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Advances in targeting cancer-associated fibroblasts through single-cell spatial transcriptomic sequencing

Biomarker Research volume 12, Article number: 73 (2024) Cite this article

Abstract

Cancer-associated fibroblasts (CAFs) are the major components of the tumor microenvironment and are related to tumor proliferation, metastasis, relapse, and drug resistance. With the development of sequencing technologies, single-cell RNA sequencing has become a popular method for identifying CAFs in the tumor microenvironment. Whereas the drawbacks of CAFs, such as the lack of a spatial landscape, still exist, recent research has utilized spatial transcriptomics combined with single-cell RNA sequencing to address this issue. These multiomics analyses can resolve the single-cell resolution problem in spatial transcriptomics. In this review, we summarized the recent literature regarding the targeting of CAFs to address drug resistance, angiogenesis, metabolic reprogramming and metastasis in tumor tissue.

Background

With respect to tumor initiation, a considerable number of studies is associated with the “seed and soil” hypothesis proposed by Stephen Paget over a century ago [1]. The last two decades have seen a growing trend toward the tumor microenvironment, which is one of the most frequently noted factors in tumor development, proliferation, metastasis, and relapse.

There are many components of the tumor microenvironment, such as tumor infiltrating lymphocytes (TILs), natural killer cells, tumor infiltrating dendritic cells (TIDCs), tumor-associated macrophages (TAMs), tumor-associated neutrophils (TANs), cancer-associated fibroblasts (CAFs), myeloid-derived suppressor cells (MDSCs), distinct proangiogenic factors and immune checkpoint biomarkers [2]. Traditionally, CAFs have been thought to interact with the cancer cells, having tumor-promoting effects; however, accumulating evidence indicates that CAFs have the apparent tumor-suppressive functions [3, 4]. Moreover, among the whole subgroup of the tumor environment, CAFs account for almost 70% [5], and they can also participate in extracellular matrix remodeling, chemoresistance; radio-resistance; immune evasion and modulation; angiogenesis; and metabolism by secreting various of chemokines, exosomes, cytokines and other effector molecules [6,7,8].

Increased knowledge of their proportion, heterogeneity, and origin, among other information, at the individual cell level would contribute to a deeper understanding of CAFs. Like separating individual components of a salad, single-cell RNA sequencing (scRNA-seq) can dissociate whole tissues into individual cells [9, 10]. However, this technology does not provide spatial information or address cross-talk in the TME. Therefore, after the wave of single-cell analysis, spatial transcriptomics (ST) has become an important method in the last decade [9, 11]. In addition to overcoming the limitations of scRNA-seq, ST is better for mapping and exploring different functional regions and intercellular interactions in the TME at the two-dimensional level [12, 13]. With increasing throughput and scale, ST produces large amounts of RNA imaging data, and a newly developed computational framework, Bento, was published for the subcellular analysis of ST data [14]. Recently, whole-transcriptomic digital spatial profiling (DSP) revealed three multicellular colonies in PDAC, i.e., treatment enriched, squamoid/basaloid and classical colonies, providing promising therapeutic targets [15]. For colorectal cancer, combined with the ssGSEA algorithm, ST can be used to determine cell types such as dendritic cells, NK cells, monocytes, and epithelial cells in different regions [16]. In addition, according to an ST analysis, high expression of MMP14 has been shown to be associated with tumor progression, poor prognosis, and CAFs and TAMs in tumor tissue [17]. Moreover, ST results showed that CAFs induce glycoprotein nonmetastatic B (GPNMB), which promotes the invasion and migration of tumors in breast cancer [18]. Overall, the combined application of ST and scRNA-seq to explore CAFs allows not only for spatial distribution mapping but also for an assessment of cellular heterogeneity [19, 20]. (Fig. 1)

Fig. 1
figure 1

single cell RNA sequencing combined with spatial transcriptomics. Single cell sequencing could research tumor heterogeneity at cellular level, and spatial transcriptomics revels spatial information in tumor tissue. Single-cell spatial transcriptomic sequencing combined the merits of both. (created with biorender.com.)

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Fig. 2
figure 2

CAFs with angiogenesis through cytokine factors and ECM. A Upregulated by CHI3L1/IL-13Rα2 axes, CAFs promotes angiogenesis in IL-8. B Activated by IL-1/TNF, CAFs could stimulate TAK1-NFκΒ/AP1-MMP9 signaling which promotes tumor angiogenesis and invasion. C In some case, it is important for CAFs to secret angiogenesis factor via the autocrine of CXCL12. D In melanoma, miR-155-5p induces tumor angiogenesis and migration in CAFs through JAK2/STAT3 signaling pathway. E During ECM formation, myeloid cell upregulates TGFβ promoting angiogenesis in CAFs. F Reduced by ProAgio, CAFs decreases tumor angiogenesis and promotes apoptosis

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Although extensive research involving single-cell analysis has been carried out for the tumor environment, a complete picture with the comprehensive cellular information is lacking. Owing to the proteomic and epigenomic heterogeneity of the tumor environment, comprehensive information obtained through single-cell multiomics is important [21]. Recently, Cle´mence Henon et al. revealed that the EWSR1::WT1 transcription factor is associated with the prognosis of desmoplastic small round cell tumor patients and customized therapies via single-cell multiomics analysis [22]. Technologies based on genetics, transcriptomics and proteomics have expanded rapidly in recent years, and TME targets and tumor cellular biomarkers can be identified directly by advanced clinical therapy [23]. Through scRNA-seq, spatial transcriptomics, proteomics, Junpeng Fan et al. identified that in cervical squamous cell carcinoma, the MP6/7 score was associated with the immunotherapy response [24]. In addition, metabolic pathway related targets and metabolic enzymes can be utilized in advanced therapeutic strategies, while spatially resolved metabolomics methods can be used to identify genes in their native state [25, 26]. Whereas, single-cell multiomics studies have revealed different challenges, mainly in terms of insufficient sample sizes, a lack of validation in different cancer types [22, 24, 26, 27]. Overall, studies have indicated that multiomics analysis is more beneficial for obtaining a comprehensive understanding of cellular process than any single omics analysis is [28, 29].

The TME, as described above, is a key factors in drug resistance, immunotherapy targeting and tumor progression and metastasis. To date, a considerable number of single-cell multiomics studies of the TME have been published. Furthermore, many studies regarding CAFs, which are a hot topic of TME and cancer research, have been conducted [30].

CAFs with angiogenesis

As the hallmark of malignant tumors in solid tissue, many cell types play the significant roles in angiogenesis, such as lymphocytes, NK cells, pericytes, CAFs and TAMs [31]. CAFs secrete proangiogenic factors directly and produce ECM indirectly to regulate angiogenesis.

Proangiogenic factors

Secreted from CAFs, different kinds of cytokines, such as the CXCL family, FGF, WNT2, VEGF, and HGF, promote angiogenesis in solid tumors. Recently, studies have demonstrated that CXCL8(IL-8) is a proangiogenic chemokine in pancreatic cancer and TNBC, playing a role through HUVECs [32, 33]. In addition, CXCL12 is another important angiogenesis-promoting factor in lung cancer, prostate cancer and melanoma. CXCL12 expression is higher in healthy tissue (C-MSCs) than tumor tissue (T-MSCs) [34]. In FAP-positive tumor stromal cells, CXCL12 induced angiogenesis via the CXCL12-CXCR4 axis in melanoma and prostate cancer, findings that were authenticated separately [35, 36]. (Fig. 3C) Moreover, in prostate cancer, NIH-CXCL14 has been shown to stimulate angiogenesis [37].

Fig. 3
figure 3

CAFs with glycolysis reprogramming, amino acid reprogramming and lipid metabolism reprogramming. In glycolysis reprogramming, we have described five related signaling pathways between CAFs and tumor cells. ASPN, secreted from tumor cell and CAFs, induces glucose metabolism through HIF1α and invasion through CD44/Rac1 and TPA/MMP9 axis. Under the hypoxia, both PKM2 and ITGB4 promote Warburg effect in tumor cell and CAFs in different pathways. Besides, through BNIP3L gene and lncRNA H19, JUN increases CAFs lactate in breast cancer, as well as PFKFB3 promotes Warburg effect in oral cancer. In amino acid reprogramming, four signaling pathways have been summarized. In lung cancer, LINC01614 could promote SLC7A5 and SLC38A2 expression for glutamine in cancer cells. And in pancreatic cancer, secreting IL-6 and SDF-1α, CAFs regulates glutamine metabolism in tumor cell via Nrf2. Another signaling pathway indicates TGF-β/SMAD5/BCAT1 axis to regulate branched chain amino acids. In addition, miR-105 and MYC in CAFs activate each other for metabolic reprogramming. In lipid metabolism reprogramming, FASN, secreted from CAFs, reprograms lipid metabolism in CRC tumor cell. And HSPC111 also promotes lipid reprogramming in CRLM through CXCL5/CXCR2/ACLY signaling pathway

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As one of the proangiogenic factors in CAFs, FGF2 is a promising target for normalizing vessel tubes in lung cancer, breast cancer, melanoma and pituitary tumors [38,39,40,41]. In addition, some studies have indicated that FGF2 regulates angiogenesis through the JAK2/STAT3 signaling pathways in both lung cancer and melanoma [38, 42]. (Fig. 3D) In addition, another study demonstrated that FGF7 promoted angiogenesis in breast cancer cells and HUVECs via crosstalk between CAFs and tumor cells [41].

Like tumor proliferation and invasion, angiogenesis can be induced by ECM stiffness and degradation, and MMP-related pathways play significant roles in the degradation of the ECM around ECs to promote neovessel formation [43]. In addition, MMP11 expression is increased through different pathways in T-MSCs in lung cancer as well as in breast cancer via coculture with mononuclear inflammatory cells [34, 41]. In addition, high expression of MMP9 has been detected in breast cancer, having similar effects as those observed in oral squamous cell carcinoma, and regulates the stimulation of vascularization via the MAPK-AP1 and TAK1-RELA axes [44, 45]. (Fig. 3B)

Secreted from CAFs, both Il-6 and Il-8 are proangiogenic factors, and Il-6 induces proangiogenic effects via the IL-6/STAT3/NF‐κB positive feedback loop in breast cancer and is regulated by WNT2 in CRC [41, 46, 47]. In addition, studies have demonstrated that the Il-8(CXCL8)/CXCR2 axis is involved in tumorigenesis by promoting angiogenesis in metastasized pancreatic cancer and TNBC [32, 33, 48] (Fig. 3A).

As demonstrated by a considerable number of recent studies, vascular endothelial growth factor (VEGF) supports angiogenesis to promote tumor growth [39, 41, 49]. Herein, we summarized the related articles that address downstream VEGF effects, upstream VEGF effects and anti-VEGF effects. VEGF inhibits the expression of apoptotic cytokines and induces enzymes involved in ECM degradation [50]. However, exo-miRNAs promote proangiogenic factor in melanoma and lung cancer via miR-155-5p and by miR-210 via the JAK2/STAT3 signaling pathway, respectively [42, 51]. (Fig. 3D) In colon cancer, VEGFA expression is modulated by CHI3L1, similar to IL-8 secretion, and is altered by p53 status [52, 53]; however, its secretion can be reduced by eicosapentaenoic acid (EPA) during angiogenesis, similar to the ability of EPA to inhibit the secretion of IL-6 [54]. Research on anti-VEGF factors has focused primarily on bevacizumab, which acts against VEGF by neutralizing sEVs [55, 56].

Extracellular matrix (ECM)

Unlike proangiogenic factors, component proteins, such as proteoglycans, periostin, tenascin, fibronectin and collagen, have been shown to increase ECM stiffness and remodel the ECM [57]. Studies have demonstrated that both ATF4 and ProAgio are correlated with angiogenesis in melanoma, lung cancer and breast cancer via the expression of collagen I [58, 59]. (Fig. 3F) In addition, we also reported that tumor angiogenesis involves the TGFβ-fibronectin axis via ECM formation and tumor-fibroblast crosstalk in breast cancer [60, 61] (Fig. 3E).

CAFs with metabolic reprogramming

As the process of changing one cell fate to another, reprogramming affects in tumor progression, metastasis, proliferation and invasion in different cancers. In this review, we summarize advanced research in the following categories: glycolysis reprogramming, amino acid metabolism reprogramming and lipid metabolism reprogramming.

Glycolytic reprogramming

Aerobic glycolysis, also known as the Warburg effect, plays a major role in tumor glucose metabolism in digestive cancer, breast cancer, and lung cancer. Some studies have focused on the reverse Warburg effect in CAFs, and others have focused on lactate utilization in cancer cells [62,63,64,65].

Recently, studies have demonstrated that glycolytic reprogramming in CAFs is involved in tumor progression and heterogeneity in breast cancer via different modes, such as cancer cell-secreted exo-miR-105 promoting MYC expression, cancer cells overexpressing ITGB-4; and normal fibroblasts overexpressing HIF-1α [66,67,68]. In lung cancer, hypoxia-induced exosomal PKM2 regulates the Warburg effect in CAFs, and ROS, TGF-β and GFPT2 reprogram metabolism by increasing aerobic glycolysis [69,70,71]. In addition, we found that the MAPK and ERK1/2 signaling pathways are involved in glycolysis reprogramming in CAFs of oral cancer through H10/miR-675-5p/PFKFB3 and CAV-MCT4/MCT1 respectively [72, 73]. In ovarian cancer, LPA secreted from cancer cell induces aerobic glycolysis reprogramming via NOX1, ROS and HIF1α [74, 75].

In gastric cancer, the LDHA and ENO2 genes as well as ASPN, are related to the reprogramming of the Warburg effect and anaerobic glycolysis, respectively, in cancer cells [76]. In addition, normal fibroblasts reprogram glucose metabolism into aerobic glycolysis and secrete ROS and MCT4 in oral squamous cell carcinoma [77] (Fig. 4).

Fig. 4
figure 4

CAFs with metastasis in lung cancer, gastric cancer, colorectal cancer and breast cancer. In gastric cancer, CAFs promotes tumor cell metastasis through IL33/ST2L/SP1 and HGF/c-MET/STAT3 signaling pathways. In breast cancer, DDR2 and FAK are two therapy targets in tumor metastasis through miR-16/miR-148a and ITGB β1. In lung cancer, TGF-β1 promotes metastasis via SMAD2/3-HOTAIR axis and NFκΒ, which activated by miR-1247-3p, increase metastasis through IL-6/8. In colorectal cancer, secreted from CAFs, miR-92a increase tumor metastasis and drug resistance through FBXW7 and MOAP1. CAFs can also promotes metastasis via IL-6/8, which activated via RUNX2/ITGBL1/ NFκΒ axis. (created with biorender.com.)

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Amino acid metabolism reprogramming

As major metabolites, amino acids are essential for tumorigenesis and metastasis. Moreover, as a major amino acid, glutamine is essential for metabolic reprogramming [62, 64, 78]. Herein, we summarize recent studies of the reprogramming of stromal cells and cancer cells. In CAF-derived exosomes, LINC01614 inhibited LUAD growth and reprogrammed glutamine addiction in tumor cells by activating NF-κB to upregulate the expression of the glutamine transporters SLC38A2 and SLC7A5 [79]. In addition, other studies have indicated that CAFs regulate glutaminolysis in CRC and prostate cancer via distinct pathways, such as glutamine synthetase in CRC and Ras, which activates micropinocytosis, in prostate cancer [80, 81]. Additionally, in pancreatic cancer, stromal cells have been shown to regulate glutamine metabolic reprogramming in PDAC cells through the TGF-β/SMAD5 axis, which targets BCAT1, SDF-1a and IL-6 secretion activated by Nrf-2 respectively [82, 83].

However, resistance to glutamine deprivation in stromal cells has been demonstrated by p62-mediated polyubiquitination via upregulated ATF4 expression [84]. In addition, the glutamine metabolism has been shown to be reprogrammed by CAFs through the secretion of miR-105 from cancer cells, promoting tumor growth and metastasis in many solid cancers [68, 85] (Fig. 4).

Lipid metabolism reprogramming

Previous studies have rarely investigated the lipid metabolism of CAFs; however, recent studies have focused on the principal role of lipid metabolism reprogramming in tumorigenesis, metastasis and potential therapeutic targets [62, 64, 86].

With respect to lipid metabolism, most studies have focused on how lipid metabolic reprogramming affects CAFs. HSP111 reprograms the metabolism of CAFs and promotes CRLM by phosphorylating ACLY to increase H3K27 acetylation and the expression of components of the CXCL5-CXCR2 axis [87]. Additionally, in CRC, iCAFs are correlated with lipid metabolism, and FASN in CAFs promotes tumor migration by lipid metabolism reprogramming [16, 88]. In prostate cancer, the reprogramming of lipid metabolism and amplification of MTOCs have been shown to increase CAF plasticity [89].

However, few studies have investigated lipid metabolism in stromal cells and tumor cells. TNBC-derived CAFs can reprogram monocytes into lipid-associated macrophage (LAMs) via the CXCL12-CXCR4 axis, suppressing immune response such as T cell activation [90] (Fig. 4).

CAFs with metastasis

CAFs are the major stromal cells in tumor tissue, and their crosstalk with TAMs, TANs, epithelial cells and cancer cells regulates tumorigenesis, invasion, drug resistance and metastasis [91]. Next, we summarize studies of the association between CAFs and metastasis in different cancer types.

Gastric cancer

Secreting numerous cytokines in the TME, CAFs remodel the tumor stroma in gastric cancer, supporting tumor progression, angiogenesis and metastasis. Herein, we summarize recent studies on tumor cell metastasis and lymph node metastasis.

TNC and twist1 are regulators of many malignant tumors, such as ESCC and CRC, and a recent study revealed that their expression was related to lymph node metastasis in gastric cancer patients [92, 93]. Yang et al. also demonstrated that the expression of KLF5 was associated with lymph node metastasis via activation of the CCL5/CCR5 axis [92]. In addition, other studies have indicated that lymph node metastasis in gastric cancer is associated with the expression of CD9 and the downregulation of FGF9 expression in CAFs [94, 95].

Recently, CAFs were shown to promote the metastasis of gastric cancer via the TNF-α/IL-33/ST2L signaling pathway and the CAF-derived HGF and IL-11/MUC1 signaling pathways [96,97,98]. However, another study indicated that exo-miR-139 derived from CAFs inhibited the tumor progression and metastasis of gastric cancer by decreasing MMP11 expression, indicating that CAFs have bidirectional functions [99] (Fig. 5).

Fig. 5
figure 5

CAFs with drug resistance in promoting tumorigenesis and inhibiting tumorigenesis. Secreting PAI-1, CAFs promoting tumor proliferation and chemoresistance through increasing AKT/ERK and decreasing CASP-3/ROS. And targeting CCL5-Akt/STAT3 axis could reduces drug resistance and tumorigenesis

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Colorectal cancer

Colorectal cancer (CRC) is the world’s most lethal cancer worldwide, and colorectal metastasis (CRLM) is one of the awkward problems in CRC therapy.

A disintegrin and metalloproteinase (ADAM) and endoglin are two different factors expressed in CAFs that promote CRLM via ADAM10 levels in serum and endoglin-BMP9 axis signaling [100, 101]. In addition, the crosstalk between cancer cells and CAFs via TRAIL-BMP2 has been shown to maintain a feedback loop in a CRLM mouse model [102]. This crosstalk could lead to the development of promising treatments or serve as a predictor of CRC metastasis. The expression of exo-miR-92a-3p is related to CRLM through regulating downstream FBXW7 and MOAP1 expression in CAFs [103].

However, Ruixiao Li et al. have demonstrated that Jianpi Jiedu Recipe (JPJDR) could reduce CRLM through ITGBL1/TNFAIP3/ NF-κB signaling in CAFs [104] (Fig. 5).

Lung cancer

Lung metastasis is one of the main causes of lung cancer-related deaths worldwide, and lung cancer metastasis is also a key problem in tumor therapy and tumor relapse.

Regulated by miR-1247-3p, CAFs have been shown to induce CCL5 expression through the activation of the HIF1α/ZEB1 axis and the β1 integrin/NF-κB axis to promote lung metastasis in HCC [105, 106]. In addition, researchers have demonstrated that the TGF-β1/HOTAIR signaling pathway and the integrin α2β1/TGF-β axis were promote lung metastasis in patients with breast cancer and salivary adenoid cystic carcinoma, respectively [107, 108].

Other studies have demonstrated that several biomarkers and cytokines derived from CAFs, such as vimentin, FAPα, and HMGB1, are positively related to lung tumor metastasis [109,110,111]. However, Bin Xue et al. demonstrated that miR-200 expression is associated with lung cancer prognosis and metastasis via the induction of Notch activation in CAFs [112] (Fig. 5).

Breast cancer

As one of the most common malignant cancers in women, breast cancer is more common than lung cancer, colorectal cancer and thyroid carcinoma. Herein, we have summarize studies that address the promotion and inhibition of metastasis signaling in breast cancer.

Both the NLRP3/IL-1β axis and DDR2 have been shown to contribute to the cancer metastasis in CAFs in vivo and are promising therapeutic targets [113, 114]. In addition, exosomal miRNAs derived from CAFs, such as miR-500a-5p, miR-18b and miR-222, promote metastasis whereas miR-16 and miR-148a expression suppresses metastasis [115,116,117,118]. Other studies have revealed that the TGF-β1/HOTAIR and IL-3/integrin β3-p38 MAPK axes promote tumor metastasis [108, 119].

However, CAFs have bidirectional characteristics, i.e., promote tumorigenesis and inhibit tumor metastasis. Research has shown that p85α expression suppresses tumor metastasis via Wnt10b signaling, and that CCM3 secretion reduces metastasis through YAP/TAZ signaling [120, 121] (Fig. 5).

CAFs with drug resistance

Increasing evidence has shown that CAFs play a key role in drug resistance through signal transduction pathways, drug delivery and acceptance systems, and DNA damage repair. Drug resistance induced by CAFs can be found in many kinds of solid tumors, such as breast cancer, pancreatic cancer, and lung cancer. However, we will address how CAFs promote tumorigenesis through TGF, IL-6, CCL, PAI, NRG1 and some exosomes and inhibit tumorigenesis through CCL, TPL, Nav and GDC0449 [122,123,124,125].

Promoting tumorigenesis

As the bridge between growth factors and their corresponding receptors, TGFβ plays an important role in signaling pathways, e.g., the FOXO1/TGFβ1 signaling loop, IL1b/TGFβ-mediated crosstalk, the TGFβ1/SMAD3 signaling pathway, the TGF-β1/PI3K/AKT/mTOR pathway, and TGFβ accumulation [126,127,128,129,130]. In resistance to oxaliplatin, TGFβ signal transduction, an IL-1β antibody and a TGFBR1 inhibitor can drive TAK-mediated activation to decrease the JAK/STAT and PI3KCA/AKT pathways in CRC [127]. Furthermore, TGFβ1/SMAD3 activation, a fibrotic phenotype and nintedanib resistance were shown to be more strongly related to ADC than to SCC in lung carcinoma [128]. Moreover, in NSCLC, crosstalk activates the PI3K/AKT/mTOR pathway to induce the MDR by releasing TGF-β [129]. In another chemoresistance mechanism, the crosstalk between the tumor cells and CAFs promotes the activation and expression of FOXO1, which leads to TGFβ1 expression through autocrine/paracrine loops in ESCC. However, Yamei Chen et al. recently reported that ANXA1/FPR2 signaling could counteract the function of TGFβ in ESCC [123]. Recent research revealed TGFβ-myCAF signaling could be modulated by the EMILIN1 gene in IFNγ-iCAFs in breast cancer [125].

Many studies have demonstrated that IL-6-specific functions in CAFs involve the IL-6/CXCR7 axis and the IL-6/Jak1/STAT3 axis, which play roles in the immune response, EMT and cancer cell migration [131,132,133,134]. For DNA repair in ESCC, CXCR7 expression is increased by IL6 to protect cells from apoptosis via the activator of transcription 3/NF-κB pathway [131]. In addition, the monoclonal anti-IL-6R antibody tocilizumab increases apoptosis in cancer cells through the IL-6/Jak1/STAT3 axis, promoting tumorigenesis, invasion and antiapoptotic proteins expression in gastric cancer [132]. According to a recent study, in gastric cancer, in combination with M2 macrophages, eCAFs promote tumor invasion and decrease survival through the expression of periostin [122]. Because of anti-PD-L1 resistance in hepatocellular carcinoma, CAFs expressing high levels of IL-6 support the disruption of tumor-infiltrating T-cell function, resulting in the generation of immunosuppressive cells in the TME [133].

5-Fluorouracil and paclitaxel resistance can be induced by Snail-overexpressing fibroblasts, which secrete CCL1 via the TGFβ/NF-κB signaling pathway [135]. PAI-1, which is produced by inflammatory cells and CAFs, is involved in resistance in various tumor tissues. Research has demonstrated that AKT and ERK1/2 signaling is activated by PAI-1 and impedes the accumulation of ROS and caspase-3 activity during cisplatin resistance in ESCC [136] (Fig. 3). In addition, PAI-1 increases the expression of α-SMA, which is expressed in MFs, and reduces chemoresistance in lung cancer [137]. Recent studies have supported the resistance to antiandrogens in the EGFR/ERK pathway through miR-146a-5p and the NRG1/HER3 axis in prostate cancer; however, obstructing NRG1/HER3 and inhibiting migration and growth strengthens ADCC in NRG1-positive pancreatic tumors and CAFs [138, 139]. In addition, studies have shown that in pancreatic cancer, the SDF-1/CXCR4/SATB-1 axis induces tumor progression and GEM resistance by building a positive feedback loop [140].

For pancreatic cancer, the inhibitor of exosome release GW4869 suppresses epithelial cell proliferation and GEM resistance, as exosomes increase Snail expression, and Snail expression is correlated with the promotion of drug resistance in lung cancer [141, 142]. In addition, miR-106b, which targets to TP53INP1 and increases GEM resistance in pancreatic cancer, is released by exosomes from CAFs to tumor cells [143]. Another study reported that CAFs secrete exosomes decorated with miRNA-130a via PUM2 and inhibit apoptosis via the PKM2/BCL2 axis to promote cisplatin resistance in NSCLC [70, 144]. In CRC, exosomal miR-181d-5p, the direct target of NCALD, is affected by METTL3 via DGCR8 in CAFs, whereas the sensitivity of CRC to 5FU is affected by NCALD [145]. Recently, Arthur Dondi et al. revealed that lung cancer metastasis occurs through miR-1290/MT1G/AKT signaling in NFs [146].

Inhibiting tumorigenesis

Recently, an increasing number of nanoparticle technologies that enhance therapeutic efficacy, inhibit signaling pathways, and reduce toxic side effects, have been developed for cancer treatment [147,148,149,150]. In gastric cancer, PSN38@TPL-Nsa nanoparticles have been shown to inhibit tumor progression, and improve antimetastatic efficacy because TPL is a suitable stromal reprogramming inducer [147]. In addition, nano-doxorubicin has been shown to improve drug efficacy and reduce cardiotoxicity in pancreatic cancer patients [150]. CCL plays crucial roles in chemoresistance, such as 5-fluorouracil resistance, paclitaxel resistance, and cisplatin resistance, in CRC, HNSCC, ovarian cancer and melanoma [151,152,153]. In addition, cisplatin resistance in ovarian cancer and HNSCC has been shown to occur via the regulation of the STAT3 and PI3K/Akt signaling pathways as well as sensitization effects of CAFs, respectively [151, 153] (Fig. 2). In addition, a recent study reported that EMT was increased by miR-146a-5p through the modulation castration resistance via the EGFR/ERK pathway [154] (Table 1).

Table 1 CAFs with drug resistance in different cancer types
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Conclusion

To date, many studies have focused on components of the TME, such as CAFs, the ECM, and TAMs, rather than on tumor cells. Herein, we summarized the most recent studies regarding CAF-targeting therapy. Recently, we revealed cross-talk among miscellaneous cells and the spatial landscape in CRC, PDAC, BC. These findings have significant implications for comprehensively understanding the crosstalk between CAFs and cancer cells, the macroscopic spatial structure of CAFs and therapeutic targets in tumor tissue. Drug resistance, angiogenesis, metabolic reprogramming and tumor metastasis are four hallmarks of cancer. Findings thus far have identified promising therapeutic targets that should be developed in future studies. Taken together, more studies involving single-cell spatial transcriptomics sequencing should be conducted to obtain further knowledge of tumor progression, metastasis, drug resistance, angiogenesis, and metabolic reprogramming.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

CAF:

Cancer associated fibroblast

TILs:

Tumor infiltrating lymphocytes

TIDCs:

Tumor infiltrating dendritic cells

TAMs:

Tumor associated macrophages

TANs:

Tumor associated neutrophils

MDSCs:

Myeloid derived suppressor cells

ST:

Spatial transcriptomics

DSP:

Digital spatial profiling

PDAC:

Pancreatic ductal adenocarcinoma

GSEA:

Gene set enrichment analysis

NL cell:

Natural killer cell

MMP:

Matrix metalloproteinase

GPNMB:

Glycoprotein nonmetastatic B

TME:

Tumor microenvironment

TGF:

Transforming growth factor

IL:

Interleukin

CCL:

C-C motif chemokine ligand

PAI:

Plasminogen activator inhibitor

NRG:

Neuregulin

TPL:

Triptolide

FOXO:

Forkhead box protein

SMAD:

The Caenorhabditis elegans SMA and MAD family

PI3K:

Phosphoinositide 3-kinases

mTOR:

the mammalian target of rapamycin

AKT:

Protein kinase B

ADC:

Lung adenocarcinoma

SCC:

Lung squamous cell carcinoma

MDR:

MultiDrug Resistance

ESCC:

Esophageal squamous-cell carcinoma

CXCR7:

C-X-C Motif Chemokine Receptor 7

JAK1:

Janus kinase 1

STAT:

Signal Transducer and Activator of Transcription

NF-κB:

Nuclear Factor kappa B

ROS:

Reactive oxygen species

EGFR:

Epidermal growth factor receptor

ERK:

Extracellular-regulated kinase

HER3:

Human epidermal growth factor receptor 3

SDF-1:

Stromal cell-derived factor-1

SATB-1:

Special AT-rich binding protein

GEM:

Gemcitabine

TP53INP1:

Tumor protein 53-induced nuclear protein 1

PUM2:

PUMILIO2

PKM2:

The M2 isoform of pyruvate kinase

BCL2:

B-cell lymphoma-2

NSCLC:

Non-small-cell lung cancer

CRC:

Colorectal cancer

NCALD:

Neurocalcinδ

METTL3:

N6‑methyladenosine (m6A) methyltransferase like 3

DGCR8:

DiGeorge Syndrome Critical Region 8

5-FU:

5-Fluorouracil

PSN38@TPL-nsa:

SN38 prodrug polymeric micelles@ triptolide-naphthalene sulfonamide

EMT:

Epithelial–mesenchymal transition

ECM:

Extracellular matrix

TNBC:

Triple-negative subtype of breast cancer

FGF:

Fibroblast growth factor

VEGF:

Vascular endothelial growth factor

HGF:

Hepatocyte growth factor

HUVEC:

Human umbilical vein endothelial cells

MSC:

Mesenchymal stem cells

MMP:

Matrix metalloproteinases

EPA:

Eicosapentaenoic acid

ATF4:

Activating transcription factor 4

sEV:

Small extracellular vesicles

ITGB4:

Integrin beta 4

GFPT2:

Glutamine-fructose-6-phosphate transaminase 2

MAPK:

Mitogen-activated protein kinases

PFKFB3:

6-phosphofructo-2-kinase/fructose-2,6biphosphatase 3

CAV1:

Caveolin1

MCT:

Monocarboxylate transporter

LPA:

Lysophosphatidic acid

HIF 1α:

Hypoxia inducible factor 1α

LDHA:

Lactate dehydrogenase A

ASPN:

Asporin

LUAD:

Lung adenocarcinoma

SDF-1:

Stromal-derived factor-1

CRLM:

Colorectal liver metastases

ACLY:

ATP-citrate lyase

MTOC:

Microtubule-organizing centers

ADAM:

A disintegrin and metalloproteinase

TRAIL:

TNF-related apoptosis-inducing ligand

BMP:

Bone morphogenetic proteins

ITGBL 1:

Integrin beta- like 1

JPJDR:

Jianpi Jiedu Recipe

TNFAIP3:

TNF alpha-induced protein 3

ZEB1:

Zinc finger enhancer-binding protein 1

HOTAIR:

HOX transcript antisense RNA

HMGB1:

High mobility group box 1

References

  1. Ishii G, Ochiai A, Neri S. Phenotypic and functional heterogeneity of cancer-associated fibroblast within the tumor microenvironment. Adv Drug Deliv Rev. 2016;99(Pt B):186–96.

    Article  CAS  PubMed  Google Scholar 

  2. Nascimento C, Ferreira F. Tumor microenvironment of human breast cancer, and feline mammary carcinoma as a potential study model. Biochim et Biophys acta Reviews cancer. 2021;1876(1):188587.

    Article  CAS  Google Scholar 

  3. Huang H, Brekken RA. Recent advances in understanding cancer-associated fibroblasts in pancreatic cancer. Am J Physiol Cell Physiol. 2020;319(2):C233–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Biffi G, Tuveson DA. Diversity and Biology of Cancer-Associated fibroblasts. Physiol Rev. 2021;101(1):147–76.

    Article  CAS  PubMed  Google Scholar 

  5. Vicent S, Sayles LC, Vaka D, Khatri P, Gevaert O, Chen R, et al. Cross-species functional analysis of cancer-associated fibroblasts identifies a critical role for CLCF1 and IL-6 in non-small cell lung cancer in vivo. Cancer Res. 2012;72(22):5744–56.

    Article  CAS  PubMed  Google Scholar 

  6. Rimal R, Desai P, Daware R, Hosseinnejad A, Prakash J, Lammers T, et al. Cancer-associated fibroblasts: origin, function, imaging, and therapeutic targeting. Adv Drug Deliv Rev. 2022;189:114504.

    Article  CAS  PubMed  Google Scholar 

  7. Zhuravlev F. Theranostic Radiopharmaceuticals Targeting Cancer-Associated fibroblasts. Curr Radiopharmaceuticals. 2021;14(4):374–93.

    Article  CAS  Google Scholar 

  8. Mao X, Xu J, Wang W, Liang C, Hua J, Liu J, et al. Crosstalk between cancer-associated fibroblasts and immune cells in the tumor microenvironment: new findings and future perspectives. Mol Cancer. 2021;20(1):131.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Marx V. Method of the year: spatially resolved transcriptomics. Nat Methods. 2021;18(1):9–14.

    Article  CAS  PubMed  Google Scholar 

  10. Jovic D, Liang X, Zeng H, Lin L, Xu F, Luo Y. Single-cell RNA sequencing technologies and applications: a brief overview. Clin Translational Med. 2022;12(3):e694.

    Article  CAS  Google Scholar 

  11. Moses L, Pachter L. Museum of spatial transcriptomics. Nat Methods. 2022;19(5):534–46.

    Article  CAS  PubMed  Google Scholar 

  12. Guo W, Zhou B, Yang Z, Liu X, Huai Q, Guo L, et al. Integrating microarray-based spatial transcriptomics and single-cell RNA-sequencing reveals tissue architecture in esophageal squamous cell carcinoma. EBioMedicine. 2022;84:104281.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Shi ZD, Sun Z, Zhu ZB, Liu X, Chen JZ, Hao L, et al. Integrated single-cell and spatial transcriptomic profiling reveals higher intratumour heterogeneity and epithelial-fibroblast interactions in recurrent bladder cancer. Clin Translational Med. 2023;13(7):e1338.

    Article  CAS  Google Scholar 

  14. Mah CK, Ahmed N, Lam D, Monell A, Kern C, Han Y et al. Bento: a toolkit for subcellular analysis of spatial transcriptomics data. bioRxiv. 2022.

  15. Hwang WL, Jagadeesh KA, Guo JA, Hoffman HI, Yadollahpour P, Reeves JW, et al. Single-nucleus and spatial transcriptome profiling of pancreatic cancer identifies multicellular dynamics associated with neoadjuvant treatment. Nat Genet. 2022;54(8):1178–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Peng Z, Ye M, Ding H, Feng Z, Hu K. Spatial transcriptomics atlas reveals the crosstalk between cancer-associated fibroblasts and tumor microenvironment components in colorectal cancer. J Translational Med. 2022;20(1):302.

    Article  CAS  Google Scholar 

  17. Makutani Y, Kawakami H, Tsujikawa T, Yoshimura K, Chiba Y, Ito A, et al. Contribution of MMP14-expressing cancer-associated fibroblasts in the tumor immune microenvironment to progression of colorectal cancer. Front Oncol. 2022;12:956270.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Truong DD, Kratz A, Park JG, Barrientos ES, Saini H, Nguyen T, et al. A human organotypic microfluidic tumor model permits investigation of the interplay between patient-derived fibroblasts and breast Cancer cells. Cancer Res. 2019;79(12):3139–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Ma C, Yang C, Peng A, Sun T, Ji X, Mi J, et al. Pan-cancer spatially resolved single-cell analysis reveals the crosstalk between cancer-associated fibroblasts and tumor microenvironment. Mol Cancer. 2023;22(1):170.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Ferri-Borgogno S, Zhu Y, Sheng J, Burks JK, Gomez JA, Wong KK, et al. Spatial transcriptomics depict ligand-receptor cross-talk heterogeneity at the Tumor-Stroma Interface in Long-Term Ovarian Cancer survivors. Cancer Res. 2023;83(9):1503–16.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Ren X, Kang B, Zhang Z. Understanding tumor ecosystems by single-cell sequencing: promises and limitations. Genome Biol. 2018;19(1):211.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Henon C, Vibert J, Eychenne T, Gruel N, Colmet-Daage L, Ngo C, et al. Single-cell multiomics profiling reveals heterogeneous transcriptional programs and microenvironment in DSRCTs. Cell Rep Med. 2024;5(6):101582.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Asleh K, Riaz N, Nielsen TO. Heterogeneity of triple negative breast cancer: current advances in subtyping and treatment implications. J Exp Clin Cancer Res. 2022;41(1):265.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Fan J, Lu F, Qin T, Peng W, Zhuang X, Li Y, et al. Multiomic analysis of cervical squamous cell carcinoma identifies cellular ecosystems with biological and clinical relevance. Nat Genet. 2023;55(12):2175–88.

    Article  CAS  PubMed  Google Scholar 

  25. Sun C, Li T, Song X, Huang L, Zang Q, Xu J, et al. Spatially resolved metabolomics to discover tumor-associated metabolic alterations. Proc Natl Acad Sci USA. 2019;116(1):52–7.

    Article  CAS  PubMed  Google Scholar 

  26. Zhou PY, Zhou C, Gan W, Tang Z, Sun BY, Huang JL, et al. Single-cell and spatial architecture of primary liver cancer. Commun Biology. 2023;6(1):1181.

    Article  CAS  Google Scholar 

  27. Zhang G, Ji P, Xia P, Song H, Guo Z, Hu X, et al. Identification and targeting of cancer-associated fibroblast signature genes for prognosis and therapy in cutaneous melanoma. Comput Biol Med. 2023;167:107597.

    Article  CAS  PubMed  Google Scholar 

  28. Lee J, Hyeon DY, Hwang D. Single-cell multiomics: technologies and data analysis methods. Exp Mol Med. 2020;52(9):1428–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Yu X, Liu R, Gao W, Wang X, Zhang Y. Single-cell omics traces the heterogeneity of prostate cancer cells and the tumor microenvironment. Cell Mol Biol Lett. 2023;28(1):38.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Dzobo K, Dandara C. Architecture of Cancer-Associated fibroblasts in Tumor Microenvironment: Mapping their origins, heterogeneity, and role in Cancer Therapy Resistance. OMICS. 2020;24(6):314–39.

    Article  CAS  PubMed  Google Scholar 

  31. De Palma M, Biziato D, Petrova TV. Microenvironmental regulation of tumour angiogenesis. Nat Rev Cancer. 2017;17(8):457–74.

    Article  PubMed  Google Scholar 

  32. Liubomirski Y, Lerrer S, Meshel T, Rubinstein-Achiasaf L, Morein D, Wiemann S, et al. Tumor-stroma-inflammation networks promote pro-metastatic chemokines and aggressiveness characteristics in Triple-negative breast Cancer. Front Immunol. 2019;10:757.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Pausch TM, Aue E, Wirsik NM, Freire Valls A, Shen Y, Radhakrishnan P, et al. Metastasis-associated fibroblasts promote angiogenesis in metastasized pancreatic cancer via the CXCL8 and the CCL2 axes. Sci Rep. 2020;10(1):5420.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Arena S, Salati M, Sorgentoni G, Barbisan F, Orciani M. Characterization of tumor-derived mesenchymal stem cells potentially differentiating into cancer-associated fibroblasts in lung cancer. Clin Translational Oncology: Official Publication Federation Span Oncol Soc Natl Cancer Inst Mexico. 2018;20(12):1582–91.

    Article  CAS  Google Scholar 

  35. Lang J, Zhao X, Qi Y, Zhang Y, Han X, Ding Y, et al. Reshaping prostate Tumor Microenvironment to suppress Metastasis via Cancer-Associated Fibroblast inactivation with Peptide-Assembly-Based Nanosystem. ACS Nano. 2019;13(11):12357–71.

    Article  CAS  PubMed  Google Scholar 

  36. Sorrentino C, Miele L, Porta A, Pinto A, Morello S. Activation of the A2B adenosine receptor in B16 melanomas induces CXCL12 expression in FAP-positive tumor stromal cells, enhancing tumor progression. Oncotarget. 2016;7(39):64274–88.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Augsten M, Hägglöf C, Olsson E, Stolz C, Tsagozis P, Levchenko T, et al. CXCL14 is an autocrine growth factor for fibroblasts and acts as a multi-modal stimulator of prostate tumor growth. Proc Natl Acad Sci USA. 2009;106(9):3414–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Nakamura Y. Multiple therapeutic applications of RBM-007, an Anti-FGF2 aptamer. Cells. 2021;10(7).

  39. Marques P, Barry S, Carlsen E, Collier D, Ronaldson A, Awad S, et al. Pituitary tumour fibroblast-derived cytokines influence tumour aggressiveness. Endocrine-related Cancer. 2019;26(12):853–65.

    Article  CAS  PubMed  Google Scholar 

  40. Ben Baruch B, Mantsur E, Franco-Barraza J, Blacher E, Cukierman E, Stein R. CD38 in cancer-associated fibroblasts promotes pro-tumoral activity. Lab Invest. 2020;100(12):1517–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Eiro N, González L, Martínez-Ordoñez A, Fernandez-Garcia B, González LO, Cid S, et al. Cancer-associated fibroblasts affect breast cancer cell gene expression, invasion and angiogenesis. Cell Oncol (Dordrecht). 2018;41(4):369–78.

    Article  CAS  Google Scholar 

  42. Zhou X, Yan T, Huang C, Xu Z, Wang L, Jiang E, et al. Melanoma cell-secreted exosomal mir-155-5p induce proangiogenic switch of cancer-associated fibroblasts via SOCS1/JAK2/STAT3 signaling pathway. J Exp Clin Cancer Res. 2018;37(1):242.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Najafi M, Farhood B, Mortezaee K. Extracellular matrix (ECM) stiffness and degradation as cancer drivers. J Cell Biochem. 2019;120(3):2782–90.

    Article  CAS  PubMed  Google Scholar 

  44. Limoge M, Safina A, Beattie A, Kapus L, Truskinovsky AM, Bakin AV. Tumor-fibroblast interactions stimulate tumor vascularization by enhancing cytokine-driven production of MMP9 by tumor cells. Oncotarget. 2017;8(22):35592–608.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Lin NN, Wang P, Zhao D, Zhang FJ, Yang K, Chen R. Significance of oral cancer-associated fibroblasts in angiogenesis, lymphangiogenesis, and tumor invasion in oral squamous cell carcinoma. J oral Pathol Medicine: Official Publication Int Association Oral Pathologists Am Acad Oral Pathol. 2017;46(1):21–30.

    Article  CAS  Google Scholar 

  46. Unterleuthner D, Neuhold P, Schwarz K, Janker L, Neuditschko B, Nivarthi H, et al. Cancer-associated fibroblast-derived WNT2 increases tumor angiogenesis in colon cancer. Angiogenesis. 2020;23(2):159–77.

    Article  CAS  PubMed  Google Scholar 

  47. Al-Harbi B, Aboussekhra A. Cucurbitacin I (JSI-124)-dependent inhibition of STAT3 permanently suppresses the pro-carcinogenic effects of active breast cancer-associated fibroblasts. Mol Carcinog. 2021;60(4):242–51.

    Article  CAS  PubMed  Google Scholar 

  48. Cohen N, Shani O, Raz Y, Sharon Y, Hoffman D, Abramovitz L, et al. Fibroblasts drive an immunosuppressive and growth-promoting microenvironment in breast cancer via secretion of chitinase 3-like 1. Oncogene. 2017;36(31):4457–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Pape J, Magdeldin T, Stamati K, Nyga A, Loizidou M, Emberton M, et al. Cancer-associated fibroblasts mediate cancer progression and remodel the tumouroid stroma. Br J Cancer. 2020;123(7):1178–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Salvatore V, Teti G, Focaroli S, Mazzotti MC, Mazzotti A, Falconi M. The tumor microenvironment promotes cancer progression and cell migration. Oncotarget. 2017;8(6):9608–16.

    Article  PubMed  Google Scholar 

  51. Fan J, Xu G, Chang Z, Zhu L, Yao J. miR-210 transferred by lung cancer cell-derived exosomes may act as proangiogenic factor in cancer-associated fibroblasts by modulating JAK2/STAT3 pathway. Clinical science (London, England: 1979). 2020;134(7):807 – 25.

  52. Watanabe K, Shiga K, Maeda A, Harata S, Yanagita T, Suzuki T et al. Chitinase 3-like 1 secreted from cancer-associated fibroblasts promotes tumor angiogenesis via interleukin-8 secretion in colorectal cancer. Int J Oncol. 2022;60(1).

  53. Hayashi Y, Tsujii M, Kodama T, Akasaka T, Kondo J, Hikita H, et al. p53 functional deficiency in human colon cancer cells promotes fibroblast-mediated angiogenesis and tumor growth. Carcinogenesis. 2016;37(10):972–84.

    Article  CAS  PubMed  Google Scholar 

  54. Ando N, Hara M, Shiga K, Yanagita T, Takasu K, Nakai N, et al. Eicosapentaenoic acid suppresses angiogenesis via reducing secretion of IL–6 and VEGF from colon cancer–associated fibroblasts. Oncol Rep. 2019;42(1):339–49.

    CAS  PubMed  Google Scholar 

  55. Li J, Liu X, Zang S, Zhou J, Zhang F, Sun B, et al. Small extracellular vesicle-bound vascular endothelial growth factor secreted by carcinoma-associated fibroblasts promotes angiogenesis in a bevacizumab-resistant manner. Cancer Lett. 2020;492:71–83.

    Article  CAS  PubMed  Google Scholar 

  56. Shen H, Yu X, Yang F, Zhang Z, Shen J, Sun J, et al. Reprogramming of normal fibroblasts into Cancer-Associated fibroblasts by miRNAs-Mediated CCL2/VEGFA signaling. PLoS Genet. 2016;12(8):e1006244.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Kobayashi H, Enomoto A, Woods SL, Burt AD, Takahashi M, Worthley DL. Cancer-associated fibroblasts in gastrointestinal cancer. Nat Reviews Gastroenterol Hepatol. 2019;16(5):282–95.

    Article  Google Scholar 

  58. Verginadis II, Avgousti H, Monslow J, Skoufos G, Chinga F, Kim K, et al. A stromal Integrated stress response activates perivascular cancer-associated fibroblasts to drive angiogenesis and tumour progression. Nat Cell Biol. 2022;24(6):940–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Sharma M, Turaga RC, Yuan Y, Satyanarayana G, Mishra F, Bian Z et al. Simultaneously targeting cancer-associated fibroblasts and angiogenic vessel as a treatment for TNBC. J Exp Med. 2021;218(4).

  60. Vasiukov G, Novitskaya T, Zijlstra A, Owens P, Ye F, Zhao Z, et al. Myeloid cell-derived TGFβ signaling regulates ECM deposition in Mammary Carcinoma via Adenosine-Dependent mechanisms. Cancer Res. 2020;80(12):2628–38.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Zonneville J, Safina A, Truskinovsky AM, Arteaga CL, Bakin AV. TGF-β signaling promotes tumor vasculature by enhancing the pericyte-endothelium association. BMC Cancer. 2018;18(1):670.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Li Z, Sun C, Qin Z. Metabolic reprogramming of cancer-associated fibroblasts and its effect on cancer cell reprogramming. Theranostics. 2021;11(17):8322–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Wu D, Zhuo L, Wang X. Metabolic reprogramming of carcinoma-associated fibroblasts and its impact on metabolic heterogeneity of tumors. Semin Cell Dev Biol. 2017;64:125–31.

    Article  CAS  PubMed  Google Scholar 

  64. Zhu Y, Li X, Wang L, Hong X, Yang J. Metabolic reprogramming and crosstalk of cancer-related fibroblasts and immune cells in the tumor microenvironment. Front Endocrinol. 2022;13:988295.

    Article  Google Scholar 

  65. Brown TP, Ganapathy V. Lactate/GPR81 signaling and proton motive force in cancer: role in angiogenesis, immune escape, nutrition, and Warburg phenomenon. Pharmacol Ther. 2020;206:107451.

    Article  CAS  PubMed  Google Scholar 

  66. Sung JS, Kang CW, Kang S, Jang Y, Chae YC, Kim BG, et al. ITGB4-mediated metabolic reprogramming of cancer-associated fibroblasts. Oncogene. 2020;39(3):664–76.

    Article  CAS  PubMed  Google Scholar 

  67. Becker LM, O’Connell JT, Vo AP, Cain MP, Tampe D, Bizarro L, et al. Epigenetic reprogramming of Cancer-Associated fibroblasts deregulates glucose metabolism and facilitates progression of breast Cancer. Cell Rep. 2020;31(9):107701.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Yan W, Wu X, Zhou W, Fong MY, Cao M, Liu J, et al. Cancer-cell-secreted exosomal miR-105 promotes tumour growth through the MYC-dependent metabolic reprogramming of stromal cells. Nat Cell Biol. 2018;20(5):597–609.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Cruz-Bermúdez A, Laza-Briviesca R, Vicente-Blanco RJ, García-Grande A, Coronado MJ, Laine-Menéndez S, et al. Cancer-associated fibroblasts modify lung cancer metabolism involving ROS and TGF-β signaling. Free Radic Biol Med. 2019;130:163–73.

    Article  PubMed  Google Scholar 

  70. Wang D, Zhao C, Xu F, Zhang A, Jin M, Zhang K, et al. Cisplatin-resistant NSCLC cells induced by hypoxia transmit resistance to sensitive cells through exosomal PKM2. Theranostics. 2021;11(6):2860–75.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Zhang W, Bouchard G, Yu A, Shafiq M, Jamali M, Shrager JB, et al. GFPT2-Expressing Cancer-Associated fibroblasts mediate metabolic reprogramming in human lung adenocarcinoma. Cancer Res. 2018;78(13):3445–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Yang J, Shi X, Yang M, Luo J, Gao Q, Wang X, et al. Glycolysis reprogramming in cancer-associated fibroblasts promotes the growth of oral cancer through the lncRNA H19/miR-675-5p/PFKFB3 signaling pathway. Int J Oral Sci. 2021;13(1):12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Jiang E, Xu Z, Wang M, Yan T, Huang C, Zhou X, et al. Tumoral microvesicle-activated glycometabolic reprogramming in fibroblasts promotes the progression of oral squamous cell carcinoma. FASEB Journal: Official Publication Federation Am Soc Experimental Biology. 2019;33(4):5690–703.

    Article  CAS  Google Scholar 

  74. Eisenberg L, Eisenberg-Bord M, Eisenberg-Lerner A, Sagi-Eisenberg R. Metabolic alterations in the tumor microenvironment and their role in oncogenesis. Cancer Lett. 2020;484:65–71.

    Article  CAS  PubMed  Google Scholar 

  75. Radhakrishnan R, Ha JH, Jayaraman M, Liu J, Moxley KM, Isidoro C, et al. Ovarian cancer cell-derived lysophosphatidic acid induces glycolytic shift and cancer-associated fibroblast-phenotype in normal and peritumoral fibroblasts. Cancer Lett. 2019;442:464–74.

    Article  CAS  PubMed  Google Scholar 

  76. Sasaki Y, Takagane K, Konno T, Itoh G, Kuriyama S, Yanagihara K, et al. Expression of asporin reprograms cancer cells to acquire resistance to oxidative stress. Cancer Sci. 2021;112(3):1251–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Zhang Z, Gao Z, Rajthala S, Sapkota D, Dongre H, Parajuli H, et al. Metabolic reprogramming of normal oral fibroblasts correlated with increased glycolytic metabolism of oral squamous cell carcinoma and precedes their activation into carcinoma associated fibroblasts. Cell Mol Life Sci. 2020;77(6):1115–33.

    Article  CAS  PubMed  Google Scholar 

  78. Vettore L, Westbrook RL, Tennant DA. New aspects of amino acid metabolism in cancer. Br J Cancer. 2020;122(2):150–6.

    Article  CAS  PubMed  Google Scholar 

  79. Liu T, Han C, Fang P, Ma Z, Wang X, Chen H, et al. Cancer-associated fibroblast-specific lncRNA LINC01614 enhances glutamine uptake in lung adenocarcinoma. J Hematol Oncol. 2022;15(1):141.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Wang J, Delfarah A, Gelbach PE, Fong E, Macklin P, Mumenthaler SM, et al. Elucidating tumor-stromal metabolic crosstalk in colorectal cancer through integration of constraint-based models and LC-MS metabolomics. Metab Eng. 2022;69:175–87.

    Article  CAS  PubMed  Google Scholar 

  81. Mishra R, Haldar S, Suchanti S, Bhowmick NA. Epigenetic changes in fibroblasts drive cancer metabolism and differentiation. Endocrine-related Cancer. 2019;26(12):R673–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Wu YS, Looi CY, Subramaniam KS, Masamune A, Chung I. Soluble factors from stellate cells induce pancreatic cancer cell proliferation via Nrf2-activated metabolic reprogramming and ROS detoxification. Oncotarget. 2016;7(24):36719–32.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Zhu Z, Achreja A, Meurs N, Animasahun O, Owen S, Mittal A, et al. Tumour-reprogrammed stromal BCAT1 fuels branched-chain ketoacid dependency in stromal-rich PDAC tumours. Nat Metabolism. 2020;2(8):775–92.

    Article  CAS  Google Scholar 

  84. Linares JF, Cordes T, Duran A, Reina-Campos M, Valencia T, Ahn CS, et al. ATF4-Induced Metabolic Reprograming is a synthetic vulnerability of the p62-Deficient tumor stroma. Cell Metab. 2017;26(6):817–e296.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Yang L, Achreja A, Yeung TL, Mangala LS, Jiang D, Han C, et al. Targeting stromal glutamine synthetase in Tumors disrupts Tumor Microenvironment-Regulated Cancer Cell Growth. Cell Metab. 2016;24(5):685–700.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Koundouros N, Poulogiannis G. Reprogramming of fatty acid metabolism in cancer. Br J Cancer. 2020;122(1):4–22.

    Article  CAS  PubMed  Google Scholar 

  87. Zhang C, Wang XY, Zhang P, He TC, Han JH, Zhang R, et al. Cancer-derived exosomal HSPC111 promotes colorectal cancer liver metastasis by reprogramming lipid metabolism in cancer-associated fibroblasts. Cell Death Dis. 2022;13(1):57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Gong J, Lin Y, Zhang H, Liu C, Cheng Z, Yang X, et al. Reprogramming of lipid metabolism in cancer-associated fibroblasts potentiates migration of colorectal cancer cells. Cell Death Dis. 2020;11(4):267.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Nardi F, Fitchev P, Franco OE, Ivanisevic J, Scheibler A, Hayward SW et al. PEDF regulates plasticity of a novel lipid-MTOC axis in prostate cancer-associated fibroblasts. J Cell Sci. 2018;131(13).

  90. Timperi E, Gueguen P, Molgora M, Magagna I, Kieffer Y, Lopez-Lastra S, et al. Lipid-Associated macrophages Are Induced by Cancer-Associated fibroblasts and mediate Immune suppression in breast Cancer. Cancer Res. 2022;82(18):3291–306.

    Article  CAS  PubMed  Google Scholar 

  91. Hill BS, Sarnella A, D’Avino G, Zannetti A. Recruitment of stromal cells into tumour microenvironment promote the metastatic spread of breast cancer. Sem Cancer Biol. 2020;60:202–13.

    Article  Google Scholar 

  92. Yang T, Chen M, Yang X, Zhang X, Zhang Z, Sun Y, et al. Down-regulation of KLF5 in cancer-associated fibroblasts inhibit gastric cancer cells progression by CCL5/CCR5 axis. Cancer Biol Ther. 2017;18(10):806–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Qi W, Yang Z, Li H, Cui Y, Xuan Y. The role of Tenascin-C and Twist1 in gastric cancer: cancer progression and prognosis. APMIS: acta pathologica, microbiologica, et immunologica Scandinavica. 2019;127(2):64–71.

  94. Wang R, Sun Y, Yu W, Yan Y, Qiao M, Jiang R, et al. 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(1):20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Miki Y, Yashiro M, Okuno T, Kitayama K, Masuda G, Hirakawa K, et al. CD9-positive exosomes from cancer-associated fibroblasts stimulate the migration ability of scirrhous-type gastric cancer cells. Br J Cancer. 2018;118(6):867–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Zhou Q, Wu X, Wang X, Yu Z, Pan T, Li Z, et al. The reciprocal interaction between tumor cells and activated fibroblasts mediated by TNF-α/IL-33/ST2L signaling promotes gastric cancer metastasis. Oncogene. 2020;39(7):1414–28.

    Article  CAS  PubMed  Google Scholar 

  97. Ding X, Ji J, Jiang J, Cai Q, Wang C, Shi M, et al. HGF-mediated crosstalk between cancer-associated fibroblasts and MET-unamplified gastric cancer cells activates coordinated tumorigenesis and metastasis. Cell Death Dis. 2018;9(9):867.

    Article  PubMed  PubMed Central  Google Scholar 

  98. Wang X, Che X, Liu C, Fan Y, Bai M, Hou K, et al. Cancer-associated fibroblasts-stimulated interleukin-11 promotes metastasis of gastric cancer cells mediated by upregulation of MUC1. Exp Cell Res. 2018;368(2):184–93.

    Article  CAS  PubMed  Google Scholar 

  99. Xu G, Zhang B, Ye J, Cao S, Shi J, Zhao Y, et al. Exosomal miRNA-139 in cancer-associated fibroblasts inhibits gastric cancer progression by repressing MMP11 expression. Int J Biol Sci. 2019;15(11):2320–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Mochizuki S, Ao T, Sugiura T, Yonemura K, Shiraishi T, Kajiwara Y, et al. Expression and function of a disintegrin and Metalloproteinases in Cancer-Associated fibroblasts of Colorectal Cancer. Digestion. 2020;101(1):18–24.

    Article  CAS  PubMed  Google Scholar 

  101. Paauwe M, Schoonderwoerd MJA, Helderman R, Harryvan TJ, Groenewoud A, van Pelt GW, et al. Endoglin expression on Cancer-Associated fibroblasts regulates Invasion and stimulates colorectal Cancer Metastasis. Clin cancer Research: Official J Am Association Cancer Res. 2018;24(24):6331–44.

    Article  CAS  Google Scholar 

  102. Ouahoud S, Voorneveld PW, van der Burg LRA, de Jonge-Muller ESM, Schoonderwoerd MJA, Paauwe M, et al. Bidirectional tumor/stroma crosstalk promotes metastasis in mesenchymal colorectal cancer. Oncogene. 2020;39(12):2453–66.

    Article  CAS  PubMed  Google Scholar 

  103. Hu JL, Wang W, Lan XL, Zeng ZC, Liang YS, Yan YR, et al. CAFs secreted exosomes promote metastasis and chemotherapy resistance by enhancing cell stemness and epithelial-mesenchymal transition in colorectal cancer. Mol Cancer. 2019;18(1):91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Li R, Zhou J, Wu X, Li H, Pu Y, Liu N, et al. Jianpi Jiedu recipe inhibits colorectal cancer liver metastasis via regulating ITGBL1-rich extracellular vesicles mediated activation of cancer-associated fibroblasts. Phytomedicine: Int J Phytotherapy Phytopharmacology. 2022;100:154082.

    Article  Google Scholar 

  105. Fang T, Lv H, Lv G, Li T, Wang C, Han Q, et al. Tumor-derived exosomal mir-1247-3p induces cancer-associated fibroblast activation to foster lung metastasis of liver cancer. Nat Commun. 2018;9(1):191.

    Article  PubMed  PubMed Central  Google Scholar 

  106. Xu H, Zhao J, Li J, Zhu Z, Cui Z, Liu R, et al. Cancer associated fibroblast-derived CCL5 promotes hepatocellular carcinoma metastasis through activating HIF1α/ZEB1 axis. Cell Death Dis. 2022;13(5):478.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Kong J, Tian H, Zhang F, Zhang Z, Li J, Liu X, et al. Extracellular vesicles of carcinoma-associated fibroblasts creates a pre-metastatic niche in the lung through activating fibroblasts. Mol Cancer. 2019;18(1):175.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Ren Y, Jia HH, Xu YQ, Zhou X, Zhao XH, Wang YF, et al. Paracrine and epigenetic control of CAF-induced metastasis: the role of HOTAIR stimulated by TGF-ß1 secretion. Mol Cancer. 2018;17(1):5.

    Article  PubMed  PubMed Central  Google Scholar 

  109. Chen L, Chen M, Han Z, Jiang F, Xu C, Qin Y, et al. Clinical significance of FAP-α on microvessel and lymphatic vessel density in lung squamous cell carcinoma. J Clin Pathol. 2018;71(8):721–8.

    Article  CAS  PubMed  Google Scholar 

  110. Ren Y, Cao L, Wang L, Zheng S, Zhang Q, Guo X, et al. Autophagic secretion of HMGB1 from cancer-associated fibroblasts promotes metastatic potential of non-small cell lung cancer cells via NFκB signaling. Cell Death Dis. 2021;12(10):858.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Richardson AM, Havel LS, Koyen AE, Konen JM, Shupe J, Wiles, WGt, et al. Vimentin is required for lung Adenocarcinoma Metastasis via Heterotypic Tumor Cell-Cancer-Associated Fibroblast Interactions during collective Invasion. Clin cancer Research: Official J Am Association Cancer Res. 2018;24(2):420–32.

    Article  CAS  Google Scholar 

  112. Xue B, Chuang CH, Prosser HM, Fuziwara CS, Chan C, Sahasrabudhe N, et al. miR-200 deficiency promotes lung cancer metastasis by activating notch signaling in cancer-associated fibroblasts. Genes Dev. 2021;35(15–16):1109–22.

    Article  PubMed  PubMed Central  Google Scholar 

  113. Ershaid N, Sharon Y, Doron H, Raz Y, Shani O, Cohen N, et al. NLRP3 inflammasome in fibroblasts links tissue damage with inflammation in breast cancer progression and metastasis. Nat Commun. 2019;10(1):4375.

    Article  PubMed  PubMed Central  Google Scholar 

  114. Bayer SV, Grither WR, Brenot A, Hwang PY, Barcus CE, Ernst M et al. DDR2 controls breast tumor stiffness and metastasis by regulating integrin mediated mechanotransduction in CAFs. eLife. 2019;8.

  115. Chen B, Sang Y, Song X, Zhang D, Wang L, Zhao W, et al. Exosomal miR-500a-5p derived from cancer-associated fibroblasts promotes breast cancer cell proliferation and metastasis through targeting USP28. Theranostics. 2021;11(8):3932–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Yan Z, Sheng Z, Zheng Y, Feng R, Xiao Q, Shi L, et al. Cancer-associated fibroblast-derived exosomal miR-18b promotes breast cancer invasion and metastasis by regulating TCEAL7. Cell Death Dis. 2021;12(12):1120.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Chatterjee A, Jana S, Chatterjee S, Wastall LM, Mandal G, Nargis N, et al. MicroRNA-222 reprogrammed cancer-associated fibroblasts enhance growth and metastasis of breast cancer. Br J Cancer. 2019;121(8):679–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Wu HJ, Hao M, Yeo SK, Guan JL. FAK signaling in cancer-associated fibroblasts promotes breast cancer cell migration and metastasis by exosomal miRNAs-mediated intercellular communication. Oncogene. 2020;39(12):2539–49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Wen S, Hou Y, Fu L, Xi L, Yang D, Zhao M, et al. Cancer-associated fibroblast (CAF)-derived IL32 promotes breast cancer cell invasion and metastasis via integrin β3-p38 MAPK signalling. Cancer Lett. 2019;442:320–32.

    Article  CAS  PubMed  Google Scholar 

  120. Chen Y, Zeng C, Zhan Y, Wang H, Jiang X, Li W. Aberrant low expression of p85α in stromal fibroblasts promotes breast cancer cell metastasis through exosome-mediated paracrine Wnt10b. Oncogene. 2017;36(33):4692–705.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Wang S, Englund E, Kjellman P, Li Z, Ahnlide JK, Rodriguez-Cupello C, et al. CCM3 is a gatekeeper in focal adhesions regulating mechanotransduction and YAP/TAZ signalling. Nat Cell Biol. 2021;23(7):758–70.

    Article  CAS  PubMed  Google Scholar 

  122. Li X, Sun Z, Peng G, Xiao Y, Guo J, Wu B, et al. Single-cell RNA sequencing reveals a pro-invasive cancer-associated fibroblast subgroup associated with poor clinical outcomes in patients with gastric cancer. Theranostics. 2022;12(2):620–38.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Chen Y, Zhu S, Liu T, Zhang S, Lu J, Fan W, et al. Epithelial cells activate fibroblasts to promote esophageal cancer development. Cancer Cell. 2023;41(5):903–e188.

    Article  CAS  PubMed  Google Scholar 

  124. Li C, Guo H, Zhai P, Yan M, Liu C, Wang X, et al. Spatial and single-cell transcriptomics reveal a Cancer-Associated Fibroblast Subset in HNSCC that restricts infiltration and antitumor activity of CD8 + T cells. Cancer Res. 2024;84(2):258–75.

    Article  CAS  PubMed  Google Scholar 

  125. Honda CK, Kurozumi S, Fujii T, Pourquier D, Khellaf L, Boissiere F, et al. Cancer-associated fibroblast spatial heterogeneity and EMILIN1 expression in the tumor microenvironment modulate TGF-β activity and CD8(+) T-cell infiltration in breast cancer. Theranostics. 2024;14(5):1873–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Zhang H, Xie C, Yue J, Jiang Z, Zhou R, Xie R, et al. Cancer-associated fibroblasts mediated chemoresistance by a FOXO1/TGFβ1 signaling loop in esophageal squamous cell carcinoma. Mol Carcinog. 2017;56(3):1150–63.

    Article  CAS  PubMed  Google Scholar 

  127. Guillén Díaz-Maroto N, Sanz-Pamplona R, Berdiel-Acer M, Cimas FJ, García E, Gonçalves-Ribeiro S, et al. Noncanonical TGFβ pathway relieves the blockade of IL1β/TGFβ-Mediated crosstalk between Tumor and Stroma: TGFBR1 and TAK1 inhibition in Colorectal Cancer. Clin cancer Research: Official J Am Association Cancer Res. 2019;25(14):4466–79.

    Article  Google Scholar 

  128. Ikemori R, Gabasa M, Duch P, Vizoso M, Bragado P, Arshakyan M, et al. Epigenetic SMAD3 repression in Tumor-Associated fibroblasts impairs fibrosis and response to the Antifibrotic Drug Nintedanib in Lung squamous cell carcinoma. Cancer Res. 2020;80(2):276–90.

    Article  CAS  PubMed  Google Scholar 

  129. Movia D, Bazou D, Prina-Mello A. ALI multilayered co-cultures mimic biochemical mechanisms of the cancer cell-fibroblast cross-talk involved in NSCLC MultiDrug Resistance. BMC Cancer. 2019;19(1):854.

    Article  PubMed  PubMed Central  Google Scholar 

  130. Kodet O, Dvořánková B, Bendlová B, Sýkorová V, Krajsová I, Štork J, et al. Microenvironment–driven resistance to B–Raf inhibition in a melanoma patient is accompanied by broad changes of gene methylation and expression in distal fibroblasts. Int J Mol Med. 2018;41(5):2687–703.

    CAS  PubMed  PubMed Central  Google Scholar 

  131. Qiao Y, Zhang C, Li A, Wang D, Luo Z, Ping Y, et al. IL6 derived from cancer-associated fibroblasts promotes chemoresistance via CXCR7 in esophageal squamous cell carcinoma. Oncogene. 2018;37(7):873–83.

    Article  CAS  PubMed  Google Scholar 

  132. Ham IH, Oh HJ, Jin H, Bae CA, Jeon SM, Choi KS, et al. Targeting interleukin-6 as a strategy to overcome stroma-induced resistance to chemotherapy in gastric cancer. Mol Cancer. 2019;18(1):68.

    Article  PubMed  PubMed Central  Google Scholar 

  133. Liu H, Shen J, Lu K. IL-6 and PD-L1 blockade combination inhibits hepatocellular carcinoma cancer development in mouse model. Biochem Biophys Res Commun. 2017;486(2):239–44.

    Article  CAS  PubMed  Google Scholar 

  134. Thongchot S, Ferraresi A, Vidoni C, Loilome W, Yongvanit P, Namwat N, et al. Resveratrol interrupts the pro-invasive communication between cancer associated fibroblasts and cholangiocarcinoma cells. Cancer Lett. 2018;430:160–71.

    Article  CAS  PubMed  Google Scholar 

  135. Li Z, Chan K, Qi Y, Lu L, Ning F, Wu M, et al. Participation of CCL1 in snail-positive fibroblasts in Colorectal Cancer contribute to 5-Fluorouracil/Paclitaxel Chemoresistance. Cancer Res Treat. 2018;50(3):894–907.

    Article  CAS  PubMed  Google Scholar 

  136. Che Y, Wang J, Li Y, Lu Z, Huang J, Sun S, et al. Cisplatin-activated PAI-1 secretion in the cancer-associated fibroblasts with paracrine effects promoting esophageal squamous cell carcinoma progression and causing chemoresistance. Cell Death Dis. 2018;9(7):759.

    Article  PubMed  PubMed Central  Google Scholar 

  137. Masuda T, Nakashima T, Namba M, Yamaguchi K, Sakamoto S, Horimasu Y, et al. Inhibition of PAI-1 limits chemotherapy resistance in lung cancer through suppressing myofibroblast characteristics of cancer-associated fibroblasts. J Cell Mol Med. 2019;23(4):2984–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Zhang Z, Karthaus WR, Lee YS, Gao VR, Wu C, Russo JW, et al. Tumor Microenvironment-Derived NRG1 promotes Antiandrogen Resistance in prostate Cancer. Cancer Cell. 2020;38(2):279–. – 96.e9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Ogier C, Colombo PE, Bousquet C, Canterel-Thouennon L, Sicard P, Garambois V, et al. Targeting the NRG1/HER3 pathway in tumor cells and cancer-associated fibroblasts with an anti-neuregulin 1 antibody inhibits tumor growth in pre-clinical models of pancreatic cancer. Cancer Lett. 2018;432:227–36.

    Article  CAS  PubMed  Google Scholar 

  140. Wei L, Ye H, Li G, Lu Y, Zhou Q, Zheng S, et al. Cancer-associated fibroblasts promote progression and gemcitabine resistance via the SDF-1/SATB-1 pathway in pancreatic cancer. Cell Death Dis. 2018;9(11):1065.

    Article  PubMed  PubMed Central  Google Scholar 

  141. You J, Li M, Cao LM, Gu QH, Deng PB, Tan Y, et al. Snail1-dependent cancer-associated fibroblasts induce epithelial-mesenchymal transition in lung cancer cells via exosomes. QJM: Monthly J Association Physicians. 2019;112(8):581–90.

    Article  CAS  Google Scholar 

  142. Richards KE, Zeleniak AE, Fishel ML, Wu J, Littlepage LE, Hill R. Cancer-associated fibroblast exosomes regulate survival and proliferation of pancreatic cancer cells. Oncogene. 2017;36(13):1770–8.

    Article  CAS  PubMed  Google Scholar 

  143. Fang Y, Zhou W, Rong Y, Kuang T, Xu X, Wu W, et al. Exosomal miRNA-106b from cancer-associated fibroblast promotes gemcitabine resistance in pancreatic cancer. Exp Cell Res. 2019;383(1):111543.

    Article  CAS  PubMed  Google Scholar 

  144. Zhang T, Zhang P, Li HX. CAFs-Derived exosomal miRNA-130a confers Cisplatin Resistance of NSCLC cells through PUM2-Dependent packaging. Int J Nanomed. 2021;16:561–77.

    Article  Google Scholar 

  145. Pan S, Deng Y, Fu J, Zhang Y, Zhang Z, Qin X. N6–methyladenosine upregulates miR–181d–5p in exosomes derived from cancer–associated fibroblasts to inhibit 5–FU sensitivity by targeting NCALD in colorectal cancer. Int J Oncol. 2022;60(2).

  146. Zhou Z, Qu C, Zhou P, Zhou Q, Li D, Wu X, et al. Extracellular vesicles activated cancer-associated fibroblasts promote lung cancer metastasis through mitophagy and mtDNA transfer. J Exp Clin Cancer Res. 2024;43(1):158.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Zheng S, Wang J, Ding N, Chen W, Chen H, Xue M, et al. Prodrug polymeric micelles integrating cancer-associated fibroblasts deactivation and synergistic chemotherapy for gastric cancer. J Nanobiotechnol. 2021;19(1):381.

    Article  CAS  Google Scholar 

  148. Guo J, Zeng H, Chen Y. Emerging Nano Drug Delivery systems Targeting Cancer-Associated fibroblasts for Improved Antitumor Effect and Tumor Drug Penetration. Mol Pharm. 2020;17(4):1028–48.

    Article  CAS  PubMed  Google Scholar 

  149. Chen B, Dai W, Mei D, Liu T, Li S, He B, et al. Comprehensively priming the tumor microenvironment by cancer-associated fibroblast-targeted liposomes for combined therapy with cancer cell-targeted chemotherapeutic drug delivery system. J Controlled Release: Official J Controlled Release Soc. 2016;241:68–80.

    Article  CAS  Google Scholar 

  150. Zhou Q, Zhou Y, Liu X, Shen Y. GDC-0449 improves the antitumor activity of nano-doxorubicin in pancreatic cancer in a fibroblast-enriched microenvironment. Sci Rep. 2017;7(1):13379.

    Article  PubMed  PubMed Central  Google Scholar 

  151. Peltanova B, Liskova M, Gumulec J, Raudenska M, Polanska HH, Vaculovic T et al. Sensitivity to Cisplatin in Head and Neck Cancer cells is significantly affected by patient-derived Cancer-Associated fibroblasts. Int J Mol Sci. 2021;22(4).

  152. Benedicto A, Hernandez-Unzueta I, Sanz E, Márquez J. Ocoxin increases the Antitumor Effect of BRAF Inhibition and reduces Cancer Associated fibroblast-mediated Chemoresistance and Protumoral Activity in Metastatic Melanoma. Nutrients. 2021;13(2).

  153. Zhou B, Sun C, Li N, Shan W, Lu H, Guo L, et al. Cisplatin-induced CCL5 secretion from CAFs promotes cisplatin-resistance in ovarian cancer via regulation of the STAT3 and PI3K/Akt signaling pathways. Int J Oncol. 2016;48(5):2087–97.

    Article  CAS  PubMed  Google Scholar 

  154. Zhang Y, Zhao J, Ding M, Su Y, Cui D, Jiang C, et al. Loss of exosomal miR-146a-5p from cancer-associated fibroblasts after androgen deprivation therapy contributes to prostate cancer metastasis. J Exp Clin Cancer Res. 2020;39(1):282.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Funding

This study was supported by grants from Henan Provincial Natural Science Foundation Youth Project (242300421487); Henan Provincial Medical Science and Technology Research Program Joint Construction Project (LHGJ20200276); Henan Medical Science and Technology Research Plan ( LHGJ20230294).

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  1. Pin Lyu, Xiaoming Gu and Fuqi Wang contributed equally to this work.

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  1. Department of Colorectal Surgery, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Erqi District, Zhengzhou, 450000, Henan, China

    Pin Lyu, Xiaoming Gu, Fuqi Wang, Haifeng Sun, Quanbo Zhou, Shuaixi Yang & Weitang Yuan

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  1. Pin Lyu
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Authors’ contribution: L.P., Y.S. and Y.W. drafted the work and wrote the main manuscript text; Y.W. and Y.S. made contributions to the conception or design of the work; L.P., G.X. and W.F. prepared Figs. 1, 2, 3, 4 and 5. and Table 1 in the work; W.F., Z.Q. and S.H. made contributions to the acquisition, analysis and interpretation of data; L.P., and Z.Q. made contributions to revise the manuscript text; All authors reviewed the manuscript.

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Correspondence to Weitang Yuan.

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Lyu, P., Gu, X., Wang, F. et al. Advances in targeting cancer-associated fibroblasts through single-cell spatial transcriptomic sequencing. Biomark Res 12, 73 (2024). https://doi.org/10.1186/s40364-024-00622-9

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Biomarker Research

ISSN: 2050-7771

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