AKR1C1 controls cisplatin-resistance in head and neck squamous cell carcinoma through cross-talk with the STAT1/3 signaling pathway
Cisplatin is the first-line chemotherapy used against most upper aerodigestive tract carcinomas. In head and neck cancer, sensitivity to cisplatin remains the key issue in treatment response and outcome. Genetic heterogeneity and aberrant gene expression may be the intrinsic factors that cause primary cisplatin-resistance.
Combination of the HNSCC gene expression data and the cisplatin sensitivity results from public database. We found that aldo-keto reductase family 1 member C1 (AKR1C1) may be associated with cisplatin sensitivity in HNSCC treatment of naïve cells. We examined the AKR1C1 expression and its correlation with cisplatin IC50 and prognosis in patients. The in vitro and in vivo AKR1C1 functions in cisplatin-resistance through overexpression or knockdown assays, respectively. cDNA microarrays were used to identify the upstream regulators that modulate AKR1C1-induced signaling in HNSCC. Finally, we used the cigarette metabolites to promote AKR1C1 expression and ruxolitinib to overcome AKR1C1-induced cisplatin-resistance.
AKR1C1 positively correlates to cisplatin-resistance in HNSCC cells. AKR1C1 is a poor prognostic factor for recurrence and death of HNSCC patients. Silencing of AKR1C1 not only reduced in vitro IC50 but also increased in vivo cisplatin responses and vise versa in overexpression cells. Cigarette metabolites also promote AKR1C1 expression. Transcriptome analyses revealed that STAT1 and STAT3 activation enable AKR1C1-induced cisplatin-resistance and can be overcome by ruxolitinib treatment.
AKR1C1 is a crucial regulator for cisplatin-resistance in HNSCC and also poor prognostic marker for patients. Targeting the AKR1C1-STAT axis may provide a new therapeutic strategy to treat patients who are refractory to cisplatin treatment.
KeywordsAKR1C1 Cisplatin-resistance HNSCC STATs Ruxolitinib
Gene Expression Omnibus
Head and neck squamous cell carcinoma
Cisplatin is the standard chemotherapeutic drug in head and neck squamous cell carcinoma (HNSCC) treatment  . Cisplatin causes platinum-DNA adducts that induce G2/S arrest and subsequent cell death in rapidly growing cancer cells. Furthermore, cisplatin also increases highly reactive mono- and biaquated cisplatin forms  and intracellular reactive oxygen species (ROS) levels following reaction with cytoplasmic proteins and biomolecules . For treatment of naïve, locally advanced HNSCC patients, the initial cisplatin-based chemotherapy response can be up to 50% . Half of the patients remain without response to cisplatin; furthermore, most patients will develop acquired cisplatin-resistance, which induces cancer recurrence. Cisplatin-resistance and recurrence are the major factors leading to cisplatin-based therapeutic failure in HNSCC patients . Thus, it is important to understand the mechanism of cisplatin-resistance, which may enable the development of strategies that help patients to overcome chemoresistance and improve clinical outcome in HNSCC.
A tumor is a heterogeneous cell mixture which harbors various genetic mutations and diverse gene expression. Therefore, precision medicine has become a rising field in cancer therapy . Recently, patient-derived tumor xenograft models function as accurate preclinical models to predict therapeutic response; however, they are labor intensive and expensive projects for the prediction of therapeutic outcome . In contrast, a well characterized cancer cell line database such as Genomics of Drug Sensitivity in Cancer (GDSC) [8, 9, 10] could provide reliable information on chemotherapy drug-response, and gene expression profiles from the Cancer Cell Line Encyclopedia (CCLE)  could provide guidance in the search for novel resistance genes. Moreover, the expression level of candidate genes and their prognostic value can be examined in public microarray databases or TCGA cohorts of clinical cancer patients [12, 13, 14]. Using in silico analysis could assist researchers in elucidating the candidate genes accounting and provide a potential therapy niches for overcoming chemoresistance in HNSCC.
The mammalian hydroxysteroid dehydrogenases comprise four enzymes (AKR1C1-C4) that catalyze reduction of steroids and prostaglandins  and cluster on the chromosome 10p14–15 region. AKR1C1 and C2 are located on different strands of DNA but have highly similar (> 98%) protein coding sequences . AKR1C1 and -C2 contribute 40% of the detoxification function of 4-methylnitrosamino-1-(3-pyridyl)-1-butanone (NNK) in tobacco-derived nitrosamine carcinogens  In this study, we analyzed the HNSCC cell gene expression profiles and inhibitory concentration (IC50) of cisplatin from the CCLE and GDSC databases. Interestingly, the AKR1C1 expression level was highly correlated to cisplatin IC50, and modulated AKR1C1 expression could affect the cisplatin response. Furthermore, the cigarette metabolites stimulate AKR1C1 expression in HNSCC. Using a JAK inhibitor will overcome AKR1C1 induced primary cisplatin-resistance. Here, we provided a novel, independent enzymatic mechanism of AKR1C1 through STAT3 activation for primary cisplatin-resistance in HNSCC.
Materials and methods
In silico analysis of cisplatin response and patient prognosis
The HNSCC gene expression profiles (GSE36133) in the CCLE database  were downloaded from Gene Expression Omnibus (GEO) and analyzed by Genespring GX software (Agilent). The HNSCC cisplatin IC50 data were downloaded from the GDSC database (release version 4, ). The TCGA HNSCC prognostic value and clinical characteristics of the recurrent HNSCC cohort were analyzed in SurvExpress or the CancerBrowser database and reformatted in GraphPad Prism or SPSS Software.
Cell culture and reagents
Cell cultures were prepared and maintained according to a standard protocol. 293 T, FaDu, Cal-27, HSC-2, and HSC-4 cells were purchased from ATCC or JCRB cell bank and maintained according to the manufacturer’s instructions. Chemical reagents, vectors, and antibodies are listed in Additional file 1: Table S1. The cisplatin and 5-PBSA were prepared in sterile PBS or water and the ruxolitinib and cigarette metabolites, such as NAB, NAT, NNK and NNN, were prepared in DMSO.
Cell viability assay and caspase activity assay
In the cisplatin viability assay, HNSCC cells (2 × 103) were seeded in 96-well plates. After incubation overnight, the medium was replaced with 200 μl fresh medium containing various dosages of cisplatin, 5-PBSA or ruxolitinib for 72 h. At the endpoint, the medium was replaced with 200 μl fresh medium containing 30 μl AlamarBlue solution, then incubated an additional 4 h and measured for fluorescent intensity (Ex/Em: 560 nm/590 nm). In the caspase activity assay, stable cells were infected by pCT-Apoptosis-Luc virus and seeded in 6-well plates (2 × 105 / well). Then, cells were incubated in the same conditions as previously described, but the caspase activity was measured by the One-Glo™ luciferase assay after cisplatin treatment at the IC50 for 24 h.
Vector construction, gene expression and microarray assay
All primer sequences are listed in Additional file 1: Table S1. The AKR1C1 and AKR1C2 cDNA was purchased from DNASU and wild type and constitutive activation STAT1 and STAT3 were purchased from Addgene then recombined into pLenti6.3-DEST through gateway LR II recombinase. The enzymatic domain dead E127D clone was generated from AKR1C1 cDNA by site-direct mutagenesis. The AKR1C1 knockdown clones were purchased from RNAiCore (Taiwan). The AKR1C1 gene manipulation was performed as previously described . AKR1C1 promoter region (− 1276 to + 0) was amplified from Cal-27 genomic DNA then cloned into HE cloning kit (Bio-tools, Taiwan) then confirmed sequence by Sanger sequencing. Then AKR1C1 promoter was subclone into SBI pGreenfire reporter vector. The AKR1C1 downstream genes and regulators in HNSCC were discovered by Affymetrix U133 microarray assays. The microarray analysis approach was analyzed as previously described . Genes that were up- or downregulated with greater than 1.5-fold changes in response to AKR1C1 overexpression/knockdown were further subjected to computational simulation by Ingenuity Pathway Analysis (IPA; QIAGEN, Valencia, CA, USA) online tools to predict potential upstream regulators and the significant cellular pathways and functions. The microarray data were uploaded to the National Center for Biotechnology Information Gene Expression Omnibus (GEO, NCBI, GSE119444). The specific genes were validated by real-time CPR with EvaGreen-based qPCR assays.
Western blot and real-time quantitative PCR (qPCR)
Cancer stem cell sphere formation assay
Stable cells (1 × 103) were seeded in Corning Ultralow attachment 6-well plates with 2 mL sphere medium (50 mL DMEM with 20 ng/mL EGF, bFGF and 1 mL B27 supplement) and then incubated for 14 days to form cancer spheroids. Spheroids were stained with Hoechst 33342, and the spheroid numbers were measured by an ImageXpress Micro XLS HCS system. The spheroid number was counted only when cell number was above 50 cells.
All animal experiments were performed in strict accordance with the recommendations in the guidelines for the Care and Use of Laboratory Animals of Academia Sinica. The protocol was approved by the Institutional Animal Care and Use Committee of the Genomic Research Center, Academia Sinica (Protocol No: AS-IACUC-18-03-1195). Male Nod-SCID gamma (NSG) mice aged 5–6 weeks were bred in the Genomic Research Center. The animals were housed in a climate-controlled room (12:12 dark-light cycle, with constant humidity and temperature) with food and water provided ad libitum. All efforts were made to minimize suffering. For the in vivo tumor burden assay, 5 × 106 stable cells were resuspended in sterile phosphate-buffered saline (PBS), then injected subcutaneously (SC) into the right flank of the mice. Each group consisted of 5 animals. The tumor burden was measured with the following formula: tumor volume (V) = L × W × H. The mice were sacrificed, and the tumors were weighed and photographed. In in vivo cisplatin response assays, 2 mg/kg cisplatin were dissolved in PBS then injected through intraperitoneal injection.
The association between cisplatin response and HNSCC gene expression level was analyzed by Pearson correlation coefficient. The HNSCC IC50 values were determined by the curve-fitting model with four-parameter logistic equation model in GraphPad Prism Software. An unpaired t-test was performed to compare the mRNA expression levels in different treatment groups. Estimates of the survival rates were calculated using the Kaplan-Meier method and compared using the log-rank test. Patient follow-up time was censored if the patient was lost during follow-up. For all experiments, bar graphs represent the mean (±SEM) from three independent experiments, and statistical analyses were performed using SPSS (Statistical Package for the Social Sciences) 21.0 software. Unless otherwise stated, significant differences between means were determined using a Student’s t-test. A p value of < 0.05 was considered significant for all of our analyses.
AKR1C1 expression is correlated with cisplatin-resistance and clinical outcome
Silencing of AKR1C1 can increase cisplatin response in HNSCC through enzyme independent function
Ectopic AKR1C1 can promote cisplatin-resistance, anti-apoptosis response and cancer stemness in HNSCC
AKR1C1 induces STAT activation and influences downstream survival and inflammatory signaling in HNSCC
Cigarette metabolites promote AKR1C1 expression and STAT1 and 3 activation in HNSCC
JAK inhibitor, ruxolitinib, prevents AKR1C1 induced JAK-STAT signaling and cisplatin-resistance
In this study, we determined that AKR1C1 may account for cisplatin-resistance via activating STAT signaling pathways, ultimately resulting in poor clinical outcome. Cisplatin has been the standard chemotherapy for most upper aerodigestive tract carcinomas, including HNSCC, lung cancer, and esophageal cancer, for decades. Mechanisms of cisplatin-resistance have also been discussed, and currently there are several major factors that are considered to contribute to it: membrane transporters for cisplatin uptake or efflux, such as CRT1 and ABC transporter MRP2; DNA repair proteins, such as ERCC1 and TP53; apoptosis associated proteins including BCL-2, caspases, or MAPKs . Since primary cisplatin-resistance has been regarded as a very poor prognostic factor and many clinical trials have excluded patients who recurred within 6 months after primary or adjuvant cisplatin-based chemoradiotherapy in HNSCC, understanding additional details in cisplatin-resistance mechanisms can enable clinical oncologists and medical researchers to design novel therapeutic strategies for these cancer patients.
AKR1C1 expression is a poor prognostic marker in a wide variety of cancers, including breast, prostate, non-small cell lung, and esophagus , and it is upregulated in recurrent tumors and cancer stem cells [23, 33]. In acquired cisplatin-resistance and metastatic ovarian and gastric cancer cells, AKR1C1 is upregulated by IL-6 stimulation and nuclear factor erythroid 2-related factor 2 (Nrf2) and promotes chemoresistance. [34, 35, 36, 37, 38]. Because AKR1C1 works as cellular ROS scavenger and up-regulation in cancer-stem cells which hint that AKR1C1 might be a broad-range chemoresistance gene in cancer. However, the molecular mechanism remains unclear of AKR1C1 in HNSCC cisplatin-resistant. In this study, we found AKR1C1 contributing to cisplatin-resistance and cancer stemness phenotype in HNSCC. Furthermore, we found that cigarette metabolites could induce AKR1C1 expression and further activate STAT signaling. Previously, we identified an AKR1C1 enzymatic-independent mechanism that induced STAT1 and STAT3 activation in treatment-naïve NSCLC cells  and demonstrated that this activation could be attenuated by ruxolitinib. STATs are key regulators which stimulate IL-6 expression. AKR1C1, STATs, and cytokine IL-6 potentially form a positive feedback loop in cancer to enhance cisplatin-resistance.
Smoking is one of the most important environmental carcinogens that induces “field cancerization” in upper aerodigestive tract carcinoma . There are more than 20 carcinogens involved in tobacco , and the smaller particles, such as air pollutants from second-hand smoke, may predominantly deposit in lung parenchyma and promote local inflammation. TSNAs, specifically NNK, promote NSCLC proliferation and prevent chemotherapy-induced apoptosis (32, 33); however, studies to provide similar information for HNSCC are relatively few. In this study, we determined that the similar chemical structure of NNK and NNN lead to more potent STAT-stimulating activity than NAB and NAT. These phenomena may arise from the inhibitory function of NNK in E3-ligase protein and βTrCP  and prevent degradation of EMI1 and CTNNB1  . The situation found in the oral cavity and upper aerodigestive tract may also occur in the lung. From this study we observed that AKR1C1 was overexpressed after exposure to TSNAs, resulting in STAT activation and cisplatin-resistance (Fig. 7f). The reason why TSNAs would induce AKR1C1 expression may be due to the compensatory metabolic effects of the cells. Based on this evidence, upper aerodigestive tract carcinoma patients who are receiving cisplatin treatment should cease smoking immediately to prevent acquired cisplatin-resistance.
Ruxolitinib is a JAK1/2 inhibitor that targets STAT-associated signaling. It has been approved by the FDA for hematologic premalignancy including myelofibrosis and polycythemia vera. Clinical studies of ruxolitinib primarily focus on hematologic malignancies and some aggressive solid cancers that may harbor stem-like features, such as glioblastoma multiforme or triple negative breast cancer. In HNSCC, STAT3 activation has been observed in tumors and may be regulated by upstream EGFR overexpression, IL-6 inflammatory cytokines, or additional pathways. Targeting STAT3 to overcome drug resistance in HNSCC has been discussed, but trials are seldom conducted using ruxolitinib . In this study, we showed that ruxolitinib could overcome intrinsic cisplatin-resistance in HNSCC. Further studies focusing on targeting this novel AKR1C1/STAT network are warranted.
This is the first conceptual link between cigarette metabolites which induce AKR1C1 overexpression and cisplatin resistance in HNSCC and cause poor prognosis. The AKR1C1/STAT crosstalk is associated with primary cisplatin-resistance and may be overcome by the JAK inhibitor ruxolitinib. Whether AKR1C1 could be an effective prognostic or predictive factor for HNSCC patients treated with cisplatin-based chemotherapy warrants further validation. New combination therapy with cisplatin and drugs targeting AKR1C1/STAT signaling also may be beneficial to primary cisplatin-resistant HNSCC patients.
The authors would like to acknowledge the great help and assistance of Experimental Animal Imaging and Molecular Pathology Core Facilities of Genomic Research Center, Academia Sinica (Taipei, Taiwan).
Conception and design: MH, PMC, WMC. Development of methodology: WMC, YCC, YCY. Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): WMC, Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): MH, PMC, SKL, WMC, YCC, YC Y. Writing, review, and/or revision of the manuscript: MH, PM C, WMC, YCC, YCY Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): MH. Study supervision: MH. All authors read and approved the final manuscript.
The study was financially supported by the Academia Sinica [AS-SUMMIT-108]] to Michael Hsiao and MOST 107–2627-M-075 -001 to Peter Mu-Hsin Chang.
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The authors declare that they have no competing interests.
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