The Role of the Extracellular Matrix and Its Molecular and Cellular Regulators in Cancer Cell Plasticity. Front. Oncol. 2018, 8, 431. [Google Scholar] [CrossRef] [Green Version]
  137. Flavell, R.A.; Sanjabi, S.; Wrzesinski, S.H.; Licona-Limón, P. The Polarization of Immune Cells in the Tumour Environment by TGFbeta. Nat. Rev. Immunol. 2010, 10, 554–567. [Google Scholar] [CrossRef] [Green Version]
  138. Park, Y.P.; Choi, S.-C.; Kiesler, P.; Gil-Krzewska, A.; Borrego, F.; Weck, J.; Krzewski, K.; Coligan, J.E. Complex Regulation of Human NKG2D-DAP10 Cell Surface Expression: Opposing Roles of the γc Cytokines and TGF-β1. Blood 2011, 118, 3019–3027. [Google Scholar] [CrossRef] [Green Version]
  139. Tang, Z.; Li, C.; Kang, B.; Gao, G.; Li, C.; Zhang, Z. GEPIA: A Web Server for Cancer and Normal Gene Expression Profiling and Interactive Analyses. Nucleic Acids Res. 2017, 45, W98–W102. [Google Scholar] [CrossRef] [Green Version]
  140. Bu, L.; Baba, H.; Yoshida, N.; Miyake, K.; Yasuda, T.; Uchihara, T.; Tan, P.; Ishimoto, T. Biological Heterogeneity and Versatility of Cancer-Associated Fibroblasts in the Tumor Microenvironment. Oncogene 2019, 38, 4887–4901. [Google Scholar] [CrossRef]
  141. Rosty, C.; Ueki, T.; Argani, P.; Jansen, M.; Yeo, C.J.; Cameron, J.L.; Hruban, R.H.; Goggins, M. Overexpression of S100A4 in Pancreatic Ductal Adenocarcinomas Is Associated With Poor Differentiation and DNA Hypomethylation. Am. J. Pathol. 2002, 160, 45–50. [Google Scholar] [CrossRef] [Green Version]
  142. Kim, S.; You, D.; Jeong, Y.; Yu, J.; Kim, S.W.; Nam, S.J.; Lee, J.E. TP53 Upregulates α-Smooth Muscle Actin Expression in Tamoxifen-Resistant Breast Cancer Cells. Oncol. Rep. 2019, 41, 1075–1082. [Google Scholar] [CrossRef] [Green Version]
  143. Österreicher, C.H.; Penz-Österreicher, M.; Grivennikov, S.I.; Guma, M.; Koltsova, E.K.; Datz, C.; Sasik, R.; Hardiman, G.; Karin, M.; Brenner, D.A. Fibroblast-Specific Protein 1 Identifies an Inflammatory Subpopulation of Macrophages in the Liver. Proc. Natl. Acad. Sci. USA 2011, 108, 308–313. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  144. Sun, S.; Wang, Y.; Wu, Y.; Gao, Y.; Li, Q.; Abdulrahman, A.A.; Liu, X.-F.; Ji, G.-Q.; Gao, J.; Li, L.; et al. Identification of COL1A1 as an Invasion-Related Gene in Malignant Astrocytoma. Int. J. Oncol. 2018, 53, 2542–2554. [Google Scholar] [CrossRef] [PubMed]
  145. Qin, X.; Yan, M.; Zhang, J.; Wang, X.; Shen, Z.; Lv, Z.; Li, Z.; Wei, W.; Chen, W. TGFβ3- Mediated Induction of Periostin Facilitates Head and Neck Cancer Growth and Is Associated With Metastasis. Sci. Rep. 2016, 6, 20587. [Google Scholar] [CrossRef] [Green Version]
  146. Fujimura, T.; Kakizaki, A.; Furudate, S.; Aiba, S. A Possible Interaction Between Periostin and CD163+ Skin-Resident Macrophages in Pemphigus Vulgaris and Bullous Pemphigoid. Exp. Dermatol. 2017, 26, 1193–1198. [Google Scholar] [CrossRef]
  147. Hu, Q.; Tong, S.; Zhao, X.; Ding, W.; Gou, Y.; Xu, K.; Sun, C.; Xia, G. Periostin Mediates TGF-β-Induced Epithelial Mesenchymal Transition in Prostate Cancer Cells. Cell. Physiol. Biochem. Int. J. Exp. Cell. Physiol. Biochem. Pharmacol. 2015, 36, 799–809. [Google Scholar] [CrossRef] [Green Version]
  148. Kitano, H.; Kageyama, S.-I.; Hewitt, S.M.; Hayashi, R.; Doki, Y.; Ozaki, Y.; Fujino, S.; Takikita, M.; Kubo, H.; Fukuoka, J. Podoplanin Expression in Cancerous Stroma Induces Lymphangiogenesis and Predicts Lymphatic Spread and Patient Survival. Arch. Pathol. Lab. Med. 2010, 134, 1520–1527. [Google Scholar] [CrossRef]
  149. Schoppmann, S.F.; Berghoff, A.; Dinhof, C.; Jakesz, R.; Gnant, M.; Dubsky, P.; Jesch, B.; Heinzl, H.; Birner, P. Podoplanin-Expressing Cancer-Associated Fibroblasts Are Associated With Poor Prognosis in Invasive Breast Cancer. Breast Cancer Res. Treat. 2012, 134, 237–244. [Google Scholar] [CrossRef]
  150. Pula, B.; Jethon, A.; Piotrowska, A.; Gomulkiewicz, A.; Owczarek, T.; Calik, J.; Wojnar, A.; Witkiewicz, W.; Rys, J.; Ugorski, M.; et al. Podoplanin Expression by Cancer-Associated Fibroblasts Predicts Poor Outcome in Invasive Ductal Breast Carcinoma. Histopathology 2011, 59, 1249–1260. [Google Scholar] [CrossRef]
  151. Ono, S.; Ishii, G.; Nagai, K.; Takuwa, T.; Yoshida, J.; Nishimura, M.; Hishida, T.; Aokage, K.; Fujii, S.; Ikeda, N.; et al. Podoplanin-Positive Cancer-Associated Fibroblasts Could Have Prognostic Value Independent of Cancer Cell Phenotype in Stage I Lung Squamous Cell Carcinoma. Chest 2013, 143, 963–970. [Google Scholar] [CrossRef]
  152. Neri, S.; Ishii, G.; Hashimoto, H.; Kuwata, T.; Nagai, K.; Date, H.; Ochiai, A. Podoplanin-Expressing Cancer-Associated Fibroblasts Lead and Enhance the Local Invasion of Cancer Cells in Lung Adenocarcinoma. Int. J. Cancer 2015, 137, 784–796. [Google Scholar] [CrossRef]
  153. Segade, F. Functional Evolution of the Microfibril-Associated Glycoproteins. Gene 2009, 439, 43–54. [Google Scholar] [CrossRef] [PubMed]
  154. Spivey, K.A.; Banyard, J. A Prognostic Gene Signature in Advanced Ovarian Cancer Reveals a Microfibril-Associated Protein (MAGP2) as a Promoter of Tumor Cell Survival and Angiogenesis. Cell Adhes. Migr. 2010, 4, 169–171. [Google Scholar] [CrossRef] [PubMed]
  155. Zhou, Z.; Cui, D.; Sun, M.-H.; Huang, J.-L.; Deng, Z.; Han, B.-M.; Sun, X.-W.; Xia, S.-J.; Sun, F.; Shi, F. CAFs-Derived MFAP5 Promotes Bladder Cancer Malignant Behavior Through NOTCH2/HEY1 Signaling. FASEB J. 2020. [Google Scholar] [CrossRef] [Green Version]
  156. Principe, S.; Mejia-Guerrero, S.; Ignatchenko, V.; Sinha, A.; Ignatchenko, A.; Shi, W.; Pereira, K.; Su, S.; Huang, S.H.; O’Sullivan, B.; et al. Proteomic Analysis of Cancer-Associated Fibroblasts Reveals a Paracrine Role for MFAP5 in Human Oral Tongue Squamous Cell Carcinoma. J. Proteome Res. 2018, 17, 2045–2059. [Google Scholar] [CrossRef] [PubMed]
  157. Leung, C.S.; Yeung, T.-L.; Yip, K.-P.; Wong, K.-K.; Ho, S.Y.; Mangala, L.S.; Sood, A.K.; Lopez-Berestein, G.; Sheng, J.; Wong, S.T.; et al. Cancer-Associated Fibroblasts Regulate Endothelial Adhesion Protein Lpp to Promote Ovarian Cancer Chemoresistance. J. Clin. Investig. 2018, 128, 589–606. [Google Scholar] [CrossRef] [Green Version]
  158. Yeung, T.-L.; Leung, C.S.; Yip, K.-P.; Sheng, J.; Vien, L.; Bover, L.C.; Birrer, M.J.; Wong, S.T.C.; Mok, S.C. Anticancer Immunotherapy by MFAP5 Blockade Inhibits Fibrosis and Enhances Chemosensitivity in Ovarian and Pancreatic Cancer. Clin. Cancer Res. 2019, 25, 6417–6428. [Google Scholar] [CrossRef]
  159. Sahai, E.; Astsaturov, I.; Cukierman, E.; DeNardo, D.G.; Egeblad, M.; Evans, R.M.; Fearon, D.; Greten, F.R.; Hingorani, S.R.; Hunter, T.; et al. A Framework for Advancing Our Understanding of Cancer-Associated Fibroblasts. Nat. Rev. Cancer 2020, 20, 174–186. [Google Scholar] [CrossRef] [Green Version]
  160. Huber, M.A.; Kraut, N.; Park, J.E.; Schubert, R.D.; Rettig, W.J.; Peter, R.U.; Garin-Chesa, P. Fibroblast Activation Protein: Differential Expression and Serine Protease Activity in Reactive Stromal Fibroblasts of Melanocytic Skin Tumors. J. Investig. Dermatol. 2003, 120, 182–188. [Google Scholar] [CrossRef] [Green Version]
  161. Wen, Y.; Wang, C.-T.; Ma, T.-T.; Li, Z.-Y.; Zhou, L.-N.; Mu, B.; Leng, F.; Shi, H.-S.; Li, Y.-O.; Wei, Y.-Q. Immunotherapy Targeting Fibroblast Activation Protein Inhibits Tumor Growth and Increases Survival in a Murine Colon Cancer Model. Cancer Sci. 2010, 101, 2325–2332. [Google Scholar] [CrossRef] [PubMed]
  162. Ostermann, E.; Garin-Chesa, P.; Heider, K.H.; Kalat, M.; Lamche, H.; Puri, C.; Kerjaschki, D.; Rettig, W.J.; Adolf, G.R. Effective Immunoconjugate Therapy in Cancer Models Targeting a Serine Protease of Tumor Fibroblasts. Clin. Cancer Res. 2008, 14, 4584–4592. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  163. Wang, H.; Wu, Q.; Liu, Z.; Luo, X.; Fan, Y.; Liu, Y.; Zhang, Y.; Hua, S.; Fu, Q.; Zhao, M.; et al. Downregulation of FAP Suppresses Cell Proliferation and Metastasis Through PTEN/PI3K/AKT and Ras-ERK Signaling in Oral Squamous Cell Carcinoma. Cell Death Dis. 2014, 5, e1155. [Google Scholar] [CrossRef] [PubMed]
  164. Santos, A.M.; Jung, J.; Aziz, N.; Kissil, J.L.; Puré, E. Targeting Fibroblast Activation Protein Inhibits Tumor Stromagenesis and Growth in Mice. J. Clin. Investig. 2009, 119, 3613–3625. [Google Scholar] [CrossRef]
  165. Wang, L.-C.S.; Lo, A.; Scholler, J.; Sun, J.; Majumdar, R.S.; Kapoor, V.; Antzis, M.; Cotner, C.E.; Johnson, L.A.; Durham, A.C.; et al. Targeting Fibroblast Activation Protein in Tumor Stroma With Chimeric Antigen Receptor T Cells Can Inhibit Tumor Growth and Augment Host Immunity Without Severe Toxicity. Cancer Immunol. Res. 2014, 2, 154–166. [Google Scholar] [CrossRef] [Green Version]
  166. Scott, A.M.; Wiseman, G.; Welt, S.; Adjei, A.; Lee, F.-T.; Hopkins, W.; Divgi, C.R.; Hanson, L.H.; Mitchell, P.; Gansen, D.N.; et al. A Phase I Dose-Escalation Study of Sibrotuzumab in Patients with Advanced or Metastatic Fibroblast Activation Protein-Positive Cancer. Clin. Cancer Res. 2003, 9, 1639–1647. [Google Scholar]
  167. Hofheinz, R.-D.; al-Batran, S.-E.; Hartmann, F.; Hartung, G.; Jäger, D.; Renner, C.; Tanswell, P.; Kunz, U.; Amelsberg, A.; Kuthan, H.; et al. Stromal Antigen Targeting by a Humanised Monoclonal Antibody: An Early Phase II Trial of Sibrotuzumab in Patients With Metastatic Colorectal Cancer. Onkologie 2003, 26, 44–48. [Google Scholar] [CrossRef]
  168. Narra, K.; Mullins, S.R.; Lee, H.-O.; Strzemkowski-Brun, B.; Magalong, K.; Christiansen, V.J.; McKee, P.A.; Egleston, B.; Cohen, S.J.; Weiner, L.M.; et al. Phase II Trial of Single Agent Val-BoroPro (Talabostat) Inhibiting Fibroblast Activation Protein in Patients With Metastatic Colorectal Cancer. Cancer Biol. Ther. 2007, 6, 1691–1699. [Google Scholar] [CrossRef] [Green Version]
  169. Rosen, L.S.; Gordon, M.S.; Robert, F.; Matei, D.E. Endoglin for Targeted Cancer Treatment. Curr. Oncol. Rep. 2014, 16, 365. [Google Scholar] [CrossRef]
  170. Haubeiss, S.; Schmid, J.O.; Mürdter, T.E.; Sonnenberg, M.; Friedel, G.; van der Kuip, H.; Aulitzky, W.E. Dasatinib Reverses Cancer-Associated Fibroblasts (CAFs) From Primary Lung Carcinomas to a Phenotype Comparable to That of Normal Fibroblasts. Mol. Cancer 2010, 9, 168. [Google Scholar] [CrossRef] [Green Version]
  171. Du, H.; Che, G. Genetic Alterations and Epigenetic Alterations of Cancer-Associated Fibroblasts. Oncol. Lett. 2017, 13, 3–12. [Google Scholar] [CrossRef] [Green Version]
  172. Mishra, R.; Haldar, S.; Suchanti, S.; Bhowmick, N.A. Epigenetic Changes in Fibroblasts Drive Cancer Metabolism and Differentiation. Endocr. Relat. Cancer 2019, 26, R673–R688. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  173. Musumeci, M.; Coppola, V.; Addario, A.; Patrizii, M.; Maugeri-Saccà, M.; Memeo, L.; Colarossi, C.; Francescangeli, F.; Biffoni, M.; Collura, D.; et al. Control of Tumor and Microenvironment Cross-Talk by Mir-15a and Mir-16 in Prostate Cancer. Oncogene 2011, 30, 4231–4242. [Google Scholar] [CrossRef] [Green Version]
  174. Melling, G.E.; Flannery, S.E.; Abidin, S.A.; Clemmens, H.; Prajapati, P.; Hinsley, E.E.; Hunt, S.; Catto, J.W.F.; Coletta, R.D.; Mellone, M.; et al. A miRNA-145/TGF-β1 Negative Feedback Loop Regulates the Cancer-Associated Fibroblast Phenotype. Carcinogenesis 2018, 39, 798–807. [Google Scholar] [CrossRef] [PubMed]
  175. Al-Harbi, B.; Hendrayani, S.-F.; Silva, G.; Aboussekhra, A. Let-7b Inhibits Cancer-Promoting Effects of Breast Cancer-Associated Fibroblasts Through IL-8 Repression. Oncotarget 2018, 9, 17825–17838. [Google Scholar] [CrossRef]
  176. Thambyrajah, R.; Fadlullah, M.Z.H.; Proffitt, M.; Patel, R.; Cowley, S.M.; Kouskoff, V.; Lacaud, G. HDAC1 and HDAC2 Modulate TGF-β Signaling during Endothelial-to-Hematopoietic Transition. Stem Cell Rep. 2018, 10, 1369–1383. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  177. Kim, D.J.; Dunleavey, J.M.; Xiao, L.; Ollila, D.W.; Troester, M.A.; Otey, C.A.; Li, W.; Barker, T.H.; Dudley, A.C. Suppression of TGFβ- Mediated Conversion of Endothelial Cells and Fibroblasts Into Cancer Associated (Myo)Fibroblasts via HDAC Inhibition. Br. J. Cancer 2018, 118, 1359–1368. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  178. Liu, L.; Sun, X.; Xie, Y.; Zhuang, Y.; Yao, R.; Xu, K. Anticancer Effect of Histone Deacetylase Inhibitor Scriptaid as a Single Agent for Hepatocellular Carcinoma. Biosci. Rep. 2018, 38. [Google Scholar] [CrossRef] [Green Version]
  179. Albrengues, J.; Bertero, T.; Grasset, E.; Bonan, S.; Maiel, M.; Bourget, I.; Philippe, C.; Herraiz Serrano, C.; Benamar, S.; Croce, O.; et al. Epigenetic Switch Drives the Conversion of Fibroblasts Into Proinvasive Cancer-Associated Fibroblasts. Nat. Commun. 2015, 6, 10204. [Google Scholar] [CrossRef] [Green Version]
  180. Hurwitz, H.I.; Uppal, N.; Wagner, S.A.; Bendell, J.C.; Beck, J.T.; Wade, S.M.; Nemunaitis, J.J.; Stella, P.J.; Pipas, J.M.; Wainberg, Z.A.; et al. Randomized, Double-Blind, Phase II Study of Ruxolitinib or Placebo in Combination With Capecitabine in Patients With Metastatic Pancreatic Cancer for Whom Therapy with Gemcitabine Has Failed. J. Clin. Oncol. 2015, 33, 4039–4047. [Google Scholar] [CrossRef]
  181. Park, J.S.; Hong, M.H.; Chun, Y.J.; Kim, H.R.; Cho, B.C. A Phase Ib Study of the Combination of Afatinib and Ruxolitinib in EGFR Mutant NSCLC with Progression on EGFR-TKIs. Lung Cancer 2019, 134, 46–51. [Google Scholar] [CrossRef] [PubMed]
  182. Yu, H.A.; Perez, L.; Chang, Q.; Gao, S.P.; Kris, M.G.; Riely, G.J.; Bromberg, J. A Phase 1/2 Trial of Ruxolitinib and Erlotinib in Patients with EGFR-Mutant Lung Adenocarcinomas with Acquired Resistance to Erlotinib. J. Thorac. Oncol. 2017, 12, 102–109. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  183. Mertens, J.C.; Fingas, C.D.; Christensen, J.D.; Smoot, R.L.; Bronk, S.F.; Werneburg, N.W.; Gustafson, M.P.; Dietz, A.B.; Roberts, L.R.; Sirica, A.E.; et al. Therapeutic Effects of Deleting Cancer-Associated Fibroblasts in Cholangiocarcinoma. Cancer Res. 2013, 73, 897–907. [Google Scholar] [CrossRef] [Green Version]
  184. Rizvi, S.; Mertens, J.C.; Bronk, S.F.; Hirsova, P.; Dai, H.; Roberts, L.R.; Kaufmann, S.H.; Gores, G.J. Platelet-Derived Growth Factor Primes Cancer-Associated Fibroblasts for Apoptosis. J. Biol. Chem. 2014, 289, 22835–22849. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  185. Lagares, D.; Santos, A.; Grasberger, P.E.; Liu, F.; Probst, C.K.; Rahimi, R.A.; Sakai, N.; Kuehl, T.; Ryan, J.; Bhola, P.; et al. Targeted Apoptosis of Myofibroblasts With the BH3 Mimetic ABT-263 Reverses Established Fibrosis. Sci. Transl. Med. 2017, 9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  186. Diop-Frimpong, B.; Chauhan, V.P.; Krane, S.; Boucher, Y.; Jain, R.K. Losartan Inhibits Collagen I Synthesis and Improves the Distribution and Efficacy of Nanotherapeutics in Tumors. Proc. Natl. Acad. Sci. USA. 2011, 108, 2909–2914. [Google Scholar] [CrossRef] [Green Version]
  187. Masamune, A.; Hamada, S.; Kikuta, K.; Takikawa, T.; Miura, S.; Nakano, E.; Shimosegawa, T. The Angiotensin II Type I Receptor Blocker Olmesartan Inhibits the Growth of Pancreatic Cancer by Targeting Stellate Cell Activities in Mice. Scand. J. Gastroenterol. 2013, 48, 602–609. [Google Scholar] [CrossRef]
  188. Osumi, H.; Matsusaka, S.; Wakatsuki, T.; Suenaga, M.; Shinozaki, E.; Mizunuma, N. Angiotensin II Type-1 Receptor Blockers Enhance the Effects of Bevacizumab-Based Chemotherapy in Metastatic Colorectal Cancer Patients. Mol. Clin. Oncol. 2015, 3, 1295–1300. [Google Scholar] [CrossRef] [Green Version]
  189. Murphy, J.E.; Wo, J.Y.; Ryan, D.P.; Clark, J.W.; Jiang, W.; Yeap, B.Y.; Drapek, L.C.; Ly, L.; Baglini, C.V.; Blaszkowsky, L.S.; et al. Total Neoadjuvant Therapy With FOLFIRINOX in Combination With Losartan Followed by Chemoradiotherapy for Locally Advanced Pancreatic Cancer: A Phase 2 Clinical Trial. JAMA Oncol. 2019, 5, 1020–1027. [Google Scholar] [CrossRef]
  190. Alvarez, R.; Musteanu, M.; Garcia-Garcia, E.; Lopez-Casas, P.P.; Megias, D.; Guerra, C.; Muñoz, M.; Quijano, Y.; Cubillo, A.; Rodriguez-Pascual, J.; et al. Stromal Disrupting Effects of Nab-Paclitaxel in Pancreatic Cancer. Br. J. Cancer 2013, 109, 926–933. [Google Scholar] [CrossRef] [Green Version]
  191. Feng, R.; Morine, Y.; Ikemoto, T.; Imura, S.; Iwahashi, S.; Saito, Y.; Shimada, M. Nab-Paclitaxel Interrupts Cancer-Stromal Interaction Through C-X-C Motif Chemokine 10-Mediated Interleukin-6 Downregulation In Vitro. Cancer Sci. 2018, 109, 2509–2519. [Google Scholar] [CrossRef] [PubMed]
  192. Schmid, P.; Rugo, H.S.; Adams, S.; Schneeweiss, A.; Barrios, C.H.; Iwata, H.; Diéras, V.; Henschel, V.; Molinero, L.; Chui, S.Y.; et al. Atezolizumab Plus Nab-Paclitaxel as First-Line Treatment for Unresectable, Locally Advanced or Metastatic Triple-Negative Breast Cancer (IMpassion130): Updated Efficacy Results From a Randomised, Double-Blind, Placebo-Controlled, Phase 3 Trial. Lancet Oncol. 2020, 21, 44–59. [Google Scholar] [CrossRef]
  193. Schmid, P.; Adams, S.; Rugo, H.S.; Schneeweiss, A.; Barrios, C.H.; Iwata, H.; Diéras, V.; Hegg, R.; Im, S.-A.; Shaw Wright, G.; et al. Atezolizumab and Nab-Paclitaxel in Advanced Triple-Negative Breast Cancer. N. Engl. J. Med. 2018, 379, 2108–2121. [Google Scholar] [CrossRef]
  194. West, H.; McCleod, M.; Hussein, M.; Morabito, A.; Rittmeyer, A.; Conter, H.J.; Kopp, H.-G.; Daniel, D.; McCune, S.; Mekhail, T.; et al. Atezolizumab in Combination With Carboplatin Plus Nab-Paclitaxel Chemotherapy Compared With Chemotherapy Alone as First-Line Treatment for Metastatic Non-Squamous Non-Small-Cell Lung Cancer (IMpower130): A Multicentre, Randomised, Open-Label, Phase 3 Trial. Lancet Oncol. 2019, 20, 924–937. [Google Scholar] [CrossRef]
  195. Feig, C.; Jones, J.O.; Kraman, M.; Wells, R.J.B.; Deonarine, A.; Chan, D.S.; Connell, C.M.; Roberts, E.W.; Zhao, Q.; Caballero, O.L.; et al. Targeting CXCL12 from FAP- Expressing Carcinoma-Associated Fibroblasts Synergizes with Anti-PD-L1 Immunotherapy in Pancreatic Cancer. Proc. Natl. Acad. Sci. USA 2013, 110, 20212–20217. [Google Scholar] [CrossRef] [Green Version]
  196. Zhu, W.-B.; Zhao, Z.-F.; Zhou, X. AMD3100 Inhibits Epithelial-Mesenchymal Transition, Cell Invasion, and Metastasis in the Liver and the Lung Through Blocking the SDF-1α/CXCR4 Signaling Pathway in Prostate Cancer. J. Cell. Physiol. 2019, 234, 11746–11759. [Google Scholar] [CrossRef]
  197. Daniel, S.K.; Seo, Y.D.; Pillarisetty, V.G. The CXCL12-CXCR4/CXCR7 Axis as a Mechanism of Immune Resistance in Gastrointestinal Malignancies. Semin. Cancer Biol. 2019. [Google Scholar] [CrossRef] [PubMed]
  198. Holmgaard, R.B.; Schaer, D.A.; Li, Y.; Castaneda, S.P.; Murphy, M.Y.; Xu, X.; Inigo, I.; Dobkin, J.; Manro, J.R.; Iversen, P.W.; et al. Targeting the TGFβ Pathway with Galunisertib, a TGFβRI Small Molecule Inhibitor, Promotes Anti-Tumor Immunity Leading to Durable, Complete Responses, as Monotherapy and in Combination with Checkpoint Blockade. J. Immunother. Cancer 2018, 6, 47. [Google Scholar] [CrossRef]
  199. Hammad, S.; Cavalcanti, E.; Werle, J.; Caruso, M.L.; Dropmann, A.; Ignazzi, A.; Ebert, M.P.; Dooley, S.; Giannelli, G. Galunisertib Modifies the Liver Fibrotic Composition in the abcb4ko Mouse Model. Arch. Toxicol. 2018, 92, 2297–2309. [Google Scholar] [CrossRef]
  200. Melisi, D.; Garcia-Carbonero, R.; Macarulla, T.; Pezet, D.; Deplanque, G.; Fuchs, M.; Trojan, J.; Kozloff, M.; Simionato, F.; Cleverly, A.; et al. TGFβ Receptor Inhibitor Galunisertib Is Linked to Inflammation-and Remodeling-Related Proteins in Patients With Pancreatic Cancer. Cancer Chemother. Pharmacol. 2019, 83, 975–991. [Google Scholar] [CrossRef]
  201. Mendt, M.; Rezvani, K.; Shpall, E. Mesenchymal Stem Cell-Derived Exosomes for Clinical Use. Bone Marrow Transplant. 2019, 54, 789–792. [Google Scholar] [CrossRef] [PubMed]
  202. Lin, W.; Huang, L.; Li, Y.; Fang, B.; Li, G.; Chen, L.; Xu, L. Mesenchymal Stem Cells and Cancer: Clinical Challenges and Opportunities. BioMed Res. Int. 2019, 2019, 2820853. [Google Scholar] [CrossRef] [Green Version]
  203. Hmadcha, A.; Martin-Montalvo, A.; Gauthier, B.R.; Soria, B.; Capilla-Gonzalez, V. Therapeutic Potential of Mesenchymal Stem Cells for Cancer Therapy. Front. Bioeng. Biotechnol. 2020, 8, 43. [Google Scholar] [CrossRef]
  204. Kamerkar, S.; LeBleu, V.S.; Sugimoto, H.; Yang, S.; Ruivo, C.F.; Melo, S.A.; Lee, J.J.; Kalluri, R. Exosomes Facilitate Therapeutic Targeting of Oncogenic KRAS in Pancreatic Cancer. Nature 2017, 546, 498–503. [Google Scholar] [CrossRef] [PubMed]
  205. Mendt, M.; Kamerkar, S.; Sugimoto, H.; McAndrews, K.M.; Wu, C.-C.; Gagea, M.; Yang, S.; Blanko, E.V.R.; Peng, Q.; Ma, X.; et al. Generation and Testing of Clinical-Grade Exosomes for Pancreatic Cancer. JCI Insight 2018, 3. [Google Scholar] [CrossRef] [PubMed]
  206. Bonomi, A.; Steimberg, N.; Benetti, A.; Berenzi, A.; Alessandri, G.; Pascucci, L.; Boniotti, J.; Coccè, V.; Sordi, V.; Pessina, A.; et al. Paclitaxel-Releasing Mesenchymal Stromal Cells Inhibit the Growth of Multiple Myeloma Cells in a Dynamic 3D Culture System. Hematol. Oncol. 2017, 35, 693–702. [Google Scholar] [CrossRef] [PubMed]
  207. Brini, A.T.; Coccè, V.; Ferreira, L.M.J.; Giannasi, C.; Cossellu, G.; Giannì, A.B.; Angiero, F.; Bonomi, A.; Pascucci, L.; Falchetti, M.L.; et al. Cell-Mediated Drug Delivery by Gingival Interdental Papilla Mesenchymal Stromal Cells (GinPa-MSCs) Loaded with Paclitaxel. Expert Opin. Drug Deliv. 2016, 13, 789–798. [Google Scholar] [CrossRef] [PubMed]
  208. Niess, H.; von Einem, J.C.; Thomas, M.N.; Michl, M.; Angele, M.K.; Huss, R.; Günther, C.; Nelson, P.J.; Bruns, C.J.; Heinemann, V. Treatment of Advanced Gastrointestinal Tumors With Genetically Modified Autologous Mesenchymal Stromal Cells (TREAT-ME1): Study Protocol of a Phase I/II Clinical Trial. BMC Cancer 2015, 15, 237. [Google Scholar] [CrossRef] [Green Version]
  209. Ren, C.; Kumar, S.; Chanda, D.; Kallman, L.; Chen, J.; Mountz, J.D.; Ponnazhagan, S. Cancer Gene Therapy Using Mesenchymal Stem Cells Expressing Interferon-Beta in a Mouse Prostate Cancer Lung Metastasis Model. Gene Ther. 2008, 15, 1446–1453. [Google Scholar] [CrossRef] [Green Version]
Cancers 12 03108 g001 550
Figure 1. Origin of Cancer-Associated Fibroblasts. The different cellular sources for CAFs are shown, colors indicate the type of origin. Factors involved in the recruitment, differentiation and activation of these cells into CAFs are indicated for each cell type.
Figure 1. Origin of Cancer-Associated Fibroblasts. The different cellular sources for CAFs are shown, colors indicate the type of origin. Factors involved in the recruitment, differentiation and activation of these cells into CAFs are indicated for each cell type.
Cancers 12 03108 g001
Cancers 12 03108 g002 550
Figure 2. Heterogenous Function and Phenotype of Cancer-Associated Fibroblasts. The inner circle lists subtypes of CAFs reported by various groups of investigators. The middle circle indicates markers and proteins secreted by each subtype and in the outer circle, the functions attributed for each subtype are indicated by the colored circles representing one among the six CAF functions listed in the margin.
Figure 2. Heterogenous Function and Phenotype of Cancer-Associated Fibroblasts. The inner circle lists subtypes of CAFs reported by various groups of investigators. The middle circle indicates markers and proteins secreted by each subtype and in the outer circle, the functions attributed for each subtype are indicated by the colored circles representing one among the six CAF functions listed in the margin.
Cancers 12 03108 g002
Cancers 12 03108 g003 550
Figure 3. In silico gene expression analysis of 14 genes expressed by CAFs in human tumors. (A). Heat map representation of the expression of 14 genes (column) among 33 types of cancer (row). Data were generated by Gene Expression Profiling Interactive Analysis (GEPIA) of The Cancer Genome Atlas (TCGA) database; (B). Correlation analysis between the expression of S100A4 and COL1A2 in cancer.
Figure 3. In silico gene expression analysis of 14 genes expressed by CAFs in human tumors. (A). Heat map representation of the expression of 14 genes (column) among 33 types of cancer (row). Data were generated by Gene Expression Profiling Interactive Analysis (GEPIA) of The Cancer Genome Atlas (TCGA) database; (B). Correlation analysis between the expression of S100A4 and COL1A2 in cancer.
Cancers 12 03108 g003
Table
Table 1. Phenotypic and functional heterogeneity of Cancer-Associated Fibroblasts and therapeutic approaches.
Table 1. Phenotypic and functional heterogeneity of Cancer-Associated Fibroblasts and therapeutic approaches.
CancersSubtypesClustersIHC/Flow CytometryscRNA-seqFunctionsRef.Preclinical/Clinical Trials
Not SpecificProbably Specific
Breast/PDACCAF-1 FSP1, VEGF, TNC Angiogenesis, Metastasis[54,55,56,57]αFAP therapy, CD105 mAb, Dasatinib, miRNAs therapy, Scriptaid, Ruxolitinib, Losartan, Nab-paclitaxel, AMD3100, Galunisertib
CAF-2 αSMA, NG2, PDGFRβ Physical Barrier, ImmunosuppressionDasatinib
OSCCCAF-N HA, MMP Invasion, Immunosuppression[58,59]Losartan, Nab-paclitaxel
CAF-D TGF-β MigrationGalunisertib
ColorectalCAF-A MMP2, αFAP, COL1A2 [60]αFAP therapy, Losartan, Nab-paclitaxel
CAF-B αSMA, PDGFA, TAGLN
PDACrCAFs PDPN, meflin Anti-tumorigenic[61,62]
myCAFs (pCAFs) PDPN, αSMAαSMA, TAGLN, TPM1, TPM2, POSTNProliferation, Migration, Invasion, Metastasis[63,64,65,66]Galunisertib, Losartan, Nab-paclitaxel
LRRC15PDPN, αSMA, LRRC15 Chemoresistance[66]
iCAFs (pCAFs) PDPN, IL-6, LIF, IL-11IL-6, IL-8, CXCL1, CXCL12, CFD, LMN, DPTMetastasis, Angiogenesis, Immunosuppression[63,64,65,66]Ruxolitinib
apCAFs (pCAFs) PDPN, COL1A2H2-Aa, H2-Ab1, CD74Immunosuppression[64,67]
BreastCAF-S1ecm-myCAFCD29, αFAP, PDGFRβ, FSP1, αSMA, cav1LRRC15, GBJ2Proliferation, Migration, Invasion, Metastasis, Immunosuppression[68,69,70,71]αFAP therapy (CAF-S1), Dasatinib (CAF-S1), Galunisertib (myCAF), Ruxolitinib (iCAF)
detox-iCAFADH1B, GPX3
IL-iCAFRGMA, SCARA5
TGFβ-myCAFCST1, TGFβ1
wound-myCAFSEMA3C, SFRP4
IFNγ-iCAFCCL19, CCL5
IFNαβ-myCAFIFIT3, IRF
acto-myCAFGGH, PLP2
CAF-S2
CAF-S3 CD29, FSP1, PDGFRβ Dasatinib
CAF-S4 CD29, FSP1, PDGFRβ, αSMA Proliferation, Migration, Invasion, MetastasisDasatinib
CD10/GPR77 CD10, GPR77 Proliferation, Migration, Chemoresistance[72]
vCAFs Cdh5, Pecam1, CD34, Notch3, Nr2f2, Epas1Angiogenesis[73]
dCAFs MFAP5, Scgr1, Sox9, Sox10
mCAFs Dcn, Lum, Fbln1, Smoc, Lox, Loxl1
Table
Table 2. Different mechanisms of pro- and anti-tumorigenic CAFs activities with the secretion associated.
Table 2. Different mechanisms of pro- and anti-tumorigenic CAFs activities with the secretion associated.
ActivityMechanismsProteins involvedRef.
Proliferation, SurvivalStimulation of proliferationTGF-β1, CXCL-12, FGF, POSTN, OPN, HGF, IL-6, IL-22[83,84,85,86,87,88,89,90]
Inhibition of apoptosisUpregulation of BCL-2 and MCL1, downregulation of Bax[83,84]
ChemoresistanceInhibition of apoptosisIL-6, IL-17A, PDGF, IGF, upregulation of MCL-1[91,92,93,94,95]
Stimulation of CSCsC5a, IL-6[72,94]
Inhibition of bioavailability, vascular collapseHA, collagen[96,97,98,99]
Ferroptosis, cell cycle inhibitionmiR-522, CmiR-98-5p[100,101]
Migration, Invasion, MetastasisStimulation of EMTTGF-β, IL-32, PDGF, FGF, HGF, C3a[102,103,104,105]
Stimulation of cytoskeleton (motility)TGF-β, upregulation of ARHGAP29[103,106]
ECM remodelingMMP2, MMP3, MMP9[59,104]
AngiogenesisRecruitment/Proliferation of ECs and pericytesVEGF, PDGF, CXCL-12, HGF, IL-6, IL-8[107,108,109,110,111]
Vascular mimicryTGF-β, CXCL-12, MMP2[112,113]
ImmunomodulationRecruitment/Proliferation of immune cellsIL-1β, CCL22, CXCL-12, CCL2, CXCL1, CXCL5, IL-8, PGE2[80,114,115]
Polarization of immune cellsIL-10, IL-12[116,117,118,119,120]
Immunotolerance (MDSC, Treg…)CCL17, CCL22, CCL2, CXCL-12, IL-6, IL-17, IL-10, PD-1, CTLA4[68,70,71,80,81,82]
Inhibition of cytotoxic cells (lymphocyte, NK cells…)TGF-β, CXCL1, IL-10, βig-h3, IL-6, IL-17[68,70,121,122,123,124,125]
Antigen presentingMHC-II, CD74[64,67,71]
Anti-tumorigenicInhibition of proliferationIL-6, TNF-α, TGF-β[126,127,128,129,130,131]
Inhibition of CSCs stimulationBMP4[132]
Inhibition of angiogenesisDownregulation of HGF, FGF, VEGF, IL-8[126,127,133]
Inhibition of Treg cellsDownregulation of HGF, IL-6, FGF, CXCL-12[126,127,133]
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Louault, K.; Li, R.-R.; DeClerck, Y.A. Cancer-Associated Fibroblasts: Understanding Their Heterogeneity. Cancers 2020, 12, 3108. https://doi.org/10.3390/cancers12113108

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Louault K, Li R-R, DeClerck YA. Cancer-Associated Fibroblasts: Understanding Their Heterogeneity. Cancers. 2020; 12(11):3108. https://doi.org/10.3390/cancers12113108

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Louault, Kévin, Rong-Rong Li, and Yves A. DeClerck. 2020. "Cancer-Associated Fibroblasts: Understanding Their Heterogeneity" Cancers 12, no. 11: 3108. https://doi.org/10.3390/cancers12113108

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Louault, K., Li, R. -R., & DeClerck, Y. A. (2020). Cancer-Associated Fibroblasts: Understanding Their Heterogeneity. Cancers, 12(11), 3108. https://doi.org/10.3390/cancers12113108

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