The Role of Recruited Adipose Stromal Cells and Their Fibroblastic Differentiation in Cancer

Lingyi Cai , Mikhail G. Kolonin , Dimitris Anastassiou

Frontiers in Bioscience-Landmark ›› 2025, Vol. 30 ›› Issue (8) : 36559

PDF (1014KB)
Frontiers in Bioscience-Landmark ›› 2025, Vol. 30 ›› Issue (8) :36559 DOI: 10.31083/FBL36559
Review
review-article
The Role of Recruited Adipose Stromal Cells and Their Fibroblastic Differentiation in Cancer
Author information +
History +
PDF (1014KB)

Abstract

Adipose stromal cells (ASCs) are perivascular mesenchymal progenitors of adipose tissue. In cancer patients, ASCs can mobilize and migrate to the tumor, where they subsequently play an important role in cancer progression. This biological process involves the conversion of recruited ASCs into cancer-associated fibroblasts (CAFs). ASC-derived CAFs influence the tumor microenvironment through extracellular matrix remodeling, vascularization, and immunomodulation. These and other processes mediated by secreted paracrine factors also affect gene expression in carcinoma cells to promote the epithelial-mesenchymal transition (EMT), metabolic adaptation, survival, and invasiveness of cancer cells. ASC-derived CAFs can enhance tumor aggressiveness, accounting in part for the link between obesity and mortality observed in many cancer types that are surrounded by adipose tissue. In this review, we highlight recent findings on the characteristics and functions of ASCs in cancer and discuss their potential as therapeutic targets.

Graphical abstract

Keywords

adipose stromal cells / adipose-derived fibroblasts / cancer-associated fibroblasts / tumor microenvironment

Cite this article

Download citation ▾
Lingyi Cai, Mikhail G. Kolonin, Dimitris Anastassiou. The Role of Recruited Adipose Stromal Cells and Their Fibroblastic Differentiation in Cancer. Frontiers in Bioscience-Landmark, 2025, 30(8): 36559 DOI:10.31083/FBL36559

登录浏览全文

4963

注册一个新账户 忘记密码

1. Introduction: Overview of Adipose Stromal Cells

The cells in adipose tissue can be separated by enzymatic digestion into the stromal vascular fraction (SVF) and the buoyant fraction [1, 2]. The SVF contains a heterogeneous population of cells that includes adipose stromal cells (ASCs), immune cells and endothelial cells, while the buoyant fraction contains adipocytes and some pre-adipocytes [2]. The immunophenotypes of individual ASC sub-populations have been studied previously [1, 3], but are still not completely understood.

Single-cell RNA sequencing (scRNA-seq) has helped to delineate populations within white adipose tissue (WAT), including ASCs and their subpopulations [4, 5]. ASCs reside in the perivascular niche and support endothelial function, as well as differentiating into adipocytes or fibroblasts depending on the cues they receive [5, 6]. A subpopulation of mesenchymal stromal cells (MSCs) is comprised of preadipocytes with high adipogenic potential and expression of Platelet Derived Growth Factor Receptor Alpha (PDGFRα) and Platelet Derived Growth Factor Receptor Beta (PDGFRβ). The transient signaling balance of these receptors determines whether MSCs differentiate into beige or white adipocytes [7]. Another major subpopulation, referred to as fibro-inflammatory precursors or interstitial progenitor cells, is characterized by a gene expression profile that has been associated with modeling of the extracellular matrix (ECM) and with inflammation [8]. Age-related subpopulations, such as aging-dependent regulatory cells, have also been identified. These secrete cytokines that may contribute to the reduced subcutaneous adipose tissue and tissue plasticity observed in human aging [9].

One particular ASC subpopulation has a characteristic signature containing several co-expressed genes, such as Apolipoprotein D (APOD), Decorin (DCN), Lumican (LUM), Complement Factor D (CFD), C-X-C Motif Chemokine Ligand 14 (CXCL14), and Prostaglandin D2 Synthase (PTGDS). This signature has been identified in several studies, indicating consistency across different tissues. For example, it was found among adipocyte progenitors in subcutaneous WAT from the dataset used in study [10], as shown in cluster visceral adipose tissue-derived progenitor cells 4 (VP4) of Supplementary Table 20. Moreover, the abundance of this population in the SVF was demonstrated by analyzing the same dataset in Supplementary Fig. 1 of the paper by Cai et al. [11].

Interestingly, a cell population with the same characteristic signature was found among fibro-adipogenic progenitors (FAPs) in skeletal muscle. For example, in the study by Rubenstein et al. [12] they were reported as LUM+ FAPs in Supplementary Table 1, and included the genes APOD, PTGDS, LUM, DCN, Matrix Gla Protein (MGP), CFD, CXCL14, Dermatopontin (DPT), and Serpin Family F Member 1 (SERPINF1). A similar population was found in Supplementary Fig. 3a of the study by Fitzgerald et al. [13], referred to as a Membrane Metalloendopeptidase (MME)+ FAP population, and which expressed the genes APOD, PTGDS, CXCL14, MGP and Secreted Frizzled Related Protein 2 (SFRP2). These cells can differentiate into adipocytes. Cai et al. [11] referred to this subpopulation of ASCs as “the ASC/FAP population”, with its progenitors having both adipogenic and fibroblastic differentiation potential. Consistent with these findings, Gao et al. [14] identified a fibroblast progenitor subtype in a multi-tissue fibroblast atlas. This was characterized by the expression of adipogenic genes such as APOD, and cluster “c03” shown in Supplementary Table 2 of the report by Gao et al. [14], which includes all ASC/FAP genes. Furthermore, the presence of this progenitor population in both adipose tissue and skeletal muscle is consistent with the finding that adipose tissue is a source of FAP-like cells recruited to the skeletal muscle during remodeling [15].

2. Recruitment of ASCs in Cancer

ASCs can be recruited into tumors to enhance the supportive properties of the tumor microenvironment (TME), as indicated by resistance to anti-cancer therapy in mouse models [16, 17, 18, 19]. The recruitment and infiltration of ASCs into tumors is driven by specific molecular and signaling mechanisms that create a favorable environment for cancer progression. One such mechanism involves chemokine signaling, whereby chemokines such as C-X-C Motif Chemokine Ligand 1 (CXCL1) and C-X-C Motif Chemokine Ligand 8 (CXCL8) bind to receptors such as C-X-C Motif Chemokine Receptor 1 (CXCR1) and C-X-C Motif Chemokine Receptor 2 (CXCR2) on ASCs and guide their migration towards the tumor [17]. Mouse models have demonstrated the importance of the CXCL1 chemokine gradient for obesity-dependent tumor ASC recruitment that promotes the progression and metastatic potential of prostate cancer [17, 20].

Once recruited, ASCs infiltrate the tumor and contribute to the stromal compartment by secreting agents that stimulate vascularization, immune modulation, and tissue remodeling [21]. ASC mobilization from WAT is initiated by molecular triggers such as the interaction between adipocyte-secreted proteins and integrins on the surface of ASCs [22]. Signaling pathways such as IL-22 also activate ASCs, thereby increasing their recruitment and integration into the tumor stroma where they produce ECM components and promote cancer cell survival [22, 23]. These processes highlight the important role of chemokine-mediated recruitment and integrin signaling in ASC mobilization. In summary, ASCs are key contributors to the tumor-supportive stroma, and as such represent a potential target for therapeutic intervention [20].

We have previously studied the role of ASC-derived cancer-associated fibroblasts (CAFs) in epithelial-mesenchymal transition (EMT) induction and cancer aggressiveness [24, 25, 26]. C-X-C Motif Chemokine Ligand 12 (CXCL12 (alias, SDF1)) is a paracrine chemokine secreted by ASCs and adipose-derived CAFs and which signals via CXCR4 and CXCR7 to promote obesity-associated cancer progression via EMT. The SVF derived from WAT of obese mice shows significantly higher CXCL12 expression than the SVF from lean mice. Signaling by CXCL12 results in the activation of Signal Transducer and Activator of Transcription 3 (STAT3), Nuclear Factor Kappa-light-chain-enhancer of activated B cells (NF-κB), and c-Jun N-terminal Kinases (JNK). Targeting of ASCs with a hunter-killer peptide D-CAN, which specifically depletes these cells, or with inhibitors of CXCR4 or CXCR7, leads to the suppression of cancer metastases and chemoresistance [27].

Single-cell analysis of biopsies from many cancer types has identified computationally-derived clusters that include cells with the same gene signature as the APOD+DCN+LUM+ ASC/FAP population mentioned previously. This indicates they are likely to be recruited ASCs. For example, Chen et al. [28] identified a fibroblastic population in esophageal cancer that was characterized by gene expression for CFD, APOD, Gelsolin (GSN), and Peptidase Inhibitor 16 (PI16). Zhang et al. [29] clustered stromal cells into nine subtypes, including one labeled as “normal activated fibroblasts” that was characterized by expression of APOD, CFD, DPT, CXCL14, PTGDS, and MGP. Other examples of the signature in breast cancer are found in Supplementary Table 9 (inflammatory CAF (iCAF) minor) of the study by Wu et al. [30], and Supplementary Table 3 (iCAF) of the study by Cords et al. [31], both of which feature the ASC markers APOD and CFD at the top.

The presence of recruited and infiltrated ASC/FAPs in cancer biopsies is in most cases thought to represent inflammatory CAFs, as described below. This is because computationally-derived clusters are typically labeled with one of several pre-assigned cell subtypes. To date, the ASC/FAP population has not been widely recognized as a stromal population in the TME, and as a consequence this population is usually assumed to be a type of CAF.

The TME reflects the progression to aggressive disease [32, 33]. CAFs are a heterogeneous and plastic population of non-malignant mesenchymal cells within this microenvironment that modulate tumor vascularization and growth, EMT, chemotherapy resistance, ECM remodeling, metastatic dissemination, and immunosuppression [34]. They are recruited early in cancer development and evolve as the disease progresses [35, 36]. Several major CAF subtypes are generally recognized, with the main ones being myofibroblastic CAFs (myCAFs) and inflammatory CAFs (iCAFs). MyCAFs exhibit a matrix-producing, contractile phenotype with high alpha-smooth muscle actin (αSMA) (ACTA2) expression. They are associated with high TGFβ signaling levels and are observed adjacent to cancer cells. iCAFs are more distant and exhibit an immuno-modulatory phenotype that expresses a high level of interleukin 6 (IL6). Moreover, iCAFs display TGFβ-mediated suppression of the IL1 receptor, which is responsible for driving NF-κB signaling upstream of IL6 induction [14, 37, 38, 39, 40]. In addition to these subtypes, CAFs that express major histocompatibility complex class II (MHC II) and CD74 Molecule (CD74) are termed antigen-presenting CAFs (apCAFs) [39].

Tumor infiltrating ASCs in their original, undifferentiated progenitor state should not be classified as one of the three widely recognized CAF subtypes described above. However, they are often included within non-homogeneous, computationally-derived clusters. Since part of the cell population in such clusters expresses inflammatory markers, this has been thought to represent iCAFs in their original state, meaning that even genes such as APOD and CFD have been mischaracterized as iCAF markers. In reality, iCAFs are characterized by the signature previously reported by Elyada et al. [39], which includes the expression of IL6, C-C Motif Chemokine Ligand 2 (CCL2), and Hyaluronan Synthase 1 (HAS1). For example, “cluster 1” in Fig. 5D of the study by Dominguez et al. [41] is marked by the expression of CFD, PTGDS, and C7, all of which are expressed in ASCs. This cluster is distinct from “cluster 2” marked by IL6, HAS1, and CCL2, and which corresponds to the true iCAF population. Similarly, Chen et al. [28] identified iCAFs in esophageal cancer as a population that expressed inflammatory genes such as CXCL1, CXCL8, and Interleukin 24 (IL24). Ho et al. [42] found both iCAF and “adipose-like CAF” in head and neck squamous cell carcinoma (HNSCC), with iCAFs expressing IL6 and CXCL1, while adipose-like CAFs expressed APOD and CFD, and clearly included recruited ASCs. The distinction between ASCs and iCAFs is further supported by the cross-tissue human fibroblast atlas. This identifies inflammatory fibroblasts as expressing IL6, CXCL1 and CXCL2, whereas APOD and PI16 expression is found in progenitor cells that are distinct from IL6-expressing cells [14]. Therefore, recruited ASCs in their original state should not be confused with IL6+ iCAFs, although some may independently transition to that state.

There are many examples in different cancer types where recruited ASCs with a consistent gene signature have been misclassified as iCAFs [43, 44, 45, 46, 47, 48, 49, 50, 51]. For example, transcriptomic analysis shown in Extended Data Fig. 7 of the study by Cui Zhou et al. [43] identified a stromal subpopulation in pancreatic ductal adenocarcinoma (PDAC) with a signature that included the marker genes APOD, PTGDS, CXCL14, CFD, DCN, and LUM. The study also identified 12 genes (APOD, C3, PTGDS, C7, IGFBP3, SFRP4, CXCL14, CFD, SFRP2, DCN, FBLN1, and LUM) that formed a “chemoresistance signature”. Chemoresistant samples of pancreatic cancer showed a three-fold enrichment of this signature. Similarly, Supplementary Table 6-1 in the study by Wang et al. [49] identified the iCAF cluster C0, with high expression levels of APOD, PTGDS, MGP, DCN, LUM, SERPINF1, CFD, CXCL14, and DPT. Additionally, Zhao et al. [44] reported that iCAFs in obesity-associated breast cancer showed upregulation of genes including CFD, APOD, and CXCL14. Chen et al. [45] found a cluster labeled iCAF in bladder cancer that expressed genes such as APOD, DCN, LUM, CFD, CXCL14, PTGDS, MGP, SERPINF1, and DPT. Pu et al. [46] identified a cell population in thyroid carcinoma, labeled iCAF, that was characterized by high expression of ASC genes including APOD, CFD, DCN, and CXCL14. However, these authors noted a lack of key iCAF markers such as IL6 and IL8 (Supplementary Fig. 9e in study [46]). Finally, Thorlacius-Ussing et al. [47] suggested the existence of two separate populations of iCAFs in PDAC, with one being IL6 positive and the other IL6 negative. In fact, the IL6-negative cluster contained mostly the ASC population (Supplementary Fig. 4 in study [47]) without inflammatory gene markers.

3. Fibroblastic Differentiation of ASCs

Recruited ASCs have been found to undergo fibroblastic differentiation as part of a multi-faceted, cancer invasiveness-related biological mechanism [11] (Fig. 1). By analyzing datasets from multiple cancer types, including a particularly rich dataset from pancreatic cancer [52], Zhu et al. [53] identified a cell transition starting from APOD-expressing ASCs. The endpoint of this transition is an aggressive type of CAF with prominent expression of Collagen Type XI Alpha 1 Chain (COL11A1), referred to as “CAFs in aggressive tumors (aCAFs)”. These also have a well-defined and characteristic gene expression signature that includes THBS2, INHBA, POSTN, COL10A1, and MMP11. First identified by Kim et al. [54], the aCAF gene signature was strongly associated with cancer invasiveness and poor prognosis. It was also found to be associated with tumor stage, consistent with the presence of adjacent adipose tissue. For example, in ovarian cancer the aCAF signature only occurs after the tumor cells have reached the omentum in stage III disease, whereas in breast cancer it occurs in stage I already. Following analysis of six cancer types, Ma et al. [51] reported a potential transition from an APOD+CFD+MGP+CXCL14+ population labeled as iCAF (Fig. 2b in study [51]), to a COL11A1+COL10A1+MMP11+POSTN+ population labeled mCAF (Fig. 2i in study [51]). In pleomorphic sarcoma, Lu et al. [55] identified APOD as a stem cell-related gene involved in cell transition, with decreased APOD expression accompanied by increased COL11A1 expression.

Many other studies have also suggested that ASCs serve as precursors to CAFs within tumors, with some demonstrating their ability to transition into myofibroblast-like cells that contribute to tumor progression. For example, Kidd et al. [56] showed that adipose-derived cells could differentiate into αSMA-positive myofibroblasts within the tumor stroma in a mouse model of breast cancer. Similarly, Jotzu et al. [57] found that a significant percentage of human ASCs differentiate into a CAF-like myofibroblastic phenotype with expression of αSMA. Song et al. [58] reported that tumor extracellular vesicles can convert adipose stem cells into myofibroblasts.

Strong et al. [59] proposed that obesity alters adipose-derived stromal/stem cells, making them more likely to convert into CAFs in the presence of tumor-derived factors. This in turn promotes the proliferation, invasiveness, and expression of pro-tumorigenic factors by breast cancer cells [59]. Okumura et al. [60] demonstrated that ASCs contribute to pancreatic tumor progression by being recruited to extra-pancreatic invasion sites, where they produce dense collagen matrices that enhance tumor growth. In ovarian cancer, Tang et al. [61] suggested that adipose-derived mesenchymal stem cells (ADSCs) from the omentum can differentiate into CAF-like cells via the TGF-β1 signaling pathway, thereby enhancing the proliferation and invasion of epithelial ovarian cancer cells and contributing to the formation of metastatic niches. In both in vitro and in vivo studies, ASCs were observed to migrate to extra-pancreatic invasive lesions, where they formed dense collagen matrices that promote tumor progression [60].

Importantly, both in vitro and in vivo experiments conducted by Miyazaki et al. [62] confirmed that adipose-derived stromal cells have the ability to differentiate into CAFs. Specifically, direct co-culture of ASCs with tumor cells resulted in the expression of genes such as COL10A1, COMP, and INHBA [62]. Using mouse xenografts derived from human tumor cell lines, the same authors subsequently demonstrated the ability of ASCs to differentiate into CAFs with strongly upregulated expression of COL11A1 [63].

Pan-cancer single-cell transcriptomic analyses further support the above conclusions, as evidenced by the fact that clusters which include genes such as APOD and CFD are typically located adjacent to clusters that include COL11A1. For example, Fig. 4 in the study by Hornburg et al. [64] shows two clusters in ovarian cancer, with each being defined by characteristic genes for the two populations (APOD, CFD, MGP, DPT, CXCL14 and COL11A1 for the first cluster; MMP11, POSTN, and INHBA for the second cluster). Similarly, Fig. 2 in the study by Wang et al. [49] on pancreatic cancer shows adjacent clusters C0 and C3, characterized by marker genes including APOD, PTGDS, MGP, DCN, and LUM for C0, and MMP11, POSTN, COL10A1, COL11A1, INHBA, THBS2, SULF1 for C3. Other workers have also demonstrated adjacent clusters characterized by ASC gene markers and CAFs expressing genes such as COL11A1, COL10A1 and MMP11. In PDAC, these include cluster 1 and clusters 3, 4 and 6 [47], “iCAF” and “myCAF” in study [48], and C1 and C0 in study [41]. In breast cancer, similar marker profiles were observed for the adjacent CFD-expressing “iCAF1” and COL11A1-expressing “iCAF2” clusters [44]. In gastric cancer, Zhao et al. [65] observed a similar pattern in the “poor prognosis” CAF_0 cluster, wherein POSTN appears alongside APOD, CFD, and CXCL14 with expansion of the cluster, consistent with a transition.

Gao et al. [14] analyzed 517 samples spanning 11 different tissues. Their RNA velocity results revealed a transition from cluster c03 expressing the ASC/FAP signature, to cluster c16 with SFRP4 as the top differentially expressed gene, identified as marking the start of the transition in another study [53]. The final transition to c04 included the top marker genes COL11A1, THBS2, INHBA, COL10A1, MMP11, POSTN, and SPARC. It remains to be determined whether any of these genes play a role in the pro-carcinogenic properties of ASC-derived CAFs, and whether their targeting could have therapeutic value.

4. Prospects for ASC-derived CAF Targeting

CAFs have often been considered to represent a potential therapeutic target [36, 66, 67, 68, 69]. According to some studies, selective depletion of certain CAF subtypes can impede tumor growth and improve treatment outcomes. For example, conditional depletion of FAP+ stromal cells in transgenic mice led to slower PDAC growth [70]. Similarly, depletion of Leucine Rich Repeat Containing 15 (LRRC15)+ CAFs in pancreatic tumors reduced their overall CAF content, decreased tumor burden, and boosted the responsiveness to anti-programmed cell death ligand-1 (anti-PD-L1) immunotherapy [71]. Collectively, these findings indicate there may be therapeutic potential in modulating the aCAF population to improve cancer treatment. However, the general approach of targeting CAFs remains a subject of ongoing debate. Depletion of αSMA-expressing CAFs [68] or Sonic Hedgehog (SHH)-dependent CAFs in mice was actually found to promote metastasis and reduce survival [69]. This effect may be due to the effect of CAFs in supporting endothelial cells, thereby reducing the hypoxia that drives cancer invasiveness. Additionally, inflammatory CAFs appear to facilitate cytotoxic T cell infiltration, thereby improving the efficacy of immunotherapy [72] and potentially meaning their inactivation is actually a disadvantage.

It remains to be determined whether selective inactivation of ASC-derived CAFs can provide a unique therapeutic benefit. A few studies have investigated the effects of ablating CAFs that express ASC markers [25, 73, 74]. Our group used the hunter-killer peptide D-CAN, which specifically targets ASCs and their non-glycanated decorin- and PDGFRβ-expressing derivatives to induce apoptosis [25, 73]. D-CAN was found to suppress tumor growth and metastasis in mouse models of breast cancer [25]. A recent study by our group also showed that D-CAN suppressed tumor growth in a mouse PDAC model, but induced metastasis [74]. This result is consistent with observations that genetic depletion of perivascular stromal cells can promote metastasis [68]. In both studies, depletion of stromal cells was shown to suppress ECM deposition and the vascularization of tumors. The balance between the anti-metastatic effect of ECM reduction and the pro-metastatic effect of tumor hypoxia varies between different cancer types, possibly explaining model-specific effects. The roles played by ASC-derived CAFs in regulating tumor progression are likely to be cancer type- and stage-specific, with further investigation required. Importantly, there is growing evidence that targeting of ASC-derived aCAFs may be effective in combination with other treatments [11]. In mouse models of breast cancer, the depletion of ASC/CAFs was found to synergize with chemotherapy to suppress cancer progression [25]. We also recently found that ASCs are involved in immune evasion by tumors, suggesting that targeting of ASC-derived CAFs could improve immune checkpoint blockade immunotherapy [74].

5. Conclusion

The recruitment of ASCs in cancer and their differentiation into CAFs is associated with invasiveness, poor prognosis, and resistance to therapy. Although the identification of viable therapeutic targets that play driver roles in the clinical setting show considerable promise, several challenges remain. Accumulating evidence suggests that blocking ASC-derived CAFs can help to suppress tumor growth and metastatic dissemination, as well as overcoming therapy resistance. The identification of specific markers expressed by adipose-derived CAFs, together with a better understanding of their function, may lead to targeted treatments against these cells that could transform cancer management with adjuvant therapies.

References

[1]

Gimble JM, Bunnell BA, Chiu ES, Guilak F. Concise review: Adipose-derived stromal vascular fraction cells and stem cells: let’s not get lost in translation. Stem Cells (Dayton, Ohio). 2011; 29: 749–754. https://doi.org/10.1002/stem.629.

[2]

Daquinag AC, Zhang Y, Kolonin MG. Vascular targeting of adipose tissue as an anti-obesity approach. Trends in Pharmacological Sciences. 2011; 32: 300–307. https://doi.org/10.1016/j.tips.2011.01.004.

[3]

Eckel-Mahan K, Ribas Latre A, Kolonin MG. Adipose Stromal Cell Expansion and Exhaustion: Mechanisms and Consequences. Cells. 2020; 9: 863. https://doi.org/10.3390/cells9040863.

[4]

Maniyadath B, Zhang Q, Gupta RK, Mandrup S. Adipose tissue at single-cell resolution. Cell Metabolism. 2023; 35: 386–413. https://doi.org/10.1016/j.cmet.2023.02.002.

[5]

Lin T, Mohammad A, Kolonin MG, Eckel-Mahan KL. Mechanisms and metabolic consequences of adipocyte progenitor replicative senescence. Immunometabolism (Cobham, Surrey). 2024; 6: e00046. https://doi.org/10.1097/IN9.0000000000000046.

[6]

Traktuev DO, Merfeld-Clauss S, Li J, Kolonin M, Arap W, Pasqualini R, et al. A population of multipotent CD34-positive adipose stromal cells share pericyte and mesenchymal surface markers, reside in a periendothelial location, and stabilize endothelial networks. Circulation Research. 2008; 102: 77–85. https://doi.org/10.1161/CIRCRESAHA.107.159475.

[7]

Gao Z, Daquinag AC, Su F, Snyder B, Kolonin MG. PDGFRα/PDGFRβ signaling balance modulates progenitor cell differentiation into white and beige adipocytes. Development (Cambridge, England). 2018; 145: dev155861. https://doi.org/10.1242/dev.155861.

[8]

Hepler C, Shan B, Zhang Q, Henry GH, Shao M, Vishvanath L, et al. Identification of functionally distinct fibro-inflammatory and adipogenic stromal subpopulations in visceral adipose tissue of adult mice. eLife. 2018; 7: e39636. https://doi.org/10.7554/eLife.39636.

[9]

Nguyen HP, Lin F, Yi D, Xie Y, Dinh J, Xue P, et al. Aging-dependent regulatory cells emerge in subcutaneous fat to inhibit adipogenesis. Developmental Cell. 2021; 56: 1437–1451.e3. https://doi.org/10.1016/j.devcel.2021.03.026.

[10]

Vijay J, Gauthier MF, Biswell RL, Louiselle DA, Johnston JJ, Cheung WA, et al. Single-cell analysis of human adipose tissue identifies depot and disease specific cell types. Nature Metabolism. 2020; 2: 97–109. https://doi.org/10.1038/s42255-019-0152-6.

[11]

Cai L, Kolonin MG, Anastassiou D. The fibro-adipogenic progenitor APOD+DCN+LUM+ cell population in aggressive carcinomas. Cancer Metastasis Reviews. 2024; 43: 977–980. https://doi.org/10.1007/s10555-024-10181-y.

[12]

Rubenstein AB, Smith GR, Raue U, Begue G, Minchev K, Ruf-Zamojski F, et al. Single-cell transcriptional profiles in human skeletal muscle. Scientific Reports. 2020; 10: 229. https://doi.org/10.1038/s41598-019-57110-6.

[13]

Fitzgerald G, Turiel G, Gorski T, Soro-Arnaiz I, Zhang J, Casartelli NC, et al. MME+ fibro-adipogenic progenitors are the dominant adipogenic population during fatty infiltration in human skeletal muscle. Communications Biology. 2023; 6: 111. https://doi.org/10.1038/s42003-023-04504-y.

[14]

Gao Y, Li J, Cheng W, Diao T, Liu H, Bo Y, et al. Cross-tissue human fibroblast atlas reveals myofibroblast subtypes with distinct roles in immune modulation. Cancer Cell. 2024; 42: 1764–1783.e10. https://doi.org/10.1016/j.ccell.2024.08.020.

[15]

Sastourné-Arrey Q, Mathieu M, Contreras X, Monferran S, Bourlier V, Gil-Ortega M, et al. Adipose tissue is a source of regenerative cells that augment the repair of skeletal muscle after injury. Nature Communications. 2023; 14: 80. https://doi.org/10.1038/s41467-022-35524-7.

[16]

Zhang Y, Daquinag AC, Amaya-Manzanares F, Sirin O, Tseng C, Kolonin MG. Stromal progenitor cells from endogenous adipose tissue contribute to pericytes and adipocytes that populate the tumor microenvironment. Cancer Research. 2012; 72: 5198–5208. https://doi.org/10.1158/0008-5472.CAN-12-0294.

[17]

Zhang T, Tseng C, Zhang Y, Sirin O, Corn PG, Li-Ning-Tapia EM, et al. CXCL1 mediates obesity-associated adipose stromal cell trafficking and function in the tumour microenvironment. Nature Communications. 2016; 7: 11674. https://doi.org/10.1038/ncomms11674.

[18]

Kolonin MG, Anastassiou D. Adipose Stromal Cell-Derived Cancer-Associated Fibroblasts Suppress FGFR Inhibitor Efficacy. Cancer Research. 2024; 84: 648–649. https://doi.org/10.1158/0008-5472.CAN-23-3904.

[19]

Hosni S, Kilian V, Klümper N, Gabbia D, Sieckmann K, Corvino D, et al. Adipocyte Precursor-Derived NRG1 Promotes Resistance to FGFR Inhibition in Urothelial Carcinoma. Cancer Research. 2024; 84: 725–740. https://doi.org/10.1158/0008-5472.CAN-23-1398.

[20]

Klopp AH, Zhang Y, Solley T, Amaya-Manzanares F, Marini F, Andreeff M, et al. Omental adipose tissue-derived stromal cells promote vascularization and growth of endometrial tumors. Clinical Cancer Research: an Official Journal of the American Association for Cancer Research. 2012; 18: 771–782. https://doi.org/10.1158/1078-0432.CCR-11-1916.

[21]

Lengyel E, Makowski L, DiGiovanni J, Kolonin MG. Cancer as a Matter of Fat: The Crosstalk between Adipose Tissue and Tumors. Trends in Cancer. 2018; 4: 374–384. https://doi.org/10.1016/j.trecan.2018.03.004.

[22]

Tseng C, Kolonin MG. Proteolytic Isoforms of SPARC Induce Adipose Stromal Cell Mobilization in Obesity. Stem Cells (Dayton, Ohio). 2016; 34: 174–190. https://doi.org/10.1002/stem.2192.

[23]

Zhang Y, Kolonin MG. Cytokine signaling regulating adipose stromal cell trafficking. Adipocyte. 2016; 5: 369–374. https://doi.org/10.1080/21623945.2016.1220452.

[24]

Su F, Ahn S, Saha A, DiGiovanni J, Kolonin MG. Adipose stromal cell targeting suppresses prostate cancer epithelial-mesenchymal transition and chemoresistance. Oncogene. 2019; 38: 1979–1988. https://doi.org/10.1038/s41388-018-0558-8.

[25]

Su F, Wang X, Pearson T, Lee J, Krishnamurthy S, Ueno NT, et al. Ablation of Stromal Cells with a Targeted Proapoptotic Peptide Suppresses Cancer Chemotherapy Resistance and Metastasis. Molecular Therapy Oncolytics. 2020; 18: 579–586. https://doi.org/10.1016/j.omto.2020.08.012.

[26]

Su F, Daquinag AC, Ahn S, Saha A, Dai Y, Zhao Z, et al. Progression of prostate carcinoma is promoted by adipose stromal cell-secreted CXCL12 signaling in prostate epithelium. NPJ Precision Oncology. 2021; 5: 26. https://doi.org/10.1038/s41698-021-00160-9.

[27]

Saha A, Kolonin MG, DiGiovanni J. Obesity and prostate cancer - microenvironmental roles of adipose tissue. Nature Reviews. Urology. 2023; 20: 579–596. https://doi.org/10.1038/s41585-023-00764-9.

[28]

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: 903–918.e8. https://doi.org/10.1016/j.ccell.2023.03.001.

[29]

Zhang X, Peng L, Luo Y, Zhang S, Pu Y, Chen Y, et al. Dissecting esophageal squamous-cell carcinoma ecosystem by single-cell transcriptomic analysis. Nature Communications. 2021; 12: 5291. https://doi.org/10.1038/s41467-021-25539-x.

[30]

Wu SZ, Al-Eryani G, Roden DL, Junankar S, Harvey K, Andersson A, et al. A single-cell and spatially resolved atlas of human breast cancers. Nature Genetics. 2021; 53: 1334–1347. https://doi.org/10.1038/s41588-021-00911-1.

[31]

Cords L, Tietscher S, Anzeneder T, Langwieder C, Rees M, de Souza N, et al. Cancer-associated fibroblast classification in single-cell and spatial proteomics data. Nature Communications. 2023; 14: 4294. https://doi.org/10.1038/s41467-023-39762-1.

[32]

Rozenblatt-Rosen O, Regev A, Oberdoerffer P, Nawy T, Hupalowska A, Rood JE, et al. The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution. Cell. 2020; 181: 236–249. https://doi.org/10.1016/j.cell.2020.03.053.

[33]

Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000; 100: 57–70. https://doi.org/10.1016/s0092-8674(00)81683-9.

[34]

Chen Y, Kim J, Yang S, Wang H, Wu CJ, Sugimoto H, et al. Type I collagen deletion in αSMA+ myofibroblasts augments immune suppression and accelerates progression of pancreatic cancer. Cancer Cell. 2021; 39: 548–565.e6. https://doi.org/10.1016/j.ccell.2021.02.007.

[35]

Chhabra Y, Weeraratna AT. Fibroblasts in cancer: Unity in heterogeneity. Cell. 2023; 186: 1580–1609. https://doi.org/10.1016/j.cell.2023.03.016.

[36]

Sahai E, Astsaturov I, Cukierman E, DeNardo DG, Egeblad M, Evans RM, et al. A framework for advancing our understanding of cancer-associated fibroblasts. Nature Reviews. Cancer. 2020; 20: 174–186. https://doi.org/10.1038/s41568-019-0238-1.

[37]

Biffi G, Oni TE, Spielman B, Hao Y, Elyada E, Park Y, et al. IL1-Induced JAK/STAT Signaling Is Antagonized by TGFβ to Shape CAF Heterogeneity in Pancreatic Ductal Adenocarcinoma. Cancer Discovery. 2019; 9: 282–301. https://doi.org/10.1158/2159-8290.CD-18-0710.

[38]

Öhlund D, Handly-Santana A, Biffi G, Elyada E, Almeida AS, Ponz-Sarvise M, et al. Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. The Journal of Experimental Medicine. 2017; 214: 579–596. https://doi.org/10.1084/jem.20162024.

[39]

Elyada E, Bolisetty M, Laise P, Flynn WF, Courtois ET, Burkhart RA, et al. Cross-Species Single-Cell Analysis of Pancreatic Ductal Adenocarcinoma Reveals Antigen-Presenting Cancer-Associated Fibroblasts. Cancer Discovery. 2019; 9: 1102–1123. https://doi.org/10.1158/2159-8290.CD-19-0094.

[40]

Caligiuri G, Tuveson DA. Activated fibroblasts in cancer: Perspectives and challenges. Cancer Cell. 2023; 41: 434–449. https://doi.org/10.1016/j.ccell.2023.02.015.

[41]

Dominguez CX, Müller S, Keerthivasan S, Koeppen H, Hung J, Gierke S, et al. Single-Cell RNA Sequencing Reveals Stromal Evolution into LRRC15+ Myofibroblasts as a Determinant of Patient Response to Cancer Immunotherapy. Cancer Discovery. 2020; 10: 232–253. https://doi.org/10.1158/2159-8290.CD-19-0644.

[42]

Ho NCW, Yap JYY, Zhao Z, Wang Y, Fernando K, Li CH, et al. Bioengineered Hydrogels Recapitulate Fibroblast Heterogeneity in Cancer. Advanced Science (Weinheim, Baden-Wurttemberg, Germany). 2024; 11: 2307129. https://doi.org/10.1002/advs.202307129.

[43]

Cui Zhou D, Jayasinghe RG, Chen S, Herndon JM, Iglesia MD, Navale P, et al. Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer. Nature Genetics. 2022; 54: 1390–1405. https://doi.org/10.1038/s41588-022-01157-1.

[44]

Zhao G, Zhang X, Meng L, Dong K, Shang S, Jiang T, et al. Single-cell RNA-sequencing reveals a unique landscape of the tumor microenvironment in obesity-associated breast cancer. Oncogene. 2024; 43: 3277–3290. https://doi.org/10.1038/s41388-024-03161-7.

[45]

Chen Z, Zhou L, Liu L, Hou Y, Xiong M, Yang Y, et al. Single-cell RNA sequencing highlights the role of inflammatory cancer-associated fibroblasts in bladder urothelial carcinoma. Nature Communications. 2020; 11: 5077. https://doi.org/10.1038/s41467-020-18916-5.

[46]

Pu W, Shi X, Yu P, Zhang M, Liu Z, Tan L, et al. Single-cell transcriptomic analysis of the tumor ecosystems underlying initiation and progression of papillary thyroid carcinoma. Nature Communications. 2021; 12: 6058. https://doi.org/10.1038/s41467-021-26343-3.

[47]

Thorlacius-Ussing J, Jensen C, Nissen NI, Cox TR, Kalluri R, Karsdal M, et al. The collagen landscape in cancer: profiling collagens in tumors and in circulation reveals novel markers of cancer-associated fibroblast subtypes. The Journal of Pathology. 2024; 262: 22–36. https://doi.org/10.1002/path.6207.

[48]

Ge F, Zeng C, Wang J, Liu X, Zheng C, Zhang H, et al. Cancer-associated fibroblasts drive early pancreatic cancer cell invasion via the SOX4/MMP11 signalling axis. Biochimica et Biophysica Acta. Molecular Basis of Disease. 2024; 1870: 166852. https://doi.org/10.1016/j.bbadis.2023.166852.

[49]

Wang Y, Liang Y, Xu H, Zhang X, Mao T, Cui J, et al. Single-cell analysis of pancreatic ductal adenocarcinoma identifies a novel fibroblast subtype associated with poor prognosis but better immunotherapy response. Cell Discovery. 2021; 7: 36. https://doi.org/10.1038/s41421-021-00271-4.

[50]

Werba G, Weissinger D, Kawaler EA, Zhao E, Kalfakakou D, Dhara S, et al. Single-cell RNA sequencing reveals the effects of chemotherapy on human pancreatic adenocarcinoma and its tumor microenvironment. Nature Communications. 2023; 14: 797. https://doi.org/10.1038/s41467-023-36296-4.

[51]

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. Molecular Cancer. 2023; 22: 170. https://doi.org/10.1186/s12943-023-01876-x.

[52]

Peng J, Sun BF, Chen CY, Zhou JY, Chen YS, Chen H, et al. Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma. Cell Research. 2019; 29: 725–738. https://doi.org/10.1038/s41422-019-0195-y.

[53]

Zhu K, Cai L, Cui C, de Los Toyos JR, Anastassiou D. Single-cell analysis reveals the pan-cancer invasiveness-associated transition of adipose-derived stromal cells into COL11A1-expressing cancer-associated fibroblasts. PLoS Computational Biology. 2021; 17: e1009228. https://doi.org/10.1371/journal.pcbi.1009228.

[54]

Kim H, Watkinson J, Varadan V, Anastassiou D. Multi-cancer computational analysis reveals invasion-associated variant of desmoplastic reaction involving INHBA, THBS2 and COL11A1. BMC Medical Genomics. 2010; 3: 51. https://doi.org/10.1186/1755-8794-3-51.

[55]

Lu Y, Chen D, Wang B, Chai W, Yan M, Chen Y, et al. Single-cell landscape of undifferentiated pleomorphic sarcoma. Oncogene. 2024; 43: 1353–1368. https://doi.org/10.1038/s41388-024-03001-8.

[56]

Kidd S, Spaeth E, Watson K, Burks J, Lu H, Klopp A, et al. Origins of the tumor microenvironment: quantitative assessment of adipose-derived and bone marrow-derived stroma. PloS One. 2012; 7: e30563. https://doi.org/10.1371/journal.pone.0030563.

[57]

Jotzu C, Alt E, Welte G, Li J, Hennessy BT, Devarajan E, et al. Adipose tissue derived stem cells differentiate into carcinoma-associated fibroblast-like cells under the influence of tumor derived factors. Cellular Oncology (Dordrecht, Netherlands). 2011; 34: 55–67. https://doi.org/10.1007/s13402-011-0012-1.

[58]

Song YH, Warncke C, Choi SJ, Choi S, Chiou AE, Ling L, et al. Breast cancer-derived extracellular vesicles stimulate myofibroblast differentiation and pro-angiogenic behavior of adipose stem cells. Matrix Biology: Journal of the International Society for Matrix Biology. 2017; 60-61: 190–205. https://doi.org/10.1016/j.matbio.2016.11.008.

[59]

Strong AL, Pei DT, Hurst CG, Gimble JM, Burow ME, Bunnell BA. Obesity Enhances the Conversion of Adipose-Derived Stromal/Stem Cells into Carcinoma-Associated Fibroblast Leading to Cancer Cell Proliferation and Progression to an Invasive Phenotype. Stem Cells International. 2017; 2017: 9216502. https://doi.org/10.1155/2017/9216502.

[60]

Okumura T, Ohuchida K, Kibe S, Iwamoto C, Ando Y, Takesue S, et al. Adipose tissue-derived stromal cells are sources of cancer-associated fibroblasts and enhance tumor progression by dense collagen matrix. International Journal of Cancer. 2019; 144: 1401–1413. https://doi.org/10.1002/ijc.31775.

[61]

Tang H, Chu Y, Huang Z, Cai J, Wang Z. The metastatic phenotype shift toward myofibroblast of adipose-derived mesenchymal stem cells promotes ovarian cancer progression. Carcinogenesis. 2020; 41: 182–193. https://doi.org/10.1093/carcin/bgz083.

[62]

Miyazaki Y, Oda T, Mori N, Kida YS. Adipose-derived mesenchymal stem cells differentiate into pancreatic cancer-associated fibroblasts in vitro. FEBS Open Bio. 2020; 10: 2268–2281. https://doi.org/10.1002/2211-5463.12976.

[63]

Miyazaki Y, Oda T, Inagaki Y, Kushige H, Saito Y, Mori N, et al. Adipose-derived mesenchymal stem cells differentiate into heterogeneous cancer-associated fibroblasts in a stroma-rich xenograft model. Scientific Reports. 2021; 11: 4690. https://doi.org/10.1038/s41598-021-84058-3.

[64]

Hornburg M, Desbois M, Lu S, Guan Y, Lo AA, Kaufman S, et al. Single-cell dissection of cellular components and interactions shaping the tumor immune phenotypes in ovarian cancer. Cancer Cell. 2021; 39: 928–944.e6. https://doi.org/10.1016/j.ccell.2021.04.004.

[65]

Zhao Z, Mak TK, Shi Y, Li K, Huo M, Zhang C. Integrative analysis of cancer-associated fibroblast signature in gastric cancer. Heliyon. 2023; 9: e19217. https://doi.org/10.1016/j.heliyon.2023.e19217.

[66]

Chen X, Song E. Turning foes to friends: targeting cancer-associated fibroblasts. Nature Reviews. Drug Discovery. 2019; 18: 99–115. https://doi.org/10.1038/s41573-018-0004-1.

[67]

Yang D, Liu J, Qian H, Zhuang Q. Cancer-associated fibroblasts: from basic science to anticancer therapy. Experimental & Molecular Medicine. 2023; 55: 1322–1332. https://doi.org/10.1038/s12276-023-01013-0.

[68]

Cooke VG, LeBleu VS, Keskin D, Khan Z, O’Connell JT, Teng Y, et al. Pericyte depletion results in hypoxia-associated epithelial-to-mesenchymal transition and metastasis mediated by met signaling pathway. Cancer Cell. 2012; 21: 66–81. https://doi.org/10.1016/j.ccr.2011.11.024.

[69]

Rhim AD, Oberstein PE, Thomas DH, Mirek ET, Palermo CF, Sastra SA, et al. Stromal elements act to restrain, rather than support, pancreatic ductal adenocarcinoma. Cancer Cell. 2014; 25: 735–747. https://doi.org/10.1016/j.ccr.2014.04.021.

[70]

Feig C, Jones JO, Kraman M, Wells RJB, Deonarine A, Chan DS, et al. Targeting CXCL12 from FAP-expressing carcinoma-associated fibroblasts synergizes with anti-PD-L1 immunotherapy in pancreatic cancer. Proceedings of the National Academy of Sciences of the United States of America. 2013; 110: 20212–20217. https://doi.org/10.1073/pnas.1320318110.

[71]

Krishnamurty AT, Shyer JA, Thai M, Gandham V, Buechler MB, Yang YA, et al. LRRC15+ myofibroblasts dictate the stromal setpoint to suppress tumour immunity. Nature. 2022; 611: 148–154. https://doi.org/10.1038/s41586-022-05272-1.

[72]

Ortiz-Muñoz G, Brown M, Carbone CB, Pechuan-Jorge X, Rouilly V, Lindberg H, et al. In situ tumour arrays reveal early environmental control of cancer immunity. Nature. 2023; 618: 827–833. https://doi.org/10.1038/s41586-023-06132-2.

[73]

Daquinag AC, Tseng C, Zhang Y, Amaya-Manzanares F, Florez F, Dadbin A, et al. Targeted Proapoptotic Peptides Depleting Adipose Stromal Cells Inhibit Tumor Growth. Molecular Therapy: the Journal of the American Society of Gene Therapy. 2016; 24: 34–40. https://doi.org/10.1038/mt.2015.155.

[74]

Rupert J, Daquinag A, Yu Y, Dai Y, Zhao Z, Kolonin MG. Depletion of Adipose Stroma-Like Cancer-Associated Fibroblasts Potentiates Pancreatic Cancer Immunotherapy. Cancer Research Communications. 2025; 5: 5–12. https://doi.org/10.1158/2767-9764.CRC-24-0298.

Funding

Levy-Longenbaugh Fund

Bovay Foundation

PDF (1014KB)

0

Accesses

0

Citation

Detail

Sections
Recommended

/