Fibroblasts have been researched consistently over the years, including multiple studies on the role of cancer-associated fibroblasts (CAFs), which have demonstrated the complexity of the interaction between CAFs and cancer cells. CAFs are activated fibroblasts, also called myofibroblasts, which have been associated with cancer and have been shown to play an important role in the dynamics of the stroma, also known as the tumor microenvironment (TME). Typically fibroblasts are quiescent and will only become activated when there is a biological need for wound healing; these activated fibroblasts can be identified by their expression of different markers such as α-smooth muscle actin (αSMA) (1). Because a tumor is technically a wound that will not heal, activated fibroblasts respond similarly as they would to injury. This response includes the recruitment of CAFs to tumor sites, which physiologically mimics excessive fibrosis secondary to chronic inflammation and aging (2). This recruitment is primarily controlled by growth factors such as TGF-β, but also cytokines, chemokines, and even cyclo-oxygenase-2; however, the exact means by which fibroblasts differentiate into CAFs are still being elucidated (3). It has been reported by different groups that CAFs are a prognostic marker of poor survival outcomes (4–6). Transcriptomic signatures of tumors have been assessed for their prognostic value, but a major component of this tumor transcriptome comes from the TME rather than the cancer cells themselves (7). In fact, many of the genes that correlate with a poor prognosis are actually derived from CAFs (8). Association between CAFs and poor prognosis is particularly true for colorectal cancer. A higher expression of CAF-associated genes, or even transcriptomic subgroups enriched with signals related to the epithelial-to-mesenchymal transition, have been associated with higher mortality. This is possibly secondary to the role of CAFs in promoting invasion and metastasis through TGF-β signaling, angiogenesis, matrix remodeling, and complement-mediated inflammation (9–11). In this issue of the Journal, Hanley et al. report that the transdifferentiation of fibroblasts to myofibroblasts depends on the enzyme NAD(P)H oxidase 4 (NOX4), thus highlighting the potential of NOX4 inhibitors to be explored as targeted therapies in multiple cancers shown to display a CAF-associated phenotype (12). They used whole transcriptome sequencing (RNA-seq) of fibroblasts stimulated with TGF-β to characterize changes occurring during the activation process. NOX4 was the most upregulated gene identified, and with further elegant in vitro and in vivo experiments, they determined that inhibition of NOX4 nullified TGF-β-dependent reactive oxygen species (ROS) production as well as myofibroblast differentiation. Ultimately they show that NOX4 contributes to a TGF-β-independent delayed ROS phase that is required for myofibroblast differentiation (Figure 1) (13–15). Figure 1. View largeDownload slide Fibroblast-to-myofibroblast transdifferentiation and contribution to tumor stroma and metastasis. NOX4 inhibitors were shown by Hanley et al. (12) to abrogate myofibroblast differentiation. ALK5 = activin-like kinase 5; αSMA = alpha smooth muscle actin; CAF = cancer associated fibroblast; NOX4 = NAD(P)H oxidase 4; NADPH = nicotinamide adenine dinucleotide phosphate; ROS = reactive oxygen species; TGF-β = transforming growth factor beta. Figure 1. View largeDownload slide Fibroblast-to-myofibroblast transdifferentiation and contribution to tumor stroma and metastasis. NOX4 inhibitors were shown by Hanley et al. (12) to abrogate myofibroblast differentiation. ALK5 = activin-like kinase 5; αSMA = alpha smooth muscle actin; CAF = cancer associated fibroblast; NOX4 = NAD(P)H oxidase 4; NADPH = nicotinamide adenine dinucleotide phosphate; ROS = reactive oxygen species; TGF-β = transforming growth factor beta. Hanley et al. found that NOX4 was upregulated in a variety of tumors including head and neck cancers (HNSCC), esophageal carcinoma, colorectal cancers, breast carcinomas, and lung carcinomas. From the RNA-seq data of the tumor samples, they were able to correlate NOX4 expression with previously identified markers of CAFs including FAP, THY1, DCN, COL1A1/2, and COL6A1/2/3 and used immunohistochemistry to confirm that NOX4 expression was indeed from stromal regions (16). These data suggested NOX4 as a potential therapeutic target, prompting the team to isolate CAFs from HNSCC, esophageal carcinoma, colorectal cancers, and non–small cell lung cancer tumor samples and perform a pharmacological and genetic manipulation via the NOX4 inhibitor GKT137831 and shRNA, respectively. They subsequently observed a suppression of ROS production, αSMA expression, and migration. To further analyze NOX4 inhibition, they assessed GKT137831 in a xenograft murine model. HNSCC cells (5PT) were cocultured with HFFF2 fibroblasts, which have shown capacity to differentiate epithelial cells, demonstrating that downregulation of NOX4 resulted in a reduction of the myofibroblast compartment, subsequently impacting tumor growth. This effect was not seen in the absence of HFFF2 injection, thus suggesting that NOX4 inhibition acts directly on the tumor stroma. This work brings CAF-targeted therapies back to the forefront because the previous attempts to implement them clinically have not demonstrated any activity (17–19). Both Hedgehog signaling inhibition and CAF depletion proved to be ineffective in phase II clinical trials, signifying an obstacle as research moves forward. However, these interventions were well tolerated, and therefore have demonstrated that CAF depletion in human subjects has a favorable safety profile. Furthermore, a recent clinical trial employed the NOX4 inhibitor GKT137831 in an attempt to inhibit renal fibrosis in diabetic patients, and an excellent tolerance among participants was observed (NCT02010242). Although this inhibitor has not been assessed in cancer as of yet, it could be a potential future direction for this field. While Hanley et al. touched on the prognostic significance of αSMA, they did not focus on the prognostic value of NOX4, which could prove to be an earlier prognostic marker given its role in fibroblast-to-myofibroblast differentiation, which occurs prior to the development of the αSMA phenotype. Overall, while the idea of depleting CAFs in cancer patients is a logical approach, the clinical data have not yet demonstrated the benefit of these treatments. Coculture models using novel patient-derived organoids would be an essential tool for studying the activity of agents against CAFs. These models would allow different stroma components to be evaluated for their value as targets and simultaneously provide a platform for studying cell-cell interactions between CAFs and epithelial cells. Theoretically, stromal components could be separated by flow cytometry using different markers and then cocultured with the epithelium. The effects of drugs targeting NOX4 or other pathways relevant for other cells types in the TME could then be assessed within each compartment, thus elucidating the specificity of the specific mechanism of action as recently demonstrated in pancreatic cancer organoids (20). While the results yielded by Hanley et al. are promising, more research is certainly needed to see if there is a place for NOX4 inhibition and CAF-directed therapies in clinical cancer treatments. Note The authors declare no potential conflicts of interest. References 1 Kalluri R. The biology and function of fibroblasts in cancer. Nat Rev Cancer. 2016; 16( 9): 582– 598. Google Scholar CrossRef Search ADS PubMed 2 Dimmeler S, Zeiher AM. Netting insights into fibrosis. N Engl J Med. 2017; 376( 15): 1475– 1477. Google Scholar CrossRef Search ADS PubMed 3 Koliaraki V, Pallangyo CK, Greten FR, Kollias G. Mesenchymal cells in colon cancer. gastroenterology. 2017; 152( 5): 964– 979. Google Scholar CrossRef Search ADS PubMed 4 Erez N, Truitt M, Olson P, Arron ST, Hanahan D. Cancer-associated fibroblasts are activated in incipient neoplasia to orchestrate tumor-promoting inflammation in an NF-kappaB-dependent manner. Cancer Cell. 2010; 17( 2): 135– 147. Google Scholar CrossRef Search ADS PubMed 5 Marsh D, Suchak K, Moutasim KA, et al. Stromal features are predictive of disease mortality in oral cancer patients. J Pathol. 2011; 223( 4): 470– 481. Google Scholar CrossRef Search ADS PubMed 6 Underwood TJ, Hayden AL, Derouet M, et al. Cancer-associated fibroblasts predict poor outcome and promote periostin-dependent invasion in oesophageal adenocarcinoma. J Pathol. 2015; 235( 3): 466– 477. Google Scholar CrossRef Search ADS PubMed 7 Isella C, Terrasi A, Bellomo SE, et al. Stromal contribution to the colorectal cancer transcriptome. Nat Genet. 2015; 47( 4): 312– 319. Google Scholar CrossRef Search ADS PubMed 8 De Vlieghere E, Verset L, Demetter P, Bracke M, De Wever O. Cancer-associated fibroblasts as target and tool in cancer therapeutics and diagnostics. Virchows Arch Int J Pathol. 2015; 467( 4): 367– 382. Google Scholar CrossRef Search ADS 9 Calon A, Tauriello DVF, Batlle E. TGF-beta in CAF-mediated tumor growth and metastasis. Semin Cancer Biol. 2014; 25: 15– 22. Google Scholar CrossRef Search ADS PubMed 10 Calon A, Lonardo E, Berenguer-Llergo A, et al. Stromal gene expression defines poor-prognosis subtypes in colorectal cancer. Nat Genet. 2015; 47( 4): 320– 329. Google Scholar CrossRef Search ADS PubMed 11 Dienstmann R, Vermeulen L, Guinney J, Kopetz S, Tejpar S, Tabernero J. Consensus molecular subtypes and the evolution of precision medicine in colorectal cancer. Nat Rev Cancer. 2017; 17( 4): 268. Google Scholar CrossRef Search ADS PubMed 12 Hanley CJ, Massimiliano M, Ford K, et al. Targeting the myofibroblastic cancer-associated fibroblast phenotype through inhibition of NOX4. J Natl Cancer Inst. 2017; 110( 1): 109– 120. 13 Hinz B, Phan SH, Thannickal VJ, Galli A, Bochaton-Piallat M-L, Gabbiani G. The myofibroblast: One function, multiple origins. Am J Pathol. 2007; 170( 6): 1807– 1816. Google Scholar CrossRef Search ADS PubMed 14 Duffield JS, Lupher M, Thannickal VJ, Wynn TA. Host responses in tissue repair and fibrosis. Annu Rev Pathol. 2013; 8: 241– 276. Google Scholar CrossRef Search ADS PubMed 15 Desmoulière A, Geinoz A, Gabbiani F, Gabbiani G. Transforming growth factor-beta 1 induces alpha-smooth muscle actin expression in granulation tissue myofibroblasts and in quiescent and growing cultured fibroblasts. J Cell Biol. 1993; 122( 1): 103– 111. Google Scholar CrossRef Search ADS PubMed 16 Tirosh I, Izar B, Prakadan SM, et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science. 2016; 352( 6282): 189– 196. Google Scholar CrossRef Search ADS PubMed 17 Narra K, Mullins SR, Lee H-O, et al. Phase II trial of single agent Val-boroPro (Talabostat) inhibiting fibroblast activation protein in patients with metastatic colorectal cancer. Cancer Biol Ther. 2007; 6( 11): 1691–169. Google Scholar CrossRef Search ADS PubMed 18 Catenacci DVT, Junttila MR, Karrison T, et al. Randomized phase Ib/II study of gemcitabine plus placebo or vismodegib, a hedgehog pathway inhibitor, in patients with metastatic pancreatic cancer. J Clin Oncol. 2015; 33( 36): 4284– 4292. Google Scholar CrossRef Search ADS PubMed 19 Hofheinz R-D, al-Batran S-E, Hartmann F, et al. Stromal antigen targeting by a humanised monoclonal antibody: An early phase II trial of sibrotuzumab in patients with metastatic colorectal cancer. Onkologie. 2003; 26( 1): 44– 48. Google Scholar PubMed 20 Öhlund D, Handly-Santana A, Biffi G, et al. Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. J Exp Med. 2017; 214( 3): 579– 596. Google Scholar PubMed © The Author 2017. 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JNCI: Journal of the National Cancer Institute – Oxford University Press
Published: Aug 9, 2017
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