Abstract
Background/Aim: Transforming growth factor-β (TGF-β) plays a significant role in the formation of different cancer subtypes. There is evidence that TGF-β pathways promote cancerogenic cell characteristics but also have tumor-suppressor capabilities. The tyrosine kinase inhibitors nilotinib, dasatinib, erlotinib, gefitinib, and everolimus are approved as targeted therapies for several tumor entities, including head and neck squamous cell carcinoma (HNSCC). This study aimed to investigate the effects of these substances on the expression levels of TGFβ1 and TGF-β receptor type 2 (TGFβR2) in HPV-negative and HPV-positive SCC cell cultures. Materials and Methods: Expression patterns of TGFβ1 and TGFβR2 were determined using enzyme-linked immunosorbent assay (ELISA) in three HNSCC cell lines (i.e., HNSCC-11A, HNSCC-14C, and CERV196). These cells were incubated with nilotinib, dasatinib, erlotinib, gefitinib, and everolimus (20 μmol/l) and compared to a chemonaive control. An assessment of concentration levels was conducted after 24, 48, 72, and 96 h of treatment. Results: Statistically significant changes in the expression levels of TGFβ1 and TGFβR2 were found in all tested cell cultures (p<0.05) compared to the negative control. An increase in TGFβ-R2 expression was detected after treatment with most of the tested tyrosine kinase inhibitors, whereas a reduction in TGFβ1 was observed. The addition of everolimus had the opposite effect on both TGFβR2 and TGF-B1- expression. Conclusion: Expression of TGFβ1 and TGFβR2 was detected in all cultured HNSCC cell lines. Nilotinib, dasatinib, erlotinib, gefitinib, and everolimus had an impact on the expression levels of TGFβ1 and TGFβR2 in vitro.
Squamous cell carcinomas are the most common subtype of neoplasia in the head and neck region, accounting for about 90% of head and neck cancer cases (1). The consumption of tobacco, alcohol, and viral infections, especially with high-risk subtypes of the human papillomavirus (HPV) have been identified as the primary risk factors for the development of head and neck squamous cell cancer (HNSCC) (2, 3). Despite our increased understanding of tumor development and multimodal, interdisciplinary therapeutic approaches, the 5-year survival rate of HNSCC patients has improved only marginally during the past 30 years and remains at ≤50% (4, 5). Especially for advanced HNSCC, therapeutic options are limited (6).
The identification of key signaling pathways as well as new targets for chemotherapeutic treatment options and different drugs have been investigated intensively (7-9). Dysregulated transforming growth factor-β (TGF-β) signaling is described in several types of cancer, including HNSCC (10). There is evidence that this deregulation plays a vital role in the emergence of HNSCC (11-13). According to the available literature, TGF-β may have paradoxical effects in the tumor microenvironment. TGF-β is a tumor suppressor in normal epithelial cells or in the early stages of oncogenesis. However, TGF-β also plays an important role in tumor progression (14, 15).
TGF-β is a cytokine secreted by tumor and stromal cells in the tumor microenvironment (10). Latent TGF-β cytokines are located in the extracellular matrix. After activation, TGF-β ligands bind to TGF-β receptor type 2 (TGFβR2), which phosphorylates TGF-β receptor type 1 (TGF-βR1), the other essential component of this bipartite transmembrane receptor (16). Activated TGF-βR1 phosphorylates receptor-regulated intracellular Smad proteins, including Smad2 and Smad (Smad2/3), which build a complex with Smad4, translocate to the nucleus and bind to specific DNA sequence motifs called Smad-binding elements (SBEs). Upon binding, pSmad2/3-Smad4 complexes interact with additional transcriptional regulators to transactivate TGF-β-responsive target genes (17, 18).
The ability of TGF-β signaling to activate target genes enables the pathway to impact diverse cellular processes, including not only proliferation but also differentiation, migration, apoptosis, and extracellular matrix remodeling (16). However, the role of TGF-β is not entirely understood. This study aimed to illuminate the impact of tyrosine kinase inhibitors on the expression of TGF-β and TGF-β receptor type II in SCC.
Materials and Methods
This study was conducted in the Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital Mannheim, Germany. The study protocol was approved and reviewed by the local ethics committee board (reference number: 2018-552N). The protocol was performed in accordance with the guidelines of the Declaration of Helsinki.
Cell lines. The three tumor cell lines used in the study derived from human squamous cell carcinomas. Two human HPV16-negative squamous cancer cell lines [University of Michigan Squamous Cell Carcinoma (HNSCC)] provided by T.E. Carey, Ph.D. (University of Michigan, Ann Arbor, MI, USA), and one human HPV16-positive squamous cancer cell line (CERV196; Cell Lines Service GmbH, Eppelheim, BW, Germany) were examined. The HPV16-negative cell lines were harvested from a skin metastasis of an oral cavity squamous cell carcinoma (SCC) of the floor of the mouth after surgery and radiochemotherapy (HNSCC-14C) and from an untreated laryngeal SCC of the epiglottis (HNSCC-11A). The HPV16-positive cell line descended from a cervix SCC.
Drugs used in the study. The detailed study protocol and tested substances were described earlier by Kramer et al. (8). Additionally to the tyrosine kinase inhibitors erlotinib, gefitinib, nilotinib, and dasatinib, everolimus was tested. The substances were provided by Prof. Dr. Hofheinz (Oncological Department, University Hospital Mannheim, Medical Faculty Mannheim, University of Heidelberg, BW, Germany). All drugs were stored at room temperature and dissolved in dimethyl sulfoxide when needed. A concentration of 20 μmol/l of each drug was added to the cultures, and the cells were incubated at 37°C for 24, 48, 72, and 96 h. Untreated cells served as negative controls under identical conditions.
Cell proliferation. The alamarBlue® (AbD Serotec, Raleigh, NC, USA) cell proliferation assay was used to assess the proliferation of HNSCC cells, following the manufacturer’s protocol. The active ingredient is resazurin, a non-toxic, cell permeable compound. This ingredient is blue in color and virtually non-fluorescent. After passing the cell membrane, resazurin is reduced to resorufin, a compound that is red in color and highly fluorescent. This effect allows to identify viable cells as the overall fluorescence increases continuously. AmarBlue® reagent is added as 10% of the sample volume, followed by a 1-4 h incubation at 37°C. The resulting fluorescence is read on a plate reader or fluorescence spectrophotometer. For analysis, fluorescence intensity (or absorbance) is plotted versus compound concentration. The fluorescence intensity of alamarBlue® reagent is directly proportional to the cell number.
Enzyme-linked immunosorbent assay (ELISA). ELISA was used for TGFβ1 and TGFβ-R2. The experiments were repeated at least three times (n=3). The concentrations of all proteins were measured using the DuoSet ELISA kit (DYC391, R&D Systems, Wiesbaden, Hessen, Germany). An MRX Microplate Reader (DYNEX Technologies, Chantilly, VA, USA) was used to measure optical density at a wavelength of 450 nm and wavelength correction of 540 nm. The detection range was 250-16,000 pg/ml for IGF1R. The interassay coefficient of variation provided by the manufacturer was below 10%.
Statistical analysis. The data are normalized and a ratio of TGFβ1/TGFβR2 expression after treatment with the respective drugs and the negative control is presented. The absolute concentration levels are given in the Tables. Results are represented by mean values ± standard deviation. SAS 9.3 software (SAS Institute, Inc., Cary, NC, USA) was used for the two-coefficient variance tests and Dunnett’s test. A p-value of ≤0.05 was considered to indicate a statistically significant difference between the TGFβ1 and TGFβR2 expression level and the untreated, negative control.
Results
TGFβ1 and TGFβR2 expression was detected in all three cultured cell lines. Expression levels differed among the three cell lines. The highest expression levels were found in the HNSCC-11A, followed by HNSCC-14C. The results for TGFβ1 expression are shown in Table I and Figure 1. Table II and Figure 2 show the results for TGFβR2 expression.
ELISA of TGFβ1 expression in head and neck squamous cell carcinoma (HNSCC) 11A, 14C, and CERV196 cells after incubation with nilotinib, dasatinib, erlotinib, gefitinib and everolimus in a concentration of 20 μmol/l compared to the negative control in pg/ml. Significant results with p<0.05 are depicted in bold.
TGFβ1 expression in HNSCC-11A, -14C, and CERV196 cells after incubation with gefitinib, nilotinib, dasatinib, erlotinib or everolimus in the concentration of 20 mol/l. Data are presented as expression levels relative to the negative control ± standard deviation. Significant differences are highlighted with asterisks.
ELISA of TGFβR2 expression in HNSCC 11A, 14C, and CERV 196 cells after incubation with nilotinib, dasatinib, erlotinib, gefitinib and everolimus in a concentration of 20 μmol/l compared to the negative control in pg/ml. Significant results with p<0.05 are depicted in bold.
TGFβR2 expression in HNSCC-11A, -14C, and CERV196 cells after incubation with gefitinib, nilotinib, dasatinib, erlotinib or everolimus in the concentration of 20 mol/l. Data are presented as expression levels relative to the negative control ± standard deviation. Significant differences are highlighted with asterisks.
Transforming growth factor-β1 (TGFβ1). For TGFβ1, all measured concentrations after incubation with tyrosine kinase inhibitors were lower than their corresponding values in the negative control at 96 h (Figure 1). Yet, these reductions were not statistically significant in all cases, with p>0.05.
Significant changes in the TGFβ1 concentration due to drug exposure were detected in all three cell lines. In the HNSCC-11A cell line, a significant reduction was observed after treatment with all substances for 24 h. At 72 h, we also found a reduction in TGFβ1 expression levels for the substances nilotinib, erlotinib, and gefitinib (Figure 1); however, the significance level was not reached for dasatinib and everolimus (Table I). In the HNSCC-14C cell line, there was a significant reduction at only one time point for the substances erlotinib and everolimus at 96 h and 48 h, respectively. A significant reduction was found in the CERV196 cell line for all tested substances, except dasatinib, when measured at 24 h (Figure 1).
For everolimus, we found a significant increase in the TGFβ1 concentration after 96 h in the HNSCC-11A cell line (Figure 1). In the HNSCC-14C cell line, a non-significant reduction of TGFβ1 was found at 96 h, and in the CERV196 cell line, a non-significant increase in TGFβ1 concentration was observed. There was a continuous increase in TGFβ1 expression in the HNSCC-11A cell line and the CERV196 cell line under everolimus. The concentrations after 24 h of treatment were significantly lower in the HNSCC-11A and CERV196 cell lines compared to the negative control with p=0.0138 and p=0.0181, respectively. The concentration levels found after 96 h were even higher than the negative control, with significant results in the HNSCC-11A cell line (p<0.02). The detailed results are depicted in Figure 1.
TGF-β receptor type 2 (TGFβR2). Significant changes in the TGFβR2 concentration due to drug exposure were detected in all three cell lines at different measurement times. In the cell lines HNSCC-11A and CERV196, significant results were obtained for all tyrosine kinase inhibitors. HNSCC-14C results that met the level of significance were determined only when exposed to nilotinib and dasatinib after 48 h. TGFβR2 expression levels fluctuated over the course of time in the negative controls. In the HNSCC-11A cell line, TGFβR2 expression was reduced significantly by nilotinib at 24 h with (p<0.001), yet at 72 h and 96 h, a significant increase of TGFβR2 was detected (p<0.01). In the HNSCC-14C and CERV196 cell lines, nilotinib increased TGFβR2 levels after 24 and 72 h of treatment (p=0.013 and p=0.012). Regarding dasatinib, significantly increased levels of TGFβR2 were detected after 72 h (p<0.001) in the HNSCC-11A cell line and at 48 h in the HNSCC-14C and CERV196 cell lines (p=0.026 and p<0.01). Under the influence of erlotinib, a significant reduction in TGFβR2 expression was observed at 24 h in the HNSCC-11A line. However, at 48 and 72 h, a significant increase was detected (p<0.001 and p<0.01). In the CERV196 cell line, erlotinib increased TGFβR2 expression significantly after 96 h (p<0.01). Regarding gefitinib, significantly increased expression levels were found in the HNSCC-11A cell line at 72 h and 96 h (p<0.001 and p<0.01), and at 48 h in the CERV196 culture (p=0.02). Treatment of the cell lines with everolimus did not significantly change the expression levels of TGFβR2 (Figure 2).
Discussion
TGFβ signaling pathways are involved in a wide variety of physiological processes (19). However, TGFβ signaling plays a particularly complex role in neoplastic diseases, as TGFβ proteins function as both tumor suppressors and promoters (10, 20). TGFβ1 and TGFβR2 were detected in all three cell lines. Analogous to Bedi et al. and Wang et al., the lowest concentration levels of the controls without drug exposure were, with one exception (HNSCC-14C after 24 h), found in the CERV196 cell line (21, 22).
Expression levels of TGFβ1 and TGFβR2 fluctuated over time in the negative control and also in the treatment groups. All samples (negative control and treatment groups) were treated the same way. After the initial measurement (0 h), the cells were divided into the untreated negative control and the treatment groups. Data are represented as ratios between the treatment groups and the negative control in order to cancel out systematic effects of measurement and treatment. The defining uncertainty of our measurements is therefore the statistic uncertainty, which is determined as the standard deviation of the nominal values measured in three independent repetitions of experiments. The limitation of our study is the number of repetitions and insignificant fluctuations in the expression levels in the negative control might be less pronounced with more experiments.
Significant changes in the expression of TGFβ1 and TGFβR2 occurred with both nilotinib and dasatinib treatment. While the concentration of the receptor changed significantly in all cell lines by both substances examined, significant changes of the ligand could only be detected in two cell lines under nilotinib and in only one cell line under dasatinib. The possible influences of these kinase inhibitors on signaling cascades of the TGFβ family have already been described in previous studies. Bartscht et al. showed that dasatinib could inhibit TGFβ1-induced gene expression and cell migration in pancreatic carcinomas (23). Analogous to the data collected in our study for the HNSCC-11A cell line, Cacchia et al. found a dasatinib-induced reduction in the TGFβ1 concentration in thyroid carcinoma cells. Furthermore, Nomura et al. found a reduction in the TGFβ1 plasma concentration in patients with chronic myelogenous leukemia (CML) undergoing therapy with dasatinib or nilotinib (24, 25). Our results suggest that TGFβ proteins may be influenced by the target structures of the tyrosine kinase inhibitors used. In the literature, there is evidence of connection between TGFβ and platelet-derived growth factor (PDGF) signals in various tumors. In a liver metastasis model based on colorectal cancer cells, a dasatinib-induced increase of platelet-derived growth factor receptor alpha (PDGFR-a) in hepatic stellate cells was demonstrated, which led to an increase in the expression of TGFβR2. Since suppression of PDGFR-a also resulted in reduced tumor cell proliferation and migration, the functional significance of such correlations in tumor metastasis is suggested (26). In addition, there are other possible mechanisms that influence the expression of the TGFβ family. Connections between the TGFβ proteins and the stem cell factor (SCF), a ligand of the receptor tyrosine kinase c-Kit, may also change the expression of TGFβ proteins. In hepatic cell cancer, it has been shown that TGFβ1 expression is influenced by an SCF-dependent, STAT3-mediated autocrine feedback. The inhibition of SCF and STAT3 can reduce TGFβ1 transcription. Interrupting this feedback by switching off SCF or STAT3 also prevented TGFβ1-induced migration of tumor cells and reduced their proliferation (27). Although the data collected do not allow any specific statements about the underlying connections between the TGFβ proteins and the mechanisms described in the cell lines examined in this work, it seems reasonable to assume that similar connections may exist between the target molecules of nilotinib or dasatinib and proteins of the TGFβ family also in HNSCCs. Further studies are needed to explore explicit connections between the target proteins and the selective tyrosine kinase inhibitors.
Incubation with erlotinib and gefitinib led to significant changes in the concentration of TGFβ1 and TGFβR2. One possible explanation may be found in the literature that describes the connection between TGFβ proteins and the epidermal growth factor receptor (EGFR). Xu et al. showed that the synergistic effect of the signaling pathways of TGFβ and epidermal growth factor (EGF) in ovarian carcinoma cells can lead to the acquisition of a more invasive phenotype (28). Richter et al. demonstrated that co-stimulation with EGF and TGFβ1 significantly increases the invasive properties of oral SCC cells compared to stimulation with either factor (29). Therefore, an interaction of EGFR and TGFβ signals may play a critical role during the spread of malignant tumors. Thus, a reduction in TGFβ1 under erlotinib and gefitinib, as detected in this study in all cell lines, could indicate a tumor-suppressive mechanism. In the context of head and neck carcinomas, it has been shown that TGFβ-activated tumor-associated fibroblasts can impair the efficacy of EGFR antagonists (30). Bedi et al. detected significantly higher levels of TGFβ in erlotinib- or cetuximab-resistant variants of a HNSCC cell line than in erlotinib- or cetuximab-sensitive cells. In addition, they observed increased resistance to erlotinib therapy in various HNSCCs upon treatment with TGFβ1 or 3. Therefore, Bedi et al. concluded that elevated TGFβ levels in the tumor microenvironment may impair the efficacy of EGFR antagonists in vivo. The authors also demonstrated that adding a TGFβ antibody to cetuximab improved its efficiency in vivo and significantly extended the tumor-free survival of laboratory animals compared to monotherapy with one of these two substances (21). However, the significant decrease in the concentration of the TGFβ ligand under erlotinib and gefitinib and the increase in the expression of the receptor recorded in the present study suggest the absence of such resistance mechanisms in the cell lines examined here. Therefore, further studies are needed to reveal the underlying regulatory mechanisms in HNSCCs.
Under the influence of everolimus, significant concentration changes were only recorded for TGFβ1. In all three cell lines, the concentration of TGFβ1 decreased due to the mTOR inhibitor. However, in the HNSCC-11A cell line, a significant increase was detected at the time of measurement after 96 h. These heterogeneous results are consistent with the available literature. Two clinical studies investigated the therapeutic effect of everolimus in HNSCC. Geiger et al. found no significant therapeutic effects with everolimus in patients with recurrent or metastatic diseases (31). Based on these results, Massarelli et al. did not find therapeutic benefits of the combination of everolimus and erlotinib in patients with platinum-resistant HNSCC (32). As outlined here, the targeted inhibition of mTOR can result in the suppression of TGFβ-induced oncogenic processes. Therefore, squamous cancer cells could potentially react in a similar manner indicating a connection between both signaling pathways.
Conclusion
To date, this study represents the first examination of the impact of gefitinib, erlotinib, dasatinib, nilotinib, and everolimus on the expression profiles of TGFβ1 and TGFβR2 in both HPV-positive and HPV-negative squamous cell carcinoma in vitro. The TGFβ proteins are particularly important in the context of the migration and invasion of tumors. Accordingly, there is a need to identify therapies that can effectively influence TGFβ-mediated mechanisms. A significant reduction in TGFβ1 and an increase in TGFβR2 may be interpreted as indicators of such an effect. These effects were detected in this study for most of the tested substances. The findings also suggest potential innovative avenues for further exploration of novel strategies with regard to the TGFβ pathway in the targeted therapy of head and neck squamous cell carcinoma.
Acknowledgements
Professor C. Weiss (Head of the Department of Medical Statistics, Biomathematics and Information Processing, Medical Faculty Mannheim, University of Heidelberg, Germany) supported us in the statistical evaluation.
Footnotes
Authors’ Contributions
Lena Huber: scientific writing, review and editing; Manuel Thomas Knüttel: data collection and analysis; Benedikt Kramer: conceptualization, methodology, data curation; Anne Lammert, Nicole Rotter, Lena Zaubitzer, Claudia Zaubitzer: scientific support, proofreading; Daniel Häussler: scientific writing, data analysis.
Conflicts of Interest
The Authors declare that there are no conflicts of interest in relation to this study.
Funding
No funding applied to this study.
- Received March 25, 2024.
- Revision received June 5, 2024.
- Accepted June 6, 2024.
- Copyright © 2024 The Author(s). Published by the International Institute of Anticancer Research.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
