HER3/CYLD axis mediates ovarian cancer cell resistance to chemotherapy via upregulation of ABCB1

doi:10.21203/rs.3.rs-1756290/v1

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HER3/CYLD axis mediates ovarian cancer cell resistance to chemotherapy via upregulation of ABCB1

https://doi.org/10.21203/rs.3.rs-1756290/v1

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Background: Ovarian cancer (OC) is the most pathogenic gynecological malignant tumor in the world. Due to the difficulty of early diagnosis, most of patients developed chemo-resistance and recurrence during/after the chemotherapy. Cylindromatosis (CYLD) is one member of lysine 63 deubiquitinases, and the regulatory mechanism of CYLD in mediating cisplatin (DDP) resistance need to be elucidated.

Methods: Database analysis indicated that CYLD was associated with tumor development and prognosis; Patient tumor samples and clinicopathological characteristics were used to study the clinical significance of CYLD. Molecular biological methods were used to verify the function of CYLD in chemo-resistance with the parental and drug resistant cell lines (A2780/ A2780-DDP, OVCAR3/OVCAR3-DDP). Then flow cytometry analysis, co-IP and ChIP analysis were conducted to identify the upstream regulators and downstream effectors of CYLD; The drug combination method was used to investigate the drug synergistic effect of cisplatin combination with ABCB1 inhibitor or HER3 inhibitor. Animal models were further used to verify the role of CYLD in cancer chemo-resistance.

Results: The expression levels of CYLD were downregulated in pan-cancer, especially in ovarian cancer, leading to acceleration of tumor progression and cisplatin resistance. CYLD knockdown in the parental cells was sufficient to induce DDP resistance through inhibiting cell apoptosis and promoting the drug efflux via inducing the expression of ABCB1. HER3 expression levels were much higher in the resistant cells, and HER3 was the upstream mediator for CYLD suppression through STAT3 signaling. Moreover, overexpression of CYLD in the resistant cells was sufficient to promote sensitivity to platinum-based treatment both in vitro and in vivo. ABCB1 was a functional downstream target of CYLD to regulate tumor growth and drug resistance both in vitro and in vivo.

Conclusions: In this study, the results demonstrated that higher HER3 expression rendered CYLD suppression, consequently, increased cisplatin resistance and induced poor prognosis by inhibiting cell apoptosis and promoting the drug efflux in OC. Our findings showed that HER3/CYLD/ABCB1 is a new signaling pathway to regulate tumor growth and DDP resistance, which are potential new therapeutic targets to overcome DDP resistance.

Ovarian cancer

CYLD

Chemoresistance

HER3

ABCB1

Therapeutic target

Ovarian Cancer (OC) is the most lethal gynecological cancer. Due to difficult detection at early stage[1] and lack of significant clinical symptoms[2], 70% patients were diagnosed at an advanced stage (III-IV stage)[3], which also caused treatment failure. The most common histological type of ovarian cancer is epithelial ovarian carcinoma(EOC)[4], and the standard front-line treatment for EOC is constituted of surgery with the goal of no residual disease (R0) and platinum-based chemotherapy[5]. However, even after strict surgery and adequate chemotherapy, the survival rate of advanced ovarian cancer patients remains limited[6]. The prognosis of patients is closely associated with patients’ response to cisplatin treatment, 19% of early ovarian cancers and 60%-85% of recurrent ovarian cancers would eventually develop resistance to platinum[2]. Therefore, there is urgent need to elucidate new molecular mechanisms of drug resistance in ovarian cancer.

Cisplatin (DDP), one of platinum drugs, exerts anticancer activity by forming Pt-DNA adducts and mediating DNA dysfunction[7, 8], eventually lead to cell apoptosis and exert anti-tumor effects[9]. Preclinical and clinical studies showed that several mechanisms may be relevant with DDP resistance, such as increased drug efflux, inactivation of apoptosis, increased DNA repair and alteration in drug target genes[10, 11]. The decreasing levels of apoptosis and increasing levels of drug efflux were demonstrated to be the main causes of drug resistance in ovarian cancer [12]. Several molecular pathways underlying platinum resistance were revealed through recent scientific research, and these insights may contribute to the development of alternative treatment approaches. However, new mechanism of cisplatin resistance in OC is still not fully understood yet. The effective combinational drug therapy method for OC remains to be investigated.

HER3, a pseudokinase member of the EGFR family coded by the ERBB3 gene, plays an important role in cancer progression, despite its lack of intrinsic kinase activity[13, 14]. In our previous research, HER3 promoted angiogenesis in ovarian cancer[15] and positively regulated by reactive oxygen species (ROS)[16]. Recent studies indicated that the increased expression of HER3 in breast cancer and lung cancer were closely associated with TKi-resistance[17, 18]. However, the regulatory role of HER3 in other chemotherapy resistance was unclear yet. We found that HER3 was highly expressed in ovarian cancer cells, thus would like to test role of HER3 in drug resistance in this study.

The cylindromatosis gene (CYLD) is one member of lysine 63 deubiquitinases, which can specifically remove the k63 ubiquitin chain. CYLD was first discovered as a causative gene of familial cylinaromatosis (an autosomal dominant hereditary disease), and caused CYLD cutaneous syndrome[19-21]. CYLD was reported as a tumor suppressor to be involved in tumorigenesis and cancer development [19, 22, 23]. Loss of CYLD was associated with poor prognosis by inhibiting cell apoptosis and inducing immune response [24]. In addition, CYLD interacted with RIP1 to promote necroptosis[25]. However, role of CYLD in OC and platinum resistance is unclear yet.

In this study, we firstly identified that CYLD was downregulated in ovarian cancer, more interestingly, expression levels of CYLD were significantly decreased in cisplatin resistance cells (A2780-DDP, OVCAR3-DDP) when compared with parental A2780 and OVCAR3 cells. Herein we will address several important questions: (1) what role of CYLD is in regulating ovarian cancer resistance to DDP; (2) what downstream effector(s) is/are induced by CYLD downregulation to mediate DDP resistance; (3) what is the signal pathway that may be associated with CYLD expression and OC progression; (4) Whether there are some small molecular inhibitors or drugs that could reverse the DDP resistance due to CYLD knockdown. The answers to these questions would provide new insights into a better understanding of the pivotal role and mechanism of CYLD in OC development and drug resistance, then provide potential new therapeutic targets to overcome resistance to DDP treatment in the future.

Clinical tumor samples

The 33 EOC tissues and 10 non-cancer (Normal) tissues were obtained from the Biobank of the Affiliated Cancer Hospital of Zhengzhou University (Zhengzhou, China) from January 2017 to December 2020. The ovarian cancer tissues had been collected and stored in the tissue bank from patients who did not receive immunotherapy and neoadjuvant chemotherapy before the surgery as previously described [26]. The patient information including names and other personal information was not known to the investigators. Based on the coded information, the EOC patients were staged according to FIGO classification[27], graded according to the World Health Organization standard[28]. The tumor tissues of patient Case 1, Case 2 and Normal samples (6 fibroid patients and 4 atypical hyperplasia of endometrium patients) were also obtained from the Biobank of the Affiliated Cancer Hospital of Zhengzhou University.

Immunohistochemistry

Immunohistochemistry was carried out as previously described [29]. Briefly, the samples were performed on 3-μm-thick sections. After blocking with 10% normal goat serum, the sections were incubated with primary antibodies at 4 °C overnight, then the sections were incubated with secondary antibody for 2h at room temperature and staining for later analysis. Immunochemistry results were evaluated by the quality of the positive cells and described as immunoreactivity scores. Briefly, the density signals of positive cells were categorized into four grades: 0, negative; 1, weak; 2, moderate; and 3, strong, and categorized into two groups: negative (grade of 0 and 1), and positive (grade of 2 and 3). The percentages of the positive cells were categorized into four grades:0(0–3%) ;1, (3–25%); 2, (26–50%); 3, (51–75%); and 4, (76–100%). The immunoreactivity scores of each field were determined using the following formula: intensity score × positive score. Then the score of one section was calculated using all fields’ scores in the section, and categorized into two groups: low expression (scores of 0 to 6), and high expression (scores of 7 to 12)[30].

Cell culture

The human ovarian cancer cell lines Caov3, A2780, A2780/DDP, SKOV3, OVCAR3, OVCAR3/DDP, immortalized ovarian epithelial cell line IOSE386 and human embryonic kidney HEK293T cell line were cultured in RPMI-1640 or DMEM medium (Gibco, California, USA), supplemented with 10% fetal bovine serum (Gibco, California, USA), penicillin(100U/ml) and streptomycin(100ng/ml). All cells were cultured at 37 °C with 5% CO₂in incubator.

RNA isolation and quantitative RT-PCR (qRT-PCR)

Total RNAs of tissues and adherent cells were extracted using TRIzol reagent (Ambion, Texas, USA) according to the manufacturer’s instruction, reverse transcription were performed using HiScript III RT SuperMix (Vazyme, Nanjing, China). The real-time PCR amplifications were performed with ChamQ Universal SYBR qPCR Master Mix (Vazyme, Nanjing, China) using QuantStudio5 system (Applied Biosystems, California, USA). GAPDH levels were used as an internal control. Real-time quantitative PCR was performed in triplicate. The primer sequences used for real-time quantitative PCR were listed in Supplemental Table 1.

Western blotting

Total proteins extracted from tissues and adherent cells were separated by SDS-PAGE Gel Kit (Thermo Fisher Scientific, Waltham, USA) and transferred into poly-vinylidene difluoride (PVDF) membranes. Then the PVDF membranes were blocked with 5% non-fat milk for 2 h at room temperature and incubated with primary antibodies at 4°C overnight. After that the membranes were incubated with anti-rabbit/mouse IgG second antibody, the protein bands were detected with enhanced chemiluminescent substrate (Thermo Fisher scientific, Waltham, USA), as described previously[31]. The primary antibodies used in this study were listed in Supplemental Table 2.

The synergy of drug combination and quantitative assay

Cells were seeded into 96-well plates (5×10³per well), and treated with different doses of cisplatin, TX1-85-1 and Verapamil for 72h. Cell viability levels were analyzed by CCK-8 kit. The combined effects of drugs were analyzed by CompuSyn software (www.combosyn. com), and the drug dose-effects were calculated using the Median Effects methods. The results were quantitated according to the Chou-Talalay method using the fraction affected (Fa), and the combination index (CI). The quantitative assay staining signals were carried out and detected as described previously[32].

Chromatin immunoprecipitation (ChIP) assay

HEK293 cells (1×10⁷) was seeded into 6 cm plate and transfected with the p65 plasmid for 48h. ChIP assay was performed using the Hyperactive® In-Situ ChIP Library Prep Kit for Illumina (Vazyme, Nanjing, China) according to the manufacturer’s instructions. Briefly, the cells were harvested and bonded with ConA beads. After incubation with p65 antibody or IgG, the chromatin was bonded to Hyperactive pA/pG-Tn5 Transposon and extracted. Then the cell’s chromatin samples were detected by qRT-PCR analysis[33].

Tumor xenograft assay

Four to five-week-old female nude mice were obtained from GemPharmatech (Nanjing, Jiangsu, China). The mice were bred in a standard laboratory environment and fed with sterilized food and water. The animal study protocol was approved by the Animal Ethics Committee of Zhengzhou University.

Drug resistance test: The mice were divided into 2 groups randomly, each group has 13 female mice. The stable shNC or shCYLD OVCAR3 cells were resuspended at a density of 5× 10⁶ in mixture of Matrigel and serum-free RPMI1640, and injected subcutaneously in the armpit of nude mice. When the tumors were approximately 0.5×0.5 cm² (length of vertical radial line) in size, the mice were injected with cisplatin (5mg/kg, HANSOH PHARMA, Jiangsu, China) in intraperitoneal daily for 5 days, and the tumor sizes were measured every day. The tumor volumes (V) were calculated as: V=(π/6)×[Sum of two vertical diameter lines/2]³. Mice (26 mice used for xenograft tumors) were divided into different groups, and treated with drug to do the drug tolerance test. When the tumor volumes reached 15×15mm³, the mice were sacrificed, and tumor tissues were excised and weighted. For the survival experiment, the other shNC (n=9) or shCYLD (n=9) xenograft mice were analyzed to measure out the survival rate from cisplatin injection to death and data were recorded.

Drug resistance reversal test: 9 mice were divided into 3 groups randomly, each group has 3 female mice. The mice injected subcutaneously with A2780, A2780-DDP and A2780-DDP with CYLD overexpressed cells and resuspended at a density of 5×10⁶ in the armpit as described previously. Then the mice were treated with cisplatin (5mg/kg, daily for 5 days), tumor volumes and weights were analyzed with the same methods as mentioned above.

Drug combination test: 12 mice injected with stable CYLD knockdown OVCAR3 cells， resuspended at density of 5× 10⁶ cells in the armpit as described above. The mice were randomized into four groups and treated with the following regimens: vehicle alone (0.9% saline), DDP (3 mg/kg, intraperitoneally), Verapamil (25 mg/kg, intraperitoneally), and the combination of DDP and Verapamil daily for 5 days. Then the tumor volumes and weights of each group were analyzed with the same methods as above.

HE staining and IHC staining in tumors

Mice xenograft tumors were fixed in 4% paraformaldehyde for at least 24h. After dipped in paraffin, the tumor samples were cut into 3μm thick sections. Then Hematoxylin and Eosin (HE) were used to stain the sections, and IHC staining was carried out as described previously[34]. The anti-bodies against Ki-67, CYLD, Bcl-XL, Bcl-2, Bax, Bcl-3, ABCB1 (Supplemental table 3) were incubated with the sections at 1:200 concentration.

Statistical analysis

All data were calculated as means ± SD. and analyzed using t-test. Then the results from the statistical analysis were compared using GraphPad Prism 8 software. p-value at <0.05 was considered statistically significant.

CYLD were significantly downregulated in ovarian cancer samples and lower CYLD expression indicated poor prognosis.

To identify the role of CYLD in cancer development, the expression levels of CYLD in different types of cancer were detected to be generally lower in pan-cancer used UCSC Xena database, with especially in TCGA database of ovarian cancer, the expression levels of CYLD were significantly decreased (Supplemental Fig.1). Then the expression levels of CYLD were determined in tissue samples of 10 normal ovarian (Normal) and 33 epithelial ovarian cancer (Tumor) using immunohistochemistry, and the tumor samples had much lower CYLD expression levels and lower IHC sores compared with Normal samples (Fig.1A). In addition, the protein and mRNA expression levels of CYLD were significantly downregulated in epithelial ovarian cancer (Tumor) samples compared with the normal ovarian (Normal) tissues (Fig.1B). We further studied the relationship between CYLD expression and the clinicopathological characteristics in ovarian cancer tissues, and conveyed that there were no significant correlation in the clinical characteristics, such as age, ascites volume and metastasis site. Interestingly, the CYLD expression level decreased with the increase of the clinical stage, as well as higher CYLD expression indicated more sensitive to cisplatin treatment (Supplemental Tab.4). And the patients with lower CYLD expression levels had unfavorable outcomes compared to those with higher CYLD expression group (Fig.1C). Furthermore, CYLD expression was explored with the GEPIA database, and the results confirmed that CYLD was a tumor suppressor in ovarian cancer and the expression level decreased in higher clinical stage(Fig.1D). The prognostic roles of CYLD in ovarian cancer were further evaluated using Kaplan-Meier plotter database, and higher CYLD expression had better survival rate(Fig.1E). Thus, we firstly suggested that CYLD was a tumor suppressor in ovarian cancer, and the patients with lower CYLD expression had poor prognosis in the patient cohort.

CYLD could be an essential DDP sensitizer biomarker.

Since resistance to DDP treatment is a major clinical challenge in ovarian cancer therapy, therefore, we considered that CYLD may be associated with cisplatin resistance in ovarian cancer. Then CYLD expression levels were detected to be reduced in 24 tumor tissues lesions from cisplatin sensitivity group, compared with resistance group (Fig.2A). And the mRNA expression levels of CYLD were significantly downregulated in resistance samples compared to sensitive samples (Fig.2B).

We further selected 2 cases (Case 1 from cisplatin resistant group and Case 2 from cisplatin sensitive group ) to illustrate the crucial role of CYLD in cisplatin resistant ovarian cancer. Here, using computed tomography (CT) analysis with tumor tissues of 2 clinical patients, Case 1 showed pelvic shadow in CT image at 4 months after treatment (Fig.2C, right panel), Case 2 showed no recurrence as suggested with the CT images at six months after treatment (Fig.2D, right panel). Then regular review was checked by serum biomarker Ca125 levels and imaging examination every 2 months. Two months later, Ca125 levels were found to be raised in Case 1, but not changed in Case 2, which also suggested platinum resistance recurrence in Case 1 (Fig.2E). The mRNA expression levels of CYLD in Case 1 and Case 2 also confirmed that CYLD expression levels were significantly lower in platinum resistant ovarian cancer tissues (Fig. 2F). In addition, immuno-histochemistry staining for CYLD of these tumor tissues were conducted using the surgical specimens, the CYLD expression levels showed negative in Case 1 patient with platinum resistance recurrence, but positive in platinum sensitive Case 2 patient (Fig. 2G). Thus, we firstly identified that CYLD expression was attenuated in ovarian cancer patient tissues when the cancer became DDP resistance, and CYLD could be an essential DDP sensitizer biomarker.

CYLD knockdown rendered cells resistant to DDP, while force expression of CYLD promoted drug sensitivity.

To identify the expression of CYLD in DDP resistance ovarian cancer, we used the parental and drug resistant cell lines (OVCAR3/OVCAR3-DDP, A2780/A2780-DDP) to conduct analysis, and found that the protein expression levels of CYLD were significantly downregulated in DDP resistant cell lines compared to parental cells (Fig. 3A). Similarly, much lower levels of CYLD were identified in other types of OC cell lines (Caov3, SKOV3, A2780 and OVCAR3) compared to human immortalized ovarian epithelial cell line (IOSE386) (Fig.3B). These results showed that CYLD expression was suppressed in progression of OC cisplatin resistance, but whether it is an initiating factor of drug resistance still needed to be investigated. To test whether CYLD suppression is sufficient in affecting chemoresistance, we showed that CYLD knockdown in OVCAR3 and A2780 cells were sufficient to promote cells more resistance to DDP treatment compared to control cells by CCK-8 assay (Fig.3C-3D). Additionally, the CYLD-overexpressed OVCAR3-DDP and A2780-DDP cells were established. Overexpression of CYLD was sufficient to increase cell sensitivity to DDP treatment compared with control group, making the DDP resistant cell lines sensitive to DDP (Fig.3E-3F). These findings suggested that CYLD expression is essential in regulating DDP resistance.

CYLD knockdown inhibited cell apoptosis activities and promoted drug efflux.

Since previous studied reported that loss of CYLD expression may cause cisplatin resistance through NF-κB hyperactivation [22, 23], we wondered whether CYLD regulated DDP resistance through regulating cellular apoptosis in ovarian cancer. The apoptosis rates were analyzed in OVCAR3 and A2780 cells treated with 5μM DDP or PBS, and the percentages of apoptotic cells in CYLD knockdown group significantly decreased compared to that in the control group with DDP treatment (Fig.4A, Supplemental Fig.2A-2B). Then we found that the protein expression levels of pro-apoptosis factor Bax were downregulated in CYLD knockdown group, while the anti-apoptotic proteins Bcl-XL and Bcl-2 were upregulated (Fig.4B). In addition, the percentage of apoptosis in A2780-DDP with overexpressed CYLD group was remarkably higher than that of A2780-DDP, and the result was similar to that of A2780 (Fig.4C, Supplemental Fig.2C). Further studies suggested that compared to OVCAR3-DDP/A2780-DDP, Bax levels were upregulated in CYLD-overexpressed DDP resistant cells and OVCAR3/A2780 cells, while Bcl-XL levels were downregulated, respectively (Fig.4D). These results indicated that CYLD mediated DDP resistance through apoptosis via Bax/Bcl-XL pathway.

Base on the effect of CYLD in sensitizing cells to apoptosis might be cell type specific[20, 37]. Therefore, we considered whether there were other molecular regulatory pathways that caused drug resistance in ovarian cancer. Thus, we adopted the intracellular levels of Rhodamine 123, a fluorescent drug that can be excreted through drug transporters on the surface of cell membrane, and measured transporter activities between CYLD knockdown OVCAR3 cells and control. After incubated with different concentrations of Rhodamine 123, the fluorescence intensity of CYLD knockdown group was higher than control group, and the difference was more remarkable at the concentration of 2 μM (Fig.4E). Then the fluorescence intensities of cells at different time points after incubated Rhodamine 123 were also measured (Supplemental Fig. 3A), which showed that the fluorescence intensities were significantly different in 12h group, while there was no difference after 16h treatment (Supplemental Fig. 3B). These results suggested that CYLD knockdown promoted drug to pump intracellularly. To further examine the potential targets of CYLD in ABC transporter superfamily, we found that ABCB1 were significantly induced in CYLD-knockdown cells (Fig.4F), while ABCC1, ABCG2 and ABCG9 were not much difference(Supplemental Fig.3C-3D). In addition, ABCB1 in OVCAR3-DDP/A2780-DDP cells were showed to be greatly higher than those in other cells (OVCAR3-DDP/A2780-DDP with CYLD overexpression and OVCAR3/A2780 cells) (Fig.4G). Since CYLD is a deubiquitinase, we examined whether CYLD regulates ABCB1 expression through ubiquitination, but there is no binding between CYLD and ABCB1 by IP experiment, which suggested that CYLD may indirectly regulate ABCB1(Supplemental Fig.3E). To further gain insight into the molecular mechanism, we found that key intermediate signaling molecule p-65(ser536) in CYLD knockdown cells were induced compared with control cells (Fig.4H). Furthermore, two binding sites on the promoter region of ABCB1 were predicted in JASPAR according to the binding motif of p65, and the site 1(~1839-1848) was the direct binding site of p65 in ABCB1 promoter (Fig.4I). Hence, ABCB1 was a pivotal downstream mediator of CYLD-regulating DDP resistance.

HER3 negatively regulated CYLD expression via phosphorylation of STAT3

To further investigate the molecular mechanisms in regulation of CYLD, the mRNA expression levels of the ERBB family (EGFR, HER2, HER3, HER4) were detected in patient samples. There was a significantly negative relationship between the expression levels of HER3 and CYLD (R=-0.4333, P=0.0389, Fig.5A), while other ERBB family members had no significant correlations (Supplemental Fig.4A). Therefore, HER3 may be potential upstream regulator of CYLD in ovarian cancer. To further confirm the role of HER3 in CYLD regulation, we found that the protein expression levels of CYLD were decreased in HER3 overexpressed OVCAR3/A2780 cells, compared to control cells (Fig.5B). In addition, the expression levels of CYLD were higher in HER3 knockdown OVCAR3/A2780 cells compared to control cells (Fig.5C). These findings further suggested that HER3 may negatively regulate CYLD expression. To examine the mechanism that how HER3 attenuated CYLD’s expression, HER3-overexpressed cells showed much higher expression levels of key intermediate signaling molecule p-STAT3(T705) compared with control cells (Fig.5D), while other candidate molecules, p-c-Jun, p-p38 and p-Erk1/2 showed no significantly changed (Supplemental Fig.4B). Moreover, the expression levels of p-STAT3 in HER3-silenced OVCAR3/A2780 cells were significantly decreased compared to the control (Fig.5D). Furthermore, the immunoprecipitation assay showed that HER3 protein directly bound and interacted with CYLD protein (Fig.5E). Thus, these results showed that HER3 inhibited CYLD expression via phosphorylation of STAT3.

HER3 functioned as crucial upstream regulator in DDP resistance and HER3 inhibitor facilitated DDP sensitivity.

To further confirm the role of HER3 in ovarian cancer drug resistance, the protein levels of HER3 in OVCAR-DDP and A2780-DDP cells were showed higher compared to parental cells (Fig. 6A). The HER3-silenced cell lines showed more sensitive to drug treatment, while HER3-overexpressed cell lines found to be more resistant to DDP treatment (Fig.6B-6C). These results illustrated that HER3 played an important role in drug resistance of ovarian cancer cells.

In order to test whether HER3 inhibitor could improve the DDP sensitivity, the drug combination effect of HER3 inhibitor (TX1-85-1) and DDP in A2780-DDP cell line were analyzed. To identify combination effect, Chou-Talalay method were used to detect the synergistic effect of DDP (0, 0.1, 0.3, 0.5, 0.7, 1, 3, 5, 7, 10μM) in combination with TX1-85-1(0, 0.3, 0.7, 1, 3, 7μM). The Combination Index (CI) data of these two drugs was showed in Supplemental Fig. 4C. The Fraction Affected-combination index (Fa) analyzed the effects of the combination with different doses of TX1-85-1 and DDP (Fig.6D). The synergistic effect of these two drugs was described in a Scatter plot, and the fractions affected-combination index (Fa-CI) plot were almost below 1, that indicated that these two drugs had synergistic effect (Fig.6E). The synergistic effect suggested that inhibition of HER3 improved drug sensitivity in DDP resistance OC cells. Then according to the CI results, we selected two drug concentrations (DDP 7μM, TX1-85-1 3 and 7μM), which was the best combination values in all CI data, for further apoptosis analysis. The percentages of apoptosis cells treated with DDP and TX1-85-1 group were significantly higher than those in the cells treated with each single drug (Fig.6F). The same trends were also revealed in OVCAR3-DDP cells (Supplemental Figs. 4D-4F), and dual-treatment of TX1-85-1 and DDP alleviated drug resistance. Hence, these results strongly demonstrated that HER3 promoted DDP resistance in OC cells, and HER3 inhibitor enhanced the drug sensitivity in DDP resistance OC cells.

CYLD knockdown increased DDP resistance by inhibiting apoptosis and inducing ABCB1 expression in vivo.

To investigate whether CYLD knockdown promotes tumor growth and DDP resistance, we established a xenograft model by BALB/C nude mice with CYLD-knockdown cells and control cells: OVCAR3-shNC and OVCAR3-shCYLD (Fig.7A). The results suggested that tumors developed from OVCAR3-shCYLD group grew much faster than those of control group after DDP treatment (Fig.7B-7D). Furthermore, the survival times of the mice with OVCAR3-shCYLD cells were remarkably shorter than those of the mice in the control group (Fig.7E). These findings demonstrated that CYLD knockdown promoted DDP resistance of ovarian tumors with shorter survival time. The tumor samples developed from OVCAR3-shCYLD group showed increasing expression levels of Bcl-XL and ABCB1, but decreasing expression levels of Bax (Fig.7F-7G). Base on Bcl-XL and Bax are vital proteins in apoptosis pathway, these results showed that CYLD knockdown affected the apoptotic pathway and elevated ABCB1 expression which could promote drug resistance through drug efflux in vivo. These findings showed that inhibition of CYLD in ovarian cancer cells induced DDP resistance by inhibiting apoptosis pathway and inducing ABCB1 expression in vivo.

Overexpression of CYLD partially reversed DDP resistance, and dual-treatment with DDP and Verapamil inhibited tumorigenesis.

Based on the results above, we further established a xenograft model with CYLD-overexpressed A2780-DDP cells and its control cells: A2780 and A2780-DDP (Fig.8A). The tumors of mice in CYLD-overexpressed group and A2780 group grew slower than tumors in the A2780-DDP group after DDP treatment (Fig.8B-8C). These findings suggested that overexpressed CYLD partially reversed DDP resistance in OC.

Then we wondered whether ABCB1 inhibitor Verapamil could reverse DDP resistance caused by CYLD knockdown in OC. The synergistic effects of DDP (0, 0.1, 0.3, 0.5, 0.7, 1, 3, 5, 7, 10μM) in combination with Verapamil (0, 1, 3, 7, 10, 30μM) were detected in CYLD knockdown OVCAR3 cells. The results of the CI data of these two drugs were showed in Supplemental Fig. 5A. The synergistic effects of these two drugs in OVCAR3 cells were also described in a Scatter plot (Fig.8D), and the Fa-CI plot which showed these two drugs had synergistic effects (the value was almost below 1) (Fig.8E). According to the CI results, these two drugs’ concentrations (DDP 3μM, Verapamil 3μM) may have the best combination values among all the CI data, and the two concentrations were selected for further apoptosis experiment (Supplemental Fig. 5B). The apoptosis rates of this combinatorial group in CYLD knockdown OVCAR3 cells were significantly higher than those of each single treatment (Fig. 8F). We also obtained similar results in A2780-shCYLD cells (Supplemental Fig. 5C-5F). To further confirm the synergistic effect of DDP and Verapamil, we established a xenograft model with OVCAR3-shCYLD cells. As shown in Fig.8G-8I, treatment with DDP or verapamil alone did not effectively inhibit tumor growth, while dual-inhibitor treatment greatly inhibited tumor growth. In addition, the mice body weights were similar in all 4 groups, suggesting that the combination regimen at the indicated dose did not cause any toxicity in mice (Fig.8J). In conclusion, these findings demonstrated that CYLD is an essential DDP sensitizer biomarker in ovarian cancer, and the HER3 inhibitor and ABCB1 inhibitor combination greatly increased cisplatin sensitivity in resistant OC cells (Fig.8K).

Platinum resistance is one of major challenges that seriously affect the prognosis of ovarian cancer patients [38]. The 5-year survival rate of platinum resistant patients is approximately 30%[39], which is significantly less than that of platinum sensitive patients[2]. To understand the molecular mechanism and clinical features is important in proposing the optimal combination therapy regimen for achieving the best clinical outcome. Interestingly, we found that CYLD expression was greatly downregulated in cisplatin resistant OC, which is correlated with poor prognosis. CYLD was suggested to be crucial in regulation of tumorigenesis and drug resistance in different cancers, such as gastric cancer and lung cancer [22, 23, 35, 36]. Therefore, we hypothesized that CYLD played an important role in platinum resistance of ovarian cancer. To test the hypothesis, we performed both gain- and loss-of-function studies and demonstrated that forced CYLD expression attenuated cisplatin resistance by inducing apoptosis and apoptosis-related proteins. Overexpression of CYLD also reversed DDP sensitivity to alter cisplatin-resistant OC to become DDP sensitive in vivo. These results indicated that CYLD may be a potential target for the diagnosis and treatment of DDP resistance in ovarian cancer.

Platinum-resistance ovarian cancers are defined that the platinum-free interval (PFI) of patient, means the time between the last dose of platinum-based chemotherapy and cancer progression, less than 6 months [40]. Previous researches of platinum resistance mostly focused on apoptosis related pathways, such as the expression of apoptosis inducer molecules including “caspase” [41, 42] or apoptosis inhibitor molecules such as “Bcl-2” [43, 44]. We observed higher expression of HER3 in ovarian DDP resistant cells. Since HER3 showed no intrinsic tyrosine kinase properties unless it went under hetrodimerization and formed dimers such as HER2-HER3 and HER1(EGFR)-HER3[45]. However, role of HER3 in DDP resistance was not known yet. Our group showed higher expression levels of HER3 in ovarian cancer were induced by ROS[16] which played an important role in tumor angiogenesis[15]. HER3 could activate the PI-3K/Akt, MEK/MAPK, Jak/Stat pathways, and Src kinase[18]. In the present study, we found that HER3 promoted cisplatin resistance in ovarian cancer, which was consistent with the clinical observation in previous study [46]. More importantly, HER3 reduced CYLD expression by promoting STAT3 phosphorylation, but not by p38, c-Jun and Erk pathways. Interestingly, we also discovered combination therapy method of HER3 inhibitor TX1-85-1 and DDP showed a significant synergistic effect, and dual-treatment in ovarian cancer resistance cells remarkably reduced the dosage of platinum to be effective, which indicates that HER3 may be potential biomarker as well as therapeutic target to overcome DDP resistance, and HER3 inhibitor may be used to alleviating drug resistance in ovarian cancer in the future.

Unexpectedly, we found enhanced drug efflux in CYLD knockdown ovarian cancer cells by Flow cytometry, which had not been reported in previous studies. The higher drug efflux may be an important mechanism of chemo-resistance [47], we hypothesized that CYLD mediated platinum resistance in OC by blocking the drug efflux. Through both gain- and loss-of-function studies, we determined that CYLD mediated drug resistance by downregulating a downstream molecule, ABCB1 expression. And the significant synergistic effect of combination therapy (ABCB1 inhibitor Verapamil and DDP) further confirmed crucial role of CYLD in regulating drug resistance. Thus, this combination therapy may be used to enhance the efficacy of cisplatin, especially in cisplatin resistant OC in the future.

In summary, we firstly identified the CYLD was a novel target for the diagnosis and treatment in cisplatin resistant OC via the HER3/CYLD/ABCB1 axis. Furthermore, the drug combination of HER3 inhibitor or ABCB1 inhibitor with DDP in cisplatin-resistance OC showed significant synergistic effect. These results provide new evidence and direction to overcome chemotherapy resistance in ovarian cancer, which warrants further clinical study in the future.

OC: Ovarian cancer; CYLD: Cylindromatosis; DDP: Cisplatin; IHC: Immunohistochemistry; CCK-8: Cell counting kit 8; TCGA: The Cancer Genome Atlas; GEO: Gene Expression Omnibus.

Ethics approval and consent to participate

Animal experiments were approved by the Animal Ethics Committee of Zhengzhou University.

Consent for publication

All authors consent for publication.

Availability of data and material

All data generated or analyzed during in this study are included in this published article.

Conflicts of interest

The authors declare that they have no competing interests.

Funding

This work was supported by National Natural Science Foundation of China (81903174) and Provincial Health Commission of Henan (SBGJ202003013 and LHGJ20190656).

Acknowledgements

Not applicable.

Authors^,contributions

YZ, LW, LZL and BHJ participated in the design of the study. YZ, JGQ, XYJ and WW performed the experiments and analyzed the data. JGQ, WJL, and CD performed the bioinformatics analysis and analyzed the data. YZ, LW and BHJ prepared the manuscript. All authors read and approved the manuscript.

Shen L, Xia M, Zhang Y, Luo H, Dong D, Sun L. Mitochondrial integration and ovarian cancer chemotherapy resistance. Exp Cell Res 2021; 401: 112549.
Munoz-Galvan S, Carnero A. Targeting Cancer Stem Cells to Overcome Therapy Resistance in Ovarian Cancer. Cells 2020; 9.
Lukanovic D, Herzog M, Kobal B, Cerne K. The contribution of copper efflux transporters ATP7A and ATP7B to chemoresistance and personalized medicine in ovarian cancer. Biomed Pharmacother 2020; 129: 110401.
Kroeger PT, Jr., Drapkin R. Pathogenesis and heterogeneity of ovarian cancer. Curr Opin Obstet Gynecol 2017; 29: 26-34.
Daly MB, Pilarski R, Yurgelun MB, Berry MP, Buys SS, Dickson P et al. NCCN Guidelines Insights: Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic, Version 1.2020. J Natl Compr Canc Netw 2020; 18: 380-391.
Grunewald T, Ledermann JA. Targeted Therapies for Ovarian Cancer. Best Pract Res Clin Obstet Gynaecol 2017; 41: 139-152.
Ghosh S. Cisplatin: The first metal based anticancer drug. Bioorg Chem 2019; 88: 102925.
Galluzzi L, Senovilla L, Vitale I, Michels J, Martins I, Kepp O et al. Molecular mechanisms of cisplatin resistance. Oncogene 2012; 31: 1869-1883.
Tchounwou PB, Dasari S, Noubissi FK, Ray P, Kumar S. Advances in Our Understanding of the Molecular Mechanisms of Action of Cisplatin in Cancer Therapy. J Exp Pharmacol 2021; 13: 303-328.
Freimund AE, Beach JA, Christie EL, Bowtell DDL. Mechanisms of Drug Resistance in High-Grade Serous Ovarian Cancer. Hematol Oncol Clin North Am 2018; 32: 983-996.
Khan MA, Vikramdeo KS, Sudan SK, Singh S, Wilhite A, Dasgupta S et al. Platinum-resistant ovarian cancer: From drug resistance mechanisms to liquid biopsy-based biomarkers for disease management. Semin Cancer Biol 2021; 77: 99-109.
Wu C, He L, Wei Q, Li Q, Jiang L, Zhao L et al. Bioinformatic profiling identifies a platinum-resistant-related risk signature for ovarian cancer. Cancer Med 2020; 9: 1242-1253.
Haikala HM, Janne PAJCcraojotAAfCR. Thirty Years of HER3: From Basic Biology to Therapeutic Interventions27: 3528-3539.
Kiavue N, Cabel L, Melaabi S, Bataillon G, Callens C, Lerebours F et al. ERBB3 mutations in cancer: biological aspects, prevalence and therapeutics. Oncogene 2020; 39: 487-502.
He J, Jing Y, Li W, Qian X, Xu Q, Li FS et al. Roles and mechanism of miR-199a and miR-125b in tumor angiogenesis. PLoS One 2013; 8: e56647.
He J, Xu Q, Jing Y, Agani F, Qian X, Carpenter R et al. Reactive oxygen species regulate ERBB2 and ERBB3 expression via miR-199a/125b and DNA methylation. EMBO Rep 2012; 13: 1116-1122.
Yonesaka K. HER2-/HER3-Targeting Antibody-Drug Conjugates for Treating Lung and Colorectal Cancers Resistant to EGFR Inhibitors. Cancers (Basel) 2021; 13.
Liu X, Liu S, Lyu H, Riker AI, Zhang Y, Liu B. Development of Effective Therapeutics Targeting HER3 for Cancer Treatment. Biol Proced Online 2019; 21: 5.
Cui Z, Kang H, Grandis JR, Johnson DE. CYLD Alterations in the Tumorigenesis and Progression of Human Papillomavirus-Associated Head and Neck Cancers. Mol Cancer Res 2021; 19: 14-24.
Yang Y, Zhou J. CYLD - a deubiquitylase that acts to fine-tune microtubule properties and functions. J Cell Sci 2016; 129: 2289-2295.
Lork M, Verhelst K, Beyaert R. CYLD, A20 and OTULIN deubiquitinases in NF-kappaB signaling and cell death: so similar, yet so different. Cell Death Differ 2017; 24: 1172-1183.
Suenaga N, Kuramitsu M, Komure K, Kanemaru A, Takano K, Ozeki K et al. Loss of Tumor Suppressor CYLD Expression Triggers Cisplatin Resistance in Oral Squamous Cell Carcinoma. Int J Mol Sci 2019; 20.
Zhao J, Wang X, Mi Z, Jiang X, Sun L, Zheng B et al. STAT3/miR-135b/NF-kappaB axis confers aggressiveness and unfavorable prognosis in non-small-cell lung cancer. Cell Death Dis 2021; 12: 493.
Delbridge AR, Valente LJ, Strasser A. The role of the apoptotic machinery in tumor suppression. Cold Spring Harb Perspect Biol 2012; 4.
Dondelinger Y, Darding M, Bertrand MJ, Walczak H. Poly-ubiquitination in TNFR1-mediated necroptosis. Cell Mol Life Sci 2016; 73: 2165-2176.
Liu WJ, Huang YX, Wang W, Zhang Y, Liu BJ, Qiu JG et al. NOX4 Signaling Mediates Cancer Development and Therapeutic Resistance through HER3 in Ovarian Cancer Cells. Cells 2021; 10.
Prat J, Oncology FCoG. FIGO's staging classification for cancer of the ovary, fallopian tube, and peritoneum: abridged republication. J Gynecol Oncol 2015; 26: 87-89.
Meinhold-Heerlein I, Fotopoulou C, Harter P, Kurzeder C, Mustea A, Wimberger P et al. The new WHO classification of ovarian, fallopian tube, and primary peritoneal cancer and its clinical implications. Arch Gynecol Obstet 2016; 293: 695-700.
Werner B, Yuwono N, Duggan J, Liu D, David C, Srirangan S et al. Cell-free DNA is abundant in ascites and represents a liquid biopsy of ovarian cancer. Gynecol Oncol 2021; 162: 720-727.
Ma HM, Cui N, Zheng PS. HOXA5 inhibits the proliferation and neoplasia of cervical cancer cells via downregulating the activity of the Wnt/beta-catenin pathway and transactivating TP53. Cell Death Dis 2020; 11: 420.
Qiu J, Li Q, Bell KA, Yao X, Du Y, Zhang E et al. Small-molecule inhibition of prostaglandin E receptor 2 impairs cyclooxygenase-associated malignant glioma growth. Br J Pharmacol 2019; 176: 1680-1699.
Xia ZK, Wang W, Qiu JG, Shi XN, Li HJ, Chen R et al. Discovery of a New CDK4/6 and PI3K/AKT Multiple Kinase Inhibitor Aminoquinol for the Treatment of Hepatocellular Carcinoma. Front Pharmacol 2021; 12: 691769.
Hu J, Meng Y, Zhang Z, Yan Q, Jiang X, Lv Z et al. MARCH5 RNA promotes autophagy, migration, and invasion of ovarian cancer cells. Autophagy 2017; 13: 333-344.
Feng J, Dai W, Mao Y, Wu L, Li J, Chen K et al. Simvastatin re-sensitizes hepatocellular carcinoma cells to sorafenib by inhibiting HIF-1alpha/PPAR-gamma/PKM2-mediated glycolysis. J Exp Clin Cancer Res 2020; 39: 24.
Wang Z, Wang Q, Xu G, Meng N, Huang X, Jiang Z et al. The long noncoding RNA CRAL reverses cisplatin resistance via the miR-505/CYLD/AKT axis in human gastric cancer cells. RNA Biol 2020; 17: 1576-1589.
Welte S, Urbanik T, Elssner C, Kautz N, Koehler BC, Waldburger N et al. Nuclear expression of the deubiquitinase CYLD is associated with improved survival in human hepatocellular carcinoma. PLoS One 2014; 9: e110591.
Agarwal S, Liang G, Ahlqvist K, Pannem R, Posern G, Massoumi R. Serum Response Factor Controls CYLD Expression via MAPK Signaling Pathway. PLoS ONE 2011; 6.
He J, Yu JJ, Xu Q, Wang L, Zheng JZ, Liu LZ et al. Downregulation of ATG14 by EGR1-MIR152 sensitizes ovarian cancer cells to cisplatin-induced apoptosis by inhibiting cyto-protective autophagy. Autophagy 2015; 11: 373-384.
Hao L, Wang JM, Liu BQ, Yan J, Li C, Jiang JY et al. m6A-YTHDF1-mediated TRIM29 upregulation facilitates the stem cell-like phenotype of cisplatin-resistant ovarian cancer cells. Biochim Biophys Acta Mol Cell Res 2021; 1868: 118878.
Kumar S, Oien DB, Khurana A, Cliby W, Hartmann L, Chien J et al. Coiled-Coil and C2 Domain-Containing Protein 1A (CC2D1A) Promotes Chemotherapy Resistance in Ovarian Cancer. Front Oncol 2019; 9: 986.
Janson V, Johansson A, Grankvist K. Resistance to caspase-8 and -9 fragments in a malignant pleural mesothelioma cell line with acquired cisplatin-resistance. Cell Death Dis 2010; 1: e78.
Cui Z, Pu T, Zhang Y, Wang J, Zhao Y. Long non-coding RNA LINC00346 contributes to cisplatin resistance in nasopharyngeal carcinoma by repressing miR-342-5p. Open Biol 2020; 10: 190286.
Long X, Xiong W, Zeng X, Qi L, Cai Y, Mo M et al. Cancer-associated fibroblasts promote cisplatin resistance in bladder cancer cells by increasing IGF-1/ERbeta/Bcl-2 signalling. Cell Death Dis 2019; 10: 375.
Kuo KL, Liu SH, Lin WC, Hsu FS, Chow PM, Chang YW et al. Trifluoperazine, an Antipsychotic Drug, Effectively Reduces Drug Resistance in Cisplatin-Resistant Urothelial Carcinoma Cells via Suppressing Bcl-xL: An In Vitro and In Vivo Study. Int J Mol Sci 2019; 20.
Molavipordanjani S, Hosseinimehr SJ. The Radiolabeled HER3 Targeting Molecules for Tumor Imaging. Iran J Pharm Res 2021; 20: 141-152.
McEvoy LM, O'Toole SA, Spillane CD, Martin CM, Gallagher MF, Stordal B et al. Identifying novel hypoxia-associated markers of chemoresistance in ovarian cancer. BMC Cancer 2015; 15: 547.
Zhai J, Shen J, Xie G, Wu J, He M, Gao L et al. Cancer-associated fibroblasts-derived IL-8 mediates resistance to cisplatin in human gastric cancer. Cancer Lett 2019; 454: 37-43.

No competing interests reported.

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HER3/CYLD axis mediates ovarian cancer cell resistance to chemotherapy via upregulation of ABCB1

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